Explaining Local Policy Agendas: Institutions, Problems, Elections and Actors (Comparative Studies of Political Agendas) 303090931X, 9783030909314

Citation preview

COMPARATIVE STUDIES OF POLITICAL AGENDAS

Explaining Local Policy Agendas Institutions, Problems, Elections and Actors Peter B. Mortensen Matt W. Loftis Henrik B. Seeberg

Comparative Studies of Political Agendas Series Editors Christoffer Green-Pedersen Aarhus University Aarhus, Denmark Laura Chaqués Bonafont University of Barcelona Barcelona, Spain Arco Timmermans Leiden University The Hague, The Netherlands Frédéric Varone Université de Genève Geneva, Switzerland Frank R. Baumgartner University of North Carolina at Chapel Hill Chapel Hill, USA

The series publishes books on policy agenda-setting dynamics broadly understood. This includes for instance books dealing with the policy effects of agenda dynamics, the relationship between the political agenda, public opinion and the media agenda, and agenda dynamics in relation to particular issues. The series publishes both comparative books and books dealing with single countries if these single countries are placed in a comparative context. The books can be either monographs or edited volumes. More information about this series at http://www.palgrave.com/gp/series/14908

Peter B. Mortensen • Matt W. Loftis Henrik B. Seeberg

Explaining Local Policy Agendas Institutions, Problems, Elections and Actors

Peter B. Mortensen Department of Political Science Aarhus University Aarhus C, Denmark

Matt W. Loftis Department of Political Science Aarhus University Aarhus C, Denmark

Henrik B. Seeberg Department of Political Science Aarhus University Aarhus C, Denmark

Comparative Studies of Political Agendas ISBN 978-3-030-90931-4    ISBN 978-3-030-90932-1 (eBook) https://doi.org/10.1007/978-3-030-90932-1 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed 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 Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

A primary motivation of this book is to show the potential of doing policy agendas research at the local level of government, and on that score, this book represents the first large-scale local policy agendas study. Based on a dataset of hundreds of thousands of local policy agendas observed from across all 98 Danish municipalities, the book utilizes cross-section, longitudinal, and even quasi-experimental research to shed new light on the effects of institutions, societal problems, elections, and actors on policy agendas. It is our hope that this book will spark renewed and strengthened efforts to develop the theoretical explanations of policy agendas further through systematic measurement and rigorous empirical inquiry of local policy agendas in other countries. This book was a long time in the making. Our project on local policy agendas began in 2014, supported by a large grant from the Danish National Research Council (DFF—1327-00091). From the very beginning of the project, it was our ambition to write this book, but first, it took almost two years to get the data collected and coded. Then we got distracted by articles we started to write as a warm up to this book, but if you are not attentive, the match can be over before you finish warming up. Yet, the warm-up articles were a necessary step in familiarizing ourselves with the data and the research designs utilized in this book. Though none of the articles are closely related to the content of the book, we believe this has become a better book than the one we could have written several years ago. To be honest, we also got distracted by other research projects, and when we finally got to writing the book, we realized that we needed to v

vi 

PREFACE

update the data with another four-year election period—which involved collecting and coding almost 80,000 more agenda observations. During the process of working on this book, we have benefitted tremendously from conversations with and comments from a great many colleagues. The first sketchy contours of this book were presented to the Policy Agendas Project group at UT Austin in Texas in the fall of 2016. Drafts of Chap. 3, which is co-authored with Søren Serritzlew, have been presented at the Annual CAP Conference in Edinburgh in 2017, in the Virtual Political Economy Workshop in Oslo in 2020, and in various research sections of our amazing home institution, the Department of Political Science at Aarhus University. An earlier draft of Chap. 5 was presented at the NORKOM conference in Aarhus in 2018 and at a talk at the Department of Political Science in Gothenburg in 2019. In addition, we are grateful for comments on this book from Frank R.  Baumgartner, Martin Bækgaard, Jens Blom-Hansen, Bryan D.  Jones, Jason Eichorst, Christoffer Green-Pedersen, Carsten Jensen, Jan Erling Klausen, Søren Serritzlew, and Signy Vabo. A special thanks to Martin Bækgaard and Carsten Jensen, both of whom have been involved in the broader research project on local policy agendas. This book has also benefitted from excellent assistance in collecting and coding of local government data from the following student assistants: Emilie Christensen, Johan Garfiel, Aske Halling, Astrid Strandly Henriksen, Charlotte Hvidman, Lasse Jensen, Nanna Jensen, Maja Kirkegaard, Thomas Artmann Kristensen, Martin Helland Olesen, Kirsten Seeberg, Johanne Søndergaard, Anne Veien, and Peter Beyer Østergaard. Furthermore, we owe many thanks to Natasha Elizabeth Perera here in Aarhus for her excellent support and help in preparing the manuscript. We also thank our editor at Palgrave, Stewart Beale, for efficient collaboration and competent handling of the publication process. We dedicate the book to Frank R. Baumgartner and Bryan D. Jones. Without their path-breaking lead on how to conduct rigorous research on policy agendas, this book, as well as many, many other books and articles, may have never been written. In addition, for several decades, Frank and Bryan have offered constant support and intellectual inspiration to not only the authors of this book but a whole community of both new and established policy agenda scholars. For this, we are truly grateful. Aarhus, Denmark August  2021 

Peter B. Mortensen Matt W. Loftis Henrik B. Seeberg

Contents

1 Why Study Local Policy Agendas  1 2 How to Study Local Policy Agendas 19 3 Jurisdiction Size and the Local Policy Agenda 43 4 Committee Structure and the Local Policy Agenda 65 5 Local Problems and the Local Policy Agenda 95 6 Local Elections, Local Actors, and the Local Policy Agenda119 7 Toward an Explanatory Model of Local Policy Agendas147 Appendix A: List of Subtopics169  Appendix B: Construction of 25 Major Topics for the Local Policy Agenda181  Appendix C: Statistical Power and Assumptions of the Analyses in Study 2 in Chap. 3183

vii

viii 

Contents

 Appendix D: Municipalities Selected for the Analyses of Committee Effects in Chap. 4187 Appendix E: Dataset on Local Actors Used in Chap. 6189 Index191

List of Figures

Fig. 2.1 Fig. 2.2 Fig. 2.3 Fig. 2.4 Fig. 2.5 Fig. 2.6 Fig. 3.1 Fig. 3.2 Fig. 3.3 Fig. 3.4 Fig. 3.5 Fig. 3.6 Fig. 4.1 Fig. 4.2

Average political and institutional indicators across Danish municipalities, 2007–2016 20 Attention to each major topic (pct.) in the 98 Danish municipalities, 2007–2016 31 Attention to four issues (pct.) over time in the 98 Danish municipalities, 2007–2016 32 Attention differences by issue (pct. points) in two neighboring Danish municipalities, 2007–2016 33 The number of agenda points in the 98 Danish municipalities, 2007–201635 Proportion of variance explained by components from PCA analysis of governmental attention to all major topics across 98 Danish municipalities, 2007–2016 38 Geographic variation in measures of agenda size and complexity, 2007–2016 49 Predicted values of relationship between jurisdiction size and the local policy agenda 52 Effect coefficients for population size from seemingly unrelated regression 53 Population change over time across the sample 56 Coefficient estimates from main DiD models 58 Predicted values of outcome variables by treatment condition and time 60 The combined effect of the two forces 71 The attention (budget) constraint over issues on the policy agenda 73

ix

x 

List of Figures

Fig. 4.3

Counts of committees in Danish local councils by election periods 75 Fig. 4.4 Committee structure in Svendborg Municipality, 2010–2013 and 2014–2017 76 Fig. 4.5 Total number of committees and council seats by municipal population77 Fig. 4.6 Committee sizes across all 98 municipalities, 2008 79 Fig. 4.7 Agenda size and count of subtopics (agenda complexity) by number of committees 81 Fig. 4.8 Committee system changes and system processing capacity 85 Fig. 4.9 The agenda effects of changing committee jurisdictions 87 Fig. 4.10 Change in number of agenda points per issue when moving from two committees to one in Svendborg Municipality 90 Fig. 4.11 Percentage of subtopics that get less, more, or the same attention following a change in the committee structures in Ishøj and Svendborg 91 Fig. 5.1 Illustration of three different scenarios of a link between problems and attention 100 Fig. 5.2 Variation in local problems and attention on seven issues in 98 Danish municipalities, 2007–2016 105 Fig. 5.3 Comparing local problems and local political attention to business and unemployment at low and high levels of political competition in a pair of similar Danish municipalities 107 Fig. 5.4 Influence of local problems on local political attention in 98 Danish municipalities, 2007–2016 111 Fig. 5.5 Marginal effect of local problems on local policy agenda by majority size 112 Fig. 5.6 Effect parameter estimate on local problems for the interaction with the issue-ownership indicator variable 113 Fig. C.1 Frequency of simulated significant estimates of DiD effect by simulated true value of DiD effect and simulated error variance 184 Fig. C.2 Time trends in the outcome variable across treatment and control municipalities 186

List of Tables

Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 2.5 Table 3.1 Table 3.2 Table 4.1 Table 4.2 Table 4.3 Table 5.1 Table 5.2 Table 5.3 Table 6.1 Table 6.2 Table 6.3

Council politics, summary statistics, 98 Danish municipalities, 2007–201622 An example of a local council meeting agenda 24 Overview of the major topics and an example of the subtopics within each major topic 26 Agenda datasets 28 Summary statistics of the agenda measures in the 98 Danish municipalities, 2007–2016 37 The effect of jurisdiction size on the local policy agenda 51 Cross-tab of observations by treatment condition and reform timing57 Comparison of the two groups of municipalities on key variables 80 Agenda size and system processing capacity 84 Number of subtopics and Shannon’s H in Ishøj and Svendborg Municipalities 88 Agenda measures and problem indicators for the analysis 104 Influence of local problems on local agendas across 98 Danish municipalities, 2007–2016 110 Influence of local problems on local policy agendas across 98 Danish municipalities, 2007–2016. Interaction between issue ownership and local societal problems 113 Hypothetical example of agenda stability 130 Agenda stability, summary statistics, 98 Danish municipalities, 2007–2016131 Changes to the positions of mayor and city manager as well as the mayor party in the 98 Danish municipalities, 2007–2016 134

xi

xii 

List of Tables

Table 6.4

The effect of elections and actors on the level of agenda stability in the 98 Danish municipalities, 2007–2016 Table 7.1 Overview of tests conducted in this book Table B.1 Overview of the construction of 25 major topics from the subtopics (by numeric code) Table D.1 Municipalities selected for the analyses of committee effects in Chap. 4

137 157 181 187

CHAPTER 1

Why Study Local Policy Agendas

Every policy change governments make begins with an issue, a policy, or a new framing entering the policy agenda. In this way, agenda setting is a precursor of policy change. Attention is the scarcest currency in politics and the most in demand. Legislatures and bureaucracies spend their finite budgets of attention in a potentially infinite space of problems and policy proposals. The limits on attention are both hard and fundamental. They are hard in the sense that the resources needed for attention, that is, time, are strictly finite and exhaustible. Those limits are fundamental in that they constrain at every level, all the way down to the boundedly rational individuals inhabiting every political institution. The consequence is that the prioritization of which problems to address and which to ignore is as important or more than the question of which decisions to make once the agenda is set. Fruitful research programs are launched with a well-posed question, and for many decades, political science has been grappling with a particularly good one: What determines the policy agenda? In this book, we present an answer to this question that integrates four central aspects of any democratic political system: the institutions that structure politics (e.g. jurisdiction size and committee systems); the occurrence of general, regular, and free elections; the problems confronting the political system (e.g. unemployment and crime); and the actors navigating the political system (e.g. politicians, parties, and bureaucrats). Building an explanatory model © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 P. B. Mortensen et al., Explaining Local Policy Agendas, Comparative Studies of Political Agendas, https://doi.org/10.1007/978-3-030-90932-1_1

1

2 

P. B. MORTENSEN ET AL.

on these four factors not only improves our understanding of the determinants of the policy agenda but also points to a further integration of policy agendas research with more general questions of political science. In examining these questions, the book points a way forward to strengthening the scientific tools we bring to bear on the basic question of what determines the policy agenda. We apply strong comparative research designs for studying policy agendas, made possible with a comprehensive dataset of local policy agendas over a decade from 2007 to 2016 and across 98 geographically distinct local political systems. Each of the systems we study has its own political system, and each operates and decides on its own standing committee structure. Each has broad power over salient, and sometimes divisive, policy areas that are consequential for their constituents’ daily lives. At the same time, they feature identical electoral systems, very similar party systems, and almost the same institutional relationships to executive agencies. Usefully, they even all operate in the same language. In the often data-starved world of quantitative comparative politics, a cross-sectional policy agendas dataset this large and free of troubling omitted variables is virtually unheard of. This study is possible because the 98 units we study are all situated in the same country. They are the 98 local government councils of Denmark. Based on more than 250,000 coded units of local council agendas, this book reports the first large-scale studies of local policy agendas. Despite major advances over the past decades, the national-level policy agendas studies have a bias that we address in this book. The national-level research has been preoccupied with dynamics and change in policy agendas (Baumgartner et  al., 2008; Baumgartner & Jones, 1993; Green-­ Pedersen & Wolfe, 2009; John & Jennings, 2010; Kingdon, 1984). Yet, agenda setting is not only about change and dynamics. Fundamentally, a policy agenda is a set of issues that are communicated in a hierarchy of importance at a point in time (Dearing & Rogers, 1996, p. 2). Often, this set of issues is rather stable over time, and consequently, agenda setting is also about systematic and sometimes rather permanent biases. For instance, it might be—as shown by Crenson’s (1971) classic comparative study— that an issue is always high on the policy agenda in one city and always low on the agenda in another city. The consequences of such systematic differences in issue attention across political systems may be substantial, but they have received relatively little attention in national-level studies with a focus on agenda changes. This is likely in part because such systematic differences have

1  WHY STUDY LOCAL POLICY AGENDAS 

3

been difficult to study at the national level due to a lack of comparable cases. The local level of government offers more cross-sectional variation and thus better opportunities to study how slow-moving factors such as institutions shape policy agendas. Furthermore, moving to the numerous units at the local level of politics makes it possible to move the study of policy agenda setting into the realm of multivariate research. At the same time, this provides a basis for actually developing and testing explanatory models of the factors influencing policy agendas, which is crucial for integrating the study of policy agendas with some of the broader debates in political science and public policy. Particularly, we shed new light on the following themes and questions, and in doing so, we systematically examine a broad set of policy agenda explanations. First, jurisdiction size matters for how democracy works. This is an idea that dates as far back as Plato’s thinking on city-states. The idea has lived on in both the scholarly literature and in political discussions about amalgamation reforms. In Chap. 3, we argue that across the many arguments about why and how size matters, there is a strong common idea. The policy agenda is of a different nature in small and large jurisdictions. In larger jurisdictions, political discussions are more comprehensive, incorporate more complexity, and involve a larger number of topics and issues. The implication is that the content, complexity, and size of the policy agenda depend on the jurisdiction size. This basic expectation, however, has never been subject to systematic examination. In Chap. 3, we utilize our data on local policy agendas to study size effects across the diversity in size observed in the 98 Danish municipalities. Furthermore, we investigate in a quasi-experimental setup how an exogenously induced amalgamation reform leads to a change in the local policy agendas. Second, among the most classic questions in political science is how institutions structure and shape politics. Institutions are not neutral in their impact. Changing institutions can alter political choices and outcomes by restructuring access to information or by reallocating decision-­ making power as argued by, for instance, Krehbiel (1990), Hammond (1993), and Schattschneider (1960). In Chap. 4, we theorize and study both static and dynamic effects of committee structures on policy agendas. The chapter advances our theoretical and empirical understanding of how differences in the committee structure influence elected policymakers’ attention. Theoretically, we identify two central forces shaping the effect of the committee system: the parallel processing capacity of the system and the bottleneck of attention characteristic of all policymakers. The new

4 

P. B. MORTENSEN ET AL.

insights come when these two forces are combined into one model of the structure–agenda link. The Danish municipalities provide a fruitful setting for examining this model. There is substantial variation in committee structures both within and across municipalities. Thus, unlike earlier national-level policy agenda studies, which predominantly have worked with a relatively fixed number of committees in stable institutional systems, in Chap. 4, we model and study the effects of actual variations in committee structures. Third, the size and intensity of societal problems such as crime or unemployment vary within countries, and an important task of local governments is to address problems within the geographical jurisdiction of the local government. In fact, such variation is a standard argument for empowering subnational authorities to govern distinct geographical parts of the country differently from one another as argued by Tiebout (1956) and Dahl (1967). In Chap. 5, we examine how well the local councils perform this task. Our measurements of policy agendas are particularly well suited to examine these questions empirically. For example, social democratic parties may prefer to tackle crime through social policy, while conservative parties might favor enacting stricter penalties. However, in a healthy local democracy, with functioning accountability, parties of all political colors are concerned with tackling a rising societal problem. Thus, if local crime rates increase, then responsive local politicians attend to and deliberate the issue—even though, at that time, crime may or may not be a major problem at the national level of politics. Focusing on seven different problem domains, Chap. 5 examines local societal problems’ role in forming local policy agendas and shows how local political competition is a crucial condition for the degree of problem responsiveness. Fourth, a prime characteristic of a well-functioning democracy is the ability to include new issues on the policy agenda. Thus, the long-standing scholarly interest in agenda stability and change is well-justified (e.g. Baumgartner & Jones, 1993; Cobb & Elder, 1972; Kingdon, 1984; Schattschneider, 1960). In Chap. 6, we evaluate a range of factors that others have argued condition agenda change. In particular, we examine if a local election, a shift in the local government, or the replacement of individual local policymakers lead to changes in the local policy agenda. Building on the large number of comparable local government observations, Chap. 6 offers the first integrated, large-n study of how elections and actors (collective and individual) influence the stability and change of policy agendas.

1  WHY STUDY LOCAL POLICY AGENDAS 

5

In the remainder of this chapter, we elaborate on the two main motivations of the book. One is that local governments are important parts of most political systems and that by studying local policy agendas, we gain valuable new insights about the functioning of local politics. The other is that we can learn much about politics and policy agendas in general by studying policy agendas at the local level of politics.

Two Motivations for Studying Local Governments Many essential decisions that influence and shape our lives as citizens are made at the local level of government. In many European countries, local authorities make important decisions on issues of education, transportation, local infrastructure, town planning, social services, waste collection, libraries, local parks and leisure activities, local tax collection, and in some instances also police and fire services (Panara & Varney, 2015). The status and independence of local authorities vary across countries, from the strong and very independent Swiss Cantons to the relatively powerless German municipalities. Even in constitutionally based unitary parliamentary systems such as in the UK, we find examples of strong and important local authorities. This is, perhaps, most pronounced in the Nordic countries where municipalities spend up to 30 percent of GDP (Boadway & Shah, 2009). Local governments have an important task of prioritizing between problems of importance to the local public. Furthermore, though some countries centralize more decisions to the central level of government than others, a general trend in Europe over the last decades has been a diffusion of authority from the central level of government to the regional and local levels of government (Hooghe et al., 2010). The importance of local government is also reflected in a long-standing and massive research agenda on local government. Whereas the intensity of US research on urban politics has increased and decreased over time, partly reflecting changes in federal policies and programs toward the cities (see Pierre, 2014, p. 868), research on local politics in Europe has been more steady (see Panara & Varney, 2015). A genuine interest in local-level policy-making has driven a large strand of research (e.g. Peterson, 1981; Stone, 1989; Tiebout, 1956). Local governments are important and differ in many ways from national-level policy-making, and therefore, it is important to understand and explain how local governments work.

6 

P. B. MORTENSEN ET AL.

A second motivation to study the local level of government is the unique opportunities to use the local level of government as a research laboratory for examining questions of general relevance to political science. From this perspective, the large numbers of comparable governments allow researchers to build strong research designs with which to examine research questions that are hard to study at the national level of politics. Scholars, for instance, have shown how the local level of government can provide new and important insights into general questions about coalition formation (Serritzlew et al., 2010), party politics (Blom-Hansen et al., 2006), reform effects (Bhatti & Hansen, 2011), scale effects (Blom-­ Hansen et  al., 2016), and responsiveness to citizen demands and needs (Caughey & Warshaw, 2018; de Benedictis-Kessner & Warshaw, 2019). The most prominent example of such research is probably Robert Putnam’s (1993) Making Democracy Work, which was based on a comparison of regional governments in Italy after an institutional reform of their structures. There is no inherent contradiction between the two motivations for doing local government research, and this book is founded on a dual interest in learning more about local government politics and in answering questions of general relevance to political scientists. In pursuing these goals, we hope to contribute to a (re-)integration of local government research and the broader discipline of political science. Local politics research once occupied the epicenter of advanced theorizing, and the broader discipline embraced the questions and ideas dominating local government research. Seminal examples are work by Robert Dahl, James Q. Wilson, Floyd Hunter, Aaron Wildavsky, and Theodore Lowi. Yet, as argued and shown by Sapotichne et  al. (2007, pp.  76–77), times have changed and the field of local government research has been largely disconnected from developments and conceptual interests in other main subfields. There are important exceptions of course and also signs of a new wave of local government research of broader significance to the field of political science (e.g. de Benedictis-Kessner & Warshaw, 2016, 2019; Tausanovitch & Warshaw, 2014; Trounstine, 2010; Warshaw, 2019). In this chapter, we are particularly concerned with how the study of local policy agendas can advance both our understanding of local government politics and our understanding of broader questions about politics.

1  WHY STUDY LOCAL POLICY AGENDAS 

7

The Importance of Local Policy Agendas Understanding the local policy agenda—the list of issues to which local political decision-makers devote their attention—is of crucial importance if we want to understand how local political systems work and function. As noted by Dearing and Rogers (1996, p.  1), every political system must have an agenda if it is to prioritize the problems facing it. This prioritization is necessary for large political systems as well as for smaller communities. It follows from this observation that the list of potential issues that could be part of a local policy agenda always exceeds the number of issues actually addressed by local governments (Cobb & Elder, 1972, p.  14). One important source of this limitation is the restricted processing and attention capabilities of any human organization (Cobb & Elder, 1972, p. 10; Jones, 2001). Another source is the restriction caused by the fact that all forms of organizations have a bias favoring some issues over others (Schattschneider, 1960; Cobb & Elder, 1972, p. 10). The consequence of this agenda limitation is that the prioritization of which problems to address and which to ignore is as important or more than the question of what decisions to make once the agenda is set (Bachrach & Baratz, 1962). Thus, even though the range of issues addressed by local governments is often narrower than the range of issues addressed by national governments (e.g. defense and foreign policy is national only), local governments still have an important and demanding task of prioritizing between different problems and issues. At a given point in time, how much attention should the local council devote to issues of environmental regulation, housing issues, local business development, elder care, waste disposal, the local economy, and so on? How hard these prioritizations are may depend on a range of factors related to the organization of local politics, the size of the municipality, and the local problem context, but this is exactly the kind of question that needs to be addressed and which can only be addressed by systematically studying local policy agendas. The concept of a local policy agenda refers to the set of issues explicitly up for serious consideration by local policymakers (Cobb & Elder, 1972, p. 86). Focusing on this concept has the advantage of bringing us rather close to the policy-making process while still yielding the analytical rigor needed when comparing observations over time and across local government units. On the other hand, a limitation is, of course, that this measure does not deal with the policies decided by the politicians. An approximate

8 

P. B. MORTENSEN ET AL.

measure of local policy is local public spending, which represents an important output from the political system and which has been much used in local government research (e.g. Blom-Hansen et al., 2006; Danziger, 1978; de Benedictis-Kessner & Warshaw, 2019). Yet, the indicator of public spending is often distanced from the policy-making stage, and the use of public spending as a measurement of the policy agenda necessarily overlooks much political activity. Sometimes, an issue is discussed intensively among policymakers, but they ultimately decide not to change public spending, and therefore, there will be no indication of political activity registered in the public budget. With a focus on local policy agendas, we come closer to tracing local political attention and debate, and as further argued in subsequent chapters of this book, this focus on the agenda stage sheds new light on a range of major questions in our discipline.

What We Know About Local Policy Agendas It is difficult to identify a distinct and active local government agenda-­ setting research field. Research on urban regimes (see Mossberger, 2009; Stone, 1989) has generated a few studies that can qualify as agenda-setting studies (see also Groth & Corijn, 2005; Hula et al., 1997; Thornley et al., 2005; Wong & Jain, 1999). While there is no explicit mention of agendas and agenda setting in most of this work, a common trait of this research, which comes out of the urban regime literature, is a critical focus on who is included in the decision-making process and to what effect. Most of these scholars do case studies focusing on one to three cities (for a more elaborate review, see Eissler et al., 2016). Other examples of local policy agendas research are scholars who apply national-level theories of policy agendas to the local level of government. Some scholars have used Baumgartner and Jones’ (1993) punctuated equilibrium theory (see Breeman et  al., 2014; Goetz & Sidney, 1997; Marschall & Shah, 2005; Riposa, 2004; Sapotichne & Smith, 2012), while others have been inspired by Kingdon’s (1984) multiple streams approach (Keskitalo et  al., 2012; Liu et  al., 2010; Silver et  al., 2002; Steinacker, 2001). In terms of genuine local policy agendas research, we were only able to locate one study by Breeman et  al. (2014) that examines which issues are on the local agenda in a small selection of Dutch municipalities. Although some trends—or at least tendencies—can be observed, there is no distinct local policy agendas literature. As argued by Eissler et  al. (2016, p.  308), the studies are too few, the questions too case-specific,

1  WHY STUDY LOCAL POLICY AGENDAS 

9

and the empirical approaches too varied to qualify as a distinct research field. In line with this reading of the literature, another review concluded that the literature on local agenda-setting research is “schizophrenic” (Sapotichne & Jones, 2012, p.  456). Some pluralism is certainly warranted, but for a research field to mature, there must be consensus on a few fundamental aspects. The lack of progression and accumulation in  local policy agendas research stands in contrast to the development at the national level of politics, where agenda-setting research has proliferated over the past 25 years. Sparked by the path-breaking 1993 book, Agendas and Instabilities in American Politics, by Baumgartner and Jones, an international community of agenda-setting scholars from more than 20 countries has formed the Comparative Agendas Project (CAP) network (https://www.comparativeagendas.net/). The network is united around the systematic application of a common approach to code policy agendas over time and across countries. In a recent count, the number of studies utilizing this methodological approach to agenda setting reaches more than 400 publications since 2005 (Baumgartner et al., 2018). In this book, we provide a framework for studying local policy agendas using an adapted version of the measurement system developed in the CAP network. By systematically classifying attention to issues across local government units and over time for each local government unit, we can consistently trace political attention through time and space and thereby provide new and wide-ranging answers to the question of what determines local policy agendas. This way, we hope to inspire other researchers to exploit the laboratory of local government, and we hope to ignite a research agenda on local government and local agenda setting in particular.

The Potential of a Unified Dataset on Local Policy Agendas The empirical basis of this book is the systematic collection and coding of issue attention in ways that can be compared over time and across local government units. It builds on the measurement system approach explained by Jones (2016). Its central feature is that it enables us to trace local government issue attention within and between municipalities at the lowest level of aggregation, namely individual agenda items at city council meetings. Our data and coding approach are explained in detail in Chap. 2.

10 

P. B. MORTENSEN ET AL.

Applying this systematic measurement system to the study of local policy agendas across a large number of local political units invites a system-­ level perspective rather than a perspective focused on power or policy-making processes. Agenda-setting research originated from the community power studies in the 1950s and 1960s that centered on questions of “Who governs?” and “Who sets the agenda?” These were about biases in the system, the underrepresentation of minority viewpoints, and ultimately, it was about power—those with political power and those without political power (e.g. Bachrach & Baratz, 1962; Dahl, 1961). In other words, focus was very much on which actors were able to set the agenda. Yet, from a political system perspective, the most interesting question is not about agenda setting. Perhaps no one controls the agenda, and perhaps the process of agenda setting—the actors involved and who met with whom—does not tell us very much about the size and content of a policy agenda. Perhaps policy agendas are shaped by local institutional structures, perhaps they are relatively stable as argued by Cobb and Elder (1972), or perhaps the policy agenda is shaped by forces of the past (Walker, 1977). Thus, studying policy agendas need not be about studying the role of particular entrepreneurs or powerful actor networks. When zooming out and observing local policy agendas across several years and across a large number of local political units, we see patterns of policy agendas that can be invisible when studying the particular processes of agenda setting in one or a small number of cities or municipalities. In this book, we use a systematic measurement system to examine more structural characteristics and determinants of the policy agenda. The unified dataset allows us to examine how the local policy agenda is different in large and small municipalities (Chap. 3), how the policy agenda reflects the institutional organization of local politics (Chap. 4), how the agenda responds to changes in the severity of local societal problems (Chap. 5), and how the agenda changes when local policymakers or local political majorities are replaced (Chap. 6). It is important to note that our approach does not exclude the revelation of patterns of systematic biases, and it has the potential to contribute to critiques of the governing systems we study. Showing, for instance, that the local institutional structure matters to the issue priorities on the local policy agenda will raise new questions about who had the power to structure local politics. This also leads to the question of how that effect materialized since it must do so through some effect on the process of agenda setting. Although we do not pursue the answers to such additional

1  WHY STUDY LOCAL POLICY AGENDAS 

11

questions raised by the studies in this book, the results we present provide a strong starting point for examining them. Indeed, we argue that this book provides a much stronger starting point for asking important questions about agenda setting and local politics than beginning with the un-­ researchable and quite narrow question of “Who sets the agenda?” in a particular time and context.

What Local Politics Can Teach Us About Policy Agendas Some research questions are better analyzed and addressed at the national level of politics. There may be more at stake in party competition at the national level, institutions may be different than at the local level of politics, and some issues are national (even international) and therefore not well-suited to study at the local level of government. If the interest is, for instance, in the policy agenda on foreign policy, macroeconomics, or defense, then there can be little to learn from studying local policy agendas. There may also be methodological opportunities at the national level of politics that are not present at the local level. For instance, many of the national-level agendas data time series cover several decades, which is made possible by high-quality national-level registers. At the local level of politics, centralized registers are frequently of lower quality, and they are often not systematized many years in the past across local governments. What we gain when we move to the local level of politics is a dramatic expansion of the number of comparable cases, which means that cross-­ sectional variation can better be observed and explained. Such an increase in the number of political systems to observe and to compare improves the explanatory power of the analyses. Using local government data offers strong opportunities for multivariate statistical studies. Furthermore, when observing local political systems both over time and across a large number of systems, we obtain a panel data structure, which means that we do not need to pool very old data with recent observations to assemble enough observations for analysis. Instead, we can focus only on comparable recent data. Furthermore, the national-level agenda-setting literature has, so far, revealed little about the importance of slow-moving factors that impact policy agendas, for instance, the influence of institutions that are substantially different across political systems but rarely change or the impact of leadership changes following long spells of electoral stability.

12 

P. B. MORTENSEN ET AL.

One objection to the use of local-level political units as observations is the important question of whether they are, indeed, independent political systems. Certainly, local governments are more constrained than most nation-states on a range of dimensions (Peterson, 1981). Furthermore, their independence varies across political systems, and competencies at the local level are to a large extent determined by central government. This also implies that local policy agendas may be influenced by non-local factors that we do not pursue further in this book. In the next chapter, we argue that the Danish municipalities make autonomous and politically important local decisions. We further show empirically that there is not much common variation in the policy agendas across the 98 local councils. Rather, policy agendas tend to vary almost completely independently across municipalities, with our data revealing no evidence of patterns across all municipalities nor even evidence that there are clusters of similar municipalities whose agendas vary similarly. Instead, at first glance, Danish local government agendas exhibit a certain chaos. Each municipality has a unique pattern of policy agenda and changes its agenda at its own tempo. As we will see, theory will lead us to uncover many systematic patterns in this chaos, but none of those patterns support the argument that local governments in Denmark are just disempowered or subsidiary administrative units.

Structure of the Book In this chapter, we have argued why the study of local policy agendas is important, not just for learning about local politics but also for advancing our understanding of policy agendas in general as well as our understanding of the effects of central factors identified by the literature of comparative politics, that is, institutions, problems, elections, and actors. In Chap. 2, we lay out an approach for a systematic, large-n study of local policy agendas and justify our choice of the Danish local government as a highly useful research setting. This includes an introduction to the structure of Danish local government and a description of the central agendas dataset used throughout the book. The book adopts a pluralistic approach to theory, in the sense that Chaps. 3, 4, 5, and 6 each take up a unique political science question and treat it rather independently of the other chapters. Thus, every chapter begins with a motivation and a theoretical introduction to its topic followed by a presentation of the research approach pursued in the chapter. This means that each chapter can be read independently of the others.

1  WHY STUDY LOCAL POLICY AGENDAS 

13

Chapter 3 examines the relationship between the jurisdiction size of the municipality and the local policy agenda. The question of scale effects is one of the most enduring questions in political science. It is also a question that has gained much attention at the local level of government (e.g. Dahl, 1967; Newton, 1982). However, neither local nor national-level policy agenda studies have investigated the effect of jurisdiction size on the policy agenda. The chapter investigates two aspects of this. First, it systematically compares similarities and differences in policy agendas across small and large municipalities. Second, it utilizes a major structural reform of the Danish municipalities where two-thirds of the municipalities were merged by January 2007. This reform can be seen as a quasi-­ experiment offering a unique opportunity to examine how such mergers of local political systems influence the local policy agenda formed after the amalgamation. Chapter 4 addresses an important institutional question. The main interest of the chapter is the relationship between the local committee structure and the local policy agendas. The role of committees in agenda setting has also been explored at the national level of policy-making (e.g. Sheingate, 2006; Talbert et al., 1995), but the local municipalities offer the possibility to investigate new aspects of this question. Not only does the number of committees vary between municipalities and over time, but so does the scope of committee policy jurisdiction. Furthermore, the local government setting provides a unique opportunity to investigate the relationship between committee agendas and the agenda of the council (the local assembly). In Chap. 4, we provide new theoretical and empirical answers on how the number of committees affect the policy agenda, how a change in the number of committees responsible for a given issue domain influences attention to the issues within that domain, and how different issues are affected differently by such organizational changes. Chapter 5 investigates the responsiveness of local policy agendas to local problems such as the rate of local unemployment or local crime statistics. The opportunity to adopt local solutions to a problem that may be nation-wide but differs geographically in its severity is a key argument for decentralization (Treisman, 2007) and is expected to enhance democratic participation because it shows that local democracy works (Dahl & Tufte, 1973). Yet, despite the prominence of this argument in favor of having a potent level of local government, there is hardly any empirical research on the topic. To capture this aspect of political representation, we introduce and define the concept of problem-based representation. Furthermore, we

14 

P. B. MORTENSEN ET AL.

collect data on problem indicators across seven issue areas and show how the local policy agendas respond to local problems. Moreover, we evaluate the importance of competitive democracies by examining if local policy agendas in municipalities with more intense political competition are more responsive to local problems. Chapter 6 examines the policy agenda effects of elections and of change in key local actors—both collective and individual. In addressing these effects, the chapter taps into broader discussions in the discipline about the role of elections in politics, the importance of individual policymakers, and the question of whether “parties matter.” In Chap. 6, these effects are evaluated for the first time in an integrated multivariate statistical analysis of policy agendas. Especially the possibility to investigate the effect of the replacement of high-level individual actors—both elected and appointed— across a large number of observations provides new insights about the general importance of individual policymakers in agenda setting. In Chap. 7, we summarize the empirical findings of the book, and based on these, we draw the contours of a set of new explanatory models of local policy agendas that give theoretical and methodological direction for not only local government policy agendas research but also national-­ level policy agendas research. The model outline is followed by a reflection on what the book has shown about (local) democracy as well as reflections on how to further advance explanatory research on policy agendas.

References Bachrach, P., & Baratz, M. S. (1962). Two faces of power. The American Political Science Review, 56(4), 947–952. Baumgartner, F. R., De Boef, S., & L., & Boydstun, A. E. (2008). The decline of the death penalty and the discovery of innocence (1st ed.). Cambridge University Press. Baumgartner, F. R., & Jones, B. (1993). Agendas and instability in American politics. University of Chicago Press. Baumgartner, F. R., Jones, B. D., & Mortensen, P. B. (2018). Punctuated equilibrium theory: Explaining stability and change in public policymaking. In C. M. Weible & P. A. Sabatier (Eds.), Theories of the Policy Process (pp. 55–101). Westview Press. Bhatti, Y., & Hansen, K.  M. (2011). Who “marries” whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations. European Journal of Political Research, 50(2), 212–238.

1  WHY STUDY LOCAL POLICY AGENDAS 

15

Blom-Hansen, J., Houlberg, K., Serritzlew, S., & Treisman, D. (2016). Jurisdiction size and local government policy expenditure: Assessing the effect of municipal amalgamation. American Political Science Review, 110(4), 812–831. Blom-Hansen, J., Monkerud, L. C., & Sørensen, R. (2006). Do parties matter for local revenue policies? A comparison of Denmark and Norway. European Journal of Political Research, 45(3), 445–465. Boadway, R., & Shah, A. (2009). Fiscal federalism: Principles and practices of multiorder governance. Cambridge University Press. Breeman, G., Scholten, P., & Timmermans, A. (2014). Analyzing local policy agendas: How Dutch municipal executive coalitions allocate attention. Local Government Studies, 41(1), 20–43. Caughey, D., & Warshaw, C. (2018). Policy preferences and policy change: Dynamic responsiveness in the American states, 1936–2014. American Political Science Review, 112(2), 249–266. Cobb, R.  W., & Elder, C.  D. (1972). Participation in American politics: The dynamics of agenda-building. Johns Hopkins University Press. Crenson, M. (1971). The un-politics of air pollution: A study of non-decisionmaking in the cities. The Johns Hopkins University Press. Dahl, R. (1961). Who governs? Yale University Press. Dahl, R. (1967). The city in the future of democracy. American Political Science Review, 61(4), 953–970. Dahl, R., & Tufte, E. R. (1973). Size and democracy. Stanford University Press. Danziger, J. N. (1978). Making budgets: Public resource allocation. SAGE. de Benedictis-Kessner, J., & Warshaw, C. (2016). Mayoral partisanship and municipal fiscal policy. The Journal of Politics, 78(4), 1124–1138. de Benedictis-Kessner, J., & Warshaw, C. (2019). Politics in forgotten governments: The partisan composition of county legislatures and county fiscal policies. The Journal of Politics, 82(2), 460–475. Dearing, J. W., & Rogers, E. M. (1996). Agenda-setting (Vol. 6, p. SAGE). Eissler, R., Mortensen, P. B., & Russell, A. (2016). Local government agenda setting. In N.  Zahariadis (Ed.), Handbook of public policy agenda setting (pp. 297–313). Edward Elgar Publishing. Goetz, E. G., & Sidney, M. S. (1997). Local policy subsystems and issue definition: An analysis of community development policy change. Urban Affairs Review, 32(4), 490–512. Green-Pedersen, C., & Wolfe, M. (2009). The institutionalization of environmental attention in the United States and Denmark: Multiple- versus single-venue systems. Governance, 22(4), 625–646. Groth, J., & Corijn, E. (2005). Reclaiming urbanity: Indeterminate spaces, informal actors and urban agenda setting. Urban Studies, 42(3), 503–526. Hammond, T. H. (1993). Toward a general theory of hierarchy: Books, bureaucrats, basketball tournaments, and the administrative structure of the nation-­ state. Journal of Public Administration Research and Theory, 3(1), 120–145.

16 

P. B. MORTENSEN ET AL.

Hooghe, L., Marks, G., & Schakel, A. (2010). The rise of regional authority: A comparative study of 42 democracies. Routledge. Hula, R. C., Jackson, C. Y., & Orr, M. (1997). Urban politics, governing nonprofits, and community revitalization. Urban Affairs Review, 32(4), 459–489. John, P., & Jennings, W. (2010). Punctuations and turning points in British politics: The policy agenda of the Queen’s speech, 1940–2005. British Journal of Political Science, 40(3), 561–586. Jones, B. D. (2001). Politics and the architecture of choice: Bounded rationality and governance. University of Chicago Press. Jones, B.  D. (2016). The comparative policy agendas projects as measurement systems: Response to Dowding, Hindmoor and Martin. Journal of Public Policy, 36(1), 31–46. Keskitalo, E. C. H., Westerhoff, L., & Juhola, S. (2012). Agenda-setting on the environment: The development of climate change adaptation as an issue in European states. Environmental Policy and Governance, 22(6), 381–394. Kingdon, J.  W. (1984). Agendas, alternatives, and public policies (Vol. 45). Little, Brown. Krehbiel, K. (1990). Are congressional committees composed of preference outliers? American Political Science Review, 84(1), 149–163. Liu, X., Lindquist, E., Vedlitz, A., & Vincent, K. (2010). Understanding local policymaking: Policy elites’ perceptions of local agenda setting and alternative policy selection. The Policy Studies Journal, 38(1), 69–91. Marschall, M., & Shah, P. (2005). Keeping policy churn off the agenda: Urban education and civic capacity. The Policy Studies Journal, 33(2), 161–180. Mossberger, K. (2009). Urban regime analysis. In J. S. Davies & D. L. Imbroscio (Eds.), Theories of urban politics (pp. 40–54). SAGE. Newton, K. (1982). Is small really so beautiful? Is big really so ugly? Size, effectiveness, and democracy in local government. Political Studies, 30(2), 190–206. Panara, C., & Varney, M.  R. (Eds.). (2015). Local government in Europe: The “fourth level” in the EU multi-layered system of governance. Routledge. Peterson, P. (1981). City limits. University of Chicago Press. Pierre, J. (2014). Can urban regimes travel in time and space? Urban regime theory, urban governance theory, and comparative urban politics. Urban Affairs Review, 50(6), 864–889. Putnam, R. (1993). Making democracy work: Civic traditions in modern Italy. Princeton University Press. Riposa, G. (2004). Reinventing paradise: Santa Monica’s sustainable city program. Public Administration Quarterly, 28(1/2), 222–251. Sapotichne, J., Jones, B., & Wolfe, M. (2007). Is urban politics a black hole? Analyzing the boundary between political science and urban politics. Urban Affairs Review, 43(1), 76–106.

1  WHY STUDY LOCAL POLICY AGENDAS 

17

Sapotichne, J., & Jones, B.  D. (2012). Setting city agendas: Power and policy change. In K. Mossberger, S. E. Clarke, & P. John (Eds.), The Oxford handbook of urban politics (pp. 442–467). Oxford University Press. Sapotichne, J., & Smith, J. (2012). Venue shopping and the politics of urban development: Lessons from Chicago and Seattle. Urban Affairs Review, 48(1), 86–110. Schattschneider, E. (1960). The semisovereign people: A realist’s view of democracy in America. Wadsworth Publishing Company. Serritzlew, S., Blom-Hansen, J., & Skjæveland, A. (2010). Portfolio allocation or policy horizons? Determinants of coalition formation in Danish local government. Local Government Studies, 36(6), 843–866. Sheingate, A. D. (2006). Structure and opportunity: Committee jurisdiction and issue attention in Congress. American Journal of Political Science, 50(4), 844–859. Silver, D., Weitzman, B., & Brecher, C. (2002). Setting an agenda for local action: The limits of expert opinion and community voice. Policy Studies Journal, 30(3), 362–378. Steinacker, A. (2001). Prospects for regional governance: Lessons from the Miami abolition vote. Urban Affairs Review, 37(1), 100–118. Stone, C.  N. (1989). Regime politics: Governing Atlanta, 1946–1988. Kansas University Press. Talbert, J. C., Jones, B. D., & Baumgartner, F. R. (1995). Nonlegislative hearings and policy change in Congress. American Journal of Political Science, 39(2), 383–405. Tausanovitch, C., & Warshaw, C. (2014). Representation in municipal government. American Political Science Review, 108(3), 605–641. Thornley, A., Rydin, Y., Scanlon, K., & West, K. (2005). Business privilege and the strategic planning agenda of the great London authority. Urban Studies, 42(11), 1947–1968. Tiebout, C. (1956). A pure theory of local expenditures. Journal of Political Economy, 64(5), 416–424. Treisman, D. (2007). The architecture of government. Cambridge University Press. Trounstine, J. (2010). Representation and accountability in cities. Annual Review of Political Science, 13(1), 407–423. Walker, J. (1977). Setting the agenda in the US Senate: A theory of problem selection. British Journal of Political Science, 7(4), 423–445. Warshaw, C. (2019). Local elections and representation in the United States. Annual Review of Political Science, 22(1), 461–479. Wong, K. K., & Jain, P. (1999). Newspapers as policy actors in urban school systems. Urban Affairs Review, 35(2), 210–246.

CHAPTER 2

How to Study Local Policy Agendas

Our study of local policy agendas relies on a massive dataset of local council agendas in all of the 98 Danish municipalities from 2007 to 2016. In some instances, the data extend back to the year 2000. We have collected more than 250,000 agenda items and classified them by the political issue on which each focuses. Our coding system includes 25 major topics and 189 subtopics covering the gamut of Danish local government activities such as primary schools, elder care, unemployment, park maintenance, and so on. These data allow us to trace political attention precisely and consistently across the 98 local Danish councils. Moreover, we include detailed data on numerous background variables in the 98 local governments such as characteristics of the population and the political system. This offers the opportunity to move the study of policy agendas into the realm of systematic multivariate analysis. In this chapter, we present our data and introduce Danish local government.

Structure of Local Government in Denmark Denmark’s 98 municipalities are potent political units with delegated responsibility in a variety of policy domains. The municipalities have an average population of 57,000 inhabitants (standard deviation is 65,000), and all feature the same basic political institutions and electoral system. A

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 P. B. Mortensen et al., Explaining Local Policy Agendas, Comparative Studies of Political Agendas, https://doi.org/10.1007/978-3-030-90932-1_2

19

20 

P. B. MORTENSEN ET AL.

council with an average of 25–27 members governs each municipality, with its members organized into standing committees. A coalition comprising a majority of council seats elects a mayor to a four-year term. The mayor chairs the council and is automatically the chair of the powerful committee on economic affairs, which oversees local financial and administrative matters. Council sizes vary from 9 in the least populated municipality to 55  in the capital and largest municipality of Copenhagen. On average, each council operates four to six standing committees—though in the years our data cover, the smallest had only three standing committees and the largest had 15. Local council elections take place on a fixed schedule every fourth year through proportional representation using a d’Hondt allocation method with open or semi-closed lists in multi-­ member districts and with no formal minimum vote thresholds (Kjaer & Elklit, 2014, pp. 161–162). Voter turnout is generally high—averaging 72 percent—and councils regularly include representatives of seven or more parties. Figure 2.1 shows the distribution of council size, number of committees, and effective number of parties across Denmark and suggests that there are no obvious geographical clusters. Between 2007 and 2016, local elections took place in 2009 and 2013. As a sign of the level of local political competition for office, 48 of the 98 municipalities saw a center-left mayor replace a center-right one or vice versa in at least one of these two election cycles. This also means that a mayor from the same political bloc remained in power throughout this period in 50 of the 98 municipalities. In the 2009–2013 electoral term,

Fig. 2.1  Average political and institutional indicators across Danish municipalities, 2007–2016 Note: This figure shows a map of Denmark divided into the 98 municipalities. Municipalities are colored based on their measured average value of the respective indicator over the ten years our data cover

2  HOW TO STUDY LOCAL POLICY AGENDAS 

21

most mayors came from the center-right political bloc, but across the full sample, the average municipality is governed by a center-left mayor. Hence, there is considerable variation in the partisan composition of the local councils. We go into more detail on the councils’ party compositions in Chap. 6. Common to all 98 municipalities is that they exercise wide local autonomy across a range of important policy areas (Kjaer & Elklit, 2014, p. 161). The Danish municipalities are multipurpose political units, delivering most of the extensive welfare services for Danish citizens. They have considerable policy responsibilities, subject to national legislation and regulation, in areas such as care for the disabled and elderly, pre-school child care, schools, unemployment assistance, job training and placement, public housing, road and park maintenance, environmental regulation and inspection, social policy financing and administration, integration of immigrants with regard to housing and labor market participation, firefighting, utilities and garbage collection, local public transportation, libraries, arts, and recreation. About 50 percent of total public spending in Denmark is allocated at the local level (Boadway & Shah, 2009), and local taxes account for around 75 percent of municipal finances, with the remainder covered mainly by block grants from the central government. In 2019, the municipal income taxes set by the local councils ranged between 21.7 and 27.5 percent across municipalities, and the average income tax across all municipalities was 24.9 percent (www.noegletal.dk). Local council members normally maintain their private employment and spend about 18 hours per week working in local politics for an average annual remuneration of EUR 26,000 (Pedersen et al., 2013). The mayor is typically the only politician employed full time by the municipality.1 To assist the elected political leaders, each municipality has its own sizeable and professional local administration averaging more than 700 employees (calculated based on www.noegletal.dk). All municipalities use a form of committee government in which the local council’s standing committees—composed of local council members—oversee daily administration in their respective jurisdictions (Baekgaard, 2011). Apart from a mandatory committee on economic affairs that oversees the budget and coordinates across the other committees, each municipality is free to set up its own committee system. Changes 1  The only exceptions are found in the biggest Danish municipalities where there are a few other full-time positions for elected politicians.

22 

P. B. MORTENSEN ET AL.

to the committee system typically occur when a new council is seated following elections, which means that the number of committees also varies within municipalities over time (see Table  2.1). These committees are “standing” in the sense that they are set up permanently by the council— at least until the next election—to administer and oversee the policy area(s) under their jurisdiction. Municipalities can also set up temporary, ad hoc committees to deal with particular issues. In addition to the variation in the number of standing committees, there is great variation in committee jurisdictions. Some municipalities might have a single joint committee for labor and welfare, while others have one for labor and another for welfare. We explore this and its implications for the local policy agenda in Chap. 4. At public council meetings, which typically occur once or twice monthly, the local council plenary makes final decisions. The mayor usually prepares the council agenda together with the city manager (the top civil servant and director of the local administration), taking inputs from committee chairs and council members. Council meetings typically last between two and three hours, and on average, councils address about 25 items on each meeting agenda. The municipalities vary considerably in their socio-economic and demographic composition. A crucial advantage of studying the 98 Danish municipalities is that they offer access to granular data on this Table 2.1  Council politics, summary statistics, 98 Danish municipalities, 2007–2016 Variable Population Area (km2) Vote for center-left parties (%)

Local councilors

Number of standing committees

Overall Overall Overall Between Within Overall Between Within Overall Between Within

N

Mean

SD

Min.

Max.

980 980 980 98 10 980 98 10 980 98 10

56,843 360.9 45.5

64,464 371 12.5 11.8 2.1 6.0 6.0 0.3 1.6 1.4 0.2

1795 8 14.0 17.7 42.7 9 9 24.9 3 3 6.7

591,481 1488.8 77.8 76.4 47.6 55 55 25.7 15 11.5 7.0

25.3

6.8

Note: N = 98 (municipalities) × 10 (years) = 980 observations. “Between” summarizes the data averaging each municipality over time. “Within” summarizes the data averaging each year over municipalities. SD = standard deviation

2  HOW TO STUDY LOCAL POLICY AGENDAS 

23

composition. We have data on the crime rate, the unemployment rate, the immigration rate, the number of single parents, the proportion of retired persons, the number of children in need of day care, the number of elementary school pupils, and so on. Throughout the book, we utilize in various ways this rich source of local register data.

Coding the Local Policy Agenda The local council agenda refers to the docket of items the local council addresses during a meeting. Debates on most items end with a decision that may or may not lead to new local regulation or to reallocations of local public spending. No nationally defined institutional rules set local council agendas; each council puts together its own meeting agendas. National-level regulation may require that some issues—such as an annual local school performance report—are placed on the council agendas, but this is the exception and it affects all municipalities equally, meaning that it cannot account for the agenda variation we study. From the homepages of each municipality, we collected the text of each agenda point on the docket for every local council meeting between 2007, or as far back as available, and 2016—in total, more than 250,000 agenda items. The comprehensive reform of local government in 2007 involving large-scale municipal mergers prevents an extension of the time series further back in time. We then coded the topic of each agenda point. To do so, we applied an adapted version of the issue-coding scheme of the Comparative Agendas Project (CAP) to categorize the issue content of each item on the agenda. The CAP codebook applies topic codes to agenda items at the national level of government, and therefore, it includes a number of categories that are not relevant at the local level, such as foreign affairs and defense. At the same time, the national-level CAP codebook groups together certain policy areas that we must treat as distinct policy areas at the local level, such as day care, primary schools, and secondary schools. We preserved the basic structure of the CAP codebook, and where necessary, we subdivided select coding categories in the codebook to harmonize them with the powers and responsibilities of local governments. This produced a local-­ level policy agenda codebook with 189 distinct subtopics. Each subtopic is re-grouped into one of 25 major topics. Table 2.3 illustrates the codebook with an excerpt. The Appendix A contains a full list of topics.

24 

P. B. MORTENSEN ET AL.

Table 2.2  An example of a local council meeting agenda Agenda item    1. Future sex education—following a recommendation from the city council on children and youth   2.  Sale of workshop, Tomsagervej 23, 8230 Åbyhøj   3. Enquiry from the Liberals’ city council group to the Mayor’s Department about policies for visitors in Aarhus    4.  Heating plan Aarhus, future organization    5.  Final approval of LP 913, center area in Lystrup   6.  Final approval of District Plan 915, business in Skødstrup    7.  Final approval of LP 929, business park in Harlev   8.  Making permanent 9 temporary culture grants   9. Reduction of the waiting list for residential accommodation for handicapped adults  10.  Quota plan for public housing 2012–2015  11.  Continuation of parts of the measures in the Homeless Plan  12.  Health and Care’s Housing Plan—stage 1  13.  Health and Care’s Housing Plan—stage 2  14. Fifty-two residential care facilities with service area by community support center, Sandkåsvej 1, 8210 Aarhus V  15.  Restoration of Courtyard 345, Trøjborg—addition to decision  16.  Implementation of musical political initiatives  17.  Activities and partnerships in the Multimedia House  18.  Population figures and investments in leisure and sports Note: This is the (translated) agenda of the local council meeting in Aarhus on August 29, 2012

To give an example of a local council agenda, Table  2.2 reports the agenda for the council meeting in Aarhus on August 29, 2012, in which there were 18 items to discuss. The council discussed many different topics during the meeting. On the agenda is a plan for homeless persons, the construction of residential care facilities, and the sex education curriculum in  local secondary schools, to highlight just a few of the items on the agenda. Moreover, the council debated both large-scale plans such as the future heating plan for the entire municipality and quite specific questions such as the sale of a specific workshop. Despite the diversity in issue attention that we see in this meeting agenda, we also see here a general characteristic of local council agendas: housing and property issues (subtopics 1400–1499)—both broad and specific—are major points of discussion, especially in the larger municipalities (see Chap. 3). The coding scheme addresses attention only, leaving aside both the tone of the debate relating to the agenda items and any decisions taken or not taken. This focuses our measurement on the concept of the local

2  HOW TO STUDY LOCAL POLICY AGENDAS 

25

policy agenda: the set of issues explicitly up for serious consideration by local policymakers. Each item on the agenda is assigned to a single subtopic code. Subtopics are relatively specific categorizations, like “maternity leave” or “higher education.” These we subsequently group into major topics, largely as a way of providing an overview of attention to related groups of subtopics. Major topics, in the local agendas codebook, are broad and cover classic groupings of policy issues such as transportation, the environment, the labor market, and so on. Table 2.3 provides an excerpt of our grouping of subtopics into major topics to illustrate. The column to the left-hand side of the table lists all 25 major topics, mapping three of them to their underlying subtopics listed in the right-hand column. The complete list of topics and subtopics is listed in the Appendix A of this book. A useful feature of adapting our coding system from the nationallevel CAP coding system is that its topics retain comparability to national-level agendas data. Some of the categories, especially “Defense, international relations, and EU,” are obviously not very relevant when coding local policy agendas and therefore required a small number of subtopics, relative to the national-level codebook, to fill out these categories. We have expanded on the subtopics within other major categories in order to get a detailed view of the policy agenda in areas central to local politics. The coding scheme aims to capture the issue content of the measures discussed in the agenda items coded. When aggregated over time, such as across meetings or over entire years, this coding scheme provides a measure of the proportion of attention to distinct policy issues on the various policy agendas in our data. Policy issues are an organizing structure for politics—an observed feature of politics in the real world, rather than an invention of the CAP coding scheme (see Jones, 2016). Standing committees in legislatures are typically organized around policy issues such as education, labor market, health care, or the environment; indeed, we see these aggregations reflected in the names of local council committees in our sample of municipalities (see Chap. 4). At the national level, ministerial portfolios also resemble broad policy issues such as education, agriculture, or defense. Political parties typically have spokespersons for such broad policy areas, and so on. That said, there is no single definitive explanation for why we end up constructing 25 major topics instead of the 21 major topics constructed in the CAP codebook. This flexibility is a major advantage of the issue-­coding

26 

P. B. MORTENSEN ET AL.

Table 2.3  Overview of the major topics and an example of the subtopics within each major topic Major categories

Subtopics (selected)

1: Local economy 2: Civil rights and personal freedom 3: The Danish National Church 4: Refugees and immigrants 5: Health 6: Agriculture, fishery, and food 7: Labor market 8: Education 9: Culture and sports 10: Environment 11: Energy and utilities 12: Traffic issues 13: Law and crime

8: Education 600 General questions (education) 601 Higher education 604 Vocational training and production schools 606 Special education for young people with learning disabilities 610 The public school (including after-school care) 611 Private and free schools 612 High school, higher commercial examination (HHX), higher technical examination (HTX), higher preparatory examination (HF) 613 10th grade, continuation schools, youth clubs 699 Other questions (education)

14: Social and family issues 15: Child care and youth politics 16: Elder care 17: Housing and planning issues 18: Business and tourism 19: Disaster relief 20: Defense, international relations, and EU 21: Research, technology, and communication 22: Central–local relations 23: Local government administration 24: Local council politics 25: Public land and water resources

14: Social and family issues 1208 Family questions 1300 General questions (social policy) 1302 Welfare benefits/social benefits, poverty reduction 1304 Aid for disabled persons, disability policy 1305 Voluntary social work 1308 Maternity leave 1316 The specialized field of social work 1399 Other questions (social policy) 1410 Housing for disabled 17: Housing and planning issues 1400 General questions (housing) 1401 Housing in urban areas 1404 Housing in rural areas 1406 Housing for low-income groups, such as social housing 1409 Homeless people 1411 The market for homeowners (e.g. property taxation) 1412 Planning questions, including district plans, master plans 1413 Purchase and sale of property 1499 Other questions (housing)

Note: The construction of major topics is explained in Appendix B to this book. The codebook defines subtopics, which are the fundamental coding scheme. Major topics are produced by grouping together sets of subtopics. As such, major topics can be redefined at will to suit the researcher’s purposes. The major topics we define are consistent throughout this book

2  HOW TO STUDY LOCAL POLICY AGENDAS 

27

measurement system, and the goal behind the major topics we present is to get close to the idea of the broad “policy issues” that play an important role in the organization of politics in the empirical setting chosen for this book.

Acquiring the Data In terms of data availability, the large amalgamation reform in 2007 marked a watershed moment in Danish local government. Denmark’s 271 pre-reform municipalities were reconfigured into only 98 post-reform municipalities. The reform meant that for most municipalities, digitized archives of pre-2007 meeting agendas were lost. However, for the period after 2007, we have been able to retrieve online almost every local council agenda from all 9363 council meetings until the start of 2017. When agenda information was not available online, we received the data by contacting the municipality directly to request the missing data. In addition, a number of municipalities have maintained physical agenda archives back to 2000 and in some instances even all the way back to the early 1990s, including agendas from municipalities that were amalgamated and ceased to exist in 2007. We were able to retrieve agenda data from 23 pre-2007 municipalities by visiting the municipalities in person to access their physical archive and photocopy each meeting agenda. In this way, we collected data for an additional 4539 meetings in total. We paid a local Danish company to manually transcribe the photocopied documents into machine-readable data. In addition to these two council agenda datasets, we have collected every committee meeting agenda between 2007 and 2016—8392  in total—for 15 municipalities. Although it only covers 15 municipalities, this is a massive data collection effort since every municipality has multiple committees, each with their own meeting agendas, and the dataset therefore covers 149,371 agenda items in total. These data are not available in every municipality, but our data offer a unique window into understanding committee dynamics at the local level in 15 of the 98 municipalities. We use this dataset to analyze the relationship between committee structures and committee and council agendas in Chap. 4. For our analysis, we rely primarily on these three different datasets (see Table  2.4 for an overview). Our main dataset covers 250,354 agenda items for the 98 municipalities from 2007 to 2016. Our second dataset contains 70,032 agenda items from 23 municipalities before 2007, with

28 

P. B. MORTENSEN ET AL.

Table 2.4  Agenda datasets Years

Venue

Units

Meetings (total number)

Agenda items (total number)

2007–2016

Council Committees Council

98 15 23

9363 8392 2241

250,354 149,371 37,362

2000–2006

some of these time series extending as far back as 1990. We use our main dataset in every analysis in Chaps. 3, 4, 5, and 6, and we use the longer time series in Chap. 3. Following elections, local councils typically hold a larger-than-usual meeting at which the city council organizes its committees and allocates seats on them. Instead of addressing policy questions, these meetings address how the local council will organize itself, and the agendas for these meetings are markedly broader than normal meetings. For this reason, we exclude all these constituting meetings from the analyses reported in this book. Thus, the number of meetings and agenda points in our data for analysis, reported in Table  2.4, are slightly smaller than the number of meetings and agenda points that actually took place.

Applying the Coding Scheme Trained student coders, in combination with supervised machine learning for classification, assigned one of the 189 subtopic codes to each agenda item in the data. We applied machine-learning tools to both boost the efficiency of the coding process and improve its final accuracy. The procedure began with student coders who applied subtopic labels to an initial dataset of 25,000 agenda items randomly selected from the data. With these coded data in hand, we turned to the old and well-understood supervised classification algorithm Naïve Bayes to get computer-generated predictions for the correct subtopics of all the remaining data. At this point, the data coding was a months-long process of alternating between human coders and the machine-learning algorithm. Student coders corrected random selections of predictions from the algorithm to check its accuracy. Then, we added the newly corrected data to the training data, ran the algorithm again, and predicted subtopics for the entire dataset. When the accuracy of the computer-generated coding converged to a performance level better than our intercoder reliability scores for human

2  HOW TO STUDY LOCAL POLICY AGENDAS 

29

coders, we considered the process complete and built our final dataset by combining our human-coded training data with the remainder of our collected data labeled by the final trained algorithm. Around 83,000 council agenda items, roughly a third of the main data, were coded solely using automated tools. All committee agenda items were coded automatically and checked to ensure that accuracy was comparable with the council agendas data. To check the accuracy of the machine-coded committee agenda items, we randomly sampled several hundred items for review and correction by human coders. These checks confirmed that the accuracy of the automated tools on the committee agendas was comparable to the accuracy we achieved in the council agendas data. This process worked well because supervised classification algorithms for text require training data of the type the student coders produced: the text of many agenda items paired with their correct subtopic labels. The Naïve Bayes algorithm is a simple calculation based on the conditional probability law known as Bayes Rule. It states that the conditional probability of two outcomes—say, outcome A conditional on outcome B—is equal to the conditional probability of B given A, multiplied by the probability of A and then divided by the probability of B. Formally, this is: P ( A|B ) =

P ( B|A ) P ( A ) P ( B)



Replace A and B with subtopic and word, and the logic behind the algorithm becomes apparent. Based on the training data, the algorithm learned the relative frequency of each word and subtopic, across all of the data—that is, P(word) and P(subtopic). The target, then, was to estimate the probability that a given agenda item belonged to a given subtopic, conditional on seeing a particular word in that agenda item, that is, P(subtopic|word). Loftis and Mortensen (2020) lay out the details of our implementation of Naïve Bayes, namely how it simultaneously calculates these probabilities for all words in the data and all subtopics and then derives the probability that each agenda item falls into each category. As with any machine-learning task, there is a nearly endless number of different algorithms one can apply to a problem. We selected Naïve Bayes for three reasons: 1. It is cheap in terms of computing power. We could make predictions on our dataset of hundreds of thousands of agenda items in a few seconds on a laptop computer.

30 

P. B. MORTENSEN ET AL.

2. It is reasonably well suited for our task. Agenda items are all relatively short sentences, so the words in a text clearly indicate its topic (cf. Table 2.2). Furthermore, attention to political issues is extremely imbalanced. Many algorithms work best with longer texts (i.e. more data), and their predictions can go awry when classifying data into categories that range from extremely common to extremely uncommon. Naïve Bayes is relatively unsophisticated, but it is highly robust to these particular data limitations. 3. Finally, Naïve Bayes is completely transparent. One can inspect and interpret all the intermediary steps and estimates that go into producing the model’s predictions. This allowed us to understand what the algorithm was “learning” from our data and to improve the quality of our training data with input from human experts. Our final computer-generated predictions achieved accuracy rates over 80 percent, which we verified with a final check from student coders. Naturally, this also implies that our computer classifications suffer from a nearly 20 percent error rate. However, the bar for success is set by the best alternative. In our case, we asked student coders to apply one of 189 policy subtopics to thousands of sentences. We estimated that well-trained student coders generally achieved intercoder reliability rates—the common standard for accuracy of human coding—under 80 percent. Our computer accuracy rate was at least as good as human performance, and when applied to national-level data, our model performed at a level comparable to other algorithms (see Loftis & Mortensen, 2020). Furthermore, the errors produced by computer predictions were largely confined to distinguishing between similar categories and identifying the rarest subtopics in the data. For the most frequent subtopics in our data, computer performance was nearly perfect.

Measures of the Council Agenda From the raw, coded agendas data, we can create various measures of relevance to the study of policy agendas. Throughout the book, we utilize several measures of policy agendas familiar from national-level research on policy agendas. The measures capture (1) the issue content of the local policy agenda, (2) the scope or size of the local policy agenda, and (3) the complexity of the local policy agenda. In addition, we construct a measure of agenda stability introduced and explained in Chap. 6.

2  HOW TO STUDY LOCAL POLICY AGENDAS 

31

Measuring the Issue Content of the Local Policy Agenda A much-used measure in the agendas literature is the proportion of individual agenda items dedicated to a particular policy area over a period of time—typically one calendar year in our analyses. The agenda may grow or contract somewhat in the longer run in terms of the number of items or subtopics on the agenda. In the short to medium term, however, the question is not how large the agenda is but which issues are on the agenda at the expense of other issues (Baumgartner et al., 2011). Therefore, attention to an issue is usually measured in relative terms—that is, percentages—instead of absolute terms, and most analyses focus on developments in the allocation of relative attention to specific issues over time (see, e.g., Baumgartner & Jones, 1993; Green-Pedersen & Walgrave, 2014; John et al., 2013). This is a central part of characterizing the agenda. Figure 2.2 shows the relative distribution of attention to each of the 25 major topics in our codebook across the 98 municipalities and over time.

Fig. 2.2  Attention to each major topic (pct.) in the 98 Danish municipalities, 2007–2016 Note: The attention is the average over municipalities and years

32 

P. B. MORTENSEN ET AL.

Overall, municipalities are primarily preoccupied with debating a handful of issues. Housing is by far the issue receiving the most attention—drawing, on average, about 17–18 percent of local council attention. Council issues, the environment, and the economy draw about 10 percent, whereas education, culture, local administration, and traffic take up 6–8 percent of council attention. The remaining 11 major topics take up less than 5 percent of agendas, on average, in any given year and sometimes do not appear at all. Not surprisingly, the national issues of defense, agriculture, research, and the state church take up only very limited attention in the local councils. Figure 2.3 reveals considerable variation in attention to each of the four issues that receives the most council attention across the 98 municipalities and over time. The attention to housing can vary from little more than 5 percent up to 30 percent across municipalities. Attention to the economy, environment, and education are more evenly spread, with variation

Fig. 2.3  Attention to four issues (pct.) over time in the 98 Danish municipalities, 2007–2016 Note: Boxplot shows the distribution of attention to four major topics across municipalities and over time

2  HOW TO STUDY LOCAL POLICY AGENDAS 

33

between 5 and 12 percent in the large majority of municipalities. Average attention to housing has fluctuated a bit over time from about 18 percent in 2007 down to 15 percent in 2011–2013 and rising up to nearly 20 percent by 2016. Attention to the economy has risen on average from about 7 percent to 10 percent. Attention to education has declined from about 8 percent down to 5 percent. In contrast, attention to the environment has been bumping a bit up and down at about 8 percent. These patterns speak to the vibrancy of local policy agendas and their ample variation both across municipalities and over time. It is the aim of Chaps. 3, 4, 5, and 6 to provide some explanations for such variation in issue attention. In Fig. 2.4, we further break down the issue variation in council agendas by comparing the patterns across two individual municipalities, the

Fig. 2.4  Attention differences by issue (pct. points) in two neighboring Danish municipalities, 2007–2016 Note: Differences in attention are calculated by, respectively, subtracting attention to each major topic in Norddjurs from attention to the same topic in Syddjurs. Differences on the horizontal axis are in terms of percentage points

34 

P. B. MORTENSEN ET AL.

municipalities of Syddjurs and Norddjurs. Syddjurs and Norddjurs are located adjacent to one another on the eastern coast of the Central Denmark Region. They are of similar size and have a very similar political organization. Nevertheless, they have strikingly different council agendas, as shown in Fig. 2.4. Figure 2.4 shows the agenda differences between Syddjurs and Norddjurs in terms of the difference in the proportion of agenda space allocated to each major topic. There is marked variation. Although Syddjurs and Norddjurs are otherwise quite similar, council politics and the economy receive 4 percentage points more attention in Syddjurs than Norddjurs—a large difference given the statistics plotted in Fig. 2.4. At the same time, the issues of traffic and education receive greater than 3 percentage points less attention in Syddjurs relative to Norddjurs. In the center of the figure, with hardly any differences at all, the issues that receive the most (housing, in particular) and the least (defense, labor, and immigration) attention across all municipalities are located. Hence, the two municipalities have a markedly different issue composition in their council agendas, the type of variation that calls for further explanation. Measure of Agenda Size To measure the upper limits of the total attention of the council, we look at the agenda size. Some councils simply manage to process more items on their local council agenda. With greater overall attention to allocate, these municipalities can process more issues or get deeper into an issue by debating many items concerned with the same topic. With this in mind, we measure the size of local agendas by counting the total number of agenda items a municipality addresses over the course of a year. This can also tell us if the agenda is contracting or expanding over time (e.g. McCombs & Zhu, 1995). Our measurement of size ignores which subtopics these agenda items address. As mentioned, the upper size of the agenda may only change very slowly, and the change we observe in the data between 2007 and 2016 may, therefore, be modest. Yet, size may differ substantially across municipalities, and our cross-sectional data allow us to analyze this variation. Several authors (e.g. Baumgartner & Jones, 2015; GreenPedersen, 2007) use a size measure to characterize the development of policy agendas since World War II in Western countries, but no one has compared the size of the policy agenda systematically across political systems (though see Mortensen & Seeberg, 2016).

2  HOW TO STUDY LOCAL POLICY AGENDAS 

35

On average, our 98 Danish municipalities process 260 agenda points per year from 2007 to 2016. With about ten meetings per year, this means the average local council meeting covers around 25 agenda items. As displayed in Fig. 2.5, this average summarizes considerable variation across municipalities. The standard deviation in agenda size is around 90 items and the minimum observed size per year is 67 items, compared to a maximum of 790. There is, in fact, also variation in agenda size over time in our sample, as also visible from the boxplot in Fig. 2.5. We see a bumpy decline from almost 300 items per year on average at its highest in 2007 to close to 200 on average in 2016 at its lowest point. Although many policy agenda scholars do not explicitly claim that the size of policy agendas is fixed, it seems fair to conclude that this aspect of policy agendas has largely been ignored in the literature on policy agendas (though see Jones et al., 2019). Furthermore, the variation in agenda size is a particularly intriguing observation given that the Danish municipalities are so similar in many aspects. Despite these similarities, some municipalities are managed with fewer than 100 items on the council agendas a

Fig. 2.5  The number of agenda points in the 98 Danish municipalities, 2007–2016 Note: Boxplot shows the distribution of agenda points across municipalities (average over municipalities) and their development over time

36 

P. B. MORTENSEN ET AL.

year, whereas the council agendas in other municipalities sum to more than 500 items per year (see also Mortensen & Seeberg, 2016). Measures of Complexity Complexity is concerned with the number of subtopics on the agenda at any given point in time. The more subtopics discussed, the more complex the local policy agenda since it touches on a greater range of policy questions. Hence, we measure complexity as the number of subtopics appearing at least once on a local council agenda over the course of the year. This subtopic measure is intuitive and therefore attractive, but it does not tell us how local councils allocate attention among these topics. Some agendas cover many issues but concentrate on only a few, while others allocate attention relatively evenly to the different issues they cover. The entropy measure, developed in communication research, operationalizes this diversity of attention to different items on the agenda. The entropy score is used in an increasing number of national-level policy agenda studies to understand the degree to which attention is allocated in a concentrated or diffuse way across policy issues (e.g. Baekgaard et  al., 2018; Baumgartner & Jones, 2015; Boydstun, 2013; Jennings et al., 2011). There are several ways to calculate the entropy score, and Boydstun et al. (2014) argue that Shannon’s H is the most appropriate for agenda studies because it minimizes the dangers of spurious findings that could result from the less sensitive Herfindahl measures. Shannon’s H is calculated by multiplying the proportion of the agenda each topic receives by the natural log of that proportion, then taking the negative sum of those products: H = −∑ p ( xi ) ln ( p ( xi ) ) i

Here, xi represents topic i, and p(xi) is the proportion of the total attention the item receives, and ln(p(xi)) is the natural log of the proportion of attention the item receives. If one issue receives all the attention, then Shannon’s H takes the value zero, and the score increases as the spread of attention across all topics becomes more equal (Boydstun et  al., 2014). Hence, a higher entropy score indicates a more complex agenda—that is, one that allocates attention more evenly over the different issues appearing on the agenda. We need the two measures of agenda complexity together because they complement each other and ensure a more complete understanding of

2  HOW TO STUDY LOCAL POLICY AGENDAS 

37

Table 2.5  Summary statistics of the agenda measures in the 98 Danish municipalities, 2007–2016 Variable Agenda points

Subtopics

Entropy (Shannon’s H)

Overall Between Within Overall Between Within Overall Between Within

N

Mean

SD

Min.

Max.

980 98 10 980 98 10 980 98 10

260.8

90.4 77.2 21.8 11.7 8.9 5.5 0.23 0.14 0.03

67 135.4 234.2 29 40.2 55.6 2.2 3.3 3.6

790 614.0 296.7 110 93.1 72.6 4.3 4.1 3.7

65.0

3.7

Note: N = 98 (municipalities) × 10 (years) = 980 observations. “Between” summarizes the data averaging each municipality over time. “Within” summarizes the data averaging each year over municipalities. SD = standard deviation

agenda complexity. The subtopic count is a transparent, simple, and intuitive way to get an impression of the agenda. Yet, it does not reveal how attention is divided across subtopics, which makes the entropy score attractive. Table 2.5 summarizes key descriptive statistics of the agenda measures introduced and discussed in this chapter. On average, each Danish municipality attends to about 65 different subtopics out of the 189 in the codebook every year. This has a relatively low standard deviation of only 12 subtopics. Although counting subtopics ignores which subtopics municipalities attend to, there is surprising similarity in the number of subtopics that appear on a local agenda in the course of a year. The average entropy score across the 98 Danish municipalities over 2007–2016 is 3.7 with a standard deviation of only 0.2. This number is not far from the entropy score that previous studies find for the spread of attention on national policy agendas in several countries (Boydstun et al., 2014; Jennings et al., 2011). It indicates quite a considerable spread of attention across subtopics.

A Local Policy Agenda The analyses of this book rest on the assumption that our units of analysis are independent. Hence, to uphold this assumption, we demonstrate that despite Danish municipalities’ many similarities, local council agendas are

38 

P. B. MORTENSEN ET AL.

distinct from one another. We base this conclusion on an examination of the degree of similarity in municipalities’ individual policy agendas. In particular, we applied clustering algorithms (k-means with varying numbers of clusters, x-means, and hierarchical Ward clustering, using a variety of distance metrics) to identify similar groups of municipalities or municipality-­years. The results were universally uninformative and often unstable, shifting markedly with any changes to model hyperparameters. To make sense of these results, consider Fig.  2.6. The figure plots the proportion of variance explained by each component estimated from a principle components analysis of the matrix of local council attention to major topics across municipalities and over time. The relatively flat slope of the line indicates that no component explains greater than 11.1 percent of the variance, showing there is virtually no discernible systematic pattern in municipalities’ annual distribution of attention across issues. We conclude from this that municipal council agendas share no apparent patterns that one could consider a universal local policy agenda for Denmark. This

Fig. 2.6  Proportion of variance explained by components from PCA analysis of governmental attention to all major topics across 98 Danish municipalities, 2007–2016 Note: Horizontal axis plots all principal components estimated from a PCA analysis of the proportion of the local policy agenda dedicated to the 25 major topics in each of the 98 municipalities in each year from 2007 to 2016. Principal components are ordered high to low from left to right according to the proportion of total variance they explain

2  HOW TO STUDY LOCAL POLICY AGENDAS 

39

analysis strongly indicates a lack of any distinctive patterns across all local policy agendas. Nor do we detect any regional or other patterns producing clusters in local policy agendas. This leads us to the conclusion that local governments in Denmark are sufficiently independent to pursue their own priorities and to act independently of one another when setting their policy agendas—validating our assumption that our units of analysis are independent and allowing us to pursue the analyses in this book. We do not argue or claim that their qualitative level of independence is good, bad, or sufficient by any normative standard. These are separate questions, subject to political contestation, and they do not necessarily bear on the question of whether Danish municipalities are an appropriate setting for our research designs. Furthermore, these results cannot be taken as evidence that local policy agendas are not shaped by non-local factors such as decisions made at the national or even EU level of politics. What Fig. 2.6 indicates is that we see sufficient variation in local policy agendas to justify a thorough examination in Chaps. 3, 4, 5, and 6 of the importance of local institutions, local problems, local elections, and local actors.

Summary The data on the local policy agenda in the 98 Danish municipalities is vast, and the descriptive statistics reveal considerable variation across municipalities as well as over time, and even between pairs of otherwise similar municipalities. It is the ambition of the following chapters to try to use our knowledge about key explanatory variables—institutions, elections, problems, and actors—to better understand this variation. This research design, built around studying many homogenous units of analysis (the 98 Danish municipalities) and rich information on many background variables and characteristics of the municipalities, allows us to take the analysis of policy agendas into the uncharted land of doing multivariate analysis of policy agendas data.

40 

P. B. MORTENSEN ET AL.

References Baekgaard, M. (2011). Committee bias in legislatures with a high degree of party cohesion: Evidence from Danish municipalities. European Journal of Political Research, 50(3), 315–335. Baekgaard, M., Mortensen, P. B., & Seeberg, H. (2018). The bureaucracy and the policy agenda. Journal of Public Administration Research and Theory, 28(2), 239–253. Baumgartner, F. R., Brouard, S., Green-Pedersen, C., Jones, B. D., & Walgrave, S. (2011). The dynamics of policy change in comparative perspective. Comparative Political Studies, 44(8), 947–972. Baumgartner, F. R., & Jones, B. (1993). Agendas and instability in American politics. University of Chicago Press. Baumgartner, F. R., & Jones, B. (2015). The politics of information. University of Chicago Press. Boadway, R., & Shah, A. (2009). Fiscal federalism: Principles and practices of multiorder governance. Cambridge University Press. Boydstun, A., Bevan, S., & Thomas, H. (2014). The importance of attention diversity and how to measure it. Policy Studies Journal, 42(2), 173–196. Boydstun, A. E. (2013). Making the news: Politics, the media and agenda setting. University of Chicago Press. Green-Pedersen, C. (2007). The growing importance of issue competition: The changing nature of party competition in Western Europe. Political Studies, 55(4), 608–628. Green-Pedersen, C., & Walgrave, S. (2014). Agenda setting, policies, and political systems: A comparative approach. University of Chicago Press. Jennings, W., Bevan, S., Timmermans, A., Breeman, G., Brouard, S., Bonafont, L., Green-Pedersen, C., John, P., Mortensen, P., & Palau, A. (2011). The effects of core functions of government on the diversity of executive agendas. Comparative Political Studies, 44(8), 1001–1030. John, P., Bertelli, A., Jennings, W., & Bevan, S. (2013). Policy agendas in British politics. Palgrave Macmillan. Jones, B.  D. (2016). The comparative policy agendas projects as measurement systems: Response to Dowding, Hindmoor and Martin. Journal of Public Policy, 36(1), 31–46. Jones, B. D., Theriault, S. M., & Whyman, M. (2019). The great broadening. . How the vast expansion of the policymaking agenda transformed American politics. Chicago University Press. Kjaer, U., & Elklit, J. (2014). The impact of assembly size on representativeness. The Journal of Legislative Studies, 20(2), 156–173.

2  HOW TO STUDY LOCAL POLICY AGENDAS 

41

Loftis, M. W., & Mortensen, P. B. (2020). Collaborating with the machines: A hybrid method for classifying policy documents. Policy Studies Journal, 48(1), 184–206. McCombs, M., & Zhu, J.-H. (1995). Capacity, diversity, and volatility of the public agenda: Trends from 1954 to 1994. Public Opinion Quarterly, 59(4), 495–525. Mortensen, P. B., & Seeberg, H. B. (2016). Why are some policy agendas larger than others? Policy Studies Journal, 44(2), 156–175. Pedersen, L.  H., Houlberg, K., Hansen, S.  W., Olsen, A.  L., & Bordacconi, M. J. (2013). Lokalpolitikeres rolle og råderum. KORA.

CHAPTER 3

Jurisdiction Size and the Local Policy Agenda With contrib. by Søren Serritzlew

Size matters for several aspects of how a democracy works (Almond & Verba, 1963; Dahl & Tufte, 1973; Denters et  al., 2014). Gerring and Veenendaal (2020) examine the effects of size on cohesion, representation, participation, succession, professionalism, power, and even civil conflict and more. At a very basic level, participation in the democratic process is fundamentally different in larger than in smaller jurisdictions (Verba & Nie, 1972; Denters et al., 2014). In large jurisdictions, it requires more coordinated action to get influence, and the political landscape of individual and institutional actors is more complex. The scope of politics is also often broader in larger jurisdictions (Treisman, 2007). Larger jurisdictions can handle more types of policies. For instance, larger units can provide more specialized services and have larger organizations, and therefore, citizens in larger units find democracy more complex. Size is important for heterogeneity (Tiebout, 1956; Newton, 1982). In larger jurisdictions, diversity in socio-economic conditions of citizens is higher (Galasso & Nannicini, 2011), and it is harder to get elected, which again affects the types of representatives. Moreover, size matters for internal political efficacy (Dahl & Tufte, 1973, p. 43). Larger units make politics Søren Serritzlew is a professor at the Department of Political Science, Aarhus University. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 P. B. Mortensen et al., Explaining Local Policy Agendas, Comparative Studies of Political Agendas, https://doi.org/10.1007/978-3-030-90932-1_3

43

44 

P. B. MORTENSEN ET AL.

more complex and simultaneously shrink the power and representation of each individual citizen. As Verba and Nie (1972, p. 231) put it, “in small jurisdictions, it is easier to know the ropes of politics.” Consequently, citizens feel less confident and competent to participate in democracy in larger units (Lassen & Serritzlew, 2011). Dahl (1967, p. 960) sums up the dilemma between small and large units like this: “[F]or most citizens, participation in very large units becomes minimal and in very small units it becomes trivial.” The main takeaway from this ongoing debate is the broad agreement that size is a crucial feature of a polity, with important implications for how a democracy works. Across the arguments is a fundamental, common idea: the political discussion is of a different nature in small and large jurisdictions. In larger jurisdictions, political discussions are more comprehensive, more complex, and involve a larger number of topics and issues. This implies that the policy agenda is different in small and large political systems. This basic implication, however, has never been subject to thorough empirical examination. In this chapter, we examine how the policy agenda is influenced by the size of the political system. Robert Dahl (1967, p. 960), in his APSA presidential address from 1967, speculated about this aspect of politics when he argued that one advantage of larger units is their ability to juggle a larger set of issues of relevance to their citizens. Along similar lines of reasoning, Newton (1982) claimed that the political agenda in larger political units is often characterized by a more diverse and engaging set of topics than in smaller units. By utilizing our council agendas dataset and the measures of agenda size, content, and complexity introduced in Chap. 2, we examine these ideas across our large number of comparable Danish municipalities. Municipality size can be an endogenous variable as the borders may be formed and changed partly in response to the politics of the local area. We address this by using quasi-experimental evidence from a major and sudden municipal reform in Denmark in 2007, which was imposed on 271 municipalities that were merged into 98. The question about the relationship between jurisdiction size and the policy agenda has not been given scholarly attention in policy agenda research. This neglect probably reflects a focus on longitudinal changes in policy agendas, where the more or less constant size of the national political systems prevents an examination of scale effects.

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

45

Why Jurisdiction Size Matters to the Policy Agenda There are strong arguments that the policy agenda changes when democracies grow. As Newton (1982, p. 200) puts it, “large authorities are not just bigger versions of small ones. They develop their own distinctive characteristics, which create qualitative variations between units of different sizes.” Here, we review three classic arguments on heterogeneity, scope, and competition that rest upon this basic idea. First, a classic argument in the literature is that with more people, the heterogeneity in preferences naturally increases (Tiebout, 1956). For example, residents in a newly added neighborhood may be more affluent or younger, and this will enhance politicians’ attention to, for instance, schools, day care, and leisure facilities. Moreover, with a more diverse and larger jurisdiction, politicians may need to spend more time discussing cross-cutting issues such as geographical coherence and planning, urbanization, inequality, infrastructure, and financial management (Newton, 1982, p. 193). Thus, through political representation and mobilization by citizen associations and community groups, the policy agenda will become more heterogeneous because the political space spans a greater variety of concerns and opinions (Newton, 1982, p. 200). Moreover, the heterogeneity may easily force politicians not to debate single cases such as requests from a company in order to avoid neglecting the rest, and therefore, the nature of the political debate changes. For a citizen, the debate no longer just concerns the local community and a problem with the neighbor down the road. An indicator of this is that politicians’ workload increases and their immediate user orientation, that is, motivation to serve individuals in the electorate, drops when amalgamations generate larger constituencies for them to serve (Dahlgaard & Pedersen, 2010). Second, jurisdiction size is related to the scope of tasks that the political system can manage. At the local level, larger municipalities have the capacity and scale to provide more specialized services to cater to special needs in day care, schools, and elderly care (Dahl & Tufte, 1973, p. 38; Treisman, 2007). This requires a higher level of planning, coordination, and infrastructure, and new government agencies may pop up. In general, larger size entails higher complexity (Gerring & Veenendaal, 2020, p. 230). At the same time, it is easy to imagine that such more potent local governments would want to make the jurisdiction an attractive place of settlement by establishing and expanding sports facilities, malls, theaters, museums, and art galleries (Peterson, 1981). To get there and to manage

46 

P. B. MORTENSEN ET AL.

all of these engagements and tasks, politicians will have to spend more time debating the bigger picture and the longer term as well as use the political debate to regularly check in with the new government agencies and the administrative cross-coordination. They will need to spend more time on the principles and less time on every little detail. In large jurisdictions, it is impossible to discuss every single detail. Political discussions must be more general to be tractable. Consider, for example, local political discussions on primary schools, which in many countries is one of the most important tasks of local government. Municipalities with, say, 5000 citizens have perhaps two or three schools, and debates on school policy may often concern a specific school. In large municipalities with dozens of schools, political debates on school policy must have a less specific character (cf. Lassen & Serritzlew, 2011, pp. 239–240). Hence, complexity in the service provision and government organization in larger jurisdictions changes the local policy agenda. Third, jurisdiction size affects political competition. In larger jurisdictions, a larger group of potential politicians compete for relatively fewer seats, increasing the competition for office. All else equal, the most ambitious, experienced, competent, and energetic candidates with the greatest resources will make it (Kjaer et al., 2010). This creates a council of representatives with a strong motivation to get re-elected and who want power and know how to navigate the political system. Such representatives will most likely try to influence and control the agenda (Dahlgaard & Pedersen, 2010; Olsen, 2010, pp. 39–40) since the policy agenda is a central tool for politicians to represent their constituencies (Cobb & Elder, 1972). This can leave a more crowded policy agenda. Common to these arguments is the idea that jurisdiction size affects different dimensions of the policy agenda. We do not claim that this is an exhaustive review of such arguments; the literature on the effects of jurisdiction size is rich and multifaceted. Nor do we attempt to separate or distinguish empirically between different ways in which jurisdiction size matters. Our claim is more modest: the effect of jurisdiction size on the nature of the policy agenda is a fundamental implication of the literature, and this implication has never been subjected to empirical testing. Thus, we cannot take for granted that it is in fact true. The policy agenda may seem to be different in larger jurisdictions, but perhaps it is really just citizens’ perceptions of the agenda that change. From this perspective, changes in the policy agenda in larger units may be illusory. According to Newton (1982, p. 196), governments in larger units “take

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

47

on a monolithic structure and an inhuman face.” Dahl and Tufte (1973, p. 55) have a similar concern because only in smaller units do “citizens tend to believe that their local government is a more human-sized institution, that what it does is more understandable, that it handles questions they can more readily grasp.” Hence, larger units move away from the ideal of a small, face-to-face community consisting of prolonged, first-­ hand political commitment where the councilor can “play darts in the village pub and meet constituents at Sunday church” (Newton, 1982, p. 199). Each politician simply has less time to engage with the citizens on a personal level and to explain what is going on (Dahl, 1967, p. 957), and the local governing unit feels less accessible, less manageable, and less subject to citizens’ control (Dahl & Tufte, 1973, p. 38). Larger democracies may alienate citizens and cut away citizens’ daily encounters with the political system (Lassen & Serritzlew, 2011, p.  238; Bhatti & Hansen, 2019, p. 699). Due to this alienation and lack of translation and guidance in interpreting and digesting the political debate, citizens may struggle more to comprehend the policy agenda even if it has not qualitatively changed much.

Studying Jurisdiction Size and the Policy Agenda Empirically To move the literature forward, it is a critical task to scrutinize empirically the link between jurisdiction size and the relevant dimensions of the policy agenda. To do so, we apply two supplementary research designs in this chapter. One is based on the dataset of local council agendas covering all 98 Danish municipalities in the period 2007–2016. The other is structured over the dataset consisting of a sample of Danish municipalities observed both before and after the major amalgamation reform of 2007. The reform is explained in detail below. The major advantage of this dual research strategy is that it provides both the benefits of a large-n, multivariate analysis and an effective handling of the issue of endogeneity. Using council meeting data, we focus in this chapter on three different aspects of the council meeting agendas that together capture the central implications derived from the review of the literature above. First, we measure the size of the local policy agenda as the total number of items on the council meetings in a year. This is a simple sum over all agenda items considered during all city council meetings over the course of the calendar

48 

P. B. MORTENSEN ET AL.

year.1 These sums serve as a relatively direct measure of the total size of the policy agenda in a municipality—the number of agenda items it covers in a year. As such, there is no predefined upper bound to this count; the greater the number of agenda items discussed in a year, the larger that municipality’s policy agenda. Underlying this tallying of agenda items is the assumption that each new item on the agenda brings up another facet of a problem or an entirely separate problem. However, as argued in Chap. 2, we can get closer at this aspect of the local policy agenda by utilizing our content coding to create measures of the issue complexity of local policy agendas. More particularly, we measure complexity by calculating the total number of subtopics used to code a municipality’s policy agenda in a year and by calculating the entropy of attention to subtopics (Shannon’s H) over a year. The former is a simple sum over the number of subtopics that appear at least once on a council meeting agenda during a calendar year. The coding procedure sorts each agenda item into one of 189 subtopic categories, and we leverage this feature of the coding system and count the number of distinct subtopics that ever appear on the local council agenda over the course of the year. This measure has a natural lower bound at one and a natural upper bound of 189—the total number of subtopics in the codebook. Municipalities addressing more subtopics have a broader policy agenda and therefore a more complex policy agenda. The second indicator of complexity is the entropy of the local policy agenda’s distribution of attention across subtopics. The calculation, Shannon’s H (or Shannon’s diversity index), is a single number summary of the degree to which a discrete distribution—in our case, the distribution of agenda items to subtopics—is concentrated on few categories or diffused across many. For the exact calculation of Shannon’s H, see Chap. 2. Higher values of Shannon’s H indicate that an agenda is more evenly spread across subtopics; thus, it is more diverse or complex since the local council is devoting more equal amounts of its time to the various subtopics on its agenda. Low values of Shannon’s H indicate that the agenda in a local council focuses heavily on one or a few issue subtopics.  Our coding excludes special meetings (see Chap. 2). For example, after each election, local city councils hold a long meeting to allocate committee seats to the newly seated city council. Special meetings like these often have deceptively long agendas including a wide variety of topics, while the actual meetings do not feature discussion of all these policy areas but rather discussions about the organization of the new council. For this reason, special meetings of this variety are excluded from the data. 1

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

49

Fig. 3.1  Geographic variation in measures of agenda size and complexity, 2007–2016

For all three measurements, we anticipate positive relationships with municipalities’ size. Agenda size and complexity will increase in terms of the total number of agenda items, the total number of subtopics addressed, and the evenness of the distribution of attention across subtopics. Figure 3.1 illustrates the variation in our outcome variables averaged over the period 2007–2016. With respect to the measure of jurisdiction size, we adhere to the standard in the literature and focus on the citizens as a measure of size—that is, population size (Gerring & Veenendaal, 2020, p. 25). This is because citizens, not geography, increase the constituency’s preference heterogeneity, the need to provide more specialized services, and the need for coordination and cross-cutting political debates. In the analyses, however, we do include a control for the size of the geographical area covered by a municipality. We refrain from using population density as a measure of size since it is a composite measure that combines population and geography and because we do not have explicit expectations on how population density affects the policy agenda.

Study 1: Jurisdiction Size and the Policy Agenda— Cross-sectional Evidence We begin by examining the link between population size and the local policy agendas in a cross-sectional setting, regressing each measure of agenda size and complexity on the population size of the municipality. In

50 

P. B. MORTENSEN ET AL.

the period from 2007 to 2016, the size of the Danish municipalities varies from about 1800 to just under 600,000 citizens (mean 56,843; standard deviation 64,464). We study the effect of this variation on the approximately 250,000 agenda items that we have archived and coded to measure the local policy agenda of each municipality from 2007 to 2016. Since the size of the jurisdiction is such a basic property of local democracy, the concern with confounding variables should be limited. To show that it is indeed population that matters and not geography or other structural or political features of the municipality, we include controls in our cross-­ sectional analysis for the average square kilometers of the municipality, the partisanship of the mayor, and the socio-economic conditions in the municipality. Since our measure of population size varies extremely little over time, and our measure of geographic size does not vary at all in this period, we collapse all measures to their means over 2007–2016 to avoid inflating our sample size and privileging statistical significance. Mayoral partisanship is measured with an indicator variable taking on a value of 1 during years in which the municipality’s mayor is identified with a left party and 0 otherwise. Averaged over time, this variable varies continuously between 0 and 1 and captures the proportion of years between 2007 and 2016 in which the municipality was governed by a left mayor. Our measure of socio-­ economic conditions is a composite index compiled by the Danish Ministry of the Interior and Social Policy (available at www.noegletal.dk). The index consists of 14 indicators. The same criteria and the same index construction are used throughout the period of analysis. In this way, the index measures the relative general severity of socio-economic problems facing a municipality. If a municipality scores above (below) 1, its socio-economic problems are above (below) average. Averaging this index over time gives the mean socio-economic conditions in the municipality (see also Mortensen & Seeberg, 2016). Our results all point in the same direction. Larger democratic units have more items and subtopics on the council agenda, and the complexity of the agenda is greater. This is visible from the positive and statistically significant coefficients in the upper row of Table  3.1. In each case, the coefficients indicate that a standard deviation increase in logged municipal population is associated with, on average, around half a standard deviation increase in agenda size or complexity—for example, around 40 additional agenda items or an additional four subtopics receiving attention on the council meetings.

−342.15*** (86.58) 98 0.34

56.69*** (8.11)

−344.02*** (86.06) 98 0.35

61.25*** (8.67) −6.14 (4.86) −20.42 (18.73) 82.33** (29.51) −425.41*** (89.97) 98 0.40

60.58*** (8.48) −7.23 (4.90)

0.14 (10.26) 98 0.29

6.10*** (0.96)

0.27 (10.27) 98 0.29

5.82*** (1.01) 0.52 (0.59)

5.89** (1.01) 0.69 (0.56) −2.88 (2.18) 12.40*** (3.43) −11.93 (10.46) 98 0.39

(6)

3.00*** (0.19) 98 0.13

0.07*** (0.02)

(7)

3.00*** (0.19) 98 0.14

0.06** (0.02) −0.01 (0.01)

(8)

0.06** (0.02) 0.02 (0.01) −0.07* (0.04) 0.25*** (0.06) 2.75*** (0.19) 98 0.26

(9)

Agenda complexity (mean)

Note: Standard errors in parentheses. * p < 0.05, ** p < 0.01, *** p < 0.001 (two-sided). The data cover 2007–2016 in the 98 Danish municipalities

Observations R2

Constant

Socio-econ. index

Left party mayor

Area (km2, log)

Inhabitants (log)

(5)

(4)

(3)

(1)

(2)

Subtopics (mean)

Agenda points (mean)

Table 3.1  The effect of jurisdiction size on the local policy agenda 3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

51

52 

P. B. MORTENSEN ET AL.

Fig. 3.2  Predicted values of relationship between jurisdiction size and the local policy agenda Note: Rugs show original data distributions. Lines show predicted relationship between logged municipal population and the respective outcome variable in the indicated models from Table 3.1. Axis labels in natural units. Gray regions are 95% confidence intervals around predictions

Table 3.1 further indicates that population size is the relevant indicator to consider instead of the municipality’s geographical size. In contrast to the consistently statistically significant effect of population size, geographical size shows little relationship to any of the outcome variables we analyze. A further visual examination of the results reinforces these conclusions. We plot in Fig. 3.2 the substantive effects of population size on our outcomes in the form of predictions with confidence intervals from our final models. The content of the policy agenda is also different in larger units. This is visible from Fig. 3.3, which shows the relationships between population size and attention to each of our 25 major issue categories. The major issue categories are constructed by aggregating the 189 subtopics into 25 major categories (see Appendix B). Population size’s relationship to most individual issues is rather small, but we do see systematic statistical relationships between population size and attention to the issues of social and family issues, traffic issues, child care and youth politics, central–local relations, local government administration, health issues, and public land and water resources. Furthermore, three issues stand out as having the most prominent relationships to population size. The local economy and local

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

53

Fig. 3.3  Effect coefficients for population size from seemingly unrelated regression Note: We regress population size on the proportion of attention to each of the 25 major topics. Points are point estimates for the effect of logged population size on the proportion of attention to each category. Horizontal lines are 95% confidence intervals

council administration take up markedly less space on the local policy agenda in larger units, whereas the issue of housing and planning becomes much more important in larger municipalities. The sizes of the estimated relationships between population size and these latter issues are considerable. Taken together, these results indicate that the local policy agenda is qualitatively different in larger units. The agenda in larger units contains more items and more unique issues, and attention is spread more evenly across issues. Although these results suggest some clear conclusions, the cross-sectional data cannot eliminate the possibility of reverse causality in which municipalities that prefer a certain way of debating political issues may opt to merge in order to grow to a larger jurisdiction (that will ensure this type of debate) or avoid such mergers all together. This is incredibly

54 

P. B. MORTENSEN ET AL.

hard, if not impossible, to address in a cross-sectional setting since it requires controlling for factors that make some municipalities develop a preference for a certain size and type of policy agenda. Some of these factors are probably observable, though some are surely not. A way to overcome this inherent challenge is to adopt a research design in which variation in municipal size is exogenously given. Such a quasi-experiment outside the laboratory is very hard to identify. We take advantage of the so-called municipal reform of the Danish municipalities in 2007 that approximates an exogenous source of jurisdiction size, and our analysis therefore turns to the quasi-experimental virtues of our data.

Study 2: Jurisdiction Size and the Local Policy Agenda—Quasi-experimental Evidence In this second set of analyses, we utilize the exogenous variation in jurisdiction size imposed by the major amalgamation reform in 2007. In this reform, the number of municipalities in Denmark was reduced from 271 to 98 by the national government. About one-third of municipalities were unaffected by the reform, making it possible to compare treatment and control groups. Characteristic to quasi-experiments, treatment is not assigned with perfect randomness but rather by a mechanism exogenous to the outcome under study (Blom-Hansen et al., 2015). In our case, the central government selected municipalities for amalgamation based on the non-random criterion of a population-size threshold at 30,000 inhabitants. Since most pre-reform municipalities had fewer than 30,000 inhabitants, they were forced to merge. Due to the reform, the average number of inhabitants increased from roughly 20,000 in 2006 to 56,000 in 2007 (Bhatti & Hansen, 2011, p. 215). Subsequent to setting this threshold, the central government asked the municipalities to indicate by January 1, 2005, with whom among their immediate neighbors they would like to merge. There is ample reason to believe that this process of selecting merger partners played out exogenously to the local policy agenda. Quantitative and case study evidence indicate that municipalities’ choices of merger partners were driven by factors such as commuting patterns, shared local identity, or local politicians’ ambitions for higher office (Bhatti & Hansen, 2011). Thus, we assume that any pre-existing differences between the control and treatment groups’ local policy agendas were exogenous to the choices made

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

55

about the amalgamation process, and thus, treatment effects can be attributed to the amalgamation itself. Moreover, the reform provides a close-to-exogenous allocation of jurisdiction size because observers and scientists describe the process leading up to the reform as unusually short and disclosed. Hence, local politicians had little opportunity to influence the reform. In July 2002, political debate and media attention emerged regarding the question of the structure of local government. The Liberal-Conservative government appointed an expert commission to investigate the need to reform and possible solutions. In the report that arrived in April 2004, the commission suggested several mostly modest reform paths that stakeholders and politicians largely considered non-controversial. The government, however, proposed a much more expansive amalgamation reform in the wake of the committee’s report. This more expansive reform proposal was quickly adopted in Parliament in June 2004 based on a narrow parliamentary majority upheld through votes from the Danish People’s Party (Christiansen & Klitgaard, 2010, pp. 191–192; Bundgaard & Vrangbæk, 2007, p. 509). This analysis was made possible by the fact that a selection of Danish municipalities has maintained physical agenda archives back to 2000. We went to these municipalities to access their physical archive and photocopy each meeting agenda from 2000 until the 2007 reform where digital archives were set up. We then scanned each of these photocopies and paid a local not-for-profit company specialized in employing people with reduced working capacity to transcribe the copies into machine-readable data. Given the massive effort required to obtain these data, this part of the analysis is based on data from 12 post-reform municipalities, 4 of which are new municipalities created by mergers and 8 control municipalities that were not subject to mergers in the 2007 reform. The four treated municipalities—that is, created by mergers in 2007—are amalgamations of 14 pre-reform municipalities.2 These data span the time period from 2000 to 2016—six years before the 2007 reform and ten years after it.

2  Post-reform Billund Kommune combines the pre-reform municipalities of Billund and Grindsted; post-reform Frederikshavn Kommune combines Frederikshavn, Skagen, and Sæby; post-reform Silkeborg Kommune combines Gjern, Kjellerup, Silkeborg, and Them; and post-reform Vejle Kommune combines Børkop, Egtved (excluding one neighborhood), Give, Jelling, Vejle, and one neighborhood from Tørring-Uldum.

56 

P. B. MORTENSEN ET AL.

Fig. 3.4  Population change over time across the sample Note: Vertical dashed line indicates 2007, the year of the amalgamation reform. Treated municipalities have multiple lines to the left of 2007. The horizontal gaps in the line are not breaks in the time series. Rather, data on the pre-reform municipalities end in 2006, and data from the new amalgamated municipalities start in 2007

Since availability of pre-reform agendas data was an issue, we could not select municipalities at will. Yet, the sampled municipalities (both treatment and control) do represent municipalities of varying population size from different parts of the country. Figure  3.4 illustrates population change over time across this sample of municipalities. Note that the treated municipalities experienced dramatic population growth at the moment of the 2007 reform, while the control municipalities experienced almost no or very little population change slowly over the sample period. This sample gives us a total of 260 observations: 135 treated and 125 control with 143 pre-reform observations and 117 post-reform. Table 3.2 cross-tabulates treatment condition by time. This sample size and variation

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

57

Table 3.2  Cross-tab of observations by treatment condition and reform timing 00 01 02 03 04 05 06 Treatment 14 14 14 14 14 14 14 Control 4 5 6 6 8 8 8 Pre-reform

07 08 09 10 11 12 13 14 15 16 4 8

4 8

4 8

4 8

4 8

4 8

4 8

3 8

3 8

3 8

Post-reform

Note: Table shows the number of cases in the treatment and the control group for each year, 2000 to 2016

over treatment and time provide us ample statistical power to detect a range of effect sizes (see statistical power calculations in Appendix D). Our main results estimate a difference-in-difference (DiD) effect, comparing control (unmerged) and treatment (merged) municipalities before and after the 2007 reform. The logic of our main analysis is to isolate the effect of the reform on treated municipalities, independent of any unique features of treated municipalities and any universal impact of the reform or the timing of the reform. We do so by regressing our outcome variables, measuring the size and complexity of the local policy agenda, on a set of indicator variables. An indicator for treated observations takes on a value of 1 for merged municipalities and 0 otherwise. An indicator for time takes on a value of 1 for observations in 2007 or later and 0 otherwise. Finally, the indicator used to estimate the DiD effect is the interaction of these two variables, taking on a 1 in the 37 observations of a treated municipality in the post-reform period (2007 or later) and 0 otherwise. Our main model is thus:

Yi  xi  time  1  xi  treated   2  xi  timetreated   3  

Here, Yi is the value of the outcome variable (policy agenda size or complexity) for observation i, and the xi variables are the indicators discussed above. Our quantity of interest is the estimate of the DiD effect, β3. Subsequent analyses relax these constraints by modeling time in more flexible ways or by introducing additional control variables to probe our assumptions underlying the quasi-experimental research design. Our findings support the argument that the size of democratic units has a sizeable—causal—effect on the size and complexity of the policy agenda. We present these findings in a few steps. In Fig. 3.5, we present our main DiD estimator and then describe several additional analyses conducted to

58 

P. B. MORTENSEN ET AL.

probe the credibility of the assumptions underlying our causal interpretation. Figure 3.5 plots the coefficients from our OLS regression estimation of the effects. If a marker is to the right of the vertical zero-line and does not touch it, the effect is positive and statistically significant. If a marker is to the left of the vertical zero-line and does not touch it, the effect is negative and statistically significant. In Fig. 3.5, the important information is that the marker for the DiD estimate (treatment x time) is visibly and consistently to the right of the vertical dashed line. This indicates a positive and statistically significant agenda effect of merging the municipalities in the 2007 reform: Overnight, they grew markedly bigger, and this caused a marked difference in the policy agenda. It is also noteworthy that the effect coefficient for time (pre

Fig. 3.5  Coefficient estimates from main DiD models Note: Regressions are estimated on data standardized by subtracting the means and dividing by the standard deviations of the outcome variable. This standardization ensures that coefficient effect sizes can be compared within models. Coefficients reflect the expected standard deviation change in the outcome variable conditional on a change in the explanatory variable from 0 to 1

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

59

to post) is virtually zero and not statistically significant—this is the absence of an effect of time when the treatment indicator is zero, that is, the continuity in the control group. Moreover, the coefficient for the effect of treatment is far to the left, indicating that the treated municipalities before the reform (when the time indicator is zero) therefore had systematically fewer agenda items or subtopics on the policy agenda and a lower value of Shannon’s H compared to control municipalities before the reform. Follow-up analyses indicate further support for our argument. Since all municipalities were already aware of and preparing for the impending reform the year before in 2006, it might have been the case that the treated municipalities saw the size and diversity of their agendas shrink as they prepared for their coming amalgamations. However, if we remove all observations from the year before the reform was implemented, all effects remain roughly the same with the same pattern of statistical significance. Similarly, we also checked that the jump in the size and diversity of treated municipalities’ agendas was not concentrated only in the years immediately following the amalgamations (i.e. 2007 and 2008) since this could indicate that the effects we estimate are attributable to the process of amalgamation itself. If amalgamation caused an expanded and diversified policy agenda, it would be difficult to attribute these effects to municipalities’ change in size. To examine this, we reran the analyses, replacing the indicator for time with nine indicator variables, one for every post-­ reform year (2007–2016), each interacted with treatment status. With only 260 observations, these expanded models estimating 22 parameters are less precisely estimated than our main analysis. Nevertheless, in each expanded analysis, we estimate a large and statistically significant difference between treated and control municipalities before the reform, and in every post-reform year, our estimates reveal no difference between treated and control municipalities. Returning to our main analysis, illustrated in Fig. 3.5, we further probe the effects by plotting the predicted values for each outcome variable under each combination of treatment condition and time period. Results are shown in Fig. 3.6. To the left is the change in the policy agenda for the control group from pre-reform to post-reform, and to the right is the treatment group. Note that control municipalities exhibit no statistical difference in policy agenda size or complexity from before to after the reform because the pre to post markers are at similar heights in the figure. Treated municipalities, on the other hand, experience a large increase in their policy agendas’ size and complexity upon their amalgamations in the

Fig. 3.6  Predicted values of outcome variables by treatment condition and time Note: Control group to the left (pre-reform and post-reform) and treatment group to the right (pre-reform and post-reform) on the three outcome variables (top, center, bottom of the figure)

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

61

2007 reform as evident from the jump in the markers to the right in the figure. After the reform, these municipalities’ agendas become comparable to—and in some cases statistically indistinguishable from—the control municipalities. This jump applies to each of our three measures of the policy agenda.

Summary In the course of time, countries, counties, and municipalities change. Due to population growth, the US population has more than tripled during the last century. The European Union has—primarily due to enlargement— multiplied from its establishment by “the inner six” countries until its peak with more than half a billion citizens and 28 members states in 2019 just before Brexit. Since the 1950s, a wave of local government amalgamations has swept developed countries, typically increasing the jurisdiction size dramatically (Denters et al., 2014; Erlingsson & Ödalen, 2013; see also the overview in Blom-Hansen et al., 2016). These dramatic changes in the architecture of government (Treisman, 2007) have consequences for democracy. This argument that jurisdiction size is essential to how a polity works dates back to Plato and Aristotle, and a large literature documents that jurisdiction size affects important aspects such as cohesion, representation, participation, succession, professionalism, power, and civil conflict (Gerring & Veenendaal, 2020). But why is jurisdiction size so important? In this chapter, we have argued that a fundamental, but often tacit, assumption in the literature is that jurisdiction size affects the policy agenda. However, the assumption has never been systematically tested. In this chapter, we have taken the first step to do so. Using our different measures of the policy agenda, we find strong evidence that larger units change the policy agenda. The agenda gets more crowded, gets more diverse, and focuses on different issues. This is an important first hard-evidence-based indication that the policy agenda of the political system visibly changes in larger democracies. With respect to jurisdiction size, the empirical range of national-level jurisdictions is, for most countries, outside the empirical range across the Danish municipalities. That may distort the scale effects found in this chapter. Yet, as argued in a recent book by Gerring and Veenendaal (2020), there is no reason to limit the study of population and politics to decentralized, local political systems. The classic arguments about scale effects tested in this chapter regard political systems as such. What the extension

62 

P. B. MORTENSEN ET AL.

to smaller or larger political systems may add to the analyses is a more precise estimation of the shape of the relationship between jurisdiction size and the policy agenda. In this chapter, we found a relationship that is well approximated by a linear function, but this may change as we move toward more extreme observations on the scale of populations. One might see the findings of this chapter as “democratic complexity costs” of larger jurisdictions. Since jurisdiction size matters for the size, scope, and complexity of the policy agenda, increasing jurisdiction size will impede at least some aspects of democracy. The complexity costs should, of course, be seen in relation to the “democratic scope gains” of larger units. Larger units have the capacity to manage a broader portfolio of tasks. Dahl’s (1967, p.960) dilemma (“… participation in very large units becomes minimal and in very small units it becomes trivial”) seems highly relevant. Regarding the aim of advancing our explanations of policy agendas, the findings of this chapter clearly point out jurisdiction size as an important institutional scope condition that affects several dimensions of the policy agenda. Therefore, it is a variable that clearly deserves to be part of any general explanatory model of policy agendas.

References Almond, G. A., & Verba, S. (1963). The civic culture. Princeton University Press. Bhatti, Y., & Hansen, K.  M. (2011). Who “marries” whom? The influence of societal connectedness, economic and political homogeneity, and population size on jurisdictional consolidations. European Journal of Political Research, 50(2), 212–238. Bhatti, Y., & Hansen, K. M. (2019). Voter turnout and municipal amalgamations: Evidence from Denmark. Local Government Studies, 45(5), 697–723. https:// doi.org/10.1080/03003930.2018.1563540 Blom-Hansen, J., Morton, R., & Serritzlew, S. (2015). Experiments in public management research. International Public Management Journal, 18(2), 151–170. Blom-Hansen, J., Houlberg, K., Serritzlew, S., & Treisman, D. (2016). Jurisdiction size and local government policy expenditure: Assessing the effect of municipal amalgamation. American Political Science Review, 110(4), 812–831. Bundgaard, U., & Vrangbæk, K. (2007). Reform by coincidence? Explaining the policy process of structural reform in Denmark. Scandinavian Political Studies, 30(4), 491–520.

3  JURISDICTION SIZE AND THE LOCAL POLICY AGENDA 

63

Christiansen, P.  M., & Klitgaard, M.  B. (2010). Behind the veil of vagueness: Success and failure in institutional reforms. Journal of Public Policy, 30(2), 183–200. Cobb, R.  W., & Elder, C.  D. (1972). Participation in American politics: The dynamics of agenda-building. Johns Hopkins University Press. Dahl, R. A. (1967). The city in the future of democracy. American Political Science Review, 61(4), 953–970. Dahl, R. A., & Tufte, E. R. (1973). Size and democracy. Stanford University Press. Dahlgaard, J., & Pedersen, L. (2010). Kommunesammenlægningernes betydning for kommunalpolitikernes motivation. Politik, 13(3), 17–27. Denters, B., Goldsmith, M., Ladner, A., Mouritzen, P. E., & Rose, L. E. (2014). Size and local democracy. Edward Elgar. Erlingsson, G., & Ödalen, J. (2013). How should local government be organised? Reflections from a Swedish perspective. Local Government Studies, 39(1), 22–46. Galasso, V., & Nannicini, T. (2011). Competing on good politicians. American Political Science Review, 105(01), 79–99. Gerring, J., & Veenendaal, W. (2020). Population and politics: The impact of scale. Cambridge University Press. Kjaer, U., Hjelmar, U., & Olsen, A. L. (2010). Municipal amalgamations and the democratic functioning of local councils: The case of the Danish 2007 structural reform. Local Government Studies, 36(4), 569–585. Lassen, D., & Serritzlew, S. (2011). Jurisdiction size and local democracy: Evidence on internal political efficacy from large-scale municipal reform. American Political Science Review, 105(2), 238–258. Mortensen, P. B., & Seeberg, H. B. (2016). Why are some policy agendas larger than others? Policy Studies Journal, 44(2), 156–175. Newton, K. (1982). Is small really so beautiful? Is big really so ugly? Size, effectiveness, and democracy in local government. Political Studies, 30(2), 190–206. Olsen, A. (2010). Kommunalreformens konsekvenser: Kommunalpolitikernes rolle, borgernes lokaldemokratiske opfattelse og den administrative organisering. Politik, 13(3), 38–48. https://doi.org/10.7146/politik.v13i3.27457 Peterson, P. (1981). City limits. University of Chicago Press. Tiebout, C. (1956). A pure theory of local expenditures. Journal of Political Economy, 64(5), 416–424. Treisman, D. (2007). The architecture of government. Cambridge University Press. Verba, S., & Nie, N. H. (1972). Participation in America. Harper and Row.

CHAPTER 4

Committee Structure and the Local Policy Agenda

Among political science’s basic questions is how institutions structure and shape politics. Institutions are not neutral. Changing institutional arrangements can alter political choices and outcomes by restructuring access to information, redefining alternative choices, or reallocating decision-­ making power (Krehbiel, 1990; Hammond, 1993; Schattschneider, 1960). Studies of institutions’ effects are also prominent in national-level research on policy agendas. Scholars have studied how friction created by institutions influences patterns of stability and change in various types of policy agendas in several countries (e.g. Jones et al., 2003; Baumgartner et al., 2009) and how institutional differences across countries influence attention to specific policy issues (e.g. Green-Pedersen & Wilkerson, 2006; Green-Pedersen & Walgrave, 2014). A main contribution of policy agenda studies is the demonstration of how a fixed institutional structure facilitates and interacts with processes of change. A series of studies of the US Congress committee system, for instance, has shown how that institutional setup offers a variety of venues that strategic policy entrepreneurs can use to promote new understandings and definitions of certain issues (Baumgartner & Jones, 1993; Jones et al., 1993; Baumgartner et al., 2000; Sheingate, 2006). Policy agendas research has thereby helped provide a much-needed corrective to the view of institutions as stability-inducing features of politics found in much of the new institutionalism scholarship (Baumgartner et al., 2011). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 P. B. Mortensen et al., Explaining Local Policy Agendas, Comparative Studies of Political Agendas, https://doi.org/10.1007/978-3-030-90932-1_4

65

66 

P. B. MORTENSEN ET AL.

Yet, a one-sided focus on change and fluctuations in attention over time—frequently termed agenda dynamics—has left fundamental questions about the structure–agenda link in the dark. There is no reason to believe that institutionally induced biases on the policy agenda only appear in times of change or in issue areas characterized by instability. Rather, there is a strong argument for assuming that institutional structures also exert significant influence on policy agendas in times of relative stability and in issue areas (the most numerous) that are neither subject to redefinition nor to new understandings in the short to medium term. Furthermore, if we are actually to study the effects of institutional structure, we must compare policy agendas across political units with salient institutional differences. The contribution of this chapter is to theorize and study the policy agenda effects of committee structures. Theoretically, we develop a new understanding of committee structure effects that builds on an integration of two important forces of decision-making: parallel processing and the bottleneck of attention. Empirically, we examine a list of different implications that can be derived when these two forces are combined. Our main ambition with the chapter is to advance our understanding of how differences in committee structures over time and across political systems influence elected policymakers’ attention. The Danish municipalities are a fruitful laboratory for examining this question. There is substantial variation in committee structures both within and across municipalities. Thus, unlike earlier policy agenda studies, which predominantly worked with a relatively fixed number of committees in a stable institutional system, we model and study effects of actual variations within and between committee structures in readily comparable political units.

Current Understanding of the Structure– Agenda Link In the 1990s, Baumgartner, Jones, and colleagues provided an alternative to the preference-dominated perspective on the role of committees by putting policy issues at the center of the analysis (Baumgartner & Jones, 1993; Jones et al., 1993; Baumgartner et al., 2000). They showed how the committee system not only structures attention to policy issues but also how those issues are portrayed. They identified a pattern in which different committees in the US Congress clearly vary systematically and

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

67

predictably in the way in which they allocate attention to policy issues. Agricultural committees, for instance, focus on agricultural issues, and when they take up borderline or developing issues, they approach them from a farmer and agriculture industry-friendly perspective. Health or environmental committees, likewise, attend to health and environment-­ related issues, and when they address cross-cutting issues, they do it from a health or environmental perspective (Jones et al., 1993). The main interest and the main contribution of these agenda-setting-­ based committee studies was, however, their focus on the interplay between issue dynamics and the rather fixed committee structure. In this perspective, the congressional committees provide venues where issue entrepreneurs can shop around to find venues that are hospitable to new issues or to a new understanding of existing issues, thereby paving the way for agenda and policy changes. The relevance of the dynamic perspective is illustrated by systematically tracing congressional hearings on the issues of, for instance, pesticides, nuclear power, tobacco, and drug abuse over several decades. The early agenda-setting-based committee studies clearly demonstrate how the change in attention to and redefinition of these issues interacted with the committee structure (Baumgartner & Jones, 1993; Jones et al., 1993). Later work generalized this understanding of the interplay between issue dynamics and the committee structure (Baumgartner et  al., 2000). Focusing on the issue of biotechnology, Sheingate (2006) found similar dynamics. Sheingate sees the committee structure as an “opportunity structure,” and the destiny of an issue depends on its fit with the existing committee structure, that is, the “fit hypothesis.” The careful demonstration of the interaction between the relatively fixed structure of the US congressional committees and the changing understandings of policy issues was a major contribution to research on both agenda setting and congressional committees. Yet, it leaves open more basic questions about the relationship between a given committee structure and the policy agendas of the committees, and between the committee structure and the policy agenda of the assembly as a whole. In the short to medium term, sometimes several decades, most issues do not undergo major changes in definition or in politicians’ understanding of the issue (Baumgartner & Jones, 1993). Yet, attention to those issues may still be strongly influenced by the committee system, and the most fundamental premise of agenda-setting research is that attention matters in politics. Examining this question, however, requires multiple comparable

68 

P. B. MORTENSEN ET AL.

committee structures and hence a different research design than the US Congress allows. Furthermore, previous research on committee structures lacks a measure of the agenda of the assembly. This omission may be justified in a system like the US Congress where committees are the powerful decision-­ making venues, but in many other systems, including parliamentary systems, one typically finds a more balanced relationship between committees and the assembly (Baekgaard, 2011). In such systems, committees may still perform vital functions in channeling information and preparing regulation and decisions, but the floor of the assembly will remain the ultimate forum for making important political decisions. Such systems invite a closer look at the relationship between the committee structure, the committee agendas, and the policy agenda of the assembly as a whole. To examine this, we need a means of comparing committee attention to the attention of the assembly as a whole. As laid out in more detail below, the Danish municipalities offer this opportunity since we have comparable data that can be matched across committee and council meeting agendas.

Two Important Forces In line with much of the new generation of policy agendas research, we approach the structure–agenda link from a bounded rationality perspective. We adopt the basic assumption that all humans, including politicians, and human institutions, like assemblies, suffer from hard limitations on their attention capacity. Individual policymakers process information sequentially, and at any given point in time, they can focus only on a limited subset of issues. As individuals, policymakers can never escape this bottleneck of attention. By the same token, politicians on the floor of the assembly attend to items on its agenda serially—that is, one at a time—and therefore confronts its own bottleneck of attention. Thus, we can speak of individual-­ level and assembly-level bottlenecks of attention. Yet, the assembly can expand its collective processing and decision-making capacity by creating an organizational structure that allows for parallel processing. For instance, by creating hierarchies that divide labor by sorting tasks and people into more focused subunits (Hammond, 1993; Hammond et al., 2007), the assembly can multiply its attention capacity. Each subunit of the hierarchical organization can specialize and focus on only a small subset of the total number of tasks and issues that the organization as a whole needs to handle.

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

69

As Hammond (1993) argues, a committee system has many of the same traits as a hierarchy. It distributes policymakers into narrow and specialized committees, subsidiary to the assembly itself, which allows committee members to specialize and focus on only a subset of issues. Within each committee, its members can process and respond to issues in parallel to the activities of other committees. Committee-induced improvements to the assembly’s parallel processing capacity are widely recognized, but the limits of parallel processing have been neither theoretically nor empirically examined. These limits come from two sources. The first is a natural tendency for new committees to yield diminishing marginal returns to increased efficiency, thanks to the assembly-level bottleneck of attention. When all deliberation and every decision takes place on the assembly floor, delegating some deliberation and decision-making responsibility to a committee can contribute a real boost to the capacity of the assembly floor to attend to more issues. However, if a hypothetical assembly with one hundred committees were to add one more committee, the floor’s attention capacity would likely already be saturated, and so we should expect further parallel processing to free up little or no additional attention capacity for the assembly floor. The second source of limitations on parallel processing capacity relates to the individual-level bottleneck of attention. Its relevance comes from the fact that committees, in contrast to large hierarchies like public agencies, are composed from one limited pool of actors, namely the representatives. In most assemblies, politicians are members of several committees, and the committees’ common pool of members is fixed at the total number of assembly members. As committees proliferate, the bottleneck of attention facing individual politicians eventually imposes its own constraint on the surplus parallel processing capacity that can be gained by creating additional committees. For example, say there are ten members in an assembly and it constitutes two committees with five members in each, such that each legislator is a member of one committee. Establishing two additional committees would yield a diminished marginal boost to the committee system’s parallel processing capacity since the additional committee seats must be distributed among the same ten politicians that make up the full assembly. An overall increase in processing capacity from the two new committees might be expected since committees often come with staff support. Nevertheless, in our four-committee system, each politician sits on an average of two committees, and each five-member committee added will push up the

70 

P. B. MORTENSEN ET AL.

average committee assignments per legislator by one half. As each individual legislator sits on more committees, his or her individual capacity to attend to additional issues will be stretched thinner and can eventually become fully saturated. Of course, bottlenecks of attention do not automatically limit productivity every time a legislature adds new committees. As long as there is slack attention capacity at the individual or assembly level, then new committees can boost productivity for the assembly. For example, creating two new committees may result in some net additional committee meeting activity. It may also inspire some politicians to spend more time and energy on their committee work or otherwise increase their effort. Thus, the parallel processing effect of committees expands the legislature’s capacity to attend to additional agenda items, but this effect is gradually counteracted by the individual-level bottleneck of attention since the total number of politicians the assembly can allocate to additional committees is fixed by the size of the legislature. As the representatives sit on more committees, natural limits on their individual attention capacity will drag down the parallel processing boost from marginal increases to the number of committees. Figure 4.1 provides a stylized illustration of the combined effect as these two forces interact with one another as a function of the number of committees in a given system. To the left-hand side of the figure—where the legislature has few committees—the marginal boost in parallel processing capacity caused by an increase in the number of committees is expected to dominate the net effect. The bottleneck of attention effect, on the other hand, is expected to be largely invisible under these conditions since the number of committee memberships per politician is low in the left-­ hand region of Fig. 4.1. In other words, at low numbers of committees, there will be some excess capacity in the assembly that can be utilized for productivity, for instance, by activating backbenchers when dividing tasks into more committees. At some point, however, the legislature’s excess capacity is used up, and the net effect of marginal additions of new committees will be dominated by the bottleneck of attention force. In the right-hand region of Fig. 4.1, each politician sits on more than one committee, and excess parallel processing capacity gives way to an individual lack of time and limited attention. Furthermore, the parallel processing effect should flatten out as committee jurisdictions are sliced more and more narrowly. Thus, the net effect of the two forces, as illustrated by the solid line in Fig.  4.1, is

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

71

Fig. 4.1  The combined effect of the two forces Note: Lines are a stylized representation of our argument

expected to follow a curve showing increasing returns on issue-handling capacity up to a certain point and then decreasing returns as the number of committees further increases beyond that point. We are not in a position to pinpoint theoretically where the peak is and what the exact shape of the curve would look like. Nevertheless, Fig. 4.1 lays out the intuition behind our argument for the expected aggregate result of the two forces shaping the effect of the committee system on the assembly’s capacity to attend to issues on the policy agenda, and it provides a clear prediction against which to evaluate our empirical results. We further anticipate the number of committees to have different impacts on the committee system agenda (i.e. the collective agenda aggregated across all committees) and the assembly agenda (i.e. the agenda of the assembly floor). For instance, we expect the bottleneck of attention force to be more clearly evident in the assembly agenda than in the aggregated committee system agenda. We have argued that a higher number of committees will channel more issues into the central assembly and more information about problems that need to be tackled. This will result in a

72 

P. B. MORTENSEN ET AL.

larger and more complex assembly agenda. Yet, the single-venue character of the assembly as a whole means that the bottleneck of attention force will be particularly strong here because both the assembly and its members are subject to bottlenecks of attention. By contrast, the committee system is only subject to the individual-level bottleneck of attention since the committee system agenda is the sum of parallel activities across multiple fora. The reasoning behind these aggregate-level expectations can also be used to generate specific issue-level predictions. As a starting point, imagine an assembly allocating a limited time budget between two major issues. The issues can either be handled by a single committee or separated into two committees, with each committee having jurisdiction over one of the two issues. Our argument leads to the prediction that utilizing two committees in this way expands the assembly’s ability to attend more to both issues. This way of approaching the question has similarities with a simple economic model of spending with a budget constraint. In this case, the two goods are attention to the two issues, and the budget line represents the attention limitation facing the assembly. The logic is illustrated in Fig. 4.2. When the two issues are placed in two separate committees, the theoretical budget line is “Budget constraint (two committees).” When both issues are placed under the jurisdiction of the same committee, the theoretical budget line retracts to “Budget constraint (one committee).” The exact positions of the lines are, of course, only illustrative in the figure and will depend on additional factors such as the average number of committee memberships per politician in the assembly. Figure 4.2 shows a hard budget constraint on attention and illustrates how adding a committee (if the assembly does not already have too many) should increase the total amount of attention allocated to the two issues. The plot illustrates our argument that additional committees increase the attention capacity, or attention budget, of the assembly. The assembly’s preference for attention to each issue is represented by an ideal point at maximal attention to both idealized issues. Instead, if we assume that salience or some other factor weights the assembly’s preference toward attending more to one issue over another, the basic takeaway from the figure is the same. Furthermore, Fig.  4.2 illustrates our argument that the processing capacity of the system does not increase proportionally to the increase in the number of committees. The positions of the three budget constraints

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

73

Fig. 4.2  The attention (budget) constraint over issues on the policy agenda Note: Dashed lines are production possibility frontiers for issue attention, given the respective attention “budget” constraints and a constant opportunity cost between issues. Solid gray lines are symmetrical indifference curves representing distance from an assembly ideal point of maximal attention to both issues

show that, for example, if the number of committees were to double, the total amount of attention dedicated to those issues would not double. Exactly how much additional capacity is gained from adding an additional committee depends on the operative constraints from the bottleneck of attention force, which is shaped by the average number of committee

74 

P. B. MORTENSEN ET AL.

memberships per representative. In this chapter, we empirically probe these committee-specific mechanisms illustrated in Fig. 4.2. In the last part of the chapter, we derive and examine some further issue-specific implications from the perspective laid out in this section.

An Overview of Committees in the 98 Danish Municipalities The Danish municipalities have a high level of discretion with regard to the number of committees the local council creates and how tasks are distributed among them. The law on government in the municipalities (Kommunestyrelsesloven) requires that each municipality appoints at least one committee on economic affairs and one standing committee (i.e. a permanent committee until the next election), but the law neither sets an upper limit to the number of standing committees nor specifies jurisdictions beyond finance. The mayor always chairs the committee on economic affairs, and this committee should address all issues with financial and administrative implications before these issues are presented in council meetings. Furthermore, it is the responsibility of the committee on economic affairs to coordinate policies and activities across the municipality. Most municipalities maintain between four to six standing committees, but the number varies substantially, as shown in Fig. 4.3. The three panels represent the three different election periods covered by our data. We aggregate by election periods since the number and structure of committees tend to be very stable within election periods, with virtually all changes occurring right after elections when a new council takes office. In the first election period, the count of committees varied from 3 to 15. In the next period (2010–2013), the maximum number of committees was 10, and from 2014 to 2017, the span across municipalities was 3 to 11 standing committees. Across all years in the data, the mean number of committees in Danish municipalities is about seven with a standard deviation of 1.5.1 The committees are responsible for distinct policy domains. Examples of standing committees include “Public works & environment,” “Children & youth,” “Culture & recreation,” “Employment,” and “Business.” The council itself decides the portfolio and responsibilities of standing committees, and it normally does so in written bylaws voted on at the 1  Counted in 2008, 2012, and 2016 based on several editions of the Danish Local Government Handbook (Kommunalhåndbogen) and local bylaws.

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

75

Fig. 4.3  Counts of committees in Danish local councils by election periods Note: Election periods are defined by the electoral calendar. Although our data do not include the year 2017, that year marks the end of the respective election period

beginning of an election period after the new council is seated. Within their jurisdictions, the committees prepare items for council deliberation and recommend council decisions. If not prohibited by national law, the council can also delegate to the standing committees to make final decisions on an issue. Figure 4.4 shows an example of two committee structures in the municipality of Svendborg. In the election period from 2010 to 2013, the Svendborg local council decided to have nine standing committees, including the committee on economic affairs. In the following election period, from 2014 to 2017, the council reduced the number of standing committees to only five. Specifically, it merged the “Social” and “Health & prevention” committees into “Social & health.” It further merged the three committees of “Labor market,” “Culture & planning,” and “Business” into one committee: “Business, employment, & culture.” In both election periods, the council had 29 elected members. This is exactly the kind of committee variation that, together with cross-municipal variation, provides a unique opportunity to investigate our theoretical expectations empirically. In the analysis section, we return to the example of Svendborg Municipality. There may be various drivers behind changes in the committee structure. Sometimes it may reflect coalition politics. For example, a coalition

76 

P. B. MORTENSEN ET AL.

Fig. 4.4  Committee structure in Svendborg Municipality, 2010–2013 and 2014–2017 Note: The left column lists all city council committees in Svendborg Municipality for the 2010–2013 election period. Arrows connect each committee to its status in the 2014–2017 election period, following a reorganization in the wake of the 2013 local elections

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

77

Fig. 4.5  Total number of committees and council seats by municipal population Note: Each municipality appears three times in each panel, once during each election period: 2007–2009, 2010–2013, and 2014–2017. Plot excludes the capital and largest municipality, Copenhagen, due to its special status

partner may demand a committee chair position or may have demands regarding how committee chair seats are allocated. Creating a new committee may also be a way for the council to signal to voters that it cares about a given policy domain, or it may reflect a sincere reprioritization of issues by the council. Whatever the exact motives for a given committee structure—and there may be many different ones—it is important to learn about the policy-agenda consequences of those structures. Importantly, the number of committees is not just a product of the size of the municipality. This is visible in the left panel of Fig. 4.5, which plots the annual municipal population against the number of committees. Although the size of the municipality does matter for the number of committees in the council, as evidenced by the positive relationship between the two measures, there is also much variation in the pattern. We find many municipalities of about equal size with different numbers of committees, and we see municipalities of very different sizes that have the same number of committees. This corroborates our assumption that municipalities exercise the discretion national law provides them when it comes to deciding the local committee structure.

78 

P. B. MORTENSEN ET AL.

The law on government in the municipalities contains some regulation of the number of seats on the city council and the number of seats in committees. This regulation, however, also gives the local council much leeway. With respect to the size of the council, the total number of council seats must be an odd number between 9 and 31 if the number of inhabitants in the municipality is below 20,000 people. In municipalities with more than 20,000 inhabitants, the number of council seats must be an odd number between 19 and 31.2 The right panel of Fig. 4.5 shows how the sizes of the councils vary with municipal population, but it also shows that municipalities of equal size have rather different numbers of seats on the council and that municipalities of very different sizes have similarly sized councils. Regarding committee size, national regulation stipulates that committees should also contain an odd number of seats and that the total seats on any committee cannot be greater than half the size of the council. In practice, most municipalities’ standing committees contain between five and nine members, and committee sizes often vary across committees within a given municipality. The right panel of Fig. 4.6 shows that we also see noteworthy variation across municipalities—with respect to the average number of committee seats per council member. The lowest average number of committee memberships per council member is a little more than one, whereas the largest is more than three. The law on municipal governance stipulates that each committee must consist of members proportionately representing the parties in the council, according to council seats. For parties with more than one representative in the council, it is entirely up to the party to allocate committee memberships among their councilors. In principle, the number of committee memberships may vary within the parties, but in practice, most parties allocate committee memberships about equally among their elected representatives.

The Committee Dataset The main data used in this chapter to examine our theoretical expectations consist of a subset of the municipalities for which we have collected and coded meeting agendas from their standing committees from 2007 to 2016. Just for these 15 municipalities, the number of coded committee 2

 The law states that the main capital Copenhagen should have 55 seats on the council.

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

79

Fig. 4.6  Committee sizes across all 98 municipalities, 2008 Note: Each panel consists of 98 observations, one for each Danish municipality. Vertical axes show the percentage of municipalities with the respective number of seats in a committee or average committee seats per council member in the year 2008—that is, during the 2007–2009 election period

agenda points adds up to 149,371  in total. Thus, when moving to the level of individual committees, the scope of the task of collecting and coding agendas multiplies, making it impossible to conduct for all 98 municipalities. The selection of municipalities for this coding of committees was mainly based on the availability of complete committee agendas data, though we also targeted select municipalities of different sizes and covering different parts of the country. We also intentionally included municipalities that reflect some of the diversity in the committee structure found across municipalities in Denmark. Though representativeness was not the main selection criterion, Table 4.1 shows that the selected sample is not that different on key characteristics from the total group of municipalities in Denmark. Appendix D to this book shows a list of the municipalities represented in the analyses of this chapter. In the next sections, we utilize these data in combination with our data on the council agendas to examine our theoretical ideas about how the two forces, parallel processing capacity and the bottleneck of attention, shape the agenda effects of the committee structure.

80 

P. B. MORTENSEN ET AL.

Table 4.1  Comparison of the two groups of municipalities on key variables

Avg. inhabitants Avg. council size Avg. number of committees Number of municipalities

Case municipalities

All municipalities

49,197 (21,203.0) 25.8 (4.2) 7.0 (1.1) 15

45,956 (23,593.8) 24.8 (5.1) 6.8 (1.5) 94

Note: Averages over municipality means, standard deviations of municipality means in parentheses. “All municipalities” summary statistics exclude the four largest municipalities in Denmark

Parallel Processing Gains Meet the Bottleneck of Attention The upper panels of Fig. 4.7 examine the relationship between the number of committees in a council and the size of the agenda across all committees (left panel) and in city council meetings (right panel). Recall that based on the dual forces of parallel processing and the bottleneck of attention, we expect to find a concave relationship in which municipalities with very few or a high number of committees attend to fewer issues or agenda points compared to municipalities with a number of committees nearer the median. The patterns in Fig. 4.7 corroborate this expectation. Beginning in the upper left-hand panel of Fig. 4.7, we see that up to around eight committees, there is a positive relationship between the number of committees and the total number of committee meeting agenda points. Then, however, the curve flattens out, and municipalities with nine or more committees address fewer agenda points in committee agendas than municipalities with eight committees. The implication of the finding is that the finite number of city council members is eventually stretched too thin—serving on an excessive number of committees—for us to observe a boost to agenda size from the greater number of committees. At a certain point, the time demands the larger committee system places on individual legislators swamp the parallel processing benefits of increasing the number of committees. The upper right-hand panel of Fig. 4.7 shows the relationship between the number of committees and points on the council meeting agendas. The pattern is flatter, but it does show an increase in the size of council agendas when moving from four to seven committees, and there are signs

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

81

Fig. 4.7  Agenda size and count of subtopics (agenda complexity) by number of committees Note: Points are the 15 municipalities in our committee dataset, one observation per election period. Dashed lines are second-order polynomial regression lines

of a slight decrease in agenda size at seven or more committees. Most councils have a relatively fixed meeting frequency for any given year, and as argued above, this imposes a limit on the number of issues that can be processed in council meetings. The upper panels of Fig.  4.7 show that some councils process more issues than others, and the effect of the committee system is more limited here. These patterns are clarified in the dashed lines in each panel, which show quadratic predictions based on the observations in the plots. Consistent with the combined parallel processing/bottleneck of attention argument, we see declines in the size of both council and committee agendas at the highest counts of committees. The lower panels of Fig. 4.7 show similar effects, but here, the number of agenda points is replaced with the number of subtopic categories used to code the annual agendas, that is, the complexity or diversity of the

82 

P. B. MORTENSEN ET AL.

committee and council agendas (see Chap. 2). We can see that up to a certain point, an increasing number of committees imply that the council and the committee systems also cover more distinct political issues and likely also cover more aspects of these issues. At some point, however, increasing numbers of committees may overload the council and result in a more narrowly focused council agenda—the same pattern of diminishing returns that we observed with respect to the size of the overall agendas. This diminishing return is less apparent in the committee agendas, but the curve does flatten out in those municipalities with the highest number of standing committees. Statistical evidence for the diminishing marginal return on increasing numbers of committees is apparent here. In the cases of the size of the committee agenda and the complexity of the council agenda, likelihood ratio tests between the polynomial models pictured in Fig. 4.7 and a simple linear model excluding the polynomial term are highly significant. In both cases, a growing number of committees are significantly associated with increases in the outcome variable, while the square of the number of committees is significantly associated with decreases. The same pattern holds in the case of the complexity of the committee agenda, though the significance of the likelihood ratio test is p = 0.055. The likelihood ratio test is not significant in the case of council agenda points. With our limited sample size, it is, nevertheless, worth noting that the simple linear model finds no relationship between the number of committees and the size of the council agenda, while the model including the polynomial term estimates p-values of 0.065 for both the linear and polynomials terms and both have their expected signs. In sum, Fig. 4.7 clearly displays a relationship between the number of committees and the issue processing capacity of the local political system. Yet, these relationships are not linear. Instead, there is a particular concave shape to the relationship, which is highly consistent with the expected net effect derived from our argument about the combined forces of parallel processing and the bottleneck of attention. To get closer to these two forces, we create an empirical indicator of each. We take the number of committees in a municipality as an indicator of parallel processing capacity in the system, whereas we consider the average number of committee memberships per politician to be an indicator of the countervailing bottleneck of attention effect. Estimating these effects simultaneously, we aim to disentangle the effects of the two forces. Thus, although Fig. 4.7 (and Fig. 4.1) suggests a more complex process at work,

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

83

to test our basic expectations, we estimate the following statistical relationship:



System processing  capacity

number of average number of committee   f a  b  memberships per politician   committees

As an indicator of parallel processing capacity, we use the number of committees in the council. The bottleneck of attention limitation, on the other hand, we measure as the average number of committee memberships per local council member. The higher the number of committee memberships, the lower the capacity of each council member to invest more in his or her committee work. Thus, if we run a regression using these two indicators to explain the agenda capacity of the system, we would expect the number of committees (the parallel processing effect) to have a positive effect on agenda capacity and for the number of committee memberships (the bottleneck of attention effect) to exert a negative effect. Table 4.2 shows the results of estimating this model. We get one observation from each municipality averaged over each of the three election periods, adding up to only 44 observations.3 With this reservation in mind, Table 4.2 provides further support for the importance of the two highlighted mechanisms. In Model 1 in Table 4.2, we estimate only the effect of the number of committees. This effect is positive, and when estimated with the average committee membership variable (Model 2), the effect becomes stronger and more positive. As expected, the coefficient on the average number of committee memberships is negative. The estimated effects in Model 2  in Table  4.2 are exactly as expected, and comparing Models 1 and 2 further indicates that part of the positive effect of adding committees to the system may get suppressed if we do not control for the negative effect caused by the higher average number of committee memberships created by such an expansion of the committee system. Finally, in Model 3 in Table 4.2, we control for the possibility of omitted variable bias from the size of the municipal population. As we saw in Chap. 3, large municipalities have bigger agendas, while Fig.  4.5 illustrates that larger municipalities also have systematically more committees and more seats in

3  The number adds up to 44 because we miss observations from one election period in one of the 15 municipalities.

84 

P. B. MORTENSEN ET AL.

Table 4.2  Agenda size and system processing capacity Total number of agenda points across committees per year

Number of committees

(1)

(2)

(3)

102.71*** (25.69)

168.69*** (33.54) −408.72** (146.22)

323.58 (183.61) 0.26 44

590.56** (195.26) 0.36 44

150.461*** (32.01) −432.840** (136.64) 0.004* (0.00) 536.030** (183.22) 0.45 44

Average number of committee memberships Municipal population Constant Adjusted R2 Observations

Note: Standard errors in parentheses. * p < 0.05, ** p < 0.01, *** p < 0.001 (two-sided)

the local council. Nevertheless, including this control only strengthens our conclusions from Model 2.4

The Impact of Changes in Committee Structures In Fig.  4.8, we zoom in on those instances in which a council has changed the number of committees from one election period to the next. We record 28 instances of such changes in our subset of data on committee agendas. One advantage of looking at changes is that it lessens the impact of structural and invariant (in the short term) factors such as municipality size, council size, and demographic composition of the local population. In Fig. 4.8, we measure percentage changes in the count of committees and in agenda items in order to get closer to the question of the 4  Note that Model 3 in Table 4.2 also raises the concern that municipal population is a background variable, whose impact on the size of the committee agenda is primarily realized through the effect of population on the other two explanatory variables in Model 3. To probe this, we modeled the bivariate relationship between municipal population and committee agenda size. In this bivariate model, the coefficient on population increases slightly to 0.006, but the model’s R2 drops to 0.18. This indicates that the number of committees and the average number of committee memberships have their own distinct relationships to the size of the local policy agenda.

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

85

Fig. 4.8  Committee system changes and system processing capacity Note: Each point is one year-on-year percentage change in number of committees in one municipality. All observations with zero change are excluded. Dashed line is the fitted regression line for the bivariate relationship. Shaded regions illustrate our expectation about where most observations should appear

proportionality between changes in the committee system and changes in policy agendas. Theoretically, our argument implies that we should see an effect on the agenda from a change in the committee system, but it need not be proportional. Thus, if the number of committees in the council is increased by 20 percent, then the increase in total agenda capacity will be positive but less than 20 percent. Conversely, if the number of committees is cut by 20 percent, the reduction in agenda capacity will also be less than 20 percent. Since the 45-degree line marks a proportional effect, the gray-shaded area in Fig. 4.8 indicates the space for observations consistent with our expectations. A majority of the observations is situated in this region of the plot, and the estimated best linear fit across the observations is also

86 

P. B. MORTENSEN ET AL.

in this region. Thus, on average, increasing the number of committees leads to an increase in the overall agenda processing capacity of the committee system, whereas decreasing the number of committees has the opposite effect. Yet, there is much variation around this overall trend. Furthermore, again, with reservation for the low number of observations, there could well be a curved relationship in the right-hand part of Fig.  4.8, indicating that the expansionary agenda effect of very large increases in the committee system is very limited. Again, this implies that both the bottleneck of attention and parallel processing effects are important factors to consider when evaluating the effect of changes in the committee systems. The findings presented so far have all focused on the system-level relationship between the committee structure and the policy agenda. We now move to the level of individual committees to see how changes in the committee structure may influence the agendas of individual committees. Based on a careful reading of the local bylaws determining the committee structure for the sample of municipalities covered in our committee dataset, we have selected two municipalities for more detailed examination. One of them is Ishøj Municipality, where the council in 2009 decided to divide the “Infrastructure & environment” committee into two new committees: an “Infrastructure & public works” committee and a “Climate & environment” committee. The other case is from Svendborg Municipality, which in 2013 decided to merge the “Social” and “Public health” committees into one new “Social & health” committee. The choice of these two examples is based on the fact that the committees covered essentially the same jurisdictions before and after these changes according to the councils’ bylaws. Often, a change in committees can be accompanied by other jurisdictional changes and reallocations of responsibilities, which hamper the identification of an effect from just the change in the number of committees. Furthermore, these two cases provide the opportunity to compare the split of a committee to the merger of two committees. Figure 4.9 summarizes the resulting changes in committee agenda points from the change in the committee setup. To the left-hand side of Fig. 4.9, we see that the two new committees on infrastructure/environment in Ishøj produced around a 20-percent increase in the number of agenda points on this issue domain compared to when the issue domain

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

87

Fig. 4.9  The agenda effects of changing committee jurisdictions

was covered by just one committee. To take into account that there may have been a general trend in Ishøj Municipality in that period of committee change, the bar to the left of Fig.  4.9 shows the average change in agenda points for the other committees in Ishøj Municipality (those that were neither merged nor split). Clearly, the increase seen from the two new committees does not just reflect an average trend across the other committees in Ishøj. Turning to Svendborg Municipality (right-hand side of Fig. 4.9), we see how the merger of committees, as expected, led to fewer agenda points in the areas affected by the merger. In fact, Svendborg is almost a mirror image of what we see in Ishøj. The rightmost bar in Fig. 4.9 shows the effect of the simultaneous change from three committees to one in the area of “Labor market, culture, & business.” The clear impression from Fig.  4.9 is that changes in the committee structure affect the agendas of the committees subjected to the change. Furthermore, it is worth noting that the effect is not proportional. Moving

88 

P. B. MORTENSEN ET AL.

from one to two committees doubles the number of committee seats dealing with the issue domain, but it does not double the number of agenda points covering the respective jurisdictional issue domain. We argue that this reflects the bottleneck of attention limiting the individual committee members. The bottleneck of attention imposes a de facto “attention budget constraint,” as illustrated by the budget lines in Fig. 4.2. Table 4.3 shows similar effects regarding other measures of agenda capacity. The number of subtopics used to code the relevant committee agendas increases when moving from one to two committees (Ishøj) but decreases when moving from two committees to one (Svendborg). This shows that in this case, not only do more committees in a given policy domain lead to more points on the agenda, but this also means that more aspects and subtopics within the major issues covered by the committee are taken up by politicians. A similar picture arises when using Shannon’s H as a measure of agenda complexity: agenda complexity is higher in the case with two committees, compared to the case with just one committee. More particularly, the lower Shannon’s H scores in the one-committee cases indicate that the distribution of issue attention in these committees tended to be more peaked and concentrated on fewer issues compared to the two-committee cases. Table 4.3  Number of subtopics and Shannon’s H in Ishøj and Svendborg Municipalities Ishøj Municipality

Number of subtopics Shannon’s H

One committee (A) (2007–2009)

Two committees (B) Difference (B−A) t-value (2010–2013)

30

37

7

2.98*

2.30

2.95

.66

3.01*

Svendborg Municipality

Number of subtopics Shannon’s H

Two committees (A) (2010–2013)

One committee (B) (2014–2017)

Difference (B−A) t-value

40

30

−10

−3.74**

3.17

2.85

−.32

−5.44**

Note: * p < 0.05, ** p < 0.01, *** p < 0.001 (two-sided)

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

89

Further Explorations of Issue-Specific Committee Effects For each subtopic, Fig. 4.10 shows the agenda points of the new committee in Svendborg subtracted from the agenda points of the previous two committees when combined over the course of the respective election periods. This shows another aspect of the disproportional effect of committee changes on committee attention to issues. When moving from two committees to one, most issues, as expected, get less attention in the new single committee compared to the former two committees. Yet, as can be seen in Fig.  4.10, some issues actually gain more attention in the new single committee—measured in absolute terms—than they received in the two old committees together. This pattern is consistent with our theoretical explanation that accounts for the limited and disproportional attention of policymakers, but it also invites additions to the argument. Policymakers may always tend to focus on a rather limited set of issues, and this tendency gets reinforced when the institution-driven parallel processing capacity is lowered. Another implication of Fig. 4.10 is that some, likely more secondary, issues get ignored when two committees are merged into one. Other, more politically salient, issues may actually get even more attention from such a change. The single-case pattern shown in Fig. 4.10 should not be exaggerated, but it could be consistent with this saliency argument that subtopics such as health, senior citizens policy, and social policy receive more attention when the committee capacity is reduced from two to one. Furthermore, it is interesting to see the two relevant general categories (300 and 1300) among the top ten issues at the top of Fig. 4.10. According to the coding instructions, meeting items that cut across two or more subtopics should always be coded in the relevant x00 category, implying that more meeting items get a general (less specific) character when the issue domain of a committee broadens. Figure 4.11 shows that the pattern observed in Fig.  4.10 is reversed when we look at the issue-level effects of an increase in the number of committees covering the same policy domains. In fact, the results from Ishøj Municipality in Fig. 4.11 look remarkably symmetrical to the pattern from Svendborg Municipality. About 60 percent of the issues covered by the two committees in Svendborg get less attention when covered by one

90 

P. B. MORTENSEN ET AL.

Fig. 4.10  Change in number of agenda points per issue when moving from two committees to one in Svendborg Municipality

committee, whereas about 30 percent of the issues get more attention after the change. In Ishøj, we see almost exactly the opposite pattern. About 60 percent of the issues get more attention when moving from one committee to two, whereas about 30 percent of the issues get less attention.

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

91

Fig. 4.11  Percentage of subtopics that get less, more, or the same attention following a change in the committee structures in Ishøj and Svendborg Note: The committee structure is expanded in Ishøj and reduced in Svendborg

Summary This chapter has examined a prominent idea in political science, namely that the institutional setup structuring the policy-making process influences the attention of the policymakers. Though prominent, it is an idea that has been in need of theoretical specification and more direct empirical examination. Focusing on the committee system, which is an institutional characteristic found in almost any local or national democratic legislature, this chapter makes two important contributions to our understanding of the structure–agenda link. First, drawing on classic insights from behavioral organizational theory, we identify two central forces shaping the effect of the committee system. One is parallel processing capacity, which in itself implies a gain in the processing capacity of the assembly when delegating part of the policy-­ making process to specialized committees. Our argument here is largely consistent with traditional perceptions of the efficiency gains that can be achieved by dividing effort among a larger number of policy-making venues instead of centralizing it in a single institution. The new insights arise when this force is supplemented with an understanding of how the bottleneck of attention force limits the attention capacity of all policymakers.

92 

P. B. MORTENSEN ET AL.

When these two forces are considered together, we can derive more precise and realistic predictions about the agenda effects of a given committee structure. This is a critical finding for our understanding of organizations and attention: there is no magic bullet to surpass the fundamental limits of human attention. Parallel processing is an efficient way for institutional design to enlarge the total attention span of an organization, but beyond a certain margin, dividing things up more becomes counterproductive to the organization’s attention capacity. Second, the chapter derived and examined observable implications from this basic argument at several levels of aggregation, from the individual issue level up to the level of overall agenda size. In some parts of the analyses, the number of observations was reduced due to the demanding data collection requirements, but across the many different analyses, we found strong empirical support for the expectations derived from the core theoretical argument. The basic argument of this chapter is based on rather generic aspects of any policymaker and (almost) any political system, and that raises the likelihood that the argument and the empirical results are relevant outside the context of Danish local government. Of course, the total number of committees may be much higher in a national assembly, just as the average number of committee memberships may vary, but such variation is internal to the model introduced in this chapter. Thus, as long as the basic use and functioning of committees is rather similar to what we have observed in the Danish municipalities, we see good reasons that our argument can travel to other systems, both local and national. One aspect that may be especially context dependent is the effect found between committee agendas and the agenda of the council (the assembly). In systems like the US Congress where important decisions are not only prepared but also decided upon in the committees, the interplay with the agenda of the floor of the assembly may, of course, be of a different character. The main finding—that institutional structures influence the policy agenda—has implications for our understanding of the Danish local governments and legislatures organized through a committee system more broadly. Our results indicate that splitting up a committee into two or merging two committees into one is a highly effective way to control the flow of information. Hence, politicians might not only reconfigure the committee system to enhance coordination between issue areas or to divide more committee chairs between ruling party members, but surely

4  COMMITTEE STRUCTURE AND THE LOCAL POLICY AGENDA 

93

also to curb or expand political attention to an issue area. Committees are a central—if not the central—way for issues to reach the floor of the assembly, and committee members act in a critical role as information processors on the issue area of their committee. They pay particular attention to the jurisdiction of their committee(s), and they keep in contact with key societal stakeholders. Hence, if a party wants to limit public intervention in an issue area, the most effective way to accomplish this might not be through fights over the budget but instead by squeezing the information channel much earlier in the policy-making process (Baumgartner & Jones, 2015).

References Baekgaard, M. (2011). Committee bias in legislatures with a high degree of party cohesion: Evidence from Danish municipalities. European Journal of Political Research, 50(3), 315–335. Baumgartner, F. R., & Jones, B. (1993). Agendas and instability in American politics. University of Chicago Press. Baumgartner, F. R., & Jones, B. (2015). The politics of information. University of Chicago Press. Baumgartner, F. R., Jones, B. D., & MacLeod, M. C. (2000). The evolution of legislative jurisdictions. Journal of Politics, 62(2), 321–349. Baumgartner, F. R., Breunig, C., Green-Pedersen, C., Jones, B. D., Mortensen, P. B., Nuytemans, M., & Walgrave, S. (2009). Punctuated equilibrium in comparative perspective. American Journal of Political Science, 53(3), 603–620. Baumgartner, F.  R., Jones, B., & Wilkerson, J. (2011). Comparative studies of policy dynamics. Comparative Political Studies, 44(8), 947–972. Green-Pedersen, C., & Walgrave, S. (2014). Agenda setting, policies, and political systems: A comparative approach. University of Chicago Press. Green-Pedersen, C., & Wilkerson, J. (2006). How agenda-setting attributes shape politics: Basic dilemmas, problem attention and health politics developments in Denmark and the US. Journal of European Public Policy, 13(7), 1039–1052. Hammond, T. H. (1993). Toward a general theory of hierarchy: Books, bureaucrats, basketball tournaments, and the administrative structure of the nation-­ state. Journal of Public Administration Research and Theory, 3(1), 120–145. Hammond, T. H., Jen, K. I., & Maeda, K. (2007). Learning in hierarchies: An empirical test using library catalogues. Journal of Theoretical Politics, 19(4), 425–463. Jones, B. D., Baumgartner, F. R., & Talbert, J. C. (1993). The destruction of issue monopolies in Congress. American Political Science Review, 87(3), 657–671.

94 

P. B. MORTENSEN ET AL.

Jones, B. D., Sulkin, T., & Larsen, H. A. (2003). Policy punctuations in American political institutions. American Political Science Review, 97(1), 151–169. Krehbiel, K. (1990). Are congressional committees composed of preference outliers? American Political Science Review, 84(1), 149–163. Schattschneider, E. (1960). The semisovereign people: A realist’s view of democracy in America. Wadsworth Publishing Company. Sheingate, A. D. (2006). Structure and opportunity: Committee jurisdiction and issue attention in Congress. American Journal of Political Science, 50(4), 844–859.

CHAPTER 5

Local Problems and the Local Policy Agenda

Across the world, the emergent problem of the Covid-19 pandemic quickly reshaped government priorities. Election promises, economic policies, new and planned climate regulation, health care reforms, infrastructure investments; all or most of these were swept off policy agendas by the sudden need to address the problems created or exacerbated by the pandemic. Covid-19 is an extreme illustration of a fundamental but overlooked means by which democratic leaders represent their citizens’ interests. Elected representatives must respond and adapt to a dynamic flow of changing problems confronting society. These problems are rarely as extreme, global, and fast moving as Covid-19, but a general and central characteristic of a well-functioning democracy is that worsening societal problems will be the subject of political attention and deliberation. This problem-solving aspect of democratic governance is missing from much research on political representation. The bulk of mainstream empirical studies on political representation assess the quality of representation based on how well policymakers’ issue positions or ideologies correspond to those of citizens (e.g. Bartels, 1991; Miller & Stokes, 1963; Shapiro & Page, 1992; Weisberg, 1976) or to what extent governments’ policies or policy positions respond to aggregate measures of public opinion (Adams et  al., 2004; Caughey & Warshaw, 2018; Einstein & Kogan, 2016; McDonald & Budge, 2005; Soroka & Wlezien, 2010; Tausanovitch & Warshaw, 2014; Trounstine, 2010; Warshaw, 2019). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 P. B. Mortensen et al., Explaining Local Policy Agendas, Comparative Studies of Political Agendas, https://doi.org/10.1007/978-3-030-90932-1_5

95

96 

P. B. MORTENSEN ET AL.

The Covid-19 problem illustrates how this opinion–policy approach is incomplete when judging governments’ representation of citizens’ interests. A crucial aspect of representation is to identify, prioritize, debate, and decide on changing societal problems (Adler & Wilkerson, 2013; Baumgartner & Jones, 2015; Robertson, 1976). Societal problems can evolve significantly between elections and frequently concern issues about which voters lack strong preferences regarding the policy solution that should be pursued (Arnold, 1990; Egan, 2014; Petrocik, 1996). Since citizens’ preferences may be based on misguided information and their expressed policy preferences may have detrimental side effects or terrible economic or social consequences (Baumgartner & Jones, 2015), good representation need not imply that representatives mechanically strive to reflect voters’ expressed opinions. In practice, representatives are often called on to exercise judgment and context-specific knowledge to make decisions on difficult and sometimes dynamic societal problems on behalf of their constituents. We refer to this type of representation as problem-­ based representation. For instance, politicians on the left and right often disagree on the best policy response to rising unemployment. It is far from obvious that a given policy to counter unemployment is objectively best at all times, and often, the best solutions require political debate to arrive at them. Thus, from this perspective, it would be hard—and perhaps impossible—to assess the quality of political representation based only on observing policy outputs. In some instances, a status quo policy may be the best solution against unemployment, but from a representational perspective, it matters if such inaction follows from ignorance or extensive political debate. In a well-­ functioning representative democracy, elected representatives must deliberate and make decisions about worsening societal problems. In our perspective, these deliberations are the observable implication of problem-­ based representation—if politicians attempt to address societal problems, then we will observe them attending to and deliberating on worsening societal problems. In this chapter, we introduce and discuss this important aspect of political representation and demonstrate with systematic empirical evidence that it occurs. Moreover, we account for electoral competition’s central role in the relationship between problems and responsiveness. Competition for office is a fundamental motivation for politicians to be responsive to citizens’ welfare (e.g. Powell, 2004). Hence, if political reactions to societal problems are a central feature of representative democracy, then we

5  LOCAL PROBLEMS AND THE LOCAL POLICY AGENDA 

97

expect to see this link strengthened where political competition—that is, the risk of losing re-election—is stronger. Structuring a thorough empirical examination of problem-based representation is demanding. It requires data on elected leaders’ attention to societal problems, systematic measures that capture variation in those problems’ severity, and data of sufficient size and variation to allow controlling for several sources of omitted variable bias. We argue that our extensive data from the 98 Danish municipalities meet these demands. The Danish local government setting holds constant a broad range of potentially confounding variables, including basic political institutions and the structure of party competition, while providing substantial variation in the key variables for evaluating problem-based representation: the mix of local societal problems confronting local elected representatives, local political attention to those problems, and the degree of local electoral competition. More specifically, we track the relationships between seven different problem measures and local government attention to these seven issues based on our council agendas dataset. Our findings demonstrate that the elected local council representatives respond systematically to changes in this diverse set of societal problems. Furthermore, and most notably, this problem responsiveness is strongest in  local councils experiencing the greatest electoral competition.

Empirical Studies of Political Representation Reconsidered The definition of representation dominating empirical research is one in which elected representatives’ positions or policies correspond as closely as possible with constituents’ expressed wishes and opinions (e.g. Adams et al., 2004; Bartels, 1991; Miller & Stokes, 1963; Shapiro & Page, 1992; Soroka & Wlezien, 2010; Weisberg, 1976; Wlezien, 1995). We do not repudiate the major contributions of this research. Yet, democratic representation should not be limited to this understanding of representation (see Mansbridge, 2003). The public may, for instance, be largely unaware of looming societal problems as many citizens were when the earliest lockdowns and travel restrictions were announced to deal with the Covid-19 pandemic in March 2020. Even when voters are aware of problems, they often lack relevant information about which solutions will best serve their

98 

P. B. MORTENSEN ET AL.

interests, and the public may not have clear preferences over how to address a given societal problem (Manin et  al., 1999). Pitkin (1967, p. 223) quotes one US legislator, who puts it this way: “I know that they [his constituents] would vote as I do if they had the facts that I have … I figure if they knew what I know … they would understand my vote.” In line with this perspective, Arnold (1990, p. 18) claims that citizens often lack policy preferences simply because they do not understand the precise relationship between policies and outcomes. Such reasoning also calls into question the use of public policy measures—that is, spending, regulation, and so on—as indicators of government responsiveness to societal problems. For instance, the best policy response to a problem does not necessarily cost more. Sometimes, a societal problem is best addressed by cutting spending to avoid throwing good money after bad. Public spending preferences of majorities of voters can be identified on broad issues with public opinion surveys asking whether more or less money should be spent on education, health care, defense, and so on (Caughey et al., 2019; Stimson et al., 1995; Wlezien, 1995). However, voters’ expressed preferences for more spending are most likely not really preferences for more spending but rather preferences for better education, better health care, or more security. If politicians achieve better outcomes with the same or less money, no reasonable observer would conclude that voters had been poorly represented. A similar ambiguity applies to regulation, where it can be difficult to assess a priori whether hard, soft, or zero regulation best serves the public interest. Public opinion on regulation is, again, best understood as a mixed signal about preferences for better outcomes and a proxy for citizens’ general trust in government. Politics tends to revolve around specific problems, and representatives can often gain little practical guidance from broad measures of constituents’ opinions or ideologies. Another dominant model in this camp of empirical research on representation is the “mandate” version of representation. In this model, democratic governance means that winning coalitions implements the policies they proposed to voters before the election. Conditions may change, however, in ways that mean that the proposed policy is no longer best for the voters (Manin et al., 1999). Some problems may be best confronted by sticking to election promises, while others may require abandoning promises. Most policy choices can only be optimized conditional on the state of the world: a policy can be superior in good conditions but inferior in bad conditions (see, e.g., Manin et al., 1999, p. 36). The Covid-19 crisis again

5  LOCAL PROBLEMS AND THE LOCAL POLICY AGENDA 

99

illustrates how emergent problems can turn the logic of many policies on their heads. Due to the pandemic, governments that may have entered office in favor of boosting international trade and tourism suddenly found themselves implementing border closings and travel bans with broad public support. More generally, however, elected representatives frequently face a choice between deviating from election promises in voters’ interest and adhering fecklessly to a mandate despite altered circumstances. Both an incoming government and voters may later learn something that was unknown at the last election. The intrusion of new issues and problems that demand attention from political leaders is a constant process (Jones & Baumgartner, 2005). Thus, as Mansbridge (2003, p.  516) also argues, representative democracy is not merely about promissory representation, where a fixed (or “mandated”) set of policy solutions are applied to a fixed set of problems. In Chap. 6, we return to a modified “mandate hypothesis,” but in this chapter, we explore a different type of representation— what we term problem-based representation.

Problem-Based Representation The problem-based perspective on representative democracy calls for a new measure of responsiveness. The usual measures of responsiveness in the opinion–policy literature are simply not adequate to capture problem-­ based representation. Instead, we advocate approaching the question of responsiveness from a policy agenda perspective. Though we cannot generate normative claims about which solutions should be offered by political leaders when societal problems arise, we can confidently expect that politicians will attend to and discuss those problems. The act of attending to and deliberating an issue is putting the issue on the policy agenda. This is the core of our argument integrating the policy agenda into the study of political representation. An important pathway of democratic responsiveness is to put worsening societal problems on the policy agenda. Our concept of problem-based representation centers on the linkage between indicators of societal problems and the policy agenda as defined throughout this book as the set of issues to which politicians attend. To clarify our ideas, Fig. 5.1 plots three responsiveness scenarios reflecting a familiar situation: a societal problem emerges and eventually recedes in importance (dotted lines), and politicians’ attention takes three hypothetical trajectories (solid lines). To the left, we sketch a scenario (1) with

100 

P. B. MORTENSEN ET AL.

1 #

2 #

Responsive

3 #

Weakly responsive

Unresponsive

t

Fig. 5.1  Illustration of three different scenarios of a link between problems and attention Note: Societal problems [dotted line]; governmental agenda [solid line]

ideal-typical problem-based representation. Politicians’ attention closely tracks the problem’s severity, elevating and declining in close correspondence. The opposite scenario, one with poor problem-based representation (3), is sketched to the right of Fig. 5.1. Here, the problem has no influence on the level of political attention and debate. In the center of Fig. 5.1, we sketch a scenario (2) between the two extremes. Politicians’ attention responds weakly to problem severity. When problem severity ramps up steeply from a low level, attention is at a fairly low level and increases only moderately as the problem worsens. If, in reality, we observe empirical patterns somewhere between Scenarios 1 and 2, and definitely closer to Scenario 1 than 3, then we take this as supportive evidence of well-functioning problem-based representation. That is, the policy agenda of representatives responds to variation in the severity of societal problems. Regular, free elections are crucial for representative democracy. As Pitkin argues (1967, p.  233), there need not be a constant activity of responding, but there must be a potential readiness to respond, and competition for office provides a strong motivation for this (see also Powell, 2004). Competitive elections are the sine qua non of democracy because they provide the risk for incumbents to lose, ensuring that politicians face uncertainty regarding their future in office (Przeworski et  al., 2000, pp. 16–18). This strong intuition is also evident in the literature on representation as preference satisfaction (Carroll & Eichorst, 2013; Griffin, 2006). Politicians may, of course, be intrinsically motivated to solve a problem (Heclo, 1974), but they are certainly motivated to seek re-­ election for themselves or their party. The implication is that absent

5  LOCAL PROBLEMS AND THE LOCAL POLICY AGENDA 

101

substantial competition for office, politicians are not compelled to improve citizens’ welfare or respond to societal problems. Thus, if policy agenda responsiveness to societal problems is a central feature of representative democracy, then a core implication of problem-­ based representation is that electoral competition enhances this responsiveness. In other words, we expect to find that greater electoral competition for office will draw responsiveness toward resembling Scenario 1 in Fig. 5.1.

How to Study Problem-Based Representation There are substantive reasons for examining problem-based representation at the local level of government as well as methodological advantages to doing so. Substantially, a central argument for local governments’ existence is that they respond to problems in their local jurisdiction (Dahl, 1967; Tiebout, 1956). Societal problems’ size and intensity vary within countries, and arguably, a core task for local governments is to prioritize among the problems facing the local public to provide welfare to them (Treisman, 2007). Methodologically, examining the link between societal problems and the policy agenda is demanding. First, we need detailed and comparable measures of societal problems over time and across a number of political units. Second, we need comparable measures of the policy agenda that map to the measurements of societal problems and cover the same period and political units. Moreover, we need theoretically relevant variation in the main explanatory variables—societal problems and the degree of electoral competition—as well as measures of relevant control variables. These requirements are impossible to meet at the country level of analysis where the number of confounding variables is excessive, institutional differences imply that responsiveness takes place in various ways, and there are too few units to support a statistically reliable comparison. Furthermore, relevant measures are often incomparable between countries. Our time series cross-sectional data spanning the 98 Danish municipalities from 2007 to 2016 overcome these challenges presented by national-­ level data. As shown in Chap. 2, the municipalities have the same basic political institutions and electoral system, they are all governed by similarly structured local councils, and they all feature wide autonomy across a range of important policy areas. For the research question of this chapter, it is particularly important that the Danish municipalities are multipurpose

102 

P. B. MORTENSEN ET AL.

political units with considerable policy responsibilities (subject to national legislation and regulation). As laid out in Chap. 2, their policy responsibilities span areas such as care for the disabled, elderly care, pre-school day care, schools, unemployment assistance, job training and placement, public housing, road and park maintenance, environmental regulation and inspection, social policy financing and administration, integration of immigrants (housing and labor market participation), firefighting, utilities and garbage collection, local public transportation, libraries, arts, and leisure activities. Among these policy responsibilities, we study local responsiveness to seven key local political issues: immigration, crime, business, child care, schools, unemployment, and elderly care. We include multiple issues to avoid a single-issue analysis subject to idiosyncrasies associated with a single policy area. We select these particular issues because they can all be core concerns for citizens’ welfare. All seven can be termed “valence” issues (Stokes, 1963) in the sense that citizens and politicians usually prefer less compared to more crime, bankruptcies, immigration, and so on. Likewise, all seven issues are more pragmatic than principled in the sense that voters just want politicians to handle the problems (Tavits, 2007). One challenge in studying problem-based representation is that the concept of societal problems “spans a terrain between illusion and objective reality” (Robertson, 1976, p. 4). We certainly acknowledge this challenge. However, it should not be exaggerated. The connection between problem and measurement is not always elusive. Systematically measured problem indicators have proliferated in modern democracies, covering a variety of important policy areas (Davis et al., 2012; Kelley & Simmons, 2015). Danish local government is no exception. A broad range of nationally produced problem indicators is publicly available and allows us to compare problem severity systematically across local government units and over time. Although some issues lack readily available indicators, the seven issues included in this study can all be coupled to standardized, nationally produced problem indicators—that is, none of these issues are subject to intentional local-level manipulation or variation in  local data collection practices. Hence, the seven issues allow us to measure problem severity in a systematic and comparable way. Crime and immigration might seem like odd issues since Danish municipalities lack legal jurisdiction to regulate them directly. Nevertheless, both are important concerns for citizens and consequently for local politicians who can address both issues in indirect ways. If, for example, crime rates

5  LOCAL PROBLEMS AND THE LOCAL POLICY AGENDA 

103

in the municipality go up, citizens can expect local politicians to consider and debate how to tackle the problem through measures besides growing the police force or implementing tougher sentencing (which only the national parliament can do). Another advantage of the selected issues is that it is hard to imagine how politicians can substantially influence them in the short or medium term. This goes for demand for day care or retirement home spots, and for crime rates, immigration rates (the central government allocates immigrants based on a set algorithm), bankruptcy rates, and even unemployment rates. This lends strength to our expectation that local politicians will attend to these issues as they worsen: none are subject to quick fixes, but inattention may exacerbate them. To measure relevant, local variation in societal problems, we collect statistical indicators of local problems targeted to each of our seven issues. To measure unemployment, immigration, crime, and business, we use standard indicators such as the local unemployment rate, the total local immigration rate, the total local crime rate, and the number of bankruptcies locally. Since Danish municipalities are responsible for building, maintaining, and operating facilities for day care, schools, and elderly care, a useful statistical problem indicator is simply the proportional size of the local populations of pre-school children (3–5  years), in-school children (6–13 years), and retired citizens (65+ years) relative to the entire local population. As these groups of citizens grow as a proportion of the local population, local politicians must consider a variety of policy reactions to the increased demand this generates for services to that population group (i.e. cutting down on the services, building new facilities, deciding on how to use existing facilities more efficiently, etc.). Thus, when these indicators suggest a greater level of problem severity, we expect politicians to attend to this change and debate the implications.1 To take into account variation in the sizes of municipalities, each indicator is measured as the respective proportion of the local population. To allow comparative analyses across issues, all seven statistical problem indicators have been standardized within each indicator to a 0–1 interval, where 1 is the maximum observed value of the respective indicator in our data and 0 the minimum.2 1  We measure our problem indicators by levels, but the fixed-effects estimation is an analysis of change. 2   For a given problem indicator (x), our final measure (xfinal) is defined xraw  min  xraw  . as: x final  max  xraw   min  xraw 

104 

P. B. MORTENSEN ET AL.

Table 5.1  Agenda measures and problem indicators for the analysis Issue area

Topic in the council agendas data

Problem indicators

Immigration

9 “Immigration.”

Immigrants (per 1000 pop.) Violations of the penal code in total (per 1000 pop.)

Crime

1200 “Crime in general”; 1201 “Weapons”; 1202 “Organized crime”; 1203 “Drugs”; 1205 “Prisons”; 1206 “Juvenile crime”; 1211 “Sentences” Business 1500 “Business in general”; 1501 “Banking”; 1521 “Small business”; 1524 “Tourism”; 1530 “Local trade”; 1532 “Major local firms and companies”; 1599 “Other business related questions” Unemployment 500 “Labor in general”; 502 “Active labor market policy”; 506 “Youth unemployment”; 507 “Benefits”; 508 “Specific industries”; 529 “Seasonal workers” Schools 610 “Elementary and secondary schools”

Elderly care

1303 “Elderly care”

Child care

1310 “Child care”

Bankruptcies (per 1000 pop.)

Local unemployment rate

6–13-year-olds (percent of population) +65-year-olds (percent of population) 3–5-year-olds (percent of population)

Note: The problem indicators are available from the Ministry of Social Affairs and the Interior (www. noegletal.dk). See Appendix A for a further description of the topics in the agendas codebook

The match between the subtopics selected from our council agendas data and the problem indicators is shown in Table 5.1. We organize our data at the level of municipality-issue-years. Thus, observations join measurements of a societal problem to the attention it receives on the local council agenda and the level of political competition in a given municipality during a given year. We augment this with measures of several important control variables, detailed below. As visible from the top panels in Fig. 5.2, attention to our seven issues on the council agendas varies considerably over time and across municipalities. Schools, the issue area with the greatest level of council attention in our analysis, receive a relatively high level of attention—about 5 percent of all agenda items. Sometimes councils spend 10 or even 15 percent of annual agenda items on the school issue during our period of analysis.

5  LOCAL PROBLEMS AND THE LOCAL POLICY AGENDA 

105

Fig. 5.2  Variation in local problems and attention on seven issues in 98 Danish municipalities, 2007–2016 Note: Attention is measured as percentage of local annual political attention to the respective issue. For display purposes, all attention and problem measurements are standardized within problem areas by subtracting means and dividing by standard deviations

Another high-attention issue is business. On average, business received 4–5 percent of council attention early in our period of analysis, and this slightly decreases over time. The issue areas of child care, unemployment, and elderly care each receive about 2 percent of council attention annually. Yet, in some years and in some municipalities, council attention to these issues grows to 6, 8, or even 10 percent. Immigration and crime generally garner the least attention of our seven focus areas, although these issues can occasionally receive considerably more attention. As Fig. 5.2’s bottom panels show, problem indicators vary considerably across municipalities and over time. The crime, unemployment, and bankruptcy rates have all slowly decreased after a surge around the 2008–2009 financial crisis. In contrast, immigration rates have steadily increased. According to the figures, the number of pre-school children and in-school children is slowly decreasing, while the number of elders (+65) is on the rise. Measuring Political Competition Between 2007 and 2016, local elections occurred in 2009 and 2013. As a sign of the high political competition, in just those two elections, 48 of 98

106 

P. B. MORTENSEN ET AL.

municipalities saw center-left mayors replace center-right ones, or vice versa, at least once. The eight parties in the national parliament win seats in most local councils, but their seat shares vary considerably over time and across municipalities. The two largest parties in the national parliament, the Social Democrats (Socialdemokratiet) and the Liberals (Venstre), are often the largest in local councils as well.3 We measure competition in the local councils as the electoral surplus enjoyed by the sitting incumbents (Carroll & Eichorst, 2013, p. 91). With the almost perfect relationship between votes and seats in the proportional electoral system, we use seats on the council to capture electoral surplus. Specifically, we calculate the distance of the combined seat share of the center-left parties from 50 percent—expressed in percentage points. If the measure is positive (negative), center-left parties constitute the majority (minority) of local council members. If the measure is close to zero, then the ruling majority is slim and the distribution of seats between left and right is close to even. Our models also include the square of this measure since we can expect that larger magnitude seat surpluses matter more to responsiveness. Moreover, a squared measure allows for dissimilar changes in responsiveness above and below the zero-point—that is, it allows, for instance, that left majorities’ responsiveness is differently affected by the size of the majority compared to that of right majorities. The interaction of these variables with our measure of problem severity allows us to examine the expectation that political leaders are more responsive to problems when elections are more competitive. Figure 5.3 provides a first glance at the linkage between societal problems and the council agenda. The municipality shown to the left (Vejle) is governed by a very small majority in the council, whereas the one to the right (Varde) is governed by a solid and rather stable majority. With a higher level of competition in Vejle than in Varde, we expect a closer correspondence between local problems and local attention in the former. Dissimilar levels of problem attention are immediately visible in Fig. 5.3. On business, the problem and the council agenda are almost synchronous in the high-competition municipality of Vejle. This resembles Scenario 1 in Fig. 5.1, while in Varde, the low-competition municipality, problems, and the council agenda run counter to each other as in the “poor responsiveness” scenario (3) in Fig. 5.1. This is not to conclude that problem responsiveness is entirely absent in the low-competition municipality of  In some municipalities, a local list unaffiliated with any national party sometimes gains at least one seat in the council. 3

5  LOCAL PROBLEMS AND THE LOCAL POLICY AGENDA 

107

Fig. 5.3  Comparing local problems and local political attention to business and unemployment at low and high levels of political competition in a pair of similar Danish municipalities Note: Solid lines plot local problems; dashed lines plot local political attention. “Low” refers to a municipality with a low degree of electoral competition. “High” refers to a municipality with a high degree of electoral competition

Varde, but the correspondence between the slopes of the two lines is clearly weaker than that visible in Vejle. Interestingly, the lower panels of Fig. 5.3 reveal an impressive overlap in the development of the unemployment problem and council meeting attention to this issue in both municipalities. Amidst the financial crisis, the level of unemployment quickly jumped, peaked, and tapered off again. It seems that local representatives in both municipalities adjusted their attention in response. That said, the correspondence between the two lines differs predictably between the high- and low-competitiveness cases. In Varde, with a low level of competition, council meeting attention takes a large jump after unemployment declines, out of sync with the problem. This contrasts with Vejle, where the council seems to have allocated attention directly in relation to problem pressure. Again, this preliminary look at the data suggests a higher level of problem responsiveness in the high-­ competition municipality.

108 

P. B. MORTENSEN ET AL.

This comparison provides important suggestive, yet very tentative, empirical evidence that local policy agendas respond to local problems depending on the level of competition in the council. A more thorough statistical testing is required to examine if these examples reflect a more general pattern. Model Estimation and Control Variables To avoid omitted variable bias, we include several controls that may confound the relationships between local problems, local political competition, and local political attention. Our controls address features of municipalities’ geography, population, and financial situation. Among these are the logged population size of each municipality and a socio-­ economic index calculated by the Ministry of the Social Affairs and the Interior, which is a composite index based on the number of single mothers, people receiving social benefits, and so on, within the municipality (this index was also used in Chap. 3). These variables help ensure that our analysis captures variation across municipalities and over time that is not simply attributable to relatively static cross-sectional differences among Danish municipalities. If, for example, larger municipalities tend simultaneously to have similar societal problems, political competition, and mixes of political attention, then including these controls avoids trivial or biased findings. In terms of the local financial situation, we control for the level of debt in the local government finances. Each model includes a measure of the debt level per citizen (as of January 1) in each municipality to avoid the risk that local debt levels—whatever their provenance—contribute to differing issue attention, party competition, or societal problem severity (from www.noegletal.dk). Finally, all models include a lagged dependent variable and a year count taking on a value of 1 in 2007 and counting upward by one each year until 2016. We include the count to rule out confounding from any time trend effects and the lagged dependent variable to account for autocorrelation detected by diagnostic tests. Our models use a within (fixed-effects) estimator excluding a constant; that is, data are mean-differenced within panel units to filter out effects associated with particular municipalities.4 We define our panel units as the intersection of municipalities and 4  Hausmann tests reveal strongly significant differences between fixed-effects and random-­ effects specifications of our models. This is to be expected given that our data feature a large number of panels and relatively few time periods. These results underlie our decision to analyze fixed-effects (i.e. within-effects) models.

5  LOCAL PROBLEMS AND THE LOCAL POLICY AGENDA 

109

problems: 98 municipalities  ×  7 problems  =  686 panels. Each panel includes nine time periods (2008–2016) since the year 2007 is absent from the analysis to create lags. The final data for analysis include 5911 observations since 110 observations contain missing data for annual bankruptcies—our measure of the severity of local problems for the “business” issue. These data are missing in the original administrative records. Jackknife analyses show that all results remain the same excluding the issue of business or any other particular issues.

Empirical Findings Table 5.2 reports the main findings regarding the effect of local problem indicators on local council meeting agendas as well as the moderating effect of local political competition. Each column reports estimated coefficients and standard errors from normal linear panel regressions. The first column in Table 5.2 focuses on the main argument and shows that local problems draw local political attention in local councils. When a statistical problem indicator changes one unit, that is, from minimum to maximum value (0–1), the average council attention increases by just over 1.2 percentage points. This is a large change in the problems facing the municipality but also a substantial change in attention when taking into account that the average level of attention to each of the seven issues is 2.2 percent. This effect amounts to more than half a standard deviation. Figure  5.4 shows that predicted attention increases with the level of local problems on the horizontal axis. At a problem indicator level of 0.2—one standard deviation below the average level—we can expect about 1.8 percent of the local council agenda to focus on the respective issue. When that indicator rises to 0.8—two standard deviations above the mean—we can expect attention to rise to 2.6 percent of the local council agenda. Next, we examine whether the effect of local problems on local political attention depends on the level of competition between parties in the local council. The results in Model 2 in Table 5.2 show that the level of competition systematically influences problem responsiveness. The interaction term reveals a ∩-shaped problem response in which responsiveness is greatest at high levels of competition. The combined estimated effect is seen in Fig. 5.5: when the division of seats to the center-left and center-­ right is near 50/50 (zero on the horizontal axis), we estimate a statistically significant relationship between problems and the council agenda. With a solid majority for the center-left or center-right, problem responsiveness is

110 

P. B. MORTENSEN ET AL.

Table 5.2  Influence of local problems on local agendas across 98 Danish municipalities, 2007–2016

H1 H2

(L) Local problemsi, m, t (C) Competitivenessm, t L × C C × C L × C × C Yi, m, t−1 Municipal populationm, t (log) Left mayorm, t Socio-demographicm, t Debtm, t Women representationm, t Counter t Observations Panels Municipalities Issues Years (modal)

(1)

(2)

1.124*** (0.21)

1.266*** (0.24) −0.009 (0.01) 0.024 (0.02) 0.000 (0.00) −0.001* (0.00) 0.100*** (0.01) 0.002 (1.00) 0.060 (0.06) 0.296 (0.47) 0.004 (0.00) −0.001 (0.00) −0.028*** (0.01) 5911 686 98 7 9

0.101*** (0.01) 0.122 (1.00) 0.075 (0.05) 0.141 (0.47) 0.003 (0.00) 0.002 (0.00) −0.027*** (0.01) 5911 686 98 7 9

Note: Standard errors in parentheses. *p