Territorial Impact Assessment [1st ed.] 9783030545017, 9783030545024

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Advances in Spatial Science

Eduardo Medeiros  Editor

Territorial Impact Assessment

Advances in Spatial Science The Regional Science Series Series Editors Manfred M. Fischer, Vienna University of Economics and Business, Wien, Austria Jean-Claude Thill, University of North Carolina, Charlotte, NC, USA Jouke van Dijk, University of Groningen, Groningen, The Netherlands Hans Westlund, Jönköping University, Jönköping, Sweden Advisory Editors Geoffrey J. D. Hewings, University of Illinois, Urbana, IL, USA Peter Nijkamp, Free University, Amsterdam, The Netherlands Folke Snickars, Editorial Board, Heidelberg, Baden-Württemberg, Germany

This series contains scientific studies focusing on spatial phenomena, utilising theoretical frameworks, analytical methods, and empirical procedures specifically designed for spatial analysis. Advances in Spatial Science brings together innovative spatial research utilising concepts, perspectives, and methods relevant to both basic science and policy making. The aim is to present advances in spatial science to an informed readership in universities, research organisations, and policy-making institutions throughout the world. The type of material considered for publication in the series includes: Monographs of theoretical and applied research in spatial science; state-of-the-art volumes in areas of basic research; reports of innovative theories and methods in spatial science; tightly edited reports from specially organised research seminars. The series and the volumes published in it are indexed by Scopus. More information about this series at http://www.springer.com/series/3302

Eduardo Medeiros Editor

Territorial Impact Assessment

Editor Eduardo Medeiros DINÂMIA’CET Instituto Universitário de Lisboa – Iscte Lisbon, Portugal

ISSN 1430-9602     ISSN 2197-9375 (electronic) Advances in Spatial Science ISBN 978-3-030-54501-7    ISBN 978-3-030-54502-4 (eBook) https://doi.org/10.1007/978-3-030-54502-4 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Foreword

The European Committee of the Regions (CoR) is the voice of regions and cities in the European Union (EU). It represents local and regional authorities and advises on new laws that have an impact on regions and cities. This represents 70% of all EU legislation. For this reason, the Commission for Territorial Cohesion Policy and EU Budget (COTER) has created a Territorial Impact Assessments (TIAs) methodology with the goal to provide CoR with an analysis of the potential territorial impacts of EU legislative proposals. Developing Territorial Impact Assessments is a way to foster territorial cohesion and to make sure that it is taken into account by the European, national, regional and local authorities when implementing policies in their areas of responsibility. In order to ensure that the EU regulatory framework is tailored to meet the needs of those affected by its implementation, it must always be based on a comprehensive assessment of its impact, which also takes into account the territorial component. Recognising and considering the territorial context and the specificities of a given territory (e.g. functional, urban, macro-regional, cross-border areas) is a prerequisite for success when designing the policy interventions. Over the past decade, the CoR has striven to promote the use of TIAs for evaluating EU legislation. Following from this experience, the COR acknowledges the importance of the use of TIAs as a fundamental policy evaluation tool, which has now entered into a phase of maturity. At the same time, it recognises the limitations of current methodologies. As such, we highly welcome and recommend this TIA Handbook to everyone interested in selecting the most appropriate TIA methodology to assess the main ex-ante or/and ex-post impacts of projects, programmes or policies with a territorial dimension. The COR remains convinced that to improve the quality of EU policymaking we must ensure that the territorial impacts of new policy proposals and existing EU legislation are taken into account by the EU institutions. It therefore calls for dedicated attention to the Commission’s inception impact assessments and for the development of existing instruments and the investigation of new instruments and approaches. This, together with the improvement of the quality and quantity of statistical indicators at sub-national level, would help to develop a territorially sensitive diagnosis for tailored policy responses.

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Foreword

This TIA Handbook presents a collection of specific TIA tools designed to assess the main impacts of EU policies and programmes. These include cross-border cooperation programmes which are particularly important if we consider that around 60% of the EU territory and 40% of its population live in cross-border areas. This Handbook can thus contribute towards a more effective, evidence-based policymaking. Former President of the Committe of the Regions Brussels, Belgium

Karl-Heinz Lambertz

Contents

1 Introduction: A Handbook on Territorial Impact Assessment (TIA)������������������������������������������������������������������������    1 Eduardo Medeiros Part I Territorial Impact Assessment (TIA): Mainstream Methodologies 2 TARGET_TIA: A Complete, Flexible and Sound Territorial Impact Assessment Tool��������������������������������������������������������������������������    9 Eduardo Medeiros 3 The Pioneering Quantitative Model for TIA: TEQUILA��������������������   27 Roberto Camagni 4 STeMA: A Sustainable Territorial Economic/Environmental Management Approach ��������������������������������������������������������������������������   55 Maria Prezioso 5 The ESPON EATIA: A Qualitative Approach to Territorial Impact Assessment������������������������������������������������������������   77 Naja Marot, Mojca Golobič, and Thomas B. Fischer Part II Territorial Impact Assessment for Cross-Border Cooperation Programmes 6 The Bottom-Up Approach: Experiences with the Impact Assessment of EU and National Legislation in the German, Dutch and Belgian Cross-Border Regions ��������������������������������������������  103 Martin Unfried, Lavinia Kortese, and Anouk Bollen-Vandenboorn 7 Cross-Border Territorial Impact Assessment����������������������������������������  123 Gyula Ocskay 8 Enhancing Cross-Border Cooperation Through TIA Implementation��������������������������������������������������������������������������������  143 Ricardo C. B. Ferreira and Nathalie Verschelde

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Contents

Part III Territorial Impact Assessment: Alternative Models and Complementary Approaches 9 From Territorial Impact Assessment to Territorial Foresight ������������  157 Kai Böhme, Christian Lüer, and Frank Holstein 10 The LUISA Territorial Modelling Platform and Urban Data Platform: An EU-Wide Holistic Approach����������������  177 Carlo Lavalle, Filipe Batista E. Silva, Claudia Baranzelli, Chris Jacobs-Crisioni, Mert Kompil, Carolina Perpiña Castillo, Pilar Vizcaino, Ricardo Ribeiro Barranco, Ine Vandecasteele, Boyan Kavalov, Jean-Philippe Aurambout, Andrius Kucas, Alice Siragusa, and Davide Auteri 11 Territorial Effects of EU Cohesion Policy Supporting Entrepreneurship: Findings from the Czech Republic������������������������  195 Ondřej Dvouletý, Ivana Blažková, and Oto Potluka 12 Guidelines for Territorial Impact Assessment Applied to Regional Research and Innovation Strategies for Smart Specialisation��������������������������������������������������������������������������  211 Paulo Neto and Anabela Santos Conclusion��������������������������������������������������������������������������������������������������������   231 Index������������������������������������������������������������������������������������������������������������������  235

Editor and Contributors

Editor Eduardo Medeiros  is Professor of Geography and an Integrated Research Fellow in DINÂMIA'CET-IUL, Instituto Universitário de Lisboa, Portugal. He has a PhD in Geography – Regional and Urban Planning, and has more than 150 publications, including more than 30 published papers in international journals, 10 books and 13 book chapters. His research interests are focused on Territorial Impact Assessment, Territorial Cohesion, Territorial Development, Territorial Cooperation and Spatial Planning. Professor Medeiros is a DG REGIO (European Commission) and UEBACT III expert and a Horizon 2020 evaluator. He is also a Regional Studies Association Fellow and belongs to its Cohesion Policy Research Network. Professor Medeiros has coordinated several international policy evaluation projects and was a member of DG REGIO and ESPON projects. He was invited as a Project Adviser and to write reports and position papers by DG REGIO. Professor Medeiros has been an invited keynote speaker at several international universities and EU institutions (European Commission and Committee of the Regions). He is part of the scientific and editorial committees of several journals and a peer reviewer of more than 35 international journals.

Contributors Jean-Philippe Aurambout  European Commission, Joint Research Centre (JRC), Ispra, Italy Davide Auteri  European Commission, Joint Research Centre (JRC), Ispra, Italy Claudia  Baranzelli  European Commission, Joint Research Centre (JRC), Ispra, Italy Ricardo Ribeiro Barranco  European Commission, Joint Research Centre (JRC), Ispra, Italy Ivana  Blažková  Department of Regional and Business Economics, Mendel University in Brno, Brno, Czech Republic ix

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Kai Böhme  Spatial Foresight, Heisdorf, Luxembourg Anouk Bollen-Vandenboorn  Institute for Transnational and Euregional Cross-border Cooperation and Mobility (ITEM), Maastricht University, Maastricht, Netherlands Roberto  Camagni  Department ABC - Architecture, Built Environment and Construction Engineering,  Politecnico di Milano, Milan, Italy Carolina Perpiña Castillo  European Commission, Joint Research Centre (JRC), Ispra, Italy Ondřej  Dvouletý  Department of Entrepreneurship, University of Economics, Prague, Prague, Czech Republic Ricardo C. B. Ferreira  DG REGIO – DG for Regional and Urban Policy, European Commission, European Union, Brussels, Belgium Thomas B. Fischer  Environmental Assessment and Management Research Centre, School of Environmental Sciences, University of Liverpool, Liverpool, UK Research Unit for Environmental Sciences and Management, North West University, Potchefstroom, South Africa Mojca  Golobič  Biotechnical Faculty, Department of Landscape Architecture, University of Ljubljana, Ljubljana, Slovenia Frank Holstein  Spatial Foresight, Heisdorf, Luxembourg Chris  Jacobs-Crisioni  European Commission, Joint Research Centre (JRC), Ispra, Italy Boyan Kavalov  European Commission, Joint Research Centre (JRC), Ispra, Italy Mert Kompil  European Commission, Joint Research Centre (JRC), Ispra, Italy Lavinia  Kortese  Institute for Transnational and Euregional Cross-border Cooperation and Mobility (ITEM), Maastricht University, Maastricht, Netherlands Andrius Kucas  European Commission, Joint Research Centre (JRC), Ispra, Italy Carlo Lavalle  European Commission, Joint Research Centre (JRC), Ispra, Italy Christian Lüer  Spatial Foresight, Heisdorf, Luxembourg Naja  Marot  Biotechnical Faculty, Department of Landscape Architecture, University of Ljubljana, Ljubljana, Slovenia Eduardo  Medeiros  DINÂMIA’CET, Instituto Universitário de Lisboa – Iscte, Lisbon, Portugal Paulo Neto  Department of Economics, UMPP, CICS.NOVA. UÉvora, CIES-IUL and CEFAGE.UÉ, University of Évora, Évora, Portugal Gyula  Ocskay  Central European Service for Cross-Border Initiatives (CESCI), Budapest, Hungary

Editor and Contributors

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Oto  Potluka  Department of Management, University of Economics, Prague, Prague, Czech Republic Maria Prezioso  Department of Management and Law, University of Rome “Tor Vergata”, Rome, Italy Anabela  Santos  Solvay Brussels School of Economics and Management, iCite, Université Libre de Bruxelles, Brussels, Belgium UMPP, University of Évora, Évora, Portugal Filipe  Batista  E.  Silva  European Commission, Joint Research Centre (JRC), Ispra, Italy Alice Siragusa  European Commission, Joint Research Centre (JRC), Ispra, Italy Martin  Unfried  Institute for Transnational and Euregional Cross-border Cooperation and Mobility (ITEM), Maastricht University, Maastricht, Netherlands Ine  Vandecasteele  European Commission, Joint Research Centre (JRC), Ispra, Italy Nathalie Verschelde  DG REGIO – DG for Regional and Urban Policy, European Commission, European Union, Brussels, Belgium Pilar Vizcaino  European Commission, Joint Research Centre (JRC), Ispra, Italy

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Introduction: A Handbook on Territorial Impact Assessment (TIA) Eduardo Medeiros

Abstract

Territorial Impact Assessment (TIA) is a relatively ‘new kid on the block’ of policy evaluation. Resting upon the holistic notion of territory, which encompasses multiple analytic dimensions (economy, society, environment, governance, spatial planning), TIA is the most complex, yet with the policy evaluation procedure with the largest potential to assess projects, programmes and policies. Indeed, policy evaluation procedures are now deeply rooted in sub-national, national and transnational territorial development strategies and processes. However, unlike the plethora of published books on Environmental Impact Assessment (EIA) and other Impact Assessment (IA) methodologies, presently no TIA handbook has been published by any major international publisher. As such, this one intends to add a substantial contribution to available literature by presenting to the interested reader the most relevant TIA methodologies that have been produced so far. Furthermore, all the chapters, written by the authors of each TIA methodology presented, provide a detailed, updated and scientifically accurate explanation of their particular purpose and methodological operation. In the end, the reader is presented with a complete set of TIA methodologies to select from based on their advantages/disadvantages for a particular casestudy. For a better understanding of how all the presented TIA methodologies work, concrete examples are presented in each chapter. Keywords

Territorial Impact Assessment – TIA · Impact Assessment – IA · Environmental Impact Assessment – EIA · Policy evaluation · Territorial dimension

E. Medeiros (*) DINÂMIA’CET, Instituto Universitário de Lisboa – Iscte, Lisbon, Portugal e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_1

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Why this Book?

Territorial Impact Assessment (TIA) is a relatively ‘new kid on the block’ of policy evaluation. Resting upon the holistic notion of territory, which encompasses multiple analytic dimensions (economy, society, environment, governance, spatial planning), TIA is the most complex, yet with the policy evaluation procedure with the largest potential to assess projects, programmes and policies. Indeed, policy evaluation procedures are now deeply rooted in sub-national, national and transnational territorial development strategies and processes. However, unlike the plethora of published books on Environmental Impact Assessment (EIA) and other Impact Assessment (IA) methodologies, presently no TIA handbook has been published by any major international publisher. As such, this one intends to add a substantial contribution to available literature by presenting to the interested reader the most relevant TIA methodologies that have been produced so far. Furthermore, all the chapters, written by the authors of each TIA methodology presented, provide a detailed, updated and scientifically accurate explanation of their particular purpose and methodological operation. In the end, the reader is presented with a complete set of TIA methodologies to select from based on their advantages/disadvantages for a particular case-study. For a better understanding of how all the presented TIA methodologies work, concrete examples are presented in each chapter. Rather than proposing a consensus to unifying singular TIA approaches, this TIA Handbook presents to the interested reader the main characteristics, as well as the strengths and weaknesses of several TIA methodologies. Having been around for a bit more than a decade, TIA methodologies are now coming of age. Their infancy phase has passed with the typical growing pains. Several matured and perfected TIAs are, by now, out on the market to be used when there is a need to assess the main territorial impacts of basically every project, programme and policy with a territorial dimension. Being largely a European construct, there is no reason for TIA methodologies not to be used on other territories. Crucially, this handbook intends to serve as a fundamental vehicle to expand the use of TIA methodologies on other continents. At the same time, we expect to see an increasing use of TIA tools by national and sub-national entities, and in a wide variety of projects, programmes and policies across the world. Echoing the recent interest in the use of more broad and holistic policy evaluation methods to assess the main impacts of public funding, at all territorial levels, this TIA Handbook complements the presentation of mainstream TIA methodologies with others focused on more specific policy sectors and programmes (cross-­ border cooperation, smart specialisation, etc.). In this light, this TIA handbook is aimed at a wide audience, from academics to practitioners, interested in assessing the full scope of the impacts of implemented projects, programmes and policies, at all territorial levels. Thus, it also intends to serve as a TIA ‘bible’ for the next decade, and to instill increasing interest in the use of TIA methodologies on all continents and territorial levels.

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 he Genesis of TIA Methodologies and an Introduction T to the Chapters

The EIA, emerged in the 1960s in the United States (see Petts 1999), and the Strategic Environmental Assessment (SEA), forged by the EU, are focused on assessing the field of environmental sustainability, and both tend to target programmes and projects, rather than policies (ESPON 3.2 2006). Instead, the TIA has its roots in the EU concerns about the limited policy evaluation scope of these (EIA and SEA) two mandatory European Union (EU) IA procedures. In this regard, there is no doubt about the crucial influence of the European Spatial Development Perspective (ESDP – EC 1999) in opening the avenues for EU Member States to develop, implement and intensify TIA processes, experiences, regulations and instruments (Medeiros 2016a). On a practical level, however, the genesis of the TIA methodologies resulted from the European Territorial Observatory Network (ESPON) Programme’s intense search for univocal causality relations between territorial development processes and public policy investments, and not only the environmental dimension of development which can be assessed by EIA and SEA tools. Initiated in 2002, the ESPON programme financed the elaboration of the first TIA tool (the TEQUILA TIA tool, developed by Roberto Camagni; see Chap. 3) which was presented in 2006 (ESPON 3.2 2006) and specifically built to assess the ex ante impact of policies, programmes and integrated projects supported and financed by the EU.  Since then, European entities, such as the European Commission (EC) and the Committee of the Regions (CoR) have tested and applied ESPON TIA methodologies to assess the ex ante impacts of EU directives and other EU-financed programmes (CoR 2014). As expected, this ‘new kid on the block’ of IA methodologies has experienced several methodological developments since its genesis. This can be witnessed by the creation of new TIA methodologies and the perfection of existing ones, most of these resulting from ESPON-financed projects. Besides the already mentioned and pioneering TEQUILA TIA methodology, several others were, later, introduced to stakeholders. These include the STeMA (developed by Maria Prezioso; see Chap. 4), the EATIA (Developed by Naja Marot, Mojca Golobič, Thomas B. Fischer and others; see Chap. 5), the ARTS (requested to address the issue of impact of EU directives) and the related Quick_Check TIA. In this context, the first part of this book presents the three of the ESPON TIA methodologies. Firstly, the aforementioned TEQUILA TIA tool, which introduced crucial elements for properly assessing the main impacts of policies, such as an ‘evaluation policy impact score’ (from negative to positive impacts), as well as the ‘policy intensity’ and the ‘regional sensibility’ evaluation parameters. Secondly, the STeMA TIA tool facilitates the use of a vast array of policy indicators to assess territorial impacts of policies. Thirdly, built as an alternative option to existing ESPON TIA tools, the EATIA introduced an interesting bottom-up approach to TIA procedures, as well as the notion of cumulative territorial impacts. Being built with the erroneous rationale that it is possible to assess territorial impacts in a so-called ‘quick and dirty’ way, the ESPON Quick_Check TIA is not

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presented in this book. As is widely recognised within the ESPON programme, the Quick_Check TIA is a simplified first step to obtain ex ante impact scores of EU directives. Hence, it does not seem appropriate to present it in a TIA handbook as a viable, sound and relevant TIA tool. Moreover, our overview of studies which have used it to assess territorial impacts show that it is plagued by the largely non-­ transparent way it aggregates information and reaches the presented potential impact scores. In parallel, other TIA tools were produced outside the ESPON auspices, with a view to assess, not only ex ante, but also the ex post impacts of projects, programmes and policies, in a more robust way. From these, the first part of the book presents one example: TARGET_TIA (developed by the editor; see Chap. 2). In synthesis, TARGET_TIA is an alternative mainstream, sound, flexible and relevant TIA tool to existing ESPON TIAs. It has been successfully tested in assessing the main territorial impacts of EU-financed programmes (e.g. INTERREG-A cross-border cooperation) and policies (e.g. EU Cohesion Policy) in different countries (Portugal, Spain, Sweden and Norway) and territorial scales (regional, national and European). In a context of emerging policy evaluation methodologies specifically designed to assess the main impacts of EU cross-border cooperation (CBC) programmes, the second part of the book presents three TIA techniques specifically designed to assess their implementation. Existing literature shows how the territorial impacts of CBC programmes can also be appropriately assessed with TARGET_TIA (see Medeiros 2015, 2017a, b, 2018a). Though in very different modes, the three chapters of this second part of the book can be regarded as alternative policy evaluation methods to assessing the main potential impacts of specific policy aspects of CBC programmes. Firstly, in Chap. 6 (written by Anouk Bollen-Vandenboorn, Lavinia Kortese & Martin Unfried) a methodology developed by Maastricht University (ITEM) shows how to specifically assess the impacts of legislation in border regions. This is particularly important, as the ultimate goal of CBC programmes is the reduction of border barriers, of which the legal-administrative ones are still the most important (Medeiros 2018b). Thus, CBC processes are intended to increase territorial integration and development processes across border areas. In this light, Chap. 7 (written by Gyula Ocskay) presents a holistic and sound alternative policy evaluation tool developed by CESCI, to existing CBC TIA tools, which has been used to assess the main territorial impacts of Hungarian CBC programmes. On the flipside, Chap. 8 (written by Ricardo Ferreira & Nathalie Verschelde) present the European Commission perspective on the relevance of ex ante and ex post TIA methodologies, whilst focusing on the importance of performing territorial impact evaluations of cross-border cooperation programmes. Finally, the third part of this book presents more generic models and complementary approaches to assess territorial impacts of policies to the mainstream TIA methodologies presented in the first part of the book. To start with, in Chap. 9 (written by Kai Böhme, Christian Lüer & Frank Holstein), Spatial Foresight develops an interesting methodology to assess territorial foresights with a strong link to TIA

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procedures. Likewise, the LUISA Territorial Modelling Platform, analysed in Chap. 10 (written by Carlo Lavalle and his team), and developed by the EC Joint Research Centre, applies the widespread use of online cartography of a vast territorial database at all territorial levels. Instead of producing TIA scores, like mainstream TIA, it uses mathematical calculations to forecast territorial trends over time, making it particularly useful when used in conjunction with other TIA tools to assess potential ex ante territorial impacts. Chap. 11 (written by Ondřej Dvouletý, Ivana Blažková, & Oto Potluka), brings to the fore a concrete example of how to appropriately use counter-factual evaluation to assess the territorial effects of EU Cohesion Policy, taking the case of Czech Republic. Finally, the last chapter (Chap. 12 written by Paulo Neto & Anabela Santos) demonstrates how to apply TIA methodologies to assess the main impacts of Regional Smart Specialisation Strategies, which are especially relevant for the EU territorial development context.

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The Need for TIA Methodologies

What is the ultimate goal of public investment? Generically, it ultimately aims at promoting, directly or indirectly, positive territorial development tends (Medeiros 2019; Potter et al. 2008) and, ideally, territorial cohesion processes (Faludi 2006; Medeiros 2016b; Medeiros and Rauhut 2018). Put differently, large-scale infrastructural projects, as well as growth/development/cohesion programmes and policies hold the potential to create either negative or positive potential impacts in several policy sectors and territories. The salient point is that such projects, programmes and policies have a clear multidimensional and territorial dimension (Medeiros 2017a). Taking the example of EU Cohesion Policy, its main impacts do not only encompass the environmental dimension of development, but also entail potential impacts in socioeconomic, governance, and spatial-planning-related components. The same goes for the impacts of the construction of an international airport, or the implementation of an EU-funded programme, such as the INTERREG-A (cross-border cooperation) (Medeiros 2017b). In short, the basic argument for using TIA methodologies, instead of EIA and SEA tools, is that a TIA tool can provide a complete picture of the potential impacts of the analysed project, programme or policy, whereas EIA and SEA are only designed to capture the main environmental impacts. This is a useful starting point to campaign for the replacement of the legal requirements to use EIA and SEA methodologies, with the more complete and holistic TIA ones. In this new potential scenario, however, the credibility of TIAs should be safeguarded. On the whole, in our opinion, the use of quick, dirty and shallow TIA methodologies, such as the ESPON Quick_Check TIA, need to give way to relevant, sound and credible TIA tools. Only then can TIAs show rapid progress in their overall acceptance as the optimal policy IA tool, for all involved in policy evaluation processes.

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References CoR (2014) Smooth phasing out of the milk quotas in the European Union. Report of the workshop Committee of the Regions 27th November 2014, Brussels ESPON 3.2 (2006) Spatial scenarios and orientations in relation to the ESDP and cohesion policy, Volume 5 – Territorial Impact Assessment, Final Report, October 2006, ESPON, Luxembourg Faludi A (2006) From European spatial development to territorial cohesion policy. Reg Stud 40(6):667–678 Medeiros E (2015) Territorial impact assessment and cross-border cooperation. Reg Stud Reg Sci 2(1):95–115 Medeiros E (2016a) Territorial impact assessment and public policies: the case of Portugal and the EU. Public Policy Portuguese J 1(1):51–61 Medeiros E (2016b) Territorial cohesion: an EU concept. Eur J Spatial Dev 60. http://www.nordregio.org/publications/territorial-cohesion-an-eu-concept Medeiros E (2017a) The territorial dimension of European policies: a conceptual approach. In: Medeiros E (ed) Uncovering the territorial dimension of European Union cohesion policy. Routledge, London, pp 9–22 Medeiros E (2017b) Cross-border cooperation in inner Scandinavia: a territorial impact assessment. Environ Impact Assess Rev 62(2017):147–157 Medeiros E (2018a) Focusing on cross-border territorial impacts. In: Medeiros E (ed) European territorial cooperation, The urban book series. Springer, Cham Medeiros E (2018b) Should EU cross-border cooperation programmes focus mainly on reducing border obstacles. Documents d’Anàlisi Geogràfica 64(3):467–491 Medeiros E (2019) Spatial planning, territorial development and territorial impact assessment. J Plan Lit 34(2):171–182 Medeiros E, Rauhut D (2018) Territorial cohesion cities: a policy recipe for achieving territorial cohesion? Reg Stud. https://doi.org/10.1080/00343404.2018.1548764 Petts J (1999) Handbook of environmental impact assessment, Environmental impact assessment in practice; impact and limitations, vol 2. Blackwell Science, Oxford Potter R, Binns T, Elliott J, Smith D (2008) Geographies of development. an introduction to development studies, 3rd edn. Pearson Education Limited, Essex

Part I Territorial Impact Assessment (TIA): Mainstream Methodologies

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TARGET_TIA: A Complete, Flexible and Sound Territorial Impact Assessment Tool Eduardo Medeiros

Abstract

This chapter presents TARGET_TIA as a relevant and flexible Territorial Impact Assessment (TIA) methodology. TARGET_TIA was created in a context where existing ESPON TIA tools were mainly designed for assessing ex ante territorial impacts of EU directives. Hence, in view of the need to properly assess the main ex post territorial impacts of EU Cohesion Policy in several countries in a relevant and sound way, the author decided to design, test and apply his own TIA methodology, named TARGET_TIA. When compared with other existing TIA methodologies, TARGET_TIA can be used both at ex ante and ex post policy evaluation phases. In addition, it brings to the table the possibility to use counterfactual evaluation elements to allow the production of credible and sound TIA evaluation scores. Following on from its implementation in assessing the main territorial impacts of EU policies and programmes, mostly at the ex post evaluation phase, it is possible to conclude that it is a credible, flexible, easy-to-operate, cost-effective and robust TIA methodology, which can be applied to projects, programmes and policies, at all territorial levels. Keywords

Territorial Impact Assessment · TARGET_TIA · EU Cohesion Policy · Iberian Peninsula · Territorial Cohesion · Territorial Development

E. Medeiros (*) DINÂMIA’CET, Instituto Universitário de Lisboa – Iscte, Lisbon, Portugal e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_2

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Historical Background, Main Goals and Application

The genesis of TARGET_TIA is easily explained. In early 2011 the author embarked on a 6-year study to assess the main territorial impacts of EU Cohesion Policy in four countries (Portugal, Spain, Sweden and Norway). By then, all existing ESPON TIA tools were tested, such as TEQUILA (see Chap. 3) and STeMA (see Chap. 4). These were the first versions of already improved ESPON TIA methodologies. As such, they suffered from several shortcomings, which were immediately detected when testing them for the Portuguese EU Cohesion Policy case-study. In particular, it was found that the TEQUILA ESPON TIA tool was well designed, with a comprehensive rationale and formula, and with appropriate evaluation elements such as ‘regional sensibility’ and ‘policy intensity’ (see ESPON 3.2 2006). However, since it was mainly designed to assess ex ante impacts of EU directives in a simple way, the TEQUILA tool proved to be inappropriate for our research goals of assessing ex post impacts of policies in a sound way. In addition, just like in most existing ESPON TIA tools, TEQUILA did not incorporate crucial policy counterfactual evaluation elements, such as substitution, deadweight and displacement effects (see EC 1999: 113). As a result, it was decided that the best option was to elaborate a novel TIA tool that would: 1. Be both simple to operate and scientifically robust to assess territorial impacts of projects, programmes and policies 2. Assess territorial impacts in both ex post and ex ante policy evaluation phases 3. Incorporate counterfactual evaluation elements, in order to validate its scores 4. Use a simplified evaluation score scale, which incorporates both potential negative and positive impacts, based on the TEQUILA rationale 5. Use the useful TEQUILA policy evaluation tuning elements of ‘regional sensibility’ and ‘policy intensity’, but with a distinct and simplified rationale 6. When used in the ex post policy evaluation mode, allow for incorporating both qualitative and quantitative data in the formula 7. Allow for the possibility to use a simple, flexible and cost-effective spreadsheet to include all evaluation scores and automatically produce the impact scores for all selected dimensions, as well as a general impact score. The use of a spreadsheet also permits the automatic cartography of these scores, either via the incorporated Excel mapping tool or via a Geographical Information System (GIS) Software add-on. Moreover, the use of a spreadsheet allows for a simple change/ incorporation of the appropriate analytic dimensions required for any territorial impact analysis and permits the automatic inclusion of aggregated statistical indexes, generated in a different sheet, thus facilitating the whole process of producing relevant and sound TIA scores in a single platform. In a nutshell, and unlike most ESPON TIA tools (see Medeiros 2014a), TARGET_TIA was designed to assess territorial impacts not in a quick, dirty and simple manner, but in a relevant, sound and simple one. This is why it took around 2 years to be designed, tested and perfected, taking the Portuguese EU Cohesion

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Policy’s main ex post territorial impacts as the first case-study, applied at the national scale (Medeiros 2013). This was then adjusted to assess the main ex post impacts of EU Cohesion Policy at the regional scale in the continental Portuguese regions (see the Algarve case in Medeiros 2014b). After being published, the TARGET_TIA tool attracted attention from the Committee of the Regions (CoR), which was dealing with the ESPON Quick Check TIA that, as the name indicates, is only designed to provide a quick and dirty check of potential impacts of EU directives, and not proper, sound and credible impact scores. Amid several conversations, the Committee of the Regions (CoR) was allowed to test TARGET_TIA. By then, it used a territorial cohesion index to input quantitative scores in each analysed dimension. Soon it was realised that a more simplified option should be available for this process, as the use of this index requires specific knowledge in statistical analysis. Hence, TARGET_TIA 2.0 was presented later on with a simplified option to input the quantitative impact scores, now based on the expertise of the person responsible to input those scores on the project/programme/policy being assessed. This might make the scores somewhat more biased, as they depend on personal judgement, but they allow for anyone without technical skills in statistics to perform the TIA evaluation process. It goes without saying that the former option (less impartial with the statistical index) is still valid and possible if the evaluator decides to use it. In the meantime, TARGET_TIA was used to assess the main impacts of the EU Cohesion Policy in Spain (Medeiros 2017b) and in Sweden (Medeiros 2016a). Furthermore, for the first time, it was fully adapted to assess a specific EU programme: the INTERREG-A (cross-border cooperation) (see Medeiros 2015, 2018a). This required the inclusion of a complete new set of analytical dimensions and was a valid opportunity to test TARGET_TIA in a slightly new policy evaluation environment. In conclusion, it proved that the initial formula was perfectly adapted to assess all kinds of projects, programmes and policies, thus paving the way to replace quick and dirty TIA tools with relevant ones (Medeiros 2016b, 2017b). The operationalisation of TARGET_TIA in a specific INTERREG-A sub-­ programme (Inner Scandinavia  – Sweden-Norway cross-border cooperation programme) showed that it was particularly adapted to assess the main impacts of this programme, unlike the ESPON Quick Check TIA tool. At the same time, a concrete analytic framework was proposed to apply TARGET_TIA in assessing the main territorial impacts of spatial planning instruments (see Medeiros 2019). So far, however, this tool has not yet been applied in the ex ante policy evaluation phase, despite the fact that it is also designed to be used in that policy evaluation framework.

2.2

The Methodology in a Nutshell: Elements and Formula

The use of a specific policy evaluation tool presents numerous advantages in terms of guaranteeing an evaluation content and comparability of results. Evidently, these tools must always be adapted to their context of use and to the functions they aim to

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fulfil. In this regard, TARGET_TIA can generically be used in the following evaluation contexts to: 1. Assess territorial impacts of projects, programmes and policies: Unlike environmental, social or economic impact assessment procedures, territorial impacts imply the assessment of all of these dimensions (EC 2009; ESPON 2012) as well as others, such as governance and territorial articulation (Medeiros 2014a). More concretely, TARGET_TIA is ideal to assess the impacts of large-scale infrastructural projects, such as the construction of an airport or a highway, as they will inevitably produce economic, environmental, social and spatial-planning-related impacts. Likewise, TARGET_TIA is the most appropriate evaluation tool to assess programmes and policies which have potential socioeconomic, environmental, governance and spatial-planning-related impacts. These include most growth, development and cohesion programme policies, such as urban, regional and national development policies, and EU Cohesion Policy and related programmes. 2. Assess both ex ante and ex post evaluation phases: Unlike other TIA tools, TARGET_TIA is designed to assess ex ante, mid-term and ex post policy phases. This presents a great advantage since it can present comparable impact scores at all policy evaluation phases. 3. Assess all territories: TARGET_TIA can assess territorial impacts at all geographical scales, but is especially appropriate to assess impacts from urban/local to global scales, like any other TIA.  This allows for the cartography of the obtained potential impact scores, either in spreadsheet software, or via GIS software, for instance. 4. Time: The impacts of projects, programmes and policies are not immediately measured after they are implemented (EC 2008, 2013). Normally, it takes 2–3 years after they are finished to detect their potential territorial impacts. At the same time, these impacts have to be compared with a base-line scenario (before the project, programme and policy was implemented). For instance, to assess the 2000–2006 EU Cohesion Policy phase, qualitative and quantitative data would have had to be collected for around 2000 and 2009 approximately. TARGET_TIA permits the selection of any given time that the evaluator thinks is more appropriate for the evaluation process. Taking a concrete example of the evaluation of the main ex post territorial impacts of EU Cohesion Policy on the Iberian Peninsula (Portugal and Spain) from 1989 until 2013, from an evaluator standpoint, these would be the main steps, stages and features of using TARGET_TIA: 1. Identify the main evaluation dimensions and respective components: Following the rationale in which EU Cohesion Policy aims at ultimately achieving territorial cohesion processes, the first step to implement TARGET_TIA would be to identify the main dimensions and respective components of the concept of territorial cohesion (see Medeiros 2016c) in order to produce appropriate impact scores for each component.

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Fig. 2.1 TARGET_TIA impact scores. (Source: own elaboration)

2. Select an impact score: The impacts of EU Cohesion Policy in each selected component can be either positive, neutral or negative. To guide the evaluator, a predefined evaluation score scale can be provided in the TARGET_TIA spreadsheet software. Following the initial testing phase, it was decided that the most appropriate scale would range from −4 (very significant negative impacts) to +4 (very significant positive impacts), where 0 represents a neutral impact (see Fig. 2.1); 3. The construction of a counterfactual situation: It is expected that the impacts of EU Cohesion Policy account for only its share of the imputable change it produced in the analysed components. In other words, the counterfactual situation is a way to describe what would have happened without the implementation of this policy, vis-à-vis with what actually happened. In this context, it is recommended that a few counterfactual evaluation elements are used when assessing territorial impacts (see Fig. 3.2). For that, TARGET_TIA includes the possibility to add three other counterfactual evaluation vectors to the normal positive-negative evaluation vector, in assessing the overall impacts. These should be evaluated in distinct spreadsheet columns. Firstly, the endogenous–exogenous vector addresses the impacts of each analysed component in the analysed territory, vis-­ à-­vis exterior territories. Secondly, the sustainable–short-term vector assesses in what measure the changes produced are sustainable in time or whether they are just short-term impacts. Thirdly, the multiplier–substitution vector takes into account in what measure the estimated impacts produce multiplier effects in other territorial development dimensions and components or, conversely, if they are just replacing positive impacts that used to exist. In the end, the arithmetic average of the four vectors will determine the appropriate impact score for each analysed component. Alternatively, the evaluator can decide just to stick with the positive-negative evaluation vector for simplification reasons. This can sometimes be the logical choice if it is difficult to collect elements related to the counterfactual evaluation vectors mentioned above. 4. The policy intensity evaluation element: As seen in Fig. 2.2, the TARGET_TIA formula for obtaining the final potential impact score for each analysed

14

Fig. 2.2  TARGET_TIA ex ante and ex post formulas. (Source: Medeiros 2017c)

E. Medeiros

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component is not only based on a quantitative/qualitative data analysis which supports the selection of the impact score for the analysed period of time. Instead, it adds two crucial evaluation elements. The first is the policy intensity. In simple terms, on a scale of 0 (no intensity) to 1 (maximum intensity), the evaluator selects a score for each analysed component that represents how much investment was allocated to that component in the global context of the project, programme and policy implementation. The underlying rationale here is that components which received large volumes of financing are expected to be greatly affected by the evaluated project, programme or policy. The opposite goes for poorly financed components. 5. The regional sensibility evaluation element: the ‘regional sensibility’ element also uses a scale from 0 (no sensibility) to 1 (maximum sensibility) to better tune the final impact score for each analysed component. In synthesis, this evaluation element implies that certain investments have the potential to produce distinct territorial impacts, depending on the regional development situation of a given region. For instance, the installation of a large car factory in an under-developed region, with higher unemployment rates, would most likely bring higher impacts for the regional development process there, than in a region that is already highly developed and with lower unemployment rates. In short, when inputting the score in this evaluation parameter, the evaluator will always ask about the needs of the region in relation to this specific component. If these needs are very high, then a score of 1 is attributed. Conversely, if these needs are very low, then a score of 0 should be given. To simplify the process, three other predefined scores are also available in the spreadsheet: 0.25, 0.5 and 0.75. The evaluator has, of course, the possibility to input other scores they think are more appropriate. 6 . Quantitative synthetic index for ex post evaluation phases: In order to make the final impact score more robust, TARGET_TIA allows the use of a final evaluation element for the ex post evaluation phase. Logically, for the ex ante phase, this is not required since no effective change has yet been produced. The basic idea is to paint a picture of quantitative changes in indicators related to each analysed component, which can be imputed to the evaluated project, programme or policy. For that, it is possible to analyse the evolution of statistical indicators prior to and post implementation. Again here, a 0 would signify a null impact, whereas a 1 would represent a maximum impact. This value can be inserted directly by the evaluator in each analysed component after a deep statistical analysis, as a simplified procedure that does not require deep knowledge on statistical methods. Alternatively, an evaluator with that knowledge could instead decide to produce an aggregated statistical index to input the end value in the final formula.

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2.2.1 Qualitative and Quantitative Data Sources As previously explained, the insertion of all the evaluation scores, for all the selected components, is done using a spreadsheet software (normally Microsoft Excel) with predefined selection values to facilitate the introduction of scores. Moreover, all the necessary formulas are already included in the appropriate cells. This means that the final impact scores for each analysed dimension and the general impact score is obtained automatically after all the individual evaluation scores are introduced for each analysed component. Hence, what requires more time when using TARGET_ TIA is the process of collecting sound (qualitative and quantitative) evidence to lead to the selection of an appropriate impact score. From our past experiences, it is possible to conclude that the qualitative elements are better obtained via individual semi-open interviews to a few selected experts, already involved in collecting on the main impacts of the project, programme or policy, in the selected dimensions and respective components. Generally, it is recommended to interview a few experienced policy officials who deal with the evaluated subject on a daily basis, whilst adding a couple of academic experts to the mix. Moreover, qualitative elements should include existing evaluation reports and other relevant literature on the evaluation subject and respective territory. Also crucial is a deep project database analysis. Indeed, on certain occasions where projects or programmes do not have financial muscle to impact certain quantitative indicators such as GDP, only a deep project analysis can provide proper and sound evaluation indications on their impacts, as is the case in the evaluation of EU INTERREG-A programmes. In the same way, the selection of appropriate quantitative data depends on the evaluated project, programme or policy. As a TIA tool, TARGET_TIA provides a holistic analytic policy scope. As such, the selection of related quantitative indicators for some components can be complex. This is true in particular for indicators associated with territorial-governance-related components and also with environmental indicators. The problem here is particularly severe when trying to find comparable indicators for two periods of time, one of them being prior to 2000. Before that date, few governance- and environmental-related statistical indicators were available in official statistics. This might require additional work to find those indicators in national and regional entities. Again here, the contact with experts on each analysed dimension can help to mitigate this problem. In the end, the TARGET_TIA formula will produce a general territorial impact score situated between −4 and + 4. Normally, in such a broad policy, such as EU Cohesion Policy, which might have high positive impacts in a few components of territorial cohesion dimensions, and low or negative impacts in some others, we can expect a general impact score situated between −2 and + 2 (low to moderate negative or positive impacts). On a positive note, TARGET_TIA permits the automatic retrieval of impact scores for all the selected dimensions. In the case of the evaluation of EU Cohesion Policy on the Iberian Peninsula, that allows for obtaining potential territorial impact scores for socioeconomic cohesion, environmental sustainability, territorial governance/cooperation and morphological polycentrism.

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This is particularly important as distinct impacts from projects, programmes and policies in such diverse dimensions could be anticipated.

2.3

 oncrete Example of Its Application on a Project/ C Programme/Policy

Following from the previous section, the ex-post territorial impacts of EU Cohesion Policy on the Iberian Peninsula (1989–2013) were selected to exemplify how the step-by-step implementation of TARGET_TIA works. This choice was based on our previous work in assessing the main territorial impacts of EU Cohesion Policy in Portugal (Medeiros 2013) and Spain (Medeiros 2017a). Building upon this previous work allowed us to have all the necessary qualitative (interviews, literatures, project analysis) and quantitative (statistics) information to input the impact scores using the pre-formatted TARGET_TIA spreadsheet matrix (Table 2.1). As can be seen, the four dimensions of the territorial cohesion concept were selected as an analytic framework. Several key components were then selected for each one of these dimensions. In this case, the ‘Socioeconomic Cohesion’ dimension had double (8) the number of components of the remaining three dimensions, since it incorporates two crucial domains of territorial development (economy and society). The main concern here was to select a balanced number of analytic components per dimension so that the final impact scores for each dimension were sound and balanced. Another important decision was to select components that had a real possibility to be impacted by the selected project, programme or policy. The reason for this is simple: one irrelevant component in this mix would get a value that would negatively affect the overall impact score of the analysed subject. After defining the proper analytic dimensions and respective components, the evaluator needs to collect as much relevant qualitative and quantitative information as possible to input the most appropriate impact score in each column of the TARGET_TIA matrix (light blue values in Table 2.1). In the case of a very detailed and complete procedure, all the values available in the ‘type of impacts’ columns should be inserted, in order to provide the counterfactual evaluation scenario. In certain cases, however, it might be difficult to obtain the appropriate counterfactual vector score for certain components. In these cases, the same value of the positive-­ negative evaluation vector should be inserted in the three counterfactual evaluation vectors, so as not to affect the overall average in this evaluation parameter. The following step is to fill-up the next two columns with two adjusting evaluation elements. For the ‘policy intensity’ there is a need to know the detailed allocation of funds of the analysed subject for each one of the analysed components. The higher the financial value allocated, the higher the value in this parameter. Similarly, the selection of the most appropriate value to be inserted in the ‘regional sensibility’ column requires a deep knowledge of the territory in which the project, programme or policy is being implemented. In brief, the higher the need of this territory (in general) to improve in a specific analysed component, the higher should be the score included in this parameter.

2 2 2 2 1

1 2 2 2 1

Socioeconomic Cohesion (SOC) Social Exclusion

Socioeconomic Cohesion (SOC) Income

Socioeconomic Cohesion (SOC) Employment

Socioeconomic Cohesion (SOC) Productivity

Socioeconomic Cohesion (SOC) Innovation

Environmental Protection

Recycling/Infrastructures

Biodiversity

Environmental Sustainability

Environmental Sustainability

Environmental Sustainability

Vertical Cooperation

Participation

Involvement

Governance / Cooperation

Governance / Cooperation

Governance / Cooperation

1

-1

1,72

1,25

1

1

1

2

2,00

2

2

1

3

2,00

0

3

3

2

1,38

2

2

1

1

1

1

2

3

1,75

1,50

1

3

3

-1

1,50

1

1

1

3

2,00

1

3

3

1

2,00

1

2

2

3

1

2

2

3

1,62

1,19

0,5

1,75

2,25

0,25

1,63

1,5

1,5

1

2,5

1,88

0,75

2,75

2,75

1,25

1,78

1,25

2

1,75

2

1,25

1,5

1,75

2,75

0,46

0,63

0,25

0,75

0,75

0,75

0,31

0,25

0,25

0,25

0,5

0,31

0

0,75

0,25

0,25

0,59

0,75

0,75

0,75

1

0,25

0,25

0,25

0,75

Pol/Int

0 to 1

0,90

0,81

0,75

0,75

0,75

1

1,00

1

1

1

1

0,88

0,75

1

0,75

1

0,91

1

1

0,75

1

0,75

0,75

1

1

Sen/Reg

0,29

0,25

0,25

0,25

0,25

0,25

0,25

0,25

0,25

0,25

0,25

0,38

0,5

0,25

0,5

0,25

0,28

0,25

0,25

0,5

0,25

0,25

0,25

0,25

0,25

1989

TCI 0 to 1

0,5

0,5

0,5

0,5

0,5

0,5

0,5

0,5

0,53

0,44

0,25

0,75

0,5

0,25

0,56

0,5

0,5

0,5

0,75

0,63

0,5

0,5

0,75

0,75

0,50

2016

Source: own elaboration Legend: Pos/Neg (Positive/Negative); End/Exo (Endogenous/Exogenous); Sust/Shor (Sustainable/Short Term); Mul/Sub (Multiplier/Substitution); Pol/Int (Policy Intensity); Sen/Reg (Regional Sensibility)

1,91

1,75

1

2

1,09

Distribution / Form

Polycentricity

3

2

General Average

Connectivity

Polycentricity

2

-2

2

1 2,00

2

1 1,00

3 1

1 1

0,25

Density

Polycentricity

1

1 2,00

3

2 1,50

1 3

1 2

Average

Hierarchy / Ranking

Polycentricity

Average

Horizontal Cooperation

Governance / Cooperation

Average

Energy

Environmental Sustainability

1,88

2

1

Socioeconomic Cohesion (SOC) Culture / Sport

1,63

2

1

Socioeconomic Cohesion (SOC) Health

Average

2

Pos/Neg End/Exo Sust/Shor Mul/Sub Average

Type of Impacts (-4 to 4) 3

Component

Socioeconomic Cohesion (SOC) Education

Dimension

Table 2.1  TARGET_TIA matrix – territorial impact scores: EU Cohesion Policy Iberian Peninsula – 1989/2013

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If the evaluation was aimed at assessing the main ex ante impacts of EU Cohesion Policy on the Iberian Peninsula, the evaluation process would halt here, since the use of further quantitative elements aimed at showing the territorial trends in the analysed components would be useless. In the selected example, however, they are much needed, as they add a more impartial and objective analysis to the territorial impact evaluation process. The first column of this ‘quantitative territorial trend analysis’ represents the base-line scenario of the impact evaluation process. In other words, the score values to be inserted in this column portray the ‘territorial development status’ of the analysed territory (as a whole) in the analysed component in a wider context. In the presented case (Iberian Peninsula) this wider context is the European Union (EU) average. Concretely, the lower the score, the less positive territorial context in the analysed component. Evidently, the second column represents a period of time after the project, programme or policy was implemented. This period varies from case to case. For a policy like EU Cohesion Policy it is recommended to wait around 3 years for its impacts to take full effect. After all these scores are incorporated into the TARGET_TIA matrix, the impact scores for each selected analytic dimension are automatically produced, as well as a ‘general impact score’ of the evaluated subject. In this case, the general impact score was low to moderate positive (1.137) (see Table  2.2). This ‘general score’ results from the arithmetical average of the four impact scores obtained in the selected four dimensions. These, instead, show that higher positive impacts of the implementation of EU Cohesion Policy on the Iberian Peninsula were obtained in promoting ‘socioeconomic cohesion’ and ‘morphologic polycentrism’, whereas the ‘environmental sustainability’ process was the least positively affected (Medeiros 2018b). As previously stated, EU Cohesion Policy produces impacts in basically all territorial development dimensions and respective components (see EC 2017; Medeiros 2016d). As such, the general impact value obtained when assessing the main territorial impacts of this Policy, has to be interpreted with care. Firstly, in certain policy domains, these impacts can be quite reduced or even negative. This might contrast with other policy domains, where this Policy was able to produce very high positive Table 2.2  Territorial impact scores per main dimension: EU Cohesion Policy in Iberian Peninsula – 1989/2013 General

Soc/Eco

Sus/Env

Gov/Coo

Polycen

EIMql = Estimated Qualitative Impacts

1,617

1,781

1,875

1,625

1,188

Territorial Cohesion Index

0,242

0,219

0,250

0,313

0,188

EIMqt = Estimated Quantitative Impacts

3,875

3,500

4,000

5,000

3,000

EIM = (EIMql * EIMqt)

2,738

2,609

2,938

3,313

2,094

I = Regional Intensity of ‘p’

0,461

0,594

0,313

0,313

0,625

S = Regional Sensibility to ‘p’

0,898

0,906

0,875

1,000

0,813

1,137

1,421

0,803

1,035

1,063

Source: own elaboration Note: Soc/Eco: Socioeconomic cohesion; Sus/Env: Environmental Sustainability; Gov/Coo: Territorial Governance and Cooperation; Polycen: Morphological polycentrism

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Fig. 2.3  Potential territorial impact scores for the implementation of EU Cohesion Policy in Iberian Peninsula (NUTS II) – 1989–2013. (Source: Own elaboration)

impacts. Secondly, the potential territorial impacts of EU Cohesion Policy vary from region to region, as the less developed regions, in a given EU member state, are supposed to receive higher volumes of funding. In this context, it is recommended that a similar TIA evaluation should be done for each region, thus allowing more detailed and comparable cartography of the obtained impact scores (Fig. 2.3). Taking the analytic component of ‘education’ as one concrete example on how to decide on the most appropriate potential impact score to fill up the TARGET_TIA evaluation matrix (see Table 3.1). After collecting all the necessary qualitative and quantitative information, it became evident that, in overall terms, the Iberia Peninsula was positively impacted in a high degree with the investments from EU Cohesion Policy in this policy sector. This justifies the score of ‘3’ in the positive-negative evaluation vector. The same score was given to the multiplier–substitution effect, as education is widely recognised to have profound and widespread multiplier effects in many development dimensions and components, such as health, income, political decisions and others (OECD 2018; UNESCO 2012). This is true for all territories and is particularly true for the two Iberian countries, which are relatively young democracies within the European context. Likewise, the investments in education were, in large part, sustainable over time, as they focused on infrastructural renovation, supporting research and innovation in universities, and in establishing professional training courses, amongst other education-related instruments (IGFSE 2009a, b, 2011; Fuentes and Mariscal 2005; Requena 2006). In this context, a 3 was attributed to this counterfactual evaluation vector. Conversely, a lower impact score (2)

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was given to the endogenous–exogenous evaluation vector, since the brain drain effect (Schiller and Diez 2011) on the Iberian Peninsula was considerable, in particular during the 2008 financial crisis (Hasanefendic 2017; Lorca-Susino 2011). For the ‘policy intensity’ score, the project analysis showed that, in Portugal, education and training were the third most financed policy sector by EU Cohesion Policy, and the sixth in Spain. Therefore a 0.75 score was attributed, in a maximum of 1. From a ‘regional sensibility’ perspective, however, in a base line scenario (around 1989) the need for improving the education panorama was very high in both Iberian countries, within the EU context. This scenario justified the maximum score (1) attributed in this parameter. Finally, the statistical data demonstrated how both Iberian countries were lagging in the education attainment related indicators by around 1989 (EC 1996). As such, for the first territorial development trend score, a low score (0.25) was attributed. By 2016, all these indicators had substantially improved, so a higher score was inserted (0.75) for the second column, which represents a more recent scenario. Here, the maximum score (1) was not yet achieved since the most recent education-related data for both Iberian countries did not yet attain, in general, the levels of most EU developed countries (EUROSTAT 2018). A similar evaluation rationale is applied to the remaining selected components in the TARGET_TIA matrix. Understandably, the higher the knowledge on each one of these components, the higher the quality and reliability of the final general potential impact score of the evaluated project, programme or policy. The following section will summarise the main strengths and weaknesses of TARGET_TIA based on almost 10 years of constant use and adaptation to different evaluation contexts.

2.4

 ain Results, Strengths and Weaknesses, M and Future Prospects

TIA tools are relatively recent and are not, in most cases, integrated into the national policy evaluation frameworks (Medeiros 2016b). By and large, they are still very much included within the group of EU Impact Assessment (IA) tools, such as the mandatory SEA and EIA procedures (see Anjaneyulu and Manickam 2007; Glasson et al. 1999; Lawrence 2003). Ultimately, these EU IA tools are intended to improve the quality and coherence of the policy development process, whilst contributing to a more effective and efficient regulatory environment towards the implementation of the European Sustainable Development Strategy (White 2010). By the same token, TARGET_TIA has been, until now, mainly used to assess the ex-post territorial impacts EU funded programmes and policies, with a clear territorial dimension (see Medeiros 2017d). More particularly, it was initially used to assess the main impacts of EU Cohesion Policy in three EU countries: Portugal, Spain and Sweden. The end result was quite positive, as it allowed to produce sound and comparable impact scores in all analysed dimensions of this Policy: (i) socioeconomic cohesion; (ii) environmental sustainability; (iii) territorial governance/ cooperation; and (iv) morphologic polycentrism. Unlike existing ESPON TIAs, which were designed to assess EU directives (TEQUILA – see Chap. 3, and ESPON

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Quick Check TIA), TARGET_TIA was designed to provide a sound and relevant potential impact score of analysed projects, programmes and policies. In the end the intended results were achieved in full, within quite an acceptable time schedule, taking into consideration the number of persons involved in the evaluation (one) and the amount of collected and treated information. Taking the last studied case (EU Cohesion Policy in Sweden), the whole evaluation process (collecting and treating qualitative and quantitative data + production of cartography + production of the report and article) took around 4 months to complete. This means that a larger research unit of, for instance, five persons, with an already deep knowledge on the studied territory and policy, can deliver the final evaluation report in around 2 months. This is often times less that the ESPON TIAs evaluation reports take to be produced. Furthermore, TARGET_TIA was used to assess territorial impacts at different territorial scales: national, regional and cross-border. Indeed, following the EU Cohesion Policy TIA experience, which was particularly demanding, since this Policy expands its tentacles to all branches of territorial development, TARGET_ TIA was tested in the EU INTERREG-A programmes (cross-border cooperation). More specifically, it was used to assess the main territorial impacts of the Inner Scandinavia sub-programme of the Swedish-Norwegian INTERREG-A programme (1994–2013). For this particular case, all new analytic dimensions were selected, with respective components. This was the ultimate opportunity to test the flexibility and adaptability of the TARGET_TIA matrix and formula. The end result was, once again, extremely positive as no further methodological changes were required to the existing evaluation matrix in the spreadsheet. In this light, and based on concrete and already published results from implementing TARGET_TIA, it can be concluded that its main strengths as a sound and relevant TIA tool are the following: • Credibility: TARGET_TIA is designed to produce sound and relevant potential impact scores. This is the only TIA tool which makes use of counterfactual evaluation vectors, which are fundamental elements for implementing sound impact assessment tools. In addition, it adds two crucial TIA evaluation tuning elements (‘policy intensity’ and ‘regional sensibility’) to improve the robustness of the TIA analysis. Furthermore, by not following the erroneous notion that it is possible to obtain these scores in a quick way, TARGET_TIA is particularly designed to be used by all entities which intend to realistically and effectively understand the main territorial impacts of projects, programmes and policies. • Flexibility: TARGET_TIA is designed to be used in all evaluation phases: ex ante, mid-term and ex post. At the same time, it can be used to assess the territorial impacts of all sorts of policies, programmes and projects. By being implemented via a spreadsheet, it permits an easy inclusion and/or elimination of evaluation dimensions and respective components. This tailor-made possibility to adjust the TARGET_TIA evaluation matrix to completely different evaluation subjects can be particularly useful for entities which operate in distinct policy evaluation environments. More importantly, however, unlike most ESPON TIA tools, TARGET_TIA is independent from online platforms, which have little

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flexibility to tailor-made TIA procedures to a concrete project, programme and policy. • Easy to operate: As previously explained, TARGET_TIA is operated in a spreadsheet matrix with all the necessary formulas already incorporated. As such, after the evaluator collects all the necessary information concerning the main territorial impacts of the evaluated project, programme or policy, the inclusion of the most appropriate impact scores for each selected component becomes quite a straightforward, fast and easy process. In overall terms, the whole spreadsheet completion procedure takes around 15 min. Moreover, there is no need for specific technical knowledge to operate TARGET_TIA (read spreadsheet matrix) as the only thing that is required is the insertion of appropriate impact scores in the appropriate columns. • Cost-effective: A spreadsheet like Microsoft Excel is commonly present in every computer of policy evaluation entities. Moreover, there are cost-free alternative spreadsheets (Open Office) available, compatible with Microsoft Excel, for anyone who does not have this software already installed. In this light, no extra costs are involved when using TARGET_TIA to assess territorial impacts. Furthermore, the latest versions of Microsoft Excel have incorporated a Mapping Tool, which permits automatic cartography of impact scores across different territories. Better still, an Arc GIS add-on can be incorporated into Microsoft Excel as a way to produce automatic professional cartography. As regards the potential weaknesses of TARGET_TIA, there is one issue which is transversal to all TIA tools: no one with limited knowledge on the analysed subject and territory should use this tool. The fact that TARGET_TIA is very simple and flexible to operate does not signify that anyone can use it for assessing territorial impacts. Conversely, only someone with deep knowledge of what is being assessed should use TARGET_TIA or any other policy evaluation tool. This means that officials from local, regional, national and EU entities can use it on a regular basis, as well as any other policy evaluation professionals. Oher than that, TARGET_TIA does not present any other significant shortcoming. For the next few years, it is expected that TARGET_TIA will also be applied to assess ex-ante impacts of regional, national and EU programmes and policies, and especially the ones associated with EU Cohesion Policy, which will soon enter into a new programming phase (2021–2027). Additionally, it could be applied to assess the main territorial impacts of spatial planning instruments (Medeiros 2019), large scale projects, such as airports, and urban development policies, for instance. From a methodological perspective, no particular changes are anticipated, since the present formula has been intensively tested in distinct policy environments with success. However, a relatively recent verbal agreement was made with the EU Joint Research Centre to test the possible link of TARGET_TIA with the LUISA Territorial Modelling Platform (see Chap. 10). The basic idea was to take the best of both worlds: (i) provide TARGET_TIA with online automatic cartography of impact scores and (ii) provide LUISA with a sound and relevant TIA methodology.

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More important, however, would be to see the use of TARGET_TIA by several local, regional and national entities responsible for promoting and assessing territorial development processes. As a flexible, sound, easy-to-operate and low-cost TIA tool, TARGET_TIA can be regarded as an optimal choice for all those that want to implement this holistic and more complete policy evaluation methodology, with the ultimate goal of improving the effectiveness and efficiency of public policies.

References Anjaneyulu Y, Manickam V (2007) Environmental impact assessment methodologies, 2nd edn. BS Publications, Hyderabad EC (1996) First report on economic and social cohesion. European Commission, Luxembourg EC (1999) MEANS – evaluation socio-economic programmes – evaluating design and management, vol 1. European Commission, Luxembourg EC (2008) EVALSED – the resource for the evaluation for socio-economic development. European Commission, Brussels EC (2009) Impact assessment guidelines, 15 January 2009. European Commission, Brussels EC (2013) EVALSED  – the resource for the evaluation for Socio-Economic Development, September 2013. European Commission, Brussels EC (2017) My Region, My Europe, Our Future, Seventh report on economic, social and territorial cohesion. European Commission, Brussels ESPON (2012) Territorial Impact Assessment of Policies and EU Directives. A practical guidance for policymakers and practitioners based on contributions from ESPON projects and the European Commission. ESPON, Luxembourg ESPON 3.2 (2006) Spatial Scenarios and Orientations in relation to the ESDP and Cohesion Policy, Volume 5 – Territorial Impact Assessment, Final Report, October 2006. ESPON, Luxembourg EUROSTAT (2018) Eurostat regional yearbook, 2018th edn. European Commission, Eurostat, Brussels Fuentes R, Mariscal C (2005) Efectos de la Política regional Comunitaria sobre la Dotación de Infraestruturas: La contribución de los fondos estructurales para su mejora (2000–2002), Ciudad y Territorio. Estudios Territoriales XXXVII(143):21–42 Glasson J, Therivel R, Chadwick A (1999) Introduction to environmental impact assessment, principles and procedures, process, practice and prospects, 2nd edn. UCL Press Limited, London Hasanefendic S (2017) “Brain drain, brain gain… Brain sustain?” Challenges in building Portuguese human research capacity. Sociologia, Problemas e Práticas 83(1):117–135 IGFSE (2009a) Contributo do Fundo Social Europeu para a Formação dos Activos Empregados, Estudo de Avaliação integrado na colecção de estudos: temas fundo social europeu. Instituto de Gestão do Fundo Social Europeu, I.P., Lisbon IGFSE (2009b) Intervenção do FSE e Desenvolvimento do Potencial Humano em Portugal, Estudo de Avaliação integrado na colecção de estudos: temas fundo social europeu. Instituto de Gestão do Fundo Social Europeu, I.P., Lisbon IGFSE (2011) Síntese da intervenção do FSE no QREN, Informação reportada a 31 de Dezembro de 2011. Instituto de Gestão do Fundo Social Europeu, I.P., Lisbon Lawrence D (2003) Environmental impact assessment. Practical solutions to recurrent problems. Wiley, Hoboken Lorca-Susino M (2011) Spain and the Brain Drain in the 21st century: it is not only what you can do for your Country, but also what your Country can do for you. In: Roy J, Lorca-Susino M (eds) Spain in the European Union: the first twenty-five years (1986–2011). Miami-Florida European Union Center/Jean Monnet Chair, Miami, pp 211–228 Medeiros E (2013) Assessing territorial impacts of the EU Cohesion Policy: the Portuguese case. Eur Plan Stud 22(9):1960–1988

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Medeiros E (ed) (2014a) Territorial impact assessment (TIA). The process, methods and techniques (ed.) Centro de Estudos Geográficos, ZOE, Lisbon University, 126p Medeiros E (2014b) Assessing territorial impacts of the EU Cohesion Policy at the regional level: the case of Algarve. Impact Assess Proj Apprais 32(3):198–212 Medeiros E (2015) Territorial impact assessment and cross-border cooperation. Reg Stud Reg Sci 2(1):95–115 Medeiros E (2016a) EU cohesion policy in Sweden (1995–2013). A territorial impact assessment. Eur Struct Invest Funds J 3(4):209–230 Medeiros E (2016b) Territorial impact assessment and public policies: the case of Portugal and the EU. Public Policy Port J 1(1):51–61 Medeiros E (2016c) Territorial cohesion: an EU concept. Eur J Spat Dev 60. http://www.nordregio. org/publications/territorial-cohesion-an-eu-concept Medeiros E (2016d) Is there a rise of the territorial dimension in EU Cohesion policy? Finisterra 103:89–113 Medeiros E (2017a) European Union Cohesion Policy and Spain: a territorial impact assessment. Reg Stud 51(8):1259–1269 Medeiros E (2017b) From simple to relevant TIA tools for European policies. In: Medeiros E (ed) Uncovering the territorial dimension of European Union Cohesion Policy, Routledge, London: pp 147–160 Medeiros E (2017c) Cross-border cooperation in inner Scandinavia: a territorial impact assessment. Environ Impact Assess Rev 62(2017):147–157 Medeiros E (2017d) The territorial dimension of European policies: a conceptual approach. In: Medeiros E (ed) Uncovering the territorial dimension of European Union Cohesion Policy, Routledge, London: pp 9–22 Medeiros E (2018a) Focusing on cross-border territorial impacts. In: Medeiros E (ed) European territorial cooperation, The urban book series. Springer, Cham Medeiros E (2018b) EU Cohesion Policy in the Iberian Peninsula: main territorial impacts (1986–2013) and challenges for a more efficient new programming period (2014–2020). Eur Struct Invest Funds J 6(4):284–295 Medeiros E (2019) Spatial planning, territorial development and territorial impact assessment. J Plan Lit 34(2):171–182 OECD (2018) Education at a Glance 2018, OECD Indicators. The Organisation for Economic Co-operation and Development, Paris Requena M (2006) España en la Unión Europea: cambios sociales y dinámicas demográficas. In: da História T (ed) Portugal e Espanha. Crise e convergência na União Europeia, Parede, pp 49–73 Schiller D, Diez JR (2011) The impact of academic mobility on the creation of localized intangible assets. Reg Stud 46(10):1319–1332 UNESCO (2012) Shaping the education of tomorrow, report on the UN decade of education for sustainable development. United Nations Cultural Organization, New York White S (2010) Impact assessment  – experience from the European Commission. In: Bizer K, Lechner S, Führ M (eds) The European impact assessment and the environment. Springer, Berlin/Heidelberg

3

The Pioneering Quantitative Model for TIA: TEQUILA Roberto Camagni

Abstract

The request for building an operational model for the ex ante assessment of the territorial impact of EU policies, projects and regulations was addressed directly to the author by the ESPON managing authority. A rationale and definition of what could be intended as TIA was proposed, a prototype model and the connected software was built and applied to the TEN (Trans-European Network) program in 2004–2006. The convincing results achieved were followed by subsequent new and deeper studies, where the model was improved, simplified and implemented on EU transport and agricultural policies and to some EU directives in the environmental fields. TEQUILA is a multi-criteria model working on a quantitative base on Nuts3 regions in the EU; however, it integrates in a statistically consistent way qualitative judgements by experts, when necessary. The criteria refer to the main dimensions of territorial cohesion – territorial efficiency, territorial quality and territorial identity  – and their sub-dimensions/criteria, measurable by multiple indicators. Particularly the goal of territorial identity captured the interest and favour of policy makers. Impact maps on concrete applications, illustrated here, were used in official reports of the European Commission. Keywords

Territorial Impact Assessment · territorial cohesion · integrated spatial policies and planning · multi-criteria analysis

R. Camagni (*) Department ABC - Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Milan, Italy e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_3

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Historical Background, Main Goals and Applications

The idea of launching a Territorial Impact Assessment (TIA) in order to evaluate ex ante a wide spectrum of potential outcomes of European plans, measures and projects, emerged and was deeply debated during the preparation of the ESDP, the European Spatial Development Perspective, in the years 1995–1999. The initiative to produce this document  – and its main political elaboration  – intended to be a ‘policy framework’ for the Commission, the Member States, their regions and local authorities (EC 1999: 5), came from the European Council of Ministers responsible for spatial planning and development, and was implemented through the Committee on Spatial Development  – encompassing delegates of the Member States  – the European Commission holding the task of secretariat. In my position of representative of Italy in that Committee,1 I was totally in favour of that proposal, perfectly consistent with the newly acknowledged role assigned to ‘territory’ in sustainable development and cohesion policy and with the request for integrated policy and planning tools. The term explicitly referred to an ex ante evaluation of impacts of any policy intervention directly or indirectly implemented by the European Union on all dimensions that insist on geographical space, namely the economic, social, environmental, but also the cultural and identitarian ones. The last draft of the ESDP by the Committee, approved in Glasgow in June 1998 by the Ministers for Spatial Planning, speaks about a “Spatial Impact Assessment” necessary in order “to strengthen co-ordination of regionally significant plans and measures” and “assist an informal discussion of proposed projects, including alternatives”. Moreover, it suggests that the task of further developing the necessary techniques be assigned to the European Spatial Planning Observatory Network (CMSP 1998: 84–85), still to be approved. The subsequent final draft of the ESDP, published by the Commission and approved by Ministers in Potsdam in May 1999, turns the term ‘spatial’ into ‘territorial’, quite a neologism in the English language but widely employed in spatial development planning in the Latin countries (France, Italy, Portugal, Spain) with a much richer meaning with respect to abstract ‘space’. Territory in fact can be understood as: • A system of localised technological externalities, both ‘technological’ and ‘pecuniary’, i.e. an ensemble of material and immaterial assets and production factors • A system of economic and social relations, functional and hierarchical, which make up the relational capital (Camagni 1999) or the social capital (Putnam 1993; World Bank 2001) of a certain geographic space • A system of representations, sense of belonging and loyalty to places • A system of local governance, which brings together collectivities, ensembles of private actors and systems of local public administrations (Camagni 2002) 1  In that period, 1997–1998, I was serving as head of the Department of Urban Affairs at the Presidency of the Council of Ministers in Rome, under the first Prodi government.

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3.1.1 Initial Institutional Definition and the Main Goals of TIA The final ESDP draft (EC 1999) refers to TIA in many cases, particularly where the different preferences of public decision makers and private stakeholders have to find a difficult equilibrium point. This happens in the sphere of transport policies – the accessibility/environment trade-off  – but also in the management of natural and cultural resources, where clashes between private and collective interests are the norm. In all these cases the need for comprehensive and integrated territorial strategies is considered crucial and the development of a sound TIA tool is considered the right way to provide useful evidence and rational advices to policy makers. Therefore, the Document strongly suggests that “in the future, territorial impact assessment should be the basic prerequisite for all large transport projects” (par. 109); that it should “provide the necessary information” for a wise balancing of protection and development in the “conservation and management of natural resources” (par. 138), and that, in the sphere of water resource management, “the impact of large water exploitation related projects should be examined through territorial and environmental impact assessment” (par. 145). In all these three cases, TIA is recommended explicitly in the policy options paragraphs (n. 29, 42, 52).2 The mandate to develop a consistent methodology for TIA was subsequently launched with the ESDP Action Programme at the Informal Ministerial Meeting in Tampere, in September 1999. Inside the general goal of promoting “a spatial dimension in Community and national policies”, the action concerning Territorial Impact Assessment was formulated in the following precise words: “The development of a common concept for territorial impact assessment (TIA) is necessary to support spatial development policies. The concept shall be of a cross-sectoral nature and include socio-economic, environmental and cultural indicators for the territory in question”. Three elements have to be underlined: the implicit acknowledgement that no common concept did in fact exist3; the necessary multi-sectoral nature of the methodological approach; the fact that impact should take into consideration the specificity of each territory. The task to properly define and develop the concept in operational terms was later assigned to the newly established ESPON program. The Commission supported the proposal, introducing a new Impact Assessment (IA) procedure, designed to contribute to the implementation of the Sustainable Development Strategy through the assessment of the potential impact of policy options (EC 2002), and subsequently applying it to a number of Commission’s 2  In the final paragraph of the ESDP (326), where the case of cultural sites and art cities is dealt with, particularly with reference to tourism and “property market speculation” threats, similar spatial development strategies integrating different approaches are suggested, but not a formalised impact assessment tool (probably due to the immaterial costs and benefits which are intrinsic in Cultural Heritage (CH). However, as it will be shown later, some reliable quantitative measurements are possible also in the field of CH. A recent econometric work on the relationship between CH and development through such immaterial processes as inspiration and creativity has produced solid and convincing results. See: Cerisola 2019. 3  A careful scoping document on the subject was produced by Williams et al. 2000, confirming the non-existence of such a tool.

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proposals. Impact assessment is conceived as “a set of logical steps which structure the preparation of policy proposals” at the European level (EC 2005: 4), cutting across and integrating different sectors and dimensions (economic, environmental and social) and replacing all previous single-sector-type assessments (environmental, gender, business, health assessments) (EC 2004a). The main difference in this proposal with respect to TIA regards its aggregate, Europe-wide, a-spatial perspective, while TIA should be designed in order to cope with the specificities of each region or place in terms of objective conditions and subjective priorities.

3.1.2 A  More Precise Theoretical and Operational Definition of TIA Knowing well the previous history of the TIA concept, this author started early to reflect on a more precise definition of the term, possibly opening the way to its operational translation. In my opinion, TIA should be intended as the assessment of the effects of policies, plans and projects on the new major goal of the Union: achieving territorial cohesion (TC). In fact, in those years, the Commission proposed to add it to the two traditional pillars of the Union, namely economic and social cohesion (EC 2004b), a proposal that was authoritatively accepted and formalised in the Draft Constitution (2004) and in the Lisbon Treaty (2008): “The Union …. shall promote economic, social and territorial cohesion” (art. 3.3). The importance of this statement is reinforced by art. 4.2.c of the Treaty on the Functioning of the European Union: “Shared competence between the Union and the Member States applies in the area of … economic, social and territorial cohesion” (TC). Unfortunately, the TC concept was never adequately defined by the Commission, especially for what concerns its difference with respect to socio-economic cohesion. In fact, speaking about a “more balanced development” or “avoiding territorial imbalances” (EC 2004b: 27) does not add much to the previous goals.4 A slightly better indication came in a subsequent document (EC 2004c: 3): TC “translates the goal of sustainable and balanced development assigned to the Union into territorial terms”. This statement was relaunched by the Presidency Conclusions of the Luxembourg Ministerial Meeting in 2005, acquiring a more “practical” meaning when included in a policy frame: “In practical terms territorial cohesion implies: focusing regional and national territorial development policies on better exploiting regional potentials and territorial capital – Europe’s territorial and cultural diversity; better positioning of regions in Europe ...facilitating their connectivity and territorial integration; and promoting the coherence of EU policies with a territorial 4  The subsequent listing of the empirical issues encompassed by the new concept look more interesting: the concentration of economic activity and population in the European “Pentagon”; the imbalance between metropolitan areas and the rest of the countries; growing congestion, pollution and social exclusion in the main conurbations; the presence of rural areas suffering from inadequate accessibility; urban sprawl.

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impact....” (p. I; original emphasis) (Luxembourg Presidency 2005).5 Later reflections did not add any precision nor rationale to TC, even when the Commission launched a public call for more appropriate definitions of the concept. In my opinion, if the territorial cohesion concept has to be different from economic and social cohesion, it has to be linked to the sustainable development issue. In synthesis, TC should be looked at as “the territorial dimension of sustainability” (Camagni 2006), going beyond the other three main dimensions of the concept, namely: the technological one, having to do with production processes and performance of buildings and goods; the behavioural one, referring to life-styles, consumption habits, organisational models of production and personal mobility (just-in-time production, single passenger car trips, …); and the diplomatic one, concerning international strategies and agreements to assure international cooperation on global environmental challenges. The fourth dimension, the territorial one, looks particularly relevant, having to do with the form of settlements and an ordered, resource-efficient, environmental-friendly distribution of human activities in space (Camagni 1998). On its turn, territorial cohesion presents three sub-­dimensions, which can be indicated in the following: • Territorial efficiency: resource-efficiency with respect to energy, land and natural resources; competitiveness of the economic fabric and attractiveness of the local territory; internal and external accessibility • Territorial quality: the quality of the living and working environment; comparable living standards across territories; similar access to services of general interest and to knowledge • Territorial identity: presence of ‘social capital’; capability of defining and implementing shared visions of the future; local know-how and specificities, productive ‘vocations’ and competitive advantage of each territory (Camagni 2006) In a normative sense, these three dimensions can become societal goals and values in themselves: no modern society can do without them, as they are at the basis of local wellbeing and of local competitiveness as well. This double role was conceptually utilised in many cases to justify compliance and consistency between cohesion policies and development policies, at least in the long run. While the first two objectives are rather familiar, the third, namely territorial identity, may look rather surprising, but is crucial and will become increasingly so in Europe. Territorial identities incorporated in local culture, know-how, social capital and landscape represent the ultimate glue of local societies, facilitate processes of collective learning, consequently boosting the efficiency of the local production fabric (Camagni 2002); moreover, they may easily coexist with wider, layered identities – religious, national, 5  Two relevant innovations are present here. Firstly, traditional “spatial development” policies are called “territorial”; secondly, the concept of ‘territorial capital’ is used for the first time, implicitly suggesting that territory is a resource, generating productivity increases (“higher return for specific kinds of investment”) and wellbeing to local communities. On the meaning and use of the territorial capital concept, see Camagni 2019.

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European (Capello 2018, 2019). But they may generate idiosyncratic behaviours vis-à-vis other identities, and therefore they deserve political attention and wise assessment. Concluding on this point, in our opinion territorial impact assessment means assessing impacts on the territorial cohesion goal and its sub-dimensions (goals): territorial efficiency, quality, identity.

3.2

The Methodology in a Nutshell: Elements and Formula

3.2.1 The Mandate The mandate to develop an operational methodology for TIA was assigned by ESPON inside Project 3.2 concerning “Spatial scenarios and orientations in relation to the ESDP and cohesion policy” in 2005. The terms of the contract were clear and tight: • To build an operational methodology for ex ante impact assessment based on rigorous economic logic, consistent with the guidelines issued by the Commission on the subject • To be used for the assessment of any EU policy, program, integrated project or regulation with territorial impact • Working at different geographical scales (particularly Europe 28 and Nuts3 regions) • Able to handle both quantitative measures and qualitative judgements • Easy to build and operate, understandable by policy makers • Interactive, in order to be used in public meetings Almost impossible mission! Challenge nevertheless accepted. The rationale and the internal logic of the proposed model are the ones previously presented. The best viable spatial level was indicated in Nuts3, the lowest with sufficient availability of data, which means 1360 EU regions.

3.2.2 The Pioneering Model: TEQUILA Given the goal of assessing impacts on the three sub-dimensions of TC, as explained before, the model is called TEQUILA: Territorial Efficiency QUality Identity Layered Assessment. (a) Due to the multiplicity of the ‘dimensions’ converging on territory, each one with its list of potential indicators only rarely measurable in monetary terms, multi-criteria methods looks the most appropriate, as also suggested by well-­ known scholars (Beinot and Nijkamp 2007; Nijkamp et al. 1990) and utilised in

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similar practices like strategic environmental assessment (Nardini 1997; Thérivel and Partidario 1996). (b) The three dimensions of TC and their sub-components through which they can be explored become the criteria and sub-criteria of the assessment model. Measurable sub-criteria for the intensity of the impacts may be listed tentatively as follows (Camagni 2006): • Territorial efficiency: resource efficiency (consumption of energy, land, water); general accessibility, infrastructure endowment; competitiveness; sustainable transport (share of public transport, congestion); intensity of city-networks; compact city form, absence of sprawl; reduction of technological and environmental risk • Territorial quality: conservation and creative management of natural resources; access to services of general interest; quality of life and of working conditions; quality of transport and communication services; reduction of emissions; health (reduction of illness, mortality, ..); safety; attractiveness for external firms; reduction of poverty, unemployment, exclusion; multi-­ ethnic solidarity and integration • Territorial identity: conservation and creative management of cultural heritage; quality of urban and rural landscapes; cooperation between city and countryside; development of region-specific know-how and knowledge; accessibility to global knowledge and creative ‘blending’ with local knowledge; development of territorial ‘vocations’; development of territorial visions through strategic planning practices; social capital, development of trust and shared behavioural rules (c) Among the many models belonging to the multi-criteria family, the simplest one was chosen, namely the linear additive evaluation model based on multi-­ attribute utility theory (Scriven 1994; OECD 2005), operationalised through a simple weighted average of impact scores. Given its simplicity and transparency, the model “comes closest to universal acceptance” (DCLG 2009: 24). The condition of ‘preferential independence’ among criteria, necessary for its appropriate use, is perfectly met by the fact that scores on each criterion derive from completely different statistical sources, are collected separately and, in case of qualitative judgements, are formulated by experts with different professions and background.6 (d) The weights assigned to the single criteria – the most sensitive element in multi-­ criteria – may be defined in multiple ways: through internal discussions among 6  As in the usual performance matrix of MCA showing scores (in our case the impacts of a policy), on columns we find the dimensions/criteria, but on the rows, we do not find alternatives (different projects or alternatives of the same project) but regions. In our case, the goal is not to choose among alternatives as in multi-criteria decision analysis, but to compare impacts on different regions on the basis of consistent quantitative scoring on each single dimension/criterion, the goal being to detect spatial cases where strong mitigation measures should be provided or alternative implementations of the policy investigated. Inside the matrix, weighted summation can be made by column (summative evaluation of impacts on single regions) or by rows (giving a general assessment of the policy impact on the entire EU territory in each dimension/criterion).

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experts, through open discussions with policy makers and stakeholders, through Delphi procedures. In our case, they should reflect a generalised view, valid throughout the EU,7 on the priorities and political preferences among the different dimensions of territory (i.e. the criteria and sub-criteria, relevant for the typology of the program to be assessed). Inside the model, the weights should be flexible in order to guarantee interactivity and, in all cases, they have to be perfectly transparent. Tests with changing weights allows the assessment of sensitivity and stability of the outcome. (e) The impacts on all and each region in each criterion should be defined through ad hoc studies in the appropriate unit of measure of the single impacts (quantitative assessment) or through experts’ judgement collected in interactive meetings (qualitative assessment). In the latter case, scores should be differentiated at least by classes of regions. (f) The impact values expressed in each unit of measure have to be transformed into value scores and normalised on a common interval through a value function that for practical purposes is assumed to be linear. In general, 0–1 or 0–100 intervals are used, and the same for negative scores. In our case, when scores are given through a qualitative expert judgement, a different normalised interval is chosen (−5 to 0 to +5) for a better understanding of the meaning of intermediate values.8 This same interval is also applied in normalisation of quantitative scores. (g) The direct transformation of observed values into normalised scores is normally implemented through the so-called local scaling, where the minimum observed/ calculated value is assigned to 0 and the maximum to 1 (5 in our case), as shown in Fig. 3.1a.9 When there is evidence that people assign a positive or negative value only to extremes impacts, the linear value function can be replaced by a non-linear curve. (h) However, in any weighted sum for the construction of complex indicators, a relevant problem arises: the different variability of scores inside each criterion. In fact, in some cases, the spectrum of observed or calculated values may be wide and the two extremes totally dissimilar, while in some other cases all values may stay close to the average. In both cases the ‘local scaling method’ stretches the data into the same interval 0–1 (or 0–100 or 0–5 as in our case),  For the consideration of the specific priorities of local communities, see later at point l.  On the positive side: 5 = very high advantage for all; 4 = high advantage for all; 3 = high advantage for some, medium advantage for all; 2  =  medium advantage; 1  =  low advantage; 0  =  nil impact. Thanks to the linearity hypothesis, scores in the 0–5 interval are easily transformed in the normal intervals, if needed. 9  In algebraic terms, when n stands for normalised scores and o for observed or calculated values, the normalised value nx of any observed ox is given by: 7 8

nx 



 nmax  nmin   o  ox    omax  omin  max

3  The Pioneering Quantitative Model for TIA: TEQUILA a) ‘local scaling’

b) ‘ad hoc scaling’

+5

+3

0

+2 180 250 Calculated impact on regional employment

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180 250 Calculated impact on regional employment

Fig. 3.1  Alternative scaling methods in quantitative assessment. (Source: own elaboration)

attributing the two extreme normalised scores to the minimum and maximum observed/calculated values. This condition can be acceptable in the former case, but in the latter it is due to generate a huge bias in the sum of scores of all criteria. Manuals suggest two alternative solutions, which do not work properly in our case: either assigning the two extreme normalised scores not to observed values but respectively to the worst and the best values that are expected or likely to be encountered in an assessment of the general type being addressed (global scaling), or assigning a lower weight to the criterion with a limited variability of values/impacts (DCLG 2009, sect. 5.6). The first solution is difficult to manage in general and in our case almost impossible, as the value vector refers to impacts of policy measures with different intensities on different regions and not to impacts of similar alternative projects on the same region (as in frequent multi-criteria decision making). On the other hand, the criticism this author moves to the second solution is methodological: it simply reduces the importance, in the weighted sum, of a biased and misleading vector of data instead of intervening directly with a correction of the mistake.10 (i) Our solution to the previous problem utilises an ad hoc scaling (Fig.  3.1b), namely defining a sub-interval inside the 0–5 one on which to normalise observed/calculated values: it is conceptually similar to the global scaling one, is easier to manage in operational terms and is only apparently introducing a slightly higher level of subjectivity in the procedure (Camagni 2006).11

 Weights are at the same time ‘importance’ coefficient – indicating the priorities of national or regional communities, for example with respect to the common development-environment tradeoff – and ‘substitution indicators’, i.e. marginal substitution rates among impacts on different criteria, allowing compensations among them. The author prefers not to add a third, unconventional role to weights, especially if different solutions can be found. 11  In the example of Fig. 3.1, the values of calculated impacts of an abstract development measure on the different regions (x axis) are very similar: why then should we attribute 0, meaning a hell condition, to 180 new jobs and 5, meaning heaven, to 250? Better to distribute scores between 2 and 3, half point around the average. 10

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(j) Given the differentiated nature of territories, a generalised assessment of the impact of policies on the overall EU territory does not make much sense.12 On the other hand, a truly ‘territorial’ assessment taking into consideration the specificities of the single regions or areas would look much more interesting and even crucial, as: • The intensity of the policy application may be different in the different regions, or even nil. • Its territorial impact is likely to be different on the different regions, given their geographical and socio-economic specificities. • The importance of the single criteria in the assessment methodology is likely to be different in the different regions: different development stages, different histories and cultures, different shared values would determine different views concerning the relative relevance of impacts on growth, on environment, on social wellbeing, on competitiveness. (k) Therefore, a regionalised territorial impact model is built for the assessment of policies, programs and integrated schemes, keeping in mind the request for simplicity, operationality and transparency. In the case of fully quantitative assessment, the formula is (Camagni 2009): TIMr   c  c . PIMr ,c . Sr ,c . (3.1)

where:

TIM = territorial impact (total or for each dimension: territorial efficiency, quality, identity), r = region, c = criterion or sub-criterion in the multi-criteria method, PIM r,c = potential impact of policy (abstract) on region r and criterion c θc = weight of the c criterion/sub-criterion 0 ≤ θc ≤ 1;    Σcθc = 1 S r,c = sensitivity of region r to criterion c. (l) The rationale for the previous equation comes from traditional risk assessment procedure, where risk = hazard (potential risk) x vulnerability. Similarly, here the territorial impact is seen as the product of a potential impact (PIM) times a sensitivity indicator S, expressing the specificity of the region and its preferences. Therefore, Sr,c is a set of regional characteristics, defining two main elements: desirability of the dimension/criterion in single regions (technically: the territorial ‘utility function’ indicating local preferences, measured by socio-­ economic indicators) and vulnerability to impact (mainly geographic indicators): Sr ,c = Dr ,c . Vr ,c

where:

12

 But it can be implemented easily: see footnote 6.

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37

D r,c = desirability of criterion c for region r (territorial ‘utility function’) V r,c = vulnerability of region r to impact on criterion c (receptivity for positive impacts).13 (m) The potential impact PIM is calculated through appropriate, external quantitative models defining impacts on each criterion c and each region r, duly normalised as indicated in point (i). D and V are designed as coefficients scaling up and down respectively the θc and the PIM r,c of a given maximum percentage. The quantitative indicators to be used for the desirability regional coefficient are in general the same used for the impact, in their status form and not in their change consequent to the policy implementation: e.g. desirability of an increase in GDP is inversely proportional to the present GDP per head in the regions.14 The vulnerability coefficient is mainly present in the environmental dimension/criteria and requests ad hoc indicators. Receptivity (in case of positive effects of policies) could be quantified linking it to quality of government, and utilised in case it is explicitly considered a plus in the allocation of funds. In our experience it is set to 1 (neutral role). (n) In case a quantitative assessment is not viable, for technical or economic reasons, for the entire model or just for some criteria, a qualitative assessment can be implemented through experts’ judgements. In this case the PIM r,c is calculated in a simplified form:

PIMr ,c = PIM c . PI r

(3.2)

where PIMc is an abstract potential impact of the policy measure on the c criterion without geographical reference and PIr is policy intensity in region r. Therefore, in the qualitative assessment case the full formula is:

TIMr   c c . Sr ,c .

 PIMc

. PI r  (3.3)

(o) The proposed ‘summative’ evaluation procedure (totally quantitative, totally qualitative or mixed) implies allowing compensation among criteria, namely that negative scores in one criterion may be compensated by positive scores in another. This condition is not always politically acceptable or accepted; therefore, non-compensatory multi-criteria approaches have been developed (like the one by Munda 1995). In our case, beyond single-criteria calculations and mapping that are always shown and that could be emphasised in a political debate, a ‘conditional’ non-compensatory method was presented in the  For example: in the case of a technological risk, PIM gives the probability of explosion of a given plant, and Vr the damage in case the plant is located close to a city or in an inhabited site. 14  In this case, if max % change allowed is 20%, for a region with a per capita GDP equal to the EU average the coefficient will be 1 (no change); for the poorest region it will be 1,20 and for the richest region 0,80. Therefore the same increase in GDP will have a superior value in the poor region and an inferior (perceived) value in the rich one. 13

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subsequent TIP-TAP version of the TEQUILA general model, where compensation is stopped in those regions where some conditions are not met (see later).

3.2.3 The Prototype Implementation The TEQUILA model is operated through an Interactive Simulation Package, the TEQUILA SIP. The initial spreadsheet of the model presents: • The full list of criteria and sub-criteria employed, with weights in the actual and in the previous run (in order to have a test on sensitivity) • The result of the quantitative assessment (expressed in scores from −5 to +5) for the tree criteria (TE, TQ, TI) and the summative one, both for the actual and the previous run, in numbers and histograms In the following sheet the same results are shown for the single Nuts3 regions. Two series of graphs are also produced: for all the TIMs by single criterion (TE, TQ, TI) and sub-criterion and for the summative evaluation, and for all the PIMs by sub-­ criterion. This is particularly useful in order to compare results – analytical ones and summative – among regions and pick up outliers15 (or even to pick-up mistakes) and poor/excessive impacts at a glance. Under each graph, the interval chosen for the normalisation procedure and the form of the value function – linear or exponential – are indicated. All hypotheses and assumptions can be changed interactively – weights, intervals for normalisation, intervals of higher/lower desirability of single goals, form of the value function – and results instantaneously achieved. All results are due to be mapped directly by the same procedure.16 As a prototype implementation, the TEQUILA model was applied to a EU transportation policy, namely the ‘quick start’ priority infrastructure projects proposed inside the TEN (Trans European Networks) by Commissioner van Miert in 2003, to be completed by 2020.17 The results were presented to the ESPON Monitoring Committee in Amsterdam, in May 2006, referring to the 28 countries of the ESPON space (including Norway and Switzerland). Nine sub-criteria were chosen for impacts, 3 for each main criterion, with the same weights (1/3), namely:  The political relevance of ‘outliers’  – i.e. of excessive impacts on some aspects, population classes or regions – is made explicit by the European Commission: “When a single Member State or region is disproportionately affected (so-called ‘outlier’ impact), this should be mentioned. Where such disparities appear to be significant, they should be analysed as they may be a reason to adapt the initiative, for instance to offer mitigating or transitional measures for the ‘outlier’” (EC 2009: 41). 16  Mapping procedures directly integrated inside the computational machine were finalised only in the TIP-TAP version of the TEQUILA model. 17  The choice of this policy field was due to the existence of multiple studies, allowing a quantitative territorial assessment. Collaboration with the teams involved in these studies was gratefully acknowledged. 15

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Table 3.1  TEQUILA model, TEN policy 2000–2020: criteria for quantitative impact assessment (PIM) PIMr

PIM_E

PIM_E

PIM_E

PIM_Q

PIM_Q

PIM_Q

c

1

2

3

1

2

3

Subcriteria

Indicator

Unit of measure

Dir

.

Interval

Weight

Source of data

Dif transport endowment (road + rail)/GDP

Km / GDP

+

0 to 4

0,333

ESPON 3.2: Mcrit

External Accessibility

Dif accessibility (road/rail passenger travel)

Number of people

+

2 to 5

0,333

ESPON 1.2.1: SASI, Mcrit

Growth

Dif GDP per capita, 2000-2021

Dif % GDP/inhabitant

+

2 to 4

0,333

ESPON 2.1.1: SASI Model

Congestion

Dif-flows, baseline scenario 2015

Million Vehicles/Km

-

2 to -5

0,333

ESPON 3.2: Mcrit

Emissions

Dif CO2 emissions baseline 2015

Million Tons CO2 / Year

-

2 to -5

0,333

ESPON 3.2: Mcrit

Dif rail - Dif road, baseline scenario 2000-2015

Km - Km

+

-3 to 3

0,333

ESPON 3.2: Mcrit

Internal Connectivity

Transport sustainability

PIM_I1

Creativity

Dif accessibility* [knowledge and creative services]

(# people)*( # libraries + theatres)

+

1 to 4

0,333

ESPON 2.1.1: SASI Model

PIM_I2

Cultural heritage

Dif accessibility* [# Monuments + museums]

(# people)* (#monuments + museums)

+

1 to 4

0,333

ESPON 2.1.1: SASI Model

PIM_I3

Landscape

Dif. Transport endowment (road+rail) / GDP

Km / GDP

-

0 to -4

0,333

ESPON 3.2: Mcrit

Source: ESPON 3.2 (2006) and Camagni (2009)

• For Territorial Efficiency: internal connectivity, external accessibility, economic growth • For Territorial Quality: congestion, emissions, transport sustainability • For Territorial Identity: creativity, cultural heritage, landscape quality Indicators for impacts (PIMs) and sensitivity parameters (S, D, V) are presented in Tables 3.1 and 3.2. It is worth mentioning the treatment devoted to the relatively new identity dimension. The assumption was that new transport infrastructure would widen the accessibility to (and the ‘market’ for) regional creativity, knowledge and culture, some important elements of local identity. Therefore, two complex indicators were built: (new accessibility, measured by increased population potential) x (knowledge and creative services, measured by libraries and theatres) and (new accessibility) x

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Table 3.2  TEQUILA model, TEN policy 2000–2020: sensitivity indicators Sensitivity

Sensitivity Indicators

Unit of measure

Variatio n

Functional shape

Source of data

S_E1

D = LOG of current density of transport endowment [density=(road+rail)/GDP] R=1 S = D norm

LOG[km road+rail] / GDP

0,8 to 1,2

Linear

ESPON 3.2: Mcrit; ESPON 3.1

S_E2

D = LOG [current accessibility] R=1 S = D norm

LOG [# of people daily accessible by car]

0,8 to 1,2

Non Linear

ESPON 2.1.1: SASI Model

S_E3

D = GDP 2000 PPP per inhabitant R=1 S = D norm

GDP 2000 PPP per inhabitant]

0,9 to 1,2

Linear

ESPON 3.1, Eurostat DG Regio

S_Q1

D=Present congestion V=Share of natural areas S= mean of normalised D and V

D= Million Vehicles / network Km V= share of natural 2 areas (Km )

0,8 to 1,2

D = Non Linear

ESPON 3.2: Mcrit; BBR Corine Landcover

S_Q2

D=Present emissions V=Share of natural areas S= mean of normalised D and V

Present emissions CO2 year 2000 [million tons] V= share of 2 natural areas (Km )

0,8 to 1,2 0,9 to 1,2

D = Non Linear V = Linear

ESPON 3.2: Mcrit, BBR Corine Landcover

S_Q3

D=Present share of railways on total transport ntw. R=1 S = D norm

Km / Km (%)

0,8 to 1,2

D = Non Linear

ESPON 3.2: Mcrit

S_I1

D=GDP 2000 PPP per inhabitant R=1 S = D norm

GDP 2000 PPP per inhabitant

0,9 to 1,2

Linear

ESPON 3.1, Eurostat DG Regio

S_I2

D=GDP 2000 PPP per inhabitant R=1 S = D norm

GDP 2000 PPP per inhabitant

0,9 to 1,2

Linear

ESPON 3.1, Eurostat DG Regio

S_I3

D=1 V = Natural vulnerability (natural area fragmentation) S= V norm

Natural area fragmentation indicator 1-5: 1= very low; 5 = max fragmentation

0,9 to 1,2

Linear

ESPON 1,3,1; GTK

Source: ESPON 3.2 (2006) and Camagni (2009)

(monuments and museums). The third impact, on quality of landscape, was measured by (new km of rails and roads on GDP) x (vulnerability, measured inversely by the present landscape fragmentation). Necessarily, the indicators were proxies for the true variables, but they proved effective and the results quite convincing (for a prototype model). The four maps of the TIMs for impacts on TE, TQ, TI, and the summative one, are presented in Figs. 3.2, 3.3, 3.4 and 3.5. A bizarre result emerges as a curiosity, concerning impact of infrastructure projects on Italian territory: the negative impact

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41

Territorial Efficiency

Territorial Efficiency.shp 1.58 - 1.74 1.74 - 1.86 1.86 - 1.96 1.96 - 2.05 2.05 - 2.15 2.15 - 2.26 2.26 - 2.41 2.41 - 2.58 2.58 - 2.87 2.87 - 3.57

Fig. 3.2  TEQUILA model: impact of TEN policy 2000–2020 on territorial efficiency. (Source: ESPON 3.2 (2006) and Camagni (2009))

on territorial quality was forecasted as being much higher on the Brenner corridor (where the basic tunnel is under construction since many years with no claims) than the one on the Susa valley for the high-speed train Turin-Lyon, on which a hard political confrontation is going on since 15 years. Whom should we trust?

3.3

Subsequent Improvements and Applications

3.3.1 The TIP-TAP Project Concrete applications of the model have been implemented subsequently under two new contracts gained with ESPON: the TIP-TAP project (Territorial Impact Package for Transport and Agricultural Policies), 2008–2009, and the ARTS project (Assessing Regional and Territorial Sensitivity to European Directives), 2010–2011. The request in the former case was to provide a robust and fully operational tool for the TIA and to apply it to transport and agricultural policies; to calculate single-­ dimension impacts on single criteria like climate change, economic competitiveness, society, together with the general territorial impact; to use expert judgements for strengthening the definition of the range of scores, the form of the value functions and the weights assigned to criteria; to explore the possibility of computing

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Fig. 3.3  TEQUILA model: impact of TEN policy 2000–2020 on territorial quality. (Source: ESPON 3.2 (2006) and Camagni (2009))

Fig. 3.4  TEQUILA Model: impact of TEN policy 2000–2020 on territorial identity. (Source: ESPON 3.2 (2006) and Camagni (2009))

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Fig. 3.5  TEQUILA model: global territorial impact of TEN policy 2000–2020 (Source: ESPON 3.2 (2006) and Camagni (2009))

interregional spatial spill-overs; to consider the case of non-compensation among impacts. In fact, all these issues were left open in the prototype TEQUILA model; the demand was for a complexification of the model. On the other hand, the request in the latter case (ARTS) was for a simplification of the procedure, given the fact that the detailed, selective and often ad hoc nature of European Directives does not allow an econometric analysis of the single impacts, pushing towards the construction of complex indicators requiring experts inclusion, namely the ones presented in Eqs. (3.2) and (3.3). Concerning the TIP-TAP project, the first important request concerned an expert support in the procedural phases in which subjectivity of the model operator was high. This request was reasonable and expected, and, in the case of the definition of weights, allowed to reach interesting results. In fact, the average distribution of weights to the criteria and sub-criteria that emerged from the meetings of experts in the two sectors analysed was confronted with the one that came from answers to a direct questionnaire distributed to the many participants to the ESPON Conference in Prague, in June 2009 (encompassing policy makers, public officials, academics and practitioners). Results from almost 100 answers (presented in Table 3.3 only for the three aggregate dimensions TE, TQ, TI) showed more traditionalist attitudes on the side of experts, favouring most the efficiency dimension and relatively neglecting the novel dimension of identity, followed in the same sense by public officials; academics were more attracted by territorial quality aspects, but were also

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Table 3.3  Preferences concerning relevance of policy goals (weights) Crite ria

EXPERTS CAP

EXPERTS TEN

Policy makers EU view

TE TQ TI

58 30 12 100

47 30 23 100

45,00 30,00 25,00 100,00

National view 42,50 33,75 23,75 100,00

Public officials EU view 49,16 31,31 19,52 100,00

National view 46,66 33,81 19,52 100,00

Academics EU view 39,75 36,75 23,50 100,00

National view 36,50 38,00 25,50 100,00

Practitioners EU view 39,00 34,00 26,86 100,00

National view 39,00 34,00 26,86 100,00

Source: Own elaboration

interested in the identitarian ones; policy makers, to my surprise, were relatively the group most attracted by the identity dimension, together with practitioners,18 anyway putting efficiency at the first place. Concerning the third request, namely the possibility of including spatial spill-­ over effects into the model, much depends on which spill-over to consider. Economic spill-overs are easy to estimate and to include. The example comes from another model that the group of spatial economists of the Politecnico di Milano developed for the same client, the ESPON program, in the same years: the MASST model, a Macroeconomic, Sectoral, Social and Territorial forecasting model for EU regions producing ‘quantitative conditional foresights’ on the basis of consistent scenarios in the medium term (15 years). In the first draft of the model (Capello et al. 2008) GDP spill-overs growth were estimated on the basis of a gravitational potential, while in the most recent draft (MASST-4) also interregional input-output exchanges are considered (Capello and Caragliu 2019). Spill-overs on the labour markets are also measurable through commuting statistics. In the environmental fields, estimating spill-overs would be more difficult and expensive, but some interregional flows can in principle be computed for water (rivers and underground water) and perhaps for dominant winds. In the TIP-TAP version of the TEQUILA model the single criteria on which impacts are computed are, respectively, for the two policies: (a) For CAP: Economic growth (E1), Unemployment (E2), Tourism diversification E3), Environmental quality (Q1), Community viability (Q2), Emissions (Q3), Risk of soil erosion (Q4), Landscape diversity (I1), Community identity (I2), Heritage products (I3) (b) For TRANSPORT: Productivity of inland infrastructure (E1), Productivity of airports (E2), Economic growth (E3), Congestion costs (E4), Traffic passing through (Q1), Emissions (Q2), Safety (Q3), Market opportunities (Q4), Landscape fragmentation (I1), Exposure to external visitors (I2), Regional integration (I3) The assessment was made in quantitative terms – necessary in the presence of such a huge number of regions  – using external econometric ad hoc studies or

 Ten years ago the identitarian issue was not so politically clear as today; policy makers, academics and practitioners proved to be closer to people’s feelings than public officers and experts.

18

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complex indicators, in spite of the difficulties coming from lack of data, especially in the case of CAP policies. In this last case, the impact assessment study was able to indicate that reductions in public resource distribution (as the ones imposed to countries with the re-­ modulation between the two Pillars of the CAP) may end up not only in income reductions and land abandonment by weaker farms, but also in homologation of landscapes and reduction of their diversification, risks of soil erosion and reduction of community viability if alternative job opportunities are not available in the regions. Positive impacts are likely to come from tourism diversification of agricultural activities, calculated by an indicator merging present tourist ‘vocation’ and expected increase in unemployment (Fig. 3.6). In the case of transport policies, three scenarios were built: a ‘baseline’ scenario at 2030, encompassing all investments which were being carried out in 2008 or already decided (scenario a); an ‘infrastructure’ scenario, encompassing new infrastructure links under discussion or already decided at the national level (scenario b); and a ‘pricing’ scenario, encompassing new regulatory tools such as rules on safety and road pricing with respect to the baseline scenario (scenario c). In the baseline scenario, increased congestion was pervasively found throughout the territory and particularly in large northern metropolitan areas: ongoing infrastructure looked insufficient to accommodate new forecasted mobility. However, congestion was due to reduce, especially in eastern countries, according to the second scenario and even more according to the pricing scenario, especially in most congested areas (Fig. 3.7). In the case of transport policies, a new device was introduced in the TEQUILA model in order to take care of the problem of compensation of impacts. Among the available ways and methods to handle this issue, the one proposed by Nijkamp and Ouwersloot (1997) with the ‘Flag’ model was chosen. When impacts on some crucial societal goal/criterion – generally concerning environmental matters like emissions, congestion or safety – overcome some shared or legal thresholds, valid for the entire EU territory or for some typologies of regions, the model indicates a ‘flag’ on the concerned map and compensation of impacts in summative evaluations is stopped. In the case of emissions, a double threshold is proposed: an increase in emissions by 2030 with respect to the 2008 condition and an initial level of emissions higher than the European average (28 + 4 countries). Three flag colours are used – yellow, orange and red – according to percentage of threshold overcoming: up to +50%, +50 to +100% and higher. The relative maps, utilised also by the Commission in its 2012 Cohesion Report, are shown here (Fig. 3.8). The enhanced infrastructure scenario (b) allows to reduce considerably the high level of emissions emerging in the baseline scenario, and the ‘pricing’ scenario (c) would be virtually able to solve the problem.

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Fig. 3.6  Impact of expected tourism diversification of agricultural activities. (Source: ESPON 2009)

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Fig. 3.7  Expected congestion costs according to the ‘pricing’, regulatory scenario. (Source: ESPON 2009)

3.3.2 The ARTS Project The ARTS project (2010–2011), implemented through an enlarged international team directed by Austrian Institute for Regional Studies and Spatial Planning, Vienna (OIR), responded to the need to assess the territorial impact of EU Directives. Given the strong specificity and diversity of each of them, the challenge was in this

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a. Baseline scenario

b. Enhanced infrastructure scenario c. Regulatory “pricing” scenario

Fig. 3.8  Expected emission levels overcoming compensation possibility thresholds. (a) Baseline scenario (b) Enhanced infrastructure scenario (c) Regulatory ‘pricing’ scenario. (Source: ESPON 2009)

case twofold: an accurate definition of the logical chain from goals and text regulations to impacts and the consequent simplified but consistent methodology based necessarily on the construction of complex indicators, quantitative but widely based on experts judgement (models (2) and (3)). 12 Directives and 41 exposure fields were chosen, and were approved by the ESPON Managing Authority.19 Methodological definitions of the core concepts are rooted in the vulnerability concept developed by the IPCC, the Intergovernmental Panel on Climate Change, and broadly discussed in the impact assessments in natural sciences, especially concerning climate change; these concepts are as follows: • Field Exposure describes the intensity by which EU directives and policies involve particular ‘fields’ of the territorial realm (e.g. surface water quality, emissions, sectoral production). • Regional Exposure defines the particular typologies of regions potentially affected by the Directives. • Sensitivity describes how single territories/regions are sensitive to, or evaluate, impacts in specific exposure fields, due to their socio-economic and geographical characteristics and to the social values and priorities they are likely to show (with no reference to specific directives). • Territorial Impact is the potential effect (in the future) of a given EU directive or policy as a consequence of field exposure, regional exposure and regional sensitivity. The impact can be direct or indirect along specific cause-and-effect logical chains.

19

 Exposure fields are in a fixed number, but each directive activates only some of them.

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Fig. 3.9  The territorial impact matrix. (Source: Espon ARTS (2011))

Operationally, these concepts correspond directly to the ones proposed in the original TEQUILA model (respectively: Potential Impact – PIM c; Policy Intensity – PI r; Sensitivity – S r,c); they are better suited for this analysis and allow an easier interaction with the environmental culture. The synthetic scheme of the methodology is shown in Fig. 3.9; the list of Exposure Fields and their relative indicators in the Sensitivity Matrix is shown in (Table 3.4).

3.4

 ain Results, Strengths and Weaknesses, M and Future Prospects

In synthesis, the TEQUILA model introduces itself as a tailor-made version of a consolidated methodology, namely Multi-Criteria Analysis (MCA) in its simplest form, able to build in both an analytical and synthetic (‘summative’) form an ex ante territorial impact assessment of EU policies, programs, measures and integrated projects on European regions. Its flexibility, simplicity and transparency allow a utilisation for differentiated policies, utilising at best the present availability of quantitative policy assessment studies in specific fields at the European scale and integrating in a consistent way, when necessary, some ad hoc qualitative expert judgements. By the time it was created, TEQUILA model constituted a pioneering effort, as no such methodology existed. It requires, to be honest, some fantasy in order to devise quantitative indicators, especially for the immaterial and quality dimensions of the territorial realm. The aggregation of single impacts on the three constituents of TC, namely ‘Territorial Efficiency – Quality – Identity’, looks scientifically appropriate but is not intended to be compulsory: a more traditional

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Table 3.4  Exposure fields and sensitivity indicators in the Espon ARTS project Area

Fields

Indicators

Source

Soil

erosion

% areas at risk of soil erosion

CLC

pollutants in soil

(pop+empl)/ usable land

ESPON

share of artificial areas/soil sealing

% artificial area

CLC

water consumption

% inland water

ESPON on CLC

pollutants in ground/surface water

(pop+empl)/ usable land

ESPON

Air

pollutants in air

concentration of PM10

5th Cohesion Report

Climatic factors

emissions of CO2

((vehicles per 1000 inhab) + (popul.dens.))/2

EUROSTAT+E SPON

heavy rain/flood hazard/occurrence of landslides

risk of flood hazard

ESPON

Fauna/Flora/ Habitat

biodiversity

areas in Natura 2000

Univ. of Natural Resources and Life Sciences, Vienna

Landscape and cultural heritage

conservation of natural heritage (landscape diversity)

% natural areas

DG Agriculture – Rural Devel. Report

conservation of cultural heritage

n° of TCI 3-stars

ESPON ATTREG Projec

economic growth (GDP/capita)

GDP per capita

ESPON

innovation

Share of product &/or process innovation

ESPON

entrepreneurship

% self employment

EUROSTAT

market barriers

1

employment in primary sector

GDP per capita

ESPON

% of arable area, permanent grass area, permanent crops area

% agricultural areas

ESPON on CLC

Industry

employment in secondary sector

Share of empl. in secondary sector on total empl.

EUROSTAT

Services

employment in tertiary sector

Share of empl. in tertiary sector on total employment

Tourism

overnight stays

nights on population

EUROSTAT+ ESPON

Social disparities

disposable income in PPS per capita

disposable income p/capita

ESPON

equal income distribution

poverty index

5th Cohesion Report

employment rate

unemployment rate

5th Cohesion Report

Demography

out-migration/brain drain/"shrinking regions”

net migration balance

5th Cohesion Report

Health

number of people exposed to noise

% population in urban areas

CLC

accident rate in transport

road fatalities

5th Cohesion Report

accident risk: industry/energy supply

technological &/or environmental risk

ESPON

healthy life expectancy at birth

life expectancy at birth

EUROSTAT

daily accessibility by air

potential accessibility by air

ESPON Data Base

daily accessibility by waterways

1

daily accessibility by road

potential accessibility by road

ESPON Data Base

daily accessibility by rail

potential accessibility by rail

ESPON Data Base

renewable energy

vulnerability to climate change

5th Cohesion Report

fossil fuel consumption

vulnerability to climate change

5th Cohesion Report

increase of urbanization relative to population growth

% discontinuous urban fabric

ESPON on CLC

mixed land use

1

efficiency of government/ governance mechanisms

1

duration or complexity of planning procedures

1

participation rate

1

societal transfers (e.g. tax added)

1

transnational cooperation between member states

INTERREG IIIa expenditure per capita

Natural environment

Water

Economy

Economic development

Agriculture

Society and people

Accessibility

Built environment

Governance

Source: own elaboration

EUROSTAT

EUROSTAT

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aggregation on the economic, environmental, cultural and social dimensions can be easily implemented in case the triad might look too ‘creative’. TEQUILA is particularly designed and equipped for comparative analyses and assessments of impacts of policy interventions, when the interest of administrations – from the European to the regional – is to have a picture at a glance on relative impacts, both specific and summative, on a wide array of regions. On the other hand, it is not particularly useful in the assessment of the impact of single projects on single regions. Especially in case of territorialised assessments with a national and European view, the quantitative response of the TEQUILA model, based on econometric or dynamic simulation tools and on complex statistical indicators, looks crucial. Qualitative studies could be the best solution when evaluation concerns single or a few areas, not for sure when it concerns more than one thousand NUTs3 European regions: the consistency of results in single fields for so many areas (e.g. competitiveness or quality of life) would be questionable and making an overall assessment almost impossible. For the future, it is possible to pinpoint some conditions for a proper and sound utilisation of any ex ante, quantitative TIA model for policy assessment: • Policy measures to be inspected should be clearly and carefully defined. • Policy intensity in each region should be also precisely defined, as it constitutes the logical starting point of any elaboration.20 • A wider array of quantitative studies (with econometric models, simulation models, impact models) concerning forecasts and impacts in specific fields should be made available, at least for some crucial typologies of impacts (environmental, economic, social, …). • A wider array of statistical data on regional conditions in fields that represent main policy goals should be produced by statistical institutions at different spatial scales – e.g. poverty, underground water quality, emissions, etc., − in order to be able to estimate econometrically territorial sensitivity and elasticities to alternative policy strategies. • The extension of regional accounts and statistics to the sub-regional level of metro-areas. Looking back to the historical trajectory of the TIA program, a last reflection emerges. The program was launched in a period of fast and profound institutional change (the Euro, the enlargement to new CEECs, the new Treaties), deep economic transformation (the rise of globalisation, the emergence of the knowledge society, new global confrontations) and important scientific and political debates on the role of territories, cities and special areas. The spatial and territorial perspective in European policies was pervasive. However, starting from the beginning of the second decade of the present century, territorial attention in the policy discourse  This condition was not met in case of our assessment of CAP policy, due to the national responsibility on inter-regional resource allocation.

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became negligible, and even disappeared. In the present European policy lexicon, terms and concepts like TC, or territorial capital, can hardly be heard. The Report Europe 2020 (EC 2010) did not mention the territorial dimension at all, with the sole exception of poverty policies. Most recent policy documents, like the Junker Report (EC 2015a), the Dombrovskis-Moscovici-Thyssen Report on “A deeper and fairer economic and monetary Union” (EC 2015b) or the last Commission Contribution on the Spring Semester EC, 2019), all take up a macroeconomic and institutional approach, speaking about general goals, values and rules, crucial in many ways but detached from the day-to-day realm of people’s life, concerns and expectations. Forgetting about the territorial dimension may imply the risk of losing touch with the emerging new “geography of discontent” (Rodriguez-Pose 2017), at the basis of many present anti-European attitudes. Hopefully, regional development policies are still existing, and they still require sound and innovative assessment tools.

References Beinot E, Nijkamp P (eds) (2007) Multi-criteria analysis for land-use management. Springer Verlag, Berlin Camagni R (1998) Sustainable urban development: definition and reasons for a research programme. Int J Environ Pollut 1:6–26 Camagni R (1999) The city as a milieu: applying GREMI’s approach to urban evolution. Revue d’Economie Régionale et Urbaine 3:591–606 Camagni R (2002) On the concept of territorial competitiveness: sound or misleading? Urban Stud 13:2395–2412 Camagni R (2006) Territorial Impact Assessment  – TIA: a methodological proposal, Scienze Regionali. Italian J Reg Sci 5(2):135–146. Republished in: Capello R. (ed.) (2017) Camagni R (2009) Territorial impact assessment for European regions; a methodological proposal and an application to EU transport policy. Eval Program Plann 32:342–350 Camagni R (2019) Territorial capital and regional development: theoretical insights and appropriate policies. In: Capello R, Nijkamp P (eds) Handbook of regional growth and development theories, 2nd edn. Edward Elgar, Cheltenham, pp 124–148 Capello R (ed) (2017) Seminal studies in regional and urban economics: contributions from an impressive mind. Springer, Berlin Capello R (2018) Cohesion policies and the creation of a European identity: the role of territorial identity. J Common Mark Stud 56(3):489–505 Capello R (2019) Interpreting and understanding territorial identity. Reg Sci Policy Pract 11(1):141–158 Capello R, Camagni R, Fratesi U, Chizzolini B (2008) Modelling regional scenarios for an enlarged Europe. Springer Verlag, Berlin Capello R, Caragliu A (2019) Merging macroeconomic and territorial determinants of regional growth; the MASST4 model. Paper presented at the 59th ERSA Conference, Lyon, 27–31 August Cerisola S (2019) Cultural heritage, creativity and economic development. Edward Elgar, Cheltenham CMSP  – Council of Ministers responsible for Spatial Planning (1998) European Spatial Development Perspective (ESDP). Presented at the Ministerial Meeting in Glasgow, Brussels DCLG – Department for Communities and Local Government (2009) Multi-criteria analysis: a manual. London EC – European Commission (1999) European Spatial Development Perspective (ESDP). Brussels

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EC – European Commission (2002) Impact assessment (COM (2002) 276). Communication from the Commission, Brussels EC  – European Commission (2004a) Impact assessment: next steps (SEC (2004) 1377). Commission Staff Working Paper, Brussels EC – European Commission (2004b) A new partnership for cohesion, third report on economic and social cohesion, Brussels EC – European Commission (2004c) Interim territorial cohesion report. Brussels. June EC – European Commission (2005) Impact assessment guidelines (SEC (2005) 791). Brussels, June EC  – European Commission (2009) Impact Assessment Guidelines, (SEC(2009)92). Brussels. January EC – European Commission (2010) Europe 2020, Brussels EC  – European Commission (2015a) Completing Europe’s Economic and Monetary Union, Junker Report, Brussels, June EC – European Commission (2015b) “10 Commission Priorities for 2015–19”, Dombrovskis – Moscovici – Thyssen Report, Brussels, October EC  – European Commission (2019) Commission Contribution to the European Council on European Semester. Brussels, Spring Eggenberger M, Partidario MR (2000) Development of a framework to assist the integration of environmental, social and economic issues in spatial planning, in Impact Assessment and Project Appraisal, September, 18:3 ESPON - European Spatial Planning Observation Network (2006) Spatial Scenarios and Orientations in relation to the ESDP and Cohesion Policy, Lead Partner IGEAT, Brussels; Final Report, Vol. 5, “Territorial Impact Assessment (TIA)”, Politecnico di Milano, Dept. DIG, director R. Camagni ESPON - European Spatial Planning Observation Network (2009) TIP-TAP - Territorial Impact Package for Transport and Agricultural Policies, Lead Partner Politecnico di Milano, Dept. BEST, director R. Camagni ESPON - European Spatial Planning Observation Network (2011) ARTS - Assessment of Regional and Territorial Sensitivity to European Directives, Lead Partner OIR, Vienna; Final Scientific Report, Chapter 3, “Tha Analytical Approach”, Politecnico di Milano, Dept. BEST, director R. Camagni Luxembourg Presidency (2005) Scoping document and summary of political messages for an assessment of the territorial state and perspectives of the European Union: towards a stronger European territorial cohesion in the light of the Lisbon and Gothenburg ambitions, Luxembourg, May Munda G (1995) Multicriteria evaluation in a fuzzy environment; theory and application in ecological economics. Physika Verlag, Heidelberg OECD (2005) Handbook on constructing composite indicators: methodology and user guide, OECD statistics working paper, STD/DOC(2005)3. Paris Nardini A (1997) A proposal for integrating environmental impact assessment, cost benefit analysis and multicriteria analysis in decision making. Project Appraisal, Sept Nijkamp P, Ouwersloot H (1997) A decision support system in regional sustainable development. In: van den Bergh JCJM, Hofkes MW (eds) The flag model, theory and implementation of sustainable development modelling. Kluwer Academic Publisher, Dordrecht, pp 255–273 Nijkamp P, Rietveld P, Voogd H (eds) (1990) Multicriteria evaluation in physical planning. North Holland Publ, Amsterdam Putnam RD (1993) Making democracy work. Princeton University Press, Princeton Rodriguez-Pose A (2017) The revenge of places that don’t matter(and what to do about it). Camb J Reg Econ Soc 11(1):189–209 Scriven M (1994) The Final Synthesis, Evaluation Practice, 15(3):367–382 Thérivel R, Partidario MR (eds) (1996) The practice of strategic environmental assessment. Earthscan Pub. Ltd, London

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Williams R, Connolly P, Healey A (2000) Territorial impact assessment: a scoping study, Final Draft Submission to the Committee on Spatial Development, CREUE-Newcastle and ECOTEC, mimeo World Bank (2001) Understanding and measuring social capital: a synthesis of findings and recommendations from the social capital initiative, Social Capital Initiative Working Paper n. 24, April, Washington, DC Roberto Camagni  is Emeritus Professor of Politecnico di Milano where he taught Urban Economics and Assessment of urban transformations; is President of the Research Unit on Regional and Urban Economics of Politecnico. Served as Head of the Department for Urban Affairs at the Presidency of the Council of Ministers, Rome, under the Prodi Government, 1997–1998, and was Vice-president of the Group on Urban Affairs of OECD, Paris, 1998. Past President of the European Regional Science Association-ERSA (2003–2005) and of the Italian Regional Science Association–AISRe (1990–1993). He is the author of more than 150 international scientific publications and more than 150 national publications; has published a textbook of Urban Economics in Italian (1992), French (1996) and Spanish (2005). Has worked for DG Regio of the European Commission, OECD, DATAR (the French national Agency for spatial planning), the Italian Ministries of Public Works and of European Affairs, the ESPON project of the EU and for many Italian and European Regional Governments in the fields of innovation diffusion, strategic planning, regional forecasting modelling and territorial impact assessment. In 2017 was elected Fellow of the Regional Science Association International. In 2010 was awarded the Prize of the ERSA/European Investment Bank and in 2008 the Prize of the Fondazione Confalonieri, Milan, for his studies in urban sustainable development.

4

STeMA: A Sustainable Territorial Economic/Environmental Management Approach Maria Prezioso

Abstract

The STeMA-TIA model has been devised to support an integrated strategic vision of general, territorialised and sectoral policies at all decision-making levels. This assessment tool was created within the context of spatial planning and as part of the territorial dimension of the European Strategies. STeMA-TIA is based on an original qualitative-quantitative methodological approach comprising 10 simplifying hypotheses and 9 logical steps. It develops along interactive coaxial matrices (indicators-policies-effects), which return ex ante and ex post results and maps. It was fruitfully applied to the Territorial Dimension within the Lisbon/Gothenburg Strategy, the Territorial Cohesion Policy, and National and Regional Operative Plans 2020, as well as to Italian structural reforms at the metropolitan and regional level. The strength of this tool lies in its flexibility and ability to combine different indicators related to economic, social, environmental, cultural, organisational and financial dimensions, which assess Territorial Impact Assessment in relation to original Systemic Territorial Functional Typologies. One existing weakness of STeMA-TIA is that, during a pairwise comparison process, identifying indicators such as ‘dominant’ and ‘secondary’ may not always be straightforward. Further developments and applications may help overcome this limitation. Future applications of STeMA-TIA include using it to measure Territorial Cohesion within green economy policies at the national-­ regional level or to evaluate the post-2020 Europe strategy, cultural heritage and tourist strategies via Innovative Technologies and within Smart Specialisation Strategy.

M. Prezioso (*) Department of Management and Law, University of Rome “Tor Vergata”, Rome, Italy e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_4

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Keywords

Territorial impact assessment · STeMA · European sustainable policies

4.1

Historical Background, Main Goals and Application

The STeMA-TIA tool has been devised to make the existing Sustainable Territorial environmental/economic Management Approach (STeMA) applicable to policy/ decision-making.1 It is the result of extensive research that has been carried out over the last 35 years in the areas of economic and political geography and spatial (and territorial) planning. It seeks to create and integrate territorial governance at the European, cross-broader, national and local levels. STeMA-TIA has been conceived as a support methodology that helps policymakers make sustainable choices. It is a multilevel framework that works bidirectionally, since it can receive top-down and bottom-up inputs. Consequently, it is perfectly suitable for drafting cutting-edge sustainable programs, planning and projects, which can subsequently be refined using existing and related tools such as STeMA–SEA (Strategic Environmental Assessment) and STeMA–EIA (Environmental Impact Assessment). STeMA-TIA is based on a multidisciplinary approach that combines Von Bertanlaffy’s (1969) General Theory of Systems and Saaty’s (1977, 1980, 1990) Analytical Hierarchy Process (cf. also Saaty et al. 1983; Saaty and Kearns 1985). It additionally draws on assessment tools for territorial and environmental systems (Malcevschi 1986) as well as macroeconomic models based on the interrelation and interdependence among economic and environmental variables (cf. Georgescu-­ Roegen 1971, 1977 on the input-output model as applied to integrated open/closed circles, etc.). In addition, it relies on microeconomic models, stemming from marginal analysis, that seek to create territorial assessment techniques based on non-­ monetary principles. The STeMA-TIA methodology uses techniques and processes relating to the selection and correlation of indexes, impacts and effects (Adkins and Burke 1971; Leopold et al. 1971; Warner and Preston 1974; Falque 1975). It draws on studies that attempt to establish an adequate level of interaction among the many factors that come into play during decision-making and political processes, which are based on the relationship between socioeconomic and ecological growth (Vernasdky 1945). Finally, it takes into account research on the concept of Resilience when calculating unstable equilibrium, Chaos Theory to determine the sensitivity of a system to initial conditions, Fractal Theory (Mandelbrot 1975) and the analysis of similar phenomena at different levels.

1  STeMA-TIA is a copyrighted tool owned by Maria Prezioso © (all rights reserved); copyright no. 0602007/2006.

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Likewise, the STeMA model relies on systemic and qualitative research designed to support decision-making (Prezioso 1995, 2010), which has previously resulted in studies that include the preliminary assessment of territorial systems and subsystems. These studies contain policy indicators and actions (cf. for instance, the interpretation of NUTS, which has been applied to various levels, such as functional systemic territorial typologies, relational structuring processes, etc.). STeMA also helps policymakers select and subsume indicators according to clusters related to policy usage; it enables them to categorise policy assessment processes according to their scope and the evaluation of the effects connected to policy choices; finally, it detects and measures impacts to determine which are the most appropriate policies for each territory. In addition, research on policy indicators (Prezioso 1990, 2006, 2008) has proven the need to include them in a detailed examination of the structure and dynamics of territorial and non-spatial systems, prior to decision-making. The STeMA-TIA GIS (Prezioso 2006; Prezioso and Ottaviani 2009) tool has been created to this end; it helps users to manage georeferenced information regarding indicators,2 policy effects and their impact. Figure 4.1 shows a ‘logical tree’ (Bereano 1972) according to which indicators are georeferenced, organised and correlated via progressive indexicality. They are directly linked to the geographical scale and political actions under review, including: (1) the local level (municipal, metropolitan and provincial scale; cf. the left-­ hand column regarding ‘indicators’ and ‘categories’); (2) the regional and national level (clustered under the ‘sector’ and ‘typology’ column); and (3) the European level (reporting the results of the assessed policy; cf. the right-hand column). This well-structured process makes it possible to detect and redistribute all selected indicators according to thematic policy clusters and their representing groups, which may be geographical, social, economic, environmental, cultural or financial. The analysis takes into account different levels3 so that they can be framed within the TIA context. The indicators (and related metadata) are used to interpret evidence (i.e. assessment process) and detect phenomena (according to their ‘recognizability’). STeMA-TIA considers the indicators pertaining to all the levels under scrutiny and examines how important each level is. The criteria according to which each level is ranked in importance have been established by looking at those factors that enable interaction among indicators. This means that indicators may weight4 differently on different TIA geographical, political and administrative scales. Policies are

 Indicators are seen as messengers/receptors of the impact at different policy levels.  Drawing on the AHP technique, each level is determined by three weighting criteria: absolute, distributive and ideal mode (Saaty and Vargas 1993). 4  WIx refers to the weight of the indicator I, which depends on the position or capacity of I to apply a given policy and its contents, as per its determinant D (e.g. smart growth in the Europe 2020 Strategy). During policy assessment, the weight can show how important the objectives and actions must be in order to reach a given target. The Impact can also be defined according to its intrinsic and specific weight. 2 3

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Fig. 4.1  An example of a logical tree applied to the Smart Growth policy built according to the STeMA-TIA indicators. (Source: Prezioso and Coronato, in Prezioso, 2019a p. 23)

tackled in a similar fashion, but the weighting criteria differ because they include algebra (geometric, arithmetic, quadratic, quantile, quartile mean, etc.), experimental inputs, econometric analysis (i.e. economic evaluation of territorial value or usage), subjective and experts’ evaluations (cf. the Delphi methodology and the Battelle-Columbus Model; Duke et  al. 1977), and evaluation of preferences and sensitivity. This makes it possible to devise (territorial) quality function curves that help to measure each weighting level on a quality scale5 (quality being an intrinsic part of the policy and territorial index under scrutiny), which is further normalised to achieve the objectives set by the policy. Indeed, such a methodology can be applied to any generic, detectable and comparable indicator and to any further indexing this indicator is part of, or else to any analysis that attempts to determine the importance of each policy domain that includes this indicator as one of its territorial receptors. Considering the quality variation index between 0 and 1 to calculate value (Mueller 1970) has helped to understand the importance of such a value in relation to the indicators under review.

5  The quality of each indicator refers to its initial state, which can be incremented due to the impact of a policy during a TIA process.

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During a TIA, it will therefore be possible to determine how potentially positive a policy decision may be in relation to specific policy needs. STeMA-TIA combines existing theories to compare the values of the indicators that have been distributed according to the quartile methods on the ordinal scales (i.e. A >  B  >  C ...). The pairwise comparison (cf. Fig…4.3) assigns a ‘level of importance’ to each indicator in relation to other indicators.6 Thanks to the progressive indexing process mentioned above, it can be determined to which related geographical scales an indicator belongs (NUTS). Between 1995 and 2003, several studies attempted to further investigate and determine concepts such as ex ante sensitivity,7 which is a composite synthetic territorial value. They also tried to gather results on the analyses aiming at determining qualitative and quantitative geographical features. These studies also attempted to assess impacts by specifically determining their weight, gravity and effects. They devised methods to forecast phenomena linked to the concepts of identity, permanence and geography and allow for ex ante and ex post comparisons (i.e. simulations to support decision-making). Between 1995 and 2006, determining the weight of each indicator, effect, impact and policy proved to be an extremely challenging endeavour, which could be divided into five different strands: • Analysis of preferences, which measures what decision-makers are most likely to choose so that pre-set criteria and judging parameters can be linked together. • Behavioural analysis, which entails the study of policymakers’ reactions during similar decision-making processes. Using Revealed Preference Theory, this approach can be applied to repeated and standardised actions such as policies that require well-defined weighting and preference (i.e. sensitivity). • Direct description of measuring features (i.e. weights) of selected indicators. This has proven to be very useful in studying the indicators and determinants used during the STeMA-TIA ex ante stage. • Indirect description of indicators and objectives (i.e. expected policies); this helps to determine the weighting of results that will have a key role during the Impact Assessment procedure. This approach was used to determine the STeMA metadata. • Hypothetical priority, or analysis, which entails a qualitative investigation of value judgements and stakeholders’ perspectives to classify indicators. It may be ordered according to decreasing or increasing values and assessing parameters based on political, economic, social, cultural, environmental and sectoral factors. By comparing these diverse approaches from an operative standpoint, considering both the territory and policy choices, it has been possible to investigate recurrent patterns and reduce any uncertainty deriving from asymmetrical information, or 6  In order to make them verifiable, all values have been normalised according to a 0–1 scale, which makes quantitative weighting possible. 7  Also known as the capacity of a system to maintain/reacquire balanced positions.

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lack thereof, regarding the scope and indicators under review. This further investigation process has been divided into three main stages: • Analysing the territorial basis upon which to carry out the assessment and assign an ex ante related position. This work has been recently updated by adding new Systemic and Functional Typologies while applying the STeMA-TIA to Territorial Cohesion (Prezioso 2018). • Determining the final value of territorial quality for each policy alternative. • Choosing the best solutions of adaptive policy to minimise impact (interpretative local solutions on the NUTS scale). Further contributions to the creation of the STeMA-TIA have derived from studies on matrix interactions. Drawing on a series of experimental methodologies concerning applied management that were developed in 1972 by the Central New York Regional Planning and Development Board, it has been possible to establish a close relationship among all three dimensions of TIA (i.e. indicators/receptors, effects and policies). This has helped to determine the impact of such dimensions on the many levels of the geographic decision scale (including indicators, categories, sectors, typologies and the determinants mentioned above). The STeMA-TIA methodology has also been improved thanks to non-neutral studies that have underlined the existence of ‘first nature’ advantages (e.g. climate, natural resources, geographic location). These studies are considered sufficiently objective because they lead to settlement, social, environmental and productive policies resulting in successful outcomes. ‘Second nature’ advantages, by contrast, are those advantages that cannot be created by forcing the ‘sustainability paradox’ (cf. Sect. 4.2 below). Specific modelling considerations aside, policy supply and demand are bound to come together to create planning activities that will be hopefully balanced. By using the STeMA-TIA GIS tool and relying on the existing studies, it has been possible to acquire statistical historical data from reliable sources. These data have been shown to be essential for spatial assessment, although not equally important for territorial evaluation. Rather than relying on a structured but mechanical approach (Roy 1996), administrative and geographic systems (such as NUTS and TSFT) have preferred new approaches based on place evidence for territorial analysis and policy evaluation. In other words, each territory has been examined according to morphological and physical criteria, as well as its general socioeconomic relations.

4.2

The Analytical Process

STeMA-TIA has been designed to create an alternative model to existing theories that are based on approaches that do not consider how diversified a space may be and merely look at how cost-effective an investment is. STeMA-TIA consists of 10 hypotheses that can be easily conveyed to students and end-users. As simple as it

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may appear, STeMA-TIA has been devised via complex procedures that make it operationally applicable to its related STeMA-TIA GIS tool. Each territorial phenomenon and, consequently, each effect that a policy produces can also be seen as a system, meaning that such a system is a set of elements that are subject to one or more ordering rules or criteria, whether they share common characteristics or not. Hence, the first simplifying hypothesis of STeMA postulates that a territory is to be seen as an ‘artificial system’ that includes biotic and abiotic composing elements. Consequently, a system includes systems and subsystems, such as society, politics, environment and the economy. The second simplifying hypothesis follows suit as it implies that politics, society, environment and the economy are all part of a single system, which is the territory itself. Therefore, a territorial system can be investigated individually or in relation to the system of policies that governs it. Drawing on Georgescu-Roegen (1971, 1977), a territory can be studied as a closed circle, according to its own administrative, political, cultural, physical, scientific and field-related boundaries; alternatively, it can be examined as an open circle which interacts with other systems that are all interdependent. The territorial system is consequently analysed according to the administrative and sectoral criteria that define it (i.e. a region is defined as such according to well-established criteria). It can also be analysed with regard to the way it interacts with other entities (e.g. how it cooperates with another region) or in light of the interdependence of existing policies. This approach leads to the conceptualisation of the third simplifying hypothesis. The system remains a synthesis of the behaviour and general state of biotic and abiotic elements composing it, regardless of whether one uses a close- or open-­ oriented approach to examine it. In other words, a territorial system is unique and differs from all the others (the fourth simplifying hypothesis or ‘hypothesis of geographical diversity’). Nonetheless, the policies to be assessed for each territory remain the same, since they are the reason why a territory is under scrutiny in the first place. In order to assess a territorial system, it is important to understand which process links all the elements that shape it (e.g. by using the TIA logical tree and attempting to determine an ex-ante or preliminary value). In addition, one needs to measure the status or criticality value of all those elements (i.e. indicators and indexes) that are representative of its weight and quality (the fifth simplifying hypothesis). If t0 is used to define the historical moment in which the TIA process is initiated (i.e. ex ante), the territory will be investigated as being partially balanced at that time. Furthermore, its distinguishing features will be seen as the result of existing (historical and political) processes that have determined the initial configuration of the system, which can be measured and assessed (the sixth simplifying hypothesis) even when the policies have not been implemented. This initial configuration is called Initial Territorial Value (ITV). Every system can be broken down into sublevels (cf. for instance the NUTS 0, 1, 2...) and analysed according to the criteria of territorialisation mentioned above. Each sublevel corresponds to a geographic scale and it can be examined as per indicators and indexes that can subsequently be compared to other indicators (the

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seventh simplifying hypothesis). Every system or subsystem is subject to internal and external inputs that have been introduced by policies seeking change. In applying a TIA procedure, the system will change its initial balanced position but will remain within the limits that the indicators have established to cope with the changes that the applied policy has enacted. By doing so, these indicators become active ‘receptors’ (cf. note 2 above) of impact.8 During the analysis of the way the policy under scrutiny has been received, the impact may be defined as positive (+), neutral (0), or negative (−). A neutral or negative response in terms of impact can limit the acceptable development potential of the system regarding the time and ways this will happen (the eighth simplifying hypothesis or ‘sustainability paradox’). The acceptable development potential is called the threshold of sustainability of a territorial system (the ninth simplifying hypothesis), and it stems from the initial sustainability (or sensitivity) of the system. The name of the final configuration is Final Territorial Value (FTV) and it simulates the existing scenario during a given t1 and TIA procedure. The term carrying capacity (∂) is used to define the difference between the initial balance of the system (ITV) and the final tolerance threshold (FTV), or sustainability, of the territorial system (the tenth simplifying hypothesis). This capacity describes how supply meets demand, as established by a given policy; it implies that a new partial balance is likely to result from the continuous growth and improvement of the territory. This is possible if the most appropriate policies are chosen to this end. Starting an operational procedure (i.e. the 9 steps in Fig. 4.2) requires the following preliminary actions: 1. Creating functional and well-defined typologies (at the national, regional, sub-­ regional level, etc.) that help shape a Territorial Reference Framework, which can in turn be used to georeference all estimated indicators. These typologies can trigger the STeMA-TIA procedure to provide a broad territorial assessment, rather than just a partial one. 2. Analysing each ‘closed circle’ determining system (e.g. the 2020 strategy seeks to achieve smart, sustainable and inclusive growth, as well as the costs of the cohesion policy and its related objectives), which are in turn divided into typologies, sectors, categories and indicators. All determining systems are included in the Territorial Reference Framework as if they were trees, whose roots are represented by their basic indicators. After indexing these indicators via a cross-check approach (including indicators, categories, typologies etc.), it will be possible to obtain a spatial and territorial VTId for each system determinant. Each determinant can interact with other determinants (in an open circle) to obtain the total IVT (or complex synthetic index) for a given territory (which is also its ex ante sensibility). The final IVT is determined by combining state and process. 3. Creating a Planning and Policy Framework that can include the proposals and actions deriving from the objectives the TIA process has been initiated for (e.g. 8  The term ‘impact’ here is used to describe the moment a given aspect is modified, due to the contact between an indicator/receptor and a policy action.

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Fig. 4.2  Logical Framework of the STeMA-TIA decision-making process. (Source: Prezioso 2006, pp. 55–57)

a new governing procedure, the Europe 2020 strategy or any post-2020 action, regional spending, availability of funds for future investments, etc.); 4. Drafting a Reference List of the objectives for which a policy has been devised. All the policies, actions and effects utilised to this end are bound to the objectives to be reached by applying a given policy. STeMA-TIA has been designed to initially deal with a territory and its closed circle indicators in relation to each policy domain under scrutiny (e.g. Lisbon Strategy, Smart Growth, Cohesion Policy, spending review, etc.). The existing

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frameworks discussed above are used to create a three-way coaxial matrix, which is employed during the STeMA-TIA procedure to detect the determinant used to evaluate the FTV and the coherence between supply and demand (Fig. 4.4). The territory is examined in its initial state (i.e. ITV), which establishes quality, gravity and weight for each element and process, thus combining all the methodologies in Sect. 4.1. Using ad hoc mapping procedures that are directly linked to this process makes the results of the analyses readily detectable. This ensures that such results are transparent and objective, as expressively recommended by the EU. It is worth remembering that TIA aims to support policy- and decision-makers in calculating territorial quality for each proposed policy, in relation to the weight and state of its elements and the process as it occurs. Such increments are determined according to: • The quality value of the system and its representing indicators in terms of state and process (i.e. logical tree of correlations) • The gravity9 of each impact • The importance of each impact in relation to the carrying capacity of the system to meet expectations The weight of the impact depends on its gravity because it is calculated by considering the relationship between the actions and the effects of a policy; the weight is expressed as a percentage and depends on the gravity of each impact in relation to each action of a policy. This impact gravity, which helps to assess the increasing or decreasing level of the ITV, is determined by correlating: • The impacted area (i.e. territorial application of a policy) • The main features of the policy and its scope The impact gravity can be found at different levels, which are determined according to the many possible combinations of the importance of a policy10 and in relation to pre-established criteria. Using a policy within a given territorial domain involves changing its status (i.e. FTV) as a system (∂). The comparison of ex ante values and the territorial variation(s) that resulted from the application of a given policy makes it possible to determine the latter’s appropriateness. If the use of such a policy proves to be inappropriate, this methodology can suggest alternatives to enhance the quality of the territory under review and its policy needs. Multiple scenarios of public policymaking can be simulated to determine the most balanced preliminary option(s) in relation to the initial territorial sensitivity. This is done using macro and micro analyses according to which each interacting factor is considered in detail to include all those criteria and aspects that help to

 The impact level that a policy action has in the attempt to reach set targets.  Cf. for instance 3, 2, 1 and 0 in the Lisbon/Gothenburg Strategy evaluation.

9

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Fig. 4.3  A qualitative interaction matrix resulting from the pairwise comparison of two indicators. (Source: Prezioso 2011a, b, p. 57)

implement the best policy in a given situation (e.g. the spending to implement services within the inner peripheries; Prezioso 2019b). STeMA-TIA has employed the pairwise comparison approach to establish the ‘weighted positioning’ of a determinant. This has been done by also establishing how decision-making processes are implemented and what interaction matrices are used to this end. The many indicators that stemmed from this comparison have been progressively transformed into detailed indexes. The resulting matrices offer a qualitative value, which proceeds from the quantitative value of each indicator (i.e. I1 is a dominant while I2 is a secondary indicator). This procedure returns a synthetic/ composite index (Ix; Fig. 4.3). In which: Aa > Ab > ……. > Ba > Bb > ….. > Dd And the (Ix) values are organised to return the following results: Ix = Aa, Ab = high value = A Ix = Ac, Ad, Ba, Bb, Bc = medium high value = B Ix = Bd, Ca, Cb, Cc, Cd, Da = medium low value = C Ix = Db, Dc, Dd = low value = D The pairwise comparison matrices assess how important determinants are within the macro policy they refer to. In addition, it also assesses the typologies, category sectors and indicators that are part of this macro policy from a (geographic) standpoint. The weight (WIx) (or Index, if referring to categories, sectors or typologies) of each single indicator is reported as a percentage so that the sum of all the values is always 1 (even when using ordinal scaling). The same procedure applies when summing the many weights of the same level of indicators. Each weight relates to a single indicator, which in turn relates to a category, sector, typology and determinant. Hence, the final weight is defined by the initial percentage multiplied by the

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percentage of each category, which is subsequently multiplied by the percentage of the sector and then the typology it belongs to. The same procedure applies to the pairwise comparison on the ordinal scale. The (qualitative and quantitative) function of territorialisation is used to relate each indicator to a given determinant, which is verified via scientific analysis and the Delphi method. This function is established via a solid methodology that uses verified metadata during the initial investigation stage; when the elements to be analysed are more difficult to determine, they can be defined via repeatable or indirect decision-making models that have been established beforehand. This procedure does not influence the retrieved value regarding the correlations among indicators; it facilitates establishing such correlations, while using well-­ defined criteria. This is possible because STeMA-TIA includes the sensitivity notion in its analyses of sensitivity and sustainability related to different territorial scales. STeMA-TIA determines the ex ante sensitivity of a territory by always taking into account the many aspects connected to the indicator under scrutiny, while initially disregarding the final objective of the policy at hand. Once the quality function of each indicator has been made explicit (and applied in order to determine the initial quality value QIx), it will be possible to calculate the Initial Territorial Value (ITV). This value is defined for each territorial typology and determinant under review and expressed as a synthetic index. It also stems from subsequent quality pairwise comparisons (Q) for every indicator, which are then multiplied by the weight (W) of each indicator. The analysis continues on each level along the evaluation scale. By using this general ex ante value (or territorial quality) regarding the area under scrutiny, it will be possible to determine the gravity (G) of the impacts produced on the effects of alternative policies. Cross-check analyses may also be carried out via normalizing processes on the retrieved values (e.g. regarding 1 or A; cf. Fig. 4.3). Once a process has been defined, policy/decision-makers can use STeMA-TIA to find which policy action is best suited to achieve the objective they have in mind in terms of sustainability. To this end, they will compare ex ante quality with the quality that results from the ex post simulation. In order to verify any related increment in territorial quality resulting from the policymaker’s decisions, the STeMA-TIA methodology suggests that: • The detection of any high initial sensitivity within the territory may be the result of this territory’s willingness to embrace change. In many cases, there is a direct correlation between the sensitivity value and the increased/decreased quality value of a policy action. • In order to compare ex ante and ex post quality, they must be simultaneous. • Any variation in quality may be different in each territorial system under scrutiny, and its function may also vary in terms of the level of impact, the initial quality of the indicator, the level and importance of the impact in relation to the indicator/receptor, the number of impacts on the territorial unit under review (i.e. functional systemic typology) and so on.

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Each increment in quality (δ) is therefore a function relating to the number of impacts produced by a given policy that is applied to a territory along with all previous parameters established during the initial assessment stage. Consequently, the increment/decrement value will be the Initial Territorial Value minus the Final Territorial Value.

VTI  VTF  

When applied, policy actions have real impacts on the territory; hence, their comparison with any territorialised indicators can determine theoretical impacts. Each determinant is assessed in terms of its related initial indicators and the order in which each impact has been produced; this impact will be measured according to a high, medium, low or nil level on the Bereano’s (1972) tree of effects. Since the analytical level required is particularly high, STeMA-TIA includes monitoring procedures used for designing three-way coaxial correlation matrices to determine the indicators/receptors-effects-actions correlations of a policy. Fig. 4.4 includes the correlation scheme for the processes carried out via the STeMA-TIA methodology. Description: A = list of actions that correlate to one or more policies. A = 1,...,h,.....l. This list includes all the actions that a policymaker can use in relation to EU strategies such as Europe 2020 or the EU Cohesion Policy.

Fig. 4.4  Correlation matrix of the STeMA-TIA model, version 1.0. (Source: Prezioso 2006, p. 61)

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B = the role that each single action has for each effect (i.e. each action may have a different weight and some actions may not have any effect at all). C = list of effects of a policy. This list includes all the effects that relate to the objectives for a given policy (i.e. determinants). It varies for each objective/determinant. D = the impact of each effect on the indicators. E = weighted list of indicators. This list includes all the indicators used to calculate the ex ante objectives/determinants (E – status quo of time t0) and their ex post values, before (E′ is time t1) and after territorialisation (E″ at time t1). Each policy action can initially be considered in binary terms, which are respectively absence (0) and presence (1). Once the ‘presence’ of an action has been determined (as 1), a policy is potentially able to cause an effect. Hence, each policy action will be weighted according to the following scale of its capacity to produce effects: 3 (high), 2 (medium), 1 (low) e 0 (nil).11 Each indicator is linked to a given number of theoretical impacts within a matrix; therefore, the correlation between impact and indicator is obtained by taking into account all related levels of gravity (G) and quality (Q). This will be expressed according to incrementing/decrementing percentages or the ordinal value after the initial quality. The gravity of each impact is based on a series of parameters, such as: • The impact domain or territorial entity, which includes all involved territorial sub-units • Any parameter that can be detected from the applied policy • Any parameter that can be detected by taking into account the (methodological) coherence between the techniques and procedures used to analyse and create territorial working bases (i.e. systemic functional typologies) • All the solutions that can be applied in the event that conflicting policies overlap Again, a pairwise comparison can be used to estimate how important each correlation is on various quality scales. The matrix results can be then converted into an impact function with normalised values from 0 (zero impact) to 1 (maximum impact). While evaluating the Final Territorial Value (FTV), any impact on an indicator will cause an increment or decrement in quality. This increment/decrement can be calculated not only in relation to the initial quality of indicator Ix (which has been georeferenced within the Systemic Functional Typology SFTx), but also in relation to a quality that may be presumed to be the result of the effects produced by other impacts. The FTV of each SFTx results from the ITV (W*Q) of every Ix indicator, which has been calculated within the determinant it belongs to. In its simplified version (referring to one indicator and impact only), the FTV is basically the difference  The matrix correlation for weight, effect and indicator/receptor will return values that can range from ‘absolute’ (A) to ‘absent’ (‘nil’); they can be easily detected in the STeMA-TIA GIS and in its mapping process.

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between the ITV and the quality increment that results when multiplying the IVT by the gravity (G) and the increment/decrement (I/D) an impact has caused. Like weight W, I/D is predetermined thanks to a weighted list for the policy under review. Conversely, G and Q are always linked to the territory being investigated. The FTV will therefore include a correlation, defined as δ (while Δ is used for the final determinant), which results from the analysis of W, Q, D and G. All other correlations (δ1, δ2 …, δn) are instead reported on maps of territorial variation (or δ maps) because they reflect the changes that different policies can trigger. This makes it possible to determine a maximum δ above which an indicator will not absorb a given policy during t1. It goes without saying that such a large number of variables cannot be handled without the STeMA TIA-GIS tool. In addition, it is important to consider the data resulting from territorial place evidence, as the latter helps to define territorial sensitivity and programme policy adaptive choices that meet the existing technical, socioeconomic, cultural and environmental parameters. The use of Systemic Functional Typologies (be they regional, sub-regional and local) is therefore an essential part of the STeMA-TIA methodology. These functions can offer ex ante and ex post territorialised information in relation to several assessment scales. On the basis of previous experiences (Prezioso 2006, 2011a, b), STeMA TIA has drawn up 7 Systemic Territorial Functional Typologies (STFTs) (Prezioso 2019b, p. 50), which can be used to evaluate those policy actions related to geographical diversity. These STFTs are proposed solutions for territorialised SFRTs (Systemic Functional Regional Typologies) that can be adopted in the TIA process and applied to several policy actions (Fig. 4.5). The SFRTs are: 1. MEGA and metropolitan systems with strong urban influence and transnational/ national functions that can facilitate cooperation between cities (or city parts) at the regional, national and transnational levels 2. High urban influence systems with transnational/national specialised functions that can facilitate urban–rural cooperation between authorities in interconnected areas at the regional, national and transnational levels 3. High urban influence systems without specialised functions and with few transnational/national functions that can facilitate urban–rural cooperation between authorities in interconnected areas at the regional, national and transnational levels 4. High urban influence systems without specialised functions or any transnational/ national functions, thus unable to facilitate urban–rural cooperation between authorities in interconnected areas at the regional, national and transnational levels 5. Low urban influence systems with regional/local specialised functions that can facilitate urban–rural cooperation between authorities in interconnected areas at the regional, national and transnational levels 6. Low urban influence systems with regional/local functions that can facilitate urban–rural cooperation between interconnected areas at the regional and local levels

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Fig. 4.5  Example of systemic territorial functional typologies in Italy. (Source: Prezioso 2019b)

7. Low urban influence systems without specialised functions or transnational/ national functions, thus unable to facilitate urban–rural cooperation between authorities in interconnected areas at the regional, national and transnational levels The link between STFTs and TIA springs from theoretical and applied studies, including the relevant literature on territorial cohesion. These typologies assume that a geographic economic region represents the quality, efficiency and identity of its territorial systems, as well as its interrelations. The capacity of a region to combine existing resources and valorise its efficiency reflects the initial (ex ante) milieu; in other words, a region can create socio-territorial and governance models thanks to shared principles. A region has a potential that can positively influence its GDP and wealth. The STFTs can help define each region’s uniqueness and strengthen the territorial capital of an area. They may also be used to evaluate the Territorial Cohesion level at t0, thus influencing the spending capability and making it possible to match local needs and political goals.

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The STeMA-TIA method addresses policy/decision-making within STFTs on different geographic scales.

4.3

Some Applications of STeMA

In 2003, STeMA-TIA methodology was used experimentally to verify the correctness of governance approaches to the General Territorial Plan of the Metropolitan City of Rome. Subsequently, it was used in the ESPON project called Territorial Dimension of Lisbon/Gothenburg Strategy (2004–2006), which sought to assess territorial capability across different European areas in terms of sustainable competitiveness (Prezioso 2006). Furthermore, STeMA-TIA helped to study and measure the territorialised impact of four major policies and determinants at the European NUTS 2 and 3 level, which are: • Innovation and Research (including actions for implementing ICT, R&D, Innovation, and studying factors such as Human capital, Age, etc.) • Global/local interaction (including actions for implementing SMEs, Human capital, Employment, Transport, Trade, Tourism, etc.) • Quality (including actions for implementing Climate, Public health, Natural resources, Poverty, Transport, Age) • Use of resources and funds (including the spending required in implementing all previous policies) The evaluation of these policies derived from 116 simple indicators (and metadata) included in the revisited and updated Lisbon Agenda (2000–2004), which was also implemented within the Gothenburg Strategy (2001) to support the new 2013 programming period. These four determinants assumed the role of the Strategy key-­ messages. Territorial cohesion was also introduced to indicate ways of integrating the Strategy into the new Structural Funds in the 2013 programming period. This STeMA-TIA 1.0 version was the result of a fruitful discussion among scholars upon receiving scientific and institutional inputs relating to growth and employment, the adaptation of the Cohesion Policy and Sustainable Development Indicators to monitor the implementation of the EU Strategy. The application of STeMA-TIA demonstrated that the initial Lisbon monitoring/evaluation proposal based on the 14 simple and synthetic indicators (EC list 2004) was not sufficient. By contrast, STeMA-TIA offered a concrete and operational response to how the EU countries (25 + 2 + 2 at NUTS 0), regions (NUTS 2) and sub-regional areas (NUTS 3) could achieve a territorial cohesive Strategy in 2006 and in later years simply by exploiting their regional potential. It pinpointed exactly what the regional functional typologies were, and which of them could best benefit from using the 2013 Structural Funds in a cooperative way. STeMA-TIA was also applied to the territorial investigation of spatial (statistical) data. This showed that it can be used to put forward proposals that cater to

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cross-thematic co-operative regions and identify their potentialities. This can be done because STeMA-TIA entails a ‘bottom-up’ approach to studying the regional and sub-regional qualitative and quantitative values. Comparing two types of results (from the EC and STeMA lists) confirmed the soundness of the STeMA-TIA model (Beta testing). A more selective and ‘customised’ set of policy recommendations was presented together with scenarios to support the implementation of the Strategy. These recommendations concerned the different capabilities of the analysed territories and their related aggregated hypotheses regarding co-operation, thus confirming that STeMA-TIA methodology is a pioneering approach that helps assess the potential impact of initial interventions, by taking into account the specificity of each region (i.e. geographical diversity) as well as any related recommendations. The STeMA-TIA methodology and its indicators underwent a further process of development and updating to produce a 2.0 version (Prezioso 2008). Thus, its political effectiveness could be assessed before new National Operative Programs (NOPs) and the 2014–2020 EFS programmes were launched as part of EU Cohesion Policy. Guidelines, approaches, proposals and initiatives defined the sub-regional (provinces or districts) level as part of the increasingly close relationship between the spatial/territorial dimension and programming responsibilities regarding the organization and governance of the territory, economy, society and environment. STeMA-TIA is now available in its 3.0 version, which was launched in 2017. It has become a pillar of Italian national research on territorial cohesion within many regions and provinces (e.g. inner peripheries, rural and urban/metropolitan areas). This has been done in view of the Europe 2020 Strategy and its allocated ESIF budget. STeMA-TIA has also had a hand in drafting post-2020 national policies (Prezioso 2018, 2019b), ten years after its first application (Prezioso 2006). This work was supported by the Italian Ministry of Infrastructures to strengthen the link between structural policies and economic governance via intergovernmental cooperation based on the Territorial Agenda and the Leipzig Charter. From 2005 to 2017, STeMA-TIA served as a sound methodological and scientific tool applicable to several projects in the field of cooperative programs. It contributed to the adoption of a more markedly challenge-based approach and it also enhanced the multidisciplinary interpretation of knowledge.12

 The application of STeMA-TIA can be found in projects such as: the CADSES project POLY. DEV (Italy, Slovenia, Slovakia, Bulgaria and Greece) (Prezioso 2007); the NewCiMed project under the ENPI CBC Med Programme (Italy, Spain, Greece, Tunisia, Jordan and Lebanon); Observation and Territorial activities of the Centre of Excellence–Technological District of Cultural Heritage of the Lazio Region; the planning activities across the metropolitan city of Rome; the green economy development (Prezioso et  al. 2016); the spending review of Italian regions (Prezioso 2019); the relation with the Maritime Spatial Planning (D’Orazio and Prezioso, 2017).

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 ain Results, Strengths and Weaknesses, M and Future Applications

The STeMA-TIA methodology has been applied to a host of areas, sectors, levels and geographical scales, including European transnational and inter- and intraregional and local cases studies. Unlike previous TIA tools that conceived ex ante and ex post evaluations as two separate processes, STeMA-TIA has proven its validity and flexibility in aptly combining both evaluations. This has always been done by considering sustainability as its driving principle, which dictates learning and evaluating before taking any decision. One of STeMA-TIA’s main strengths is that it is a replicable tool that can be applied to evaluate all levels of territorial governance. It facilitates policy- and decision-­making by creating assisted processes that are analysed according to the way the identity of an area and its territorial capital changes over time, when being subject to political action. STeMA-TIA can create new perspectives for planning and programming and helps policymakers interpret how a policy can be adapted at both macro and micro levels. Moreover, it can define territorial contexts in light of their potential investment and attractiveness. Another main strength of this methodology lies in its multidisciplinary nature that allows it to combine basic but diverse kinds of information (e.g. quantitative and qualitative; the latter can also be examined in quantitative terms) by making it operationalised across the board. It may also include economic, social, environmental, cultural and organisation phenomena that in the past could hardly be treated using one single model. STeMA-TIA also meets the European Commission’s expectations, according to which the TIA 2020 will pursue SMART (i.e. Specific, Measurable, Acceptable, Realistic and Time-based) objectives at different and hierarchically organised levels. STeMA-TIA can help understand what development potential a single economic and territorial system may have by evaluating its demand for policy needs and planning. It also makes it possible to establish whether a territory is able to solve its problems by offering an adequate response to the challenges it faces; this response is adequate when it remains within the limits of its system (i.e. subsidiary and sustainable supply). It can also help to calculate the territory’s initial performance, its capacity building in terms of management and spending, its innovation level and the risks that it may take in relation to the cohesion that has been achieved by the socioeconomic system and its administrative and political institutions. However, if those who intend to use the STeMA-TIA methodology do not have a solid grasp of its implementing aims (i.e. policy assessment), weaknesses in the application of this tool may arise. In particular, the pairwise comparison may make it difficult to properly select and classify the indicators as ‘dominant’ or ‘secondary’. Patently, choosing an aggregating function and weighting system is never free of criticism. Therefore, the STeMA-TIA model uses several interactive matrices that compare many indicators and progressively transforms them into indexes and determinants.

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Despite these possible limitations, STeM-TIA can easily adapt to different contexts and policy questions. It is applicable to different geographical areas because it also includes a territorialising process in its model. STeMA can promote any economic policy that is connected to the territorial capital because it takes into account the initial stated and achieved objectives of a territory (i.e. ex ante regional and provincial TIA) to measure whether the targets of a policy have been achieved. This evaluation process is still ongoing, and the importance of place evidence is gaining so much momentum that political institutions cannot help but abide by it. However, the responsibility for any decision-making ultimately rests in the hands of the institutions, and STeMA cannot be seen as a substitute for them. From a conceptual standpoint, and despite its many applications, STeMA-TIA and its ‘measure and assessment’ processes are still far from reaching a political and institutional consensus among decision-makers. Consequently, it may often not be the assessment model of choice at the regional and local level. Furthermore, its complex framework sometimes clashes with traditional political outlooks that only take into account the relationship between assessment and decision-making. Another issue that still needs to be addressed is whether and, if so, how STeMA-­ TIA can be used to create a set of norms and regulations based on geographical diversity. The EU initially used TIA as an indirect economic assessment tool which also helped to determine the coherence of any proposed project in light of pre-­ determined target values for its growth. Today, a TIA is also able to determine decision-making at the national and regional level that also takes into account EU recommendations. This has resulted in the need to reconsider the role of the TIA even before acting on the STeMA model. The latter will naturally continue to measure, for instance, the impact of EU strategies on the territorial cohesion of regions and provinces, as well as reinforce the (macro) role of regionalisation. Clearly, STeMA sets itself apart from other homogenising approaches used for this type of investigation.

References Adkins WG, Burke D Jr (1971) Social, economic and environmental factors in highway decision making. Texas Highway Dep., Dallas Bereano A (1972) A proposed methodology for assessing alternative technologies. Cornell University, New York D’Orazio A, Prezioso M (2017) Surfing multiple dimensions: an integrated approach in maritime spatial planning. In: Kitsiou D, Karydis M (eds) Marine spatial planning: methodologies, environmental issues and current trends. Nova Science Publishing, New York, pp 115–154 Duke KM et  al (1977) Environmental quality assessment in multi-objective planning. Battelle-­ Columbus Laboratories, Columbus Falque M (1975) Pur une planification écologique, Falque Max, Paris Georgescu-Roegen N (1971) The entropy law and the economic process. Harvard University Press, Cambridge, MA Georgescu-Roegen N (1977) Bioeconomics: a new look at the nature of the economic activity. In: Junker L (ed) The political economy of food and energy. University of Michigan, Ann Arbor, pp 105–134

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Leopold LB et  al (1971) A procedure for evaluating environmental impact, Geological Survey, Circ. N. 645, Leopold Luna Bergere, Washington, DC Malcevschi S (1986) Indicatori eterogenei e bilanci di impatto ambizntale. Elementi per un paradigma di collegamento. In: Schmidt di Friedberg P (a cura di) Gli indicatori ambientali: valori, metri e strumenti nello studio dell'impatto ambientale. FrancoAngeli, Milano, pp 883–914 Mandelbrot BB (1975) Les objets fractals: forme, hasard et dimension. Flammarion, Paris Mueller JH (1970) Statistical reasoning in sociology. Houghton Mifflin, Boston Prezioso M (1990) Gli indicatori socioeconomici nella ricerca geografica applicata. Prime considerazioni di stima e reperimento delle fonti. Geografia nelle Scuole 4:327–335 Prezioso M (1995) La base geoeconomica della Valutazione di Impatto Ambientale. Pacini, Ospedaletto Prezioso M (ed) (2006) Territorial dimension of the Lisbon-Gothenburg process. Aracne, Rome. http://www.espon.eu/main/Menu_Projects/Menu_ESPON2006Projects/Menu_ CoordinatingCrossThematicProjects/lisbonstrategy.html. Last accessed: July 2019 Prezioso M (2007) Model application remarks. In: Quaglia T (ed) Common best practices in spatial planning for the promotion of sustainable POLYcentric DEVelopment. Regione Veneto, Venezia, pp 57–59 Prezioso M (2008) Cohesion policy: methodology and indicators towards common approach. Rom J Reg Sci 2:1–32 Prezioso M (2010) The sustainable territorial environmental/economic management approach to manage global policy impacts and effects. In: Cancilla R, Garganos M (eds) Global environmental policies: impact, management and effects. Nova Science Publisher, Hauppauge, pp 110–163 Prezioso M (ed) (2011a) Competitiveness in sustainability: the territorial dimension in the implementation of Lisbon/Gothenburg processes in Italian regions and provinces. Pàtron, Bologna, pp 19–36 Prezioso M (2011b) STeMA: proposal for scientific approach and methodology to TIA of policy. In: Farinos Dasi J (ed) De la Valuacion Ambiental Estrategica a la Evalucion de Impacto Territorial, Generalitat Valenciana/PUV. Valencia Autonomus Region Government/University of Valencia Publications Office, Valencia, pp 100–130 Prezioso M (ed) (2018) Quale territorial impact assessment della coesione territoriale nelle regioni italiane. La concettualizzazione del problema. Pàtron, Bologna Prezioso, M (2019a) Methodological approach for a new economic geography of the territorial cohesion in Europe and Italy. Bollettino della Società Geografica Italiana serie 14 (2 Special Issue): 7–24 Prezioso M (2019b) Measuring the progress towards Territorial Cohesion: a TIA application to the regional development programs. In: ESPON 2020 Scientific Conference, Building the next generation of research on territorial development, London 14 Nov. 2018, ESPON, Luxembourg, pp 49–53 Prezioso M, Ottaviani V (2009) New Methodological rules in order to measure the sustainable territorial development. In: PISTA 2009: politics and information systems, technologies and applications, Orlando, Florida, July 10th – 13th Prezioso M, Coronato M, D’Orazio A (2016) Green Economy e capitale territoriale. Dalla ricerca geografico economica, proposta di metodi, indicatori, strumenti. Patron, Bologna Roy B (1996) Multicriteria methodology for decision aiding. Kluwer Academic Pub, Dordrecht Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psycol 15:234–281 Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48(1):9–26 Saaty TL, Kearns KP (1985) Analytical planning. Pergamon Press, Oxford Saaty TL, Vargas LG, Wendell RE (1983) Assessing attribute weights by ratios. Omega 11(1):9–13 Saaty TL, Vargas LG (1993) Experiments on rank preservation and reversal in relative measurement. Mathematical and Computer Modelling, Volume 17, Issues 4–5, pp. 13–18. Vernasdky WI (1945) The biosphere and the noosphere. Am Sci 33:1–12

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Von Bertalanffy L (1969) General system theory. G. Braziller, New York Warner ML, Preston EH (1974) A review of environmental impact assessment methodology. US Government Printing Office, Washington, DC. EPA 600/5-74-002 Maria Prezioso  is full Professor of Economic Geography and Territorial Planning at the University of Rome “Tor Vergata” with more than 35 years of experience in developing research in academic and applied contexts on European transnational territorial development. Appointed by several national public institutions as scientific expert in the field of European Expert in Territorial and Urban development, European spatial planning systems, European Regional and Cohesion Policy, Green and Blue Economy, Political Regional Geography, Local and Regional Development, and International Cooperation for Development, Scientists/Decision-Makers bridging. Expert in Territorial Impact Assessment of programmes plans and projects with development of TIA and SEA procedures by of STeMA (Sustainable territorial economic/environmental Management Approach) patented methodology. Active participation in several EU projects and programmes (ESPON 2006, 2013, 2020 programme, CADSES, INTERREG ENPI CBC MED, URBACT II) as lead partner, scientific coordinator, partner or external expert. Director of Master in Economy and European Planning of territorial sustainable development (Tor Vergata) especially devoted to CH issues and directly related with Technology District of Cultural Heritage and Activities in Latium Region (DTC). She is author of more than 200 publications and the STeMA-TIA patent.

5

The ESPON EATIA: A Qualitative Approach to Territorial Impact Assessment Naja Marot, Mojca Golobič, and Thomas B. Fischer

Abstract

This chapter presents the results of the European ESPON EATIA research project in which a Territorial Impact Assessment (TIA) methodology was developed for administrations in EU member states in order to inform their national positions in European draft directives’ negotiation processes. Rather than applying another EU-wide top-down quantitative modelling approach based on indicators, the EATIA project explored the possibility to use a qualitative bottom-up approach that is simple to perform and comprehend for regional and/or local stakeholders, and national administrations of the 27 EU member states. The project was conducted between 2010 and 2012 in a transnational manner, connecting four universities and ministries, responsible for planning from the UK, Portugal, Slovenia and the Netherlands. The main output of the project is a TIA framework (Fischer TB, Sykes O, Gore T, Marot N, Golobič M, Pinho P, … Perdicoulis A. Territorial impact assessment of European Draft Directives—the emergence of a new policy assessment instrument. Eur Plan Stud 23(3): 433–451, 2015), based on a process consisting of screening, scoping, assessment and evaluation, with possible techniques allocated to each of these stages, and proposed governance arrangements. Testing of the TIA framework on various EU directives

N. Marot (*) · M. Golobič Biotechnical Faculty, Department of Landscape Architecture, University of Ljubljana, Ljubljana, Slovenia e-mail: [email protected]; [email protected] T. B. Fischer Environmental Assessment and Management Research Centre, School of Environmental Sciences, University of Liverpool, Liverpool, UK Research Unit for Environmental Sciences and Management, North West University, Potchefstroom, South Africa e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_5

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(e.g. Natura 2000, SEVESO) has shown that the approach meets the expectations of experts, but its success to a large extent rests on the commitment of the governing stakeholders to engage with and contribute to the process. Keywords

Territorial Impact Assessment · Qualitative approach · ESPON · public administration · directives

5.1

A Historical Background, Main Goals and Application

The need for Territorial Impact Assessment (TIA) was first established by the European Spatial Development Perspective (ESDP; Commission of the European Communities 1999), confirmed in Territorial Agenda (EU Ministers for Spatial Planning and Development 2007), and finally adopted by the Commission by the Commission’s Fifth Report on Economic, Social and Territorial Cohesion (Commission of the European Communities 2010). The latter claimed that policies with and without an explicit spatial dimension could benefit from an assessment of territorial impact which could be performed both, quantitatively and qualitatively. Subsequently, it was the ESPON programme who adopted it and dedicated significant amount of financial resources to the project’s development methodological approaches on TIA. The first attempts to TIA, supported by ESPON, were based on highly complex and quantitative, computer modelling approaches such as the SASI model (Wegener 2008), the CGEurope model and the STEMA model (see Chap. 4), focusing on the ex post assessments of EU policies, e.g. the Transport and Trans European Network (TEN) Policies (ESPON 2004), energy policy (ESPON 2005b) and others (ESPON 2005a, 2006a, b, 2010b). Furthermore, the ESPON programme invested in the research of ex-ante assessment, in projects such as TIPTAP (Territorial Impact Package for Transport and Agricultural Policies; ESPON 2010a), TEQUILA (Camagni 2006) and TEQUILA 2 model (ESPON 2010a), both of which resting heavily on the indicators, computing formulas and the engagement of researchers capable of running such calculations. As a consequence, initial approaches were not found to be applicable to the institutional settings of public administrations. Hence, ESPON realised that alternative approaches to TIA should be sought for, as argued in Fischer et  al. (2011). The first project to include the stakeholders in TIA and modelling was the ESPON ARTS project (Assessment of Regional and Territorial Sensitivity, ESPON 2011) with the intention to provide a more qualitative and participative approach to TIA, and to simplify the performance of the assessment. In addition to this, in 2009, an ESPON call was initiated by ministries responsible for spatial planning from three EU member states, to develop a TIA methodology which is simple and user friendly for administrations at local and regional levels. In addition, a request was made to shorten the time of conducting TIA, so

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that evaluation results would be available as quickly as possible having practical usage value. Furthermore, the approach should not lead to new formal assessment obligations, similar to, e.g., Strategic Environmental Assessment (SEA) but should instead be flexible and sensitive to different member states’ contexts. The grounds for this were established in the Commission’s Impact Assessment Guidelines, adopted in 2009 (Committe of the European Communities 2009). With these goals in mind, the ESPON EATIA (ESPON and Territorial Impacts Assessment) project started in the year 2010 with four project partners (University of Liverpool, University of Ljubljana, University of Porto and TU Delft). The aim was to develop a bottom-up, participative and qualitative approach. A TIA methodology was to be developed and used by EU member states for the pre-assessment of potential impacts, and to assess how the adoption of EU policy (e.g. directives) might impact their regions and local communities. Ultimately, results of the assessment should help member states to formulate the national opinion on a particular proposal. This chapter presents the approach developed and examples of its implementation and elaborates on future usage. Most of the chapter rests on the results presented in the report by Fischer et al. (2012).

5.2

The Methodology in a Nutshell

The TIA framework/methodology was developed in four phases over an 18-month period. In the first phase the differences and similarities of existing assessment tools and TIA were established, comparing the existing EC Impact Assessment procedures, as well as Environmental Impact Assessment and Strategic Environmental Assessment in the UK, Slovenia and Portugal; as well as Regulatory Impact Assessment (shorter RIA) in the UK and Slovenia; and Sustainability Appraisal and Rural Proofing, both only applied in the UK. Existing assessment instruments were checked for their nature (legal status, spatial scale, focus, existence of guidelines, types of impacts considered, timing, initiating parties and end users), procedural elements, content (alternatives, format, types of impact considered, territorial relevance, data collection, uncertainties and consideration of mitigation measures), and consultation and influence (Fig. 5.1). It was concluded that TIA could be best combined with the existing RIA procedures at the national level, and regional/local spatial-planning-related SEA activities. In the second phase, a preliminary TIA framework was designed in a transnational manner and then tested in three countries on various directives. After testing the approach, the usefulness and benefits were evaluated together with the associated costs of applying the TIA framework. On the basis of the findings, there was further refinement of the TIA approach. The EATIA framework consists of three main elements, including process and techniques, applied at each of the procedural stages, as well as governance. Procedural elements concern the stages of the TIA process, which include (1) screening, (2) scoping, (3) assessment and (4) evaluation. The governance dimension concerns the allocation of tasks to different administrative levels and communication/collaboration between different partners, and is especially relevant as

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Fig. 5.1  EATIA procedure (Golobič et al. 2015, p. 46)

orientation to different MSs as to how they can adapt the process to their different governance and institutional arrangements.

5.2.1 Screening During the screening phase, national government departments decide on whether a TIA is necessary. This is done on a case-by-case basis. The decision will be positive if the potential impacts of the policy proposal are likely to be undesirable, are unintended or are expected to vary in nature across the country’s territory. The decision should be reached in the multidisciplinary group of policymakers and other relevant experts on the topic, including the representatives of the spatial planning sector, e.g. the representatives of the ministry, responsible for spatial planning. The information used to reach a decision are outputs of the EC impact assessment procedure and other existing studies. In addition, the following approaches can be applied to facilitate the process:

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1. Preparation of the logical chain, which is usually a result of structured brainstorming. Firstly, the facilitators present the content of the policy proposal in a schematic manner which serves as an input for the brainstorming. Then the participants in the process who contribute to the screening list all the possible direct or indirect territorial impacts, depicting them diagrammatically, underlying the cause-effect logic or pathways. The result can be either a very simple logical chain or a more sophisticated diagram, in other words, it can vary from being a hand-drawn sketch on the back of an envelope to a complex computer-­ designed figure. 2. The preparation of a checklist is the second tool to support the screening phase. In the checklist we predefine the assessment criteria, selected to cover a range of dimensions/characteristics of the territory. Taking into account these characteristics, it should be possible to identify the likely conflicts between EU policy proposals and national/subnational political priorities or objectives. Criteria can be developed ad hoc for each case or nationally/EU standardised through prior agreement between stakeholders in the MS, enabling the policymakers to compare the results for different policy proposals. An example of such a set could elaborate Europe 2020 objectives. Importantly, the criteria should disallow different interpretation and should not be too numerous.

5.2.2 Scoping The scoping phase is again carried out by the national ministries, responsible for a draft directive, after the initial decision to pursue with the TIA is made. An interdisciplinary expert team possessing information on the baseline data, territorial characteristics and future development scenarios should execute this phase in a collaborative manner. The major task is to define the scope of the process by determining whether major territorial impacts are likely to result from the proposed policy, the nature of these impacts, and the geographic locality of these impacts. Three activities should be carried out during the scoping phase, namely completing a scoping checklist, developing an Impact Assessment Matrix to be used at the next TIA stage and identifying where impacts may be particularly noticeable. 1. The scoping checklist is based on a template, provided in the TIA Guidance (see ESPON 2013). While completing the checklist it should first be determined whether a policy proposal is considered as a whole or divided into several individual elements (e.g. articles of the policy proposal), for each to be assessed individually. On the one hand, this allows for a more precise determination of the impacts and produces richer data to inform negotiations. However, on the other hand, it can increase the work load substantially. The impacts of the policy proposal are considered against each of the territorial characteristics, and it is decided if either there is (yes) or isn’t (no) an impact. Additionally, an “uncertain” category can be used. If necessary, the logical chain can be used again to identify cause-effect relationships. In addition, the features and/or the type of

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impact at the regional/local level is specified in terms of resources  – physical characteristics  – and economic activities, e.g. energy production, education, agriculture, industry. Hereby, the participants can write comments on the anticipated magnitude of the expected impacts. 2. The scoping checklist is used to prepare the Impact Assessment Matrix (IAM). This forms the basis for the assessment stage at the regional/local level. To prepare the IAM, the scoping team should use the template provided in the TIA guidance and populate the matrix’s axes with (a) the assessment criteria/characteristics employed in the scoping checklist and, (b) if utilised, the identified policy elements. 3. The last exercise of the scoping phase is to define the types of regions in which the impacts might materialise. It is preferable to consider all subnational areas in terms of potential impacts. However, this might not always be possible. Thus, it is either possible to hand pick the regions with the most likely effects, or to cluster the regions according to their common characteristics, relevant for the policy proposal being discussed. For the latter, a typology can be prepared which again requires a skilled researcher, capable of GIS analysis and data management. Another approach is to make an inquiry across all the regions if they are interested in participating in the TIA process.

5.2.3 Impact Assessment Assessment is done by regional/local-level spatial planning authorities (in very small member states possibly together with national administrations), possibly by existing spatial planning teams, which already convene at regular intervals. At the beginning, authorities are informed about the first two stages of the TIA either via a dedicated website (or via a digital TIA tool/platform if that exists). Afterwards, they should start with the assessment procedure.  The assessors need to complete the impact assessment matrix (IAM), developed during scoping, by considering the impact of the policy proposal (or of each policy proposal element) on the locality in question in terms of the territorial characteristics used in scoping and possibly other, local characteristics they find important. Any quantitative modelling exercises conducted at the EU level can support the assessment here. When potential impacts are identified, following the format of the IAM, they should be described with reference to the following three characteristics. A full justification should be provided to facilitate later interpretation and processing: • Magnitude of the impact: This refers to the expected size or scale of the impact and should be defined numerically (0 = no impact, 1 = some impact or 2 = major impact); no intermediary values should be used (uncertainties can be reflected in the comment section). • Orientation: This refers to the impact’s direction of action in relation to the baseline condition, for instance, will it act to increase soil pollution or decrease soil pollution?

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• Temporal distribution: This refers to the duration of the impact; this should be described in terms of: short term (e.g. up to 5 years), medium term (e.g. up to 10 years) and long term (e.g. over 10 years); in cases where the nature of the impact varies over time, this can also be outlined. Throughout this exercise, it is important to consider potential indirect and possible spill-over effects from impacts in adjoining localities, in particular in cases when these could be particularly influential. For instance, if an externally located important local employer was to close as a result of a proposed policy. It is also important to utilise all available sources of information and evidence such as the outputs of the scoping process which can provide a valuable source of insight, especially when the proposed directive is highly technical. Additionally, whilst extensive baseline data compilation exercises are not necessary when the exercise is done within the context of a workshop attended by expert representatives of different departments coming together routinely, e.g. to make a local spatial plan, detailed supporting studies can be conducted if deemed necessary and if resources and time permit. Impact matrices and impact maps may be produced as the final result of this phase; testing has shown that assessment may be done in as little as half a day to a full day, depending on the complexity of the directive or policy to be assessed and the experience of the assessment team.

5.2.4 Impact Evaluation Evaluation, the summarisation phase of the TIA process, is done by central government ministries, based on national, and possibly European, territorial policy objectives. The evaluation is based on information provided by regional and/or local authorities, possibly through the centrally managed website. The main purpose of this stage is to determine whether the potential impacts identified in the assessment are significant, both, positively or negatively, and how any undesirable impacts could be avoided or mitigated via changing the wording of a directive proposal or altering the transposition approach. Thus, the impacts identified and described in the IAM(s) are interpreted in terms of their compliance with various territorial policy objectives, using an Evaluation Table. Evaluation tables can be supported by creating thematic maps highlighting and representing the spatial distribution of the anticipated impacts. The basic content of the Evaluation Table are the policy objectives and the criteria employed in the assessment process in order to bring the score together. Taking this into account, the significance of the impacts detailed in the completed IAMs should be defined by considering both, the nature of the policy proposal’s potential impacts (e.g. magnitude, direction of action) as well as the nature of the objective itself. Impacts should be defined in the Evaluation Table, using a 5-point scale (−2, −1, 0, +1, +2), reflecting whether the potential impacts are considered to be positive or negative for the objective concerned and the impact’s degree of significance (neutral to high). The preferable option to perform this is in a

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group manner. Each determination in the table should be accompanied by a written commentary and justification which should include, in each case, an explanation of the specific policy impacts that have led to the significant determination given in terms of each objective, and if possible any suggestions of how negative impacts may be avoided or mitigated or potentially positive impacts be maximised. Following the evaluation process, best practice dictates that a written summary of the results/outputs of the overall TIA process be prepared and sent to local/ regional-level partners who participated in the TIA, if not to all regional/local authorities. Alternatively, similar evaluation procedures can also be conducted by the regional/local authorities to evaluate the impacts in the frame of their policy objectives. Overall, the final document should include any proposed changes to the policy proposal. Regarding the time dimension of the assessment, testing the approach with a range of directives in Portugal, Slovenia and the UK showed that, if TIA is to be completed with only minimal resources being available, national screening and scoping can be completed during half day workshops. However, a precondition is the existence of a skilled interdisciplinary team, coming together in a co-operative spirit, reflecting a high level of familiarity with the policy area and territorial expertise. A similar amount of time is required for the assessment stage conducted at regional or local levels, whilst the overall evaluation might take as little as between half a day and a full day, depending on how many authorities are actually involved and how extensively technical elements are elaborated on. If more substantial resources are available, there are no barriers to conducting more comprehensive assessments, which may include, e.g., the generation and presentation of territorial baseline data and the preparation of more elaborate TIA reports. In particular, this may enhance transparency.

5.3

Application of the EATIA Procedure in the UK

5.3.1 Introduction In the UK, testing of the procedure was done internally by the project team and externally by practitioners involved in the project through national learning network. Their engagement covered the assessment and local/regional evaluation stages. External testing was initiated by some members of the learning network, e.g. representatives of governmental agencies, who wanted to be engaged more actively in the TIA process. Despite the framework being designed for the ex ante assessment of EU draft directives (and policies), given the relatively limited time available for testing, it was agreed that it would be most practical to test the framework by applying it to EU directives in a ‘mock’ ex ante fashion, i.e. treating adopted directives as if they were proposals. The following directives were identified as suitable: 1. Directive 92/43/EEC on the conservation of natural habitats and of wild fauna and flora (Habitats Directive)

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2. Directive 2009/28/EC on the promotion of the use of energy from renewable sources (Renewable Energy Directive) 3. Directive 2010/31/EU on the energy performance of buildings (Energy Performance of Buildings Directive) 4. Directive 2009/72/EC concerning common rules for the internal market in electricity and repealing Directive 2003/54/EC (Electricity Directive; not fully assessed due to the limited time available) The priority in testing was not to produce an accurate assessment of the directives under question, but rather to use them to explore and evaluate various aspects of the framework. Operationalising the framework would require further in-depth testing, involving all stakeholders and engaging with the real-time policy development process.

5.3.2 Screening and Scoping Whilst in practice, screening and scoping should be a central government department’s responsibility, in this case, these stages were undertaken internally by members of the national project team, three to four team members respectively, and were completed in around 5 h. For each directive, screening was undertaken using the logical chain approach. These chains were initially hand-drafted in a participatory

Fig. 5.2  Digitised logical chain for Directive 2009/28/EC (Fischer et al. 2012, p. 77)

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setting, following an approach similar to that advocated in the ESPON ARTS project (ESPON 2011), but were subsequently refined and digitised for reporting purposes (Fig.  5.2). A logical chain shows the potential impacts of the directive’s measures on the elements (indicators) of the natural environment, society and people, and economy. The marked connections are also designated by their nature, so if they rather increase or decrease the value of the indicator. Scoping was again undertaken in a participatory manner within the project team following the format of the scoping checklist.

5.3.3 Assessment and Evaluation The assessment and evaluation stages for each directive were undertaken a few weeks after the initial screening and scoping stages and were carried out primarily by external participants under the guidance of the project team. The testing of these two stages was done at two levels, the local and the ‘regional’ (devolved administration). Accordingly, for this part of the testing, contact was made with the authorities that were represented on the national learning network. Testing was conducted in two small workshops held in December 2011 and January 2012. The first of these was held with local planning authorities (local level testing; Dover and Leeds), of which two authorities attended. Testing at the local level was based on the Habitats and Energy Performance of Buildings directives. The second workshop was held just over a month later with representatives from the devolved government (‘regional’ level testing). One administration (Northern Ireland) participated directly in the testing, and another (Scotland) met with the project team in Edinburgh in the testing period and provided detailed feedback on the approach based on preliminary TIA guidance. Regional-level testing was based on the Renewable Energy Directive. Each workshop followed the same format, as follows: 1. Prior to each workshop each participant was sent: (a) detailed TIA guidance outlining the approach; (b) a full copy of the directive(s) to be assessed in the workshop; and (c) a summary of the directive’s main measures. 2. At the start of each workshop the TIA framework/methodology was presented and an opportunity provided for participants to ask questions and seek any clarifications. 3. The case study directive was then presented, and the outputs of the screening and scoping stages prepared by the project team were introduced. 4. Participants were asked to conduct the assessment and the local/regional-level evaluation for their corresponding areas working in their teams (stages 3 and 4 were repeated if multiple directives were assessed). 5. At the end of each workshop there was a general discussion and participants were invited to complete an evaluation questionnaire. Following the practitioner workshops, the outputs from the completed assessments were synthesised by the project team and mapped (Fig. 5.3). From this, the

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Admin_costs

Airpol

Biodiv

Culture

Econdev

Edtrain

Energy

GHGs

Health

Innov

jobs

Rand D

Rescon

Social

Soilpol

Waste

Waterpol Duration Term NA Short Medium Long

Impact

−2 −1 0 1

−2 −1+1 −2+2

Directive 2009/28/EC Northern Ireland

Fig. 5.3  Mapped outputs for Directive 2009/28/EC on Northern Ireland and Directive 92/43/EEC on Dover District (Fischer et al. 2012, p. 78)

national-level evaluation was conducted by the project team based on objectives derived from Europe 2020.

5.4

Application of the EATIA Procedure in Slovenia

5.4.1 Introduction In Slovenia, testing has mainly been performed through workshops. Internally, the project team covered screening and scoping (logical chains, checklists and preliminary assessment matrix), the evaluation stage, including the synthesis and graphical representation of the data. External participants were involved in preparation of the logical chains and in the assessment stage. Policymakers and practitioners from the national, regional and local levels took part in these workshops jointly, so the results do not distinguish between the applicability of the framework for each administrative level separately. Workshops attracted groups of people consisting between 5 and 11 individuals, depending on the content of the directive in the assessment. For example, the workshop of the proposed SEVESO III Directive took place on 18 November 2011 and attracted 6 people, including an expert on environmental impact assessment, representative of the Ministry of Environment and Spatial Planning and a person responsible for the implementation of this directive in Slovenia, employed at the same ministry. The list of invited people varied, e.g. for the testing of the Habitats Directive, representatives of local communities with the

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highest share of areas, protected under Natura 2000, were sent invitations. Additionally, the aim was to invite the person in charge for the transposition of the directive into national legislation and its implementation. Each workshop followed the same schedule, as follows: • • • •

Short TIA framework/methodology introduction Brief presentation of the Directive’s content Designation of possible impacts through brainstorming (group work) Determination of suitable criteria for assessment of the directive (short presentation) • Introduction to spatial typologies • Assessment, using matrix-based method (individual work) • Short discussion on the synthesis and the list of territorial development objectives to use To ensure active participation, the research team distributed workshop materials (the workshop programme, brief description of directive and its measures, text of directive, typology) prior to each workshop. Similar to the UK approach, a ‘mock’ ex ante assessment was performed; the directives used for the testing were selected as a result of the first learning network workshop and discussions with the national stakeholders. The tested directives included: 1. Directive 92/43/EEC on the conservation of natural habitats and of wild fauna and flora (Habitats Directive) 2. Directive 2009/28/EC on the promotion of the use of energy from renewable sources (Renewable Energy Directive) 3. Directive 2010/31/EU on the energy performance of buildings (Energy Performance of Buildings Directive) 4. Proposal for a Directive on the control of major-accident hazards involving dangerous substances COM(2010) 781 final SEC(2010) 1591 final. The purpose of Slovene testing was twofold; firstly, the TIA framework/methodology was critically examined by the participants. Secondly, the accuracy of the results of the assessment of the directives was of interest to the participants. The reports on the testing were drafted separately for each of the four directives and contain information on the general potential impacts of the directive as evaluated through the logical chain exercise, the list of criteria determined for the detailed assessment of the directive, assessment tables with numeric scores and final evaluation results, which include information about the most significant policies introduced by a directive, as well as the most affected areas and the graphical illustration of impacts in maps and charts.

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5.4.2 Screening and Scoping Screening was done as part of the first workshop where participants together with the research team decided on directives to be tested. The project team prepared ‘the content part’ of the logical chain which consisted of the policy background for a directive’s adoption, the description of a directive’s objectives and a presentation of the specific policies/measures introduced by a directive. In the supplementary materials, each measure was described with the name, summary of contents, objectives, target groups and the territorial/administrative level at which policies/measures of a Directive would be performed/implemented. The exercise started with a brainstorming session in which workshop participants were divided into groups of 3–4 and were asked to think about the potential impacts of the directive in terms of four areas: (1) environment and territory, (2) economy, (3) society and (4) governance/administration (Fig.  5.1). Each group reported on their results, which led to the drafting of the final logical chain. Due to the numerous impacts recognised by the participants and not to limit the participants in their ideas, the direct links between measures and impacts were not drawn during the workshop but instead added later on by the research team members. Due to the complexity and high number these links are not graphically presented but are visible in the box of each impact where the relevant measures are written (Fig. 5.4). Next in scoping was the selection of the criteria for the directive’s impacts assessment. The initial list of criteria (see Table 5.1, column two) consisted of 61 criteria,

Fig. 5.4  Example of a logical chain for Directive 92/43/EC (Fischer et al. 2012, p. 84)

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Table 5.1  List of assessment criteria agreed on by workshop participants (Fischer et  al. 2012, p. 85) Environment / Territory Soil

Biodiversity and landscape Water resources

Air and climate

Built environment

Energy production

Waste treatment Economy Economic development

Agriculture

Industry Service Tourism

Small business Infrastructure Transport Society Demography Health

Social inequalities and social protection

Education Cultural heritage Governance and administration Efficiency

Transparency Subsidiarity Territorial organization

Erosion exposure Soil quality Sealing Area of multifunctional forest Landscape quality Biodiversity Protected areas Water consumption Water quality Water availability Pollution with solid particles Emissions of NOx Noise pollution Emissions of greenhouse gases Urbanization Size of degraded area Vulnerability of areas, exposed to natural disasters Use of renewable Use of fossil fuels Energy import dependency Quantity of collected waste Economic growth Number of innovation Market burdens Employment in primary sector Farm size Extent of agricultural incentives Level of self-sufficiency Employment in secondary sector Import rate Employment in tertiary sector Employment in tourism Number of visitors Accommodation availability Number of small business Administrative costs, connected to establishment of the company Utilities quality Utilities accessibility Use of public transport Commuting Migration Fertility Mortality in traffic accidents Industry accidents hazards Life expectancy Hospital costs Distribution of income Unemployment Social transfers Elderly protection Poverty Child protection Education level Cultural heritage protection Planning process (duration...) Administrative costs Impact on national budget Public participation Obligations and tasks on different territorial/administrative levels Level of central places hierarchy Accessibility of the closest regional centre

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Fig. 5.5  Typology map, example for Habitat directive (Fischer et al. 2012, p. 86)

which were clustered into four main thematic groups: environment and territory (21 detailed criteria), economy (19), society (14) and governance and administration (7). A debate initiated at the workshop led to the selection of the specific, so-called primary, criteria for each of the directives. On average, around half of the criteria were usually designated to describe the impacts of a specific directive and assess them numerically; the range is from 22 for SEVESO III proposal to 34 for the Renewable Energy Directive. The last part of the scoping phase was the preparation of typologies for each directive separately in order to decrease the number of territorial units in which the assessment would be performed later on. Units were created on the basis of the territorial characteristics relevant for a particular directive, e.g. for the Habitat Directive the share of the area in the region, protected under Natura 2000 was used. Regions were clustered on the quantitative basis and with the help of cluster analysis performed with the SPSS programme. Ward method and the square of the Euclidian distance were used as a measure. Figure 5.5 shows an example of such typology, in this case for the Habitat directive three types of affected regions were designated: most, medium and least likely affected.

5.4.3 Assessment and Evaluation The assessment was done by each participant individually outside of the workshop environment. With the use of prepared matrices, participants assessed the impacts of

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the directive in the particular group of regions for the selected criterion. Criteria were defined in a way to allude to the wanted state. For example, ‘the quality of air’ aimed at improvement of the quality or in other words to increase of the quality of air. This means that a positive score would illustrate an improvement while a negative score would indicate deterioration. Besides the direction of the impact, evaluators also marked the strength of the impact with the help of a 5-point scale: −2 score meaning a very negative impact, −1 negative impact, 0 impact exists but it is not possible to define the direction of it, +1 positive impact and + 2 very positive impact; and were invited to add an explanation for their decision. Numeric scores were then analysed and summarised as part of an evaluation procedure performed by the research team. Average scores were calculated for each group of regions for each criterion. Further on, averages were calculated for the impact of each measure to all four impact areas (economy, environment, society, governance). To distinguish the extent of an impact on an individual topic, sums were calculated for the number of evaluated criteria in the cell. Summarising matrices were drafted for: • Impacts of all policies/measures on each impact area • Summarised impacts of each policy/measure on the individual impact area for which the weighted average of all individual groups of regions was calculated with the area of relevant regions (also graphically presented in charts) (Table 5.2) • Sum of the impacts of all policies/measures, i.e. the impact of the whole directive on each area type separately (graphically presented on maps). In a report, numeric scores are summarised separately for each measure/policy and expected impacts, a comparison of scores between the groups of regions is provided. The last part of the evaluation is an estimation of how much the directive will contribute to delivery of the spatial development policies on different territorial/ governmental levels. For this, we used spatial development objectives of: Territorial Table 5.2  Sum up matrix for first three measures/policies of the Habitat Directive (Fischer et al. 2012, p. 88)

Impact area Environment and territory Economy Society Governance, administration

M1: Designation of sites as special areas of conservation

R1*

0,4 (10 / 14) 0,4 (5 / 10) 0,5 (1 / 1) -0,7 (5 /5)

R2*

0,6 (10 / 14) 0,1 (9 / 10) 0,7 (1 / 1) -0,8 (5 /5)

R3*

0,5 (11 / 14) 0,1 (10 / 10) 0,4 (1 / 1) -1,1 (5 /5)

M2: Establishing the necessary conservation measures for areas of Natura 2000

M3 Assessment of acceptability of the effects of the implementation of plans on protected areas

0,7 (9 / 14) -0,2 (6 / 10) 0,6 (1 / 1) -0,7 (5 /5)

1,4 (2 / 14) -0,8 (1 / 10) 0,8 (1 / 1) -0,9 (5 /5)

R1

R2

0,6 (11/ 14) -0,1 (8 / 10) 0,6 (1 / 1) -0,9 (5 /5)

R3

0,8 (12/ 14) 0,1 (9 / 10) 0,3 (1 / 1) -0,9 (5 /5)

R1

R2

1,0 (5 / 14) -0,4 (4 / 10) 1,7 (1 / 1) -1,0 (5 /5)

R3

0,8 (5 / 14) -0,3 (4 / 10) 1,0 (1 / 1) -1,1 (5 /5)

a R1 – regions with the smallest share of Natura 2000 protected sites and the smallest area of ‘agricultural’ and ‘settlement’ Natura b R2 – regions with a large share of Natura 2000 protected sites, medium exposed ‘agricultural’ and ‘settlement’ Natura and a large area of the rest of Natura c R3 – regions with a medium share of Natura 2000 protected sites, a large area of ‘agricultural’ and ‘settlement’ Natura and a medium-sized area of the rest of Natura

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Fig. 5.6  Territorial presentation of impacts, proposal of SEVESO III directive (Fischer et  al. 2012, p. 89)

Agenda (EU Ministers, 2007; EU level), Spatial development strategy of Slovenia (national level) and Municipal plan of the City municipality Novo mesto (local level). The summarisation has been enabled with the preceding exercise of the research team which content-wise linked the criteria from the initial list with the objectives. Then this ‘theoretical’ list was confronted with the criteria selected to evaluate a particular directive, so the impact of the directive on the policy objectives has been summarised by the cross-section of theoretical and empirically selected criteria. Again, the average was used as summarisation function but results are presented with symbols by using the following scale: −2 to −1,2: very negative impact (−) −1,2 to −0,4: negative impact (−) −0,4 to 0: negligible negative impact (o−) 0: impact for which it is not possible to define the direction (o) 0 to 0,4: negligible positive impact (o+) 0,4 to 1,2: positive impact (+) 1,2 to 2: very positive impact (++)

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The initial five-point scale was reorganized on the basis of distribution of the scores to better diversify the scores. On the maps, the symbols o−, o and o+ are illustrated with a unified colour (Fig. 5.6). A synthesis was prepared for policymakers at the EU, national and local level. At the national level, the national government has undergone significant changes, and now the Ministry of Foreign Affairs is in charge of coordinating Slovenian participation in EU legislation preparation and its transposition into national legislation. Additionally, National Assembly representatives should be informed about the results, along with national lobbyists, planners and officials of the ministries and policymakers on regional and local level.

5.4.4 Strengths and Weaknesses of the Approach Testing undertaken over the course of the project has shown that an experienced impact assessor is likely to find the TIA methodology approach simple and straightforward to conduct, while less experienced individuals might need some time when taking part in TIA for the first time. More precisely, the screening and scoping stages could be conducted in half a working day, the assessment stage and the local/ regional level evaluation would require the same amount of time, depending on how many localities are engaged in the process, so altogether approximately 1–2 days. In addition, the testing has shown that once a person starts with the assessment, they usually find themselves handling the qualitative TIA methodology in an effective manner rather quickly; however, handling the process depends on the expertise of the participants and the previous experience in the impact assessment processes. The participants in the pilot TIA processes elaborated the following strengths of the approach: • EATIA procedure is a simple procedure that does not require much human capacity and advanced knowledge in the assessment, neither for the public administrators to facilitate it nor for the stakeholders to participate in it. • The participative part of the process increases its legitimacy and enables for sectors to come together in the collaborative manner in order to reflect on the policy proposals. In the Slovene case, for example, the participants commented the procedure performed in the neutral academic environment enabled them first to come together at the same table, and to talk openly about the policy content and also about the governance framework in which the policy is supposed to be implemented, and implementation obstacles that might occur in the framework. The testing provided also valuable information on the individual steps of the EATIA procedure and the content-wise decisions facilitators of the process need to undertake: • Usefulness of the logical chains: Logical chains and brainstorming about the (potential) impacts of the directives have been recognised as useful exercises for

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developing a first idea of potential impacts of the directive. More ambitious participants were willing to connect the measures/policies of a directive with the individual impact, so in future this might as well be added to the exercise. Selection of the criteria: The Slovenian research team worked with a very long list of criteria. Participants found the list practical since it enabled a better consideration of potential impacts and supported the debate on impacts. However, they also agreed that for faster implementation of TIA the list could be shortened and the detailed criteria grouped into more general criteria which was done for the general guidelines on the procedure. The workshops showed the number of selected criteria depends on the size and content of a directive. If a directive concerns a very narrow problem, e.g. the proposed SEVESO III Directive, then the final list of criteria is shorter than for more comprehensive directives such as the Renewable Energy Directive. Selection of the territorial level of the assessment: There are advantages and disadvantages to conducting the assessment at regional and local levels. At the level of the devolved administrations (regional), whilst there is an advantage in that the coverage of the assessment is greater, it was reported by participants to be difficult to come to an overall impact judgement given the variation of policy impacts across the territory. At the local level, whilst this was evidently less of a problem, because of the increase in resolution, this comes at a cost of either increased workload or lost coverage. Consideration of the transboundary impacts: The problem of dealing with transboundary impacts was noted by participants at the local level workshop, i.e. the impacts on localities which could have consequences for others. To this end it was mentioned that in some situations it may be useful to target localities surrounding localities that are deemed in scoping to be impacted by the policy proposal. This could be considered in the scoping stage on a case-by-case basis depending on the nature of the directive. Preparation of the typology of territorial units and localities: The most controversial part of the workshop EATIA exercise was the issue of allocating typologies. Participants did not always agree with the selected criteria for classifying the regions and therefore suggested typology alterations. At times, they also provided additional sources of data. In the assessment phase, typologies were difficult to comprehend since they introduced abstract simplification of a territory and created localities with which participants had not been familiar with before. This resulted in uniformed scores granted to all groups of regions and the claim that it was difficult to distinguish between the groups of regions. Explanation of this phenomenon is twofold: (1) If more administratively oriented measures/ policies are evaluated, it can be expected that impacts will not vary among territories, so the uniformed score is justifiable. (2) If a typology is not well accepted and logical to the assessor, then the typology should be adapted and a uniform score does not represent reliable results. This indeed would bring more exact assessment but would also prolong the TIA performance.

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Furthermore, the testing of the EATIA procedure was done in a mock exercise manner, meaning that to show the real benefits and applicability value the procedure would need to be tested in real-time policy development and in the case of draft directives’ documents (of the tested ones all were already adopted and in implementation). Secondly, the experience is based on the three EU countries, which while being different in terms of their political history, planning traditions and the governance setting, they still do not represent the whole EU policy arena. Thus, testing is also necessary elsewhere, which should, however, not be difficult because of the highly flexible characteristics of the EATIA procedure. Also, the applicability of the approach should be stretched to programmes and projects, not only EU directives. In national frameworks, the main barriers to an effective TIA process are likely to include a resistance of different departments and/or administrations to co-operate due to the pre-existing tensions in the governance framework or simply the lack of time for additional tasks to be assigned to them. Additionally, central government ministries, for example, may not be experienced in co-operating in the way anticipated by the TIA methodology, and may thus be reluctant to engage in the exercise. Apart from the co-operation culture, countries also take different approaches in assessing the policies and legislation in preparation – while some, e.g. Germany, are dedicated to preliminary testing, others prepare and adopt legislation without ex ante assessment. Furthermore, regional and/or local authorities may be sceptical about the possibility to be able to influence a national position on a draft directive (or any other policy) or about the value of engaging in such a process and may thus be reluctant to participate in a TIA. Regarding both these barriers, central governments, and in particular the departments responsible for territorial development/ spatial planning, have a pivotal role in overcoming these by actively promoting and championing the approach.

5.5

Future Application of the Qualitative TIA

Since the conclusion of the project in 2012, ESPON and the EC devoted some resources to the promotion of TIA, including the EATIA approach, via several dissemination channels. The first one was publishing a practical guidance for policymakers and practitioners, based on contributions from ESPON projects and the EC (ESPON 2012). The second one was a promotional video for TIA as a concept, and the third one was an online tool for performing TIA, which was suggested as well by the EATIA stakeholders, both published on the ESPON website. Committee of the Regions (Schneider 2013a, b) adopted documents in which it recognised the relevance and importance of adopting territorially sensitive policies and that the TIA should be mandatory in a number of policy areas with territorial dimension, such as transport, energy, urban and rural policy, etc. Yet, currently, no evidence is available for how many times and to what extent the approach has been implemented in real-time policymaking. The literature review from 2012 onwards shows several examples of the TIA applications across Europe, such as Gavanas et  al. (2018), Medeiros (2017) or Fratesi and Perucca (2014), which continue to use the

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quantitative approach, very likely a consequence of the fact that these TIA applications are result of research projects on TIA. Thus, we can conclude that up until now TIA has mostly been an academic exercise and that none of the countries, so far involved in the development of the TIA approaches, have made any progress in applying the TIA, neither in their real policymaking processes nor in the preparations of responses to the new EU policy proposals. It seems that, in the times of austerity measures applied to public administrations all across Europe, such as cutting of the annual budgets, limitations on hiring new staff and any such additional tasks or approaches are only recognised as an unnecessary burden, rather than a potential beneficial exercise to the existing governance processes. In such an environment, the broader application of TIA could only happen if the procedure becomes a formal requirement by the government in existing policy preparation procedures.

References Camagni R (2006) Territorial impact assessment — TIA: a methodological proposal. Ital J Reg Sci (Scienze Regionali) 5(2):135–146 Commission of the European Communities (1999) European spatial development perspective— towards balanced and sustainable development of the territory of the EU, Committee on Spatial Development. CEC, Brussels Commission of the European Communities (2009) Impact assessment guidelines (SEC(2009)92). CEC, Brussels. Available at http://ec.europa.eu/environment/nature/natura2000/management/ docs/Wind_farms.pdf. Accessed 2 Dec 2013 Commission of the European Communities (2010) Investing in Europe’s future. Fifth report on economic, social and territorial cohesion. Publications Office of the European Union, Luxembourg ESPON (2004) ESPON project 2.1.1: territorial impact of EU transport and TEN policies. ESPON, Luxembourg ESPON (2005a) ESPON project 2.1.3: territorial impact of CAP and rural development policy. ESPON, Luxembourg ESPON (2005b) ESPON project 2.1.4: territorial trends of energy services and networks and territorial impact of EU energy policy. ESPON, Research Centre for Energy, Transport and Environment Economics, Luxembourg ESPON (2006a) ESPON action 2.1.5: territorial impacts of European fisheries policy. ESPON, Luxembourg ESPON (2006b) ESPON project 2.2.1: the territorial effects of the structural funds. ESPON, Luxembourg ESPON (2010a) The ESPON 2013 Programme, application pack, priority 2 call for proposals for targeted analyses, ESPON 2013 Programme CU, Luxembourg ESPON (2010b) ESPON TIPTAP project—territorial impact package for transport and agricultural policies. ESPON, Luxembourg ESPON (2011) ESPON project ARTS  – assessment of regional and territorial sensitivity: draft final report. ESPON, Luxembourg ESPON (2012) Territorial impact assessment of policies and EU directives—a practical guide for policymakers and practitioners based on ESPON projects and the European Commission. ESPON, Luxembourg. Available at http://www.espon.eu/export/sites/default/Documents/ Publications/TerritorialImpactAssessment/TIA_Printed_version.pdf. Accessed 2 Dec 2013 ESPON (2013) Territorial impact assessment of policies and EU directives. ESPON, Luxembourg

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EU Ministers for Spatial Planning and Development (2007) Territorial agenda of the European Union: towards a more competitive and sustainable Europe of diverse regions. Available at http://www.bmvbs.de/en/-,1872.963636/Territorial-Agenda-of-the-EU.htm. Accessed 2 Dec 2013 Fischer TB, Sykes O, Gore T (2011) Making the case for participatory TIA. Town Country Plan 80(4):204–207 Fischer T, Sykes O, Gore T, Marot N, Golobic M, Pinho P, Waterhout B, Perdicoulis A (2012) ESPON EATIA. ESPON and territorial impact assessment. Final report. ESPON & University of Liverpool, Luxembourg. Available at http://www.espon.eu/export/sites/default/Documents/ Projects/TargetedAnalyses/EATIA/FinalReportEATIA28June2012Afinal.pdf. Accessed 5 Dec 2013 Fischer TB, Sykes O, Gore T, Marot N, Golobič M, Pinho P et al (2015) Territorial impact assessment of European draft directives—the emergence of a new policy assessment instrument. Eur Plan Stud 23(3):433–451 Fratesi U, Perucca G (2014) Territorial capital and the effectiveness of cohesion policies: an assessment for CEE regions. Investigaciones Regionales-J Reg Res 29:165–191 Gavanas N, Moutsiakis E, Tasopoulou A, Verani E, Fourkas V (2018) The territorial impact assessment of transport: the case of the Egnatia motorway system in the cohesion potential of Southeast Europe. Impact Assess Project Appraisal 36(4):294–307 Golobič M, Marot N, Kolarič Š, Fischer TB (2015) Applying territorial impact assessment in a multi-level policy-making context–the case of Slovenia. Impact Assess Project Appraisal 33(1):43–56 Medeiros E (2017) Cross-border cooperation in inner Scandinavia: a territorial impact assessment. Environ Impact Assess Rev 62:147–157 Schneider M (2013a) Draft opinion of the committee of the regions assessing territorial impacts, 102nd plenary session, 3–4 July 2013. Committee of the Regions, Brussels Schneider M (2013b) Territorial impact assessments—and instrument which offers European added value, regions and cities of Europe—Newsletter of the Committee of the Regions, No. 83, May–June 2013, p. 16 Wegener M (2008) SASI model description, Working paper 08/01. Spiekermann & Wegener Stadtund Regionalforschung, Dortmund Naja Marot  graduated at the University of Ljubljana, Faculty of Civil Engineering in Geodesy in 2010 with the thesis about Regulatory Impact Assessment performed on the Slovenian planning law in order to define deficiencies and factors influencing the performance of the system and capacities of its stakeholders. At the Department of Landscape Architecture (UL) she teaches Tourism and Recreation, and Regional Planning, both in the MSc programme. Her research focuses on (territorial) governance, policy analysis and impact assessments, regional and urban planning, territorial cohesion, degraded urban areas and post-mining regions, methods for regional planning and public participation. Her international experience includes guest research at the HCU Hamburg University (Germany), University of Michigan (USA), the Federal Institute for Research on Building, Urban Affairs and Spatial Development (Germany), Leibniz Institute of Ecological Urban and Regional Development (Germany) and the University of Seville (Spain). She represents Slovenia in the Council of Representative at European Association of Schools of Planning (AESOP). Mojca Golobič  graduated and earned a PhD in landscape planning at University of Ljubljana, Biotechnical faculty. For 13 years she has worked as a researcher at the Urban planning institute of the Republic of Slovenia. Since 2003 she is affiliated with the University of Ljubljana, where she took a full-time lecturing position in 2010 and the role of the head of the Department for Landscape Architecture in 2012. She was Fulbright visiting lecturer at Harvard Graduate School of Design (2003/2004) and visiting lecturer at several universities in USA and Europe. Her research work focuses in methodological issues of environmental and land-use planning, strategic impact

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assessments and relation between landscape and people. She participated in various international and domestically funded projects in which she also took on the lead role several times. Thomas B. Fischer  is Professor for Environmental Assessment in the School of Environmental Sciences at the University of Liverpool, UK.  He earned an Extraordinary Professorship at the Research Unit for Environmental Sciences and Management, Faculty of Natural and Agricultural Sciences, North West University (Potchefstroom Campus), South Africa, and is an honorary staff member at University of Technology Berlin, Germany. His main focus of teaching has been on transport, spatial and transport planning, environmental assessment, planning and management, and his research interests include spatial and environmental planning, integrated/sustainability assessment, transport planning, health in planning and impact assessment, and International Comparative Studies. He is the editor of the journal Impact Assessment and Project Appraisal and Director of the University of Liverpool’s Environmental Assessment and Management Research Centre as well as the WHO Collaborating Centre on Health in Impact Assessments.

Part II Territorial Impact Assessment for Cross-Border Cooperation Programmes

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The Bottom-Up Approach: Experiences with the Impact Assessment of EU and National Legislation in the German, Dutch and Belgian Cross-Border Regions Martin Unfried, Lavinia Kortese, and Anouk Bollen-Vandenboorn

Abstract

Considering the myriad cross-border regions that the EU counts, it is impossible for the European Commission to map detailed territorial cross-border effects in all of the EU’s border regions for the impact assessments it conducts. National governments also face obstacles when seeking to cohesively integrate cross-­ border impact assessments in the existing frameworks that they use to assess the impact of new legislative, policy and enforcement measures. Even border regions or cross-border entities themselves face challenges in implementing impact assessments in their own territories. Despite the need for structural analyses of the border effects of newly adopted legislation and legislation under review, in terms of policy and enforcement, there are issues regarding the availability of academic resources, relevant tools and know-how. For the last couple of years, researchers from Maastricht University have been assessing as a bottom up exercise the potential effects of legislative proposals on the specific Dutch/German and Dutch/Belgium cross-border territories. This article presents the methodology used and the experiences gained from 2016 to 2019 by highlighting a number of interesting cases. It also offers future ideas for conducting similar “bottom-up” regulatory territorial impact assessments in cross-border regions. Keywords

Territorial impact assessment · Cross-border impacts · Legislative scrutiny · Border regions · Euro-regions · Germany/Netherlands/Belgium

M. Unfried (*) · L. Kortese · A. Bollen-Vandenboorn Institute for Transnational and Euregional Cross-border Cooperation and Mobility (ITEM), Maastricht University, Maastricht, Netherlands e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_6

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Introduction

In 2016, the cross-border institute “ITEM”1 at Maastricht University started an initiative to develop and apply a methodology to assess the impact of EU or national legislation on specific cross-border territories,2 either for legislative proposals, i.e. ex ante, or existing legislation, i.e. ex post. The underlying idea was to fill a specific gap: the assumption was that no comprehensive regulatory impact assessments were carried out at the EU or national level concerning cross-border territories. In this respect, ITEM seeks to complement the impact assessments carried out at the European and national level and contributes to the specific needs of the local cross-­ border regions, i.e. NL/DE/BE. The essential idea is to produce detailed knowledge on the effects or expected effects of legislation. In 2020, the institute will be conducting this assessment for the fifth time. Each year, between 6 and 10 dossiers are selected. First, the nature and background of regulatory impact assessments and the territorial dimensions of cross-border regions compared with other impact assessments will be described in Sect. 6.2. In Sect. 6.3, we describe the methodology chosen and its development. Section 6.4 describes the work done so far from 2016 to 2019. The experiences so far will be illustrated by presenting certain important dossiers and referring to practical cases. Section 6.5 discusses the specific problems – in terms of finding the right indicators and, in particular, in collecting specific cross-border data, both for ex ante and ex post dossiers – when defining principles and objectives for a certain policy field (from a cross-border perspective). Finally, in Sect. 6.6, the authors present their ideas for a network of institutes that conduct individual “bottom-­up” impact assessments in their own cross-border territories using a common approach. By doing so, cross-border impact assessments could help legislators at the EU and national level to better integrate the needs of cross-border territories into the policy-development and policy-evaluation process.

6.2

 he Objective and Background of ITEM’s Cross-Border T Impact Assessment

Citizens of cross-border territories are faced with consequences of European and national legislation, policies or programmes that have potential negative or positive effects on, for instance, cross-border cooperation, cross-border economic development or the rights and the freedom of cross-border workers. There has been a debate at the EU level on impact assessments and the territorial dimension of legislation, 1  The Institute for Transnational and Euregional cross border cooperation and Mobility was established at Maastricht University in 2015. 2  In this chapter, we will use the term cross-border region or cross-border territory. As shown in the section on methodology, the idea is not to conduct impact assessments for ‘border regions’ but for ‘cross-border’ regions or territories. The term ‘border region’ refers to a national perspective, whereas effects on cross-border regions transcend individual national views.

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policies and programmes. The European Commission has discussed the topic in the framework of its own impact-assessment strategy. In its “Better Regulation Package”, adopted in 2015, the Commission (European Commission 2015) proposed instruments to ensure that territorial aspects are factored into policy options.3 This should happen through the implementation of robust impact assessments of legislation that include territorial elements. The European Commission defines “Territorial Impact Assessment” as the procedure (or method) to “evaluate the likely impact of policies, programmes and projects on the territory, highlighting the importance of the geographic distribution of consequences and effects and considering the spatial developments in Europe”.4 However, the European Commission’s guidance documents do not discuss specific assessment criteria for cross-border regions. So far, territorial Impact Assessment (TIA) is still a non-mandatory procedure (Medeiros 2016a:97; 2016b), as opposed to, for instance, Environmental Impact Assessment. There is also a practical problem at the EU level: given the myriad border regions in the EU, it seems difficult for the European Commission to map detailed cross-border effects for all the EU’s cross-border regions in the impact assessments it conducts. This raises another question of how effects are assessed at the national and regional levels. In the first place, this is relevant for the transposition of EU legislation into national law. While EU directives can help overcome cross-border obstacles, differences in national provisions can still complicate matters across borders. In its “Boosting growth and cohesion in Border Regions” Communication (COM 2017/534), the European Commission illustrated the problem with the case of public procurement. According to the EC, differences in time limits set by Member States can make cross-border public procurement particularly difficult. Another example: ITEM researchers have found evidence of increased complexity due to specific national provisions in the case of the directives on the recognition of professional qualifications (Kortese 2018:5).5 In this case, the Member States define what falls under the content ‘regulated profession’ within the scope of national legislation. This can increase complexity and cause extra administrative burden, as is the case for specialised nurses in the Belgian-Dutch border region. National governments face similar difficulties as the European Commission when seeking to cohesively integrate cross-border impact assessments in the 3  Whereas the European Commission’s ‘Better regulation for better results  – An EU agenda’ Communication, COM(2015) 215 final of 19 May 2015 does not explicitly mention the territorial dimension, it is described in Chapter III of the Guidelines on impact assessment on page 31. See: https://ec.europa.eu/info/law/law-making-process/planning-and-proposing-law/better-regulationwhy-and-how/better-regulation-guidelines-and-toolbox_en. As part of the Impact Assessment toolbox, the European Commission has described how to assess territorial impacts under ‘tool 33’. The toolbox can be found here: https://ec.europa.eu/info/files/better-regulation-toolbox-33_en. All pages last accessed on 22 July 2019. 4  This definition can be found on DG Regio’s homepage under the heading ‘Territorial Impact Assessment’: https://ec.europa.eu/knowledge4policy/territorial/topic/regional_en (last accessed on 22 July 2019) 5  Directive 2013/55/EU as amended by Directive 2005/36/EC.

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existing frameworks with which they assess the impact of new legislative, policy and enforcement measures. The latest OECD Regulatory Policy Outlook (2018) shows that wherever national governments have established solid regulatory impact assessment, the impacts on competition, environment and on the public sector are the most frequently assessed. The territorial dimension is among the least assessed types of impact (OECD 2018: 66). The Dutch government, for example, has developed a long list of compulsory regulatory impact assessments, including the effects on administrative burden, business and the environment.6 So far, however, the assessment of territorial effects or, specifically, effects on border or cross-border regions has not been made compulsory. Recently, the government and Lower House of Parliament have been discussing the introduction of an ex ante review for national legislation and policy initiatives focusing on the Dutch border regions.7 As of yet, there is an intensive debate at the working level on how to improve the consideration of cross-border effects in the proposals of the various line ministries.8 So far (July 2019), no official procedures have been added to the different impact-assessment obligations of the Dutch line ministries. It is difficult to assess the situation in other EU Member States since there are no comparative studies focussing on the territorial dimension of regulatory impact assessments. The assumption is that, much like the EU and the Dutch government, hardly any national governments have already developed robust tools to this end. Against this background, in 2016, ITEM started to develop a methodology and conduct ex ante impact assessments of national legislative proposals issued by the EU, the Dutch, Belgian and the German governments. The reason was twofold: first, the idea was to contribute to the academic debate by providing an innovative tool for regulatory territorial impact assessment, specifically designed for cross-border territories; secondly ITEM sought to deliver practical reports for national, regional and local law-makers and cross-border authorities, in order to improve the quality of legislation with respect to the needs of cross-border regions. This is also avidly stimulated by cross-border organisations – called Euroregions in the Dutch/German/ Belgian context – which face a particular problem: they are the ones who monitor and experience legislation from a cross-border point of view and, very often, the ones who perceive the practical effects of EU or national legislations on, for instance, the cross-border labour market. However, due to very limited financial and staffing 6  The full list of obligations can be found on the homepage of the Ministry of Justice and Security, https://www.kcwj.nl/kennisbank/integraal-afwegingskader-beleid-en-regelgeving/ verplichte-kwaliteitseisen 7  As early as 2015, the Dutch Minister of Interior and Kingdom Relations promised the Dutch Parliament (Tweede Kamer) that he would investigate the necessity of establishing an interdepartmental cross-border impact assessment (Brief van de Minister van Binnenlandse Zaken en Koningrijkrelaties aan de Voorzitter van de Tweede Kamer der Staten-Generaal, Den Haag, 3 February 2015). 8  In 2019, the Ministry of Interior and Kingdom Relations asked Maastricht University (ITEM) to produce certain guidelines for a regulatory impact assessment of effects on the Dutch border regions.

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resources, the Euroregions in the Benelux/Germany area have so far not been in a position to conduct detailed regulatory ex ante impact assessments or ex post evaluations in their specific cross-border territories. Likewise, this has not been possible in the individual national border regions, including the Dutch Province of Limburg,9 where Maastricht University is based. The Province of Limburg is regularly confronted with this need to analyse border effects whenever it is asked to provide input during the national law-making process. So far, issues regarding the availability of relevant tools, data and know-how have been seen as obstacles to providing such input. Rather uniquely, the Province of Limburg has been addressing this problem at the national level for a number of years. It sparked the debate by commissioning an external consultancy to perform the first cross-border impact assessments on certain topics in 2013 and 2014 (Bangma 2014). Hence, the Province of Limburg supported the idea to conduct impact assessments on a regular basis. Moreover, many other stakeholders from border regions and cross-border entities in the area contribute to the selection of cases for the annual assessment. One of the key notions has been to involve them in the selection process as much as possible.

6.3

ITEM’s Methodology and Its Development

6.3.1 The Selection of Cases and Involvement of Stakeholders In order to fill the gap between the different existing impact-assessment tools, the ITEM Cross-Border Impact Assessment employs its very own methodology. The yearly process kicks off with the identification of the topics to be studied. These potential topics are identified by means of a survey amongst stakeholders (Unfried and Kortese 2019: 468). As discussed above, the involvement of regional stakeholders has been a priority. ITEM collaborates with stakeholders in Belgium, Germany and the Netherlands. At the beginning of the year, ITEM sends out a questionnaire to practitioners in border regions, cross-border entities and experts from different organisations dealing with cross-border aspects of social security, taxes, health insurance, etc. The survey tool allows stakeholders and other interested parties to react to the suggested research topics by sharing their experiences with ITEM. Additionally, the survey allows them to propose their own topics concerning legislative, policy and enforcement measures with (potential) effects on border regions (Unfried and Kortese 2019: 468). The selection of cases thus has two characteristics: it uses a bottom-up approach with the input of practitioners from the field and it relies on multi-regional and multi-national input. Ultimately, ITEM’s Cross-Border Impact Assessment working group makes the final selection of dossiers from the list of potential research topics. This working group consists of members from various faculties at Maastricht University as well 9  The Dutch Province of Limburg shares a longer border with neighbouring countries Germany and Belgium than it does with the rest of the Netherlands.

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as from ITEM’s external partner organisations. The proposed research topics are assessed by the working group, focussing on the topicality of the issues, the relationship with ITEM’s research focus and the number of requests submitted for a subject (Unfried and Kortese 2019: 468). ITEM aims to include between 6 and 10 topics every year. Once the research topics have been selected, the team searches for the appropriate experts. They are normally related to ITEM, Maastricht University or partner organisations. If a subject requires highly particular expertise, external experts will be asked to contribute. Every year, a team of students from Maastricht University is involved in the assessment, in the form of a special multi-disciplinary student project supervised by the core team. Despite the great variety of topics that ITEM’s Cross-Border Impact Assessment may cover, the research takes place using the same methodology as much as possible. The research results of each individual topic are collected in dossiers, which together form the annual ITEM Cross-Border Impact Assessment.10

6.3.2 Ex Ante Assessment and Ex Post Policy Evaluation The main focus lies on the ex ante assessment of the effects of legislative proposals. However, since many EU or national proposals are related to existing laws and policies, ITEM also investigates the impact of existing legislation on cross-border territories if it is related to new ideas or policy proposals. In this respect, ex ante impact research very often goes hand in hand with studying the impact of already implemented legislation or policies. In 2019, for instance, an impact assessment was conducted of a change made by the Dutch government to a certain tax regulation (the so-called 90% rule) that has been in place for several years. In the first year of its introduction, in 2017, the lack of tax declarations limited the assessment to a purely ex ante impact assessment based on previous experiences (Vink et  al. 2017). In 2019, however, the initial ex ante assessment was expanded by an evaluation of the first data available from the tax authorities. Thus, we also consider ex post evaluations to fall under our general heading of cross-border ‘impact assessment’. In fact, very often the line between ex ante and ex post is not that evident, since the effects of legislation that entered into force years ago are often in practice delayed by transitional periods or administrative delays. As already mentioned, in the fields of social security or tax law, the assessment of the effects of new legislation goes hand in hand with the evaluation of the effects of existing policies and regulations. In addition, a full-fledged policy evaluation of certain policy measures and legislation is often difficult for lack of cross-border data. This lack of data means that ex post research often takes the form of an assessment rather than a profound evaluation.

 For summaries of the annual ITEM Cross-border Impact Assessments and the final reports of the individual dossiers, visit the ITEM website: https://www.maastrichtuniversity.nl/research/institutes/item/research/item-cross-border-impact-assessment

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In this sense, ITEM’s approach observes the general distinction between impact assessment and policy evaluation described by the OECD (OECD 2014:1). Accordingly, the impact assessment focuses on the prospective effects of the intervention, i.e. what the effects might be, whereas an evaluation is likely “to cover a wider range of issues such as the appropriateness of the intervention design, the cost and efficiency of the intervention, its unintended effects and how to use the experience from this intervention to improve the design of future interventions” (ibid). Hence, if, in the course of the ITEM Cross-Border Impact Assessment, legislation is assessed ex post, the assessment is often confined to the question of the legislation’s intended and unintended effects.

6.3.3 Defining the Territory: The Cross-Border Perspective The first step according to ITEM’s internal guidelines (ITEM 2020) is the definition of the cross-border territory. This definition is often related to the availability of data, expected relevance for a certain territory or special interests of certain stakeholders. However, a common rule is that the territory cannot merely be an individual border region in a single Member State but must be a ‘cross-border territory’. It is evident that certain national legislative proposals will mainly affect the relevant national territory. Nevertheless, the idea of assuming a cross-border perspective is that these ‘national’ effects may also cause collateral effects across borders and impact the cross-border region as a whole. Depending on the nature of the dossier, researchers can define the territory as the entire border between two countries and define the cross-border territory as all NUTS 2 or NUTS 3 areas at the border. Another option is to use the geographical boundaries of an existing Euroregion as definition of the border region. This was done in 2017, when the effects of the proposed German car toll were assessed (Unfried and Hamacher 2017). In this case, the territory of the existing Euroregion Maas-Rhine was used, instead of all of the potential cross-border territories at the German/Dutch or German/Belgian border. This made it possible to limit the analysis of the mobility structures, the dissemination of the questionnaire and the ensuing qualitative interviews to a smaller target group. Nevertheless, the findings were meant to be relevant for other border territories as well. In the past, researchers also opted to use the territories as defined in the INTERREG programmes, definitions which differ from those of the Euroregions in the Benelux/Germany. The territories of two programmes were evidently the best choice to assess the effects of certain provisions in the Interreg legislation in 2016 (Van der Giessen 2016). The use of the ‘cross-border doctrine’ meant that this impact assessment could not follow the perspective of one single national government or region. The perspective was ‘cross-border’, meaning that the effects were assessed beyond purely national interests. In theory, taking a cross-border perspective could even mean that negative effects on one part of the cross-border territory (affecting only parts of one Member State) were compensated by overall positive effects on the entire territory. This would

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probably go against the interest of any national or regional government, which is only responsible for its share of the cross-border territory. However, from the perspective of organisations like Euroregions, this could be welcomed. Hence, appreciation of the difference between effects on single-border regions (as a national category) and on cross-border territories (as a bi- or multi-national category) is vital for assuming a true cross-border perspective.

6.3.4 Research Themes, Principles, Benchmarks and Indicators As a next step of the research, the potential effects of certain legislative proposals or measures are assessed using certain themes. The question is: ‘impact on what?’. As Medeiros stated on the effects of territorial cross-border programmes, they do not solely impact the socioeconomic aspects of development, “but also […] environmental, governance and […] the territorial articulation of the border regions” (Medeiros 2016a: 64). The same is true for EU or national legislation or policy measures. ITEM’s approach is not limited to socioeconomic effects; for some of the dossiers, effects on the cross-border labour market and employment, on the competitive situation of companies or on aspects of sustainability are essential. However, legislative proposals can also affect the overall cohesion of a cross-­ border territory beyond economic figures. This means that the question of whether new legislation will improve or hinder the cross-border cooperation of public bodies or private organisations can be of major importance. Regulations can also have negative or positive effects on the existing cross-border governance structures. In short: do proposals contribute to a positive development of cross-border cooperation or not? The assessment of these effects is very demanding, since they are hardly measurable in a quantitative way. Impact on the quality of cooperation or a specific governance structure has to be assessed qualitatively with the help of experts. Since ITEM is part of the Faculty of Law, it shows special dedication to an additional aspect: do legislative proposals (or existing laws) promote or limit the life of citizens in a cross-border territory in terms of the basic principles of European Integration as laid down in the Treaties or in EU legislation? This is particularly decisive given the latest developments in the European Union: the return of border controls initiated by national governments is only one measure with the potential to jeopardize the freedoms of citizens and companies in border regions in particular. This also relates to the notion that cross-border territories are a “test case” for European Integration as such and touches key aspects of the future of the EU. To conclude, the ITEM Cross-Border Impact Assessment features the following themes: 1. Cross-border impact from the perspective of individuals, associations and enterprises living in a certain cross-border territory, correlated with the objectives and principles of European Integration: freedoms, citizenship, non-discrimination 2. The cross-border impact on socioeconomic development/sustainable development of a cross-border territory

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Table 6.1  Examples of principles, benchmarks, and indicators Goals/principles European integration, European citizenship, non-discrimination Regional competitive strength, sustainable development cross-border territory Cross-border cooperation/good governance, Euregional cohesion

Good practice/benchmark No border controls, open labour market, easy recognition of qualifications, good coordination of social security facilities, taxes Cross-border initiatives for establishing companies, Euregional labour market strategy, cross-border spatial planning Functioning of cross-border services, cooperation with organizations, coordination procedures, associations

Indicators Number of border controls, cross-­ border commuting, duration and cost of recognition of qualifications, access to the housing market, etc. At Euregional level: GDP, unemployment, quality of cross-border cluster, environmental impact (emissions), poverty The number of cross-border institutions, the quality of cooperation (in comparison with the past), development of Euregional governance structures, quantity and quality of cross-border projects

Own compilation

3. The cross-border impact on cross-border cohesion and cross-border governance structures of a certain cross-border territory: cooperation with governmental agencies, private citizens, the business sector, etc. Depending on the specific dossier, the effects may be evaluated for all themes or only one or two out of three. One of the important tasks of the researchers is to find appropriate principles and benchmarks for a positive or negative situation/development. The difficulty of doing so will be described in Sect. 6.5. If benchmarks are found, indicators can be formulated for assessing the (potential) effects of a proposed or existing legislative proposal or piece of legislation. One of the crucial problems of the research, so far, has been the lack of cross-border data in many policy fields. Thus, next to offering an in-depth legal analysis of the cross-border situation, the researchers often have to produce their own data. To do so, research teams use surveys, conduct qualitative interviews and, in particular, collect expert judgements. In this respect, the network of practitioners dealing with cross-border issues is vital to the entire impact assessment. In close cooperation with Statistics Netherlands (CBS), questions related to cross-border data form an important corner stone of the annual research. Table 6.1 provides a number of examples of benchmarks and indicators.

6.4

 xamples of and Experiences with the Annual E Cross-­Border Impact Assessment Between 2016 and 2019

6.4.1 The First Round in 2016 The first Cross-Border Impact Assessment carried out by ITEM in 2016 consisted of ten dossiers covering a variety of topics. Researchers primarily investigated national topics that were the subject of much discussion along the Dutch border. A

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large part of the 2016 Impact Assessment therefore related to recently adopted legislation and policy, which posed a challenge to quantifying the effects of the measures analysed. Because of the timing, the studies resembled ex ante assessments rather than ex post assessments. For example, the impact of the then recently adopted Dutch-German tax treaty on the pensions of former cross-border workers could not yet be evaluated on the basis of data (Bollen-Vandenboorn et al. 2016). Several dossiers also dealt with effects of how EU Member States implemented European legislation. One example of this is the dossier that analysed the transposition of the Professional Qualifications Directive after its modernisation through Directive 2013/55/EU. The study indicated that, although the directive was transposed differently for various professions, it was transposed properly, meaning that from a material perspective, well-functioning recognition procedures should be possible in practice (Schneider et al. 2016). This meant that the obstacles found for cross-border workers were more related to administrative routines. An example of a dossier containing a clear ex post analysis of national legislation was the dossier on social security. The study focused on the effects of the Dutch legislation regarding short-term and long-term incapacity for work in a cross-border situation (Montebovi and Klosse 2016). A number of problem areas and possible effects liable to impede free movement whilst threatening social cohesion were identified, including, for example, a lack of knowledge about the reintegration obligations carried by employers and employees in the event of illness and occupational disability. This lack of knowledge could cause employees to receive less support and employers to face financial sanctions from the Dutch Employee Insurance Agency (UWV), potentially discouraging employment of cross-border workers (Montebovi and Klosse 2016). Another dossier focused on the three INTERREG VA programmes at the Dutch border and comprised a survey, a comparative study and in-depth interviews (Van der Giessen 2016). The study found that, due to the new territorial cooperation regulation, European rules on the implementation of INTERREG VA programmes had become simpler. However, this simplification did not always translate in the provisions and national rules of individual programmes, causing it to vary a lot between programmes. Individual programmes could not shed the image of a heavy administrative and untransparent process among stakeholders in the cross-border territory (Van der Giessen 2016). The above only describes the research and outcomes of a selection of dossiers in the ITEM Cross-Border Impact Assessment 2016. In sum, the Assessment contained ten dossiers, the topics of which are listed in Table 6.2.

6.4.2 The Second Cross-Border Impact Assessment in 2017 The 2017 edition also focused on both ex post evaluations of existing legislation and the ex ante identification of desired and/or undesired effects of certain measures on border regions (Unfried and Kortese 2019:475). Ex ante assessments included the dossier on the Commission proposals amending Regulations 883/2004 and 987/2009

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Table 6.2  Themes of the Cross-Border Impact Assessment 2016 No Subject 1. The new NL-DE tax treaty a. labour; b. pension) 2.

3.

4.

5. 6. 7.

8.

Recognition of professional qualifications National application of Directive 2013/55/ EU BE/NL/DE Cross-border cooperation effects of the INTERREG/European territorial cooperation regulation (EU) No 1299/2013 on the programmes (NL/DE/BE) Social security: Illness and disability (NL)

The qualifying foreign tax obligation of section 7.8, Income Tax Act, and EU law (NL) Proposal for a directive amending Directive 96/71/EC (COM(2016) 128 final) (EU) Flexibilisation of the Old-Age Pension Commencement Date Act (NL)

Research questions What are the possible effects of the new tax treaty between the Netherlands and Germany on frontier workers and former frontier workers? How does the recognition of certain significant professions work at the national level for the frontier labour market and what are the biggest effects on frontier workers? What are the effects of the new INTERREG regulation on the management quality of the programmes (EMR, Netherlands-Germany, Flanders-Netherlands)? What are the consequences of the Dutch systems governing illness and disability for the free movement of labour across the border? What is the impact of the Dutch 90% scheme on frontier workers? Is this scheme at odds with European law? Effects of the proposed revision of the EU posting of workers directive on cross-border territories. What are the effects on the position of workers who have accrued both a Dutch General Old Age Pension and a statutory pension in another country? What is the impact of the UWV’s current funding and mandate on the implementation of cross-border employment services?

Cross-border employment services: Effects of the mandate and capacities of the Dutch UWV (NL) 9. Cross-border train transport – Fourth Rail What are the expected effects of the Package (EU) coordination of the allocation and organization of cross-border interlocal public transport? 10. The Belgian toll system for lorries (BE) What are the additional costs for cross-border student project transport for the logistics sectors in Belgium/ the Netherlands/Germany? Source: ITEM Cross-Border Impact Assessment 2016

(Montebovi 2017) and the dossier on the Belgian legislation on the identification of travellers (Adriaensen and olde Scheper 2017). This time, a variety of research instruments was applied. The dossier on the cross-border (im)mobility of students from third countries in the Euroregion Meuse-­ Rhine, for example, adhered to the methodology of the ITEM Cross-Border Impact Assessment while using a mixed-method approach (Hoogenboom and Reinold 2017). As with many dossiers, data had to be produced. To this end, the researchers paired an analysis of the relevant student immigration legislation and policies with a survey and semi-structured interviews. These methods were applied to study whether certain assumptions underlying EU, Dutch and German legislation led to a ‘border region penalty’ (Hoogenboom and Reinold 2017).

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Other teams of researchers also used surveys and interviews for their research: researchers analysing the potential effects of the German car toll on border regions found that drivers originating from the Belgian and Dutch sides of the Euregio Meuse-Rhine perceived the car toll negatively, fearing that it would restrict cross-­ border mobility (Unfried and Hamacher 2017). Furthermore, the dossier showed that the border effects were insufficiently taken into account in the German federal government’s impact assessment. The researchers assessed that the car toll was to have particular impact on legal certainty, certain economic sectors, the regional economy, the environment and regional cohesion (Unfried and Hamacher 2017). Another dossier concerned taxes. The Dutch-German Tax Treaty was studied once again in the 2017 Assessment due to its topicality. This study used detailed practice-based calculations to determine the extent to which Dutch and German frontier workers receive equal fiscal treatment to their colleagues or neighbours under the new treaty (Bollen-Vandenboorn et al. 2017). In conclusion, researchers found that, despite the complexity in achieving full parity via national fiscal and social security systems, the treaty could lead to certain border effects, particularly in the area of sustainable/socio-economic development. For this reason, the team called for more analyses of quantitative and qualitative data and more coherent cross-border data collection (Bollen-Vandenboorn et al. 2017). The full 2017 assessment consisted of six dossiers and two pieces of preliminary research, the topics of which can be consulted in Table 6.3.

6.4.3 The Third Cross-Border Impact Assessment in 2018 Activities for the 2018 Impact Assessment commenced in November 2017, with the survey among ITEM stakeholders and other interested parties running until January 2018. Interesting dossier suggestions were received through the survey as well as via ITEM’s daily activities. As an innovative tool, ITEM for the first time applied a quick scan to analyse a list of policy proposals. It was used for the new Dutch government’s coalition agreement (regeerakkoord) of October 201711 to find out whether certain policy proposals might have special effects on the Dutch border regions and the relevant cross-border territories (Unfried 2018). Two of the announced measures were selected for the 2018 round of the Impact Assessment. The first was the proposal to increase VAT rates for certain products, such as vegetables and fruit. The other concerned a proposal for a pilot project to differently regulate the production of cannabis. After screening of the submitted dossiers and subjects, seven dossiers were ultimately selected, six of which materialised in the summer of 2018. Again, the Assessment contained a balanced list of ex ante and ex post cases and of EU, Dutch and German legislation. In some dossiers, students played a role in conducting the research. One dossier in particular was produced by a student group.  The Dutch coalition agreement was presented on 10 October 2017. https://www.kabinetsformatie2017.nl/documenten/publicaties/2017/10/10/regeerakkoord-vertrouwen-in-de-toekomst

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Table 6.3  Themes of the Cross-Border Impact Assessment 2017 No. Subject Dossiers 1. The potential effects of the German toll on border regions 2. Dutch-German Tax Treaty 3. 4.

Social security

Specification Research focused on the potential effects of the proposed German toll legislation Follow-up to the ITEM Cross-Border Impact Assessment 2016 by comparing the income situations of frontier workers (Dutch and German), their neighbours and colleagues Research focused on the ex ante analysis of the proposed amendments to EU Regulation No 883/2004 and 987/2009 Analysis and evaluation of European and national student immigration policies from a Euregional perspective

Cross-border (im)mobility of students from third countries in the Euroregion Meuse-Rhine 5. Belgian passenger name Dossier research focused on evaluating the potential impact records regulation of the proposed Belgian measure of processing passenger name records on cross-border mobility Analysis of non-resident workers in the Netherlands as of 1 6. The qualifying foreign December 2014. The purpose of the research is to provide an taxpayer obligation (‘the estimate of the potential cross-border impact of the 90% rule’): a quantitative ex ante impact assessment qualifying foreign tax liability, also known as ‘the 90% rule’, which entered into force on 1 January 2015 Preliminary research by student teams 1. Euregional mindset in two A study of the European mindset of citizens in the Euregions Euroregions Meuse-Rhine and Rhine-Meuse-North Study of how businesses in Limburg are preparing for the 2. Ex-ante analysis of the effects of the General Data 2018 legal requirements for data protection. Protection Regulation in Limburg

Source: ITEM Cross-Border Impact Assessment 2017

Unexpected results again underlined the necessity of regulatory impact assessment. This was true, for instance, for the research on Dutch VAT (Cörvers and van Oosterhout 2018). Many stakeholders in Dutch border provinces expected relevant disadvantages to arise for Dutch supermarkets and other shops near the border. This was based on the assumption that many products were already much cheaper on the German side and that consumers would respond heavily to further price differences. However, the research found that negative effects along the entire border were not so evident. The conclusions pointed towards a rather small impact of price changes on the cross-border spending behaviour of consumers, given the existing price differences on both sides of the border and the often-large price differences within the Netherlands between, for example, various supermarket chains (Cörvers and van Oosterhout 2018:23). Nevertheless, the dossiers again revealed the general problem of data collection. In this case, cross-border data on certain streams – such as the shift of purchasing power across the border  – were not part of the standard data produced by national statistics offices. Likewise, the case of the qualifying foreign taxpayer obligation (‘the 90% rule’) showed how difficult it is to identify how many cross-border workers are impacted by certain new rules. The case of the German

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Table 6.4  Themes of the ITEM Cross-Border Impact Assessment 2018 No. Subject Specification Dossiers 1. Exploring the cross-border effects of The dossier explores the potential cross-border the low VAT increase in the Netherlands effects of the increase of the lower VAT rate in the Netherlands Researchers examined trends over the 2013– 2. The qualifying foreign taxpayer 2016 period to identify any notable changes in obligation (‘the 90% rule’): A preliminary ex post impact assessment the number and composition of non-resident employees in the Netherlands since the introduction of the 90%-rule 3. Regulations on retirement age NL/BE/ The dossier consists of an analysis of the border DE: A multidisciplinary analysis effects of different national regulations on retirement age The dossier examines in depth the cross-border 4. Baukindergeld (a special German premium for family building or buying a effects of the measure and explores possible solutions to improve the legal regime for house or apartment) frontier workers The dossier assesses the position of non-­ 5. The social security of non-standard standard workers by analysing existing workers: A national and European legislation on social security (ex post) challenge Student dossiers The dossier comprises an ex ante assessment of 6. The potential effects of the regulatory pilot experiment with a closed cannabis the cross-border effects of the proposed Dutch chain on the Euroregions Meuse-Rhine pilot project on legal cannabis cultivation and Rhine-Meuse-North Source: ITEM Cross-Border Impact Assessment 2018

Baukindergeld confirmed a general problem of national policy-making: the German government had not carried out a profound analysis of whether the measures would also apply to cross-border workers living in Belgium or in the Netherlands (Niesten 2018). Table 6.4 summarises the main themes studies in the ITEM Cross-Border Impact Assessment 2018.

6.5

 pecific Problems: Defining the Territory, Principles, S Objectives, Indicators and Relevant Data

It is practical to limit the assessment of the impact of a measure like the German Autobahn toll to a specific cross-border territory (such as one Euroregion), so as to illustrate the effects with one concrete example. By doing so, the empirical research can focus on the behaviour of car drivers or consumers in a particular territory and the expected impacts. More complex are national measures like a special tax regulation or a change in pension legislation. While one can also define the territory within which the effects should be assessed, data collection for this assessment cannot be confined to current data merely from the cross-border territory itself. After all, not all cross-border workers affected by a certain measure  – a pension measure, for example – still live in that territory. Thus, there are direct effects on persons or companies that transcend the geographical boundaries set for the assessment. Hence,

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researchers tried to include data also from groups who did not, strictly speaking, live or work in the defined territory but were nevertheless affected by the effects of cross-border labour. It is also evident that so much as an awareness of disadvantages, even of former cross-border activities (of individuals or companies), can indirectly have negative effects on specific cross-border territories. Another rather complex methodological question is what we perceive to be a ‘positive’ or ‘less positive’ situation in a border territory. What can be considered a benchmark for positive or negative effects? The individual researchers have to define these benchmarks for all of the three themes. Even for socioeconomic objectives, the overall objectives are not as clear as perhaps expected. Of course, higher employment rates, increased investments by companies or greater economic growth seem to be undisputed objectives.12 However, it is not clear, for instance, whether all of the national or regional partners in a cross-border territory agree on the same objectives for the allocation of new jobs. As already mentioned, a strict cross-border perspective includes the possibility that some parts of a cross-border territory benefit more and some less from certain measures or pieces of legislation. This means that the objectives that national or regional governments formulate for their own border regions may diverge from the objectives formulated for the entire cross-­ border territory to which these regions belong. We expect cross-border organisations, such as Euroregions (such as that exist in the Benelux/Germany area) to formulate the aims, targets or principles of a sound cross-border situation in a more consistent way. Their strategies or strategic programmes are a valuable source for the collection of cross-border benchmarks. What are the objectives of a positive cross-border situation in the eyes of cross-border bodies? What, to them, are positive developments in the labour market or in terms of sustainable economic development? As already outlined, the impact assessment should be carried out from a cross-border perspective. This is likely to constitute a problem in cross-border regions where cross-border territories are not represented by specific cross-border authorities or organisations. Even regarding the German/ Dutch/Belgian border, the number of strategic cross-border documents is rather limited. This means that researchers have to rely on objectives and principles outlined by single-border regions, national governments or the EU. Obviously, where the basic principle of European Integration (e.g. the four freedoms) is concerned, the principles and objectives are formulated in EU Treaties or by the European Court of Justice, or they can be found in individual directives and regulations, as is the case with the recognition of qualifications or the coordination of social security. In addition, good practices found in other cross-border territories can also be used as a benchmark if they refer to a certain theme, e.g. the quality of cross-border cooperation between public bodies. The question of cross-border cooperation is indeed the most challenging to benchmark. How can we define the quality of cooperation across the border? What is the notion of a sound cross-border  A closer look suggests that even the ‘indisputable’ objective of economic growth could be called into question in light of sustainable development and climate change. The question of whether the expansion of airports and air traffic is a positive or negative development is a case in point.

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governance system with well-functioning cross-border networks and organisations? So far, there has been a lack of qualitative indicators to conduct this type of assessment in a comparative way. In the future, ITEM will put more emphasis on the formulation of specific qualitative indicators on cross-border cooperation and governance. From the experiences of the past years, it has become evident that there is a general lack of qualitative data. This means that data has to be produced explicitly for a specific cross-border territory. More instruments, such as expert surveys and expert workshops, are needed. Finally, the lack of quantitative data is another constant factor when conducting Cross-Border Impact Assessments. As indicated in the case of the VAT increase, there is a lack of data with respect to cross-border streams of economic activities, specific data on the labour market, cross-border investments, mobility of companies and cross-border transport streams. ITEM researchers repeatedly face problems finding relevant data on cross-border pensions and tax-related issues. In the Impact Assessment of 2019, a study was dedicated to the lack of useful cross-border data, assessing its effects on carrying out sound analyses of EU and national policies.

6.6

 ross-Border Impact Assessment: Creating a Network C in Various Member States

We have concluded that neither the European Commission nor the Member States are at the moment conducting regulatory impact assessments with the aim to better analyse potential effects for cross-border territories. The European Commission has highlighted the ITEM assessments as ‘best practice’ in its 2017 Communication on border-regions (EC 2017: 8). As already mentioned, the Dutch government has initiated an internal debate (ongoing in the summer of 2019) on an appropriate tool to better integrate border effects into their regulatory impact-assessment routine. Recently, ITEM has started a dialogue with other ‘border institutes’ in the TEIN network to agree to a joined approach. In 2020, a  joined project is conducted to assess the effects of the national measures during the Covid crisis.13 From the start, the intention was to develop an instrument that could be applied in many cross-border territories of the EU. It is obvious that results from assessments only carried out on the Benelux/Germany borders are too limited to spark EU legislation on the regulatory impact assessment process. Only if additional assessments of other cross-border situations are carried out can they make an important contribution to EU law and policymaking. Hence, there is a need for a network approach. The question is how to create a network of institutes and experts in

 The Transfrontier Euro-Institut Network (TEIN), formed in 2010, brings together 15 partners from 9 border regions in Europe. Its unique feature is that it consists of universities, research institutes and training centres which are dedicated to the practical business of cross-border cooperation in Europe. See: http://www.transfrontier.eu/. A TEIN workshop on 10 October 2019 is dedicated to cross-border impact assessment.

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different Member States (cross-border territories) with sufficient capacity to carry out their own impact assessments on a regular basis? ITEM’s approach can be used as a starting point. The task at hand would be to reach a common understanding on a methodology that allows partners from different cross-border territories to adapt the instruments to their local/regional circumstances. As already mentioned, the Euroregions (as cross-border organisations) at the German/Dutch/Belgian border are strong, which is not the case for Euroregions throughout the EU. Situations also differ widely with respect to the availability of indicators, cross-border data and expert knowledge. Despite these differences, collaboration between different institutes could make a decisive contribution to the furthering of regulatory impact assessment. One obvious reason to move ahead is also an important lesson from ITEM’s work so far: the expertise on cross-border impact can be found in cross-border territories rather than at the EU or national level.

References Adriaensen, olde Scheper (2017) Belgian passenger name records regulation, ITEM Cross-border impact assessment 2017, Dossier 5, Maastricht. https://www.maastrichtuniversity.nl/research/ institutes/item/research/archive/archive-item-cross-border-impact-assessment#cbia2017 Bangma K (2014) Grenseffectentoets 2014: Update van de toets van april 2013. Panteia, Zoetermeer Bollen-Vandenboorn et  al (2016) Tax treaty Netherlands-Germany: pension. ITEM, Maastricht. ITEM Cross-border Impact Assessment  – Dossier 1B, Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/archive/ archive-item-cross-border-impact-assessment#cbia2016 Bollen-Vandenboorn, A. et  al (2017) Tax treaty Netherlands-Germany. ITEM, Maastricht. ITEM Cross-border Impact Assessment 2017, Dossier 2, Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/archive/ archive-item-cross-border-impact-assessment#cbia2017 Cörvers F, van Osterhout K (2018) Exploration of the cross-border impact of an increase in the low VAT rate in the Netherlands. ITEM Cross-border Impact Assessment 2018 (Dossier 1), Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/ item-cross-border-impact-assessment#cbia2018 European Commission (2015) Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions ‘Better regulation for better results – An EU agenda’. COM(2015) 215 final of 19 May 2015 European Commission (2017) Communication from the Commission to the Council and the European Parliament, Boosting growth and cohesion in EU border regions Brussels. COM(2017) 534 final of 20 September 2017 Hoogenboom A, Reinhold J (2017) Cross-border (Im)mobility of students from third countries in the Euregio Meuse-Rhine. ITEM Cross-border Impact Assessment 2017, Dossier 4, Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/archive/ archive-item-cross-border-impact-assessment#cbia2017 ITEM (2020) Cross-border impact assessment 2020 manual. https://itemcrossborderportal.maastrichtuniversity.nl/p/homepage Kortese L (2018) De Grensoverschrijdende Mobiliteit van Gespecialiseerde Verpleegkundigen IC –Nederland/België, Maastricht, Report for the Dutch Ministry of Interior and Kingdom Relations. https://www.maastrichtuniversity.nl/sites/default/files/item_lkortese_de_ grensoverschrijdende_mobiliteit_van_gespecialiseerde_verpleegkundigen_ic_nederlandbelgie_20180219.pdf

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Medeiros E (2016a) Territorial impact assessment and public policies: the case of Portugal and the EU. Public Policy Port J 1(1):51–61 Medeiros E (2016b) 20 years of INTERREG-A in inner Scandinavia, online English version, Hamar. https://ec.europa.eu/futurium/en/evidence-and-data/ report-territorial-impact-assessment-cross-border-cooperation-programmes Montebovi S (2017) Social security. ITEM Cross-border Impact Assessment 2017, Dossier 3, Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/archive/ archive-item-cross-border-impact-assessment#cbia2017 Montebovi S, Klosse S (2016) Social security: illness and disability. ITEM Cross-border impact assessment 2016, Dossier 3, Maastricht. https://www.maastrichtuniversity.nl/research/ institutes/item/research/archive/archive-item-cross-border-impact-assessment#cbia2016 Niesten H (2018) Baukindergeld, (Building benefit) ITEM Cross-border Impact Assessment 2018, Dossier 4, Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/ item-cross-border-impact-assessment#cbia2018 OECD (2014) What is impact assessment? Working Document based on “OECD Directorate for Science, Technology and Innovation (2014), “Assessing the Impact of State Interventions in Research – Techniques, Issues and Solutions”, unpublished manuscript. https://www.oecd.org/ governance/regulatory-policy/ OECD (2018) Regulatory policy outlook, 66. https://read.oecd-ilibrary.org/governance/ oecd-regulatory-policy-outlook-2018_9789264303072-en#page3 Schneider et  al. (2016) Recognition of professional qualifications. ITEM Cross-Border impact assessment 2016, Dossier 2, Maastricht. https://www.maastrichtuniversity.nl/research/ institutes/item/research/archive/archive-item-cross-border-impact-assessment#cbia2016 Unfried M (2018) Effecten voor grensregio’s, ITEM’s quick scan van het Nederlandse regeerakkoord 10 oktober 2017. Quick Scan of the Dutch Coalition agreement 2017, Maastricht. https://www.maastrichtuniversity.nl/nl/nieuws/ quick-scan-van-nederlandse-regeerakkoord-effecten-voor-grensregio%E2%80%99s Unfried M, Hamacher B (2017) The potential effects of the German car toll on border regions. ITEM cross-border Impact Assessment 2017, Dossier 1, Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/archive/ archive-item-cross-border-impact-assessment#cbia2017 Unfried M, Kortese L (2019) Cross-border impact assessment as a bottom-up tool for better regulation. In: Beck J (ed) Transdisciplinary discourses on cross-border cooperation in Europe. Peter Lang, Brussels, pp 463–481 Van der Giessen M (2016) Cross-border cooperation: a study of INTERREG programmes in the Dutch border Regions. ITEM Cross-Border Impact Assessment 2016, Dossier 3, Maastricht. https://www.maastrichtuniversity.nl/research/institutes/item/research/archive/ archive-item-cross-border-impact-assessment#cbia2016 Vink et  al. (2017) The qualifying foreign taxpayer obligation (“90% rule”): a quantitative ex-­ ante impact assessment. ITEM Cross-border Impact Assessment 2017, Dossier 6, Maastricht. https://www.maastrichtuniversity.nl/sites/default/files/item_1/item_cross-border_impact_ assessment_2017_dossier6_the_qualifying_foreign_taxpayer_obligation_90_percent_rule_a_ quantitative_ex-ante_impact_assessment.pdf Martin Unfried  (1966) obtained a Master in Political Science at the University of Erlangen/ Germany. He has been working in the Netherlands since 1997 with the European Institute for Public Administration (EIPA) as an expert on EU environment and regional polies. He joined Maastricht University in 2016 as senior researcher and project leader for the annual regulatory impact assessment of cross-­border territories. Recently, he conducted studies on cross-border questions inter alia for the Dutch Province of Limburg, the Dutch Ministry of Internal Affairs and the European Commission (DG Regio). In 2019, he was also involved in an ESPON project related to impact assessment of territorial programmes.

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Lavinia Kortese  LL.M. completed her PhD in 2020 and is a researcher at ITEM and Maastricht University’s Faculty of Law. She holds a Bachelor of Arts (University of Amsterdam) and a Master of Laws (Maastricht University). The central focus of her PhD research is on examining the most important international legal instruments and cooperation initiatives and their respective competences on the recognition of professional and academic qualifications both at the international level and upon implementation into selected Member State’s legal orders and to assess their coherence. Anouk Bollen-Vandenboorn  is appointed as Professor in Cross border Pension Tax Law at Maastricht University and is affiliated at the Department of Tax Law since 1996. She graduated in Tax Law at the same university (1991–1995) and defended her PhD in 2004. She is Deputy Judge at Rechtbank Zeeland-West-­Brabant and member of the Disciplinary Board of the NOAB. She is Director of Double Degree Master Programme in International and European Tax Law. Since 2015 she is director of ITEM (Institute for Transnational and Euregional cross border cooperation and Mobility).

7

Cross-Border Territorial Impact Assessment Gyula Ocskay

Abstract

The solution for cross-territorial impact assessment (CBC TIA) developed by the Central European Service for Cross-Border Initiatives (CESCI) can be classified as a bottom-up model  – unlike the TIA tool of the European Union (cf: EC, Assessing territorial impacts: operational guidance on how to assess regional and local impacts within the Commission Impact Assessment System, European Commission, Brussels, SWD(2013) 3 final, 2013) and those designed in the framework of the ESPON programme (like ESPON EATIA, INTERCO. Indicators of territorial cohesion. (Draft) Final Report. Part B Report, 2013) and similarly to the TARGET TIA by Medeiros (Territorial Impact Assessment (TIA). Concept, Methods and Techniques, Centro de Estudos Geográficos da Universidade de Lisboa (CEG)  – Instituto de Geografia e Ordenamento do Território (IGOT). Lisbon University, Lisbon, Reg Stud Reg Sci 2(1):97–115) and the TIA of the ITEM (since 2016, annually), which are gained from daily experiences of cross-­ border cooperation. The CESCI CBC TIA focuses on processes facilitating the gradual elimination of the border effects and the shared exploitation of the territorial potential, territorial capital of the divided border area. These processes can be detected by a multidimensional toolkit including the mapping of the perceptions of Otherness and the territorial behaviour of the border people, and the analysis of the forms and embeddedness of cross-border governance. Consequently, this model does not contain a universal formula, but rather, it establishes a set of quantitative and qualitative indicators describing how, and to what extent, the assessed activities, projects and investments contribute to an eased permeability of the administrative borders.

G. Ocskay (*) Central European Service for Cross-Border Initiatives (CESCI), Budapest, Hungary e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_7

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Keywords

Territorial impact assessment · Borders · Cross-border cooperation · Territorial integration · Borderscape

Precisely because the closed or open character of the border largely depends on human interaction and interpretation, the border itself creates room for reinterpretation. It is time for a turnaround in which the border is seen not as the terminus, but the departure point for a new development. (Houtum and Eker 2017: 50)

7.1

Introductory Thoughts

This study is about two dimensions of inherent human curiosity  – manifested in space and in time. In space, since, similarly to animals, human beings follow territorial behavioural patterns too. It means that people are creating and eradicating barriers around their individual and collective territories within which they are ‘at home’ (i.e. to protect their ownership), while outside of these territories, there is something different, something strange that is both terrifying and desired (i.e. to explore, to experience the Otherness) to them (see e.g. Halls 1968; Houtum et al. 2005; Rajaram and Grundy-Warr 2007; Agnew 2008; Scott 2014; Faludi 2018). This desire is the engine of the exploration drive, the curiosity: ‘What is on the other side? What is to be found “outside”?’ In time, as every human being wishes to see the results of his/her activities. It is somehow about the prolongation of their activities, and, ultimately, of their own life. Consequently, when speaking about territorial impact assessment, it is always about people’s boundaries to maintain and to demolish – both in space and time. However, the question is more radical in the field of cross-border cooperation: it is a genuine territory of border dwellers’ life confined to territorial limits where the spatial (and timely) limitations of their existence manifest. The reflections compiled in the study are based on the experiences of a 20-year-­ long history spent with cross-border cooperation (CBC) activities, started in 1999 when the re-construction of the Mária Valéria Bridge between Esztergom (Hungary) and Štúrovo (Slovakia), ruined during World War II, commenced. As the coordinator of the cross-border activities of the municipality of Esztergom (in the framework of the Ister-Granum Euroregion and the eponymous European Grouping of Territorial Cooperation (EGTC) and later on as Secretary General of the Central European Service for Cross-Border Initiatives (CESCI), together with my skilled colleagues, we have always been looking for better-based tools and solutions facilitating high-quality CBC in Central and Eastern Europe, where borders are still considered as a set of deep scars of most recent history. The experiences referred to above include scientific research, cross-border integrated spatial planning, programming and evaluation activities, development and implementation of integrated cross-border projects and the creation and

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management of cross-border partnerships and governance structures.1 As it will be proven below, all these experiences form a comprehensive picture where all components have their own very important mission. The study will not offer a final solution to the challenges of the issue, but, rather, it intends to contribute to the EU level discourse on a more evident approach to cross-border TIA. In order to make the approach, applied at CESCI, understandable, further classification and clarification are needed. This classification and the necessary clarification are to be found in Sect. 6.2, while in Sect. 6.3, the reader will be provided with methodological and practical points of view on the application of CBC TIA methods.

7.2

Clarifications and Classifications

7.2.1 On Territorial Impact Assessment – From the Ground In general terms, territorial impact assessment is a procedure and a tool applied in parallel with the development of EU policies. It forms part of the Impact Assessment ‘toolkit’ introduced in 2002 and adapted to all regulatory acts of the European Union (Medeiros 2015: 97; Zonneveld and Waterhout 2009: 13).2 Its introduction cannot be separated from the principles of ‘good governance’ promoted by the White Paper on Governance in 2001  – giving special emphasis on effectiveness, policy coherence and greater flexibility (EC 2001: 10; 13). Obviously, the approach applied by the White Paper has a strong top-down character: it focuses on the fine-­ tuning of EU policies that the member states and the regional and local actors should adapt to.3 Forming part of the so-called Better Regulation Toolbox, TIA ‘is generically referred to as the procedure (or method) to evaluate the likely impact of policies, programmes and projects on the territory, highlighting the importance of the geographic distribution of consequences and effects and considering the spatial developments in Europe’ – as it is stated on the website of the European Commission.4 The Impact Assessment Guideline summarises the mission as follows: ‘Impact assessment is a set of logical steps to be followed when you prepare policy proposals. It is a process that prepares evidence for political decision-makers on the advantages of possible policy options by assessing their potential impacts’ (EC 2009: 4).

1  The majority of the publications presenting these experiences are available at the home page of CESCI (www.cescinet.eu). 2  For further details on the prehistory of territorial impact assessment, please refer to Evers (2011), Medeiros (2015) and Faludi (2018). 3  ‘In the same way, decisions taken at regional and local levels should be coherent with a broader set of principles that would underpin more sustainable and balanced territorial development within the Union’ (EC 2001: 13). 4  https://ec.europa.eu/knowledge4policy/territorial/topic/regional_en

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The term ‘territory’ in these documents refers to the differences observable between the European regions: ‘Assessing territorial impacts helps to identify whether a policy option risks having a large asymmetric territorial impact, also known as an ‘outlier’ impact’ (EC 2013: 2) [emphasis in original]. From this perspective, the key notions are regional/territorial specificities, sensibility, equal access, disparities and intensity of policy application (Zonneveld and Waterhout 2009; Evers 2011; EC 2013). The EU level policy documents and the majority of the relevant ESPON projects equally focus on the diverse impacts that EU policies can have on different types of regions (mountainous, sparsely populated, maritime, metropolitan, cross-border, etc.). The objective is to unfold potential risks of unexpected or unwanted consequences of the policies to set up or the planned regulations to adapt on some types of territories within the EU. To sum it up, TIA is a top-down tool where the main goal of the assessment is to unfold the ‘local’ impacts of a new community-level provision or an EU-funded programme. The TIA procedures implemented at the level of the European Commission and the toolkit developed by different ESPON projects (like TEQUILA, STeMA, ARTS, etc.)5 concentrate on the territorially sensitive implementation of European policies, rules and programmes and are designed to detect the potential impacts at EU 28 level. Our approach has a different logic: we concentrate on the phenomena and processes detected at local-regional level in a certain geographic area (in a cross-border region) without references to the diversity of European regions (one can consider it as a ‘case-study approach’ – with some limitations). There are further attempts known which address territorial impacts from a bottom-­up (regional) perspective. The Institute for Transnational and Euregional cross border cooperation and Mobility (ITEM) of Maastricht University realised the first cross-border TIA project in 2016 (see Chap. 5). The results of their projects implemented since that time are summarised in a series of annual reports. The institute systematically analyses the potential impacts that different national and EU level provisions and laws targeting, for example, taxation, social security and cross-­ border mobility issues (ITEM 2016, 2017, 2018) can have on a certain geographic area (i.e. the border area of Germany, Belgium and the Netherlands). This initiative can be considered bottom-up in the sense that the scope of the analysis is not EU-wide, it does not deal with the potential consequences of the analysed legal documents on diverse areas of the Union. At the same time, our approach has a different perspective: what we are interested in is not the (ex ante predicted) impacts of a legislation but the territorial impacts of cross-border actions (i.e. developments, projects, activities). From this perspective, our model is closer to further two bottom-­up solutions. The Northern Irish Centre for Cross Border Studies (CCBS) has published a series of guides with the mission to improve the quality of cross-border projects along the Irish-Northern Irish border. Two of these guides (one of them was drafted together with the experts of the EuroInstitut of Kehl) are dedicated to the assessment 5  The relevant ESPON projects and their results considering TIA are analysed by Evers (2011), EC (2013) and Medeiros (2014).

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of the effects (impacts) of these projects (Taillon et al. 2011; CCBS 2015). Both guides give a comprehensive formal description on the assessment methods and procedures of the social, economic, environmental and cooperation effects of a cross-border project. The other model has been developed by Eduardo Medeiros who presented his own TARGET TIA tool in several of his recent publications (e.g. Medeiros 2014, 2015, 2019). Similarly to the previously mentioned one, this model also goes beyond the terminology and the set of indicators of the general European discourse when applying a bottom-up approach and placing the specific characteristics of cross-border regions and CBC in the focus of the investigations. The multidimensional model includes 34 indicators grouped under nine components along two key axes (barrier effect reduction and territorial capital valorisation), thus reflecting the major challenges of cross-border integration. Let us mention here that the most recent example of this approach is the ESPON CBC TIA project whose draft Scientific Annex (ESPON 2019) contains a set of indicators (partly) reflecting the real characteristics of cross-border developments and cooperation. At the same time, our approach is a bit different from the above three models when deliberately ignoring several indices referring to the economic performance, environmental and social conditions of the border areas. To conclude our clarifications, the position of our approach can be classified within a 2×2 matrix presenting the different TIA tools according to the direction and the basis of their approach. CESCI’s TIA is a bottom-up, territorially based approach similar to the models of the CCBS, the TARGET TIA and the ESPON CBC TIA (Fig. 7.1).

7.2.2 O  n the Place and Function of Cross-Border TIA Within the Intervention Logic of Cross-Border Actions On the place and function of cross-border TIA within the intervention logic of cross-border actions, TIA has its own place in the intervention logic of integrated cross-border actions (see Fig. 7.2).6 As Medeiros (2014) highlights, the main objectives of cross-border programmes are ‘(i) to reduce the barrier effect and (ii) to valorise the border regions territorial capital’ (Medeiros 2014: 105).7 Still, these two missions are hard to realise due to the separating effects of state borders: as the Communication titled Boosting Growth and Cohesion in EU Border Regions points out, ‘border regions generally perform

6  The generic term ‘action’ is used here for describing the complexity and diversity of cross-border programmes, projects and other development and cooperation activities. 7  The authors of the ex post evaluation case study of the Hungary-Slovakia Cross-Border Cooperation Programme 2007–2013 put it similarly when defining the topics of the study: ‘programme’s main achievements, the cooperation mechanisms put in place, and their effects in terms of reducing barriers to cooperation and taking advantage of common opportunities’ (EC 2016b: 1) [emphasis added].

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Fig. 7.1  Classification of different TIA models (Source: own design)

less well economically than other regions within a Member State’ (EC 2017: 4); ‘many aspects of border life are over-complicated and burdensome’ (EC 2017: 5); and (based on the results of a study) ‘these regions could on average be potentially 8% richer if all current barriers were removed and a common language was used by all’ (EC 2017: 6). Hence, barrier effects and the limitations against the exploitation of territorial capital are interdependent factors: border regions usually cannot exploit their territorial potential (let us now simplify the definition of territorial capital8) because of the proximity of the administrative borders and vice versa, the administrative border matters unless the complementary advantages of the two adjacent regions are exploited in an integrated manner. So, with a view to changing these unfavourable conditions, the whole cross-border territory should be developed in an integrated way. In this road, the first step is to thematise the cross-border territory as a whole through an integrated cross-border development plan, strategy or programme.9 A recurring problem of cross-border planning is the lack of statistical data and the incompatibility/incommensurability of statistics of adjacent countries. Without reliable and evidence-based territorial data, the conclusions of the strategy will not  The limits of this study do not make it possible to give a critical analysis of cross-border interpretation of territorial capital. 9  During the recent years, CESCI has developed its own methodology used for designing integrated cross-border strategies called cross-border cohesion-based planning. The name of the methodology stems from the fact that during the planning process only those factors are taken into account which enhance or hinder stronger cross-border territorial, economic and social cohesion. The methodology has been applied in a half a dozen cases at integrated planning of EGTCs and in the design and evaluation of four cross-border programmes. 8

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Fig. 7.2  The intervention logic of cross-border actions (Resource: own design)

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be relevant, and the implementation of the strategy cannot be monitored. And here comes TIA into play. TIA should ensure this evidence behind the strategy by showing and analysing the expected/realised territorial impacts of the cross-border strategy or programme. Since very often the data for assessment are just not available, efforts have to be made to gain them from the ground through cross-border research. Another aspect and risk factor of successful cross-border actions is to guarantee the implementation of the strategy which can be provided by cross-border governance structures enabled to act and to sustain the results on both sides of the border. Definitely, this necessitates both legal harmonisation and capacity building. These components complete the comprehensive picture on the complexity of cross-border developments where TIA has a key role. Obviously, within the territory of the European Union, this picture should be built into the larger strategic framework of European Cohesion Policy which targets strengthened economic, social and territorial cohesion of the EU. At the same time, cohesion at European level cannot be enhanced without eliminating the barrier effects of the individual borders and the strengthening of the cross-border integration (cohesion) of single borderlands. Since the very topic of this volume is the assessment of territorial impacts, territorial is the key aspect of cohesion to be taken into account. Regardless of the evolution of the term since the adoption of the Torremolinos Charter in 1983 and, especially, since 2007 when territorial cohesion was built into the regulative background of the EU (included in the Treaty of Lisbon), after the adoption of the Territorial Agenda (EC 2007b) and the elaboration of the Green Paper on Territorial Cohesion (EC 2008), still there is no clear definition thereof. Those attempts made in the frameworks of the ESPON programme (EATIA, KITCASP and, most recently and in a more detailed way, INTERCO) targeted the definition of the term at European level. The indicators selected, for example, within the framework of INTERCO have nothing to say on local/regional integration; the majority of them reflect NUTS II or NUTS III level (or even national, macro-economic) processes (ESPON 2013: 16). Therefore, these studies cannot be applied to measure cross-border territorial cohesion within a borderland (i.e. a programming region). Some attempts are known to define and measure cross-border territorial cohesion at regional level. The most advanced model is the Øresund integration index10 developed in 2013 for detecting and measuring the integration processes between the two shores of the Øresund strait across the new bridge. This index is a composite tool including five sub-indices (labour market integration, real estate market, business realms, culture, transport and communication) making intelligible how the level of cross-border integration can be detected. Another example is the cross-border regional innovation integration model developed by the OECD based on a 10-factor scaling system – with a special sectoral focus, namely innovation. (OECD 2013) This model is rather qualitative in character, and it takes into account several factors defining the innovation environment. 10

 http://www.orestat.se/

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Sara Svensson and Carl Nordlund developed their ‘cross-border integration index’ based on social relations and cross-border connectivity (i.e. the ‘share of actors with cross-border connections’) (Svensson and Nordlund 2015: 384). Similarly, Decoville and Durand also consider social relationships as a key element of cross-border integration. In their opinion, when assessing the integration of a borderland, the researcher should concentrate on ‘what is currently happening in terms of functional interactions’ and ‘what people think about their neighbours’ (Decoville and Durand 2018: 137). One of the most influential thinkers of border studies, Henk van Houtum, in his doctoral thesis analysed the behaviour of entrepreneurs in a cross-border context. The research method of the investigation (called INTERFACE) demonstrated that the entrepreneurs make decisions on their business activities based on the mental distance (and not the physical one) of the other side of the border. In this context, trust plays a crucial role (Houtum 1998). The last examples represent an alternative approach to TIA which is based on a new concept of borders, borderlands and territories.

7.2.3 On the Nature of Cross-Border Territories The above-mentioned alternative approach can give an answer to the question: why cross-border cooperation programmes have such a weak cross-border effect? Apart from the low budget, these programmes barely result in really integrated sustainable developments. It was so during the pre-accession, so-called Phare period in Central and Eastern Europe (CEE) (EC 2007a), and the situation has not changed much during the last European Territorial Cooperation (ETC) period, either (EC 2016a). As the Hungary-Slovakia case study of the latter evaluation points out, ‘The partnerships were maintained only for the duration of the projects, and the developments were mostly attributable to EU funding’ (EC 2016b: 17). Furthermore, ‘[m]ost projects have been implemented in isolation from each other’ (EC 2016b: 24). It can be considered as a rather general rule what Scott summarises as follows: ‘in less successful cases, cross-border projects have often merely served to enhance local budgets without stimulating true co-operation’ (Scott 2014: 12). One of the reasons of this failure is: ‘CBC within the EU is embedded in Cohesion Policy and highly territorialised; spatially defined indicators, goals, remits and responsibilities create their own barriers to interaction’ (Scott 2014: 4). To put it differently, the mandatory list of indicators and the territorialised approach to CBC programmes hinder real territorial integration. If anyone would like to resolve this paradox, the terms ‘territory’, ‘borders’ and ‘borderlands’ must be re-defined. In one of his latest publications, Andreas Faludi, leading theorist of European spatial planning since the 1980s, gives a reference of the term ‘territory’ as ‘an act of power’ (Faludi 2018: 32) which ‘refers to the assertion by any organisation that an area of space is under its influence’ (Faludi 2018: 32). By connecting the term ‘territory’ to modernity, Faludi claims (in compliance with such influential liberal thinkers as John Stuart Mill or Lord Acton) that territory is an innovation of the

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modern democratic nation state: ‘Territoriality means states securing their borders and exercising jurisdiction within them. In defining territory, jurisdiction comes first’ (Faludi 2018: 43). Agnew calls this model of statism ‘the territorial trap’ (Agnew 1994), while Faludi thinks that ‘territorialism assumes that we live in boxes. It further assumes that each territory is an organic whole – my country, my fatherland – and that it is the duty of any sovereign government to defend it, including the people who fill its territory with life’ (Faludi 2018: 70). The terms trap, the box means that human beings live in a world of ‘territorial fixity and a set of binary oppositions (centre/periphery, internal/external, etc.)’ (Brambilla 2015: 2). ‘This kind of territorialization as a prescriptive form of regionalization regulates the inclusion and exclusion of actors and utilities’ (Werlen 2005: 54). If anything, CBC is commissioned to exceed this fixity, these binary oppositions and the world of exclusion/inclusion since borders are the marks of separation, of difference: ‘The border is not a neutral line of separation; borders between nation-­ states demarcate belonging and nonbelonging and authorize a distinction between norm and exception’ (Rajaram and Grundy-Warr 2007: ix). When initiating CBC, local actors challenge this narrative and re-shape hard territories to ‘soft spaces’: ‘transboundary territories can be understood as soft spaces of governance’ (Medeiros 2015: 99). The recently developed concept of soft spaces cannot be separated from the emergence of relational geography and the influence that the English publication of Henri Lefebvre’s Production of space (Lefebvre 1991) had on human geography in the early 1990s. According to Lefebvre, space is a social construction which is built upon the basis of people’s perceptions, but which re-impacts our daily lives, our perceptions, our identity. Accordingly, ‘…soft spaces […] involve the creation of new geographies that transcend existing political administrative boundaries. As such, they represent specific social constructions of space that do not correspond to the political-territorial boundaries and internal divisions of the nation state’ (Allmendinger et al. 2015: 4). As Houtum states, ‘the space that borders represent is a process of social production and reproduction of mental representations, leading to the creation and prolonging of the images of “us” versus “them”’ (Houtum 2000: 71). Once the concept of socially constructed borders is accepted, ‘territory’ divided by the borderline (the borderland) receives a different interpretation: perceptions, actions and spatial behaviour of the border citizens constructing, de-constructing and re-constructing this border become a dominant factor (Paasi 2005). The theory of bordering born at the early 1990s brings these everyday construction practices to the fore, allowing ‘borders to be viewed as dynamic social processes and practices of spatial differentiation…’ (Brambilla et al. 2017: 1). In this context, borders ‘are not taken-for-granted entities that are exclusively connected to the territorial limits of nation-states; rather, they are mobile, relational and contested sites’ (Brambilla 2017: 111). In this perspective, CBC is about re-wording the borders, about the creation of new spatial narratives, new perception of space (borderlands) and new imaginaries defining the spatial behaviour and identity of border citizens. ‘Such new

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imaginaries can also help overcome animosities, rivalries or suspicions’ (Othengrafen et al. 2015: 226) and find the ‘ways to help overcome mental barriers and change the perceptions of those living and working in border areas’ (Othengrafen et  al. 2015: 220). The brand new concept of ‘borderscapes’ and ‘borderscaping’11 perfectly reflects this turn since, on the one hand, the suffix ‘-scape’ refers to creation,12 while, on the other hand, it alludes to the term ‘landscape’ which means a set of physical objects represented through the lenses of human perception and reflection. Landscape ‘as a representation is far from being “objective”: it does not have a pre-existing meaning, which can be understood in the same way by every kind of audience but, on the contrary, is the result of a sum of interpretations and re-interpretations’ (Dell’Agnese and Amilhat Szary 2015: 7). Landscape (and therefore borderscape) is not a fixed physical entity like the modernist ‘territory’ is; it is rather a ‘process of becoming’ (Rajaram and Grundy-­ Warr 2007: xxiv) where human activities have a crucial role. To conclude, Borderscapes foster a new multi-sited organisation of border knowledge, which is able to overcome binary oppositions through specific attention that is paid to the multiplicity of symbolic and material interactions at/in/across borders. This would help discover alternative spatiotemporal topologies to binary oppositions (inside/outside, centre/periphery, and so on) that modern Western thought has privileged, affirming a territorialist geopolitical imaginary that conceives the border as a line separating exclusive differences (Brambilla 2017: 118).

7.3

Methods and Indicators

7.3.1 I ntroduction: On the Very Mission of Cross-Border Cooperation Within the European Union The success of the European project is intimately linked to the (non-)existence of interstate borders; this fact became transparent during the so-called migration crisis in 2015. CBC is not a marginal issue from the point of view of joint European future, but it is the heart, the engine of the project. It is so not only because of the high ratio that borderlands represent within the territory of the EU (EC 2017). It is also true because both the realisation of the Single Market is impossible without opening the borders; and the self-identification of the European citizens strongly depends on their experiences with the internal borders (see the success of the Erasmus programmes). Here, mutual influence can be detected. On the one hand, the EU – in order to lessen the separating effects of borders – ‘has helped stimulate a wider range of efforts to enable policy-makers and stakeholders on both sides of the border to join together to address common problems and challenges and exploit  For the history of the term, please refer to Dell’Agnese and Amilhat Szary (2015), Dell’Agnese (2017), Brambilla (2015) and Brambilla et al. (2017). 12  See Houtum and Eker (2017: 42) and Dell’Agnese (2017: 53). 11

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the enhanced territorial potential resultant from the development of a functionally integrated region, where two peripheral ‘back-to-back’ regions existed previously’ (Allmendinger et al. 2015: 18). On the other hand, ‘European integration and territorial cooperation policies have deeply influenced the way people in border regions live, both in terms of perceptions and actual spatial practices’ (Decoville and Durand 2018: 134). It means that, thanks to the EU policies, the Community has gained many local ‘fighters’ of CBC, cross-border integration who have been contributing, through their activities, to designing the ‘blueprints’ of European spatial policies. Consequently, European CBC policy has an added value by itself even if real territorial impacts cannot be attested: in very many cases, cooperation itself would not have been possible without the policy and financial support of the EU (Medeiros 2014; EC 2007a, 2016b). However, when going beyond this general balance and focusing on cross-border TIA techniques and methods, one can conclude that the results are not convincing. The main reason of this ‘failure’ may be the lack of appropriate definitions: What is an ‘impact’? How should ‘territory’ be defined? What does the ‘quality of cross-­ border cooperation’/the ‘level of cross-border integration’ mean? And, finally, ‘What is the real mission of cross-border programmes?’ In order to strengthen territorial, economic and social cohesion of the EU, the barrier effects of the state borders should be lessened. With a view to lessening the barrier effects, cross-border integration should be enhanced (see Fig. 7.2). Cross-­ border integration means territorial, economic and social cohesion at local/regional level, across the border. It means that the cohesion factors and processes at local (i.e. not EU) level should be placed in the focus. Territorial impact assessment of a particular cross-border action should be based on the factors defining territorial integration within the particular border region (i.e. not at EU level). The house of European cohesion should be built from the building blocks of cohesive regions across the administrative borders and in compliance with the common European goals – but not from above. The mission of the rather ‘thick’ first theoretical chapter was to highlight that when speaking about territorial impacts, the term ‘territory’ should be re-defined. If territory is something which is constructed by perceptions, narratives, spatial practices and behaviours, the assessment of territorial impacts should concentrate on these perceptions, narratives, etc. From this interpretation horizon, it can be concluded that the ultimate goal of cross-border actions co-financed by the EU should be to ensure ‘co-makership and a sense of co-ownership in redesigning our borders’ (Houtum and Eker 2017: 50).

7.3.2 On the Methodological Background of Cross-Border TIA The draft Regulations of the Cohesion Policy beyond 2020 justify the above conclusions. The draft ETC Regulation advocates the following: ‘Focusing programmes on actions that are of direct interest to people and businesses located in border regions’ (EC 2018b: 5).

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The Interreg-specific objectives include the access to quality employment, education, training and health-care services across the borders, social inclusion and better governance (EC 2018b: Art. 14). When doing this, the authors of the proposal went beyond the general statements known from the previous programming periods. What is more, the draft ERDF Regulation (EC 2018c) contains a set of Interreg-­ specific output and result indicators which should be considered as a step in the right direction. However, fine-tuning would still be needed. For instance, ‘RCO 81 – Participants in cross-border mobility initiatives’ should be rephrased to ‘Cross-­ border participants in cross-border mobility initiatives’. ‘RCO 85 – Participants in joint training schemes’ should be replaced by ‘Participants of joint training schemes coming from the other side of the border’. It is not negligible whether a cross-border mobility event is attended by many participants but nobody from ‘the other side’ of the border. Similarly, during the current budgetary period, the CBC programmes were expected to justify the improved cross-border cohesion by applying indicators like ‘number of enterprises receiving support’ (however, the real cross-border indicator should refer to joint ventures or cross-border investments), ‘increase in expected number of visits to supported sites of cultural and natural heritage attractions’ (instead, the cross-border indicator should concentrate on the number of visitors coming from the neighbouring country  – and not, e.g. from the USA or Japan), ‘population covered by improved health services’ (while, in a cross-border context, the population using the health services on the other side of the border is the indicator which should be taken into account), etc. To sum it up, in each case, the emphasis is to be given to the cross-border character of the indicator in question. At the same time, for the assessment of the impacts of the cooperation programme, it is not enough to measure the values of the selected indicators. In a period of a decade (7 years of the actual programme + 3 years), many changes and new developments can take place in the border area which the programme can contribute to – even if not only by its own. ‘Impact’ always has a time factor (Medeiros 2014) which means that unlike the outputs and the results represented by the indicators, impacts have a more comprehensive and less definitive horizon. There are a number of further regional factors which – in a longer period of time – will influence the quality of CBC and the level of cross-border integration. Furthermore, impacts have a spatial factor too: they address a particular territory (in this case: a border area) which is not a stand-alone entity separated from the remaining parts of the world. It means that the impacts to be detected will have many effects coming from outside the given area. Therefore, TIA should reflect these external factors and identify the direct and indirect impacts by using a larger set of indicators compared to the limited frameworks of a CP. Finally, we share Medeiros’s view in the sense that there is no ‘pain-free’ TIA (Medeiros 2015: 98). Also, other experts draw the attention to the need of a comprehensive data bank for assessment (e.g. Zonneveld and Waterhout 2009; ESPON 2019) which requires serious efforts from practically all relevant players in this field since necessary data are vastly missing. In parallel, the complexity of the border

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realm excludes the possibility of ‘“fast food” TIA techniques’ (Medeiros 2014: 106).13

7.3.3 On the Application of the Above Principles in Practice In 2000, Henk van Houtum published a typology of border research in which he differentiated between the so-called (1) ‘flow’, (2) ‘cross-border cooperation’ and (3) ‘people’ approaches applied by border scholars. The first group of researchers considers borders as barriers and concentrates on the factors influencing cross-­ border flows. The authors following the second approach drive their attention to networking, social integration and harmonization, while the last approach is characterised by those activities which produce and reproduce the border. Perception, cognition, behaviour, actions and the mind-set of human beings are in the focus of the last model (Houtum 2000). All these approaches can be useful when performing territorial impact assessment procedure. 1. Cross-border flows of goods, people and services mirror the physical permeability of the border which is the prerequisite of any further activities contributing to the development of a shared borderscape. At the same time, the analysis should be confined to the geographic scope of the cross-border action. 2. The cross-border cooperation approach refers to the internal connectivity of the two border communities: the level of social integration. The second group of indicators and tools represents the framework of the procedure of shaping the common borderscape. 3. The people approach concentrates on the perceptions, narratives and spatial behaviour of the border citizens. This is the most complicated factor to measure. At the same time, it gives a real picture on the integration level of the common borderland: namely on the commitment of the border citizens to their home region. CESCI’s cross-border TIA model is based on these three aspects including the indicators and methods below (Table 7.1). In our view, based on the above indicators, the level of integration of a cross-­ border territory can be well described with some limitations. On the one hand, the values of some indicators cannot be exactly given. Since the countries forming part of the Schengen zone do not perform border control, the volume of cross-border transport can only be estimated based on traffic counting. The level of connectivity of the border societies is hard to define, taking into account the high number of  The author had the opportunity to take part at the workshop targeting the TIA of the EGTC Regulation. The experts applied the ESPON TIA Quick check at the workshop. First, the stakeholders could, as a matter of fact, hardly select indicators from among the proposed list because they were just irrelevant. Second, when finally mapping the results, the maps were geographically unintelligible, e.g. one of the most affected regions was located in Scandinavia where the EGTC tool is not applied at all. It does not mean that the TIA Quick check is useless. However, apparently, it cannot be properly applied in a cross-border context because of its simplistic character.

13

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Table 7.1  Indicators and methods of cross-border territorial impact assessment of CESCI Flows Infrastructural conditions of cross-border flows  Average distance of border crossing points  Average distance between the major regional centres of the border region (travelling time and geographic distance)  Volume of cross-border traffic within the programme region

CBC Administrative conditions of cross-border cooperation  Number of interstate agreements  Number of harmonized legal provisions with the neighbouring country

People Perceptions on distance  Mental distance of the adjacent region  Affective distance of border citizens

 Level of mutual trust  Number of town-twinning agreements within the programme region  Number of cross-border  Number of cross-border service transport lines contracts between institutions Perceptions of otherness  Mediascapes of the neighbouring country (quantity and quality)  Mental maps of the border citizens Cross-border mobility Cross-border institutions Ownership of the shared territory  Reasons and  Number of cross-border  Number of EGTCs (or other motivations of commuters cross-border governance border crossings entities) and their members  Geographic scope of  Number of commuting  Average annual turnover, cross-border students across the border number of employees of EGTCs mobility (or other cross-border governance entities)  Number of visitors/overnights  Number and total value of the projects implemented by the produced by citizens coming EGTCs (or other cross-border from the neighbouring country governance entities)  Frequency and average length  Number of other operating cross-border governance of visits in the neighbouring structures (e.g. Euroregions), country their annual turnover and number of employees  Number of registered residents  Number of cross-border institutions, networks and originating from the other side clusters, their employees and of the border their annual turnover  Number of travellers using  Number and value of projects cross-border transport lines realised by cross-border structures and institutions  Average age of cross-border structures (continued)

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Table 7.1 (continued) CBC People  Number of institutions taking part in cross-border activities Cross-border business activity Cross-border projects  Number of SMEs with owners  Number, geographic scope and value of projects implemented from the neighbouring country, jointly across the border number of their employees and value of their annual turnover  Sustainability of the project  Number of cross-border joint results ventures, number of their employees and value of their annual turnover  Differences in real estate and  Sustainability of project partnerships fuel prices according to the physical distance from the border  Value of investments within the  Assessment of integrated approach applied in projects and borderland made by investors calls for tender from the neighbouring country Cross-border services Social connectivity  Level of connectivity  Number of cross-border services, their cross-border clients and the frequency of their use by these clients  Number of employees of  Number of citizens participating cross-border service providers in cross-border activities and projects  Annual turnover of cross-­  Number of joint cultural events border service providers based on the performers’ nationality  Number of participants of professional and cultural events coming from the other side of the border Bilingualism  Level of bilingualism in administration, business and everyday life  Number of students studying the neighbouring country’s official language  Changes in the interethnic structure of the borderland Flows

items. However, sample-based models (e.g. the directional connectivity index of Svensson and Nordlund or the sociometric model of Bartal and Molnár14) applied in different types of regions can give a more comprehensive picture.

14

 Bartal and Molnár (2006)

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The proposed model lacks the timely character of TIA: it can be considered both as an ex post analysis at the end of the programming period and an ex ante analysis based on which the forthcoming programme can be assessed. The research is to be repeated after the completion of every programming period. Another shortcoming of the model is that there is a remarkable fluctuation in terms of the analysed institutions (consider, for example, the history of the Euroregions in a 10-year period of time) which weakens the reliability of the benchmark of the two analyses (before and after the programme implementation). At the same time, the broad spectrum of the analysis still ensures a high degree of comparability, and from among the models known, this method can give the most reliable picture on the level of integration (it means the decreased barrier effect and internal cohesion) of a border area. Obviously, the analysis requires considerable apparatus and resources. Indeed, there are several indices that can be extracted from documents available on the Internet. However, it does not mean that the process is easy. For instance, the mediascape analysis requires an in-depth research on the online (national, regional and local) newspapers, the results of which have to be processed by a contextual analysis. Furthermore, the majority of the pieces of information necessitates ‘field work’: online and street intercept surveys, semi-structured interviews, onsite traffic counting, etc. Some components of the analysis (like the assessment of the strategic approach applied in project development and implementation or the description of interethnic structure of the borderland) make it necessary to use a complex set of different methods.15 The utilisation of new technologies can also be needed (if the data protection rules allow), like the Call Detail Records of mobile phones picturing the mobility of border people (see for this the Final Report of the PILOT project ‘Border Region Data Collection’; EC 2018a). Finally, when the picture on the impacts is painted, the results should be compared to the values of the output and result indicators: with this, the values of the outputs and the impacts can be converged in order to estimate the effect that the CP had on the changes. Taking into account the resource requirements of the work to be done, it is worth considering to include it in the CP as a strategic project what is justified by the strategic importance of the assessment.

7.4

Conclusion

The study aimed at contributing to the EU level discussion targeting the appropriate methods of how to assess the utilisation of financial resources of the Union spent on cross-border developments and cooperation. The author proposed to slightly change the orientation of the current attempts: instead of applying an EU-based point of view, the borderlands should be invited into play; instead of concentrating the  Some of the above methods were applied in a research project concerning the territorial impacts of the reopening of the Mária Valéria Bridge, published in 2019 by CESCI.

15

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sensitivity of these border areas against European policies, the mentality of the border citizens should be assessed. What else can be the mission of CBC than to make the physical and administrative border insignificant, to eliminate the foreign character of the neighbouring region and the fear of Otherness and to create a common narrative of the borderland and its future, that is: to make the cross-border area a common home to border citizens? What else does European cohesion mean than the Continent as a common home? It should not be forgotten that the Single Market, the acquis, the TEN-T network, the common foreign policy, the European institutions, etc., have all been created for providing the European citizens with peace and prosperity: a common home. By this alternative approach, the borders can be re-interpreted: instead of considering them as a terminus, we should regard them as a ‘departure point for a new development’.

References Agnew J (1994) The territorial trap: the geographical assumptions of international relations theory. Rev Int Polit Econ 1(1):53–80 Agnew J (2008) Borders in the mind: re-framing border thinking. Ethics Global Politics 1(4):175–191 Allmendinger P, Haughton G, Knieling J, Othengrafen F (2015) Soft spaces, planning and emerging practices of territorial governance. In: Allmendinger P, Haughton G, Knieling J, Othengrafen F (eds) Soft Spaces in Europe. Re-negotiating governance, boundaries and borders. Routledge, London/New York, pp 3–22 Bartal AM, Molnár K (2006) Civil kapcsolati hálók az Ister-Granum régióban. Kutatási jelentés. Eurohíd Alapítvány, Esztergom Brambilla C (2015) From border as a method of capital to borderscape as a method for a geographical opposition to capitalism, Bollettino della Società Geografica Italiana Roma 8:13, 393–402. Unofficial English translation. [online] http://societageografica.net/wp/wp-content/ uploads/2016/08/brambilla_eng_3_15.pdf [online, 12.04.2019] Brambilla C (2017) Navigating the Euro/African border and migration nexus through the borderscape lens: insights from the LampedusaInFestival. In: Brambilla C, Laine J, Scott JW, Bocchi G (eds) Borderscaping: imaginations and practices of border making. Routlegde, London/New York, pp 111–121 Brambilla C, Laine J, Scott JW, Bocchi G (2017) Introduction: thinking, mapping, acting and living borders under contemporary globalisation. In: Brambilla C, Laine J, Scott JW, Bocchi G (eds) Borderscaping: imaginations and practices of border making. Routlegde, London/New York, pp 1–9 CCBS (2015) Toolkit for evaluation of cross-border projects. Centre for Cross-Border Studies, Armagh Decoville A, Durand F (2018) Exploring cross-border integration in Europe: how do populations cross borders and perceive their neighbours? Eur Urban Reg Stud 26(2):134–157 Dell’Agnese E (2017) New geographies of border(land)-scapes. In: Brambilla C, Laine J, Scott JW, Bocchi G (eds) Borderscaping: imaginations and practices of border making. Routlegde, London/New York, pp 53–64 Dell’Agnese E, Amilhat Szary A-L (2015) Borderscapes: from border landscapes to border aesthetics. Geopolitics 20(1):1–10 EC (2001) A white paper on European Governance. European Commission, Brussels, COM(2001) 428 final

7  Cross-Border Territorial Impact Assessment

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EC (2007a) Phare ex post evaluation. Phase 3, thematic evaluations – cross-border cooperation. Thematic evaluation. Phare cross-border cooperation programmes 1999–2003. European Commission, Brussels EC (2007b) Territorial agenda of the European Union. Towards a more competitive and sustainable Europe of diverse regions. https://ec.europa.eu/regional_policy/sources/policy/what/territorialcohesion/territorial_agenda_leipzig2007.pdf [online, 24.07.2019] EC (2008) Green paper on territorial cohesion. Turning territorial diversity into strength, European Commission, Brussels, SEC(2008) 2550 EC (2009) Impact assessment guidelines, European Commission, Brussels, SEC(2009) 92 EC (2013) Assessing territorial impacts: operational guidance on how to assess regional and local impacts within the Commission Impact Assessment System, European Commission, Brussels, SWD(2013) 3 final EC (2016a) Ex-post evaluation of Cohesion Policy programmes 2007–2013, focusing on the European Regional Development Fund (ERDF) and the Cohesion Fund (CF). Final report. Main report. European Commission, Brussels EC (2016b) Ex post evaluation of Cohesion Policy programmes 2007–2013 financed by the European regional development Fund (ERDF) and Cohesion Fund (CF). Case study: Hungary-­ Slovakia Cross-border Cooperation Programme 2007–2013. European Commission, Brussels EC (2017) Boosting growth and cohesion in EU border regions. European Commission, Brussels, COM(2017) 534 final EC (2018a) Border region data collection. Final Report. European Commission, Brussels EC (2018b) Proposal for a regulation of the European Parliament and of the council on specific provisions for the European territorial cooperation goal (Interreg) supported by the European Regional Development Fund and external financing instruments. European Commission, Brussels, COM(2018) 374 final EC (2018c) Proposal for a regulation of the European Parliament and of the council on the European Regional Development Fund and on the Cohesion Fund. European Commission, Brussels, COM/2018/372 final ESPON (2013) INTERCO. Indicators of territorial cohesion. (Draft) Final Report. Part B Report ESPON (2019) Territorial impact assessment for cross-border cooperation. Draft Scientific Annex Evers D (2011) Territorial impact assessment: a critical examination of current practice. In: Farinos DJ (ed) De la Valucion Ambiental Estartegica a la Evaluacion de Impacto Territorial. Generalitat Valenciana/PUV, Valencia, pp 75–110 Faludi A (2018) The poverty of territorialism. In: A neo-medieval view of Europe and European planning. Edward Elgar Publishing, Cheltenham/Northampton Halls ET (1968) Proxemics. Curr Anthropol 9(2/3):83–95 Houtum v H (1998) The development of cross-border economic relations. ThelaThesis Publishers, Amsterdam Houtum v H (2000) An overview of European geographical research on borders and border regions. J Borderlands Stud 15(1):57–83 Houtum v H, Eker M (2017) Redesigning borderlands: using the Janus-Face of borders as a resource. In: Brambilla C, Laine J, Scott JW, Bocchi G (eds) Borderscaping: imaginations and practices of border making. Routlegde, London/New York, pp 41–51 Houtum v H, Kramsch O, Zierhofer W (2005) B/ordering space. Ashgate, Aldershot/Burlington ITEM (2016) Cross-border impact assessment 2016. Extensive report. Institute for Transnational and Euregional cross border cooperation and Mobility/ITEM, Maastricht ITEM (2017) Cross-border impact assessment 2017. Extensive report. Institute for Transnational and Euregional cross border cooperation and Mobility/ITEM, Maastricht ITEM (2018) Cross-border impact assessment 2018. Extensive Report. Institute for Transnational and Euregional cross border cooperation and Mobility/ITEM, Maastricht Lefebvre H (1991) The production of space. Blackwell, Oxford/Cambridge, MA Medeiros E (2014) Territorial Impact Assessment (TIA). Concept, Methods and Techniques. Centro de Estudos Geográficos da Universidade de Lisboa (CEG) – Instituto de Geografia e Ordenamento do Território (IGOT). Lisbon University, Lisbon

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Medeiros E (2015) Territorial impact assessment and cross-border cooperation. Reg Stud Reg Sci 2(1):97–115 Medeiros E (2019) Spatial planning, territorial development, and territorial impact assessment. J Spat Plann 34(2):171–182 OECD (2013) Regions and innovation: collaborating across borders. OECD Publishing, Paris Othengrafen F, Knieling J, Haughton G, Allmendinger P (2015) Conclusion  – what a different do soft spaces make? In: Allmendinger P, Haughton G, Knieling J, Othengrafen F (eds) Soft Spaces in Europe. Re-negotiating governance, boundaries and borders. Routledge, London/ New York, pp 215–235 Paasi A (2005) The changing discourses on political boundaries. Mapping the backgrounds, contexts and contents. In: Houtum v H, Kramsch O, Zierhofer W (eds) B/ordering space. Ashgate, Aldershot, pp 17–31 Rajaram PK, Grundy-Warr C (2007) Introduction. In: Rajaram PK, Grundy-Warr C (eds) Borderscapes. Hidden geographies and politics at territory’s edge. University of Minnesota Press, Minneapolis/London, pp ix–lx Scott JW (2014) Bordering, border politics and cross-border cooperation in Europe. Working Paper 7, EUROBORDERSCAPES. Bordering, political landscapes and social arenas: potentials and challenges of evolving border concepts in a post-Cold War World. http://www.euborderscapes. eu/fileadmin/user_upload/Working_Papers/EUBORDERSCAPES_Working_Paper_7_Scott. pdf [online, 03.12.2016] Svensson S, Nordlund C (2015) The building blocks of a Euroregion: novel metrics to measure cross-border integration. J Eur Integr 37(3):371–389 Taillon R, Beck J, Rihm S (2011) Impact assessment toolkit for cross-border cooperation. The Centre for Cross Border Studies – The Euro Institut – Institute for cross border co-operation, Armagh-Kehl Werlen B (2005) Regions and everyday regionalizations. From a space-centred towards an action-­ centred human geography. In: Houtum v H, Kramsch O, Zierhofer W (eds) B/ordering space. Ashgate, Aldershot, pp 47–60 Zonneveld W, Waterhout B (2009) EU territorial impact assessment: under what conditions? final report, OTB Research Institute Delft University of Technology. https://www.rtpi.org.uk/ media/5987/tiareport_zonneveld02072009.pdf [online, 19.09.2018] Gyula Ocskay  political philosopher and regional economist, is secretary general of Central European Service for Cross-Border Initiatives (CESCI). He has been involved in cross-border cooperation and development since 1999 when he became the coordinator of cross-border cooperation at the municipality of Esztergom located at the Hungarian-Slovak border. Since 2009, he has been managing the work of CESCI which is a think and do tank of cross-border cooperation. In this position, he is actively involved in cross-border research projects, cross-border strategic planning, programming and evaluation, institutional and project development, policy making and knowledge sharing.

8

Enhancing Cross-Border Cooperation Through TIA Implementation Ricardo C. B. Ferreira and Nathalie Verschelde

Abstract

Cross-border cooperation (CBC) has great socioeconomic potential. If onefifth of legal obstacles to cross-border interaction would be solved, 2% of Gross Domestic Product (GDP) in EU cross-border regions – 1 million jobs – could be gained. CBC is hampered by the fact that territories are regulated by different legal frameworks. Legal obstacles derive both from EU and national legislation. National legislative processes seldom take properly into account impacts across borders, including when transposing European legislation. Cross-border investments can have reduced effectiveness because of legal obstacles. To ensure not-­border-­blind legislation and increasing investment effectiveness, the European Commission (EC) has included Territorial Impact Assessment (TIA) in its Better Regulation Package. Furthermore, it is working to ensure TIA has a CB dimension. This chapter will describe the EC’s experience with CB TIA: (i) analysing tools/methodologies guaranteeing TIA is conducted ex ante, ensuring EU legislative proposals have no asymmetric impact on CB regions and how such tools/methodologies can be explored in national/ regional legislative processes and (ii) describing TIA experiences on CBC programmes’ ex post impacts. Europe is a continent characterised by many borders relatively to geographical size. Their impact on people’s lives – despite the single market  – is a major concern. That is why the EU needs to be at the forefront in terms of cross-border TIA. The information and views set out in this chapter are those of the authors and do not reflect the official opinion of the European Commission.

R. C. B. Ferreira (*) · N. Verschelde DG REGIO – DG for Regional and Urban Policy, European Commission, European Union, Brussels, Belgium e-mail: [email protected]; [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_8

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Keywords

Territorial Impact Assessment · Cross-border cooperation · Interreg · European Territorial Cooperation · European Commission

8.1

 erritorial Impact Assessment: An Enabler T of Cross-Border Cooperation

Cross-border cooperation (CBC) can be seen as “a partnership between local and regional stakeholders separated by a national frontier, whose actions have repercussions at the local and the regional level on both sides of that frontier” (Rubio 2018:607). In practice, CBC implies establishing the enabling conditions to allow agents in cross-border regions to fully exploit their potential in the totality of their natural catchment areas. Being a simple concept, it faces many obstacles in implementation. In short, it means facilitating interactions amongst social or economic agents located on different sides of a border that separates two contiguous countries. Individuals and organisations (agents) tend to establish relations with other individuals and organisations located in a territory around them, within a certain radius. This territory can be seen as a natural catchment area. The radius of this territory certainly varies not only according to the nature of the agents but also according to the nature of the relations being established: a two-person-sized enterprise selling freshly pressed juice in their van directly to the consumer in parks may have a catchment area limited to a 20-km radius, while that of a medium-sized company adapting vans to be used in the juice-selling business would have a few hundred km radius. However, when this natural catchment area is divided by the existence of a national border, everything gets more complicated. Establishing relations with agents on the other side of the border is much more difficult than with those on the same side of the border. As such, individuals and organisations tend not to fully exploit the potential relations with a significant part of their natural catchment area – that on “the other side”. Cross-border cooperation can be seen as “a partnership between local and regional stakeholders separated by a national frontier, whose actions have repercussions at the local and the regional level on both sides of that frontier” (Rubio 2018:607). In practice, CBC implies establishing the enabling conditions to allow agents in cross-border regions to fully exploit their potential in the totality of their natural catchment areas. In an ideal situation, CBC should not be necessary. If the border would not be a barrier for those relations, then interactions with agents on the other side of the border would happen as naturally as with those on the same side. The need for CBC is justified precisely because national borders represent an obstacle for those interactions. Such obstacles have a negative impact on economic development of border

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regions generally referred to as border effect. Illustrative cases can be found, for example, in Helble (2007), Gil-Pareja et al. (2006) and Ferreira and Mourato (2011). Within the European Union, with the implementation of the Single Market, interactions across the border are the smoothest. Probably nowhere else in the world has the permeability of the border reached such level. However, in spite of the Single Market, obstacles exist and impede cross-border regions to reach their full potential. The Cross-Border Review (EC 2015b, 2017a) has provided an illustrative inventory of 239 legal and administrative obstacles. In parallel, Capello et al. (2017) estimated the economic impact of such obstacles. If only one-fifth of the existing obstacles could be solved, an extra 2% GDP growth in cross-border regions could be expected (EC 2017b). But how does Territorial Impact Assessment (TIA) relate with cross-border cooperation? In Verschelde and Ferreira (2019:164), it is argued that the support for CBC should be of three types: legal, financial and political. Within the legal, two of the main components are of particular relevance: “to ensure that legislation, in all policy areas, is not harmful to border regions and that it facilitates cooperation to be established” and “to ensure that territorial planning, and public services provision, is not done in a border blind manner but that it takes into consideration the existing planning on the other side of the border”. In practice, many of the obstacles of a legal/administrative nature that hamper interactions are caused by incompatible legal frameworks on the two sides of the border. This happens because legislation, designed at national, regional or local level, is thought to be applied within the boundaries of a country and, therefore, its potential impact is assessed with that limitation. TIA should play a key role in this domain, ensuring that all territorial impacts of legislation are assessed considering also the impact beyond the borders of the territory in which the legislation is to be applied. The second component can be seen as a particular case of the first, as different elements of spatial planning can be seen as part of the legal framework sensu lato. As space does not end in national borders, the cross-border impact of spatial planning on the other side of the border is patent. Ensuring TIA with a CB dimension is applied to spatial planning elements addressing the territory of border regions is sine qua non condition to guarantee that spatial planning does not emerge as another source of obstacles. It should be noted that in a wider international perspective, the United Nations Economic Commission for Europe (UNECE) Convention on Environmental Impact Assessment in a Transboundary Context, adopted in 1991 in Espoo (FI), already provides a framework in this direction (UN 1991). However, it only addressed the environmental dimension of impact assessments. Furthermore, its scope is limited to a set of 17 actions listed in its appendix one (UN 1991:13), several being qualified with a minimum size (e.g. “large dams”; “10 million cubic meters or more”). Its applicability is therefore limited to the arena of major infrastructure projects. This naturally derives from the process of an international multilateral agreement. The actions described in this chapter go further, reaching other dimensions of territorial impact assessments than the environmental and not being limited to largescale projects.

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 IA and European Union’s Policy T for Cross-Border Cooperation

European Union’s policy for CBC, also known as European Territorial Cooperation, is one of the elements of Cohesion Policy. It has been mostly centred in the financial side of the support that can be provided for countries and regions to create the enabling conditions for cross-border interactions. Its main tool has been Interreg that is applied in the different borders according to different Cooperation Programmes. A historical evolution of Interreg can be found in Verschelde and Ferreira (2019) or in European Commission (2015a). But although Interreg was the main push for CBC in Europe, experience shows that support for cooperation should go beyond financial support. The European Commissioner for Regional Policy, on the occasion of Interreg’s 25th anniversary, clearly stated it: I am keen to explore what more can be done for border communities across Europe. Citizens and businesses in these regions sometimes still face unnecessary complications when they engage in cross-border activities. (Creţu 2015:3)

In this sense, a thorough work of consultation was launched by the European Commission to better understand the needs of cross-border regions and the perspectives of their stakeholders. This was implemented through the Cross-Border Review (EC 2015b, 2017a). This exercise has included an online public consultation (EC 2016a), a series of experts’ workshops and a study that, amongst others, included an inventory of legal and administrative obstacles (EC 2017a). This process led to a general conclusion: more emphasis has to be put on overcoming legal and administrative obstacles that still hamper cross-border interactions. To this aim, and building on the conclusions of the Cross-Border Review, the European Commission has adopted in 2017 the Communication “Boosting growth and cohesion in EU border regions” (EC 2017b). This communication has identified ten different thematic areas in which actions by the EC and by the different countries and regions are most needed. The selection of these areas does not indicate that other areas are of less importance, or that they do not face relevant obstacles. It was the natural follow-up of the knowledge base acquired with the cross-border review. An overview of the different actions can be found in Ferreira et al. (2019) and in Ferreira (2019). “Improving the legislative process” is one of those actions. One of the key elements is to ensure that in the European legislative processes, the impacts on cross-border regions would be assessed before different pieces of legislation are adopted. In this sense, the role of TIA with a cross-border perspective is of crucial importance. To this effect, the Commission has already included this perspective in its Better Regulation Package (EC 2015c) by proposing “measures to ensure that territorial aspects are factored into policy options. This happens mainly through the implementation of robust impact assessments of legislation that include territorial elements” (EC 2017b:7).

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But legal and administrative cross-border obstacles are caused at different levels. “Root causes have been attributed to the existence side by side of different regulations in national legal and administrative systems. Even where there is a European legal framework, Member States have a degree of flexibility and discretion in the way they transpose this legislation in their national systems” (EC 2017b:6). As such, improving the legislative process at European level is essential, but not enough. Also, the national, regional and local legislative processes that have an impact on border territories could be improved if they will include a proper Territorial Impact Assessments with a cross-border perspective. It is with this aim that the European Commission has been supporting the development of TIA methodologies that can be used to preventively assess the cross-­ border territorial impact on new legislative initiatives. These methodologies could be used by different countries and subnational administrations with legislative competences to enhance the positive cross-border impacts of their legislative initiatives and to prevent the negative ones.

8.3

Ex Ante Versus Ex Post: Assessing Different Impact on/of Cross-Border Cooperation

CBC is a simple but yet so diverse concept. Sometimes, it is used to mean the interactions across the border (e.g. a company hiring employees residing on the other side of the border). These interactions are normally expected to occur amongst agents of a private nature. Most frequently  – like in the definition presented by Rubio above  – CBC is seen as the process to enable, facilitate or promote such interactions. As such, it is not the interactions themselves, but the cooperation  – mainly amongst public administrations – to allow for such interactions to flourish (e.g. ensuring common recognition of diplomas to allow for workers to be employed across the border). It is in this meaning that we use this expression. But the concept has been mostly used as a consequence of the implementation of Interreg. In fact, it is very commonly understood as limited to the implementation of projects funded by Interreg Cooperation Programmes. This is certainly a major component of CBC, but it should not be limited to that. In fact, many administrations cooperate with their counterparts on the other side of the border beyond Interreg-funded projects. These different definitions of CBC imply there are different components which impact on the border territory and should be assessed using TIA methodologies. Consequentially, different methodologies presented in this book can be better applicable to one or the other type. In general terms, these can be categorised into ex ante and ex post assessments. On the one hand, ex post TIA can be applied to assess the impact of cooperation – meaning the process to enable interactions – on social economic development of border regions. In other words, ex post TIA may be used to assess the impact that Interreg Cooperation Programmes (or other forms of support) have on increasing interactions across the border and on overcoming border effects (allowing for generalisation, we refer to the OP or other element in which impact is being assessed as

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the subject of assessment). This impact is normally expected to be positive. The assessment would identify how positive it is. For example, it can be assumed that every Interreg Programme has a positive effect on cross-border interactions. But that alone does not make it a success. The assessment is to demonstrate how positive was this impact of the subject. On the other hand, ex ante TIA can be applied to assess the impact an external factor (normally a new piece of legislation) is expected to have on cooperation. In this case, CBC is seen as the level of interactions. Normally, this assessment is to be a part of the legislative process prior to the adoption of a new legislation. In this case, the importance of TIA for CB is to assess to what extent could such new legislation lead to new legal obstacles, thus with a negative effect on cooperation, or to which extent it would facilitate interactions across the border, thus having a positive effect on cooperation. These two types of TIA are applicable to assess different types of impacts. Ex ante TIA is thus much more preventive, serving as a decision support tool to the legislative process. It should permit avoiding adoption of legislation with a negative impact on cross-border interactions and reshaping legislation with a positive impact in order to maximise it. Ex post TIA is more of an evaluation tool to assess what have been the actual impacts of Interreg Cooperation Programmes or other cross-border cooperation tools. The existence of two clearly different types of TIAs has clear implications in terms of methodologies. The different natures of the impacts being measured lead to different availability of data and information on which to base the assessment. The ex ante and ex post natures of these two different types make the distinction. For ex post TIA, assessment is focusing on a real subject that has already happened. Depending on the thoroughness of the implemented monitoring systems, data and information directly related to the subject may be available allowing to establish, at least to some degree, the causality between the subject and the impacts on the cross-­ border territory. On the other hand, for ex ante TIAs, the subject of assessment has not yet become a reality. The assessment will focus on the expected impact that the subject may have on the cross-border territories. As a consequence, data and information directly related to the subject cannot be available. It becomes much more difficult to establish a direct causality between the subject and its impact on the cross-border territory. Different sources of information can thus be used for these two types of TIAs. For ex post, depending on availability, primary data like impact indicators and output indicators can be used to assess the impact of the subject. However, for ex ante, only secondary information can be used. This secondary information can be of different natures. It can focus on the perceptions that different types of stakeholders (e.g. expert groups; specific stakeholders; citizens) have on the expected impact; it can focus on real impacts of similar subjects in other territories; it can focus on study cases, etc. As input data and information are of different natures, so have to be the methodologies to be applied in ex ante and ex post TIAs. In previous chapters of this book,

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experts and authors of different methodologies have presented in detail each of them. This diversity allows the reader to assess which is best applicable to the subject being assessed. For the European Commission, both ex ante and ex post play an important, although differentiated, role. As discussed in the previous section, ex ante TIA is essential to ensure that new legislation will not cause new border obstacles. Ex post TIA is essential to understand the impact of cross-border cooperation in cross-­ border interactions allowing to continuously improve CBC policy.

8.4

Implementation Experiences at European Level

There have been several examples of ex post TIA performed in particular on Interreg cross-border cooperation programmes. “TARGET TIA” is a methodology developed by Medeiros (2013, 2017, 2019). More recently, the European-funded ESPON programme for territorial observation has also embarked on a project to attempt to define a methodology to assess ex post the impact of Interreg CBC programmes, using elements from several existing methods. The project “Territorial Impact Assessment for Cross-Border Cooperation” ESPON (2018) took place in 2018 and 2019 with as principal objective to develop a methodology to assess the impact of any cross-border cooperation programme across the EU in an ex post setting. After extensive work, both desk based and in cooperation with stakeholders, the project has made available a five-step method adapted to the Interreg CBC framework. Besides the methodology developed, the project is also interesting because it developed the methodological elements with a strong input from five Interreg CBC programmes located in different parts of the EU, namely the Netherlands/Germany, Spain/Portugal, Romania/Bulgaria, Ireland/UK (Northern Ireland) and Sweden/Norway. What distinguishes this methodology from others is the strong qualitative input from stakeholders that combines with quantitative and semi-quantitative indicators. The method starts with a robust examination and “reconstruction” of the intervention logic intended by the programme partners and stakeholders – this is a necessary step as not all Interreg programmes are equally strong in their intervention logic. Here, with step 1 of the method, experts and stakeholders set about “reconstructing strong links between the needs identified, the measures chosen and the likely effects of these measures”. The step also allows for developing corresponding indicators and already examining potential data sources necessary to perform the assessment. Step 2 consists of an in-depth exchange between the experts involved in step 1 and programme stakeholders, as well as regional and thematic experts. With step 2, the objective is to validate the intervention logic and to bring in adaptations that might be necessary because of lack of data, for instance. During step 3, the expert(s) performing the assessment decides which method is most appropriate to process the indicators agreed during step 2. The expert can mix assessment methods going from purely quantitative to purely qualitative, with intermediary mixes in between. At the end of step 3, a set of indicators has been prepared and is ready for further processing.

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In step 4, the method goes back to an interactive moment between experts and stakeholders. The focus here will naturally be on those indicators assessed via semi-­ quantitative and qualitative methods. Step 4 concludes when there is an agreed judgement on the territorial distribution of impacts in the programme area. The fifth and final step consists of consolidating the calculations and qualitative inputs from the previous steps into a comprehensive and verifiable report. The steps described above emphasise the strong iterative nature of the process. When it comes to assessing impacts in a cross-border context, iteration is essential. This is important for several reasons. First, there is a well-documented issue with data. As with the border effects to cross-border interactions described earlier in this article, border data also suffers from “negative border effects”. This results mainly in the development of national/regional data on both sides of the border that cannot be compared because they do not measure exactly the same phenomenon. The second main issue is the near-total absence of “dynamic” data measuring cross-border flows. This significant gap can only be somewhat compensated by iteration between experts and stakeholders and the use of qualitative data such as perceptions. Second, a quality TIA in a cross-border context cannot rely exclusively on statistical data. Any type of cross-border cooperation implies elements that are not necessarily “visible” – these can only emerge and enrich the assessment via an interactive exchange between experts and stakeholders. This methodology has only recently been finalised (2019), and although it has already been applied to five very different cross-border areas, it needs to be used and tested more widely before any conclusions can be drawn. Nevertheless, we can already conclude now that the method offers great potential because it has taken into consideration the limitations faced by many cross-border programmes and interventions. It does not pretend to have all the answers, but it offers those interested in measuring the impacts of their interventions with a comprehensive canvas. When it comes to ex ante TIA, there are a few examples to consider, mostly performed under the impulse of the European Commission, in line with its revised Better Regulation rules as amended in 2015. The objective of the European Commission here is to ensure that new legislation put forward to the decision-­ makers (Council and Parliament) does not create negative impacts along EU internal borders. To perform this ex ante TIA with a CB dimension, the European Commission has developed methodological steps that are coordinated by its Directorate-General for Regional and Urban Policy, its “territorial department”. Inter-service work takes place early in the legislative process, part of which is dedicated to the examination of impacts on certain clearly defined territories such as cities or cross-border regions. The challenges described above in the context of ex post TIA also apply here. Data is here too, a central dimension to the approach that has been developed. Lack of comparable and dynamic data means that here too an iterative process had to be developed. Statistical data and calculation methods cannot be solely relied upon to offer a solid and trustworthy analysis of impacts. Here too, experts need to work hand in hand with stakeholders and cross-border practitioners to combine quantitative and qualitative assessments, using a variety of indicators that are selected jointly

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in a constructively moderated session. Examples of ex ante TIA assessments on draft EU legislation conducted by the European Commission include Blue Card Directive, Energy Efficiency in Building Directive (European Commission 2016b) and European Cross-Border Mechanism Regulation. Although there are few known cases of ex ante TIA of legislation across Europe, one such case deserves attention. The Institute for Transnational and Euregional cross border cooperation and Mobility (ITEM), based in Maastricht University, has engaged with its main stakeholders for several years now, with a view to raise awareness amongst lawmakers of the need to look beyond borders. Looking at the geographical position of Maastricht, it is not surprising that the university’s legal department developed a strong interest for cross-border impact assessments. From a modest start a few years ago, the institute has now developed a well-recognised competence for ex ante assessment of legislation stemming from the Netherlands, Germany and Belgium. It has also, as a result, succeeded in highlighting several potentially serious negative cross-border effects of legislation. ITEM now publishes a yearly dossier on ex ante impact assessments which is well-worth a read. While not strictly speaking “territorial” in the sense of the other methods described above, where the methodology has been developed to be applicable to any cross-border region, ITEM’s ex ante assessment all includes a strong territorial dimension due mainly to the location of the region where the impacts are being measured and its cross-border nature.

8.5

Concluding: The Way Ahead

CBC is essential to ensure that cross-border interactions are not hampered by legal and administrative obstacles due to the need to cope simultaneously with different legal frameworks. It is a basic question of fairness: to ensure that individuals and organisations in border territories can fully exploit their natural catchment areas as easily as they would if they were located in non-border territories. At least within the European Union, this should be guaranteed. But that is yet far from being guaranteed! Indeed, legal and administrative obstacles are faced by those agents in border territories. The root causes are the differences in the legal frameworks applied on the different sides of a border. Such differences can derive not only from regional or national legislation but also from European legislation. Different transpositions of a same EU Directive are a classic example. The European Commission is committed to contribute to overcome existing cross-border obstacles. This was clearly stated with the adoption of the Communication “Boosting growth and cohesion in EU border regions” (EC 2017b) and by the implementation of the Border Focal Point in the services of DG REGIO, as announced by the Communication. But beyond solving existing obstacles, it is essential to prevent the appearance of new ones. To this aim, ex ante Territorial Impact Assessments with a cross-border dimension are of crucial importance. It should be ensured that every new legislative initiative with an impact on cross-­ border territories would be preventively assessed to ensure it would not cause new

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cross-border obstacles. TIA should guarantee an assessment of the impacts across the borders of the territory on which that new legislation is meant to be applied. The European Commission, within the limits of its competences, is working in this direction. It has introduced TIA in its Better Regulation Package (EC 2015c). The idea is to ensure that all future legislation with an impact on border territories would undergo a TIA with a cross-border dimension. Furthermore, with the adoption of the Communication on boosting border regions, and its follow-up activities, it is supporting the development of methodologies that could be used by national, regional and local authorities in their own legislative processes. It also aims “to support Member States with necessary coordination efforts during their national transposition process” (EC 2017b:7). But as legal obstacles derive from legislation at different levels, equally solutions cannot derive from action at European level alone. As such, a clear call is made for member states of the European Union, and their respective subnational administrations with legislative powers, to ensure that TIA with cross-border dimension is embedded in their legislative processes as well. The different methodologies presented in this book could be a support in that direction. But TIA’s influence on CBC is not limited to ex ante assessment of the impacts of new legislation. It can also be used ex post to assess the different impacts of Interreg Cooperation Programmes or implementation of other policies with an impact on the border. That is the example of some cases presented in the previous section. Different methodologies may be taken into account for different cases. Depending on the nature of the TIA (ex ante or ex post), depending on the nature of the subject being assessed, depending on territory being addressed and depending on the availability of data, some methodologies would apply better than others. In some cases, methodologies may even need revision according to the context. No methodology would alone serve all the cases. But beyond methodologies, the main conclusion is simple. Territories do not end in the national border. Territorial impacts of political decisions, not limited to environmental ones, should also take into account the continuation of the territory beyond those borders!

References Capello R, Caragliu A, Fratesi U (2017) Measuring border effects in European cross-border regions. Reg Stud. https://doi.org/10.1080/00343404.2017.1364843 Creţu C (2015) Foreword, in European Commission (2015) op cit ESPON (2018) Territorial impact assessment report on the establishment of the European Labour Authority, ISBN: 978-99959-55-41-0, available at: https://cor.europa.eu/en/our-work/ Documents/Territorial-impact-assessment/TIA-ELA-Labour-Authority-20180704.pdf European Commission (2015a) Territorial cooperation in Europe  – a historical perspective, European Commission  – Directorate-General for Regional and Urban Policy. Publications Office of the European Union, Luxembourg; ISBN 978-92-79-49501-4; https://doi. org/10.2776/374386 European Commission (2015b) Cross-border review, available at: https://ec.europa.eu/ regional_policy/en/policy/cooperation/european-territorial/cross-border/review/

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European Commission (2015c) Communication from the commission to the European Parliament, the Council, the European economic and Social Committee and the Committee of the Regions – better regulation for better results – an EU agenda, COM(2015)215 European Commission (2016a) Overcoming obstacles in border regions: Summary report on the online consultation, European Commission  – Directorate-General for Regional and Urban Policy. Publications Office of the European Union, Luxembourg; ISBN 978-92-79-57356-9 European Commission (2016b) Ex-post urban impact assessment energy performance of buildings directive workshop based on ESPON TIA quick scan tool, available at: https://cor.europa. eu/en/our-work/Documents/Territorial-impact-assessment/energy-performance-buildings.pdf European Commission (2017a) Easing legal and administrative obstacles in EU border regions, available at: https://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/obstacle_border/final_report.pdf European Commission (2017b) Communication from the commission to the council and the European Parliament  – boosting growth and cohesion in European Border Regions, COM(2017)534 Ferreira R (2019) Impulsionar o crescimento e a coesão nas regiões fronteiriças da UE – O apoio da Comissão Europeia à cooperação transfronteiriça. In: Conferências Internacionais de Elvas 2018, AiaR, Elvas. ISBN: 978-989-99927-7-1 Ferreira R, Mourato J (2011) Border effect in interregional Iberian trade. J Econ Bus Res XVII(1):35–50 Ferreira R, Verschelde N, Cenacchi V (2019) Debating European Commission’s support to Cross-­ Border Cooperation: time to move beyond funding Gil-Pareja S, Llorca-Vivero R, Martínez-Serrano JA (2006) The border effect in Spain: the Basque Country case. Reg Stud 40(4):335–345. https://doi.org/10.1080/00343400600725186 Helble M (2007) Border effect estimates for France and Germany combining international trade and intranational transport flows. Rev World Econ. https://doi.org/10.1007/s10290-007-0116-x Medeiros E (2013) Assessing territorial impacts of the EU Cohesion Policy: the Portuguese case. Eur Plan Stud 22(9):1960–1988 Medeiros E (2017) European Union Cohesion Policy and Spain: a territorial impact assessment. Reg Stud 51(8):1259–1269 Medeiros E (2019) Spatial planning, territorial development and territorial impact assessment. J Plan Lit 34(2):171–182 Rubio J (2018) Review of EC 2015 op cit. In: Documents d’Anàlisi Geogràfica 2018, vol. 64/3 https://pdfs.semanticscholar.org/04e4/6c1a477346d17974f75e24336a1765ec56fa.pdf United Nations (1991) Convention on environmental impact assessment in a transboundary context, available at: https://www.unece.org/fileadmin/DAM/env/eia/documents/legaltexts/ Espoo_Convention_authentic_ENG.pdf Verschelde N, Ferreira R (2019) Experiencias de cooperación transfronteriza en la unión europea y su impacto a nivel regional in Bendelac-Gordon & Guillermo-Ramírez (coord.) La cooperación transfronteriza para el desarrollo. ISBN: 978-84-9097-605-0 Ricardo C. B. Ferreira  Portuguese, graduated in Economics in Lisbon in 1994, obtained Master in International Business in Bergen (Norway) and got his PhD in Applied Economics in Spain. Ricardo is a policy officer at the European Commission, in its DG for Regional and Urban Policy (REGIO), in the unit for Cross-Border Cooperation. Currently, he coordinates the Border Focal Point which aims to foster Cross-Border Cooperation in EU internal borders, in several thematic areas. Previously in the Commission, Ricardo has been program manager for ERDF investments in Spain (in DG REGIO); in DG EMPL, he has dealt with services and tools for skills and qualifications; and in DG EAC, he has dealt with policies for Opening Up Education (inclusion of more ICT and OER in education and training).

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  Before joining the European Commission, Ricardo has been a professor of economics at the Portalegre Polytechnic Institute (PT) for about 15 years. During that period, his main research area was on Cross-Border interactions, mostly focusing on interregional trade on the PortugueseSpanish Border.

Nathalie Verschelde  was born on the Belgian-French border, 350 meters from the border post. At school in a border village, experienced daily interaction with the ‘other side of the border’, including two cross-border commuting grandfathers. She holds an MA in philology (English and Dutch literature) and served for 6 years in the Belgian and then Scottish public administrations before working in the private sector, running her own business and developing expertise on the integration and accession process in the EU. She worked on a large number of cross-border and transnational cooperation projects. She joined the Commission as a civil servant in 2004, starting work in the external affairs department working in the USA/Canada unit. She joined DG REGIO in January 2006 to work on territorial cooperation, both cross-border and transnational. Since 2015, she is the Deputy Head of Unit for the Cross-Border Cooperation Unit and coordinator for the Cross-Border Review and one of the pens of the Commission Communication ‘Boosting Growth and Cohesion in EU Border Regions’.

Part III Territorial Impact Assessment: Alternative Models and Complementary Approaches

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From Territorial Impact Assessment to Territorial Foresight Kai Böhme, Christian Lüer, and Frank Holstein

Abstract

Policy-making shapes – explicitly or implicitly – future territorial development. Therefore, sound policy making needs strong territorial and future dimensions. While territorial impact assessments focus on the territorial impact of policies, territorial foresight addresses possible long-term developments and their potential future impact on territories in order to support anticipatory or future-wise decision-making. This chapter argues to adopt territorial foresight approaches instead of territorial impact assessments when long-term developments are concerned. Territorial foresight combines elements of territorial impact assessments and foresight approaches. As such the approach supports addressing the territorial impact of future trends, visions and policy objectives when designing forward-­looking policies. It offers different steps that support policy makers in thinking territorially, allow them to anticipate on the future and increase ownership on possible actions shaping the future. In short, territorial foresight contributes to making policies future-wise, i.e. fit for the future. Keywords

Territorial impact assessment · Territorial foresight · Forward thinking · Future · Policy-making · Regional foresight

Maps are developed by Sebastian Hans. K. Böhme (*) · C. Lüer · F. Holstein Spatial Foresight, Heisdorf, Luxembourg Spatial Foresight, Berlin, Germany Spatial Foresight, Paris, France e-mail: [email protected]; [email protected]; [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_9

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Introduction

The development of the European Spatial Development Perspective (ESDP) started the debate on the need for strong territorial and future dimensions in policy-making. More than 20  years ago, it promoted the idea of territorial impact assessment at European level. Indeed, policy-making shapes – explicitly or implicitly – the future developments of our territories; hence, understanding the consequences of policies helps to improve them. Since the development of the European Spatial Development Perspective, territorial impact assessment has developed from appraising impacts of concrete projects or infrastructure investments to appraising potential impacts of policies – first ex post and then mainly ex ante. Today, this is being taken one step further by converging the approaches to territorial impact assessment and territorial foresight. A new approach to territorial foresight was developed at European level and also tested at national level in Luxembourg. Territorial foresight combines elements of territorial impact assessments and foresight approaches. It is a structured process that (a) focuses on long-term developments and their potential future impacts on territories, (b) is based on lateral thinking in participative approaches and (c) provides support for decision-making processes and designing forward-looking policies. This chapter argues to adopt territorial foresight approaches rather than territorial impact assessment when future territorial developments shall be discussed. In doing so, this chapter presents key features of the developed territorial foresight approach. First, we discuss the main determinants and characteristics of the approach. Afterwards, the steps for conducting territorial foresight are presented. Four main steps guide researchers and policymakers in assessing possible territorial consequence of policy objectives or trends. To detail the added value of the approach, the fourth section presents a few examples of cases in which the territorial foresight approach has been developed and tested. The last section reflects on the added value of territorial foresight approaches in policy-making processes. The chapter concludes that territorial foresight supports policymakers when developing and implementing future-oriented and integrated territorial policies.

9.2

Why Territorial Foresight?

Many of today’s challenges and crises of the European Union can be traced back to neglecting a spatial dimension in policy-making. Most prominently, the current risk of territorial fragmentation is a result of places feeling discontent or left behind (Böhme and Martin 2019; Dijkstra et  al. 2018; Rodríguez-Pose 2018). This is a result of the fact that there is an increasingly diverse ‘European geography of future perspectives’ (Böhme et al. 2019). Consequently, different cities and regions face different everyday realities, and their inhabitants see different future perspectives, not all of them hopeful ones. Therefore, we argue that policy-making and public

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investments would benefit from a stronger spatial dimension. One possibility to strengthen the spatial dimension in policy making is territorial foresight.

9.2.1 What Is Territorial Foresight? Territorial foresight is a future-oriented approach characterised by (a) critical, lateral thinking concerning long-term developments and their impacts on territorial development, (b) wider participatory engagement and (c) informing public and/or private decision-making. Territorial foresight provides a framework to support people concerned with a common issue to jointly think about possible futures and its territorial consequences in a structured and constructive way. As a foresight process, it provides various tools to support participants in structured forward thinking (Loveridge 2009; Steinmüller and Steinmüller 2006). Territorial foresight can be conducted at any geographical level, from the very local to the European or global level (ESPON 2018a). In short, the approach to territorial foresight discussed here brings together standard foresight approaches and elements of the territorial impact assessment (Böhme and Eser 2008; Essig and Kaucic 2017). It can be applied to any future trends, policy objectives, visions, utopias or dystopias. Foresight or forward thinking in general terms is based on the school of systemic thinking (e.g. Vester 2003). Although humans have been engaging with foresight in various forms for more than 2500 years (Loveridge 2009), it became in vogue in the 1960s and 1970s both in terms of technology forecasting and societal critics (e.g. Meadows and Club of Rome 1972). Foresight became increasingly multidisciplinary and brought together qualitative and quantitative analysis, assuming that alternative futures are possible and considering possible actions that could be taken to shape the future (Danish Technological Institute et al. 2010). Foresight aims at informing private and/or public decision-making to make them more ‘future-wise’ (e.g. Dixon 2007; European Strategy and Policy Analysis System 2015; Gaub and European Strategy and Policy Analysis System 2019). Traditionally, foresight is spatially blind and focuses on particular development features rather than paying attention to spatial differences. Even in the cases of regional foresight, the regional component merely describes the geographical delineation of the area for which the foresight is conducted but does not imply that (intra-)regional differences are considered. On the other side, however, territorial impact assessment focuses on the spatial dimension of developments but places hardly any emphasis on future-oriented forward thinking. It has its roots in the assessment of possible impacts of large-scale infrastructure investments on spatial development in the surrounding of these infrastructures. To mention, for example, are the obligatory spatial impact assessments in Austria (Raumverträglichkeitsprüfung) and Germany (Raumordnungsverfahren), but also similar procedures in Portugal, Wallonia in Belgium and Finland are often linked to environmental impact assessments (Böhme and Eser 2008). In the 1990s, the idea of impact assessments was developed further and no longer just focused on

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specific investments or plans but started to consider wider policies and in particular EU policies. ESPON has been particularly active in developing various approaches and methodologies for territorial impact assessments of policies. In the beginning, the focus was often on ex post impact assessments, but subsequently territorial impact assessments started to become more future oriented by shifting the focus on ex ante impact assessments and combining quantitative modelling approaches and qualitative as well as participatory approaches. In short, the methodology that emerged helps to assess positive or negative, intended, unintended or even unknown territorial impacts of a policy. The ESPON approach to territorial impact assessment is based on the vulnerability concept of the IPCC (Intergovernmental Panel on Climate Change) and assesses exposure and sensitivity of regions with regard to the policy in question (ESPON 2012). In the meantime, a wide body of research on territorial impact assessments on various geographical levels emerged (e.g. Camagni 2006; Essig and Kaucic 2017; Evers et al. 2009; Medeiros 2014, 2015). Taking the idea of territorial impact assessment one step further, the FP7 project FLAGSHIP made first attempts to bring together territorial impact assessment and foresight by addressing the territorial dimension of (future) grand societal challenges (Böhme and Lüer 2017; Lüer et  al. 2015). Drawing on the experience of territorial impact assessments, the idea of territorial impacts was introduced into the foresight approach. Territorial impacts are defined through the exposure and sensitivity of a territory towards a specific component (ESPON 2018a): • Exposure: taking different components of the foresight topic as starting point, exposure is determined by asking: To what degree is a region/territory likely to be (positively or negatively) affected by the change? • Sensitivity: taking regional characteristics as starting point, sensitivity is determined by asking: To what degree will regional development be affected? What is the intensity of impacts due to specific regional characteristics and endowments? In the context of an ESPON (2018a) study, this approach has been further elaborated to a territorial foresight methodology, which takes the future as starting point and which can be applied to trends and policy objectives. Later on, this approach has been tested in a national context in Luxembourg. Here, the territorial implications of the country’s strategy for the third industrial revolution and the impact of economic and demographic developments on land use and water issues were assessed.

9.2.2 Why Should One Use Territorial Foresight? Territorial foresight can help to better understand the spatial implications of either development trends or ideas for wanted or unwanted futures. In an earlier ESPON (2018a) study, we have identified various benefits territorial foresight can deliver:

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• Approaching complexity and uncertainty: With a focus on participatory approaches, territorial foresight breaks down complexities and uncertainties by bringing together views from different players, in case no or insufficient quantitative information about the future is available. If quantitative information is available, territorial foresight enriches the debate. • Understanding territorial consequences of (im)possible futures: This helps to understand possible territorial consequences of major trends, overarching development objectives or various utopias and dystopias. • Creating wide ownership: A strong focus on participatory forward thinking involving people tackling a common issue enhances the ownership of the foresight topic, possible territorial consequences and pointers for policy-making. This demands for participation and interaction. • Informing decision-making: Being aware about territorial consequences of a foresight topic can inform policy-making. This can support policy decisions that prevent unwanted or accelerate wanted implications.

9.3

Steps to Conduct a Territorial Foresight

Several steps guide researchers and policymakers in assessing the territorial consequences of a policy objective, vision or trend. In the following, we briefly address the main steps of a territorial foresight according to a handbook, which we developed during the ESPON project ‘Possible Territorial Futures’ (ESPON 2018b). The steps build on the assumption that the purpose of foresight is not just to think about the future but to support policy decisions to be taken nowadays. Any future-­ oriented study is, if anything, a call for action – the knowledge gathered is not an end in itself but a means supporting the deliberation required to agree on a given set of actions: which road to take – and often, the conclusion of a foresight study is to take the harder road ahead. Since the possible futures we are able to image are heavily constrained by our memories and present concerns, as well as by our specialised knowledge, foresight always requires a well-informed deliberation by as many and as knowledgeable and sensitive persons as possible. Needless to say, the outcomes of this deliberation process will be more useful if sound methods are applied. Consequently, foresight is understood as a framework for a group of people concerned with common issues at stake to think jointly and imagine possible futures in a structured and constructive way. The centre piece of the approach is a well-prepared and clearly structured participatory process. The participatory approach to territorial foresight contains a number of steps. Overall, the various steps can be grouped into several distinct phases, which are spelled out in the following. The first step focuses on the clear definition of the foresight question, followed by background research in step 2 to prepare the participatory processes in step 3. Finally, step 4 focuses on the post-processing, i.e. all bits and pieces are brought together, complementary information is found where needed and the narrative is polished.

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9.3.1 S  tep 1. Definition of the Question: What Defines the Foresight Question to Be Addressed? A first exploration and definition of the topic of the foresight exercise is needed. Most easily foresight questions can be formulated as ‘what if questions’, which need to comprise three elements: 1. Content – the actual topic of the foresight question (e.g. what if artificial intelligence becomes the backbone of our economy?) 2. Geography – the delineation of the territory for which will the foresight be conducted (e.g. the EU or North Macedonia) 3. Time  – the time horizon, i.e. by when shall that have become reality (e.g. by 2030 or by 2050) So, a complete territorial foresight question would read as: What if topic X became reality in place Y by year Z (e.g. “What if artificial intelligence became the backbone of our economy in the EU by 2030?”). Following this information, key facts and figures about the three elements can be collected to detail the understanding of the topic, the territory and the year for which the foresight shall be conducted. This entails developing key assumptions about what that topic will change in general (not necessarily in territorial terms) and exploring possible factors that might play a role in the future situation, assessing the current situation and considering potential disruptors. When collecting details about the territory, it is advisable to consider also relevant information on neighbouring territories or other territories with close linkages to the territory in question.

9.3.2 S  tep 2. Background Research: What Do the Data Say About Possible Territorial Implications of the Foresight Question? To explore possible territorial implications of the foresight question and break down the complexity of future thinking, elements of a territorial impact assessment (ESPON 2012; Essig and Kaucic 2017) are used for identifying key factors and their relations from different perspectives. This includes environmental, economic, societal and governance aspects of the foresight topic at stake. Before entering a participatory process, existing literature, data and models have to be employed to provide first (quantitative) insights that support territorial forward thinking with regard to the foresight topic. Although the exact literature, data and models to be utilised depend on the foresight topic, the geography and how far into the future one wants to look, there are a few common features to be addressed:

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• System picture: Which factors influence what and which other factors and which types of territories are addressed by this? In an ideal case, this can be pinned down to a number of concrete indicators and quantifiable pieces of information. • Exposure (foresight question as a starting point): Are the expected changes especially relevant for certain types of regions? This is mainly to find out which regions/territories to consider for further discussion. To give a simplified example, climate change implies rising sea water levels for all coastal areas, i.e. coastal areas are exposed to climate change. • Sensitivity (regional characteristics as starting point): To what degree will different types of regions/territories be affected? This is mainly to discuss the intensity of impacts that can be expected in exposed regions/territories, considering the specific characteristics of the regions/territories. To continue the above simplified example, coastal regions with low population density, low economic activities in areas potentially flooded through sea-level rises and enormous financial means are less sensitive than more densely populated coastal areas.

9.3.3 S  tep 3. Participatory Processes: What Do Stakeholders Say About Possible Territorial Implications of the Foresight Topic? For most foresight questions, the ‘what if question’ stretches far beyond the boundaries of available quantitative data, theories and computational models. This is where the strength of classical foresight processes comes into play as foresight supports structured lateral forward thinking about highly uncertain and complex developments (Loveridge 2009). Forward thinking about the territorial dimension of trends or policy objectives implies participatory processes, especially engaging experts, stakeholders and possibly also citizens. Participatory processes in territorial foresight increase both the robustness and representativeness of the result. A range of different participatory elements can be employed, even within one and the same foresight process (ESPON 2018b): • Online surveys to frame the foresight topics by collecting insights on how to understand them. • Participatory workshops to discuss territorial development perspectives and systematic approaches to the foresight topics. The result may shape the narrative on the future and further refine the framework for the foresight topic. • Online surveys on specific dimensions of a foresight topic to assess which territories are most likely to be positively or negatively affected. • Participatory workshops to assess the territorial implications of the foresight topic and develop initial maps of how the territory might look in the future. • Webinars to refine the foresight topic and potential extreme case assumptions and developments further.

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Regardless which participatory approach is taken, the selection of stakeholders is a key element for a successful participatory process. Basically, the composition of participants needs to strike a careful balance between experts on the foresight topic, experts on the territories covered and different types of stakeholders. Ideally, participants represent various types of organisations (e.g. academia, public authorities, NGOs) and places (e.g. rural and urban, core and peripheral areas) in the territory covered. Including a variety of different stakeholders allows to broaden the understanding of the topic, to cross-fertilise insights and to offer a platform for learning and exchange. Once the relevant stakeholders are brought on board for the participatory foresight process, a number of key tasks need to be conducted. The content and structure of the participatory process has proven to be most robust when it includes the following elements (ESPON 2018b) – which build on the corresponding elements of step 2 (see above): • Explore system picture: What are the most important cause-effect chains, i.e. which factors influence what and which other factors and which types of territories are addressed by this? In an ideal case, this can be pinned down to a number of concrete indicators and quantifiable pieces of information. • Explore exposure (foresight question as a starting point): Are the expected changes especially relevant for certain types of regions? This is mainly to find out which regions/territories to consider for further discussion. • Explore sensitivity (regional characteristics as starting point): To what degree will a region/territory be affected? This is mainly to discuss the intensity of impacts that can be expected in exposed regions/territories and consider the specific characteristics of the regions/territories. • Sketching (mapping and narrative of the future territory): The territorial impact of the future situation results in a sketch of the future situation and a foresight narrative. The sketch illustrates the territorial dimension in the future situation. Different inputs such as maps of the current situation of key territorial features and their changes over time, e.g. with regard to population structures, geographic specificities or economic structures, help participants to map the territorial dimension. The foresight narrative supports the sketch and details the rationale of the future situation. The participatory approaches provide important insights from the stakeholders’ and experts’ point of view. They may also come up with new uncertainties about future territorial implications.

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9.3.4 S  tep 4. Post-processing: What Does the Combined Picture Say About Possible Territorial Implications of the Foresight Topic? Bringing together the results of the desktop analysis and data crunching with the results of the participatory approaches will most likely pose questions for supplementary research and information gathering. Once this has been done, the final narrative and territorial images or maps can be developed, including necessary refinements and polishing to increase consistency and persuasiveness. This step may also include the development of recommendations or pointers for action on how to deal with the territorial implications. In particular, the latter may require various feedback loops with the participants with a particular focus on policy and decision-makers (ESPON 2018b).

9.4

Examples of Territorial Foresight

The above presented method has been developed and tested in different contexts. The following sections present some key findings of developing, testing and applying the territorial foresight approach. First attempts to marry territorial impact assessment with foresight approaches were performed in the frame of an FP7 project, FLAGSHIP (Forward-Looking Analysis of Grand Societal cHallenges and Innovative Policies). These approaches have been further developed in the ESPON project ‘Possible Territorial Futures’, which illustrated the variety of desired and undesired effects of (im)possible futures. Moreover, the project concluded that approach would be applicable at any territorial level. The approach has thereupon been tested twice at national level in Luxembourg, when discussing the territorial implications for a national strategy for the next industrial transition and when elaborating future scenarios focusing on land use and water issues. All of the below examples of territorial foresight are based on extinctive participatory processes and the elaboration of various alternative possible futures with several maps for each of them. The below presents just a snapshot of each example to provide a flavour of the diversity of possible results.

9.4.1 Energy and Environment in Europe in 2050 Our starting point to extend the approach of territorial impact assessment towards territorial foresight at European level was the FP7 FLAGSHIP project (Forward-­ Looking Analysis of Grand Societal cHallenges and Innovative Policies). Against the background of two visions for Europe in 2050  – a pragmatic vision

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(‘Perseverance’) based on the assumption of implementing current policies and following predominant policy paradigms and an idealistic vision (‘Metamorphosis’) based on a fundamental paradigm shift of values towards sustainability and equality  – different topics were discussed regarding the spatial structure of Europe (Böhme and Lüer 2016; Lüer et al. 2015). The subsequent guiding question for the topic of energy and environment was: What would the European energy and transport system look like in 2050 if the ‘Metamorphosis’ vision were achieved? Based on a selection of trends and related quantitative and qualitative data, indicative maps were produced to illustrate the current situation in Europe in four thematic fields (ageing and migration; goods and services; knowledge and technology; energy and environment). Applying a process of several working steps (e.g. workshops with experts, in-depth regional/local case studies, collection of complementary information), we developed for each thematic field a map on the future territorial picture under the assumptions of each vision. The assumed paradigm shift will lead to a shift in energy production and consumption. The energy system will rely on small-scale units that produce the energy they need and store the energy they do not consume immediately. The units of this energy system will be interconnected and conjointly establish a decentralised large-­ scale grid, which relies on information and communication technologies. The backbone of the European transport network will be an integrated European railway system that will have been built from a truly European perspective and will connect the main agglomeration areas. Aviation in Europe will be reduced to ensuring accessibility of remote areas. For Europe’s access to the world, aviation will still play an important role. The aviation system will however be also decentralised. The main hubs in the European core (Frankfurt, Amsterdam, London, Paris) will be replaced by more peripheral airports, each of them with an own territorial focus (Reykjavik – North America; Istanbul – East Africa/Middle and Far East; Madrid – Latin America/West Africa; Helsinki – Asia; see Fig. 9.1).

9.4.2 A Place-Based Circular Economy for Europe Another example of territorial foresight was conducted in the course of the ESPON project on possible European territorial futures. The project was based on the experience from the FLAGSHIP project and concerned among others a placed-based circularly economy at European level (ESPON 2018a). What would the European territory look like in 2030 if the economy were a place-based circular economy? A place-based circular economy brings together the idea of the circular economy (see Ellen MacArthur Foundation et  al. 2015; European Commission 2015b; European Environment Agency 2016; World Economic Forum 2014, 2015) with the idea of place-based policy-making (see Barca 2009; European Commission 2015a; Zaucha 2017; Zaucha et al. 2013). In a place-based circular economy, resource efficiency is key to economic activities, particularly production. This includes reducing waste to a minimum while maintaining the value of products, materials and resources

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Fig. 9.1  The energy and transport system in the ‘Metamorphosis’ vision in 2050 (Source: Lüer et al. 2015)

in the economy for as long as possible. In a circular economy, the amount of newly produced products declines as reuse and repair become mainstream. The transition to a place-based circular economy implies drastic transition in all cities and regions, and therefore, territorial patterns in Europe would change. Europe’s territorial structure would differ significantly from today’s structure due to effects on urbanisation and the overall territorial balance. At European level, differences between strong socio-economic areas and lagging regions may reduce under a place-based circular economy. The map below illustrates the potential for small and medium-sized towns, as well as the challenges for sparsely populated areas and inner peripheries. It also highlights the importance of networks in driving innovations in a circular economy and leading areas in the sharing economy. The map

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Fig. 9.2  Territorial impacts of the transition to a place-based circular economy (Source: ESPON 2018a)

shows areas which could expect particular transition challenges in consumer behaviour (often tourists) and changing manufacturing structures (see Fig. 9.2). Going into more detail, the study (ESPON 2018a) came up with following reflections on varied territorial impacts of a place-based circular economy: • A focus on labour-intensive repair, reuse and recycle activities will create new jobs throughout Europe and benefit polycentric development with new jobs emerging in smaller and lagging areas. However, low population areas and major urban inner peripheries will not benefit from this. • An economic model based on sharing and repairing holds potential for increasing territorial cohesion, softening the dominance of urban agglomerations. Nevertheless, boosting the sharing economy will be easier in some places than in others. It might be particularly challenging for areas with currently low levels of sharing economy, low levels of social trust and/or low population density. • Trust and governance become key aspects to promote an understanding of well-­ being beyond GDP. The areas with the most dramatic transition processes are South-Eastern Romania, Eastern Bulgaria and Southern Italy. • Major transport hubs for freight (ports and airports) will decline in importance as a result of the changing importance of transport. • International export and import of goods will decline dramatically further emphasising territorial disparities in Europe. Regions heavily dependent on

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large-scale manufacturing may fall behind, regions leading in green technology may become even more dominant, and some behavioural changes may affect convergence regions more than leading regions. • In a place-based circular economy, places with high levels of manufacturing and low resource efficiency risk falling behind (large parts of manufacturing may even disappear). • Regions with significant innovation and in particular eco-innovation could become champions, producing solutions that spread throughout Europe. • Household waste volumes and recycling are particular challenges for tourist areas with low recycling cultures as result of behavioural changes to household waste. The outcomes of the territorial foresight, such as the new territorial balance, serve as eye-opener to policymakers. In essence, it shows policymakers that a transition to a place-based circular economy implies dramatic changes for all parts of Europe and will also affect the European urban system and territorial balance.

9.4.3 T  he Third Industrial Revolution: A Smart Digital Economy for Luxembourg In 2015–2016, a vision and strategy for Luxembourg’s transition process of the third Industrial Revolution was developed (TIR Consulting Group 2016). The so-called Rifkin study was commissioned by the national Ministry of Economics, which painted a future picture of Luxembourg. Although not addressed in the ‘Rifkin study’, it became clear that this vision and strategy will mean different things for different places in the country. This triggered questions about the spatial preconditions and implications that may result from the implementation of the various transitions suggested in the ‘Rifkin study’. One key aspect of the future economy addressed by the ‘Rifkin study’ is the smart digital economy. Other elements referred to industrial symbiosis and the role of prosumers in the context of a circular economy. The smart digital economy is based on modern information and communications technologies (ICT) to bring together economic profitability and sustainability. In contrast to the ubiquitous availability of ICT applications, the development and added value in the ICT sector are already today concentrated to a few hot spots. Besides the Silicon Valley as the main global hot spot, also second-tier cities like Tel Aviv, Singapore, London, Barcelona and Zurich cover various aspects of the digital economy and do not focus on particular aspects, e.g. economic ecosystems, legal framework conditions, institutions and capabilities. The transition process therefore concerns all economic branches and territories in Luxembourg. Three examples are the financial sector, the automotive cluster and the general importance of large enterprises: (i) The financial sector plays a crucial role in the transition process. Already today it is characterised by digital processes. It is spatially concentrated in Luxembourg City, and hence, subsequent investments and restructuring processes on the labour market will

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mainly take place in the capital. (ii) Comprehensive changes in the mobility sector will imply structural changes for the automotive sector. The ‘AutoMobility Cluster’ can play an important role in this process. Related Research and Development activities currently concentrate at two places (Bissen/Colmar-Berg and Belval). (iii) Large enterprises will have to be the main drivers behind the transition process. Most of them are located in the capital, its surroundings and neighbouring municipalities. Bringing together information about the current economic structure, the development perspectives of the vision and strategy explored in the ‘Rifkin study’ and the spatial characteristics of Luxembourg leads to a few key messages what different territories need to do in the transition process. Already today, Luxembourg City is the national economic heart that is embedded in global networks. For Luxembourg City, the transition process will be no option but rather a necessity to keep pace in global competition and pick up and work on own development opportunities. For the medium-sized centres as well as the agglomeration areas in the south and the north of the country, the transition process will offer new opportunities (see Fig.  9.3). If enterprises in these areas make use of these opportunities, they will benefit significantly. Municipalities in border areas might also benefit from increasing cross-border flows. In-between areas that comprise smaller towns between the medium-sized agglomeration areas might also benefit from the transition process, however in a different way than regional centres. They could offer land for additional decentralised locations of companies that need more space or for remote forms of employment. Rural areas will also benefit from the new products, services and increasing population. The overall development will however rather be a challenge because the rural areas will first need to make considerable efforts to provide the necessary physical and digital infrastructure. They might hence still remain dependent on the development in other or neighbouring areas.

9.4.4 E  xploring the Territorial Implications for Nature-Based Water Governance in Luxembourg To better understand the relationship between water and land use, the University of Luxembourg engaged in a scenario development project, Nexus Futures.1 Nexus Futures applies a scenario building approach based on future-oriented dialogues involving participants with different expertise and interests to transform social practice (see König 2018). The project develops three scenarios of possible futures for Luxembourg. The scenarios have a strong thematic focus with little spatial differentiation. In order to assess territorial consequences of the scenarios, elements of the territorial foresight approach were used. In doing so, the following question could

 See https://sustainabilityscience.uni.lu/nexus-futures/.

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Fig. 9.3  Development opportunities in the smart digital economy in Luxembourg (Source: Spatial Foresight (own elaboration))

be formulated: How would Luxembourg’s territory look like in 2045 if water governance would be nature based? One of the scenarios describes Luxembourg’s future as smart and circular. The Smart Growth scenario reinforces current economic and demographic trends. Until 2045, technical solutions will help to make value chains more circular, but fully closed circuits are not expected. At the same time, increasing social inequalities will lead to tensions and stand in the way of a sustainable society. By 2045, Luxembourg has grown to approximately 1.3  million inhabitants, accompanied by increasing

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land-use demands. More land needs to be made available for the construction of homes, offices and industrial facilities. The assumptions and relations between key elements in the scenario have been mapped. Mapping the territorial implications helped the researchers to define their scenarios further. The maps provoked discussions about alternative ways for water governance. As such, the maps functioned as eye-opener to discover contradicting elements in the scenarios, in the assumptions and in cause-effect relations. Moreover, they serve as starting point for defining possible policy actions. Figure  9.4  Highlights possible territorial implications of the Smart Growth scenario. In order to be able to moderate the traffic flows and the ecosystem claims, the scenario tries to avoid sprawl. In the sense of polycentric development or decentralised concentration, the growth of the population and the economy focuses on

Fig. 9.4  Territorial impact of the smart growth scenario for Luxembourg in 2045 (Source: Spatial Foresight for NEXUS Futures)

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regional centres or growth poles. The four ‘Smart Development Centres’ are of particular importance for economic development. Their present economic structure provides them with favourable starting positions for a smart growth scenario. In 2045, a total of about 470,000 people live in these centres, i.e. 36% of the population or nearly twice as many as today live there. There are also ten additional regional centres, which together have about 530,000 inhabitants as regular development centres, i.e. about one-third more than today, or 41% of the population of Luxembourg in 2045. Three hundred thousand people live in rural areas, i.e. 20% more than today, or 23% of the population of Luxembourg in 2045. Rural areas are not large enough to provide ecosystem services to development centres. Excessive water abstraction, fragmentation and economic neglect have not improved the attractiveness of rural areas. Jobs continue to be highly spatially concentrated, and cities, especially Luxembourg City, remain the main attractions for the rural population. Centres focus on economic activities that are strongly integrated into the global economic system. The Internet is the backbone of economic development and is increasingly being differentiated. Different economic usage claims lead to a spatial differentiation of the Internet, e.g. Financial Internet of Things (Finternet), Internet of Value, Internet of Services, Internet of Things and Internet of Agriculture. Overall, in this scenario, the concentration on selected growth centres and a certain spatial division of labour go hand in hand with the dismemberment of natural areas (for transport and settlement areas). Ensuring increasing demands in terms of water consumption and eco-services will be a challenge.

9.5

Added Value of Territorial Foresight

The territorial foresight approach has evolved and been further elaborated step by step through the various applications presented above. In all of them, participatory and iterative processes played a crucial role, and all of them tested different levels of geographical detail. While the first European examples focus on overall network and economic structures and their spatial variations, the Luxembourg examples illustrate that territorial foresight can reach a relatively high level of geographical detail. Taken together, over time, a territorial impact assessment for future trends, visions and policies has been developed, or to put it differently, territorial impact assessment has been further developed towards territorial foresight. Given the complexity and uncertainty of future trends, visions and policies and their territorial dimension, territorial foresight draws on quantitative and qualitative approaches with a particular stress on lateral thinking in participatory processes. In an earlier ESPON (2018a) study, we outlined the following key advantages of territorial foresight:

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• Territorial foresight approaches support policymakers to think territorially. The different steps of the approach allow to unravel gradually the territorial dimension of future situations. Particularly, interaction with experts with diverse backgrounds allows to discover the foresight topic from different perspectives. This supports the development of an integrated view of the future situation. • Territorial foresight allows to anticipate future situations. The insights gathered during the territorial foresight provide tools to determine ways to deal with the future situation. In particular, the mapping of territorial implications and the territorial narrative detailing the key factors and causal relations provide policymakers with tools to anticipate on future developments. • Territorial foresight increases ownership among key stakeholders. The approach offers a platform for discussion, exchange and mutual learning. This platform is not only beneficial for policymakers conducting territorial foresight but also creates a window of opportunity to engage experts in policy-making processes. Moreover, the fuzzy maps may be used to further stimulate discussions on the future situation and pathways towards this situation. In short, territorial foresight approaches support better policy-making. Territorial foresight processes can therefore be recommended for policymakers (1) that are uncertain about the territorial dimension of visions, trends or policy objectives, (2) that are seeking for levers to anticipate or address the territorial dimension of future situations and (3) that want to build ownership among a wider group of stakeholders. In other words, territorial foresight helps to make policy and decision-making processes better fit for the future.

References Barca F (2009) An agenda for a reformed cohesion policy. A place-based approach to meeting European Union challenges and expectations. Retrieved from ec.europa.eu/regional_policy/ archive/policy/future/pdf/report_barca_v0306.pdf Böhme K, Eser TW (2008) Territorial impact analysis of EU policies. In: Faludi A (ed) European spatial research and planning. Lincoln Institute of Land Policy, Cambridge, MA, pp 43–66 Böhme K, Lüer C (2016) Europe’s territorial futures between daydreams and nightmares. Europa XXI.  Territorial Uncertainty as a Challenge for Regional Policy in Europe 2016(30):5–22. https://doi.org/10.7163/Eu21.2016.30.1 Böhme K, Lüer C (2017) Assessing territorial impacts of future trends. In: Medeiros E (ed) Uncovering the territorial dimension of European Union Cohesion Policy. Routledge, Abingdon, pp 161–183 Böhme K, Martin D (2019) Territorial fragmentation: A major european challenge (Territorial Thinkers’ Briefing No. 5), Luxembourg: Territorial Thinkers. Böhme K, Lüer C, Toptsidou M (2019) Towards a european geography of future perspectives: a story of urban concentration. In: Medeiros E (ed) Territorial cohesion: the urban dimension. Springer International Publishing, Cham, pp 173–191. https://doi.org/10.1007/978-3-030-03386-6_9 Camagni R (2006) Territorial impact assessment- TIA: a methodological proposal. In: Capello R (ed) Knowledge and accessibility for regional cohesion in the enlarged Europe: Vol. Vol.5 N.2/2006. Franco Angeli, Milano, pp 135–146

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Danish Technological Institute, ÖSB Consulting, Warwick Institute for Employment Research (2010) Anticipating skill needs of the labour force and equipping people for new jobs. In: Which role for Public Employment Services in early identification of skill needs and labour up-skilling? [Final Report]. European Commission, Brussels Dijkstra L, Poelman H, Rodríguez-Pose A (2018) The geography of EU discontent (No. 12/2018). Retrieved from Publications Office of the European Union website: https://ec.europa.eu/ regional_policy/sources/docgener/work/2018_02_geog_discontent.pdf Dixon P (2007) Futurewise: the six faces of global change; a personal and corporate guide to survival and success in the third millennium, 4th edn. Profile, London Ellen MacArthur Foundation, McKinsey Centre for Business and Environment, Stiftungsfonds für Umweltökonomie und Nachhaltigkeit (2015) Growth within: a circular economy vision for a competitive Europe. Retrieved from https://www.ellenmacarthurfoundation.org/assets/downloads/publications/EllenMacArthurFoundation_Growth-Within_July15.pdf ESPON (2012) ARTS  – assessment of regional and territorial sensitivity. Final report. Version 30/07/2012. ESPON, Luxembourg ESPON (2018a) Possible European territorial futures. Retrieved from ESPON website: https:// www.espon.eu/territorial-futures ESPON (2018b) Possible European territorial futures. Guidelines to territorial foresight. Retrieved from ESPON website: https://www.espon.eu/territorial-futures Essig S, Kaucic J (2017) ESPON TIA: balancing between policy orientation, practicability and scientific ambition. In: Medeiros E (ed) Uncovering the territorial dimension of European Union Cohesion Policy. Routledge, Abingdon, pp 184–201 European Commission (2015a) Territorial Agenda 2020 put in practice. Enhancing the efficiency and effectiveness of Cohesion Policy by a place-based approach. European Commission, Brussels European Commission (2015b, February 12) Communication from the commission to the European Parliament, the Council, the European Economic and Social Committee and to the Committee of the Regions. Closing the loop. An EU action plan for the Circular Economy. Retrieved from http://eur-lex.europa.eu/legal-content/EN/TXT/?qid=1453384154337&uri=C ELEX:52015DC0614 European Environment Agency (2016) Circular economy in Europe. Developing the knowledge base (EEA Report No. 2/2016). European Environment Agency, Luxembourg European Strategy and Policy Analysis System (2015) Global trends to 2030: can the EU meet the challenges ahead? European Strategy and Policy Analysis System, Brussels Evers D, Tennekes J, Borsboom J, van den Heiligenberg H, Thissen M (2009) A territorial impact assessment of territorial cohesion for the Netherlands. The Netherlands Environmental Assessment Agency, The Hague Gaub F, European Strategy and Policy Analysis System (2019) Global trends to 2030: challenges and choices for Europe. Retrieved from https://espas.secure.europarl.europa.eu/orbis/sites/ default/files/generated/document/en/ESPAS_Report2019.pdf König A (2018) Outlook. Citizens and science in the Anthropocene. In: König A, Ravetz JR (eds) Sustainability science: key issues. Routledge, London/New York, pp 345–355 Loveridge D (2009) Foresight: the art and science of anticipating the future. Routledge, New York/London Lüer C, Böhme K, Jæger S, Hans S, Madeira N, Holstein F et al (2015) Report on territorial impact projections. Final deliverable (D7.2) of work package 7 on Territorial Governance. FLAGSHIP project, 7th Framework Programme (FP7) Meadows DH, Club of Rome (eds) (1972) The limits to growth; a report for the Club of Rome’s project on the predicament of mankind. Universe Books, New York Medeiros E (2014) Territorial impact assessment (TIA): the process, methods and techniques. University of Lisbon, Lisbon Medeiros E (2015) Territorial impact assessment and cross-border cooperation. Reg Stud 2(1):97–115. https://doi.org/10.1080/21681376.2014.999108

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Rodríguez-Pose A (2018) The revenge of the places that don’t matter (and what to do about it). Camb J Reg Econ Soc 11(1):189–209 Steinmüller K, Steinmüller A (2006) Die Zukunft der Technologien: [Ausgangspunkt  – 2010–2020–2050 – plus ultra]. Murmann, Hamburg TIR Consulting Group (2016) The 3rd industrial revolution strategy study for the Grand Duchy of Luxembourg [Final Strategy Study]. TIR Consulting Group LLC, Luxembourg Vester F (2003) Die Kunst vernetzt zu denken: Ideen und Werkzeuge für einen neuen Umgang mit Komplexität; ein Bericht an den Club of Rome. Deutscher Taschenbuchverlag, München World Economic Forum (2014) Towards the circular economy: accelerating the scale-up across global supply chains. Retrieved from World Economic Forum website: http://www3.weforum. org/docs/WEF_ENV_TowardsCircularEconomy_Report_2014.pdf World Economic Forum (2015) Intelligent assets. Unlocking the circular economy potential. Retrieved from World Economic Forum website: https://www.weforum.org/reports/ intelligent-assets-unlocking-the-circular-economy-potential Zaucha J (2017) The territorial keys of policies. In: Medeiros E (ed) Uncovering the territorial dimension of European Union Cohesion Policy. Routledge, Abingdon, pp 23–43 Zaucha J, Świątek D, Stanczuk-Olejnik K (2013) Place-based. Territorially sensitive and integrated approach. Polish Ministry of Regional Development, Warsaw Dr. Kai Böhme  is founder and director of Spatial Foresight, a private consultancy and independent think tank in the area of European territorial policies and research, with team members located in Luxembourg, Germany and France. Kai holds PhD in Management Science from the University of Nijmegen (the Netherlands) and a master’s in Spatial Planning from the University of Dortmund (Germany). He specialises in European regional and territorial research and policies, international comparative studies in the fields of regional development policies, spatial planning, territorial governance and territorial impacts of sector policies. He has a truly European background and considerable experience in policy advice at European and national levels as well as in the management of international applied research and consultancy projects. Christian Lüer  is a senior consultant at Spatial Foresight and a visiting lecturer in the Department of Geography at the University of Münster, Germany. He has a particular interest in territorial governance, spatial planning, cross-border and transnational cooperation, and territorial impact analysis. Over the past years, he has been involved in research and consultancy projects for regional, national, cross-­border, transnational and EU institutions. Frank Holstein  is a consultant at Spatial Foresight. He holds a joint master degree in European Spatial Planning and Regional Development from Radboud University (the Netherlands) and Blekinge Institute of Technology (Sweden). Among his main professional interests lie in the European territorial cooperation, territorial governance and European Cohesion Policy. At Spatial Foresight, he has been involved in projects for DG Regio, the European Parliament and various Interreg programmes. Furthermore, he is involved in the planning and organisation of different participatory processes including focus groups, workshops and events.

The LUISA Territorial Modelling Platform and Urban Data Platform: An EU-Wide Holistic Approach

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Carlo Lavalle, Filipe Batista E. Silva, Claudia Baranzelli, Chris Jacobs-Crisioni, Mert Kompil, Carolina Perpiña Castillo, Pilar Vizcaino, Ricardo Ribeiro Barranco, Ine Vandecasteele, Boyan Kavalov, Jean-Philippe Aurambout, Andrius Kucas, Alice Siragusa, and Davide Auteri

Abstract

The Joint Research Centre of the European Commission has implemented the LUISA Territorial Modelling Platform for ex ante evaluation of European policies, measures and initiatives that might have a direct or indirect territorial impact. LUISA is based on the concept of ‘land function’ for cross-sector integration and for the representation of complex system dynamics. Beyond a traditional land use model, LUISA adopts a new approach towards activity-based modelling based upon the endogenous dynamic allocation of population, services and activities. The LUISA Platform consists of set of connected modules. A regional module is employed to regionalise (downscale) exogenous socio-­ economic projections and produce scenarios of regional development according to defined options of growth. An advanced module for the local distribution and allocation of Land Functions is based upon the  dynamic interaction between population distribution, accessibility potential and the utility-based allocation of services. Feedbacks and spillover effects are included within and between the local and regional modules. LUISA outputs are represented in terms of ‘territorial indicators’ covering a wide range of themes, from economy to demography, to accessibility and transport to resource efficiency. The territorial indicators are routinely updated and distributed by online tool Urban Data Platform Plus of the Knowledge Centre for Territorial Policies. C. Lavalle (*) · F. B. E. Silva · C. Baranzelli · C. Jacobs-Crisioni · M. Kompil C. Perpiña Castillo · P. Vizcaino · R. Ribeiro Barranco · I. Vandecasteele · B. Kavalov J.-P.  Aurambout · A. Kucas · A. Siragusa · D. Auteri European Commission, Joint Research Centre (JRC), Ispra, Italy e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_10

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Keywords

LUISA, ARDECO, Urban Data Platform Plus · Territorial modelling · Urban Data Platform · Territorial indicators · Impact scenarios of regional development · Territorial Impact Assessment

10.1 Introduction The Joint Research Centre (JRC) of the European Commission (EC) has implemented the LUISA Territorial Modelling Platform for ex ante evaluation of European policies, measures and initiatives that might have a direct or indirect territorial impact. LUISA is based on the concept of ‘land function’ for cross-sector integration and for the representation of complex system dynamics. Beyond a traditional land use model, LUISA adopts a new approach towards activity-based modelling based upon the endogenous dynamic allocation of population, services and activities. The LUISA Platform consists of a set of connected modules. A regional module is employed to regionalise (downscale) exogenous socio-economic projections and produce scenarios of regional development according to defined options of growth. The module for the local distribution and allocation of Land Functions is based upon a novel dynamic interaction between population distribution and accessibility potential and a utility-based allocation of services. Feedbacks and spillover effects are included within and between the local and regional modules. LUISA outputs are represented in terms of ‘territorial indicators’ covering a wide range of themes, from economy to demography, from accessibility and transport to resource efficiency. This chapter provides a general overview of the LUISA modelling platform, while providing reference to its main applications for Territorial Impact Assessment (TIA) of policy initiatives in the EC. Emphasis is put on those concepts that are at the core of the integrated territorial approach (the inputs, dataflow and modelling chain) and on the instruments for data/output access and dissemination.

10.1.1 Background EC policies have substantial impacts on various domains. In order to uphold and improve the quality of legislation, a thorough ex ante impact assessment of EC policies should therefore evaluate policy proposals on all three domains of sustainability: economy, environment and society. However, straightforward impact assessment of EC policies is often not possible because various policy domains are inherently intertwined. For example, a trade policy can have a direct impact on the agricultural sector, and new transport infrastructures can influence economic growth, while both policies, together and individually, may affect land use. To make the impact assessment challenge even greater, various policies may either propagate or compensate impacts, thus causing non-linear interactions. Such complex dynamics can only be

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grasped by an elaborate impact assessment effort. In 2002, the EC introduced an Impact Assessment (IA) procedure to provide ‘evidence for political decision-­ makers on the advantages and disadvantages of possible policy options by assessing their potential impacts’.1 This procedure has to be applied to all Commission initiatives that aim to quantify economic, social and environmental impact. Analysing the situation with a territorial approach helps to break down and understand these complex interactions, so capturing both the specific characteristics of a spatial context and its relations with other contexts of the same geographical level (e.g. regions) or at higher aggregation levels (e.g. countries). In such a way, local policies that take into account and target the specificities of a territory can be designed, while keeping in mind the broader context. As support activities to the practices of policy definition and evaluation, ‘territorial approaches’ identify a large family of methods, more or less sophisticated, whose main strength is the ability to analyse a wide range of thematic areas across different spatial scales. These are the basic requirements for a tool to effectively support policies that aim at increasing the well-being of regions and cities. The EC has also published guidelines for TIA, which should be carried out when policies target specific territories, or when policies may produce uneven impacts throughout the territory. The LUISA Territorial Modelling Platform is a key element of the EC toolbox for TIA.2

10.1.2 LUISA in a Nutshell LUISA is a pan-European dynamic spatial modelling platform specifically designed to assess regional and local impacts of European policies and trends. The platform allocates (in space and time) the demand and supply of resources (biotic and abiotic, including primary energy resources), the settlement of socioeconomic activities (e.g. housing, industry, services, touristic accommodations) and infrastructures (e.g. for transport, energy). The allocation of population, economic activities and resources is driven by a combination of factors, including, amongst others, biophysical suitability, policy targets and regulatory constraints and economic criteria. The projected territorial patterns cover all EU member states and Western Balkan countries at a detailed geographical resolution (100 m), typically from the base year 2015 until 2050. LUISA is also applied for the whole African Continent. The LUISA modelling platform relies on inputs from several external models, thus being a truly integrative tool that coherently links specialised macroeconomic, demographic and geospatial models with thematic spatial databases. These features allow LUISA to incorporate complex interactions among human activities that are location specific and their determinants, translating socio-economic trends and policy scenarios into processes of territorial development. LUISA is typically  https://ec.europa.eu/info/law/law-making-process/planning-and-proposing-law/ impact-assessments_en 2  https://ec.europa.eu/info/files/better-regulation-toolbox-33_en 1

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configured to project a reference (or baseline) scenario (Jacobs-Crisioni et  al. 2017), assuming official socio-economic trends, business-as-usual preferences and the effect of established European policies with direct and/or indirect territorial impacts. The baseline scenario, called ‘Territorial Reference Scenario’, intrinsically takes into account several policy implications, including the Renewable Energy Directive, the Trans-European Transport Network (TEN-T) policy, the Nitrates Directive, the Common Agricultural Policy, the EU Biodiversity Strategy to 2020 and protection of Natura 2000 areas. Variations to the reference scenario may then be used to estimate impacts of specific policies, or of alternative macro-assumptions. The final output of LUISA is in the form of a set of spatially explicit indicators (territorial indicators) covering a wide range of themes, from economy to demography, from accessibility and transport to resource efficiency, and can be represented at various geographical levels (national, regional or at finer granularity). The territorial indicators are routinely updated and openly and freely distributed by online systems implemented in the frame of the EC Knowledge Centre for Territorial Policies.

10.2 Framework of the LUISA Territorial Modelling Platform The LUISA Territorial Modelling Platform is a system of sub-models designed to assess, ex ante, the territorial implications of policy decisions. LUISA is composed of multiple interconnected modules (Fig.  10.1: LUISA flow diagram) that enable it to: 1 . Downscale national and regional information at a finer spatial scale 2. Compile, harmonise and relate datasets from various sources 3. Simulate future Land Functions, population distribution and accessibility at a 100-m pixel resolution 4. Bring together information relative to future Land Functions and other sources to produce a range of over 50 indicators 5. Share model results to external users and provide them with a capacity to analyse results (Urban Data Platform Plus) The LUISA territorial modelling framework has the capacity to work across spatial scales with various levels of detail, and its outputs can be aggregated at any spatial level (from pixel to national scale). For policy support, LUISA’s strength lies in its ability to assess impacts of EU policies that play out because of local interactions between sectors and therefore cannot be observed with typically sector-­ oriented, spatially coarse impact assessment approaches. A good example of how the outcomes of EU policies may be affected by cross-sectoral local changes can be found in Jacobs-Crisioni et al. (2016). An abstract representation of LUISA is given in Fig. 10.2 (LUISA processing scheme), in which for every relevant scale the input factors, policies and constraints

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Fig. 10.1  LUISA flow diagram (@EC/JRC)

0 Mixed scale Relevant selected data -> I National or regional Previous state -> Exogenous regional factors -> Endogenous local factors -> Potential policy impacts -> II Local (100m)

↕

Previous state -> Local factors (endog. + exog.) -> Potential policy impacts -> ↓

III Mixed scale Local and regional results -> Exogenous factors -> ↓ IV Mixed scale

Data preparation Process to generate spatial data to feed model calibration and/or model runs Endogenous scenarios and transformation of exogenous projections Some projections already at right scale as relevant resource claims (e.g. population, agricultural land demand) ↕ ↓ Local redistribution of Land Functions

Regionalisation of projections Transformation to resource claims

Pressures -> physical change -> function distribution change (Land Functions, residential population, accessibility) ↓ Indicators Production of territorial indicators ↓ Web platforms for distribution of indicators

Fig. 10.2  LUISA processing scheme (@EC/JRC)

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are given, and on the right-hand side, the respective outputs are presented. We must emphasize that this is the configuration as used in the Territorial Reference Scenario 2017; additional feedbacks between the regional and local blocks are foreseen for scenarios, for example, population spillovers between regions. The modelling chain direction is given by means of uni- or bidirectional arrows. Unidirectional arrows indicate inputs fully exogenous to a modelling block; bidirectional arrows indicate dynamic model responses. Types of inputs into each block are given on the left. The data preparation block is not given any formal position in the modelling chain but must be seen as a crucial part of the modelling process that affects essentially all steps in the modelling chain. The relevant geographical scale is given in the top left of each modelling block. LUISA is fed partially by exogenous and partially by endogenous factors. Mostly the larger-scale models feed the local allocation module unidirectionally, but currently in one submodel (which computes urban land-use claims based on population projections), the local module feeds back to the regional module. All the submodels in LUISA in sections I and II are essentially set up to disaggregate formal projections. They do so by using functions fitted on observed changes and on well-founded economic assumptions. Nevertheless, it is important to stress that the outcome of LUISA models in the reference configuration is always zero-sum with regard to input projections.

10.2.1 Reference Data for Territorial Modelling and Analysis The LUISA framework pays considerable effort to apply best available data on all the relevant factors within the modelling chain. Key activities to enhance data quality and integrate technical improvements in LUISA can be summarized as follows: • LUISA base map (Batista e Silva et al. 2013a; Rosina et al. 2018): a 100-m grid map derived from the latest CORINE land use, Urban Atlas and other auxiliary sources. The combination of datasets improves the mapping detail; in particular, urban and industrial land uses are mapped at a much higher thematic and spatial definition. It is used as the reference base map in the local allocation submodel and for the estimation of suitability functions. • LUISA reference population map (Batista e Silva et al. 2013b): a 100-m grid map derived from the LUISA base map, the EUROSTAT 1-km census map 2011 (latest updated version: 2018) and auxiliary sources. This map is used as the reference population distribution map in the model. • Economic regional statistics: regional economic statistics long time-series, the Annual Regional Database of the European Commission  (ARDECO), maintained and distributed by JRC in the frame of the Knowledge Centre for Territorial Policies. Used in the calibration of the LUISA module that regionalises countrylevel economic projections.

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• Accessibility historical time series 1961–2011: 1-km grid maps derived from historical road networks and municipal population counts. Used to fit functions of historical local population and land-use change. • Agricultural abandonment risk (Perpiña Castillo et al. 2018): a 100-m grid map that combines driving factors (biophysical, economic and demographic) for farmland abandonment into one composite risk map of agricultural land abandonment. It is used in the local land allocation procedures. • Factors used to define local suitability for land functions. These factors have been established empirically through econometric methods or derived from the GIS databases: Geomorphology (elevation, slope, south-facing slope, distance to the nearest freshwater body) Designated area for landscape protection (Natura 2000, National Areas) Yield maps for agricultural crops Travel time to nearest town Relative potential accessibility Distance to nearest main road Touristic attractions in the vicinity Restaurants in the vicinity Tourist lodging in the vicinity Population count Municipality fixed effects governing the local attractiveness of a location for residents and investors Attractiveness for bioenergy crops Likeliness of urban/industrial/agricultural abandonment Others, as required by specific applications

• Suitability for dedicated energy crops (Perpiña Castillo et al. 2015): a100-m grid map that describes the relative suitability of a location for growing energy crops. These maps are used in the local allocation procedures. • Infrastructure and emerging new geospatial data (Batista et al. 2019): collection and use of information of infrastructure and ‘geospatial big data’ for territorial analysis at the finest spatial resolution (point). These are used to ‘urban proof’ policies and measures at neighbourhood scale.

10.2.2 Linkages with Exogenous Models and Data The LUISA framework uses the following exogenous projections in the current configuration of the Territorial Reference Scenario 2017 that are predominantly provided by models used by the EC in the policy cycle: • Population: EUROPOP population projections by EUROSTAT adopted in the EC Ageing Report (EC 2015, 2017) • Economy: National economic projections (gross domestic product (GDP) and gross value added (GVA)), consistent with the EC Ageing Report (EC 2015, 2017)

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• Agriculture: regional projections of changes in agricultural land demand, including energy crops, derived from the CAPRI model (Britz and Witzke 2008) • Forestry: levels of afforestation or deforestation rates reported under the scheme of the United Nations Framework Convention on Climate Change (UNFCCC) (Baranzelli et al. 2014) • Tourism: expectations of tourism growth published by the United Nations World Tourism Organization (UNWTO) (Baranzelli et al. 2014)

10.2.3 Regionalisation and Local Allocation of Services and Activities Regional (NUTS 2, 3) demographic and economic projections are one output of the LUISA modelling framework. To obtain those, national economic projections are regionalised (Batista et al. 2016). The term ‘regionalisation’ refers to the process of obtaining regional figures of demography and economy from reference projections available at national level. In LUISA, the target spatial units are NUTS 3 regions (see Fig.  10.3). The regionalisation is technically achieved by ‘disaggregating’ a given total figure per country amongst the NUTS 3 regions which compose it. This process is also commonly referred to as ‘downscaling’. This is done using a downscaling mechanism in which past values, determinants and spatial effects play a role. The submodel governing the downscaling mechanism can be used to evaluate the redistributive economic effects of policy packages and is used to provide NUTS 3 level GDP and GVA projections to the local allocation module, where they are used to compute future industrial land demand.

Fig. 10.3  Regionalisation scheme (@EC/JRC)

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A dedicated version of the regionalisation module allows defining and computing regional scenarios of growth, leveraging on a set of factors, such as agglomerations and levels of educational attainment. The allocation module in LUISA is tasked with the local redistribution of Land Functions. This module produces, for each 100-m grid cell in each member state for each modelled time step, three maps describing discrete land uses, residential population and potential accessibility levels (Jacobs-Crisioni et  al. 2017). Many Land Functions are subsequently derived from those outputs. The redistribution of population and land use is driven by expected regional demand for specific uses as well as by ongoing inert spatial reorganisation processes driven by existing discrepancies between suitability and function patterns.

10.2.4 Territorial Indicators The LUISA modelling platform can produce over 50 indicators, encompassing many thematic domains, including demography, economy, education, energy, accessibility, environment and housing. Output indicators can be divided into a number of technical classes: (a) stand-­ alone indicators, (b) indicators that combine LUISA outputs with other bottom-up data and (c) indicators that use LUISA outputs to disaggregate coarser regional projections. In all cases, when additional data sources are used, those data are required to be based on assumptions consistent with the LUISA scenarios. • Stand-alone indicators are, for example, indicators on land consumption, degree of urbanisation or change in agricultural area. • Indicators that are computed with other bottom-up data are, for example, the network efficiency indicator (combination with TRANS-TOOLS road network), the service accessibility and the average travel distances. • Indicators that are created by disaggregating aggregate statistics using LUISA outputs concern, for example, local air quality and energy consumption. The indicators are published in UDPplus and available for past and future time series, according to their source (statistical and/or modelled).

10.3 Dissemination, Data Exchange and Interoperability The Urban Data Platform Plus (UDPplus: https://urban.jrc.ec.europa.eu) represents a concrete response to the demand for better knowledge on cities and regions for the EU.  As a key component of the joint JRC-DG REGIO ‘Knowledge Centre for Territorial Policies’ (KCTP), launched in October 2016, UDPplus aims at being the primary reference for statistical, modelled and experimental indicators at urban and regional levels in Europe and beyond.

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Fig. 10.4  The core architecture of UDPplus (@EC/JRC)

UDPplus is today the main tool for the dissemination of territorial knowledge collected and produced under the umbrella of the KCTP. In compliance with the European Interoperability Framework, it aims at becoming the reference tool for urban and regional data dissemination, visualisation and analysis in Europe.

10.3.1 UDPplus: Infrastructure and Components UDPplus infrastructure is composed of a set of data and services able to share these data. The aim of this infrastructure is to share quantitative knowledge with any interested stakeholder, following reference standards in terms of metadata, data and services (see Auteri et  al. 2019). Figure  10.4 represents the core architecture of UDPplus: Each component has a specific function: EXTERNAL WEB SERVICE: integrates in UDPplus data and services provided by external entities (like EUROSTAT, OECD, regional and local authorities, etc.) CONTAINER DB: collects all resources (data sets and documents) DB MANAGER: web tool for the management of collected data sets and documents available in CONTAINER DB TOOLS: currently, the following tools are available in UDPplus (Fig. 10.5): • T_PEDIA: metadata catalogue of data sets, documents and services. • MY PLACE: a sort of ‘Identity Card’ for each territorial area, from country to cities, including any intermediate level (region, sub-region, functional urban area, metropolitan area). • TRENDS: a contextual map showing indicator trends at any territorial level. • ANALYSES: a collection of thematic analyses starting from data collected in UDPplus. • STRATEGIES: dashboard to browse the Sustainable Urban Development (SUD) and Integrated Territorial Investment (ITI) strategies.

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Fig. 10.5  The UDPplus (Source: https://urban.jrc.ec.europa.eu)

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• NUTS CONVERTER: web-based tool allowing the conversion of European regional statistical data between different versions of the Nomenclature of Territorial Units for Statistics (NUTS) classification. • SHARED COMPONENTS: a set of services consumed by the various tools. This includes APIs for data management and data processing, graphical components, interface components and data filtering components. All tools are built as a combination of these base components.

10.4 Applications in Territorial Impact Assessment Since 2011, LUISA has provided knowledge-based contributions to several EC policies (in either a formal or informal initiatives for impact-assessment procedures). Table  10.1 illustrates examples of policy applications of the LUISA Territorial Modelling Platform, together with some selected relevant publications.

Table 10.1  Policy applications of the LUISA Territorial Modelling Platform Topics Integrated coastal zone management Common agricultural policy

Energy

Relevant selected LUISA publications Lavalle C, et al. 2011. Coastal Zones – Policy alternatives impacts on European Coastal Zones 2000–2050. EUR 24792 Lavalle C, et al. 2011. Implementation of the CAP Policy Options with the Land Use Modelling Platform – A first indicator-based analysis EUR 24909 Baranzelli C, et al. 2014. Land allocation and suitability analysis for the production of food, feed and energy crops in the period 2010–2050 EU Reference Scenario 2013 EUR 27018 Perpiña Castillo C, et al. 2018. Territorial Facts and Trends in EU Rural Areas within 2015–2030, EUR 29482 Lavalle C, et al. 2013. Spatially-resolved Assessment of Land and Water Use Scenarios for Shale Gas Development: Poland and Germany. EUR 26085. Baranzelli C, et al. 2015. Scenarios for shale gas development and their related land use impacts in the Baltic Basin, Northern Poland. ENERGY POLICY 84; p. 80–95. Baranzelli C, et al. 2015. Regional patterns of energy production and consumption factors in Europe. EUR 27697. Baranzelli C, et al. 2016. European Regional Energy Balance and Innovation Landscape (EREBILAND) – Energy demand of buildings. Deliverable 4: Case studies of optimisation. JRC104326 Perpiña Castillo C, et al. 2016. An assessment of dedicated energy crops in Europe under the EU Energy Reference Scenario 2013. EUR 27644 Vandecasteele I, et al. 2016. An analysis of water consumption in Europe’s energy production sector: The potential impact of the EU Energy Reference Scenario 2013 (LUISA configuration 2014). EUR 28048 Perpiña Castillo C, et al. 2016. An assessment of the regional potential for solar power generation in EU-28. ENERGY POLICY 88 (continued)

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Table 10.1 (continued) Topics Environment and climate

Urban and regional policy

Relevant selected LUISA publications De Roo A, et al. 2012. A multi-criteria optimisation of scenarios for the protection of water resources in Europe: Support to the EU Blueprint to Safeguard Europe’s Waters. EUR 25552 Ciscar Martinez J, et al. 2014. Climate impacts in Europe. The JRC PESETA II Project. EUR 26586 Lopes Barbosa A, et al. 2015. Evaluation of the status of natural resources in the updated Reference Configuration 2014 of the LUISA modelling platform. Methodological framework and preliminary considerations. EUR 26938; Barbosa et al. (2016) De Roo A, et al. 2016. Modelling water demand and availability scenarios for current and future land use and climate in the Sava River Basin. EUR 27701 Vandecasteele I, et al. 2018. The Water Retention Index: Using land use planning to manage water resources in Europe, SUSTAINABLE DEVELOPMENT, p. 122–131 Vizcaino M, Lavalle C 2018. Development of European NO2 land use regression model for present and future exposure assessment: implications for policy analysis. Environ Pollut, ISSN 0269-7491, 240:140–154, JRC111760 Batista E Silva F, et al. 2013. Direct and indirect land use impacts of the EU Cohesion Policy. Assessment with the Land Use Modelling Platform. EUR 26460 Ribeiro Barranco R, et al. 2014. Indicators and trends for EU urban areas Data and methods in the LUISA platform in support to EU Urban and Regional Policy. EUR 27006 Kompil M, et al. 2015. European cities: territorial analysis of characteristics and trends – An application of the LUISA Modelling Platform (EU Reference Scenario 2013 – Updated Configuration 2014). EUR 27709 Jacobs C, et al. 2016. Accessibility and territorial cohesion in a case of transport infrastructure improvements with changing population distributions. EUROPEAN TRANSPORT RESEARCH REVIEW 8 (1); 2016. p. 9. JRC91771 Lavalle C, et al. 2017. European Territorial Trends – Facts and Prospects for Cities and Regions Ed. 2017, EUR 28771 Kompil M, et al. 2019. Mapping access to generic services in Europe: a market-potential based approach, SUSTAINABLE CITIES AND SOCIETY, ISSN 2210-6707

Further examples are given in Lavalle et al. (2016, 2017b). Analyses and outputs from LUISA are routinely used to report on the status of Socio-economic and Territorial Cohesion of the European Union (Sixth and Seventh Cohesion Reports in 2014 and 2017) and in the frame of the Urban Agenda for the EU (The Future of Cities, 2019 and State of European Cities, 2016).

10.4.1 Recent Applications In addition to those listed in the table, the extensive Territorial Knowledge Base is currently supporting EC initiatives such as the Urban Agenda for the EU, Cohesion Policy and cross-border regions, rural development and others.

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10.4.1.1 The Future of Cities The report ‘The future of cities – opportunities, challenges and the way forward’ highlights the main challenges faced by cities and the people living within them currently and towards the future. The report was developed in an inclusive manner – close collaboration with the EC’s Community of Practice on Cities (CoP-CITIES) provided insights from the broader research community and city networks, including individual municipalities, as well as Commission services and international organisations. The report is supported by an online ‘living’ platform which hosts updates, including additional analyses, discussions, case studies, comments and interactive maps. Steered by the JRC in the frame of the Knowledge Centre for Territorial Policies, the platform offers a permanent virtual space to the research, practice and policy-making community for sharing and accumulating knowledge on the future of cities. As matter of example, the evaluation of aging trends in urban areas has benefitted from demographic projections produced by LUISA.  Figure  10.6 (age class ratio in France (2015 and 2040)) illustrates changes in the proportion of older people (aged 65 years or older) in Functional Urban Areas between 2015 and 2040 in France. Overall, the share of older people is increasing in every city. The ratio of older to younger population remains lower in cities such as Paris, Lyon and Toulouse, presumably because they are still increasing their total population, thanks to the offer of better employment and education opportunities for the younger, working population. However, the share increases significantly in cities along the Mediterranean coast (Marseilles, Montpelier and Avignon) as well as in north-eastern France.

Fig. 10.6  Age class ratio in France in 2015 (left) and 2040 (right) (Source: Vandecasteele et al. 2019)

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10.4.1.2 Towards a New Geography of Cross-Border Regions This application aims to add technical insights to the debate about overcoming the cross-border obstacles to growth and jobs in the EU internal border regions. Based upon a novel definition of drive time-based cross-border regions, the methodology allows looking at statistical trends for 31 EU couples of Member States and three complex border regions, where more than two EU countries are included. Traditional limitations in data collection and analysis stemming from administrative borders (typically NUTS 3) can be overcome, and comparative analysis can be performed at EU-wide scale (Kavalov et al. 2019) (Fig. 10.7). 10.4.1.3 Agricultural Land Abandonment LUISA has been employed to analyse agricultural land abandonment trends in the EU, for the period 2015–2030 (Perpina et al. 2018). The evaluation includes non-­ market (e.g. biophysical, agro-economic, demographic and geographic) and market factors. The bulk of abandoned agricultural land (4.8 million ha gross) is likely to remain unused within 2015–2030 because of negligible re-cultivation of once-­ abandoned land. Less than 600,000 ha are projected to convert into forests and natural areas, while the conversion into build-up area will be minimal – just 18,000 ha (Fig. 10.8).

Fig. 10.7  Examples of border regions defined according to drive-time distance (Source: Kavalov et al. 2019)

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Fig. 10.8  Estimated potential risk of agricultural land abandonment in 2030 (left), predicted shares of land abandonment in 2030 (Source: Perpina et al. 2018)

10.5 Conclusions The LUISA Territorial Modelling Platform offers the possibility to define scenarios based on policy options, collect and analyse data at the appropriate level of thematic and spatial granularity, and exchange and discuss with relevant stakeholders alternatives and possible future prospects, based upon a combination of advanced analytical tools and dissemination platforms. Given its highly flexible and customisable structure, LUISA has the ability to integrate under a unique modelling framework the territorial capital factors that influence the spatial patterns of socio-economic activities and population distribution at different scales. LUISA is therefore a well-suited tool for impact assessment of a wide range of policies with a territorial dimension, including their potential synergies, conflicts and trade-offs. The KCTP aims at becoming a bridge between science and policy-making, providing access to data and analyses of complex territorial dynamics, hence helping local and regional authorities to build better regulations for wealthier cities and regions. UDPplus, as a cornerstone of the KCTP, is intended to become the ‘de facto’ standard repository for quantitative knowledge and indicators at all territorial levels in Europe. All these components, together, will not only provide an invaluable source of information for policymakers and data analysts but will also represent an excellent example of a Europe closer to its citizens.

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References Auteri D, Attardo C, Bussolari I, Lavalle C (2019) Urban Data Platform plus – progress report, European Commission, JRC117350 Baranzelli C, Lavalle C, Jacobs-Crisioni C, Batista e Silva F, Perpiña Castillo C, Barbosa A, Arevalo Torres J (2014) The Reference Scenario in the LUISA platform – updated configuration 2014. JRC report EUR 27019 Baranzelli C, Lavalle C, Sgobbi A, et al (2015) Regional patterns of energy production and consumption factors in Europe: exploratory project EREBILAND – European Regional Energy Balance and Innovation Landscape. EUR 27697. Luxembourg Barbosa A, Vallecillo S, Baranzelli C, et al (2016) Modelling built-up land take in Europe to 2020: an assessment of the resource efficiency roadmap measure on land. J Environ Plan Manag: 1–25. https://doi.org/10.1080/09640568.2016.1221801, 60 Batista e Silva F, Lavalle C, Koomen E (2013a) A procedure to obtain a refined European land use/ cover map. J Land Use Sci 8(3):255–283 Batista e Silva F, Gallego J, Lavalle C (2013b) A high-resolution population grid map for Europe. J Maps 9:16–28 Batista e Silva F, Dijkstra L, Vizcaino Martinez P, Lavalle C (2016) Regionalisation of demographic and economic projections – Trend and convergence scenarios from 2015 to 2060, JRC Science for policy report. EUR 27924 EN; https://doi.org/10.2788/458769 Batista E, Silva F, Forzieri G, Marín Herrera M, Bianchi A, Lavalle C, Feyen L (2019) HARCI-EU, a harmonized gridded dataset of critical infrastructures in Europe for large-scale risk assessments, SCIENTIFIC DATA, ISSN 2052-4463 (online), 6 (126), 2019, JRC116012 Britz W, Witzke HP (2008) Capri model documentation 2008: version 2. Institute for food and resource Economicws. University of Bonn, Bonn EC (2015) The 2015 ageing report — economic and budgetary projections for the 28 EU Member States (2013–2060). Publications Office of the European Union, Luxembourg EC (2017) The 2018 ageing report  – underlying assumptions & projection methodologies, Publications Office of the European Union, Luxembourg, https://doi.org/10.2765/286359 (online) Jacobs-Crisioni C, Batista e Silva F, Lavalle C et al (2016) Accessibility and territorial cohesion in a case of transport infrastructure improvements with changing population distributions. Eur Transp Res Rev 8(9):1–16. https://doi.org/10.1007/s12544-016-0197-5 Jacobs-Crisioni C, Diogo V, Perpiña Castillo C, Baranzelli C, Batista e Silva F, Rosina K, Kavalov B, Lavalle C (2017) The LUISA territorial reference scenario 2017: a technical description. JRC report EUR 108163 Kavalov B, Kučas A, Batista e Silva F, Kompil M, Aurambout J-P, Lavalle C (2019) A Drive Time-­ Based Definition of Cross-Border Regions and Analysis of Population Trends, EUR 29859 EN, Publications Office of the European Union, Luxembourg, ISBN 978-92-76-11300-3, https:// doi.org/10.2760/86464, JRC116859 Kompil M, Aurambout J-P, Ribeiro Barranco R, et al (2015) European cities : territorial analysis of characteristics and trends – an application of the LUISA Modelling Platform (EU Reference Scenario 2013 – updated Configuration 2014). EUR 27709. Luxembourg Kompil M, Jacobs C, Dijkstra L, Lavalle C (2019) Mapping accessibility to generic services in Europe: a market-potential based approach. Sustainable Cities Soc, ISSN 2210-6707 (online), 47, p 101372, JRC112478 Lavalle C, Batista E, Silva F, Baranzelli C, Jacobs C, Vandecasteele I, Lopes Barbosa A, Maes J, Zulian G, Perpiña Castillo C, Ribeiro Barranco R, Vallecillo Rodriguez S (2016) Chapter 24 land use and scenario modeling for integrated sustainability assessment. European landscape dynamics: CORINE land cover data; CRC Press; p 237–262. JRC99277 Lavalle C et al (eds) (2017a) European territorial trends – facts and prospects for cities and regions Ed. 2017, EUR 28771 EN. Publications Office of the European Union, Luxembourg Lavalle C, Batista e Silva F, Baranzelli C et al (2017b) Modelling and projecting urban land cover. In: Gardi C (ed) Urban expansion, land cover and soil ecosystem services. Routledge, Oxon, pp 59–48

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Perpiña Castillo C, Lavalle C, Baranzelli C et al (2015) Assessing the environmental impacts of 2nd generation (lignocellulosic) feedstock under the energy-climate reference scenario using LUISA modelling platform in EU-28. In: WIT transactions on ecology and the environment. WIT Press, Chilworth, pp 367–378 Perpiña Castillo C, Kavalov B, Ribeiro Barranco R, Diogo V, Jacobs C, Batista E, Silva F, Baranzelli C, Lavalle C (2018) Territorial facts and trends in EU rural areas within 2015–2030, Publications Office of the European Union, Luxembourg, 2018, JRC114016 Rosina K, Batista E, Silva F, Vizcaino M, Marín Herrera M, Freire S, Schiavina M (2018) Increasing the detail of European land use/cover data by combining heterogeneous data sets, Int J Digital Earth, ISSN 1753-8947, JRC112016 Vandecasteele I, Baranzelli C, Siragusa A, Aurambout J, et al (eds). (2019) The future of cities, EUR 29752 EN. Publications Office of the European Union, Luxembourg, JRC116711 Vizcaino M, Lavalle C (2018) Development of European NO2 land use regression model for present and future exposure assessment: implications for policy analysis. Environ Pollut, ISSN 0269-7491, 240:140–154, JRC111760 Carlo Lavalle  has over 25 years of experience in modelling and data analysis for policy applications. Since 1990, he is with the Joint Research Centre (JRC) of the European Commission (EC). During his career in the JRC, Carlo has participated in several policies-related Working Groups of the European Union and in the evaluation of impacts of European policies in fields related to energy, agriculture, resource efficiency and territorial cohesion. He is involved in scientific policy support in the field of urban and regional development and coordinates the JRC Team in charge for the development of the LUISA Territorial Modelling Platform and of the EC Knowledge Centre for Territorial Policies.

Territorial Effects of EU Cohesion Policy Supporting Entrepreneurship: Findings from the Czech Republic

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Ondřej Dvouletý, Ivana Blažková, and Oto Potluka

Abstract

European cohesion policy aims to mitigate regional disparities and foster regions that are economically lagging behind. One way to encourage economic activities in such under-developed regions is through supporting entrepreneurship. The study explores the territorial effects of public subsidies aimed at promoting the competitiveness of Czech enterprises. The analysis evaluates the impact of the largest Czech entrepreneurship policy – Operational Programme Enterprise and Innovation (OPEI) and its regional firm-level effects. Funded by the European Regional and Development Fund, part of EU cohesion policy, it ran from 2007 to 2013. The research exploits a microeconomic dataset of 3614 supported and 6622 non-supported companies, and empirically assesses whether the outcomes of the policy differed territorially across the Czech NUTS 3 regions 2 years after the end of the intervention. The method used is the counterfactual impact evaluation. For that purpose, we operationalise firm-level competitiveness by financial performance indicators. The findings show that the effects of EU cohesion policy differed across the Czech NUTS 3 regions. The confirmed cross-regional effects of public interventions have implications for the future adjustments of cohesion policy. Accordingly, we argue that adapting calls to the specificities of the different locations (NUTS 3 regions) would enhance the response to the local needs O. Dvouletý Department of Entrepreneurship, University of Economics, Prague, Prague, Czech Republic e-mail: [email protected] I. Blažková Department of Regional and Business Economics, Mendel University in Brno, Brno, Czech Republic e-mail: [email protected] O. Potluka (*) Department of Management, University of Economics, Prague, Prague, Czech Republic e-mail: [email protected] © Springer Nature Switzerland AG 2020 E. Medeiros (ed.), Territorial Impact Assessment, Advances in Spatial Science, https://doi.org/10.1007/978-3-030-54502-4_11

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and challenges faced by local authorities and improve the place-based character of EU cohesion policy. Keywords

Territorial effects · Public grants · Entrepreneurship policy · EU cohesion policy · Counterfactual impact evaluation

11.1 Introduction EU cohesion policy forms one-third of the EU budget (European Commission 2019a, b1). Such a significant financial allocation demonstrates its political importance in negotiations among EU member states and among interest groups. Thus, this policy became a theme of fierce debates at political, academic and experts levels. Because of its importance, it has always been a subject of evaluations. Moreover, some authors claim that it has been an evaluation leading policy (Ferry 2009) applying more sophisticated evaluation approaches than national policies (Fratesi and Wishlade 2017). During the last decade, the European Commission, i.e. the Directorate-General (DG) Regio, DG Employment and evaluation community began the application of rigorous evaluation methods to assess the actual impacts of this policy (Mouqué 2012). Despite this privileged position of EU cohesion policy, the conducted evaluations are inconclusive on the actual outcomes of the policy (Berkowitz et al. 2019). Thus, they do not provide clear information on whether the outcomes are positive or negative, and therefore, the implications for policymakers are not that straightforward, as they would probably desire it to be. EU cohesion policy, also called European regional policy, mainly aims to mitigate the regional disparities among European regions, and thus the authors believe that it is very important to consider in empirical evaluations also the spatial (regional) dimension. As this was not often done in the previously published evaluations and studies, the authors believe that these studies should become more frequent. Therefore, the chapter provides empirical evidence on the effects of investment subsidies allocated to enterprises by taking into account a regional perspective. Considering local perspective is essential, because the regional economic development is significantly influenced by the companies (and their financial performance) that conduct business activity in the regions, as demonstrated by numerous empirical studies (e.g. Baptista et  al. 2008; Fritsch and Mueller 2008; Dvouletý 2017; Huggins et al. 2018).

1  According to the European Commission (2019a; 2019b) the budget allocated to regional policy constituted to 35.7% of the total budget, i.e. 347 bn EUR for the period 2007–2013 and 351 bn EUR for the period 2014–2020.

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The study aims to quantify the regional effects of public grants allocated to the enterprises within cohesion policy in the Czech Republic. The analysis explores the territorial effects of public subsidies aimed at promoting the competitiveness of Czech enterprises. The research evaluates the impact of the largest Czech entrepreneurship and SME policy  – Operational Programme Enterprise and Innovation (OPEI), which lasted during the years 2007–2013. The European Regional and Development Fund, part of EU cohesion policy, funded the programme. On the sample of 3614 supported and 6622 non-supported companies, the analysis empirically assessed whether the outcomes of the policy differed territorially across the Czech NUTS 3 regions 2 years after the end of the intervention. Methodologically, the authors follow the counterfactual impact analysis. The chapter is organised as follows. After the Introduction, in Sect. 11.2, the regional aspects of EU cohesion policy are discussed with an emphasis on previously published studies. Section 11.3 introduces the methodological approach and the data used. In Sect. 11.4, the obtained results are interpreted, and the final part of the chapter concludes.

11.2 Regional Impacts of EU Cohesion Policy Evaluations might provide arguments whether EU cohesion policy should be oriented towards regions lagging behind, i.e. towards mitigation of regional disparities, or whether the policy should support more competitive regions, by following the argument of “picking up the winners”. This political discussion takes place mainly between the group of the EU member states before 2004, and EU member states accessing the EU after this year. Both sides brought scientific arguments on whether to aim at competitiveness or cohesion. However, as there are arguments for and against both alternatives and ambiguous results of the existing evaluation studies, this debate is so far inconclusive. Arguments for supporting more competitive regions include mainly better attraction of labour force and innovations, while for the support of lagging regions are empirical results indicating immediate and short-­ term effects on their growth (Pinho et al. 2015a, b). Theories, explaining the regional economic growth originate in macroeconomic models of economic growth (Barro 1990; Barro and Sala-i-Martin 1992; Bouayad-­ Agha et al. 2013; Pinho et al. 2015b; Kolaříková et al. 2018) with the aim to provide a straightforward answer for policymakers, whether the EU cohesion policy pays off or not. Such an approach is understandable, as policymakers were interested in knowledge about effective implementation of the policy at the EU level, but the approach “one-size-fits-all” has turned out not to be correct. It was unable to capture policy effects at lower geographical levels (Tödtling and Trippl 2005; McCann and Ortega-Argilés 2015; Pělucha and Květoň 2017; Pělucha et al. 2017; Fratesi and Wishlade 2017). The current trend reflects more the regional heterogeneity in the policy evaluation, local conditions and industry specialisation (Bourdin 2018). Nevertheless, the existing empirical evidence is still quite ambiguous, as demonstrated in a recent meta-evaluation by Berkowitz et al. (2019).

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Considering these regional dimensions, a challenge still remains for the forthcoming evaluations, that aim to capture full variability of regional effects in so-­ called place-based evaluations (e.g. Barca et al. 2012; Braga et al. 2011; Kline 2010; Bachtler 2010; Mendez 2013). The motivation is to provide information on the impact at the regional level taking into account the variability of European regions and areas, as well as shared and decentralised management of EU cohesion policy (Berkowitz et al. 2019; Bourdin 2018; Fratesi and Wishlade 2017). According to the place-based approach (Barca 2009), it is possible to identify the needs of local communities and other dimensions of policy. It means that, in the evaluation studies, the research goes beyond the overall policy effects, and we try to find (1) what factors influence the policy successes and failure; (2) what are the effects at lower geographical levels; (3) what are the sectoral effects of policy; (4) what are the effects across policy form/type. The current debate on the impacts of EU cohesion policy considers the following dimensions/relationships that have been identified by the scholars and suggested for further exploration: • National policy compliance and synergy of goals with EU cohesion policy (Freyburg and Richter 2010) • Institutional capacity to absorb the funding, i.e. concerning corruption, the rule of law, government effectiveness and accountability (Bourdin 2018; Pinho et al. 2015a) • Regional characteristics, e.g. infrastructure, the structure of the economic activity, demographic characteristics of the population (Pinho et al. 2015b; Crescenzi and Giua 2018) • The concentration of funds on specific themes, i.e. more intense funding brings higher effects, but larger investments do not necessarily imply higher economic effects (Crescenzi and Giua 2018; Pinho et al. 2015a) • The ability of regional ecosystem/environment to absorb innovations and to foster spatial spillovers (Berkowitz et al. 2019; Crescenzi and Giua 2018) Another approach to the evaluation of EU cohesion policy that is being highlighted nowadays is the Territorial Impact Assessment (TIA) approach, which represents an attempt to cover the complexity of territorial impacts. It compares the factors influencing possible effects on regions using not only quantitative but also qualitative data (Medeiros 2014, 2016, 2017). The advantage of this approach lies in its complexity in terms of including cultural, social, institutional, legal, economic, technological, environmental, transportation and historical aspects of regional development. On the other hand, the disadvantage is that TIA concerns the application of a less rigorous approach, such as the classification of variables based on experts’ judgments. Even though the TIA method applies approaches similar to counterfactual analysis, due to its basement on subjective data, it is not possible to call it a counterfactual impact analysis. Methodological limitations of TIA have been reflected in increased attention towards the results of quantitative evaluation methods. The European Commission

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(2009) and Mouqué (2012), in their recommendations towards conducting evaluations, suggest using counterfactual methods, such as regression discontinuity design, propensity score matching and instrumental variables approach. Comparison of supported and non-supported individuals/units/regions and periods before and after the intervention, known as a difference in differences (DID), is becoming more popular. Nevertheless, other valuable methods might be used for evaluation, such as structural equation modelling or synthetic control method (Khandker et al. 2010). Nevertheless, rigorous evaluation approaches cannot be used to evaluate all policy initiatives. Berkowitz et  al. (2019) have examined the database of the DG for Regional and Urban Policy, and they report that counterfactual impact evaluations consist only 48 out of 292 assessments. It is also important to stress the need to study especially the long-term effects of cohesion policies, although the existing evaluations report mostly short-term effects. This might be explained by the lack of data or by the political interest in rather short-term and immediate impacts of cohesion policy. Moving from one programming period to another, sometimes it is also very difficult to transfer the obtained evaluation lesson into the new programmes (Dąbrowski 2014; Pinho et al. 2015b; Becker et al. 2018). From the economic point of view, cohesion policy needs to stay sustainable, so it is necessary to make sure that some individuals, companies and even regions would not become entirely either intentionally or unintentionally dependent on funding from the European Union. Moreover, the political instability and changes in the member states may always reshape the overall allocations of financial resources to cohesion policy (Kovách and Kučerová 2006, 2009; Di Cataldo 2017).

11.3 Methodological Approach and Data 11.3.1 Methodological Approach The goal is to quantify the regional effects of EU Cohesion policy, funded by the European Regional and Development Fund that was allocated in the Czech Republic within the Operational Programme Enterprise and Innovation (OPEI). The OPEI lasted during the 2007–2013 programming phase (European Commission 2016). The evaluation is based on an assessment of microeconomic (firm-level) effects of the OPEI concerning the region, where the firms realised their projects funded from the public funds. There are 14 NUTS 3 regions in the Czech Republic. However, the capital Prague was excluded from the funding of the OPEI, and thus, the research will provide empirical results for the 13 remaining NUTS 3 regions. Our main goal is to quantify the regional firm-level effects of public grants allocated within the OPEI. Methodologically, the analysis follows previous researchers (e.g. Čadil et  al. 2017; Brachert et al. 2018; Dvouletý and Blažková 2019a, b; Srhoj et al. 2019) and conducts a counterfactual impact evaluation. Propensity score matching is combined with the difference in differences (DID) approach, as it is also common in the

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evaluation literature (Khandker et al. 2010). The OPEI intervention took place during years 2007–2013 and thus, considers the 2  years before the programme (2005–2006) as a pre-treatment period and 2 years after the programme (2014–2015) as a post-intervention period. The effects of the programme are calculated as a difference between these two periods mentioned above (i.e. as a difference in differences). Our evaluation thus provides information on the short-term impact of this programme. As the main objective of the programme was to increase the competitiveness of the Czech enterprises, the study presents its effect on the overall financial firm-level performance, represented by the growth of assets, growth of tangible assets, sales growth and return on assets (ROA) growth.

11.3.2 Data Our data was obtained from two main sources. First, data provided by the Ministry of Industry and Trade of the Czech Republic (2013) and CzechInvest Agency (CzechInvest 2018) was used, which contained information on all applicants’ projects, i.e. in which support programme the subsidy was requested, the size of the subsidy, a region of project implementation and whether the project was supported or not. Then, a commercial database MagnusWeb (Bisnode 2018) was used to obtain Balance Sheets and Profit and Loss Statements of the Czech firms, because most of the Czech companies do not report their financial records to the official public databases of the Czech Ministry of Justice. Previous researchers (e.g. Dvouletý et al. 2019, Potluka and Brůha 2013) already pointed out the issue of lack of data. According to the official records, 10,612 enterprises applied for a subsidy from the OPEI and 6269 companies were supported. The authors have managed to collect data for 3614 supported companies (58% of supported companies). Data was also collected for a control group of 6622 firms that have not applied for a subsidy from the OPEI, and this group was selected randomly from the business register. Table  11.1 shows the sample distribution across the Czech NUTS 3 Regions for both groups. Table 11.2 reports all variables that are included in the empirical analysis and Table 11.3 reports summary statistics for the outcome variables concerning supported and non-supported enterprises.

11.4 Results and Discussion The previously introduced methodology was followed, and a counterfactual evaluation of the OPEI, based on the propensity score matching strategy combined with a difference in differences approach (DID) was conducted. From the various matching techniques, the analysis followed the nearest neighbour matching approach that allows us to match supported firms with multiple non-supported counterparts. Such an ability is helpful especially, once there was a limited number of observations with all NUTS 3 regions. An empirical estimation up to five nearest neighbours was

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Table 11.1  Sample distribution across the Czech NUTS 3 regions (with available data after calculation of differences between the periods after and before) NUTS 3 Region/Group Praha South Moravia South Bohemia Karlovy Vary Vysocina Hradec Kralove Liberec Moravia-Silesia Olomouc Pardubice Pilsen Central Bohemia Zlin Usti and Labem Total Source: Own calculations

Treated N/A (Excluded) 15.8% 4.6% 2.3% 6.3% 6.3% 5.1% 14.0% 8.4% 6.1% 3.9% 9.8% 10.9% 6.5% 100% (N = 3614)

Control N/A (Excluded) 16.2% 8.6% 2.6% 5.8% 7.7% 4.1% 11.5% 6.6% 6.3% 6.0% 11.3% 6.9% 6.4% 100% (N = 6622)

Table 11.2  List of variables Variable Group variables treated

Definition A dummy variable that indicates whether the particular firm participated in the programme OPEI

Control variables Year of The year in which the firm has officially registered, i.e. the date of registration incorporation Company size Variable divides firms into the four dummy categories according to the number of employees reported: size micro (0–9 employees), size small (10–49 employees), size medium (50–249 employees) and size large (250 and more employees) Legal form Variable divides firms according to their legal form: self-employed/ freelancer, limited liabilities company, joint stock company, other Postal code Variable characterises the location of the firm’s headquarters according to the administrative division of the territory for mail delivery purposes (as five-digit zip code) Region Variable divides firms into the 13 dummy variables according to the Czech NUTS 3 regions in which the supported firms realised their project or where the non-supported firms have an official headquarters Sector Variable divides firms into the 19 NACE dummy categories according to their business activity Total assets Variable represents the value of total assets of a firm (in ths. CZKa) Debt ratio Variable is calculated as the share of liabilities of a firm on its assets (in %) Outcome variables Assets growth Variable represents the change in the value of total assets between 2 consecutive years, measured in CZK Tangible fixed Variable represents the change in the value of tangible fixed assets assets growth depreciation between two consecutive years, measured in CZK (continued)

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Table 11.2 (continued) Variable Sales growth

Definition Variable represents the change of total sales, i.e. sales of goods and sales of own products and services, between two consecutive years, measured in CZK Return on assets ROA is calculated as the ratio of EBIT of a firm to the value of its assets. (ROA) growth Variable represents the change of ROA between two consecutive years. a The average exchange rate for period of years 2005–2016 was 26.67 EUR/CZK Notes: CZK Czech crowns. The outcome variables are calculated as average values in two analysed periods, i.e. before intervention (during the years of 2005–2006) and after the intervention (2014–2015) Source: Own elaboration (based on Brealey et al. 2017) Table 11.3  Summary statistics for outcome variables ((2014–2015) – (2005–2006)) Mean 119,813.2 64,161.4 Tangible fixed assets growth 40,519.4 13,682.8 Sales growth 132,331.2 107,994.9 Return on assets (ROA) growth −6.1 −5.5 Notes: SD standard deviation, N number of observations Source: Own calculations Indicator Assets growth

Group Treated Control Treated Control Treated Control Treated Control

SD 1,165,166 1,027,706 601,938.8 451,958 1,065,812 1,844,838 241.6 394.6

N 3614 6622 3605 6553 3528 6393 3613 6615

followed, and both groups of companies based on all observable characteristics that were available in the dataset (year of registration, company size, legal form, postal code, region, sector and pre-intervention values of total assets and debt ratio) were matched. As such, the selected covariates likely helped to reduce the heterogeneity and bias between supported and non-supported firms (Shakhnarovich et al. 2006; Todd 2010). Once both groups of companies (Treated and Control) were matched together, the quality of matching was checked to make sure that both groups of firms are not statistically different from each other (Khandker et  al. 2010). The values were checked (before and after matching) of Pseudo R2 (before matching: 0.37, after matching: 0.00), mean bias (before matching: 18.3, after matching: 1.2) and median bias (before matching: 10.3, after matching: 0.6) and led to the conclusion that both groups of companies are not different concerning the variables we have in our dataset. Therefore, the average treatment effect on the treated (ATET) concerning the 13 NUTS 3 regions (separate estimates of effects for each of the regions) was estimated. The ATET is calculated as a difference between periods after the end of the programme (2014–2015) and before the programme had started (2005–2006). The authors have bootstrapped the estimates by hundred times to achieve more stable econometric results. Based on the empirical results presented in Table  11.4, the heterogeneity of the effects of the OPEI on the firm’s performance in the Czech

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regions was explored. In this stance, the estimates are quite complex, so Table 11.5 was prepared, which summarises statistical significance and direction of impact for all variables and regions in a more nuanced way. Having looked at the empirical results (Tables 11.4 and 11.5), it is possible to support our assumption that the effects of the OPEI have differed across the Czech NUTS 3 regions. The results indicate in several regions different directions of impact, and the statistical significance differs across regions. The empirical results Table 11.4  Estimated Average Treatment Effect on the Treated (ATET) as a difference in differences ((average outcomes 2014; 2015) – (average outcomes 2005; 2006)) Outcome variable Assets growth

Tangible fixed assets growth

Sales growth

Region South Moravia South Bohemia Karlovy Vary Vysocina Hradec Kralove Liberec Moravia-Silesia Olomouc Pardubice Pilsen Central Bohemia Zlin Usti and Labem South Moravia South Bohemia Karlovy Vary Vysocina Hradec Kralove Liberec Moravia-Silesia Olomouc Pardubice Pilsen Central Bohemia Zlin Usti and Labem South Moravia South Bohemia Karlovy Vary Vysocina Hradec Kralove Liberec Moravia-Silesia Olomouc Pardubice Pilsen Central Bohemia Zlin Usti and Labem

ATET 36,349.31* 24,140.78 52,554.18* 42,502.65 256,773.5 91,628.77 14,130.43 54,060.58+ 12,275.08 208,933.4* −22,306.55 121,432.9+ 43,920.95 15,424.41* 17,284.37 24,073.74** 24,391.58 150,446.2 59,457.04 13,225.08 27,733.76* −1487.63 92,722.44** −19,575.88 42,602.26*** 28,630.08 53,078.11* −278,739.3 67,074.79 30,318.62 243,489.9 −125,551.9 −271,471.9 57,436.3 −41,766.14 452,009.4*** −134,740.8 45,945.99 51,299.8

Std. Error 18,619.79 51,606.12 25,935.72 39,099.69 238,261.2 115,869.4 388,113.7 33,220.91 43,927.04 100,286.7 76,730.5 69,941.02 30,272.13 7304.23 27,779.87 9866.58 15,736.16 134,073.9 37,668.71 100,813.3 11,977.34 20,006.91 36,939.51 49.111.83 13,928.62 21,733.71 23,470.99 229,979.1 53,407.87 64,831.47 179,177.2 98,908.18 658,573.7 50,405.45 169,291.8 153,870.3 111,040 58,210.84 41,641.58

P-value 0.05 0.64 0.04 0.28 0.28 0.43 0.97 0.10 0.78 0.04 0.77 0.08 0.15 0.04 0.53 0.01 0.12 0.26 0.11 0.90 0.02 0.94 0.01 0.69 0.00 0.19 0.02 0.23 0.21 0.64 0.17 0.20 0.68 0.26 0.81 0.00 0.23 0.43 0.22

N 1607 569 185 548 597 416 1136 694 617 420 982 789 586 1590 563 185 545 593 415 1128 692 616 416 976 785 583 1557 551 180 538 580 404 1106 668 606 398 948 774 562

(continued)

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Table 11.4 (continued) Region ATET Std. Error P-value N Outcome variable Return on Assets (ROA) growth South Moravia 2.66 0.24 1607 −3.15 South Bohemia 2.41 6.54 0.71 569 Karlovy Vary 6.07 0.55 185 −3.64 Vysocina 2.70 0.93 548 −0.24 Hradec Kralove 2.96 4.14 0.47 597 Liberec 1.78 2.61 0.49 416 Moravia-Silesia 10.66 19.11 0.58 1136 Olomouc 2.51 0.16 694 −3.51 Pardubice 1.88 0.49 617 −1.29 Pilsen 3.72 0.82 420 −0.86 Central Bohemia 4.37 18.39 0.81 982 Zlin 2.83 0.01 789 −7.35** Usti and Labem 1.62 5.15 0.75 586 Notes: Nearest neighbour matching estimates (with up to five nearest neighbours). Bootstrapped standard errors with 100 replications were used for all estimates together with common support option. Stat. significance: + p