Labormetrics: Sonderausgabe Heft 5+6/Bd. 228 (2008) Jahrbücher für Nationalökonomie und Statistik 9783110511680, 9783828204584

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Jahrbücher für Nationalökonomie und Statistik Journal of Economics and Statistics

Begründet von

Bruno Hildebrand

Fortgeführt von

Johannes Conrad, Ludwig Elster Otto v. Zwiedineck-Südenhorst Gerhard Albrecht, Friedrich Lütge Erich Preiser, Knut Borchardt Alfred E. Ott und Adolf Wagner

Herausgegeben von

Peter Winker, Wolfgang Franz Gerhard Kleinhenz, Werner Smolny Peter Stahlecker, Adolf Wagner Joachim Wagner, Dietmar Wellisch

Band 2 2 8

Lucius &c Lucius Stuttgart 2 0 0 8

© Lucius & Lucius Verlagsgesellschaft m b H • Stuttgart • 2008 Alle Rechte vorbehalten Satz: Mitterweger & Partner Kommunikationsgesellschaft mbH, Plankstadt Druck und Bindung: Neumann Druck, Heidelberg Printed in Germany

Labormetrics

Herausgegeben von Lutz Bellmann, Wolfgang Franz, Knut Gerlach, Reinhard Hujer, Wolfgang Meyer und Joachim Wagner

Mit Beiträgen von Bellmann, Lutz, Hannover Bode, Oliver, Wiesbaden Breitung, Jörg, Bonn Cornelissen, Thomas, Hannover Fitzenberger, Bernd, Frei bürg Franz, Wolfgang, Mannheim Gerlach, Knut, Hannover Hamermesh, Daniel S., Austin, USA Hart, Robert A., Stirling, Scotland Hujer, Reinhard, Frankfurt a.M. Jirjahn, Uwe, Hannover Kraft, Kornelius, Dortmund Lang, Julia, Dortmund

Lucius & Lucius • Stuttgart 2 0 0 8

M a , Yue, Hong Kong, China Meyer, Wolfgang, Hannover Pfann, Gerard A., Maastricht, The Netherlands Puhani, Patrick A., Hannover Rodrigues, Paulo J . M . , Frankfurt a.M. Ronning, Gerd, Tübingen Schnabel, Claus, Nürnberg Stephan, Gesine, Nürnberg Tsertsvadze, Georgi, Bad Homburg Wagner, Joachim, Lüneburg Wolf, Katja, Nürnberg

Anschriften der Herausgeber des Themenheftes Dr. Lutz Bellmann Institut für Arbeitsmarkt- und Berufsforschung (IAB) der Bundesagentur für Arbeit (BA) Regensburger Straße 1 0 4 9 0 4 7 8 Nürnberg E-Mail: [email protected]

Professor Dr. Reinhard Hujer Fachbereich Wirtschaftswissenschaften Johann Wolfgang-Goethe Universität Mertonstraße 17 6 0 0 5 4 Frankfurt am Main E-Mail: [email protected]

Prof. Dr. Dr. h. c. mult. Wolfgang Franz, Präsident Zentrum für Europäische Wirtschaftsforschung GmbH (ZEW) L7, 1 6 8 1 6 1 Mannheim E-Mail: [email protected]

Professor Dr. Joachim Wagner Leuphana Universität Lüneburg Campus, Raum 4 . 2 1 0 2 1 3 3 2 Lueneburg E-Mail: [email protected]

Professor Dr. Knut Gerlach Institut für Arbeitsökonomik Wirtschaftswissenschftliche Fakultät Leibniz Universität Hannover Königsworther Platz 1 3 0 1 6 7 Hannover E-Mail: [email protected]

Prof. Dr. Wolfgang Meyer Institut für Sozialpolitik Wirtschaftswissenschaftliche Fakultät Leibniz Universität Hannover Königsworther Platz 1 3 0 1 6 7 Hannover E-Mail: [email protected]

Bibliografische Information der Deutschen Nationalbibliothek Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografie; detaillierte bibliografische Daten sind im Internet über http://dnb.d-nb.de abrufbar ISBN 9 7 8 - 3 - 8 2 8 2 - 0 4 5 8 - 4

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Satz: Mitterweger & Partner Kommunikationsgesellschaft mbH, Plankstadt Druck und Bindung: Neumann Druck, Heidelberg Printed in Germany

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

Inhalt des 228. Sandes Abhandlungen / Original Papers Bartzsch, Nikolaus, Precautionary Saving and Income Uncertainty in Germany New Evidence from Microdata Bellmann, Lutz, Knut Gerlach, Wolfgang Meyer, Company-Level Pacts for Employment Benz, Ulrich, Christian Hagist, Konjunktur und Generationenbilanz - eine Analyse anhand des HP-Filters Business Cycle Effects on Generational Accounting - An Analysis using the HPFilter Blume, Lorenz, Thomas Döring, Stefan Voigt, Fiskalische Effekte der Kommunalverfassungsreformen der 1990er Jahre in Deutschland Reforming Local Constitutions in Germany during the 1990s - Their Fiscal Effects Borgloh, Sarah, Frank Kupferschmidt, Berthold U. Wigger, Verteilungseffekte der öffentlichen Finanzierung der Hochschulbildung in Deutschland: Eine Längsschnittbetrachtung auf der Basis des Sozioökonomischen Panels The Distributional Effects of Public Higher Education Financing in Germany: A Longitudinal Approach based on the Socioeconomic Panel Breitung, Jörg, Assessing the Rationality of Survey Expectations: The Probability Approach Dawid, Herbert, Simon Gemkow, Philipp Harting, Kordian Kabus, Michael Neugart, Klaus Wersching, Skills, Innovation, and Growth: An Agent-Based Policy Analysis Demary, Markus, Who Does a Currency Transaction Tax Harm More: Short-Term Speculators or Long-Term Investors? Engel, Dirk, Michaela Trax, Der Beschäftigungsbeitrag kleiner und mittlerer Unternehmen nach der EU-Definition The Employment Contribution of Small and Medium-sized Enterprises According to the EU-definition Fitzenberger, Bernd, Wolfgang Franz, Oliver Bode, The Phillips Curve and NAIRU Revisited: New Estimates for Germany Grund, Christian, Oliver Gürtler, The Effect of Reputation on Selling Prices in Auctions Haber, Gottfried, Monetary and Fiscal Policy Analysis With an Agent-Based Macroeconomic Model Hart, Robert A., Yue Ma, Wages, Hours and Human Capital Over the Life Cycle Heilemann, Ullrich, Roland Schuhr, Zur Evolution des deutschen Konjunkturzyklus 1958-2004 On the Evolution of German Business Cycles 1958-2004 Hujer, Reinhard, Paulo J.M. Rodrigues, Katja Wolf, Dynamic Panel Data Models with Spatial Correlation Jirjahn, Uwe, Thomas Cornelissen, Georgi Tsertsvadze, Parental Background and Earnings: German Evidence on Direct and Indirect Relationships Kraft, Kornelius, Julia Lang, The Causes and Consequences of Adopting a Works Council LeBaron, Blake, Peter Winker, Introduction to the Special Issue on Agent-Based Models for Economic Policy Advice

5-24 533-553

299-316

317-344

25-48 630-643 251-275 228-250

64-83 465-496 345-356 276-295 446-464 84-109 612-629 554-572 512-532 141-148

IV • Inhalt des 228. Bandes

Mueller, Steffen, Capital Stock Approximation using Firm Level Panel D a t a . . . . Nagel, Kai, Dominik Grether, Ulrike Beuck, Yu Chen, Marcel Rieser, Kai W. Axbausen, Multi-Agent Transport Simulations and Economic Evaluation Pfann, Gerard A., Daniel S. Hamermesb, Two-Sided Learning with Applications to Labor Turnover and Worker Displacement Puhani, Patrick A., Relative Demand and Supply of Skills and Wage Rigidity in the United States, Britain, and Western Germany Ronning, Gerd, Measuring Research Intensity from Anonymized Data: Does Multiplicative Noise with Factor Structure Save Results Regarding Quotients? . . . Schnabel, Claus, Joachim Wagner, The Aging of the Unions in West Germany, 1980-2006 Schnellenbach, Jan, Rational Ignorance is not Bliss: When do Lazy Voters Learn from Decentralised Policy Experiments? Schreiber, Sven, The Hausman Test Statistic can be Negative even Asymptotically Stephan, Gesine, The Effects of Active Labor Market Programs in Germany: An Investigation Using Different Definitions of Non-Treatment Weidlich, Anke, Daniel Veit, Agent-Based Simulations for Electricity Market Regulation Advice: Procedures and an Example Werding, Martin, Survivor Benefits and the Gender-Related Tax Differential in Public Pension Schemes: Observations from Germany Westerhoff, Frank H., The Use of Agent-based Financial Market Models to Test the Effectiveness of Regulatory Policies

357-371 173-194 423-445 573-585 644-653 497-511 372-393 394-405 586-611 149-172 110-134 195-227

Buchbesprechungen / Book Reviews Oberender, Peter (Hrsg.), Der „more economic approach" in der Beihilfenkontrolle Ohr, Renate (Hrsg.), Arbeitsmarkt und Beschäftigung Schmidtchen, Dieter, Max Albert, Stefan Voigt (eds.), The More Economic Approach to European Competition Law Swann, G.M. Peter, Putting Econometrics in its Place - A New Direction in Applied Economics

406 410 412 654

Cutachter zum 228. Jahrgang (2008) • V

Die Gutachter zum 228. Jahrgang der Jahrbücher für Nationalökonomie und Statistik (01.01.2008 bis 31.12.2008) Im Namen der Herausgeber danke ich allen Wissenschaftlerinnen und Wissenschaftlern, die in diesem Zeitraum bereit waren, für die Jahrbücher für Nationalökonomie und Statistik Manuskripte zu begutachten. Mit ihrer Hilfe sind wir dem Ziel, eine möglichst schnelle Entscheidung über die Publikation der Einreichungen herbeizuführen, ziemlich nahe gekommen. Die Autoren konnten die detaillierten Verbesserungsvorschläge aufnehmen, und davon hat die Qualität der Manuskripte stark profitiert. Peter Winker Albert, Max, Universität Gießen Araûjo, Tanya, Universidade Técnica de Lisboa Arntz, Melanie, Z E W Mannheim Backhaus, Jürgen, Universität Erfurt Bartzsch, Nikolaus, Deutsche Bundesbank, Frankfurt am Main Bauer, Thomas, Universität Bochum Bellmann, Lutz, IAB, Nürnberg Bischoff, Ivo, Universität Gießen Bonin, Holger, ZEW Mannheim Brachinger, Hans Wolfgang, Université de Fribourg Breitung, Jörg, Universität Bonn Büttner, Thiess, ifo Institut, München Caporale, Tony, University of Dayton Cornelißen, Thomas, Universität Hannover Crivelli, Ernesto, MPI for Research on Collective Goods, Bonn Daumann, Frank, Universität Jena Dawid, Herbert, Universität Bielefeld Deissenberg, Christophe, Université de la Méditerranée, Les Milles Dosi, Giovanni, Scuola Superiore Sant'Anna, Pisa Dreger, Christian, DIW Berlin Entorf, Horst, Universität Frankfurt Erhardt, Olaf, Fachhochschule Stralsund Feinstein, Leon, University of London Feuerstein, Switgard, Universität Erfurt Fichtner, Wolf, TU Cottbus Fitzenberger, Bernd, Universität Freiburg Fontagné, Lionel, Paris School of Economies, Université Paris 1 Franklin, Joel, P., KTH, Stockholm Frenkel, Michael, W H U Vallendar Garloff, Alfred, IAB, Nürnberg Götz, Georg, Universität Gießen Grimaldi, Marianna, Sveriges Riksbank, Stockholm Habei^ Gottfried, Universität Klagenfurt Haufler, Andreas, Universität München Heilemann, Ullrich, Universität Leipzig Heineck, Guido, Universität Erlangen-Nürnberg Heinemann, Friedrich, ZEW Mannheim Heinze, Anja, ZEW Mannheim Henke, Klaus-Dirk, TU Berlin Hennemann, Stefan, Universität Gießen

Herrmann, Roland, Universität Gießen Hirte, Georg, TU Dresden Höffler, Felix, WHU, Vallendar Holmlund, Helena, London School of Economics Hübler, Olaf, Universität Hannover Hujer, Reinhard, Universität Frankfurt Hülsewig, Oliver, ifo Institut, München Inklaar, Robert, University of Groningen Jerger, Jürgen, Universität Regensburg Jess, Heinrich, Deutsche Rentenversicherung, Berlin Jirjahn, Uwe, Universität Hannover Kaestner, Robert, University of Illinois Kappler, Marcus, ZEW Mannheim Kirchkamp, Oliver, Universität Jena Kosfeld, Reinhold, Universität Kassel Kreuz, Claudia, RWTH-Aachen Kritikos, Alexander, Hanseuniversität Rostock LeBaron, Blake, Brandeis University, Waltham, USA Lechner, Michael, Universität St. Gallen Linz, Stefan, Statistisches Bundesamt, Wiesbaden Maenning, Wolfgang, Universität Hamburg Mandler, Martin, Universität Gießen Markose, Sheri, University of Essex Mause, Karsten, Universität Bremen Mayer, Eric, Universität Würzburg McDonald, Ian Martin, University of Melbourne Meckl, Jürgen, Universität Gießen Menkhoff, Lukas, Universität Hannover Meyer, Wolfgang, Universität Hannover Neuberger, Doris, Universität Rostock Ochsen, Carsten, Universität Rostock Pohlmeier, Winfried, Universität Konstanz Puhani, Patrick, Universität Hannover Puigcerver-Penalver, Maria Carmen, Universidad de Murcia Radulesku, Doina, Universität München Reimers, Cordelia, Hunter College, New York Reitz, Stefan, Deutsche Bundesbank, Frankfurt am Main Rippin, Franziska, Niedersächsisches Landesamt für Statistik, Hannover Ronning, Gerd, Universität Tübingen

VI • Gutachter zum 228. Jahrgang (2008)

Sabates, Ricardo, University of Sussex Scharnagl, Michael, Deutsche Bundesbank, Frankfurt am Main Schefold, Bertram, Universität Frankfurt Scherf, Wolfgang, Universität Gießen Schirmeister, Raimund, Universität Düsseldorf Schnabel, Claus, Universität Erlangen-Nürnberg Schröder, Michael, ZEW Mannheim Schuknecht, Ludger, European-Central-Bank, Frankfurt am Main Schulze, Holger, Universität Göttingen Setzer, Ralph, Deutsche Bundesbank, Frankfurt am Main Spilimbergo, Antonio, IMF, Washington Squazzoni, Flaminio, Universita' degli studi di Brescia Steine^ Viktor, DIW Berlin Stephan, Gesine, IAB, Nürnberg Strulik, Holger, Universität Hannover Tesfatsion, Leigh, Iowa State University, Ames

Tooma, Eskandar, American University Cairo Tykvova, Tereza, ZEW Mannheim Uhlendorff, Arne, IZA Bonn Ulrich, Volker, Universität Bayreuth von Ehrlich, Maximilian, Universität München Vogel, Thorsten, Humboldt-Universität zu Berlin Vollmer, Uwe, Universität Leipzig von der Lippe, Peter M., Universität DuisburgEssen Wagenfels, Gerhard, Universität Hohenheim Wagner, Martin, Institut für Höhere Studien, Wien Westerhoff, Frank, Universität Bamberg Wiese, Harald, Universität Leipzig Winter, Joachim, Universität München Wrede, Matthias, Universität Marburg Yamamoto, Ryuichi, National Chengchi University, Taipei, Taiwan Zwick, Thomas, ZEW Mannheim

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

Inhalt / Contents Abhandlungen / Original Papers Pfann, Gerard A., Daniel S. Hamermesh, Two-Sided Learning with Applications to Labor Turnover and Worker Displacement Hart, Robert A., Yue Ma, Wages, Hours and Human Capital Over the Life Cycle Fitzenberger, Bernd, Wolfgang Franz, Oliver Bode, The Phillips Curve and NAIRU Revisited: New Estimates for Germany Schnabel, Claus, Joachim Wagner, The Aging of the Unions in West Germany, 1 9 8 0 - 2 0 0 6 Kraft, Kornelius, Julia Lang, The Causes and Consequences of Adopting a Works Council Bellmann, Lutz, Knut Gerlach, Wolfgang Meyer, Company-Level Pacts for Employment Jirjahn, Uwe, Thomas Cornelissen, Georgi Tsertsvadze, Parental Background and Earnings: German Evidence on Direct and Indirect Relationships Puhani, Patrick A., Relative Demand and Supply of Skills and Wage Rigidity in the United States, Britain, and Western Germany Stephan, Gesine, The Effects of Active Labor Market Programs in Germany: An Investigation Using Different Definitions of Non-Treatment Hujer, Reinhard, Paulo J.M. Rodrigues, Katja Wolf, Dynamic Panel Data Models with Spatial Correlation Breitung, Jörg, Assessing the Rationality of Survey Expectations: The Probability Approach Ronning, Gerd, Measuring Research Intensity from Anonymized Data: Does Multiplicative Noise with Factor Structure Save Results Regarding Quotients?

423-445 446-464 465-496 497-511 512-532 533-553 554-572 573-585 586-611 612-629 630-643 644-653

Buchbesprechung / Book Review Swann, G.M. Peter, Putting Econometrics in its Place A New Direction in Applied Economics Bandinhalt des 228. Jahrgangs der Zeitschrift für Nationalökonomie und Statistik Contents of Volume 228 of the Journal of Economics and Statistics

654

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

Contributions to Labormetrics: Guest Editorial In a paper published in the April 2 0 0 0 issue of the Industrial and Labor Relations Review Daniel Hamermesh introduced the term Labormetrics (that he attributes to Steven G. Allen) to describe the application of econometric techniques to issues related to the labor market. Such applications are numerous, covering all fields of labor economics from labor supply and labor demand to micro econometric studies of wages and macro econometric studies of unemployment and inflation. Modern labor economics textbooks are in large parts textbooks in applied econometrics, too, and many econometric techniques were developed or further refined with a view to analyze labor market topics (e. g., the application of sample selection models to the analysis of female wages, or the use of matching techniques to analyse the impact of labor market programs). The Jahrbücher für Nationalökonomie und Statistik have a long lasting tradition in publishing papers that apply econometrics to labor market issues, and the contributions in this special issue fit into this tradition: The first two papers by Gerard A. Pfann and Daniel S. Hamermesh, and by Robert A. Hart and Yue Ma can be considered as prototypes of this literature. Both papers deal with an important aspect of labor markets (labor turnover and worker displacement, and wage-hours contracts), build a theoretical model, and then test its implications empirically using micro data. The next seven contributions consider aspects of the German labor market. Bernd Fitzenberger, Wolfgang Franz and Oliver Bode present new estimates of a Phillips curve and the NAIRU. Claus Schnabel and Joachim Wagner, Kornelius Kraft and Julia Lang, and Lutz Bellmann, Knut Gerlach and Wolfgang Meyer consider institutions that shape the German labor market - unions, works councils, and company-level pacts for employment. Aspects of the wage structure in Germany are investigated in the papers by Thomas Cornelissen, Uwe Jirjahn and Georgi Tsertsvadze, and by Patrick Puhani, who additionally compares the results for Germany with findings for Britain and the United States. Gesine Stephan reports new results on the effects of active labor market programs in Germany. The last three papers of this issue have a focus on new empirical methods. Reinhard Hujer, Paulo J. M. Rodrigues, and Katja Wolf discuss dynamic panel data models with spatial correlation, Jörg Breitung deals with methods for the quantification of survey expectations, and Gerd Ronning looks at the consequences of using joint anonymization of all variables in a set of micro data by multiplicative noise for the research potential of scientific use files. The authors of the contributions to this issue dedicate their papers to their friend and colleague Olaf Hübler, a labormetrician par excellence, on the occasion of his 65th birthday on March 5, 2009. For many of us he has been a role model for many years - may this continue for many years to come! Lutz Bellmann, Wolfgang Franz, Knut Gerlach, Reinhard Hujer, Wolfgang Meyer, Joachim Wagner

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2 0 0 8 ) Bd. (Vol.) 2 2 8 / 5 + 6

Two-Sided Learning with Applications to Labor Turnover and Worker Displacement By Gerard A. Pfann, Maastricht, and Daniel S. Hamermesh, Austin* JEL J33, J63 Learning, job loss, quits, layoffs.

Summary We make several extensions to the recent literature on job loss while modernizing the very early job-displacement literature. After constructing a dynamic model of two-sided learning between a firm and its workers, we estimate it using personnel data from Fokker Aircraft that cover the path of layoffs and quits through its bankruptcy in March 1 9 9 6 . We find that the firm learns about workers' loyalty (demonstrating the role of information in repeated cooperative principal-agent relationships), while workers do not learn (consistent with earlier empirical results on American workers). The type of data that we use also generates information on the value of learning and on whether and how the characteristics of workers who remain until the firm's death differ from those of all affected workers. It thus allows us to measure the increases in the firm's value from learning about its workers' behavior and to infer the extent of biases in estimating losses from displacement from samples restricted to displaced workers.

1

introduction

T h e modern literature on worker displacement (surveyed by Fallick 1 9 9 6 , and recently extended t o Europe by Burda/Mertens 2 0 0 1 ) is based almost exclusively on household data describing the pre- and post-displacement experiences of workers or, in a few cases (e.g., J a c o b s o n et al. 1 9 9 3 ) on establishment information that generates similar data. This information is ideal for measuring the losses o f those workers w h o actually wind up being displaced. So long as workers anticipate a shutdown or firms layoff workers non-randomly before the shutdown, however, the potential non-randomness o f these sources o f self-selection o f workers from a declining firm means that these data do not allow us to measure the average loss that the shutdown generates. A plant shutdown is not an experiment whose impact we can infer by comparing displaced to other workers. As in many other examples where selection on one or both sides o f the m a r k e t c o m e s into play ( H e c k m a n et al. 1 9 9 8 ) , we need information on workers' mobility over the firm's pre-shutdown history t o evaluate whether the losses estimated

* Professor of econometrics and organization, Maastricht University, research associate and fellow, C E P R and IZA; Sue Killam Professor in the Foundations of Economics, University of Texas at Austin, and research associate, N B E R and IZA. We gratefully acknowledge the constructive comments and suggestions of the referees. The paper has benefitted from the many discussions during presentations at seminars, workshops, and conferences. We thank Ben Knuppe, one of Fokker's bankruptcy trustees, for making the personnel data available to us.

424 • G.A. Pfann and D.S. Hamermesh

for workers w h o are actually displaced provide an unbiased estimate of the losses of all workers affected by the eventual closing. T h e process of worker-firm interactions t h a t lead up to a plant closing is missed by a literature t h a t concentrates on comparisons of displaced w o r k e r s ' pre- and post-displacement earnings. If the agents are rational, that process must involve attempts by both sides t o gather i n f o r m a t i o n a b o u t each other's expectations and intentions, i n f o r m a t i o n that is partly revealed by the firm's recent turnover history. 1 Moreover, the typical firm is not accustomed to decline and needs i n f o r m a t i o n to design an optimal policy t o adjust d o w n w a r d s . This i n f o r m a t i o n m a y be collected optimally during a sequence of d o w n sizing operations. Even in times of low u n e m p l o y m e n t plant closings account for a substantial fraction of job losses (Dunne et al. 1989, Farber 1997); and while displaced w o r k e r s can o b t a i n jobs at such times, many will lose some or all of the firm-specific h u m a n capital and other quasi-rents that they had obtained in their previous employment (Kletzer 1989). T h e problem of w o r k e r displacement - the magnitude of displaced w o r k e r s ' losses, a n d the process by which investment in h u m a n capital adjusts as a firm declines t o w a r d shutd o w n - should be of interest regardless of the overall state of the labor m a r k e t . The a n n u a l labor cost attributable to workers involved in plant closings is large. For example, in 2 0 0 6 we estimate this to be nearly $ 10 billion in U.S. m a n u f a c t u r i n g alone. 2 In order t o understand the size of the annual savings t o employers resulting f r o m their learning during mass layoffs that lead u p to the closings, we need t o k n o w the length of time between preliminary layoffs a n d plant closing, w h a t fraction of w o r k e r s involved in the closing previously experienced a mass layoff, a n d h o w m u c h firms' learning allows t h e m t o save on the costs of those workers w h o are retained. Interestingly, economists' focus on displacement in the 1950s and early 1960s w a s as m u c h on the process of displacement as on w o r k e r s ' post-displacement a d j u s t m e n t . Those studies (e.g., Shultz/Weber 1966) had the data required to analyze i n f o r m a t i o n exchanges along the p a t h to displacement, but the necessary theoretical and econometric tools were lacking. In this study we try t o remedy w h a t we believe are holes in recent research on mobility while updating/modernizing the early displacement literature. We have data describing workers at each episode along the road to the eventual demise of a large D u t c h corporation. These data allow us t o examine the various modes of turnover before the firm's death and to use t h e m to infer h o w w o r k e r s and the firm learn a b o u t the firm's prospects and the w o r k e r s ' intentions. The data enable us to study whether and h o w the characteristics of workers w h o remain until the firm's death differ f r o m those of all of its affected w o r k e r s and thus to infer the extent of biases in measuring the losses arising f r o m displacement w h e n the sample is restricted to w o r k e r s w h o are actually displaced. The richness of the data set a n d the questions it allows us to examine more than offset any 1

2

Hamermesh (1987) used household data on the time path of wage-tenure relationships to infer learning on the workers' side of this information exchange. While useful, such data cannot provide a picture of the extent and types of labor turnover generated as a firm heads toward oblivion. Assume, following Farber's 1997: Table A-6 calculations, that the fraction 0.015 of manufacturing employees lost their jobs in 2006 due to plant closings. Average annual earnings in manufacturing are $ 16.73*41.1*52, and there are 14.215 million manufacturing employees. Assume also that non-wage costs are 20 percent of wages. Then the annual labor cost attributable to workers involved in plant closings in manufacturing is $ 9.1 billion. Since Farber includes only workers with at least three years of tenure with the firm, his numbers, and thus our estimates, are probably lower bounds.

Two-Sided Learning with Applications to Labor Turnover and Worker Displacement • 425

potential biases t h a t might result if the firm is unrepresentative of large firms that disappear. In the next section we present a stylized model of learning by workers and firms t h a t stresses the exchange of i n f o r m a t i o n between the t w o parties. In Section 3 we describe our data and provide s u m m a r y statistics charting the firm's demise, while in Section 4 we estimate an empirical version of the model presented in Section 2. Section 5 uses data on the entire pre-displacement history of the firm in order to infer the selectivity-adjusted losses generated by w o r k e r displacement, while Section 6 illustrates the m o n e t a r y gains a firm w o u l d m a k e if it accounted for learning in structuring its layoff policies. 2

A model of two-sided learning

Downsizing n o t only dislocates workers. It also changes the prospects of the workers w h o remain with the firm. A firm hit by a sequence of negative shocks t h a t result in w o r k f o r c e a d j u s t m e n t s can learn a b o u t h o w the quit behavior of its workers is affected by the a d j u s t m e n t s a n d can u p d a t e its firing policy accordingly. Workers w h o remain also have the opportunity to learn a b o u t the firm's preferences and can likewise update the i n f o r m a t i o n that enters their decision a b o u t quitting. We develop a two-sided learning model of the firm that accounts for these changes during downsizing episodes. Adjustm e n t of earnings during displacement is a c o m m o n l y addressed issue (see, e.g., Carneiro/ Portugal 2006); learning a b o u t w o r k e r s ' abilities in the context of analyzing wage dynamics has been studied before (Farber/Gibbons 1996, Felli/Harris 1996, Altonji/Pierret 2001), as has learning in the context of shocks to production (Francois/Roberts 2003); but the general issue of two-sided learning in the context of employment decisions has not heretofore been analyzed in a way amenable to empirical analysis. We assume that the firm faces fixed costs of firing. W h e n shocks arrive the firm must decide whether to downsize or not, and if it downsizes it does so by lumpy a d j u s t m e n t s ( H a m e r m e s h 1989, Pfann/Verspagen 1989). Under a fixed-cost regime there is an option value for the firm of waiting t o adjust, and during that period some workers decide to leave (Pfann 2006). A n n o u n c e m e n t s of c o r p o r a t e restructuring change the values of contracts between the workers and the firm, a n d wage a d j u s t m e n t s may be needed t o continue some of the relationships, or unintended separations may follow (see also McLaughlin 1991, Pfann 2001). We specify the following sequence of responses. An ann o u n c e m e n t f r o m the firm's m a n a g e m e n t arrives at the beginning of the first period when the employer and the employees are unacquainted with the each other's response behavior. T h e a n n o u n c e m e n t is considered as an unanticipated shock by the employees. Some workers will respond t o that shock w i t h o u t having observed the firm's management's actual realization of the a n n o u n c e d action. Upon these actions the employer forms beliefs a b o u t the intended behavior of all workers, infers f r o m that h o w other - incumbent w o r k e r s c o m p a r a b l e t o those acting could have responded but did not, a n d determines w h o should be fired a n d w h o should not. Waiting a n d collecting this extra i n f o r m a t i o n is an optimal strategy for an agent t h a t faces irreversible costs of a d j u s t m e n t . 2.1 The initial episode of decline

If the firm is hit by an unexpected shock in p r o d u c t d e m a n d that makes a d o w n w a r d a d j u s t m e n t of its w o r k f o r c e imperative, neither it nor its w o r k e r s k n o w s a b o u t the outcomes of each other's strategic choices in response to that shock. In accordance with the

426 • G.A. Pfann and D.S. Hamermesh

observed response behavior (cf. Pfann 2001: Figure 1), we assume that workers act first and that the firm waits to adjust until after it has observed its workers' responses. Worker-initiated

separations

during the initial

episode

The firm employs N\ tenured workers. First we consider optimization by worker i, i = 1 , . . . , Ni. She makes a decision whether or not to stay in the firm and continue making firm-specific investments based on a comparison of the expected streams of future earnings inside and outside the firm. Her decision under uncertainty is written as Qa = Q * ( X , i ; e , 1 ) ,

i=l,...,N,

(1)

is a vector of where q'n is the unobserved quit propensity of worker i during Episode individual characteristics explaining Q"n, and e,i is a worker-specific normally distributed error with zero mean and variance erf)2. Although Q*j is unobserved, other workers' behavior reveals to the firm which workers are likely to quit. Denote Q,i = 1 if Q", > 0 for the Np worker-initiated separations, and Q,i = 0 if Q*j < 0 for the Nf = Ni — Np workers who stay until the end of the first episode. The probability of observing that worker i quits is Pr{Q,i = l } = ^ 1 / < T p ) X , i ] ,

(2)

where is a vector of unknown parameters. A trade union might provide information to the worker about the employer's possible reneging on what workers believe to be an implicit contract (Hogan 2001), but we ignore that intermediation here. For our purposes, it does not matter if the worker's behavior is mediated by a trade union. Employer-initiated

separations

at the end of the initial

episode

The optimizing firm decides whom to layoff by comparing the expected stream of a worker's future wages to his future productivity. The unobserved propensity to fire worker i in Episode 1, F'a, is written under uncertainty as F*! =F*(Z, 1 ;v,i),

i= 1, • • •, Nf,

(3)

where Z,i is a vector of the individual worker's characteristics explaining F'n, and u,i is a worker-specific normally distributed productivity shock with zero mean and variance Firing decisions are related to the worker's age. In general, after an initial period of increase, a worker's productivity declines with age. To avoid shirking the firm will fire the most experienced workers with the lowest output (Stiglitz/Weiss 1983). Firing can also be explained by the firm's (asymmetric) information about the worker's performance. Annual evaluation scores, which may be included in Z, measure relative performance, and low-scoring workers have a higher chance of being fired. In its layoff decision at the end of the initial episode the firm incorporates the quit behavior of the workers that it observed during the episode. Firing decisions also depend on statutory replacement costs that vary among workers. Given a worker's productivity, this variation is in large part due to differences in tenure at the time of firing. An announcement of workforce reorganization changes the contingent contract between the worker and the firm. This may discourage some workers, who interpret the announcement as a departure from the informal agreement with the employer. The firm

Two-Sided Learning with Applications to Labor Turnover and Worker Displacement • 427 sees workers stay who are observationally identical to those who quit and realizes that these workers have, ceteris paribus, a high reservation wage w], or a low enThe firm can either react non-cooperatively or cooperatively. On the one hand, it can interpret a worker's low e,i as too high a reservation wage. In that case, the non-cooperative firm will match it with a high v,i, so that corr(v,i,e,i) = p\ < 0. On the other hand, the cooperative firm can observe e,i to learn about a worker's loyalty to the firm when things turn bad. A high reservation wage - a low e,i - signals loyalty to the firm. Especially in times of economic distress, disloyal workers can be extremely harmful to the firm. In a model of monitoring cooperative agreements in a repeated principal agent relationship, Radner (1981) showed that the principal (the firm) observes the agent's (the worker's) disloyalty by means of a "statistical method of detecting 'cheating' by the agent rapidly enough to deter him from doing so" (1981: 1128). Radner does not say what that method is. We propose a method for detecting idiosyncratic disloyalty based on each worker's observed reservation wage. If the firm's objective is to identify and retain the most loyal workers, it will couple a low e,i with a low v,i, so that p\ > 0. In accordance with Radner's results, disloyalty is especially harmful to a firm that faces a high bankruptcy risk. Even though one might rationalize either sign for this correlation, a positive correlation should become more likely as the firm's chance of demise increases. F'n is revealed in part to worker i when she sees other workers being fired. F,i = 1 if F'rj > 0, for Nf workers. Others are allowed to stay with the firm until the beginning of Episode 2, so that F,\ = 0 if F'n < 0 for Ni = Nf — workers. The probability individual i is fired at the end of Episode 1 conditional on not having quit during Episode 1 is Pr{F„ = l|Q,i = 0} = ® = dQ*/dF > 0. The arrival of new information on which workers base their quit decisions might indicate, for example, an unexpected continuation of deficient demand for the firm's product. This could reverse the signs of both derivatives. Observing WQ( > 0 then suggests that similar workers continue quitting as they did before, while a>£ < 0 suggests that workers who were not fired earlier are now quitting. This behavior could suggest and hence identifies - a change in beliefs about the permanence of the decline in product demand. The expectations that workers form about the likelihood of being fired at the end of this episode are based on a rational decision process that uses what occurred at the end of Episode t-1. The information used by the employer at the end of the current episode t that renders o„ different from u„_i is unknown to the worker at the time of the quit decision during Episode t and is thus uncorrelated with Q*. There are two ways the worker can interpret the observed v,t-\ and act on that interpretation. On the one hand, low signals that, compared to observationally equivalent colleagues, she was unlikely to be fired during the last episode. As a consequence workers like her have become scarce to the firm. This would raise her reservation wage, wrt, and lower e/(, so that corr((vf_i,e,-t) = pp > 0. On the other hand, she might also think, "I escaped unexpectedly last time, but I did not quit, so I may be on the chopping block this time." This could lead her to reduce her reservation wage and raise en, so that />p < 0. In this case too one might rationalize either sign for the correlation. Unlike the declining firm's decisionmaking process, for workers we cannot predict its direction and how it may evolve as the firm approaches its demise. Given (5) the conditional probability that worker i quits during episode t is: Pr{Gi/ = l | f , - . - i = 0 } = + > + >

o

I

N Ur_

0

m

w

a 1 1

I

rs + A LL. ^m |

+

x:

2

m

•o XI rt o -Q O

Q I it

o

-O

Q I VJ I

(B O

U I

-Q (0 -O

to

+

o

I a

U I 5 Q

i

A

O I

O

|

-C

R-

O

A

I

I

•o XI n) o -c XI at O

I

iT

Q

M

+

XJ O CL

n) -Q O

oh

n) +

-O

XI + n) XI O S a. I

fN .c * n

Q5 A

ULJ

CM+ *

_Q Q. Lrt >, nJ CO

+ Sm 5A

I

|

rr> m sr LU

8?-

+

452 • R.A. Hart and Y. Ma (iii) The worker stays at the end of period 1 In this event, Vs is expressed further as the sum of returns of three mutually exclusive and exhaustive events similar to V2 (see Table 1) Vs = (1 - * 2 ) . ( 1 - Q2).F3.[(1

- S ) . W I

+ g.M2).(l-Ô).h3f

-

D(h3f)}

(the worker is fired at the end of period 2) + ( 1 - F 2 ).(l - Q 2 ).(l - F3).Q3.{[«M1 -S) +gM1).{\-Ô)

+ g.M3}.h3q -

D{h3q)}

(the worker quits at the end of period 2) + ( 1 - f 2 ) . ( l - Q 2 ) . ( l - F 3 ) . ( l - Q 3 ).{[(wi.(1 -S) + M 2 ) . ( 1 -S) + m3 + E(03\e3

+£(«73173 >

> e\)].h

-

D(h3)}

(the worker stays at the end of period 2)

(8)

where h3f and h3q are the expected hours outside the firm if the worker is fired or quits, respectively. (c) Model

solutions

We deal first with periods 1 and 2. From the first-order conditions to the problem of maximising wealth in (5) - derived in Theory Appendix (a) - we obtain w2 = (1 - ô).wi +M2+

E(t}2\rh > rf2) > wi

(9)

and a - Qi-\p + y-g-M2] - (1 - Q2).[h2.E(e2\02 +[T + g.M2.(l - S).h3f] + w2.h2] = 0.

> e*2) - C(M 3 ) -

D(h2) (10)

Derivations of (9) and (10) are given in Results Appendix (b). Expression (9) provides the well known outcome, illustrated in Figure 2 (a), that the contractual wage rate rises with tenure, or w'2 > w\. Similar to the proof in Hart and Ma (2000), we can also show that working hours allocated in the post-investment period, hours

hourly wage rate

h "2 *

w. period

period (a)

1

Figure 2 Wage and hours profiles

2

(b)

Wages, Hours and Human Capital Over the Life Cycle • 453

conditional on satisfying a marginal disutility constraint, also rise relative to period 1 hours, or h*2 > h\. Thus, we have the hours profile illustrated in Figure 2 (b). An optimal solution to the problem of maximising wealth in (8) cannot be attained through the choice of a single hourly wage rate, however. The problem is that the parties are seeking to minimise sub-optimal quits and layoffs, with an eye towards the outside wage, as well as achieving the optimal length of working hours. Intuitively, at least two instruments are required in order to achieve these mutually supportive objectives. Hart and Ma (2000) establish that if an "overtime" premium is paid then contract efficiency is established. This does not rule out the use of other instruments, such as bonus payments (Hashimoto 1979) or fixed seniority promotion rules (Carmichael 1983). We now deal with period 3. A summary of the expected lifetime wealth, together with the first-order conditions (f.o.c's) for wealth maximisation are set out in the Results Appendix (a). From the f.o.c's (A3) to (A6), it is easily established that workers will quit whenever satisfaction is below 0 i ; that is, Bi r,'2)\

(11)

and 03 < B\ = \M+gM2.( 1 - S).h3q + g.M3.h3q]/h3

- [B/h3 + E(ti3|//3 > «?;)].

(12)

Further, the firm will fire the workers whenever productivity is below >/*; that is »72
0\)]

(13)

and >73 < l\ = {[' + S-M2.{\ - S).h3f] -

+ g.M2.{l

- S).h3q +

[ M l - Qi)} - [B/^3 + E(02\e2 > 0*)]

gMyh^]}/ (14)

These results state that the party wishing to separate must be made to internalise the entire expected losses from the separation at each period over the working life. Next we show that it is possible to formulate a wage-hour contract in terms of the parameters of f]'j and 6j to satisfy the first-order conditions (A3) to (A6). For period 3, there exists a wage-hour contract which can minimise the sub-optimal separation of the two parties, with (w\, h'3), satisfying the following two equations: w3 = (1 -5f.wx

+ M 2 . ( 1 -S) + M 3 +£fa3|i73

> nl)

(15)

and [t + g.M2.( 1 - S).h3f} - Q3> - ( 1 - Q3).[h3.E(03\e3

+ g.M2.( 1 - S).h3q +

g.M3.h3q]

> e\) - D(h3) + w3.h3] = 0

Equations (15) and (16) are derived in Theory Appendix (c).

(16)

454 • R.A. Hart and Y. Ma

4

Life cycle changes in investments, wages and hours

The optimal wage-hour contract (w*2, h*2, w\, h*}) the level of human capital investments (M2, M j ) are obtained by solving equations (9), (10), (15), (16), (A7) and (A8) simultaneously. In this section, we investigate four sets of questions that arise from these solutions. What are the implications of our model for (a) the level of human capital investment over the life cycle; (b) the level of hours over the life cycle; (c) the income effect on hours in the post-investment period compared to the previous period; (d) the effects on wages and hours life-time schedules of separation before period 3? We deal with each issue in turn. (a) Human capital investments We might expect that, given the retirement constraint, the optimal level of human capital produced by the training investments will rise initially and then fall as the worker becomes older. In effect, for given investments, the age of retirement serves to shorten the potential length of amortisation of period 2 compared to period 1 investments. We show formally in the Theory Appendix (d) that such an outcome is predicted by the model. Providing quit and layoff probabilities as well as the depreciation rate are small, we obtain the outcome M2 > M3 > 0

(17)

that is, returns to human capital investments that are realised in period 3 are less than those realised in period 2. Ceteris paribus, our results suggest that wages and hours rise with experience due to rent sharing and, moreover, the two profiles are concave. In terms of the wage rate, the analysis provides a theoretical underpinning of the slope and shape of the Mincer-equation (Mincer 1974). (.b) Hours There are four explicit conditions and one implicit condition to guarantee that ¿>3 rises above h2 (see Hart/Ma 2000): (i) (ii) (iii) (iv) (v)

outside working hours are not far away from ^3; the quit probability Q3 is not too high; the marginal disutility of work D'(b{) is not too large; D(0) = 0, D'(-) > 0 and D"(-) > 0; w3 > w2.

Conditions (ii) and (iv) may well hold in period 3 as the worker is approaching retirement. However, (i) and (iii) may not hold. This implies hours may fall in the pre-retirement period, independent of the wage. Furthermore, condition (v) may not hold in period 3 either. 3 This again implies that the hours may fall in period 3. 3

W h a t can w e say a b o u t the e x p e c t e d v a l u e of W3 relative t o W2? C o n s i d e r e q u a t i o n (15). It is clear that there are t w o i n f l u e n c e s o n the value of W) that serve t o render the o u t c o m e relative t o w2 as an o p e n empirical q u e s t i o n . F r o m (15), if there w e r e n o h u m a n capital i n v e s t m e n t in period 2 , w i t h the result that M 3 = 0, t h e n w e w o u l d u n e q u i v o c a l l y o b t a i n w-$ < w2 due t o the e f f e c t of the i n v e s t m e n t d e p r e c i a t i o n term, 0 d o e s n o t ensure the reverse w a g e i n e q u a l i t y b e c a u s e w e h a v e established in ( 1 7 ) that h u m a n capital i n v e s t m e n t M3 w i l l be less t h a n M 2 . In o t h e r w o r d s , it w o u l d r e m a i n the case that w 3 < w i if the i n v e s t m e n t M 3 falls steeply e n o u g h s o as n o t t o o f f s e t the h u m a n capital d e p r e c i a t i o n . T h e r e f o r e , relative sizes of wj a n d wi c a n n o t be d e t e r m i n e d a priori.

Wages, Hours and Human Capital Over the Life Cycle • 455

(c) Income effects on hours In order to gain a deeper insight into period 3 relative to period 2 hours, we need to consider the income effect on hours. From equation (10) we have a l o g ( h 2 ) / & o g ( w 2 ) = -w2/\w2

+ E(62/62 > e\) - D'(h2)}

(18)

+ E(63/63

(19)

While by equation (16) we have dlog(h3)/dlog(w3)

= -w3/[w3

> e\) - D'(h3)}

Comparing (18) and (19), we can find that the following three factors increase the income effect of period 3, relative to that of period 2. These are: (i)

w3 < w2;

(ii)

03 < d2, i.e. job satisfaction may be lower when a worker gets older;

(iii) D'(h3) i i )

D(h2)}

(stays at t i )

+ ( 1 - f 2 ) . ( l - Q 2 ) . { F 3 - [ ( ^ i • ( ! " t,\) + E{63\e3 > 0*3)].h3} where (f>, a, /?, y, t, and n, are constants.

(A2)

462 • R.A. Hart and Y. M a

The first order conditions satisfying max V are 0V/d6* = dV/drj" = 0(i = 2,3): 0 V / 9 n \ = ftf2).{a

- Q2.\fi + y.g.M2] - (1 - Q2).[A + h2.E(02\92 > 0*2)]

-(1 - Qi).h2.fi'2) = 0

(A3)

dV/de; = ((1 - F2).q(6l).{\p + y.gM2] ~[A + h2.E(r,2\r,2 > r,'2)} - h2.6'2} = 0 (A4) and dV/df,; = f{r,'2).{[x + gM2.{\-S).h3f]

- Q3.\n+g.M1.{l-6)h3q

-(1 - Q3).[B + h2.E{62\92 > e\)\ - (1 - Q3).h3-S3} dV/d0'3 = (l-F3).q(er3).{lp+gM2.(l-g).h3q

+ g.M3.h3q]

=0

(A5)

+g.M3.h3q]

-[B + h3.E(t]3\rj3 > rf3)\ - h3.6*3} = 0

(A6)

(b) Period 2 wage-hour contract The optimal period 2 wage-hour contract is obtained as follows. If the firm decides to fire a worker at the end of period 1, then (1 — S).w\ + M2 +

tj2 20 years Age Age 2 Establishment size 20-99 employees Establishment size 100-199 employees Establishment size 200-1999 employees Establishment size > 2000 employees East German establishment University degree Apprenticeship Occupation dummies Industry dummies Existence of works council in 2001 and 2006 Introduction of works council between 2001-2006 Time dummy (year = 2006) Introduction of works council * 2006 N Pseudo R 2

Coefficient 0.001 0.027 0.002 0.069 - 0.209 - 0.003 0.136 0.157 0.182 0.213 - 0.927 0.391 0.335

t-value 0.01 0.28 0.02 0.64 - 8.23*** - 8.60*** 1.32 1.24 1.57 1.81* - 14.68*** 2.96*** 3.12*** * * * *

-0.109 -0.419 - 0.644 0.520 6144 0.09

•**/**/* indicates statistical significance at the 1 %, 5 % and 1 0 % level. Source: GSOEP waves 2001-2006, own calculations.

# *

- 1.21 - 2.38** - 11.17*** 2.31**

The Causes and Consequences of Adopting a Works Council • 527

Table 5 The Effect of the Introduction and Existence of Works Councils on In (Wages) Variable Tenure 5 - 1 0 years Tenure 10-15 years Tenure 15-20 years Tenure > 20 years Age Age 2 * 1 0 - 2 Female Establishment size 20-99 employees Establishment size 100-199 employees Establishment size 200-1999 employees Establishment size > 2000 employees East German establishment University degree Apprenticeship Occupation dummies Industry dummies Year = 2006 Existence works council in 2001 and 2006 Introduction of works council between 2001 -2006 Introduction *2006 Intercept N Adjusted R2

Coefficient

t-value

0.028 0.062 0.080 0.104 0.029 - 0.030 - 0.200 0.014 0.021 0.051 0.096 - 0.236 0.173 0.050

2.13** 4.41*** 5.15*** 6.85*** 8.98*** - 8.21*** -23.28*** 1.03 1.26 3.34*** 6.11*** - 27.58*** 10.12*** 3.59*** t*t *

0.088 0.119 0.073 -0.012 2.937

* *

11.25*** ^ 99* * * 2.62*** -0.35 40.14***

5047 0.54

••*/**/* indicates statistical significance at the 1 %, 5 % and 10 % level. Source: CSOEP waves 2001-2006, own calculations.

significantly higher wages t h a n the small firms, which are considered by the constant term. Hence in accordance with empirical evidence f r o m other countries w e also find a size p r e m i u m for wages. Employees w o r k i n g in establishments which h a d a w o r k s council in 2 0 0 1 as well as in 2 0 0 6 , and also persons working in firms, which introduced a w o r k s council, earn higher hourly wages. But the introduction of a w o r k s council itself does not lead t o higher wages. To the contrary, the coefficient of the interaction term, which indicates the additional effect of an introduction, is even negative (although not significant). Companies, which introduce a w o r k s council already have paid higher wages before the adoption has taken place. T h e introduction of the w o r k s council does not lead to a w a g e increase, but also not to a significant decrease of remuneration. Since i n f o r m a t i o n on the existence of w o r k s councils is only available for 2 0 0 1 a n d 2 0 0 6 the variable "introduction of a w o r k s council" and the interaction term are highly correlated (r = 0.73). In view of the resulting high standard error of the interaction term, w e additionally r u n separate estimations for the samples 2 0 0 1 and 2 0 0 6 . Applying a Wald test on significant differences between the coefficients, which takes account of the t w o variance-covariance matrices, confirms our result f r o m the difference-in-differences approach. T h e t w o coefficients (based on the t w o samples) of the d u m m y variable for the introduction of a w o r k s council are not significantly different f r o m each other.

528 • K. Kraft and J. Lang

Table 6 The Effect of the Introduction and Existence of Works Councils on Overtime Hours Variable Regular working hours Tenure 5-10 years Tenure 10-15 years Tenure 15-20 years Tenure > 20 years Age Age 2 Female (not married, no children) Wife (no children under 16) Mother (with children under 16) Establishment size 20-99 employees Establishment size 100-199 employees Establishment size 200-1999 employees Establishment size > 2000 employees East German establishment University degree Apprenticeship Occupation dummies Industry dummies Time dummy (year = 2006) Existence works council in 2001 and 2006 Introduction of works council between 2001-2006 Introduction *2006 Intercept N

Homoscedastic Tobit

Heteroscedastic Tobit

- 0.038 -0.133 - 0.090 -0.152 - 0.361 0.252*** - 0.003*** -0.759*** - 1.481*** -2.287*** 0.602** 0.671** 0.574* 0.509 0.403** 2.052*** 0.852***

- 0.052** -0.011 -0.137 - 0.267 - 0.337 0.280*** - 0.003*** -0.508*** - 1.383*** - 1.868*** 0.559** 0.516* 0.550* 0.438 0.216 2.510*** 1.404***

* » * ** *

- 1.356*** - 1.046*** - 1.327*** 0.197 - 1.276

** * ## *

- 1.218*** -0.854*** - 1.173*** - 0.005 - 2.292

5047

•«*/**/* indicates statistical significance at the 1 %, 5 % and 10 % level. Source: GSOEP waves 2001-2006, own calculations.

Finally, we investigate the influence of works councils on overtime hours. Earlier studies report mixed results (Hubler/Meyer 1 9 9 7 , Kolling 1997, Schank/Schnabel 2004), yet only the existence of a works council was taken into account. Our estimation results for the effect of a works council's existence and formation on overtime hours are presented in Table 6. In addition to a homoscedastic tobit model we estimate a heteroscedastic tobit model. If heteroscedasticity exists, the coefficients would be inconsistent in the first case. Except for a few variables both estimations produce similar results. Most of the considered determinants of overtime are significant. In the homoscedastic tobit model regular working hours have no impact on overtime, but employees in East German establishments report working more overtime. If heteroscedasticity is taken into account the significance of the variables (but not the signs of the coefficients) is reversed. Regular working hours have a negative impact on overtime, whereas the coefficient of the dummy for firms in East Germany is insignificant. Tenure has no significant effect in either model but the coefficients for age point to an inverted u-shaped structure. Female employees work less overtime than male workers, especially if they are married or have younger children. Overtime hours increase with education level. For all considered size classes with at least 20 employees and 2000 at most, persons work more overtime than in very small establishments with less than 20 employees. Generally, overtime hours decreased during the considered period.

The Causes and Consequences of A d o p t i n g a Works Council • 5 2 9

In contrast to wage determination, works councils enjoy explicit co-determination rights to limit overtime work. Both in establishments where a works council exists as well as where it is adopted, overtime hours are significantly lower, but the introduction is not responsible 14 . Hours were already lower before a works council was installed. 6

Conclusion

We investigate the determinants of forming a works council in German firms using two panels. In the first place, the IAB-establishment panel is applied and, secondly, information on workers derived from the German Socio-Economic Panel is applied. The expectations of the top management with respect to business conditions and employment change have no impact. Concerns with respect to job security are positively related to the probability of a works council being established. These concerns are reduced if such a newly founded works council is in effect. Works councils do not affect wages and turnover. These results are also in line with the Works Constitution Act, where negotiations on wages are not allowed. But overtime working also remains unaltered, although in this respect co-determination rights exist, which grants the works councils quite explicit veto rights. According to our results, works councils are not adopted in order to increase bargaining power and to acquire a larger part of the rents. Due to the fact that turnover is already low before the works council is installed, we conclude that a workforce with low quit rates and a long-term interest in a firm's existence and performance asks for a works council, but the introduction has no impact on turnover behaviour (as it is frequently claimed). It seems that both the negative effects expected (by the critics) as well as the positive effects of works councils expected (by the supporters) are overrated. The estimated impact is largely due to the use of cross-sectional data, neglecting selectivity as well as firm-specific effects. Although the number of observations used for our study is not small, it would be useful to have access to information on many more firms in which works councils are adopted. This would render the test much more powerful. It also turns out that some firms abolish their works councils. Hence there is an additional research question: What are the reasons for and the effects of abolishing a works council?

14

A Wald test on equality of the coefficients of the dummy variable for the introduction of a works council (based on separate estimations for 2001 and 2006) confirms this result. There is no significant difference between the two coefficients.

530 • K. Kraft and J. Lang

Appendix Table A1 Matching Quality: Difference of Mean Values/ Mean Standardized Bias Variable

Before Matching

After Matching

Difference of mean values Ln(number of employees) Share of blue-collar workers Share of part-time employees Share of female employees Branch plant (yes = 1) East German establishment (yes = 1) Limited liability (GmbH, AG = 1) Collective bargaining (yes = 1) Profit sharing scheme (yes = 1) Employee share ownership (yes = 1) Profit situation (t-1, good/very good = 1) Expected sales next year (increasing = 1) Expected employment next year (increasing = 1) Expected employment in five years (1 = sharply/somewhat higher) Mean standardized error Bias Reduction

1.50*** - 0.09*** 0.02 0.06** 0.31*** -0.12*** 0.21*** 0.21*** 0.05* 0.04** -0.03 0.14*** 0.08**

0.03 -0.04 0.03 -0.00 -0.06 -0.03 0.05 -0.07 0.01 0.03 -0.02 -0.04 -0.04

0.07**

-0.01

26,57

4,99 0.81

***/*•/* indicates statistical significance at the 1 % , 5 % and 10 % level. Source: IAB Establishment Panel, waves 2001-2006, own calculations (controlled remote data access via FDZ).

References Addison, J.T., L. Bellmann, K. Schnabel, J. Wagner (2003), German Works Councils Old and New: Incidence, Coverage and Determinants. Schmollers Jahrbuch, 123: 339-358. Addison, J.T., L. Bellmann, C. Schnabel, J. Wagner (2004), The Long-Awaited Reform of the German Works Constitution Act. Industrial Relations 43: 392—420. Addison, J.T., C. Schnabel, J. Wagner (2004), The Course of Research into the Economic Consequences of German Works Councils. British Journal of Industrial Relations: 42: 255-81. Addison, J.T., K. Schnabel, J. Wagner (1997), On the Determinants of Mandatory Works Councils in Germany. Industrial Relations 36: 419-445. Addison, J.T., C. Schnabel, J. Wagner (2001), Works Councils in Germany: Their Effects on Establishment Performance. Oxford Economic Papers 53: 659-94. Addison J.T., P. Teixeira, T. Zwick (2006), Works Councils and the Anatomy of Wages. ZEW Discussion Paper 086. Ai, C., E. Norton (2003), Interaction terms in logit and probit models. Economics Letters 80: 123-129. Bauer, T., K.F. Zimmermann (1999), Overtime Work and Overtime Compensation in Germany. Scottish Journal of Political Economy 46: 419-436. Bell, D., R.A. Hart, O. Hübler, W. Schwedt (2000), Paid and Unpaid Overtime Working in Germany and the UK. IZA Discussion Paper 133. Cameron, A., P.K. Trivedi (2005), Microeconometrics- Methods and Applications. Cambridge University Press, Cambridge. Clark, A., E Postel-Vinay (2005), Job Security and Job Protection. IZA Discussion Paper No. 1489. Dehejia, R.H., S. Wahba (2002), Propensity Score Matching Methods for Nonexperimental Causal Studies. The Review of Economics and Statistics 84: 151-161.

The Causes and Consequences of Adopting a Works Council • 531

FitzRoy, F.R., K. Kraft (1985), Unionization, Wages and Efficiency: Theories and Evidence f r o m the US and West Germany. Kyklos 38: 5 3 7 - 5 5 4 . FitzRoy, F.R., K. Kraft (1987), Efficiency and Internal Organization: Works Councils in West German Firms. Economica 54: 4 9 3 - 5 0 4 . FitzRoy, F.R., K. Kraft (1990), Innovation, Rent-Sharing and the Organization of Labor in the Federal Republic of Germany. Small Business Economics 2: 9 5 - 1 0 3 . Frick, B. (1996), Codetermination and Personnel Turnover: The German Experience, Labour 10: 407-430. Frick, B., D. Sadowski (1995), Works Councils, Unions and Firm Performance. Pp. 4 6 - 8 1 in: F. Buttler, et al. (eds.), Institutional Frameworks and Labor M a r k e t Performance. Routledge, L o n d o n / N e w York. Gerlach, K., O. Hübler (1987), Personalkosten, Beschäftigtenzahl und Arbeitsstunden aus neoklassischer und institutioneller Sicht. S. 2 9 1 - 3 3 1 in: F. Buttler, K. Gerlach, R. Schmiede (eds.), Arbeitsmarkt und Beschäftigung, Frankfurt am Main: Campus. Haisken-DeNew, J.P., M . H a h n (2006), A Flexible Modularized Stata Interface for Accessing Large Scale Panel Data Sets, mimeo (www.PanelWhiz.eu). H e c k m a n , J.J., H . Ichimura, P. Todd (1998), Matching as an Econometric Evaluation Estimator. Review of Economic Studies 65: 2 6 1 - 2 9 4 . Hübler, O. (1989), Individual Overtime Functions with Double Correction for Selectivity Bias. Economics Letters 29: 8 7 - 9 0 . Hübler, O. (2000), All goes faster but lasts longer - Computer use and overtime work, ifo Studien 46: 2 4 9 - 2 7 1 . Hübler, O . (2002), Unpaid overtime, the use of personal computers and wage differentials. Jahrbuch für Wirtschaftswissenschaften 53: 8 8 - 1 0 6 . Hübler, O. (2003), Fördern oder behindern Betriebsräte die Unternehmensentwicklung? Perspektiven der Wirtschaftspolitik 4: 3 7 9 - 3 9 7 . Hübler O., U. Jirjahn (2002), Arbeitsproduktivität, Reorganisationsmaßnahmen und Betriebsräte. S. 1 - 4 5 in: L. Bellmann, A. Kölling (eds.), Betrieblicher Wandel und Fachkräftebedarf, BeitrAB 257, Nürnberg. Hübler, O., U. Jirjahn (2003), Works Councils and Collective Bargaining in Germany: The Impact on Productivity and Wages. Scottish Journal of Political Economy 50: 4 7 1 - 9 1 . Hübler, O., W. Meyer (1997), Uberstunden im Verarbeitenden Gewerbe Niedersachsens. S. 2 2 7 2 5 4 in: J. Kühl, M . Lahner, J. Wagner (eds.), Die Nachfrageseite des Arbeitsmarktes. Ergebnisse aus Analysen mit deutschen Firmenpaneldaten, BeitrAB 204, Nürnberg. Jirjahn, U. (2007), The Introduction of Works Councils in German Establishments - Rent Seeking or Rent Protection?, mimeo University of Hannover. Kölling, A. (1997), Überstunden als dauerhafte Anpassung der Arbeitsnachfrage - Theoretische Überlegungen und empirische Überprüfung anhand von Daten aus dem IAB-Betriebspanel. S. 2 0 5 - 2 2 6 in: J. Kühl, M . Lahner, J. Wagner (eds.), Die Nachfrageseite des Arbeitsmarktes. BeitrAB 204, Nürnberg. Lechner, M . (2001), Identification and Estimation of Causal Effects of Multiple Treatments under the Conditional Independence Assumption. Pp. 4 3 - 5 8 in: M . Lechner, F. Pfeiffer (eds.), Econometric Evaluation of Active Labor M a r k e t Policies, Heidelberg: Physika. N o r t o n , E., H . Wang, C. Ai (2004), Computing interaction effects and standard errors in logit and probit models. The Stata Journal 4: 1 0 3 - 1 1 6 . Rosenbaum, P.R., D.B. Rubin (1983), The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika 70: 4 1 - 5 5 . Roy, A.D. (1951), Some Thoughts on the Distribution of Earnings. O x f o r d Economics Paper 3: 135-146. Rubin, D.B. (1974), Estimating Causal Effects of Treatments in Randomized and N o n - R a n d o mized Studies. Journal of Educational Psychology 66: 6 8 8 - 7 0 1 . Rubin, D.B. (1977), Assignment to Treatment G r o u p on the Basis of Covariate. Journal of Educational Statistics 2: 1 - 2 6 . Betriebliche Determinanten des Überstundeneinsatzes, FriedrichAlexander Universität Erlangen, Diskussionspapier N o . 24. Valetta, R.G. (1998), Declining J o b Security. Journal of Labor Economics 17: 1 7 0 - 1 9 7 .

532 • K. Kraft and J. Lang

Wooldridge, J . M . (2002), Econometric Analysis of Cross Section and Panel Data. The M I T Press, Cambridge Massachusetts. Prof. Dr. Kornelius Kraft, Universität D o r t m u n d , Wirtschafts- und Sozialwissenschaftliche Fakultät, Volkswirtschaftslehre (Wirtschaftspolitik), 4 4 2 2 1 D o r t m u n d , Germany. Phone: + 4 9 ( 0 ) 2 3 1 7 5 5 3 1 5 2 . E-Mail: [email protected] Dipl.-Vw. Julia Lang, Universität D o r t m u n d , Wirtschafts- und Sozialwissenschaftliche Fakultät, Volkswirtschaftslehre (Wirtschaftspolitik), 4 4 2 2 1 D o r t m u n d , Germany. P h o n e : + 4 9 ( 0 ) 2 3 1 7553154. E-Mail: [email protected]

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

Company-Level Pacts for Employment By Lutz Bellmann, Nürnberg, Knut Gerlach, and Wolfgang Meyer, Hannover* JELJ31,J52 Collective contracts, decentralization of wage-setting, employment effects.

Summary Company-level pacts for employment are agreements between management and the company's work force that are characterized by concessions from both bargaining partners. Employees agree to company-specific deviations from a collective contract that include negative components like reduced wages or prolonged working time in exchange for employment guarantees or investment programs. These pacts are negotiated to avoid or mitigate a decline of employment or to improve the long-term competitiveness of the firm. Based on the IAB Establishment Panel of the years 2004 to 2007 the employment consequences of these pacts are analyzed. It can be shown that company-level pacts tend to correlate negatively with employment growth. This finding basically holds if the endogeneity of pacts is taken into account.

1

Introduction

With falling union density and a declining membership of companies in employers' associations the share of workers and firms covered by collective agreements declined substantially for many years in Germany (Addison et al. 2007). Due to these developments and the high unemployment rates the German wage-setting regime has come under attack. Industry-wide bargained wages are diagnosed as a source of inflexibility impeding companies to adjust the level and dispersion of wages to changing conditions in labor and product markets. 1 One reaction to this diagnosis has been the introduction of "opening clauses" or "hardship clauses" in industry-wide collective agreements that offer more leeway to companies. 2 Opening clauses were first applied to working times in the metal industry. Certain workers could be exempted from the reduction of working times that was concluded in the industry-wide contract in 1984. "Hardship clauses" were first introduced in Eastern German manufacturing and they basically permit the exemption from the industry contract wage level. Companies willing to apply hardship clauses * We are very grateful to Hans-Dieter Gerner for his excellent research assistance and to an anonymous referee for helpful comments and suggestions. 1 A firm is obliged to take into account the norms of the collective industry agreement, if it is a member of the relevant employers' association, if the contract is declared to be generally binding (Allgemeinverbindlichkeitserklärung) or if the firm's individual employment contracts refer explicitly to the collective contract. 2 Legally, "opening and hardship c l a u s e s " are based on § 4,3 of the law on collective agreements (Tarifvertragsgesetz). The law only tolerates agreements at the company-level which stipulate conditions deviating negatively for the workforce from a collective, generally industry-wide contract, if the latter contains an explicit clause for this exceptional procedure.

534 • L. Bellmann, K. Gerlach, and W. Meyer are obliged to prove their precarious economic condition to the bargaining partners at the industry-level. This type of clause gradually extended to Western Germany and the preconditions for economic hardship were slowly and steadily diluted. Normally, management and the works council have to agree upon the application of an opening or hardship clause, and in addition a consensus of the respective union and employers' association is requested. Unions and works councils generally accommodate less favorable contract norms if they expect that this is an inevitable step to avoid severe employment losses. In some cases the consent is connected to explicit pledges on the employer side like employment guarantees or investment programs, which is often called a company-level pact for employment (CLP). To clarify the terminology applied in our paper we use the term job alliance for all types of company-specific deviations from a collective contract (Tarifvertrag) that might include negative components for the workforce. The term company-level pact for employment is reserved for those job alliances that are characterized by concessions from both bargaining partners at the plant level. In the following analysis we will focus on CLP for two reasons. First, from an economic viewpoint the introduction of a CLP implies a trade-off - e.g. an employment guarantee in exchange for a moderate pay hike - and this is of theoretical interest. Second, the two most representative data sets available, that are described later, basically focus on company-level pacts for employment and enable an empirical investigation. The central issue analyzed in this paper is: Are these pacts successful in the sense that substantial employment losses can be avoided or employment increases can be attained? The paper is organized as follows. Section 2 discusses the theoretical background. Section 3 documents briefly the data sources that are available for investigating company pacts and presents the related empirical literature. In Section 4 we present our descriptive findings and the multivariate analysis of the impact of company-level pacts on employment. Section 5 concludes.

2

Theoretical background

Several approaches can explain the impact of company-level pacts for employment. They can be divided into theoretical approaches that focus on the decentralization of wagesetting, theories concentrating on efficient bargaining and approaches which investigate one by one particular concessions of employers and employees without an explicit recourse to a specific model. We discuss these approaches briefly. Calmfors and Driffill (1988) as well as Berthold and Fehn (1996) argue that the level of employment is higher in decentralized wage-setting regimes compared with wage-bargaining at the industry-level. In two noteworthy papers, however, Fitzenberger and Franz (1999, 2000) show that a transfer of wage-bargaining from the industry-level to companies does not with necessity lead to higher employment. In their model unions can bargain at the company- or industry-level either myopically (not taking into account the repercussions of wages on employment in the steady state) or with a long-term orientation (being aware of these repercussions). The results of the model (Fitzenberger/ Franz 1999,2000) are basically driven by an insider-outsider distinction assuming that in the short-term outsiders are less productive than insiders and unions have stronger preferences for incumbent workers. On the one hand employees and the union in profitable companies prefer pay hikes to new hires. They tend to accept wage cuts only if their own employment is endangered. On the other hand an industry-wide collective wage agreement specifies a uniform wage across all companies, which is relatively lower in profit-

Company-Level Pacts for Employment • 535

able companies and relatively higher in less profitable firms. Thus, the employment effect of a transfer of the wage-setting regime is ambiguous. With the existence of company-level pacts that authorize a trade-off between employment and wages, a renegotiation of wages at the plant level is feasible if a firm with posterior full information about product demand faces severe employment losses due to the prior bargained wage at the industry-level. The renegotiation, however, incurs costs of information and transactions, for instance. The existence of pacts induces the monopoly union to set a higher wage as it is no longer binding if a negative product demand with concomitant employment losses materializes. Consequently, the overall employment effect of company-level pacts is ambiguous, too, although positive employment effects might be expected for companies implementing the pacts. While the theoretical approach presented by Fitzenberger and Franz (1999, 2000) focuses on the employment impact at the industry- or firm-level with and without company-level pacts, the following approach emphasizes simultaneous negotiations of wages and employment at the company-level. In the monopoly union model the union determines the wage unilaterally and takes into account the reactions of firms which are endowed with the right-to-manage, i.e. to specify the labor demand depending on the wage set by the union (Booth 1995). In case of a negative demand shock during the term of the contract employment will be cut, because wages cannot be reduced. If the employees are endowed with firm specific human capital and quasi rents exist dismissals may be inefficient. McDonald and Solow (1981) demonstrated that the bargaining partners can augment their utility and/or profits by negotiating wages and employment simultaneously. The resulting solutions to this modified bargaining set-up can lead to lower wages and increased employment. At the industry-level renegotiations over wages and employment are not incentive compatible because employers' associations cannot specify the employment level for each company and guarantee this level to the union during the term of the contract. At the company-level, however, bargaining simultaneously over wages and employment is more efficient as firms reneging on their commitment are likely to be detected and to be exposed to a loss of reputation. In order to appropriate the benefits of efficient bargaining, management and the workforce can negotiate within the framework of a company-level pact. As Berthold et al. (2003) show this might be valid for pacts negotiated in a current economic crisis of a company, whereas preventive pacts with the goal of improving competitiveness need more flexibility and should encompass elements of profit sharing. In principle, the negotiation of an efficient contract at the company-level can substitute or complement an industry-wide agreement. Especially for larger companies Hassel and Rehder (2001) emphasize the efficiency-enhancing impact of peaceful labor relations. Industry-wide collective contracts prohibit strikes during the term of the contract. In addition, pacts at the company-level facilitate the control of labor costs by enabling a variety of working time regimes, a differentiation of working conditions and an implementation of pay cuts. Thus, particularly for larger companies it might be advantageous to retain the peace obligations of collective contracts and to simultaneously attain the higher degree of flexibility provided by company-level pacts. Small and medium sized plants dispose of more informal procedures to react to negative shocks. While the previous theoretical approaches basically argue within the framework of a coherent model and concentrate on the wage determination process and its implication for employment, Hiibler (2005, 2006) focuses on specific concessions of workers and employers analyzing wage and working time company-level pacts and their employment

536 • L. Bellmann, K. Gerlach, and W. Meyer

effects. If the monetary compensation is reduced, the firm will normally improve profitability, for instance by lowering prices and increasing sales. A positive effect on employment can be expected. However, if insiders oppose this strategy, the firm might face a productivity decline due to a loss of motivation and the expected employment increase may not be attained. To minimize the potential frustration of the workforce firms might prefer types of cutback that are less noticeable such as reductions of supplementary allowances or bonuses. Working time concessions should also reduce labor costs. If the regular weekly working time is shortened without a compensatory wage increase in case of a negative demand shock, employment could be stabilized temporarily. Fixed labor costs per hour tend to affect employment perspectives negatively in the longer run. Alternatively, working time can be extended without additional pay. This is equivalent to a wage reduction and is less noticeable for the worker as he/she continues to receive a stable monthly income. In a similar vein, overtime could be converted into regular working time with the goal to economize on overtime premiums. However, these measures can have undesired side-effects as well. Employees with longer working times might produce more defective output leading to a reduced productivity. The introduction of working time accounts increases the flexibility of the firm by adjusting working times to changes in product demand with lower costs than alternative measures of personnel policy. It combines the two mentioned measures (wage cuts and extensions or reductions of working times) and should be more efficient in stabilizing employment than a separate implementation of the two instruments. However, when working time accounts are introduced in periods of slack demand, employment reductions may ensue as labor hoarding for boom times is no longer necessary. Evidently, concessions do not have an unambiguous impact on employment and competitiveness, which requires an empirical analysis to evaluate the introduction of company-level pacts. Summarizing, CLPs tend to be more pertinent • for firms applying collective agreements, as these might be an important source of inflexibility; • for firms with a works council, as the negotiation of a pact is facilitated if an institutionalized partner for management is available; • for large companies as informal procedures to react to shocks are difficult to implement; • for companies facing a current or imminent crisis, as the willingness to concessions of the workforce will be relatively high. The employment effects of CLPs are ambiguous.

3

Data and related empirical literature

Some early investigations of the existence and effects of company-level pacts for employment are based on rather small surveys of companies (Ackermann/Vollmer 1999, Berthold et al. 2003a, Heidemann 2005). However, more recent investigations use data sets with several thousands of establishments. One of these is the Works Council Survey 2003 of the WSI (Economic and Social Research Institute affiliated with the Federation of German Unions). It uses a random sample of companies of all private economic sectors with a works council and with at least 20 employees (Seifert/Massa-Wirth 2005, 222). The WSI-Survey is not restricted to agreements with concessions from the side of management and the workforce. However, as 87 percent of all concluded job alliances in the

Company-Level Pacts for Employment • 537

2003 survey involve concessions from management (Seifert/Massa-Wirth 2 0 0 5 , 2 2 6 ) the term company-level pacts is approximately appropriate. Since works councils are very supportive for pacts, it is not surprising that the percentage of establishments with CLPs in this survey is rather high: 23 per cent. Additionally, 3 per cent of the respondents were engaged in negotiating a pact with management at the time of the survey (Seifert/MassaWirth 2005, 222). The survey of BISS (Hauser-Ditz et al. 2006) in 2005 is based on a broader target group. It covers all establishments with at least 10 employees in the private sector of the economy and sought information on the existence of a formal agreement to stabilize employment. The fact that only 7 percent (Hauser-Ditz et al. 2006, 36) report the existence of a CLP may be due to the inclusion of smaller establishments und those without a works council. The most comprehensive data base is the IAB Establishment Panel. It surveys approximately 16,000 establishments on an annual basis (Bellmann 2002). In 2005 and 2007 this panel survey asked three questions concerning "opening clauses". As already mentioned, these clauses cover a wider spectrum of job alliances at the plant level than the company-level pacts that are investigated in our study. In 2006 the IAB Establishment Panel surveyed company-level pacts for employment in greater detail. The survey focuses on agreements with concessions from the workforce or the council representing the employees and from the management of the company. Pacts with unilateral concessions are excluded. The survey provides information on the existence of pacts, the year in which the pact was concluded, and the basic motivation for establishing a pact such as counteracting an imminent crisis or strengthening the competitive position of the company. Furthermore, it surveys in detail the measures, basically concessions by the workforce and the employer, concerning working times and remuneration as well as employment, training, investments, guarantee of the production location, and a renunciation of outsourcing. In contrast to the Works Council Survey it also covers smaller companies with less than 20 employees and is not restricted to establishments with a works council. Therefore, the quantitative relevance of CLPs is drastically reduced: Ellguth and Kohaut (2008) find that 2 percent of all establishments in the private sector with five and more employees implement company-level pacts. They employ 14 percent of the workforce. Whereas 73 percent of the companies with company-level pacts implement measures pertaining to working time flexibility as well as to pay cuts, 20 (7) percent use only working time flexibility (pay cuts). The observation that concessions concerning working times are more widely spread than pay cuts is confirmed by the WSI data and BISS and by investigations based on opening clauses (Bispinck 2005, Heinbach 2005, Kohaut/Schnabel 2007, Fischer et al. 2007). Qualitative and cross-section quantitative studies inform about the goals and contents of company-level pacts. The following main aims are emphasized: improvement of competitiveness, increase of productivity, reduction of labor costs, more flexible working hours, guaranteed survival of the company at the current location, guarantee of the level of employment and a policy of no dismissals (Ackermann/Vollmer 1999, Berthold et al. 2003a, Massa-Wirth/Seifert 2004). In addition, Heidemann (2005) mentions the protection of core employees. Whereas the employers' pledges basically refer to the stabilization of employment, the avoidance of dismissals, supplementary training and a commitment to employ apprentices, the concessions of the workforce cover a wider spectrum of measures such as modifications of working times and work organization as well as changes of remuneration (Ackermann/Vollmer 1999, Berthold et al. 2003a, Massa-

538 • L. Bellmann, K. Gerlach, and W. Meyer

Wirth/Seifert 2004). The concession mix depends on the economic situation of the establishments (Seifert/Massa-Wirth 2005). With respect to the motivation for concluding company-level pacts, Berthold et al. (2003a) distinguish two types: (a) Crisis or adaptation pacts which respond to an employment loss (realized or announced) due to negative market trends or an adverse technology shock and (b) preventive pacts or pacts improving the competitiveness by aligning work and production processes with future market uncertainties. In their survey of 443 firms of the metal industry they find that adaptation pacts were negotiated as reactions to sector-wide recessions, liquidity restraints and predictable employment losses, whereas preventive pacts were prompted by goals such as productivity increases, reorganization of work processes and the stimulation of innovations. With the information provided by the IAB Establishment Panel for 2006 Ellguth and Kohaut (2008) find that in the private sector company-level pacts strengthening the competitiveness are more frequent (48 percent of all pacts) than pacts concluded to prevent a crisis (41 percent). 11 percent of all companies with a company level pact indicate "other reasons". Cross-tabulations by Ellguth and Kohaut (2008) show that sectors such as mining and energy, manufacturing, transport and communication, credit and insurance tend to implement company-level pacts frequently, whereas they are not very common in construction and service sectors. The implementation of company-level pacts is examined in several studies. Massa-Wirth and Seifert (2004) use the data of the Works Council Survey for 2003 and estimate a logit model. They find that the probability of pacts increases with establishment size, coverage by a collective agreement, a large proportion of male employees and with a collaboration between management and the works council that is based on mutual respect. Companylevel pacts are more frequent in East Germany and a satisfactory profit lowers the probability of a pact. Hiibler (2005a, 2006) presents comparable probit results based on the same data set. Ellguth and Kohaut (2008) distinguish pacts to prevent a crisis and to improve competitiveness and estimate separate bivariate probit models. Interestingly, establishment size is a highly significant determinant only for company-level pacts that pursue an improvement of competitiveness. These pacts are more likely if the company is involved in research and development, restricted by a relatively short weekly working time, exposed to high wages and if the company applies a collective agreement and has a works council. Pacts to prevent an impending crisis exist with a higher probability in establishments with a precarious profitability, a low level of productivity, and in establishments with a works council. Studies of the effects of CLPs are mainly provided by Hiibler, who focuses his investigations on the success of the company-level pacts measured in terms of employment (2005, 2005a), profits and orders (2006). He uses the 2003 Works Council Survey. 85 percent of the works councillors reported that the establishments honoured the negotiated pledges. This could be interpreted as a first sign of success. However, the following multivariate regression analysis shows that the data do not substantiate this result. Establishments which signed a company-level pact or planned so for the near future had a significantly lower probability of stable or rising employment than plants without a pact. The negative employment effect is boosted if management impedes the activities of the works council. Differentiating the estimation according to the profit assessments shows that the negative employment impact of pacts is found only in firms with high profits. The argument of reverse causation - that especially establishments with negative employment perspectives tend to sign pacts - is addressed in two different ways (Hiibler

Company-Level Pacts for Employment • 539

2005). Firstly, a d u m m y variable is introduced representing establishments which are on the verge of dismissals at the time of negotiations. Secondly, Hiibler instruments the pact variable by the estimated probabilities of signing or planning a pact. Interestingly, the negative employment effect is correlated w i t h the planning phase and not with the implementation period. With respect to the impact of different concession measures, investments in the qualifications of the w o r k f o r c e and a prolongation of w o r k i n g time are advantageous in terms of employment, while a reorganization of w o r k , pay cuts and w o r k i n g time reductions have the opposite effect (Hiibler 2005). T h e magnitudes of the effects depend on the economic situation (profitability) a n d the employment structure of the establishments (mainly qualified or unqualified employees). If a c o m p a n y a d o p t s a w o r k i n g time account the employment trend is unaffected. Although longitudinal i n f o r m a t i o n is missing in the cross section d a t a set, Hiibler estimates the time profile of the employment effect based o n data of the previous d u r a t i o n of the pact. H e assumes that the relationship is similar for all establishments a n d detects a cyclical time pattern. For company-level pacts negotiated in 2 0 0 1 the employment effects are positive at first, t u r n negative in the medium term and positive again in the very long run. T h e presented literature partly c o r r o b o r a t e s the issues summarized at the end of the section 2. T h e empirical evidence tends t o support most issues regarding the implementation of CLPs. Establishments applying collective contracts, having a w o r k s council and a large w o r k f o r c e are m o r e likely to negotiate CLPs t h a n other firms, though, not all multivariate regressions detect significant correlations between the mentioned variables a n d relative frequencies of CLPs. T h e conjecture t h a t pacts are frequently negotiated w h e n a job loss is expected is in principle in accordance with the evidence. However, CLPs are not only an o u t c o m e of an economic crisis of a company. Rather frequently profitable establishments with strong d e m a n d for their o u t p u t negotiate pacts with the goal to improve their long term competitiveness. Low profits increase the likelihood of crisis pacts. The empirical evidence is in accordance with the issue t h a t the employment effects of CLPs are ambiguous. Overall, the impact of CLPs on employment tends to be slightly negative. However, depending on the economic situation and on the specific concessions negotiated, constellations exist with positive employment effects. 4

Descriptive statistical results and multivariate analysis

We use the IAB Establishment Panel, in particular the waves for the years 2 0 0 4 t o 2 0 0 7 for our descriptive and multivariate analysis. T h e investigation focuses on establishments w i t h five and more employees of the private enterprise sector 3 w i t h o u t agriculture, forestry and fishing. Additionally, establishments with CLPs negotiated 2 0 0 4 or earlier are excluded. Therefore, n o firm has a CLP in the first year of our investigation period. Basic statistical findings f r o m wave 2 0 0 6 a b o u t the existence of CLPs, the motivation to conclude a CLP, the duration of the contract a n d other characteristics of the pacts are presented in the Appendix Table A l .

3

Excluded are establishments reporting that they characterize their transaction volume by "budget size" and companies affiliated to the sectors "education", "representation of interests, churches and other associations without pecuniary rewards", and "private households".

540 • L. Bellmann, K. Gerlach, and W. Meyer

Table 1 Existence of, motivation for and duration of the company-level pacts for employment in Germany 2006, percentages Pearson chi2a)

establishment size, number of employees 5-9

10-19

20-49

50-199

200-499 > 5 0 0

20.8

17.2

21.2

23.3

10.4

7.2

no 22.6 yes 2.5

18.4 3.5

22.3 9.9

22.8 28.7

9.1 24.9

5.0 30.4

(5) 1,2e + 03 Pr = 0.000 (5) 23.6132 Pr = 0.000

all establishments existence of CLP

motivation for CLP crisis pact competitive pact

4.3 1.4

3.9 3.0

12.8 7.1

29.8 26.3

26.7 24.9

22.5 37.3

duration of CLP > 1 year < 2 years > 2 years < 5 years no duration specified

1.5 0.5 9.0

3.3 1.8 7.8

8.8 6.2 19.9

39.7 20.3 30.7

27.9 27.5 13.9

18.8 43.6 18.7

(10) 142.4401 Pr = 0.000

a) In the first row the degrees of freedom are noted, in the second the chi2-statistic and in the third the p-value. Source: IAB Establishment Panel, wave 2006; own calculations.

Table 1 is based on wave 2006 of the IAB Establishment Panel and includes companies with and without an employment pact. The first row shows the distribution of establishments according to size classes. The next part reveals that larger companies tend to introduce company-level pacts more frequently than smaller ones. The Pearson chi2 statistic, displayed in the last column, indicates that the hypothesis of independence can be rejected. The motivation for concluding a pact differs between larger and smaller establishments. The former are more likely to introduce pacts with the intention to strengthen their competitiveness, whereas the latter tend to establish pacts as a reaction to a current or impending crisis (Table 1, part 3). Additionally, we find that pacts with a longer duration (more than 2 and less or equal 5 years) are much more common in larger companies (Table 1, part4). To characterize the development of employment, we compute yearly rates of change. If a firm implements a CLP in year t, the employment consequences can be observed in year t + 1. This poses no data problems for CLPs negotiated in 2005. To compute the rates for establishments with CLPs in 2006 the data of the wave 2007 are needed. In principle, these data are available. However, it is possible, that firms, denoted as "no C L P " , negotiated a pact in the interval between the interviews 2006 and 2007. In those cases the two states - CLP yes or no - cannot be distinguished. In addition, we compute an expected rate of change of employment for year t + 1, expressed by the respondent in year t. 4 As realized and expected employment changes might differ, this variable is of interest as it captures employment predictions during the process of implementing CLPs and it circumvents the slight problem attached to the variable realized employment changes. 4

The computation is based on a question regarding the expected number of employees in the next year. The possible items are "(1) fairly constant", "(2) rather increasing", "(3) rather decreasing" and "(4) at the moment not possible to answer". If the respondent expects a falling or rising trend he must specify roughly the employment in t + 1.

Company-Level Pacts for Employment • 541

In Table 2 we present descriptive statistical results for establishments with a n d w i t h o u t company-level pacts for both indicators of employment development prior to and after the agreement w a s concluded and c o m p u t i n g changes of the indicators for the period investigated. We c o m p a r e the indicators for establishments which had not concluded a pact in the period 2 0 0 4 - 2 0 0 6 with the indicators for those establishments w i t h o u t a pact in period 2 0 0 4 and introducing one in 2 0 0 5 or 2 0 0 6 . Firstly, we look at the establishments' employment expectations which take into account the expected employment for June 2 0 0 7 (2005) on the basis of the actual employment level in 2 0 0 6 (2004). The expectations are articulated in 2 0 0 6 (2004) and are scaled as 1 - falling, 2 - constant and 3 - rising. Interestingly, the expected developments of employment for the period 2006/ 2 0 0 7 diverge between companies with and w i t h o u t a pact. T h e f o r m e r tend to have higher frequencies (percentages) for falling and rising employment expectations t h a n the latter (Table2, p a r t i ) . Again the hypothesis of independence can be rejected. Secondly, we c o m p u t e the difference in employment expectations (demployment-expected) between the years 2 0 0 4 a n d 2006. In Table 2, part 2, demployment-expected ( - 2 ) means that the assessment of employment in 2 0 0 6 is t w o categories worse than in 2 0 0 4 . The figures indicate that demployment-expected is p r e d o m i n a n t l y stable or increasing, the changes tend to be more positive in companies with company-level pacts. T h e hypothesis of independence is rejected at conventional levels. Consequently and modifying the finding for the year 2 0 0 6 , w e obtain for the medium term the result that establishments with pacts might exhibit m o r e positive employment expectations t h a n those that never concluded CLPs. Furthermore, the equivalent results for the realized employment changes are presented in the next part of Table 2. A striking difference in the relative frequencies of the three items - falling, constant, increasing - can be observed between expected and realized employment changes. Whereas in the first case stability dominates, in the second case most establishments report either falling or increasing employment, and a significant difference in the figures for establishments with and w i t h o u t a pact c a n n o t be detected. For the differences of realized employment changes (demployment-realized) we obtain a similar result. These divergent findings for demployment-expected a n d demployment-realized can be due to t w o factors. In some establishments the changes of realized employment are numerically rather small and f r o m the perspective of m a n a g e m e n t they m a y be interpreted as indications of a stable w o r k f o r c e . M o d e s t expected employment losses and expected e m p l o y m e n t stability might facilitate the complex bargaining process accompanying the implementation of CLPs and involving m a n a g e m e n t , incumbent employees, unions, w o r k s councils, a n d the public e m p l o y m e n t service. Turning n o w briefly to the expectations of revenue and to the assessments of profitability we find that establishments with a pact apparently have more positive revenue expectations for the period 2 0 0 6 and a more polarized assessment of their profitability for 2 0 0 6 than establishments not having signed an agreement (Table 2, part 3). Summarizing, we find that larger establishments are more active in concluding c o m p a n y level pacts t h a n their smaller counterparts. In addition, their pacts are characterized by a longer duration a n d they prefer pacts to strengthen their competitiveness. With respect t o e m p l o y m e n t expectations the bivariate results are a m b i g u o u s as establishments with pacts tend to exhibit more falling and increasing employment expectations in the short run. In the longer run a c o m p a r i s o n between establishments with and w i t h o u t pacts indicates that the f o r m e r might have more positive employment expectations. However, with respect to realized employment changes the figures s h o w no clear distinctions be-

542 • L. Bellmann, K. Gerlach, and W. Meyer

Table 2 Various indicators for employment changes, revenue changes and profitability and company-level pacts of employment, percentages company-level pact for employment in 2006

total

no

yes

expected employment changes 2006 for 2007 1 falling 2 constant 3 increasing

8.4 71.4 20.2

17.5 57.3 25.2

9.2 70.2 20.6

differences of expected employment changes 2004 for 2005 and 2006 for 2007 (demployment-expected) - 2, falling 2 categories - 1, falling 1 category 0, constant + 1, rising 1 category + 2, rising 2 categories

0.9 12.4 64.8 19.9 2.0

0.0 15.6 54.8 25.3 4.3

0.8 12.6 64.3 20.1 2.2

realized employment changes 2006 for 2007 1 falling 2 constant 3 increasing

51.0 10.3 38.7

54.8 7.2 38.0

51.6 9.8 38.6

differences of realized employment changes 2004 for 2005 and 2006 for 2007 (demployment-realized) - 2, falling 2 categories - 1, falling 1 category 0, constant + 1, rising 1 category + 2, rising 2 categories

30.1 8.4 37.5 7.2 16.8

28.2 6.4 46.2 7.7 11.5

29.8 8.1 38.9 7.3 15.9

expected revenue changes 2005 for 2006 1 falling 2 constant 3 increasing

15.3 54.3 30.4

12.3 47.8 39.9

15.0 53.7 31.3

profitability assessment 2007 for 2006 1 negative 2 satisfactory 3 positive

18.8 32.6 48.6

22.5 26.2 51.3

19.1 32.1 48.8

Pearson chi2a> (2) 74.6226 Pr = 0.000

(4) 12.4883 Pr = 0.014

(2) 3.6092 Pr = 0.165

(4) 2.8063 Pr = 0.591

(2) 24.0443 Pr = 0.000 (2) 12.9612 Pr = 0.000

a) In the first row the degrees of freedom are noted, in the second the chi2-statistic and in the third the p-value. Source: IAB Establishment Panel, wave 2004 to 2007; own calculations.

tween CLP and no CLP establishments. Establishments with a pact are characterized by a more polarized assessment of profitability and tend to exhibit a more positive revenue expectation than their counterparts. In the following multivariate analysis both expected and realized employment changes are the dependent variables. As the association between the introduction of a CLP and the development of expected and realized employment is likely to be interdependent, it is essential to reduce the possible bias in the estimation caused by the endogeneity of the CLP. In a first step and in addition to the expected employment we consider the realized

Company-Level Pacts for Employment • 543

employment after the introduction of CLPs in order to avoid an overlap between the reference periods for the CLPs and the development of employment. In a second step of our analysis we instrument the variable CLP by estimating the probabilities that a CLP exists (Heckman 1978). Finally matching methods are used to account for the endogeneity of a CLP. For the econometric analysis of the association of company-level pacts for employment, on the one hand, and expected and realized employment changes, on the other hand, we adopt the following strategies: Firstly, we estimate a cross-section time-series model using the information about CLPs from the 2006 wave of the IAB Establishment Panel and we analyze the time span for the years 2004 until 2006, respectively 2007. Secondly, we distinguish between crisis or adaptation CLPs on the one hand and preventive CLPs improving the firms' competitiveness on the other hand (Berthold et al. 2003a, Ellguth/ Kohaut 2008). Thirdly, we replace the pact dummy variables by working time and remuneration elements of company level pacts for employment. Table 3 reports the results of the estimated linear probability regression models with the expected and realized employment changes as dichotomous dependent variables. 5 We start with a model specification which does not distinguish between CLPs to prevent a crisis and to strengthen competitiveness. The significant coefficient of this variable shows a negative correlation between CLPs and expected as well as realized employment changes. Among the control variables expected revenue development has a highly significant positive impact. Larger proportions of qualified and temporary employees are correlated with more favorable employment changes. Interestingly, the dummy variable for coverage by collective agreements shows a highly significant negative coefficient. Thus, establishments are less flexible to modify the working conditions of their workforce when they are restricted by collective contracts. The establishment size dummies are positive and significant indicating that employment changes of smaller establishments are more positive than those of the establishments with 500 and more employees (the reference group). The dummies for the different waves of the panel show that the employment changes of the waves 2005 and, in particular, 2006 are more favorable than those of the wave 2004 (the reference group). Basically, these findings are in accordance with results by Hiibler (2005). In the second specification in Table 3 we distinguish between CLPs to prevent a crisis and to strengthen the competitiveness of an establishment and find significant negative coefficients for both types of pacts. The impression is that the negative association between crisis pacts and employment changes is particularly strong. Competitive pacts might be more forward looking in the sense that they attempt to stabilize employment by strengthening the establishment in the medium term. The coefficient estimates of the control variables hardly change. In Table 4 we present our econometric results for the working time and remuneration elements of CLPs. Among these variables, only the wage and reorganization variables exhibit significant and negative coefficients in both the expected and realized employment change equations. Hiibler (2005) investigated the impact of concession variables on employment, not employment expectations, and showed that some concession variables have a significant impact. He stressed, however, that some concessions tend to affect s

The estimated probit models are available from the authors upon request. The results of both types of models are very similar.

544 • L. Bellmann, K. Gerlach, and W. Meyer

Table 3 Expected and realized employment changes and company-level pacts for employment, Pooled cross section time-series, Linear Probability Model Dependent variable expected employment changes, 1 if increasing or constant, 0 if falling Explanatory variables company-level pact, dummy, 1 if yes

1

2

- 0 . 0 9 2 *** (0.014)

realized employment changes, 1 if increasing or constant, 0 if falling 1

2

- 0.056 *** (0.016)

crisis pact, dummy, 1 if yes

- 0 . 1 1 6 *** (0.022)

- 0 . 0 8 9 *** (0.024)

competitive pact, dummy, 1 if yes

- 0 . 0 7 7 *** (0.017)

- 0.036 * (0.020)

expected revenue changes, 1 if falling, 2 if constant, 3 if increasing

0.121 *** (0.004)

0.122 *** (0.004)

0.090 *** (0.005)

0.090 *** (0.005)

proportion of qualified employees

0.029 *** (0.010)

0.029 *** (0.010)

0.036 *** (0.014)

0.036 ** (0.014)

proportion of temporary employees

0.127 *** (0.025)

0.127 *** (0.025)

0.145 *** (0.044)

0.145 *** (0.044)

collective agreement, dummy, 1 if yes

- 0 . 0 1 3 ** (0.005)

- 0 . 0 1 3 ** (0.005)

- 0 . 0 2 5 *** - 0 . 0 2 5 *** (0.007) (0.007)

size 5 - 9 employees, dummy, 1 if yes

0.234 *** (0.015)

0.235 *** (0.015)

0.287 *** (0.017)

0.288 *** (0.017)

1 0 - 1 9 employees, dummy, 1 if yes

0.199 *** (0.015)

0.200 *** (0.015)

0.201 *** (0.017)

0.202 *** (0.017)

20 - 49 employees, dummy, 1 if yes

0.195 *** (0.014)

0.196 *** (0.014)

0.165 *** (0.017)

0.166 *** (0.017)

50 - 199 employees, dummy, 1 if yes

0.167 *** (0.014)

0.169 *** (0.014)

0.093 *** (0.016)

0.094 *** (0.016)

200 - 499 employees, dummy, 1 if yes

0.112 *** (0.016)

0.113 *** (0.016)

0.040 ** (0.018)

0.041 ** (0.018)

year 2005, dummy, 1 if yes

0.019 *** (0.007)

0.019 *** (0.007)

0.061 *** (0.008)

0.061 *** (0.008)

year 2006, dummy, 1 if yes

0.062 *** (0.006)

0.062 *** (0.006)

0.090 *** (0.008)

0.090 *** (0.008)

constant

0.415 *** (0.039)

0.414 *** (0.039)

0.228 *** (0.066)

0.227 *** (0.066)

40 sector dummies included number of observations R2

yes

yes

yes

yes

20,480

20,480

19,658

19,658

0.0994

0.0995

0.0641

0.0642

The columns present the estimated coefficients and in parentheses the heteroskedasticity-robust standard errors. . . . . . a n c j . ¡ndicate statistical significance at the 1, 5 and 10 percent level. Not presented are the effects of the sector dummies. Source: IAB Establishment Panel, wave 2004-2007; own calculations.

Company-Level Pacts for Employment • 545

Table 4 Expected and realized employment changes and company measures negotiated in the pact, Pooled cross-section time-series, Linear Probability Model Dependent variable

Explanatory variables: subject matter of the pact

expected employment changes, 1 if increasing or constant, 0 if falling

realized employment changes, 1 if increasing or constant, 0 if falling 1

wage concessions, dummy, 1 if yes

- 0 . 0 6 5 *** (0.025)

working time concessions, dummy, 1 if yes

- 0.002 (0.024)

reorganization, dummy, 1 if yes

- 0.076 * (0.039)

further training, dummy, 1 if yes

- 0 . 0 7 8 *** (0.029)

prolongation of working time without wage compensation, dummy, 1 if yes

-0.127 *** (0.029) 0.061 **

(0.029)

-0.110 *** (0.041) 0.0002 (0.033) - 0.010

prolongation of working time with wage compensation, dummy, 1 if yes reduction of overtime, dummy, 1 if yes

(0.024)

0.012 (0.028)

0.023 (0.032)

0.087 •* (0.040)

- 0 . 1 0 8 *** (0.027)

working time accounts, dummy, 1 if yes

- 0 . 0 6 0 **

(0.030)

0.015 (0.025)

0.001

(0.028)

suspension of contractual wage increases, dummy, 1 if yes

- 0.099 *** (0.028)

- 0.034 (0.032)

reckoning up of contractual wage increases, dummy, 1 if yes

- 0.010

(0.032)

- 0.059 * (0.035)

reduction of special bonus payments, dummy, 1 if yes

- 0.046 * (0.017)

- 0.069 ** (0.028)

other company-level pacts

- 0 . 1 2 2 *** (0.035)

- 0 . 1 0 2 *** (0.040)

number of observations R

2

20,489 0.1017

20,196 0.1162

19,677 0.0653

19,376 0.0624

The columns present the estimated coefficients and in parentheses the heteroskedasticity-robust standard errors. ***,*• and * indicate statistical significance at the 1, 5 and 10 percent level. Not presented are the effects for the other control variables of Table 3 and the constant. Source: IAB Establishment Panel, wave 2004-2007; own calculations.

546 • L. Bellmann, K. Gerlach, and W. Meyer

employment positively, whereas others exert a negative impact. Therefore, we incorporate specific working time and remuneration elements of CLPs. We obtain significant results for some of the variables that characterize specific measures of the pacts which partly corroborate the findings of Table 3. It is, however, evident that the results diverge to a larger extent between the estimated equations for expected and realized employment changes. In both equations significant and negative coefficients are found for the reduction of overtime work and the reduction of special bonus payments. These negative estimates are unexpected from the perspective of standard labour demand theory, because e.g. the reduction of special bonus payments should increase both the expected and realized employment level. Insider-outsider and efficiency wage theories could explain these results. Significantly positive coefficient estimates are only obtained for the prolongation of working time with wage adjustments (for realized employment changes). In order to avoid the bias caused by the possible endogeneity of the CLPs we instrumented the CLPs. The computation of the CLP probabilities uses a probit model estimating the endogenous variable CLP ( 1 if yes) with the following regressors: proportions of qualified, temporary (supplied by an agency), fixed-term, and part-time employees, dummies for works council, collective agreement, non-affiliated establishment, firm size classes, 40 sectors, and time dummies for the years 2005 and 2006. The regression coefficient for the CLP variable is — 0.082 with a standard error of 0.042 in the equation for the expected employment change and in the equation for the realized employment change — 0.223 with a standard error 0.062. 6 Basically, the negative effect of the CLPs presented in Table 3 is corroborated with larger regression coefficients. The rest of the variables in the regression exhibit only minor changes compared to the results presented in Table 3, so that we refrain from discussing these coefficients again. Additionally, we employ a matching estimator. The basic idea is to find in a large group of companies without a CLP those establishments (control group) which are similar to the establishments with a CLP (treatment group) in almost all aspects except for the fact that they have not introduced a CLP. The establishments in both the control and the treatment group had no CLPs in the year 2004. Those observations belonging to the control group ought to be without CLP in the years 2005 and 2006, whereas those in the treatment group must have a CLP during these years. Therefore, we use a difference-in-difference approach to assess the effect of the introduction of a CLP in 2005 on the expected and realized employment changes (y) which enables us to control for time-invariant firm heterogeneity. The comparison between the control and the treatment group uses the difference in the employment change between 2004/05 and 2005/06. The difference-in-difference estimator compares the development of the dependent variable y for two points in time (T = 1 and T = 0) and the treatment and the control group (D = 1 and D = 0): [E(y\D = 1, T = 1) - E(y\D = 1, T = 0)] - [E(y\D = 0, T = 1) - (E(y\D = 0, T = 0)] We estimate the propensity scores, i.e. the conditional probability of receiving the treatment using a probit model and compare the sample means between the establishments with and without CLPs prior to and after matching by using a t-test. Each group comprises 151 establishments. The results are presented in the Appendix Table A3. The OLS regression results of the matched establishments for the expected and realized employ-

6

These regressions are not documented in this paper. They are available from the authors upon request.

Company-Level Pacts for Employment • 547

ment change 2004/05 and 2005/06 are documented in Table 5. The difference-in-difference is expressed by the coefficient of an interaction variable constructed by the product of the time dummy (1, if year 2005/06, and 0, if year 2004/05) and the group (1, if treatment group and 0, if control group) in the regression model in which the time dummy and the group variable are included as well: y = a0 + ai • RC*P + a 2 • T + a} • D + a 4 • (T • D) + £ The positive and significant coefficients of the year 2005/06 dummy show the general upward trend in both the expected and the realized employment change. The significantly positive coefficient of the expected revenue changes (RCexp) indicates the effect of the generally better economic situation on the product market for the employment development. The significantly negative coefficients of the group dummy (treated) indicating the treatment in both employment change equations reveal a selectivity effect of the introduction of CLPs and show that the establishments with worse realized employment developments used CLPs. The insignificant effects of the interaction variable representing the treatment effect demonstrate that the employment developments do not differ between establishments with CLPs and their counterparts. Our multivariate analysis of the relationship between CLPs and employment changes proceeded in three basic steps: (1) Assuming an exogeneity of CLPs, (2) taking into account their endogeneity by instrumenting CLPs and (3) using matching methods to account for their endogeneity. With neither method did we find a significant and positive association between CLPs and employment changes. Our results are more in line with a negative relationship between these two basic variables of our investigation. A cautious

Table 5 Expected and realized employment changes and company-level pacts for employment, Conditional Difference-in-Difference Matching, Linear Probability Models, 2004-2006 Dependent variable

Explanatory variables

expected employment changes, 1 if increasing or constant, 0 if falling

realized employment changes, 1 if increasing or constant, 0 if falling

treatment effect, dummy, 1 if yes

0.018 (0.055)

0.040 (0.075)

treated, dummy, 1 if yes

- 0.094 * (0.053)

- 0.102 * (0.056)

expected revenue changes, 1 if falling, 2 if constant, 3 if increasing

0.103 *** (0.024)

0.056 ** (0.026)

year 2005/06, dummy, 1 if yes

0.121 *** (0.036)

0.194 *** (0.053)

constant

0.520 *** (0.065)

0.343 *** (0.068)

number of observations 2

R

604

604

0.070

0.062

The columns present the estimated coefficients and in parentheses the heteroskedasticity-robust standard errors. * " , ** and * indicate statistical significance at the 1, 5 and 10 percent level. Source: IAB Establishment Panel, wave 2004-2006; own calculations.

548 • L. Bellmann, K. Gerlach, and W . Meyer

interpretation of this finding is that on the level of establishments the possibilities are very limited to prompt positive employment changes by implementing company-level pacts of employment. 5

Conclusions

Apart from the distinct role of larger establishments in using CLPs and in preferring competitive pacts our results concerning employment changes are sobering. Applying various methods to investigate the correlation between company-level pacts and employment we do not find evidence that the pacts help to stabilize or increase employment. The evidence is rather in favour of a negative association between pacts and employment growth. Additional investigations are urgently needed. First the longer-term effects of CLPs should be of special interest. In the wave 2008 of the IAB Establishment Panel most questions concerning CLPs will be reiterated which will facilitate the study of this research topic. Second on the basis of these prospective additional data research should concentrate on employment developments in the short and medium term and investigate the employment effects of different components of the pacts. Third the associations of CLPs with additional dependent variables such as profitability and investments should occupy a high priority on the research agenda.

Company-Level Pacts for Employment • 549

Appendix Table A1 Descriptive statistics for company-level pacts for employment 2006 Percentages Company-level pacts for employment

2

Establishments with company-level pacts

40 47

duration of pacts a) more than one year and less or equal two years more than two years and less or equal five years no fixed duration

26 20 38

legal form of the pact a) plant agreement (Betriebsvereinbarung) collective agreement (Tarifvertrag) written individual contract oral commitment

52 16 11 11

employee concessions with respect to working time b) working time accounts reduction of overtime work prolongation of working time with wage adjustment prolongation of working time without wage adjustment

49 38 25 35

employee concessions with respect to compensation suspension of contractual wage increases reckoning up of contractual wage increases reduction of special bonus payments

a)

100

reason for negotiating a pact a) reaction to a crisis (crisis pact) improvement of competitiveness (competitive pact)

b)

other subject matters of the pact reorganization of work further training

9 23

employers' commitments b) general job guarantee job guarantee for parts of the staff location guarantee investments at the location

53 24 59 32

The percentages do not add to 100 because of subcategories not reported in the table. The percentages do not add to 100 because multiple answers are possible. Source: IAB Establishment Panel, wave 2006; weighted data, own calculations. b)

31 19 51

550 • L. Bellmanri, K. Cerlach, and W. Meyer

Table A2 Descriptive statistics for regression samples in Table 3 and 4 Variables

Mean

Standard deviation

expected employment changes, 1 if increasing or constant, 0 if falling realized employment changes, 1 if increasing or constant, 0 if falling company-level pact, dummy, 1 if yes crisis pact, dummy, 1 if yes competitive pact, dummy, 1 if yes expected revenue changes, 1 if falling, 2 if constant, 3 if increasing proportion of qualified employees proportion of temporary employees collective agreement, dummy, 1 if yes size 5 - 9 employees, dummy, 1 if yes 1 0 - 1 9 employees, dummy, 1 if yes 20 - 49 employees, dummy, 1 if yes 5 0 - 199 employees, dummy, 1 if yes 200 - 499 employees, dummy, 1 if yes year 2005, dummy, 1 if yes year 2006, dummy, 1 if yes wage concessions, dummy, 1 if yes working time concessions, dummy, 1 if yes reorganization, dummy, 1 if yes further training, dummy, 1 if yes prolongation of working time without wage compensation, dummy, 1 if yes prolongation of working time with wage compensation, dummy, 1 if yes reduction of overtime, dummy, 1 if yes working time accounts, dummy, 1 if yes suspension of contractual wage increases, dummy, 1 if yes reckoning up of contractual wage increases, dummy, 1 if yes reduction of special bonus payments, dummy, 1 if yes number of observations

0.843 0.587 0.057 0.021 0.035 2.066 0.693 0.016 0.528 0.220 0.182 0.211 0.232 0.094 0.332 0.385 0.056 0.060 0.010 0.017 0.023

0.363 0.492 0.231 0.145 0.185 0.693 0.255 0.074 0.499 0.414 0.386 0.408 0.422 0.292 0.471 0.487 0.230 0.237 0.097 0.128 0.150

0.010

0.097

0.021 0.034 0.017 0.014 0.025 20,480

0.142 0.181 0.130 0.117 0.157

Company-Level Pacts for Employment • 551

Table A3 Determinants of company-level pacts for employment, Probit estimates and t-tests

Explanatory variables proportion of qualified employees proportion of temporary employees proportion of fixed-term employees proportion of part-time workers works council, dummy, 1 if yes collective agreement, dummy, 1 if yes non-affiliated establishments, dummy, 1 if yes size 5-9 employees, dummy, 1 if yes size 10-19 employees, dummy, 1 if yes size 20-49 employees, dummy, 1 if yes size 50 - 199 employees, dummy, 1 if yes size 200 - 499 employees, dummy, 1 if yes 40 sector dummies included number of observations Pseudo R 2

Dependent variable CLP, dummy, 1 if yes - 0.055 (0.209) 0.041 (0.557) - 1.419 * (0.822) - 0.069 (0.318) 0.818 (0.147) 0.540 *** (0.126) - 0.359 (0.281) - 1.085 *** (0.279) - 0 . 8 5 0 *** (0.219) - 0 . 8 1 1 *** (0.172) - 0 . 7 0 8 *** (0.137) - 0 . 4 5 5 *** (0.146) yes 3,925 0.2829

t-tests of sample means unmatched 0.99 1.70 *

matched 0.74 -0.13

-0.68

0.63

- 3.34 ***

0.83

14.14 ***

0.23

9.50 ***

0.71

- 5 . 7 3 ***

-0.82

- 5.82 ***

1.74 *

- 5.02 ***

- 1.03

- 3.58 * "

1.28

1.52 6.95 ***

-0.50 0.13

The columns present the estimated coefficients and in parentheses the standard errors. ***, ** and * indicate statistical significance at the 1, 5 and 10 percent level. Source: IAB Establishment Panel, wave 2005; own calculations.

552 • L. Bellmann, K. Gerlach, and W. Meyer

References Addison, J.T., C. Schnabel, J. Wagner (2007), The (Parlous) State of German Unions. Journal of Labor Research 28: 3-18. Ackermann, K.-F., S. Vollmer (1999), Firmenspezifische Bündnisse für Arbeit und Wettbewerbsfähigkeit in der Unternehmenspraxis. Pp. 147-207 in: K.-F. Ackermann, M. Kammüller (eds.), Firmenspezifische Bündnisse für Arbeitsplätze, Stuttgart. Bellmann, L. (2002), Das IAB Betriebspanel: Konzeption und Anwendungsbereiche. Allgemeines Statistisches Archiv 86: 177-188. Berthold, N., R. Fehn (1996), Evolution von Lohnverhandlungssystemen - Macht oder ökonomisches Gesetz? Pp. 57-94 in: W. Zohlnhöfer (ed.), Die Tarifautonomie auf dem Prüfstand, Berlin. Berthold, N., M. Brischke, O. Stettes (2003), Betriebliche Bündnisse für Arbeit. Gratwanderung zwischen Tarifbruch und Tariftreue. Wirtschaftswissenschaftliche Beiträge des Lehrstuhls Volkswirtschaftslehre, Wirtschaftsordnung und Sozialpolitik Nr. 64, Universität Würzburg. Berthold, N., M. Brischke, O. Stettes (2003a), Betriebliche Bündnisse für Arbeit. Eine empirische Untersuchung für den deutschen Maschinen- und Anlagenbau. Wirtschaftswissenschaftliche Beiträge des Lehrstuhls Volkswirtschaftslehre, Wirtschaftsordnung und Sozialpolitik Nr. 68, Universität Würzburg. Bispinck, R. (2005), Betriebsräte, Arbeitsbedingungen und Tarifpolitik. WSI-Mitteilungen 58: 301-307. Booth, A. (1995), The Economics of the Trade Union. Cambridge. Calmfors, L., J. Driffill (1988), Bargaining Structure, Corporatism, and Macroeconomic Performance. Economic Policy 6: 14-61. Ellguth, P., S. Kohaut (2008), Ein Bund fürs Uberleben? Betriebliche Vereinbarungen zur Beschäftigungs- und Standortsicherung. Industrielle Beziehungen 15: 209-232. Fischer, G., J. Wahse, V. Dahms, M. Frei, A. Riedmann, F. Janik (2007), Standortbedingungen und Beschäftigung in den Regionen West- und Ostdeutschland. Ergebnisse des IAB-Betriebspanels 2006. IAB Forschungsbericht Nr. 5. Fitzenberger, B., W. Franz (1999), Industry-Level Wage Bargaining: A Partial Rehabilitation The German Experience. Scottish Journal of Political Economy 45: 437-457. Fitzenberger, B., W. Franz (2000), Der Flächentarifvertrag: Eine kritische Würdigung aus ökonomischer Sicht. Pp. 191-232 in: W. Franz, H.-J. Ramser, M. Stadler (eds.), Ökonomische Analysen von Verträgen, Wirtschaftswissenschaftliches Seminar Ottobeuren, Tübingen. Hassel, A., B. Rehder (2001), Institutional Change in the German Wage Bargaining System - The Role of Big Companies. Max-Planck-Institut für Gesellschaftsforschung, Working Paper 01/ 09. Hauser-Ditz, A., M. Hertwig, L. Pries (2006), Kurzbericht. Erste Ergebnisse der BISS-Befragung. Bochum. Heckman, J.J. (1978), Dummy Exogenous Variables in a Simultaneous Equation System. Econometrica 46: 931-959. Heidemann, W. (2005), Betriebs- und Dienstvereinbarungen. Beschäftigungssicherung, Analyse und Handlungsempfehlungen. Edition der Hans-Böckler-Stiftung 8, 2. Auflage. Düsseldorf. Heinbach, W.D. (2005), Ausmaß und Grad der tarifvertraglichen Öffnung. Institut für Angewandte Wirtschaftsforschung, Tübingen, Report 2: 49-66. Hübler, O. (2005), Sind betriebliche Bündnisse für Arbeit erfolgreich? Jahrbücher für Nationalökonomie und Statistik 225: 630-652. Hübler, O. (2005a), Betriebliche Vereinbarungen zur Beschäftigungs- und Standortsicherung. Pp. 157-173 in: L. Bellmann, O. Hübler, W. Meyer, G. Stephan (eds.), Institutionen, Löhne und Beschäftigung. Beiträge zur Arbeitsmarkt- und Berufsforschung 294, Nürnberg. Hübler, O. (2006), Zum Einfluss betrieblicher Bündnisse auf die wirtschaftliche Lage der Unternehmen. Jahrbuch für Wirtschaftswissenschaften 57: 121-146. Kohaut, S., C. Schnabel (2007), Tarifliche Öffnungsklauseln - Verbreitung, Inanspruchnahme und Bedeutung. Sozialer Fortschritt 56: 33—40.

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Massa-Wirth, H., H. Seifert (2004), Betriebliche Bündnisse für Arbeit nur mit begrenzter Reichweite? WSI-Mitteilungen 57: 246-254. McDonald, I., R. Solow (1981), Wage Bargaining and Employment. American Economic Review 71: 896-908. Seifert, H., H. Massa-Wirth (2005), Pacts for employment and competitiveness in Germany. Industrial Relations Journal 36: 217-240. PD Dr. Lutz Bellmann, Institut für Arbeitsmarkt- und Berufsforschung, Bundesagentur für Arbeit, Regensburger Straße 106, 90327 Nürnberg, Germany. Phone: +49 (+)911 179 3046. E-Mail: [email protected] Prof. em. Dr. Knut Gerlach, Institut für Arbeitsökonomie, Wirtschaftswissenschaftliche Fakultät, Leibniz Universität Hannover, Königsworther Platz 1, 30167 Hannover, Germany. Phone: +49 (+)511 762 4713. E-Mail: [email protected] Prof. Dr. Wolfgang Meyer, Institut für Sozialpolitik, Wirtschaftswissenschaftliche Fakultät, Leibniz Universität Hannover, Königsworther Platz 1, 30167 Hannover, Germany. Phone: +49 (+)511 762 4587. E-Mail: [email protected]

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships By Thomas Cornelissen, Uwe Jirjahn, Hannover, and Georgi Tsertsvadze, Bad Homburg* JEL 121, J24, J31 Parental education, maternal labor force participation, schooling, wages, intergenerational mobility.

Summary Using data from the German Socioeconomic Panel (GSOEP), the study analyzes the direct and indirect effects of parental background on employees' earnings. To examine indirect effects we estimate the determinants of the employees' years of schooling. In a second step, we run wage regressions to examine direct effects. Our results suggest that the direct and indirect effects of parental background driving the intergenerational correlation of socioeconomic status are complex. It is not only important to differentiate between mother's and father's education. It is also important to take into account other parental characteristics such as maternal labor force participation and the parents' occupational status and fertility. Moreover, we find that interaction effects play an important role. The returns to schooling depend on the employees' parental background.

1

Introduction

The positive correlation between the socioeconomic status of parents and the socioeconomic status of their children appears to be a universal relationship. It can be found in virtually every society for which estimates are available (Hertz et al. 2007). However, the strength of this relationship differs remarkably across societies. While the correlation is particularly strong in countries with tradition-based economies and little industry, it is less pronounced but still substantial in industrialized countries (Levine/Jellema 2007). Among industrialized nations, intergenerational immobility is relatively low in C a n a d a , Finland, N o r w a y and Denmark and high in Britain and the US (Corak 2006). Germany lies in between these extremes whereby some studies place it close to the US (Couch/ Dunn 1997, 2 0 0 0 , Couch/Lillard 2 0 0 4 , Eisenhauer/Pfeiffer 2 0 0 8 , Lillard 2 0 0 1 , Schnitzlein 2008). The efforts of econometric studies to document intergenerational correlations of socioeconomic status are enormous. However, in most examinations, the transmission of socioeconomic status across generations is treated like a black box. Typically, the earnings of employees are regressed on their parents' earnings or education. This raises the question of which transmission mechanisms are responsible for the correlations. Theoretically four channels can be distinguished (Roemer 2 0 0 4 ) : (1) provision of social connec* The authors would like to thank an anonymous referee for helpful comments.

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 5 5 5

tions that facilitate access to education and jobs; (2) formation of skills in children through family culture and investment; (3) formation of motivation through family culture and investment; (4) genetic transmission of ability. Recently, empirical research has begun to investigate these channels in more detail (Blanden et al. 2007, Bowles/Gintis 2002, Heckman et al. 2006, Mason 2007). In this paper, we pursue a somewhat different approach to examine the transmission mechanisms of socioeconomic status. We do not explicitly investigate channels such as transmission of cognitive or noncognitive skills. Instead we examine whether parental background has indirect or direct effects on employees' earnings. Often only an indirect transmission mechanism is assumed. Parents' socioeconomic status has an effect on their offsprings' education. Education in turn has an influence on the offsprings' socioeconomic status when they are adults. Dustmann (2004) finds for Germany that parents' education and profession has a strong influence on the secondary track choice and subsequent educational achievements of their children. 1 Higher education translates into higher earnings later in life. If there is only an indirect effect, one may use variables on parental background as instruments to identify the causal effect of schooling on wages (Ichino/Winter-Ebmer 1999). However, the assumption that there are no direct effects of parental background is questionable. This has been shown by Bowles (1972) w h o found for the US that the estimated return to schooling in wage regressions is substantially biased upward when the socioeconomic status of the parents is not controlled for. Including variables for the number of siblings and the parents' permanent income, education and occupational status, he shows that social background can explain a much larger proportion of the variance of earnings than years of schooling. 2 While Bowles (1972) demonstrates a direct effect of parental background on earnings, he does not consider possible interactions between workers' own education and their parents' education. Indeed, relatively few studies examine if the returns to schooling vary with the employees' parental background. The evidence provided by these studies remains very mixed. Estimates for Sweden indicate that the returns to schooling appear to be higher for employees with highly educated fathers (Bjorklund 1994). However, this result is not statistically significant. Altonji and Dunn (1996) find for the US a significantly positive effect of parents' education, particularly mother's education, on the returns to schooling. Ashenfelter and Rouse (2000) do not differentiate between father's and mother's education. Instead they measure parental background by parents' average education. Although the differences are not statistically significant, their results indicate slightly higher returns to schooling for individuals w h o come from low socio-economic backgrounds. 3 Finally, Schnabel and Schnabel (2002) estimate the interaction effects of parental background and workers' schooling in Germany. They also do not differentiate between father's and mother's education. Their findings suggest that the returns to schooling are significantly higher for employees with less educated parents.

1

2

3

Even though there have been massive public policy interventions and educational reforms, Heineck/ Riphahn (2007) show that the intergenerational correlation of educational attainment did not change in Germany over the five last decades. Levine/Mazumder (2007) provide evidence for the US that the role of family background in determining economic success has grown in importance over time. Based on twin data, Ashenfelter/Rouse (1998) found that individuals from families in the middle of the socio-economic distribution receive slightly higher returns to schooling.

556 • T. Cornelissen, U. Jirjahn, and G. Tsertsvadze

As this brief review makes clear, more evidence is certainly warranted. Using data from the GSOEP, our study makes three contributions. First, we provide an integrative analysis of the indirect and direct effects of parental background. To examine indirect effects we estimate the determinants of the employees' years of schooling. We run wage regressions to investigate direct effects. Second, we demonstrate that parental background is multidimensional. It is important to differentiate between maternal and paternal background. Moreover, parental background cannot be reduced to parents' education. Other parental characteristics exert direct and indirect effects as well. Third, we show that interaction effects play a crucial role. Parental education, maternal labor force participation and parents' occupational status interact in determining the individual's educational achievement. Moreover, the wage regressions reveal that workers' returns to schooling depend on their parental background. Most interestingly, maternal and paternal background play different roles in shaping workers' returns to schooling. Estimating the determinants of the employees' years of schooling, we find that both mother's and father's education and occupational status have strong positive effects. Interestingly, maternal education interacts with maternal labor force participation. The effect of mother's education appears to be stronger if the mother does not work. Furthermore, parents' fertility is negatively associated with years of schooling. Controlling for the employee's years of schooling and other standard determinants, our wage regressions show a direct link between mother's labor force participation and the employee's earnings. Individuals from families with working mothers earn lower wages. A managerial position held by the mother has a particularly strong negative wage effect that is more pronounced for employees with less schooling. Moreover, the education of working mothers has a negative influence on employees' returns to schooling whereas father's education exerts a positive effect on the returns to schooling. Finally, parents' fertility has a direct negative impact on employees' earnings. In the next section we provide a theoretical discussion. Building on Krueger's (2004) graphical representation of the Becker-Rosen-Ben-Porath model, we develop several possible scenarios of the effects of parental background. Section 3 describes the data and variables. Section 4 presents the results while Section 5 concludes.

2

Theoretical background discussion

In what follows we develop four scenarios which we think are most important for our empirical analysis. While we differentiate in our estimations between different dimensions of parental background, our theoretical discussion typically treats parental background as one-dimensional. For the sake of a clear exposition the focus is on parental education. 2.1 Scenario I: indirect effect of parental education Several reasons suggest that parents' education exerts a positive influence on their offsprings' educational achievement. First, better educated parents tend to have higher incomes enabling them to invest more financial resources in their offsprings' human capital (Becker/Tomes 1979, 1986). The investments can take various forms. Rich parents can afford private lessons and better schooling for their children. This may include household location choices ensuring access to high-quality schools and to neighborhoods with a high level of average parental human capital producing strong human capital extern-

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 557

alities (Bayer et al. 2004, Benabou 1993). Moreover, parents may use their money to provide financial incentives for their children to achieve high education (Kalenkoski 2008, Weinberg 2001). Second, better educated and less educated parents may differ in their child-rearing practices. For example, Currie and Moretti (2003) find that higher maternal education improves infant health, as measured by birth weight and gestational age. Examining the pathways for the ultimate effect on health, they find that maternal education increases use of prenatal care and reduces smoking. More generally speaking, children of better educated parents grow up in homes where child-rearing methods may tend to develop cognitive and noncognitive skills which are important for educational success. Similarly, Cunha et al. (2006) and Cunha and Heckman (2007) argue that human skill formation is a multistage process. Skills (e.g., perseverance, dependability and consistency) acquired at earlier stages are important for the formation of human capital at subsequent stages. Third, social networks and institutional frameworks may play a role. Schiitz et al. (2008) find that the effect of parental background on children's educational performance is particulary strong in countries that track students at an early age into different school types. The secondary education system in Germany provides an example. 4 In Germany the decision about which educational track to follow is made at an early stage. Primary school covers the first four years. After completing primary school at the age of ten, students are tracked into one of three secondary school types: general school (Hauptschule), intermediate school (Realschule) or high school (Gymnasium). Primary school teachers make recommendations about which secondary track to choose. Bos et al. (2004) show that the recommendations do not only depend on the students' skills. Teachers' recommendations are strongly influenced by the socioeconomic status of the students' parents. Altogether, this line of reasoning suggests that parental background exerts an important indirect effect on employees' earnings. The socioeconomic status of parents has an influence on their offsprings' educational achievement. The educational achievement in turn has an influence on the offsprings' earnings when they are adults. This situation is depicted in Figure 1. Let us consider t w o types of individuals. Type 1 individuals have less educated parents whereas type 2 individuals have better educated parents. As illustrated by the lines 11 and h , the iso-present value curves of type 1 individuals are steeper than the iso-present value curves of type 2 individuals. This reflects that type 1 individuals have a higher marginal cost of acquiring human capital. First, individuals from poor families may face difficulties in financing education. Second, individuals from families with less educated parents may need to spend more effort in order to acquire human capital. In Figure 1 it is assumed that both types face the same earnings functions lnY. Individuals choose their optimal schooling level by finding the tangency between the their iso-present value curves and the earnings function. This constrainedincome maximization problem leads type 1 individuals to choose Si * years of schooling. Type2 individuals choose more years of schooling, namely S2*. Note that there is no direct effect of parental background in the situation depicted in Figure 1. Controlling for schooling in a wage regression, there should be no significant link between the employees' parental background and their earnings.

4

See Heineck/Riphahn (2007) for more details on education system in Germany.

558 • T. Cornelissen, U. Jirjahn, and G. Tsertsvadze

Figure 1 Indirect Effect of Parental Education

2.2 Scenario II: direct effect of parental education Parental background may not only have an indirect but also a direct effect on earnings. The skills that enable individuals to acquire a high level of education may also be directly important for their labor market outcomes and careers. Indeed, Mason (2007) confirms for the US that childhood family values such efficacy and achievement orientation have a direct influence on earnings. Similarly, findings by Blanden et al. (2007) and Heckman et al. (2006) indicate a direct role of cognitive and noncognitive skills. Moreover, parental background may have a direct influence if better educated parents are more able to help their offsprings in finding good jobs. For example, social networks may play a role (Calvo-Armengol/Jackson 2004). To the extent higher educated parents have better connections they have better access to relevant information about job vacancies they can pass to their offsprings. Figure 2 depicts a situation in which parental background has both a direct and an indirect effect. Type 1 and type 2 individuals do not only differ in their iso-present value curves. They also differ in the earnings functions they are facing. Type 1 is characterized by the earnings function lnY] while type 2 is characterized by lnY2. The curve depicting lnY2 runs above the curve depicting lnY], This reflects the direct effect of parental education. If a type 1 individual and a type 2 individual would have the same schooling level, the type 2 individual would still earn a higher wage. This has an important empirical implication. Even controlling for schooling in the wage regression, there should be a significant relationship between the employees' parental background and their earnings. However, the situation shown in Figure 2 implies that there should be no interaction effect between parents' education and the employees' own education. The curves representing the two earnings functions run parallel and, hence, have the same slope for a given level of schooling. This means that the returns to schooling do not depend on par-1 ental background.

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 559

Figure 2 Indirect and Direct Effect of Parental Education

2.3 Scenario III: positive interaction of parental education with employee's schooling Using the Armed Forces Qualification Test in the US, Blackburn and Neumark (1993) find that cognitive skills interacts with schooling. Individuals with higher cognitive skills have higher returns to schooling. 5 This may have implications for the role of parental background. If individuals with better educated parents have higher cognitive and noncognitive skills, they may have higher returns to schooling than individuals with less educated parents. Moreover, parents' social networks may help individuals to make more out of their own human capital investments. A positive interaction of parental socioeconomic status and the employees' own educational achievements is depicted in Figure 3. The curve for lnY2 does not only run above the curve for lnYi. It also has a steeper slope. This has several implications. First, even if the iso-present value curves 11 and h have the same slope, there will be an indirect effect of parental background. Due to the higher returns to schooling type 2 individuals have a stronger incentive to invest in their human capital than type 1 individuals. Second, there will be a direct effect of parental background on earnings. Third, parents' education will positively interact with the employees' own education. To clarify the last two implications, let us assume that there is an exogenous random variation in the years of schooling whereby Si* is the expected schooling level of type 1 individuals and Si* the expected schooling level of type 2 individuals. The random variation implies that there will be some type 1 and type 2 individuals with the same schooling level. For a given level of schooling type 2 individuals have higher returns to schooling and earn higher wages.

5

However, while this result is confirmed by several other studies (e.g., Pereira/Silva-Martins 2002, Tobias 2002), Denny/O'Sullivan (2007) find for Britain a negative interaction of cognitive skills with schooling.

560 • T. Cornelissen, U. Jirjahn, and G. Tsertsvadze

Figure 3 Positive Interaction of Parental Education with Employee's Schooling

2.4 Scenario IV: negative interaction of parental education with employee's schooling However, it may be questioned if there is a uniformly positive relationship between parents' education and their offsprings' skills. Consider for example a situation in which better educated parents have to work more hours and weeks than less educated parents. 6 In this situation, better educated parents have less time they can spend with their children. Hence, individuals from families with better educated parents may have lower skills than individuals from families with less educated parents. This may specifically hold true if better educated mothers participate in the labor force. 7 Women are disproportionately responsible for household production even when they work (Heywood/Jirjahn 2 0 0 2 ) . There is evidence that fathers spend surprisingly little time with their children regardless of the mothers' labor force participation. For the US Coverman and Sheley (1986) report men's childcare time by wife's employment, adjusted for other demographic factors, ranging from 2 5 to 2 6 minutes per day. Similarly, evidence from the German time use survey shows that working mothers spend more time on childcare than working fathers (Statistisches Bundesamt 2 0 0 3 ) . However, the survey also shows that working mothers devote less time to their children than nonworking mothers. If fathers

6

7

Bauer/Zimmermann ( 1 9 9 9 ) confirm for Germany that better educated employees are more likely to work overtime. The evidence on the relationship between maternal labor force participation and child development is mixed. One reason may be that the role of moderating factors has not been taken into account (Spitze 1 9 8 8 ) . T w o recent econometric studies by James-Burdumy ( 2 0 0 5 ) and Joshi/Verropoula ( 2 0 0 7 ) find some evidence that maternal labor force participation negatively affects child development in the very early childhood. M o s t importantly, R u h m ( 2 0 0 8 ) shows that the effect of maternal employment depends on mother's socioeconomic status. L a b o r force participation of highly educated mothers has a particularly negative impact on their offsprings' cognitive performance. M a ternal employment seems to reduce the time spent in enriching home environments.

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 561

Figure 4 Negative Interaction of Parental Education with Employee's Schooling

do not adjust their childcare time, maternal labor force participation clearly entails less parental childcare. 8 Figure 4 depicts a situation in which individuals from families with better educated parents have lower skills than individuals from families with less educated parents. The curve representing InYi runs below the curve representing In Yi. Moreover, it has a flatter slope, implying that type 2 individuals have lower returns to schooling than type 1 individuals. However, while type 2 individuals have relatively low skills, their parents have more financial resources to invest in the offsprings' schooling. Hence, the iso-present value curve I i has a flatter slope than the iso-present value curve I\. This scenario has several interesting implications. First, the indirect effect of parents' education is ambiguous. On the one hand, lower returns to schooling reduce the incentive of type 2 individuals to invest in their human capital. On the other hand, they have less difficulty to finance the human capital investment. This increases the incentive to invest. Figure 4 shows a situation in which the second effect dominates. Type 2 individuals acquire a higher amount of education even though they have lower skills than type 1 individuals. Second, parents' education has a direct negative effect on their offsprings' earnings. Third, parents' education interacts negatively with the employees' own education.

8

One might wonder if publicly subsidized childcare facilities could substitute for parental childcare. However, there still appears to be substantial underprovision of publicly subsidized childcare in Germany (Wrohlich 2 0 0 5 ) . Moreover, employer-provided childcare appears to be rare in Germany (Heywood/Jirjahn 2 0 0 8 ) . Interestingly, evidence from the US shows that difficulty in arranging childcare dramatically reduces the psychological well-being of working mothers but has no effect on husbands (Ross/Mirowsky 1 9 8 8 ) . Mother's psychological strain may also negatively affect child development.

562 • T. Cornelissen, U. Jirjahn, and G. Tsertsvadze

3

Data, variables and method

Our empirical analysis is based on the waves 2000 to 2006 of the GSOEP. The GSOEP is a representative longitudinal study of private households in Germany (SOEP Group 2001). Information on the individual employment situation and individual wages is surveyed in the recurrent annual person and household questionnaires. Information on parental background is available from a non-recurrent biography questionnaire. This biography questionnaire is usually administered during the first interview of each GSOEP respondent. Before 2000 the biography questionnaire only surveyed father's labor market status. Additional information on the mother's labor market status has been surveyed after that point of time. Our analysis is therefore based on individuals who answered the biography questionnaire since 2000. To ensure a homogeneous sample, we restrict the analysis to West Germany and consider male private sector employees with parents of German nationality. 9 We further require that the individuals have been living with both parents all the time through up to the age of 15. 10 Table 1 shows the variable definitions and descriptive statistics. Several variables capture the parental background at the respondent's age of 15. First, variables for mother's and father's years of schooling are included. Second, mother's labor force participation is controlled for. 11 Third, variables for a managerial position of the mother and a managerial position of the father are taken into account. Fourth, parents' fertility is controlled for by the number of siblings. Previous research has documented a trade-off between child quantity and quality (Hanushek 1992). 12 Our empirical analysis proceeds in two steps. First, we estimate the determinants of the employees' years of schooling. This provides information on the indirect effect of parental background. In these regressions, we also control for the individual's age to capture cohort effects. Second, we run wage regressions to examine the direct effects of parental background. The dependent variable is the log monthly gross wage. In addition to years of schooling and to our key variables for parental background, we include standard controls for tenure, years of full-time and part-time work experience, years of unemploy-

9

10 11

12

Obviously we do not consider unemployed individuals. One might wonder if the focus on employed persons involves a selection bias. If there is sorting of individuals into employment based on unobserved characteristics that also affect wages, a Heckman sample selection model should be estimated. However, this requires an instrument in the selection equation that has to be omitted from the wage equation. As we see no possibility to find a convincing instrument in our data, we do not implement a selection correction model. Note that we have included numerous parental background variables in the wage equation. This reduces the scope for a selection bias. The GSOEP asks this information only up to the age of 15. Note that only few fathers in the sample did not work. If they did not work, in almost all cases the mother also did not work. This makes it difficult to distinguish the effects of nonworking fathers from the effects of nonworking mothers. For this reason, and because nonworking fathers only represent a minor fraction of the observations, we excluded respondents with nonworking fathers from our analysis. As a robustness check we also performed estimates that included these observations. The pattern of results did not change. Orepoulos et al. (2008) provide Canadian evidence on intergenerational effects of worker displacement. They find that individuals whose fathers were displaced have lower annual earnings. However, Bauer/Gang (2001) provide mixed results.

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 563

Table 1 Variable Definitions and Descriptive Statistics (N = 4422) Variable

Definition

Mean

Std.dev.

Log monthly gross wage Schooling Mother's schooling Father's schooling Mother does not work Mother managerial position

Log monthly gross wage. The employee's years of education. The mother's years of education. The father's years of education. Dummy = 1 if the mother did not work. Dummy = 1 if the mother held a managerial position. Dummy = 1 if the father held a managerial position. Number of brothers and sisters. Dummy = 1 if information on the number of siblings is missing. Years of job tenure. Years of full-time work experience. Years of part-time work experience. Years of unemployment experience. Dummy = 1 if individual works full-time. Actual working hours per week (including usual overtime hours). The employee' age. Dummy = 1 if the observation is from 2001. Dummy = 1 if the observation is from 2002. Dummy = 1 if the observation is from 2003. Dummy = 1 if the observation is from 2004. Dummy = 1 if the observation is from 2005. Dummy = 1 if the observation is from 2006.

8.14 12.93 10.22 11.25 0.55 0.02

0.51 2.79 1.65 2.42 0.50 0.13

0.13

0.34

1.11 0.53

1.86 0.50

13.12 20.98 0.27 0.17 0.98 45.15

10.38 9.86 1.32 0.74 0.14 8.57

44.00 0.14 0.17 0.15 0.15 0.13 0.12

8.80 0.34 0.38 0.36 0.36 0.34 0.33

Father managerial position No. of siblings No. of siblings missing Tenure Full-time work experience Part-time work experience Unemployment experience Fulltime Actual working hours Age Year Year Year Year Year Year

2001 2002 2003 2004 2005 2006

ment experience, and actual w o r k i n g hours in the w a g e regressions. 1 3 N o t e that we do not include the individual's age in the w a g e regressions as the sum of full-time, part-time and unemployment experience is closely related to a g e . 1 4 N o t e that the G S O E P provides information on education in t w o w a y s . These are, first, categorial variables f o r the various education degrees (including secondary school degrees, vocational education degrees and higher education degrees) and, second, a combined variable f o r the years of schooling. T h e variable f o r years of education is constructed f r o m the surveyed categorial variables by assigning a standard number of years

13

14

Returns to parental education and returns to employees' own education are the main focus of our analysis. These returns may include the access to specific occupations and to jobs in specific types of firms or sectors. For the purpose of the present analysis we wish this to be reflected by the estimated coefficients on own education and parents' education. Therefore, we do not include occupation, firm size and sector dummies in the wage regressions. As a check of robustness we included age and its square also in the wage regressions. The results were qualitatively and quantitatively very similar to the findings presented in this paper.

5 6 4 • T. Cornelissen, U. Jirjahn, and G. Tsertsvadze

to each degree. 1 5 For example, a high school degree is counted as 13 years and a university degree is counted as additional 5 years of education. Including interactions of schooling with parental background changes the interpretation of the main (non-interacted) effects of parental background. To provide a meaningful interpretation we center the number of siblings and the variables capturing own and parents' years of schooling around their mean. 1 6 This implies that the main effects of parental background capture the effects for individuals with average years of schooling. Furthermore, note that schooling squared also enters the regressions. However, we do not interact the quadratic term with the variables on parental background in order to ensure a straightforward interpretation of the regression coefficients. In what follows we will present OLS regressions. The preceding literature on returns to education has devoted some effort to instrumental variable (IV) estimates (Card 1 9 9 9 , 2 0 0 1 , Flossmann/Pohlmeier 2 0 0 6 ) or models with family fixed effects (Altonji/Dunn 1996). However, the aim of our study is to examine the effects of various family characteristics and their interaction with the employee's years of schooling. Hence, there is little scope for implementing an IV strategy. We would not only need to find valid instruments for the employee's years of schooling but also for the interaction terms. Moreover, a model with family fixed effects cannot be applied as the family characteristics do not vary within families. A model with family fixed effects would imply that we cannot estimate the (non-interacted) main effects of parental background. 1 7

4

Empirical results

4.1 Determinants of educational achievement Table 2 presents the results on the determinants of the years of schooling. The initial regression (1) does not include interaction variables. Several variables take statistically significant coefficients suggesting that parents' socioeconomic status indeed plays an important role in the individual's educational achievement. Both mother's education and father's education are positive covariates of the individual's schooling level. Moreover, the father's occupational status has an influence. A managerial position held by the father increases the individual's schooling level by about 1.5 years. Parents' fertility is nega-

15

The details can be found in the GSOEP documentation available at http://www.diw.de/documents/ dokumentenarchiv/17/60055/pgen.pdf. We prefer to measure both parental education and employees' own education by the years of schooling. This allows us to capture the many different education degrees and possible combinations of education degrees in Germany in a one-dimensional measure with a straightforward interpretation. Using the categorical variables, we would need to interact all categories for the employees' own education with all categories for the parents' education. The resulting multitude of coefficients would not only be difficult to interpret. For sparsely populated combinations of own education and parents' education the effects would also be poorly identified.

16

Of course, in Table 1 where descriptive statistics are presented schooling is not centered around its mean. A further problem of applying a model with sibling fixed effects is that it dramatically reduces sample size (see also SchnabeL/Schnabel 2 0 0 2 ) . Identification of siblings in the GSOEP requires that they have entered the survey when they lived in the same household. This is generally the case when they were children. Moreover, the labor market status of the siblings can only be observed at adult age, i.e. several years after they first entered the GSOEP. As our analysis is based on GSOEP entrants after 2 0 0 0 , conducting a sibling analysis would reduce sample size by 9 5 percent.

17

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 565

Table 2 Determinants of Years of Schooling

(1) Mother's schooling Mother does not work Mother managerial position Mother's schooling * Mother does not work

0.339*** (0.029) - 0.052 (0.075) - 0.342 (0.428)

Mother's schooling * Mother nonmanagerial position Mother's schooling * Mother managerial position Father's schooling Father managerial position Father's schooling * Father nonmanagerial position

0.238*** 1.622*** (0.147)

Father's schooling * Father managerial position No. of siblings No. of siblings missing Age Age squared Constant R-squared N

-0.198*** (0.023) -0.558*** (0.096) 0.304*** (0.031) -0.003*** (0.000) - 6.174*** (0.659) 0.276 4422

(2) -0.043 (0.075) 1.046* (0.566) 0.413*** (0.035) 0.317*** (0.038) - 0.002 (0.079) (0.023) 2.207*** (0.173) 0.326*** (0.026) 0.061* (0.035) -0.180*** (0.023) - 0.535*** (0.095) 0.330*** (0.030) - 0.004*** (0.000) - 6.767*** (0.654) 0.287 4422

Notes: Robust standard errors in parantheses. * statistically significant at the 10 %-level; ** at the 5%-level; *** at the 1 %-level. The following variables are centered around the mean; all schooling variables, the number of siblings. Method: OLS

tively associated with the years of schooling. The mother's labor market status appears to play no role. Neither mother's labor force participation in general nor a managerial position held by the mother is a statistically significant determinant of the individual's educational achievement. However, the pattern of influences may remain obscured until interaction effects between our key variables have been considered. The estimates shown in column (2) take into account those interaction effects. 1 8 The results show a far richer pattern of influences than those of the initial regression. N o t only 18

In regression (2) the non-interacted variables for mother's and father's schooling are dropped because parents' schooling is interacted with the full set of occupational status dummies. This allows t o directly compare the effects of parents' schooling on the individual's schooling by occupational status without adding the interaction effects to the effects of the reference category.

566 • T. Cornelissen, U. Jirjahn, and G. Tsertsvadze

the father's but also the mother's managerial position now plays a role. The variable for a managerial position of the mother takes a significantly positive coefficient. Compared to a working mother without a managerial position, a mother with a managerial position is associated with about one more year of schooling. Furthermore, the results reveal a remarkable heterogeneity in the effects of parental education. Mother's education has a strong positive effect on the individual's educational achievement if the mother does not work. The positive effect of mother's education is lower but still significant if she has a job without a managerial position. Mother's education has no significant effect on her offspring's schooling level if she holds a managerial position. Interestingly, the effect of the father's education is also declining in the father's occupational status. However, it is still significant even for fathers with a managerial position. Altogether, the estimates suggest that the higher the occupational status of the parents, the less parental education translates into higher educational attainment of their children. Parents who are more engaged in their occupational career may have less time they can spend with their children. Remarkably, there is no effect of maternal education if the mother held a managerial position. However, while parents' managerial position reduces the role of parental education, the parents' managerial position itself has a positive influence on their children's educational attainment. This might reflect specific family values, a strong financial background or parents' social networks. 4.2 Determinants of earnings

Parental background may not only have an indirect but also a direct effect on the employees' earnings. To examine those direct effects we run wage regressions. Table 3 presents the results. Specification (1) is a standard wage regression that does not control for family background. Schooling enters the wage equation as a linear and quadratic term. Again, as before, the schooling is centered around its mean. The coefficient on the linear term is equal to 0.1. It represents the returns to schooling for an individual with mean schooling years. This result is well in the range of usual estimates. The returns to schooling reported by Gebel and Pfeiffer (2007) range from 5 percent to 14 percent. The effects of the other control variables conform to expectations and vary only slightly between the three specifications. Specification (2) adds variables on parental background but does not include interaction variables. The coefficients on schooling and schooling squared remain largely unchanged. This contrasts with the findings by Bowles (1972). Nevertheless, the estimates show that parental background indeed has a direct effect on the employees' earnings. Parents' fertility is negatively associated with the log monthly gross wage. Moreover, the mother's labor market status plays a role. We find a positive wage effect of about 2.8 percent if the mother did not work and a negative wage effect of about 10 percent if the mother held a managerial position. The reference category are working mothers without a managerial position. Mother's education plays no role in regression (2). Furthermore, the father's education and occupational status has no significant effect in this regression. However, again, the pattern of results may remain partially obscured until interaction effects have been taken into account. Interaction variables are included in specification (3). The regression reveals that parental background also has an effect on the returns to the employees' own years of schooling. The statistically positive coefficient on the interaction variable 'Schooling * Father's schooling' implies that the returns to own education are higher for employees from fa-

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 567

Table 3 Determinants of Log Monthly Gross W a g e (1) Schooling Schooling squared

0.102*** (0.003) -0.005*** (0.001)

Mother's schooling Mother does not work Mother managerial position

(2)

(3)

0.099*** (0.003) -0.005*** (0.001) 0.008 (0.005) 0.028** (0.011) - 0.098** (0.046)

0.101*** (0.006) -0.006*** (0.001) 0.015* (0.009) 0.023* (0.012) -0.209*** (0.070) -0.007*** (0.002) -0.001 (0.004) 0.053*** (0.016) 0.005* (0.003) 0.008 (0.011) -0.004 (0.004) - 0.035 (0.030) 0.004*** (0.001) 0.009 (0.008) - 0.008* (0.005) -0.001 (0.002) -0.059*** (0.014) - 0.002 (0.005) 0.009*** (0.002) -0.000 (0.000) 0.031*** (0.003) -0.001*** (0.000) -0.049*** (0.010) 0.006*** (0.001) -0.044*** (0.013)

Schooling * Mother's schooling Schooling * Mother does not work Schooling * Mother managerial position Schooling * Mother schooling * Mother does not work Mother's schooling * Mother does not work 0.004 (0.003) - 0.014 (0.022)

Father's schooling Father managerial position Schooling * Father's schooling Schooling * Father managerial position

-0.007** (0.004)

No. of siblings Schooling * No. of siblings No. of siblings missing

-0.058*** (0.014)

Schooling * No. of siblings missing Tenure Tenure squared/100 Full-time work experience Full-time work experience squared / 100 Part-time work experience Part-time work experience squared / 100 Unemployment experience

0.009*** (0.002) -0.000 (0.000) 0.031*** (0.003) - 0.001*** (0.000) -0.052*** (0.011) 0.006*** (0.001) -0.045*** (0.013)

0.009*** (0.002) -0.000 (0.000) 0.030*** (0.003) -0.001*** (0.000) -0.051*** (0.011) 0.006*** (0.001) -0.044*** (0.013)

568 • T. Cornelissen, U. Jirjahn, and G. Tsertsvadze

Table 3 continue Fulltime Actual working hours Year 2001 Year 2002 Year 2003 Year 2004 Year 2005 Year 2006 Constant R-squared N

(1)

(2)

(3)

0.601*** (0.069) 0.015*** (0.001) -0.012 (0.018) 0.108*** (0.018) 0.148*** (0.019) 0.154*** (0.020) 0.140*** (0.020) 0.136*** (0.021) 6.371*** (0.076) 0.506 4422

0.609*** (0.069) 0.015*** (0.001) -0.012 (0.018) 0.104*** (0.018) 0.144*** (0.019) 0.152*** (0.020) 0.137*** (0.020) 0.133*** (0.021) 6.395*** (0.078) 0.509 4422

0.602*** (0.068) 0.015*** (0.001) -0.012 (0.018) 0.104*** (0.018) 0.143*** (0.019) 0.151*** (0.020) 0.135*** (0.020) 0.132*** (0.020) 6.409*** (0.076) 0.513 4422

Notes: Robust standard errors in parantheses. * statistically significant at the 10 %-level; ** at the 5 %-level; *** at the 1 %-level. The following variables are centered around the mean: all schooling variables, the number of siblings. Method: OLS

milies with well-educated fathers. However, there appears to be no wage effect of the father's occupational status. Furthermore, while maternal education now has a significantly positive baseline effect, the influence of mother's education on the employee's returns to schooling depend on the mother's labor force participation. The coefficient on the interaction variable 'Schooling * Mother's schooling' equals — 0.007 whereas the coefficient on the triple interaction variable 'Schooling * Mother's schooling * Mother does not work' equals 0.005. A t-test cannot reject the null hypothesis that the sum of both coefficients is equal to zero. These results imply that maternal education has no influence on the returns to schooling if the mother did not work. Hence, only the positive baseline effect remains. In contrast, maternal education is associated with lower returns to the employee's own schooling if she participated in the labor force. Moreover, there is still a negative wage effect of working mothers who had held a managerial position. The effect appears to be particularly strong for employees with low educational achievements and to weaken with rising educational achievement, which can be seen from the positive coefficient on the interaction term 'Schooling * Mother managerial position'. 1 9 Finally, parents' fertility is still a negative directs determinant of the employee's earnings. However, it does not interact with the employee's years of schooling.

19

As a further check of robustness we added a triple interaction of own schooling, mother's schooling and a managerial position of the mother. This variable did not emerge as a statistically significant determinant. The same triple interaction for fathers also did not show a significant effect.

Parental Background and Earnings: German Evidence on Direct and Indirect Relationships • 569

5

Conclusions

O u r results suggest that the direct a n d indirect effects of parental b a c k g r o u n d driving the intergenerational correlation of socioeconomic status are complex. It is not only important to differentiate between maternal and paternal background. It is also i m p o r t a n t t o take into account other parental characteristics such as maternal labor force participation and parents' occupational status and fertility. The empirical findings can be interpreted in light of our theoretical considerations. Low parental fertility has both a positive indirect effect (via educational achievement) a n d a positive direct effect o n the employees' earnings. However, it does not influence the returns to schooling. Hence, its effects accord with Scenario II. A managerial position held by the father exerts a positive indirect effect but n o direct effect on the employees' earnings. This is the situation described by Scenario I. A managerial position held by the m o t h e r exerts also a positive indirect effect. However, additionally it has a direct negative effect on earnings that specifically holds true for employees with low levels of schooling. The father's education has a positive influence on the individuals' educational achievements. Moreover, individuals with highly educated fathers have higher returns to schooling. Altogether, the role of paternal education accords with Scenario III. While the effects of paternal education are relatively independent of the father's occupational status, the direct a n d indirect effects of maternal education a p p e a r to depend strongly on the mother's labor force participation. If the m o t h e r does not w o r k , her education u n a m biguously has both indirect and direct positive effects on her offsprings' earnings. In this case, our findings accord with Scenario II. However, the role of maternal education appears to be reduced if the m o t h e r participates in the labor force. Depending o n her occupational status, the education of a w o r k i n g m o t h e r has a smaller or even zero influence on her offsprings' years of schooling. Moreover, the education of working mothers is negatively associated with the employees' returns to schooling. Hence, if the m o t h e r works, maternal education may rather play a role similar to that described by Scenario IV. This situation clearly calls for further research. First, it may reflect women's disproportionate responsibility for household production even w h e n they w o r k . Second, it may indicate a relatively low responsiveness of fathers' childcare time with respect to their own occupational status and with respect to the mothers' labor force participation. We end with some remarks on the policy implications of our findings. O n e m a y w o n d e r if the extension of high-quality childcare provision may reduce the negative effects of m o t h e r s ' labor force participation. Yet, to the extent higher educated m o t h e r s benefit disproportionately f r o m childcare, extended childcare provision may strengthen the intergenerational correlation of socioeconomic status.

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Denny, K., V. O'Sullivan (2007), Can Education Compensate for Low Ability? Evidence f r o m British Data. Applied Economics Letters, Forthcoming. D u s t m a n n , C. (2004), Parental Background, Secondary School Track Choice and Wages. O x f o r d Economic Papers 56: 2 0 9 - 3 0 . Eisenhauer, P., F. Pfeiffer (2008), Assessing Intergenerational Earnings Persistence A m o n g Germ a n Workers. Z E W Discussion Paper N o . 0 8 - 0 1 4 , M a n n h e i m . Flossmann, A.L., W. Pohlmeier (2006), Causal Returns to Education: A Survey on Empirical Evidence for Germany. Jahrbücher für Nationalökonomie und Statistik 226: 6 - 2 3 . Gebel, M . , F. Pfeiffer (2007), Educational Expansion and its Heterogeneous Returns for Wage Workers. Z E W Discussion Paper N o . 0 7 - 0 1 0 , M a n n h e i m . H a n u s h e k , E.A. (1992), The Trade-off between Child Quantity and Quality. Journal of Political Economy 100: 8 4 - 1 1 7 . H e c k m a n , J.J., J. Stixrud, S. Urzua (2006), The Effects of Cognitive and Noncognitive Abilities on Labor M a r k e t Outcomes and Social Behavior. Journal of Labor Economics 24: 4 1 1 - 4 8 2 . Heineck, G., R. Riphahn (2007), Intergenerational Transmission of Educational Attainment in Germany: The Last Five Decades. IZA Discussion Paper N o . 2985. Hertz, T., T. Jayasundera, P. Piraino, S. Selcuk, N . Smith, A. Verashchagina (2007), The Inheritance of Educational Inequality: International Comparisons and Fifty-Year Trends. The B.E. Journal of Economic Analysis and Policy 7(2), Article 10. H e y w o o d , J.S., U. Jirjahn (2008), Family Friendly Practices and Worker Representation: Germ a n Evidence. Industrial Relations, Forthcoming. H e y w o o d , J.S., U. Jirjahn (2002), Payment Schemes and Gender in Germany. Industrial and Labor Relations Review 56: 4 4 - 6 4 . Ichino, A., R. Winter-Ebmer (1999), Lower and Upper Bounds of Returns to Schooling: An Exercise in IV Estimation with Different Instruments. European Economic Review 43: 8 8 9 - 9 0 1 . James-Burdumy, S. (2005), The Effect of Maternal Labor Force Participation on Child Development. Journal of Labor Economics 23: 1 7 7 - 2 1 1 . Joshi, H., G. Verropoula (2007), Does Mothers' Employment Conflict with Child Development? Multilevel Analysis of British Mothers Born in 1958. Journal of Population Economics, Forthcoming. Kalenkoski, C. (2008), Parent-Child Bargaining, Parental Transfers, and the Post-Secondary Education Decision. Applied Economics 40: 4 1 3 - 3 6 . Krueger, A.B. (2004), Inequality, Too M u c h of a Good Thing. Pp. 1 - 7 5 in: J.J. H e c k m a n , A.B. Krueger (eds.), Inequality in America: W h a t Role for H u m a n Capital Policies? Cambridge. Levine, D.I., J.R. Jellema (2007), G r o w t h , Industrialization, and the Intergenerational Correlation of Advantage. Industrial Relations 46: 1 3 0 - 7 0 . Levine, D.I., B. M a z u m d e r (2007), The Growing Importance of Family: Evidence f r o m Brothers' Earnings. Industrial Relations 46: 7 - 2 1 . Lillard, D.R. (2001), Cross-National Estimates of Intergenerational Mobility in Earnings. Vierteljahreshefte zur Wirtschaftsforschung 70: 5 1 - 5 8 . M a s o n , P.L. (2007), Intergenerational Mobility and Interracial Inequality: The Return to Family Values. Industrial Relations 46: 5 1 - 8 0 . Oreopoulos, P., M . Page, A.H. Stevens (2008), The Intergenerational Effects of Worker Displacement. Journal of Labor Economics 26: 455—483. Pereira, P., P. Silva-Martins (2002), Is There a Return-Risk Relationship in Education? Economics Letters 75: 3 1 - 3 7 . Roemer, J.E. (2004), Equal Opportunity and Intergenerational Mobility: Going Beyond Intergenerational Income Transition Matrices. Pp. 4 8 - 5 7 in: M . Corak (ed.), Generational Income Mobility in N o r t h America and Europe, Cambridge University Press. Ross, C.E., J. Mirowski (1988), Child Care and Emotional Adjustment to Wives' Employment. Journal of Health and Social Behavior 29: 1 2 7 - 3 8 . R u h m , C.J. (2008), Maternal Employment and Adolescent Development. Labour Economics 15: 958-983. Schnabel, I., R. Schnabel (2002), Family and Gender Still Matter: The Heterogeneity of Returns to Education in Germany. Z E W Discussion Paper N o . 0 2 - 6 7 , M a n n h e i m .

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Schnitzlein, D.D. (2008), Verbunden über Generationen - Struktur und Ausmaß der intergenerationalen Einkommensmobilität in Deutschland. IAB Discussion Paper N o . 1/2008. Schütz, G., H.W. Ursprung, L. W ö ß m a n n (2008), Education Policy and Equality of Opportunity. Kyklos 61: 2 7 9 - 3 0 8 . SOEP G r o u p (2001), The German Socio-Economic Panel (GSOEP) after more than 15 years Overview, Pp. 7 - 1 4 in: E. Holst, D.R. Lillard, T.A. DiPrete (eds.), Proceedings of the 2 0 0 0 Fourth International Conference of German Socio-Economic Panel Study Users (GSOEP 2000), Vierteljahreshefte zur Wirtschaftsforschung 70. Spitze, G. (1988), Women's Employment and Family Relations: A Review. Journal of Marriage and the Family 50: 5 9 5 - 6 1 8 . Statistisches Bundesamt (2003), Wo bleibt die Zeit? Die Zeitverwendung der Bevölkerung in Deutschland 2001/02. Can be downloaded at: http://www.destatis.de/jetspeed/portal/cms/ Sites/destatis/Interne t/DE/Presse/pm/frueher/wobleibtdiezeit,property=file.pdf (last retrieved 18.06.2008). Tobias, J.L (2002), Are Returns to Schooling Concentrated a m o n g The M o s t Able? A Semiparametric Analysis of the Ability-Earnings Relationships. O x f o r d Bulletin of Economics and Statistics 65: 1 - 2 9 . Weinberg, B. (2001), An Incentive Model of the Effect of Parental Income on Children. Journal of Political Economy 109: 2 6 6 - 8 0 . Wrohlich, K. (2005), The Excess Demand for Subsidized Child Care in Germany. IZA Discussion Paper N o . 1515, Bonn. Dipl.-Ok. T h o m a s Cornelissen, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Institut für Empirische Wirtschaftsforschung, Königsworther Platz 1, 3 0 1 6 7 Hannover, Germany. Phone: + 4 9 (0)511 762 5661. E-Mail: [email protected] Privatdozent Dr. Uwe Jirjahn, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, Institut für Arbeitsökonomik, Königsworther Platz 1, 3 0 1 6 7 Hannover, Germany. Phone: + 4 9 (0)511 762 4336. E-Mail: [email protected] Dr. Georgi Tsertsvadze, Feri Rating 8c Research AG, Rathausplatz 8 - 1 0 , 6 1 3 4 8 Bad H o m b u r g , Germany. Phone: + 4 9 (0)6172 916 3200. E-Mail: [email protected]

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

Relative Demand and Supply of Skills and Wage Rigidity in the United States, Britain, and Western Germany By Patrick A. Puhani, Hannover* JEL E24, J21, J31, J64 Wage, earnings, unemployment, non-employment, rigidity.

Summary I extend a two-skill group model by Katz and Murphy ( 1 9 9 2 ) to estimate relative demand and supply for skills as well as wage rigidity in Germany. Using three data sets for Germany, two for Britain and one for the United States, I simulate the change in relative wage rigidity (wage compression) in all three countries during the early and mid 1 9 9 0 s , this being the period when unemployment increased in Germany but fell in Britain and the US. I show that in this period, Germany experienced wage compression (relative wage rigidity), whereas Britain and the US experienced wage decompression. This evidence is consistent with the Krugman ( 1 9 9 4 ) hypothesis.

1

Introduction

C o n t r a s t i n g d e v e l o p m e n t s in u n e m p l o y m e n t rates a n d w a g e inequality b e t w e e n the United S t a t e s a n d the U n i t e d K i n g d o m o n the o n e h a n d (falling u n e m p l o y m e n t , rising w a g e i n e q u a l i t y ) a n d several c o n t i n e n t a l E u r o p e a n c o u n t r i e s like G e r m a n y o n t h e o t h e r (rising u n e m p l o y m e n t , n o m a j o r increase in w a g e i n e q u a l i t y ) led K r u g m a n ( 1 9 9 4 ) t o c o n c l u d e t h a t these t w o d e v e l o p m e n t s are " t w o sides o f the s a m e c o i n " , i.e. decreasing relative d e m a n d f o r l o w - s k i l l e d w o r k e r s . In the " f l e x i b l e " m a r k e t e c o n o m i e s this relative dem a n d s h o c k for t h e l o w skilled w o u l d t r a n s l a t e i n t o l o w e r relative w a g e s f o r this g r o u p a n d thus rising returns t o skill. In c o n s e n s u s - b a s e d systems like G e r m a n y , w i t h less e c o n o m i c f r e e d o m , w a g e rigidity c o m b i n e d w i t h negative d e m a n d s h o c k s f o r l o w - s k i l l e d w o r k e r s w o u l d i n c r e a s e u n e m p l o y m e n t . W h e r e a s w a g e rigidities m i g h t e x i s t even w i t h out l a b o u r m a r k e t r e g u l a t i o n s , e.g. due to n o t i o n s o f fairness t h a t m a n a g e r s voluntarily a p p l y (Bewley 1 9 9 9 , Falk/Fehr 1 9 9 9 ) , the G e r m a n l a b o u r m a r k e t is a d d i t i o n a l l y chara c t e r i s e d by a c o m p a r a t i v e l y s t r o n g influence o f t r a d e u n i o n s o n w a g e setting t h r o u g h c o l l e c t i v e b a r g a i n i n g . T h i s w a g e b a r g a i n i n g system seems t o c o m p r e s s the w a g e distrib u t i o n ( H u b l e r 1 9 8 3 , F r a n z et al. 2 0 0 3 , Gerlach/Stephan 2 0 0 6 ) . H i i b l e r a n d M e y e r

* Leibniz Universität Hannover; SIAW, University of St. Gallen; ERMES, Université Paris II; IZA, Bonn. This research was supported by the Volkswagen Foundation and by the German Research Foundation (Deutsche Forschungsgemeinschaft) under the project 'Labour Market Effects of Social Policy' (Arbeitsmarkteffekte sozialpolitischer Maßnahmen). Many thanks also go to IZA, Bonn, for supporting this project and my research visit to IZA. Part of the work on this paper was done during my leave at the Economics Department at MIT, whose hospitality and support are gratefully acknowledged. I thank an anonymous referee for helpful comments. All remaining errors are my own.

574 • P.A. Puhani

Year

Figure 1 Unemployment Rates 1960 - 2000

Note: "The U.S. unemployment rate is based on the CPS, which uses a definition of unemployment equivalent to the ILO definition. For Western Germany, OECD figures only provide the registered unemployment rate for a longertime period. Comparing the registered with the OECD standardized unemployment rate for united Germany suggests about a 1.5 percent difference between the two, so that the standardised unemployment rate for western Germany would also be lower than depicted in the graph. For the UK, however, the standardised unemployment rate is about 1 percentage point higher than the registered one shown in the graph. It is, however, not available for such a long time period" (Puhani, 2008). Source: OECD.

(2001) stress the importance of works councils in wage compression, but the impact of works councils seems smaller in establishments covered by collective bargaining (Hiibler/Jirjahn 2003). CorneliKen and Hiibler (2008) discuss the implications of wage rigidity on job mobility in Germany. Several studies establish that wage inequality has risen less in Germany than in the US or the UK (Gottschalk/Smeeding 1997, Steiner/Wagner 1998, Fitzenberger 1999, Katz/ Autor 1999, Acemoglu 2003 1 ). As Figure 1 shows, it was in the 1990s that unemployment in Germany increased whereas it decreased in the US and in the UK. In a recent paper, Dustmann, Ludsteck and Schonberg (2007) show that overall wage inequality (combining inequality "within" and "between" educational groups) in Germany has in fact increased continuously in Germany since the mid 1970s (see also Fitzenberger 1999), but returns to formal education (inequality between educational groups) have risen only since the 1990s, but not in the 1980s (or 1970s) as they did in the US and the UK. Recent increases in overall wage inequality in Germany are also document

1

Acemoglu (2003)'s results suggest otherwise by displaying in his Table l a a jump in the 90/10 decile ratio during the early 80s. However, this jump is driven by using two different data sets: the Luxembourg Income Study used by Acemoglu (2003) switches source data between 1981 and 1984 (http://www.lisproject.org/techdoc/ge/geindex.htm).

Relative D e m a n d and Supply of Skills and W a g e Rigidity • 5 7 5

in Kohn (2006), who similar to Fitzenberger and Wunderlich (2002), analyses the German wage structure by gender and type of employment (full-time/part-time). As I show based on three German, two British and one US data set from the early to mid 1990s, when unemployment rose in Germany but fell in the US and the UK, the returns to higher versus apprenticeship or high school education did not rise in Germany, but did so in the US and the UK. This is in spite of the fact that all three countries experienced an increase in the relative demand for skill. The divergence in wage developments is explained by two factors. First, Germany experienced a somewhat larger increase in the relative supply of skills than the US. Second, my simulation shows that the German labour market, unlike the US or the UK, has been characterised by relative wage rigidity (as defined in the following section) in the early and mid 1990s. The results can be reconciled with the findings of Dustmann et al. (2007), who do not explicitly focus on wage rigidity, in the following way: despite an increase in overall wage inequality as documented by these authors, the returns to skill seem not to have been flexible enough in Germany to accommodate changes in the skill composition of the working age population by corresponding changes in the skill composition in employment. The institutionalized nature of wage bargaining for large parts of the German labour force is consistent with this rigidity. The paper is structured as follows. Differences in the changes of the relative skill supply and demand structures between countries are documented in Section 2, where I also derive the relative wage rigidity. Section 3 concludes. 2

Relative demand and supply of wkills and wage rigidity

I draw on several person-level data sets to create cell data and adopt a constant elasticity of the substitution (CES) production function framework similar to Katz and Murphy (1992), Autor, Katz and Krueger (1998), and Acemoglu (2003). The data sets used are the Current Population Survey Merged Outgoing Rotation Group (CPS-MORG) files for the US, the British Labour Force Survey (BLFS) and the British Household Panel Study (BHPS) for Britain and the German Socio-Economic Panel (GSOEP), the German Labour Force Survey (Mikrozensus, GLFS), and the German social security record (IABR) for Germany. To obtain reliable estimates for developments across time, large sample sizes are desirable. From this perspective, the CPS-MORG, BLFS, GLFS and IABR data would be my preferred data sets. For example, in the base year used for the simulations below, these data sets contain 285,386, 38,568, 276,031, and 228,669 observations, respectively.2 The corresponding numbers are 8,946 and 8,615 for the BHPS and the GSOEP, respectively. Another important criterion for data quality for the purposes of this study is precise measurement of the hourly wage. All data sets, except the IABR are survey data. Although administrative data like the IABR may be more reliable than survey data, I do not observe hours worked in the IABR and can only distinguish between fulltime and part-time workers. Hence, when measuring the wage in the IABR, I will only consider full-time workers. Another problem is posed by the GLFS, where I

2

The BLFS is actually five times as large, but I restrict myself to the subsample of observations who were asked on their wage. In 1993, when the question on the wage was first introduced into the BLFS, only a fifth of the sample was asked this question.

576 • P.A. Puhani

only net hourly income are observed in intervals (I use the midpoints). 3 Hence, gross hourly wages for Germany are only available in the small GSOEP. However, GSOEP data also suggest that gross and net hourly wage inequality do not differ that much in Germany. For the US and British data sets, gross hourly wages are available. Measurement of employment is straightforward, although I make an adjustment for part-time employees: in the simulations below they are counted only as 50 percent employed. Part-time workers are those working 30 hours or less (in the IABR, hours of work are not given, but part-time work is indicated by a binary variable). In an extension to the approach by Katz and Murphy (1992), I distinguish between labour demand and supply, whereby the latter is proxied by the working age population and the former is given by employment. Proxying changes in labour supply by changes in the working age population can be justified by assuming that a labour market should provide work opportunities for the working age population. It is of course possible that institutions provide incentives for members of the working age population not to supply labour. As far as these tendencies increase over time, they would be accounted for as rigidities in my approach. These need not be correct in all cases, but in many this accounting is appropriate: for example, if a person does not participate in the labour market because the availability of welfare raises the reservation wage, then welfare acts like a minimum wage and thus acts like a wage rigidity. To obtain a descriptive picture of relative skill supplies (S), demands (N), and wage (W) rigidities in the US, Britain, and western Germany in the 1990s, the production of output Y is specified with high- (H) and low-skilled (L) labour as the two inputs (see Fitzenberger/Kohn, 2006, for an extension to three skill and six age groups; for the following exposition, cf. Puhani, 2005, who essentially uses the same methodology as in this paper). 4 Technology is represented by the factor-augmenting terms Af, and A/ for high and low-skilled labour, respectively: Yt =

[AltLty+(AhtHtyfM.

In a competitive labour market, the (relative) wage will be equal to the (relative) marginal product. This implies that the relative demand index In { ^ J

1 = ffln

{w^j + ' n

)

is implicitly identified (and estimated, 'hats' indicating estimated values will henceforth be dropped) by

3

4

Where top coding occurs (GSOEP, IABR and to a minor extent in the CPS-MORG), I multiply top coded wages by 1.5 (cf. Autor et al. 1 9 9 8 , Acemoglu 2 0 0 2 ) . Censoring a log-normal distribution with a standard deviation of 0 . 5 5 yields the following factors for the means in the top-coded intervals as a multiple of the censoring percentile: 60 t h percentile: factor 1 . 4 5 ; 80 t h percentile: factor 1 . 3 4 ; 95 t h percentile: factor 1.24; 99 t h percentile: factor 1 . 1 9 . As I mention in Puhani (2005: 563) "Alternatively, one may view Y a s a labour composite which is part of another production function that also contains capital (cf. Heckman et al., 1 9 9 8 : 16). An elasticity of substitution of 1 between capital and this aggregate labour composite (cf. Heckman et al. 1 9 9 8 : 25ff.) justifies ignoring capital and so I follow this procedure as Katz and Murphy (1992), Autor et al. (1998), and Acemoglu (2002) do."

Relative D e m a n d and Supply o f Skills and W a g e Rigidity • 577

H o w e v e r , this requires an a s s u m p t i o n o n the elasticity of substitution. Based o n previous l i t e r a t u r e p r o p o s i n g a r a n g e b e t w e e n 1 a n d 2 , 1 a s s u m e a = 1 / ( 1 — p) = 1 . 4 . 5 T h e s e n u m b e r s a r e l o w e r t h a n in F i t z e n b e r g e r a n d K o h n ' s ( 2 0 0 6 ) e s t i m a t e s b a s e d o n 1 8 g r o u p s ( t h r e e skill t i m e s s i x a g e g r o u p s ) , b u t n o t e t h a t a m o r e r e f i n e d c l a s s i f i c a t i o n o f skill g r o u p s (almost) by d e f i n i t i o n implies higher substitutability t h a n a binary definition as used here ( f o l l o w i n g the largest part of the international literature).6 Nh a n d N ; are d e m a n d e d ( e m p l o y e d ) quantities of high a n d l o w - s k i l l e d labour, respectively. A s relative w a g e s l n ^ ^

a n d r e l a t i v e e m p l o y m e n t In ( j ^ j are o b s e r v e d in t h e

data, the implicit relative d e m a n d f u n c t i o n w i t h k n o w n elasticity of substitution identifies the relative d e m a n d index. I s i m u l a t e r e l a t i v e w a g e r i g i d i t y t h a t h a s a r i s e n s i n c e m y b a s e y e a r to = 1 9 9 1 7 b y a s s u m i n g t h a t r e l a t i v e s u p p l y is i n e l a s t i c a n d c h a n g e s in r e l a t i v e s u p p l y e q u a l c h a n g e s in t h e

5

6

7

As I m e n t i o n in Puhani (2005: 564) "This range is derived in Freeman's (1986: 366) survey, but also m o r e recent estimates by K a t z / M u r p h y (1992: 72), H e c k m a n et al. (1998: 26) and C a r d / L e m i e u x (2001: 734) find elasticities of 1.4, 1.441, and of between 1.1 and 1.6, respectively. Consequently, A u t o r et al. (1998) a n d Acemoglu (2002) use the value of 1.4 for their simulations. Although this evidence is mostly f r o m the U.S., Angrist's (1995) estimates for the West Bank and the Gaza Strip imply an elasticity of substitution of a similar order, viz. 1.9 (derived as 1/(0.25 + 0.28) f r o m Angrist's, 1 9 9 5 : 1080; estimates). T h e O E C D estimate of 1.1 by M a n a c o r d a / P e t r o n g o l o (1999: 191) is based o n different definitions of 'skilled' versus 'unskilled', as can be seen f r o m t h e d a t a a p p e n d i x in their article (here, 'skilled' encloses qualifications significantly below college degree in G e r m a n y , for example). It is r e m a r k a b l e t h a t despite different definitions, their estimate for a b r o a d range of O E C D countries is not t o o dissimilar f r o m o t h e r estimates, either. In my case, the imposition of a c o m m o n elasticity of 1.4 across the three countries m a y be subject t o d e b a t e . However, as e q u a t i o n (4) below shows, the exact size of the elasticity of substitution c a n n o t m a k e a qualitative difference (in terms of the sign of the simulated relative w a g e rigidity term) to my simulations. Fitzenberger/Kohn's (2006) estimates of the elasticity of substitution between any of three skill g r o u p s are between 4.9 and 6.9, w h e r e a s the estimates of the elasticity of substitution between any of six age g r o u p s range between 5.2 and 20.1. H e n c e the a u t h o r s reject t h a t the elasticity of substitution b e t w e e n any t w o age g r o u p s is infinity. This is, however, w h a t is implicitly assumed in K a t z / M u r p h y ' s (1992) and m y model w h e n w e define only t w o skill g r o u p s ignoring age (such is the n a t u r e of abstraction: one makes mistakes but hopes t o extract the essence of reality). N o t e t h a t not only the fact t h a t m o r e t h a n t w o g r o u p s are defined raises the elasticity of substitution, but also the fact t h a t Fitzenberger/Kohn's (2006) m o r e refined model implicitly holds age c o n s t a n t w h e n assessing the elasticity of substitution between any t w o skill groups. By controlling for age, Fitzenberger/Kohn's (2006) elasticity of substition between any t w o skill g r o u p s relate t o w o r k e r s with different skills but the same age. In my case, I ignore the fact t h a t w o r k e r s with different skills might have different age structures, because at my level of abstraction age is ignored by the a s s u m p t i o n t h a t different age g r o u p s are perfectly substitutable. T h e fact t h a t in reality different skill g r o u p s also differ by age together with the fact t h a t different age g r o u p s might not be perfectly substitutable is likely t o bias the estimated elasticity of substitution between t w o skill g r o u p s d o w n w a r d c o m p a r e d to estimates based o n the model of Fitzenberger/Kohn (2006). Hence, I see n o a priori conflict between Fitzenberger/Kohn's (2006) estimates and the 'consensus' view in the literature t h a t the elasticity of substitution between ' h i g h ' and 'low-skilled' w o r k e r s lies between 1 a n d 2. To solve this issue empirically, one w o u l d have t o estimate elasticities of substitution with the same d a t a , once with the model restrictions of Fitzenberger/Kohn (2006) and once with the model restrictions of K a t z / M u r p h y (1992). Due t o lack of w a g e data before 1993, the base year for the BLFS is 1993. Generally, the effects of alternative choices for the base year can easily be assessed f r o m observing the results graphically in Figure 2 below.

578 • P.A. Puhani

relative population of the two skill groups, l n ^ j (as in Puhani 2 0 0 5 ) . 8 ' 9 Therefore, I define the 'market relative wage' as In

= WIt

n

/Market

In

Ht

-In

K ^ r - K I : '

(2)

The first term of the sum on the right hand side of equation (2) is the relative wage which creates equality of relative employment and relative supply. The second term (in curly brackets} enforces the view that the observed and the simulated relative wages are equal in the base year to = 1991. For the years after 1991, equation (2) states the wage that equates changes in relative employment to changes in relative supply, which is why I refer to it as the 'market relative wage'. The difference between the observed relative wage and the simulated 'market relative wage', RWRt, is a quantitative indicator for relative wage compression and hence relative wage rigidity: (3) Definition (2) guarantees that RWRt is equal to zero in the base period to = 1991. Straightforward algebraic reformulation reveals that the relative wage rigidity indicator is simply a function of the observed relative employment-population ratios of high versus low-skilled labour plus the constant term in curly brackets (which sets RWRt equal to zero in t0 = 1991). 1 0 RWRt = (

8

9

10

In

m

-In

Sh

+

(4)

This adapts the framework in Katz/Murphy (1992), Autor et al. (1998), and Acemoglu, (2002), in order to simulate the extent of relative wage rigidity. Effectively, I propose that if the relative number of people with high skills increases by 10 percent in the population, the relative labour supply of high-skilled labour will also increase by 10 percent. In estimating relative employment and supply I use headcounts unadjusted by hours of work. This makes sense for my purpose because the simulation of relative wage rigidity in equation (4) below is based on a comparison of changes in relative employment and relative working age population head counts. As there is no working-hours information available for the supply proxy (the working population head count), it is consistent to use only headcounts for the relative employment estimates, too. The German IABR data only samples the labour force (non-workers and non-receivers of benefits are not included). Hence, for this data set I proxy relative supply changes by relative skill changes in the labour force instead of in the working age population. Using this alternative proxy in the other data sets, too, does not change the qualitative results of the analysis in this section. Equation (4) is derived by substituting equation (2) into equation (3), replacing the relative demand index by its implicit definition In(A^/A/,)" -1 = uln(W(„/W/,) + In(N(,,/N/,) from equation (1) and finally rearranging terms.

Relative D e m a n d and Supply of Skills and W a g e Rigidity • 5 7 9

If RWRt is negative, a country has experienced 'wage compression', meaning that its skill premium has grown less than necessary to employ numbers of high- versus low-skilled workers corresponding to their relative supply (working age population) changes. If the Krugman hypothesis holds for the early to mid 1990s, one would expect RWRt growing negatively in western Germany, but not in the Unites States or in Britain. Before the empirical results are presented, note that it is not trivial to form similar skill categories for all three countries investigated here. I define high-skilled workers in Britain and Germany as those with higher education, similar to US college education. However, the definition of the low-skilled groups is less straightforward. For example, the German apprenticeship system offers both classroom and on-the-job training for two to three years. It is unclear how one would relate a German apprenticeship training to an American high school degree. Here I define low-skilled workers in the United States as high school graduates (as common in the US literature), whereas I define the lowskilled as O-level graduates in Britain and apprenticeship certificate holders in Germany. These choices for Britain and Germany are motivated by the fact that O-level graduates and apprenticeship certificate holders are the major low-skilled groups with formal certification in these countries. 11 As in Autor et al. (1998) and Acemoglu (2003), I form age-education-gender-region cells from the micro data sets described in the previous section. The number of cells varies by data set as I adjust the regional classification depending on data set and country size. Hence I obtain the following number of cells: 360 (US-CPS), 150 (Britain-BLFS), 100 (Britain-BHPS), 50 (Germany - GSOEP), 150 (Germany - GLFS), and 150 (Germany - IABR). To obtain a wage series for a certain skill group, I take the weighted average of the median wages in each cell with that skill, where the weights are taken to be the average working age population share of a cell in the observation period (calculations based on cell mean wages make no difference to the results presented in this section). In order to aggregate all cells into labour supply equivalents of high- and low-skilled workers, I follow and adapt the approach by Autor et al. (1998) and Acemoglu (2003): for the US, cells with some college education are allocated equally to the high-skilled (college graduates) and low-skilled (high school graduates) group. High school dropouts are counted as entailing half the human capital of high school graduates. For Britain, persons with higher (no degree) education are counted as 0.6 times degree holders, whereas those with high school (A-level) are supposed to entail 0.2 times the human capital of degree holders. Analogously, these two education groups are assigned to O-level certificate holders with factors 0.4 and 0.8, respectively. Persons with education below O-levels are assumed to provide 0.5 times the human capital of O-level certificate holders to the market. The German high- and low-skilled equivalent supplies are calculated using human capital imputations corresponding to those used for Britain for the higher no degree in the GLFS, Meister in the GLFS, or high school and apprenticeship in the IABR, and high school (Abitur) educational levels. Similarly, persons with below

11

Unlike in the US, pupils with vocational interests in Britain and Germany are not expected to obtain a high school degree to accomplish 'proper' schooling. However, it should be noted that workers with only a British O-level certificate are likely to be fewer skilled on average than American high school graduates or German apprenticeship certificate holders. The reason is that they have less years of schooling than American high school graduates, but no German-style vocational education, either. German apprenticeship certificate holders, on the other hand, have some vocational education and work experience, which American high school graduates do not obtain.

580 • P.A. Puhani

apprenticeship certificate education are counted as 0.5 times apprenticeship equivalents. Although the choices of the human capital equivalent factors imposed, they are, in the British and German cases, a plausible adaptation of used in the cited US literature. While one might argue about the one or other changes within a plausible range do not make a qualitative difference to the results of this section. 1 2

certificate are simply the factors factor, any simulation

Table 1 presents the relative wages, relative supplies, and the relative demand indices of high- versus low-skilled workers during the course of the 1990s. Note that the levels of the displayed series are not easy to compare due to the different educational systems across countries. For example, the fact that Britain (in the BLFS data) has the highest skill premium is likely to be a mere reflection of the fact that the low skilled in Britain (defined as O-level) have less formal education than the low skilled in the US (high school) or Germany (apprenticeship). Despite the difficulty in comparing the levels of the reported series across countries, the changes in the series reveal some interesting facts. The interesting period is 1991 to 1997, when unemployment rates diverged between Germany on the one hand and the US and the UK on the other. The upper panel of Table 1 shows an increasing skill premium in the US and Britain between 1991(1993) and 1997(1999) (0.03 and 0.04 log points in the CPS and BLFS data, respectively), whereas there has been a decrease in western Germany (by between 0.02 and 0.06 log points). These different relative wage developments across countries are consistent with the Krugman hypothesis and qualitatively robust across alternative data sets used for western Germany and Britain. A second fact consistent with the hypothesis is the increase in the relative demand for skills in all three economies as displayed in the lower panel of Table l . 1 3 Although there are differences in the quantitative changes in the relative demand for skills across countries, there are also marked differences in the quantitative (but not in the qualitative) relative supply changes, where Britain sticks out as the country with the largest relative supply and demand increases. One may adopt Acemoglu's (2002) interpretation that the differences in relative demand changes stem from different types of technology adoption across countries, but the lack of comparability of skills across countries also suggests a 'measurement interpretation' of these differential demand changes: As argued above, the low-skilled group in Britain is likely to entail less human capital than the low-skilled groups in the US or Germany. Hence, it is quite likely to measure a larger relative demand change for Britain than for the other countries, even if technology changed in the same way. The simulated relative wage rigidity indicator RWRt, as defined in equation (4) above, is exhibited in Table 2 and Figure 2. This is the central result of the paper. The key question for the validity of the Krugman hypothesis is whether the observed skill premium deviated from the simulated 'market skill premium' in western Germany, but not in the US or Britain in the 1990s. This is equivalent to RWRt growing negative in western Germany, but not in the Anglo-Saxon economies. As can be seen from Table 2 and Figure 2,

12

13

The reason is that I am comparing the highest skill group with the major low-skill group. This is why the allocation of the other skill groups does not carry major weight However, the increases in the relative supply of skills in all German data sets plus those in the BHPS are larger (or equal: IABR) than the relative demand index increases. This contrasts with the CPS and BLFS results, where the opposite is true. Hence, it seems from these simulations that a fall in the skill premium would have been justified by market forces in western Germany. However, it will be revealed below that the actual fall in the skill premium was larger than justified.

Relative Demand and Supply of Skills and W a g e Rigidity • 581

T a b l e 1 Relative Wages, Supply and Demand Year

USA: CPS-MORG

Britain: BLFS

Log Relative Wages ln(W h /W,) 0.56 1991 0.58 1992 0.59 1993 1994 0.60 0.60 1995 1996 0.59 0.60 1997 0.60 1998 1999 0.61 0.03 1991(3)1997(9) Log Relative Supply ln(Sh/S|) 1991 -0.51 -0.50 1992 1993 - 0.47 1994 - 0.43 - 0.41 1995 1996 - 0.39 1997 - 0.38 1998 - 0.35 - 0.32 1999 1991(3)0.13 1997(9)

Britain: BHPS

Western Germany: GSOEP 0.46 0.48 0.50 0.47 0.42 0.40 0.40 0.36 0.39 -0.06

0.61 0.61 0.61 0.64 0.64 0.66 0.65 0.04

0.59 0.56 0.59 0.52 0.57 0.60 0.60 0.53 0.55 0.01

1.02 1.01 0.98 0.97 0.96 0.91 0.86 0.17

- 1.29 - 1.22 - 1.18 - 1.13 - 1.08 - 1.05 - 1.02 -0.97 -0.94 0.27

-

- 0.29 -0.28 -0.18 -0.24 - 0.12 - 0.07 -0.04 -0.10 -0.05 0.25

-0.87 -0.78 -0.71 -0.69 -0.74 -0.79 -0.76 -0.80 -0.69 0.11

Log Relative Demand Index ln{Ah/Aff 1991 0.46 0.50 1992 0.54 1993 0.01 1994 0.58 0.00 1995 0.61 0.03 1996 0.61 0.09 1997 0.62 0.10 0.64 0.17 1998 0.68 0.20 1999 1991(3)0.75 0.21 1997(9)

1.65 1.62 1.59 1.56 1.51 1.51 1.52 1.49 1.44 0.13

Western Germany: GLFS

Western Germany: IABR

0.54 0.55 0.55 0.54 0.53 0.50 0.49

0.63 0.62 0.63 0.62 0.65 0.59 0.61

-0.06

-0.02

-

1.48 1.45 1.42 1.39 1.35 1.32 1.28

-2.42 -2.39 -2.35 -2.31 -2.27 - 2.30 -2.28

0.20

0.15

1

-0.53 - 0.49 - 0.45 -0.43 -0.41 -0.41 -0.38

0.15

-

1.52 1.48 1.41 1.39 1.31 1.42 1.37

0.15

Note: These simulations assume a = 1.4. Sources: Current Population Survey - Merged Outgoing Rotation Group Files (CPS-MORG); British Labour Force Survey (BLFS); British Household Panel Survey (BHPS); German Socio-Economic Panel (GSOEP); German Labour Force Survey - Mikrozensus (GLFS); German Adminsitrative Data - Institut für Arbeitsmarkt- und Berufsforschung Regionalstichprobe (IABR); own calculations.

5 8 2 • P.A. Puhani

Table 2 Simulated Relative Wage Rigidity (RWR) Year

USA: CPS-MORG

Britain: BLFS

Britain: BHPS

Western Germany: GSOEP

Western Germany: GLFS

Western Germany: IABR

0.00 0.01 0.00 0.01 0.01 0.02* 0.02* 0.02* 0.03* 0.02*

0.00 -0.02 - 0.03* - 0.04* -0.03 -0.02 - 0.05* -0.03 - 0.04* -0.05*

0.00 0.00 -0.01* -0.01* -0.01* - 0.02* - 0.03*

0.00 0.00 -0.02 - 0.02 - 0.02 - 0.02 - 0.02

-0.03*

- 0.02

Log Relative Wage Rigidity, RWR 1991 1992 1993 1994 1995 1996 1997 1998 1999

1991(3)1997(9)

0.00 - 0.01 * -0.01* 0.00 0.00 0.01* 0.01* 0.02* 0.02*

0.01*

0.00 0.00 0.00 0.01* 0.01* 0.01* 0.01*

0.01*

Note: Negative numbers indicate relative wage rigidity (wage compression of high-skilled versus low-skilled wages); these simulations assume a = 1.4. Significance at the 10 percent level is indicated by an asterisk and based on bootstrap 90 percent confidence intervals for the estimated relative wage rigidity. The confidence intervals are based on 500 bootstrap replications. Sources: CPS-MORG; BLFS; BHPS; GSOEP; GLFS; IABR; see also Table 1; own calculations.

•—USA: CPS-MORG •— Britain: BLFS k - B r i t a i n : BHPS •— Western Germany: GSOEP Western Germany: GLFS •— Western Germany: IABR

Figure 2 Simulated Relative Wage Rigidity (RWR)

Note: A negative number indicates relative wage rigidity (relative wage compression of high versus low-skilled wages). Source: see Table 1.

Relative Demand and Supply of Skills and W a g e Rigidity • 583

this is indeed the case: in all three German data sets, RWRt turns negative. The size of the simulated increase in the relative wage rigidity depends on the data set and varies between 0.02 (IABR) and 0.05 (GSOEP) log points for the period 1991 to 1997. By contrast, the two Anglo-Saxon economies have experienced wage decompression (of the order of 0.01 (CPS, United States; BLFS, Britain) and 0.02 (BHPS, Britain) log points), i.e. the relative wages of high- versus low-skilled workers increased by more than necessary to accommodate relative demand and supply shocks. Bootstrapped confidence intervals suggest that all these simulated relative wage rigidity indicator changes between 1991(3) and 1997(9) are significant at least at the 10 percent level {cf. Table 2). 14 As can be seen from equation (4), alternative values for the elasticity of substitution, e.g. a = 2, would simply alter the simulation results for the relative wage rigidity indicator RWRt by a fixed factor, e.g. by 1.4/2 for a = 2 instead of a = 1.4. The conclusions regarding wage compression in western Germany on the one hand and decompression in the Anglo-Saxon economies on the other are therefore robust to the choice of a within a commonly accepted range {cf. footnotes 5 and 6). 3

Conclusions

Taken together, the simple macro simulations presented in this section provide evidence consistent with the Krugman hypothesis. This evidence is qualitatively robust across the used data sets. All three countries have experienced an increase in the relative demand for skilled versus unskilled workers. However, only western Germany exhibits 'wage compression', defined as a lower rise in the skill premium than is required to accommodate changes in relative skill demands and supplies. A quantitative interpretation of the macro simulation results suggests a required skill premium that exceeds the observed values by between 2 to 5 percent in order to equilibrate the relative supply and demand changes that occurred in western Germany between 1991 and 1997 (this finding is roughly of the order of Fitzenberger's 1999, and Fitzenberger/Franz's 2000, estimates for Germany, if one takes into account that these authors ask a different question). Roughly speaking, this means that the observed compression of the German skill premium by about 2 to 6 percent was not warranted by market forces, but a stable (or only slightly falling) skill premium would have been. Although the evidence presented in this section gives an insight into the labour market developments in the US, Britain, and western Germany in the 1990s, the applied methodology makes a lot of assumptions. Furthermore, only two skill groups (high and low) are distinguished. However, as I show in Puhani (2008), a microeconometric test distinguishing more educational categories and relying on less modeling structure also supports the view of an insufficiently flexible German wage structure in the 1990s. As shown in Dustmann et al. (2007), the decline in trade union power accelerated in Germany in the late 1990s, a development that was contemporaneous with rising returns to higher versus apprenticeship education as well as declining unemployment rates.

14

I bootstrap the whole simulation procedure: blocked (in case of panel data) bootstrap samples are drawn from the micro data and then the whole aggregation and simulation process is carried out for each of the 5 0 0 replications. I use the 90 percent confidence intervals from this bootstrap to assess significance at the 10 percent level. Alternatively, analytic asymptotic standard errors could be obtained using the delta method.

584 • P.A. Puhani

H e n c e , a l t h o u g h overall w a g e inequality seems t o have increased in West G e r m a n y alm o s t c o n t i n u o u s l y since 1 9 7 5 as s h o w n in D u s t m a n n et al. (2007), I d e m o n s t r a t e t h a t this situation is n o t inconsistent w i t h rigidities in t h e r e t u r n s t o skill t h a t prevent relative e m p l o y m e n t f r o m a d j u s t i n g t o relative skill changes in the w o r k i n g age p o p u l a t i o n .

References Acemoglu, D. (2002), Technical Change, Inequality, and the Labor Market. Journal of Economic Literature 40: 7-72. Acemoglu, D. (2003), Cross-Country Inequality Trends, Economic Journal 113: F121-F149. Angrist, J.D. (1995), The Economic Returns to Schooling in the West Bank and Gaza Strip. American Economic Review 85: 1065-1087. Autor, D.H., L.F. Katz, A.B. Krueger (1998), Computing Inequality: Have Computers Changed the Labor Market? Quarterly Journal of Economics 113: 1169-1213. Bewley, T. (1999), Why Wages Don't Fall During a Recession. Cambridge, MA: Harvard University Press. Card, D., T. Lemieux (2001), Can Falling Supply Explain the Rising Return to College for Younger Men? Quarterly Journal of Economics 116: 705-746. Cornelißen, Th., O. Hübler (2008), Downward Wage Rigidity and Job Mobility. Empirical Economics 34: 205-230. Dustmann, C., J. Ludsteck, U. Schönberg (2007), Revisiting the German Wage Structure. IZA Discussion Paper No. 2685, Bonn, forthcoming in: Quarterly Journal of Economics. Falk, A., E. Fehr (1999), Wage Rigidities in a Competitive Incomplete Contract Market. Journal of Political Economy 107: 106-134. Fitzenberger, B. (1999), Wages and Employment Across Skill Groups, An Analysis for West Germany. Heidelberg: Physica/Springer. Fitzenberger, B., K. Kohn (2006), Skill Wage Premia, Employment, and Cohort Effects: Are Workers in Germany All of the Same Type? ZEW Discussion Paper N o . 06-044, Mannheim. Fitzenberger, B., G. Wunderlich (2002), Gender Wage Differences in West Germany: A Cohort Analysis. German Economic Review 3: 379-414. Fitzenberger, B., W. Franz (2000), Jobs. Jobs? Jobs! Orientierungshilfen für den Weg zu mehr Beschäftigung [Jobs. Jobs? Jobs! Orientation Assistance for the Way to Higher Employment]. ZEW Discussion Paper No. 00-49, Mannheim. Franz, W., K. Gerlach, O. Hübler (2003), Löhne und Beschäftigung: Was wissen wir mehr als vor 25 Jahren? Mitteilungen aus der Arbeitsmarkt- und Berufsforschung 36: 399-410. Freeman, R. (1986), Demand for Education. Pp. 357-386 in: O.C. Ashenfelter, R. Layard (eds.), Handbook of Labor Economics. Handbooks in Economics, Vol. 1, Amsterdam: North-Holland. Gerlach, K., G. Stephan (2006), Bargaining Regimes and Wage Dispersion. Jahrbücher für Nationalökonomie und Statistik 226: 629-645. Gottschalk, P., T.M. Smeeding (1997), Cross-National Comparisons of Earnings and Income Inequality. Journal of Economic Literature 35: 633-687. Heckman, J.J., L. Lochner, C. Taber (1998), Explaining Rising Wage Inequality: Explorations with a Dynamic General Equilibrium Model of Labor Earnings with Heterogeneous Agents. Review of Economic Dynamics 1: 1 - 5 8 (also NBER Working Paper No. 6384, Cambridge, MA). Hübler, O. (1983), Lohn- und Beschäftigungsstrukturbewegungen unter Unsicherheit. Konjunkturpolitik 29: 67-88. Hübler, O., U. Jirjahn (2003), Works Councils and Collective Bargaining in Germany: The Impact on Productivity and Wages. Scottish Journal of Political Economy 50: 471-491. Hübler, O., W. Meyer (2001), Industrial Relations and the Wage Differentials within Firms. Schmollers Jahrbuch 121: 285-312. Katz, L., K. Murphy (1992), Changes in Relative Wages 1963-1987: Supply and Demand Factors. Quarterly Journal of Economics 107: 35-78.

Relative Demand and Supply of Skills and Wage Rigidity • 585

Katz, L.F., D.H. Autor (1999), Changes in Wage Structure and Earnings Inequality. Pp. 1 4 6 3 1555 in: O.C. Ashenfelter, D. Card (eds.), H a n d b o o k of Labor Economics. H a n d b o o k s in Economics Vol. 3A. Amsterdam: Elsevier. Kohn, K. (2006), Rising Wage Dispersion, After All! T h e German Wage Structure at the Turn of the Century. IZA Discussion Paper N o . 2098, Bonn. Krugman, P. (1994), Past and Prospective Causes of High Unemployment. Economic Review, Federal Reserve Bank of Kansas City, 23—43. M a n a c o r d a , M . , B. Petrongolo (1999), Skill Mismatch and Unemployment in O E C D Countries. Economica 66: 1 8 1 - 2 0 7 . Puhani, P.A. (2005), Relative Supply and Demand for Skills in Switzerland. Schweizerische Zeitschrift für Volkswirtschafts und Statistik 141: 5 5 5 - 5 8 4 . Puhani, P.A. (2008), Transatlantic Differences in Labour Markets: Changes in Wage and N o n Employment Structures in the 1980s and the 1990s. German Economic Review 9: 3 1 2 - 3 3 6 . Steiner, V., K. Wagner (1998), H a s Earnings Inequality in Germany Changed in the 1980s? Zeitschrift für Wirtschafts- und Sozialwissenschaften 118: 2 9 - 5 9 . Patrick A. Puhani, Leibniz Universität Hannover, Institut für Arbeitsökonomik, Königsworther Platz 1, 3 0 1 6 7 Hannover, Germany. Phone: + 4 9 ( 0 ) 5 1 1 762 5620. E-Mail: [email protected]

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

The Effects of Active Labor Market Programs in Germany: An Investigation Using Different Definitions of Non-Treatment By Gesine Stephan, Nuremberg* JEL J68, J 64, J65 Evaluation of active labor market policies, definition of non-treatment, comparison group concepts, propensity score matching.

Summary This paper estimates the effects of several German labor market programs - starting in March 2003 - on the employment outcomes of participants using propensity score matching. The main objective is to analyze how estimated average treatment effects vary with the choice of the classification window that defines treatment and non-treatment. The first approach does not put any restrictions on the future of the treated as well as of their comparison group. This approach has become more and more common in the evaluation of European labor market policies. In contrast, the second approach considers only potential comparison group members, who have not entered any labor market program during the entire observation period of 3Vi years. The third approach additionally restricts itself to participants, who have not participated in further labor market programs during the observation period. The results differ considerably; program effectiveness is estimated to be much lower using the second approach. The paper highlights the fact that program careers are a non-trivial issue that deserves more attention in future research.

1

Introduction

During 2 0 0 6 , the German Public Employment Service ("Bundesagentur fur Arbeit") and the German government spent 18.5 billion Euros on active and 46.8 billions on passive labor market policies (Bundesagentur fur Arbeit 2006). The question, whether the considerable funds devoted to active labor market policies have been used effectively gains more and more attention in Germany. Olaf Htibler - to whom this volume is dedicated has contributed to the early literature, in particular for East Germany (Hiibler 1997, 1998). Large evaluation projects have analyzed the effectiveness of public job creation schemes (see for instance Caliendo et al. 2 0 0 6 b , 2 0 0 8 a , 2008b) and further vocational

* I am grateful to the T r E f f e R team of the German Public Employment Service - in particular Michael Irskens, Susanne Rässler and Torben Schewe - and to Sarah Bernhard, T h o m a s Büttner, Knut Gerlach, Reinhard Hujer and H a n s Kiesl for support and helpful hints. While the TrEffeR data set is not available for public use, it is composed of the same data flows as the Integrated Employment Biographies (IEB) of the Institute for Employment Research. Hummel et al. (2005) describe an IEB sample that is open for public use through the Research D a t a Center of the Federal Employment Agency.

The Effects of Active Labor Market Programs in Germany • 587

training p r o g r a m s (see for instance Fitzenberger et al. 2 0 0 6 , Fitzenberger/Vólter 2 0 0 7 , Lechner et al. 2 0 0 5 , 2007a). A f u r t h e r step was reached with the comprehensive evaluation of the so called " H a r t z " r e f o r m s of G e r m a n labor m a r k e t policies; this huge evaluation project involved the m a j o r i t y of G e r m a n socio-economic research institutes and has been supervised by the Federal Ministry for Labor and Social Affairs (BMAS). Furthermore, the G e r m a n Public Employment Service started the TrEffeR-project (Treatment Effects and Prediction) to develop its o w n evaluation a n d monitoring tool (Stephan et al. 2006). This paper adds to this literature by analyzing empirically a particular aspect - the definition of non-participation arising in evaluation studies t h a t utilize non-experimental d a t a . For participants in five active labor m a r k e t p r o g r a m s , starting during M a r c h 2 0 0 3 , I apply statistical matching techniques to estimate p r o g r a m effects on cumulated days spent in regular employment during the 3VÍ years after p r o g r a m entry. I c o m p a r e the results for a very n a r r o w and a very wide "classification w i n d o w " defining non-treatment. In the former case all persons are categorized as non-treated w h o did not enter a p r o g r a m during M a r c h 2 0 0 3 , while they m a y be " w a i t i n g " to participate at a later date. In the latter case the n o n - t r e a t m e n t g r o u p consists of persons w h o have never been in any prog r a m during the entire observation period of 3 V2 years. Additional estimates also include only participants, w h o did not join any f u r t h e r labor m a r k e t p r o g r a m during the observation period. This is n o minor issue, since typically a r o u n d 4 0 t o 5 0 percent of comparison g r o u p members a n d a r o u n d 50 t o 70 percent of those taking-up a p r o g r a m in M a r c h 2 0 0 3 also participated in at least one (further) p r o g r a m starting after M a r c h 2 0 0 3 . A similar analysis has been conducted by Steiger (2004) for Switzerland, w h o did, however, not distinguish between different labor m a r k e t programs. H e r main result was t h a t participation is m u c h more effective c o m p a r e d to " w a i t i n g " t h a n c o m p a r e d t o "never in any p r o g r a m " . A recent example for the possible importance of the topic is provided by three studies of G e r m a n f u r t h e r vocational training p r o g r a m s , covering p r o g r a m entries f r o m 2 0 0 0 to 2 0 0 2 : Wunsch and Lechner (2008) estimated that further vocational training - and other p r o g r a m s - had generally negative or insignificant effects on employment probabilities of participants and their cumulated days spent in regular employment 30 m o n t h s after prog r a m start. Small positive effects were f o u n d for few subgroups of participants only. This w a s taken up by a G e r m a n newspaper claiming t h a t active labor m a r k e t policy in Germ a n y wastes billions of Euros (Frankfurter Allgemeine Zeitung, August 28, 2007). Biewen et al. (2007) point out that - also 30 m o n t h s after p r o g r a m start - they f o u n d positive effects of f u r t h e r vocational training with short or medium duration on the employm e n t prospects of certain subgroups in West Germany. Rinne et al (2007), w h o investigated entries in f u r t h e r vocational training p r o g r a m s of m e d i u m duration during 2 0 0 2 , obtained - t w o years after p r o g r a m start - even positive effects on employment probabilities for all subgroups investigated. O n e of the underlying reasons might be that Wunsch and Lechner (2008) "define participants as unemployed w h o participate at least once in a p r o g r a m in the 18 m o n t h s following the inflow date into our sample. Accordingly, non-participants are all persons w h o d o not enter a p r o g r a m during this p e r i o d . " (p. 143). T h u s " n o n - t r e a t m e n t " requires t h a t n o t r e a t m e n t has occurred up t o a period of 18 m o n t h s after entry into unemployment. Biewen et al. (2007) p e r f o r m separate estimates by duration of unemploym e n t at the beginning of a treatment (up t o three m o n t h s , f o u r to six m o n t h s , seven to

588 • G. Stephan

twelve m o n t h s of unemployment) and require only t h a t non-participants have not entered a measure during an accordingly chosen classification w i n d o w of three or six m o n t h s . Rinne et al. (2007) stratify estimates by d u r a t i o n of u n e m p l o y m e n t in m o n t h s and require that non-participants had not t a k e n - u p the same type of training p r o g r a m before a n d during the quarter of the participant's p r o g r a m entry (p. 10). Sensitivity analysis conducted by these a u t h o r s (Section 4.4 of their paper) showed also that estimated p r o g r a m effects decreased considerably if they use a similar definition of n o n - t r e a t m e n t t h a n Wunsch a n d Lechner (2008) did. T h e following Section 2 briefly describes G e r m a n active labor m a r k e t policies and recent evaluation results. Section 3 discusses the evaluation problem investigated. Section 4 introduces data, variables a n d the particular m e t h o d and evaluation design used. The empirical results are presented in Section 5, while Section 6 lists the conclusions. 2

Active labor market policies in Germany and recent evaluation results

T h e " H a r t z " reforms, enacted in 2 0 0 2 , caused a f u n d a m e n t a l revision of active and passive labor m a r k e t policies in Germany: Since 2 0 0 3 the design of several active measures w a s modified a n d a n u m b e r of new instruments were introduced. Regarding passive labor m a r k e t policies, since 2 0 0 5 former u n e m p l o y m e n t assistance for long-term unemployed persons and f o r m e r social assistance has been merged into a new variant of basic social care for needy employable persons. This section gives a short overview of the main instruments of active labor m a r k e t policies in Germany. Furthermore, results f r o m selected recent evaluation studies on the effectiveness of active labor m a r k e t policies in G e r m a n y will be sketched. M o s t of these studies are based on statistical matching techniques, while a few apply d u r a t i o n analysis. Statistical matching techniques c o m p a r e a g r o u p of treated individuals with a selected g r o u p of similar, but untreated comparison persons; the estimated p r o g r a m effect is then simply given by the difference in o u t c o m e variables - mostly employment rates - between the t w o groups (see Section 3 for more details). D u r a t i o n analysis parametrically estimates the effect of treatment on the " r i s k " of entering employment or leaving unemployment. The increasingly p o p u l a r timing-of-events model (Abbring/van den Berg 2 0 0 3 , 2004) additionally takes into account the risk of entering a p r o g r a m during an unemployment spell. Table 1 shows entries a n d populations in selected p r o g r a m s of active labor m a r k e t policies administered by the G e r m a n Public Employment Service for the period 2 0 0 0 t o 2 0 0 6 . T h e empirical results presented in section 5 in this paper restrict themselves to short p r o g r a m s u p to six m o n t h s duration a n d include variants of further vocational training, short-term training measures, w a g e subsidies a n d public job creation schemes. For a long time so called " f u r t h e r " vocational training ("Forderung beruflicher Weiterbildung") belonged to the most i m p o r t a n t p r o g r a m s in Germany. It encompasses a range of different treatments, which can be broadly classified in qualification p r o g r a m s , training within "practice firms" (that offer practical occupational training w i t h o u t trainees actually w o r k i n g in a real c o m p a n y ) and long retraining programs. However, during the first half of this decade entries as well as the duration of these measures were shrinking, whereas the n u m b e r of entries increased again in 2 0 0 6 . T h e effectiveness of these programs has been analyzed in a considerable n u m b e r of studies applying statistical matching techniques. Lechner et al. (2005, 2007a) investigated p r o g r a m entries during the years 1993 and 1994, their observation period covers a b o u t seven years after p r o g r a m

The Effects of Active Labor Market Programs in Germany • 589

Table 1 Entries and average stock of participants in selected labor market programs (in 1000) 2000 2001 2002 2003 2004 2005 200< Entries Further vocational training ("Förderung beruflicher Weiterbildung") Short-term training ("Trainingsmaßnahmen") Wage subsidy ("Eingliederungszuschüsse") Start-up subsidy 1 ("Überbrückungsgeld") Start-up subsidy II ("Existenzgründungszuschuss") Public job creation 1 ("Arbeitsbeschaffungsmaßnahmen, SAM") Public job creation II ("Arbeitsgelegenheiten") Contracting-out to private placement agencies ("Beauftragung Dritter")* Temporary help-firms ("Personal-ServiceAgenturen")

523

442

455

485 152 93

551 127 96

865 188 125

-

318

-

246

-

215

185 132

247

1064 1188 894 183 157 134 159 183 157 95 168 91

978 217 108 43

255

179

-

-

-

-

-

-

-

-

-

-

-

45

Average stock of participants Further vocational training ("Förderung 343 beruflicher Weiterbildung") Short-term training ("Trainingsmaßnahmen") 52 Wage subsidy ("Eingliederungszuschüsse") 105 Start-up subsidy 1 ("Überbrückungsgeld") 43 Start-up subsidy II ("Existenzgründungszuschuss") Public job creation 1 ("Arbeitsbeschaffungs266 maßnahmen, SAM") Public job creation II ("Arbeitsgelegenheiten") Contracting-out to private placement agencies ("Beauftragung Dritter")* Temporary help-firms ("Personal-ServiceAgenturen")

161

80

80

630 635 426

742 301

56

27

16

352

340

260

184 114

119

60 118 46

74 136 56

93 153 73 40

95 69 110 60 84 83 151 234

70 82 63 210

144

117

-

237

-

193

-

-

-

-

-

-

-

-

10

61

50

201 95 103

293 100

-

25

13

6

Source: Statistics of the German Public Employment Service (Date-Warehouse). * Figures are available since 2004, while different variants started already in 1998 (contracting-out of subtasks) respectively 2002 (contracting-out of entire placement).

start. Fitzenberger et al. (2006) analyze program entries inflows in unemployment during the years 1986/87 and 1993/94 in West Germany, while Fitzenberger and Volter (2007) focus on unemployment entries during 1993/94 in East Germany. Generally, these studies obtained the result that - in the longer run - further vocational training programs had mostly significant positive effects on the employment prospects of participants. However, since program effects are rather weak, it may take some years until the estimated program effect turns positive. More recent program entries have been investigated by Biewen et al. (2007), Rinne et al. (2007) as well as Wunsch and Lechner (2008), who analyzed programs starting in the years 2000 to 2002. As has already been mentioned in the introduction, the estimates of Wunsch and Lechner indicated no positive effects of further vocational training on employment prospects of participants in West Germany. In contrast, Biewen et al. found positive effects for programs of short and medium duration in West Germany (but not in East Germany) and particular groups of unemployed. Also Rinne et al. (2007) estimated positive effects of participation in medium length programs

590 • G. Stephan

on the employment probabilities of participants in all subgroups investigated. H u j e r et al. (2006b) applied d u r a t i o n analysis to East G e r m a n data f r o m the years 1999 to 2 0 0 2 their result w a s that participation in f u r t h e r vocational training prolonged unemployment d u r a t i o n . Short-term training p r o g r a m s ( " T r a i n i n g s m a ß n a h m e n " ) , whose duration does in most cases not exceed t w o m o n t h s , have been increasing in n u m b e r in particular during 2 0 0 3 a n d 2 0 0 4 . These short-term measures are utilized to train qualifications and abilities (firm-internal and firm-external), to test the availability of unemployed persons, t o check whether unemployed are suited for f u r t h e r longer-term measures a n d t o provide job search assistance t h r o u g h application training. These short-term measures have been analyzed also in the already cited studies of Biewen et al. (2007) and Wunsch and Lechner (2008). Similar t o further vocational training, Biewen et al. obtained mostly positive, while Wunsch and Lechner f o u n d insignificant effects of short training-programs. H u j e r et al. (2006a) showed - using duration analysis - t h a t the risk of entering e m p l o y m e n t is significantly higher for individuals participating in a short-training p r o g r a m . These studies, however, d o not t a k e into account the substantial heterogeneity of this class of programs. Wolff a n d J o z w i a k (2007) distinguished between short classroom training and short training within firms for individuals; they investigated the effect o n the employm e n t prospects of unemployed receiving means-tested u n e m p l o y m e n t benefits ("Arbeitslosengeld II"). They obtained the result t h a t both variants have positive effects, which are m u c h larger for short training within firms. These are, however, also m u c h more prone to deadweight losses. Büttner (2007) used data f r o m a social experiment on short-training p r o g r a m s t o test the availability of the unemployed. H e showed that it is the notification of t r e a t m e n t rather t h a n participation that had an effect on leaving unemployment. A n u m b e r of p r o g r a m s foster a direct integration of the unemployed in the first labor market. Of particular importance are a variant of targeted wage subsidies ("Eingliederungszuschüsse"), paid to employers for a fixed period of time. They gained i m p o r t a n c e first in East G e r m a n y following the reunification a n d thereafter again in the late nineties, but lost i m p o r t a n c e until 2 0 0 5 , like f u r t h e r vocational training schemes. From 1998 to 2 0 0 3 three variants were in place: O n e w a s characterized by a rather low level of targeting, while one was aimed at hard-to-place unemployed with severe problems of reintegration and one at workers of age 50 a n d older. T h e " H a r t z " reforms collapsed these into a single wage subsidy for hard-to-place workers, with a looser definition of target groups and less generous financial support. Jaenichen and Stephan (2007) estimated average treatment effects of a subsidy on previously unemployed hard-to-place individuals. In line with the international literature o n wage subsidies, they showed that subsidies have a favorable effect on the employment prospects of participants. B o o c k m a n n et al. (2007) utilized a " n a t u r a l e x p e r i m e n t " : They c o m p u t e d the effect of changes in the legislation on wage subsidies for older workers on the e m p l o y m e n t prospects of this group, using a difference-in-differences estimator to c o m p a r e changes in transition probabilities between the affected g r o u p and a c o m p a r i s o n g r o u p comprised of slightly younger workers. The a u t h o r s f o u n d nearly n o significant effects and concluded that deadweight effects - those subsidized w o u l d have been hired a n y w a y - are a m a j o r p r o b lem of wage subsidies. T w o p r o g r a m s offering financial support for unemployed persons founding their own businesses grew in n u m b e r s until 2 0 0 6 . A first variant ("Überbrückungsgeld") encouraged unemployed persons t o start-up a n e w business by proceeding to pay unemploy-

The Effects of Active Labor Market Programs in Germany • 591

ment benefits as well as a subsidy t o social security contributions for six m o n t h s . T h e " H a r t z " reforms in 2 0 0 3 additionally introduced a second variant of a start-up subsidy ("Existenzgriindungszuschuss"), which provided a fixed, but time-decreasing a m o u n t for u p t o three years a n d w a s attractive for unemployed persons w h o received c o m p a r a tively few u n e m p l o y m e n t benefits. In August 2 0 0 6 both p r o g r a m s were collapsed in a new variant of a start-up subsidy ("Griindungszuschuss"). Baumgartner and Caliendo (2007) analyzed the effect of both previous variants on unemployed persons, w h o f o u n d e d a subsidized business in 2 0 0 3 . Their results showed t h a t u n e m p l o y m e n t rates were lower 28 m o n t h s after p r o g r a m start a n d rates of regular employment or self-employment were significantly higher across those subsidized t h a n in an unsubsidized comparison group. Previously very i m p o r t a n t p r o g r a m s for job creation in the public sector ("ArbeitsbeschaffungsmalSnahmen u n d StrukturanpassungsmalSnahmen") nearly disappeared since 2 0 0 5 . However, since then a new variant of public job creation for long-term unemployed ("Arbeitsgelegenheiten") is the most i m p o r t a n t p r o g r a m for unemployed persons receiving social basic care. T h e latter provide mostly only a modest additional reimbursement for w o r k ("Ein-Euro-Jobs"). Caliendo et al. (2006b, 2 0 0 8 a , 2008b) as well as H u j e r a n d T h o m s e n (2006c) investigated entries into public job creation schemes in 2 0 0 0 , using the matching m e t h o d . They estimated heterogeneous effects on participants, which are in the longer-run mostly negative or insignificant. Exceptions are longterm unemployed, highly qualified men and older w o m e n in West Germany. H u j e r and Zeiss (2006d) evaluated these p r o g r a m s in East Germany schemes also with the timingof-events m e t h o d . Their main conclusion is that participation in these schemes increased individual u n e m p l o y m e n t d u r a t i o n of participants. Recent results on the new " O n e Euro-Jobs" (Hohmeyer/Wolff 2007), introduced in 2 0 0 5 , highlighted the effect heterogeneity of this p r o g r a m . T h e authors f o u n d slightly positive effects in particular for participants f r o m West G e r m a n y and individuals out of regular employment for a longer time period. Contracting-out t o private placement services gained importance during the last years in Germany. O n the one h a n d unemployed persons m a y be assigned to private agencies that compete on a quasi-market ("Beauftragung privater Dritter"). O n the other hand unemployed persons m a y ask for a voucher that entitles t h e m to use the services of a private placement agency. Also t e m p o r a r y help firms m a y employ previous unemployed persons, while receiving financial reimbursement by the Public E m p l o y m e n t Service ("PersonalService-Agenturen"). Using statistical matching methods, Winterhager (2008) showed t h a t most subgroups of unemployed persons contracted out to private placement agencies in 2 0 0 4 did not experience a n increase in employment prospects during a period of nine m o n t h s after treatment start. For unemployed persons receiving basic social care and contracted-out at the beginning of 2 0 0 5 , Bernhard and Wolff (2008) obtained evidence of slightly positive effects of contracting-out on the employment prospects t w o years later. Winterhager et al. (2006) f o u n d positive treatment effects on the employment probability of individuals w h o received a job voucher during M a y and J u n e 2 0 0 3 ; Hess et al. (2006) identified n o positive effects of e m p l o y m e n t in a t e m p o r a r y help firm on the latter likelihood of being in a regular job. A n u m b e r of studies (for instance Lechner et al. 2 0 0 5 , 2 0 0 7 a , JaenichenyStephan 2007) showed that estimated treatment effects of labor m a r k e t p r o g r a m s are more positive for the o u t c o m e variable "regular e m p l o y m e n t " t h a n for the o u t c o m e variable " n o t unemp l o y e d " . Both o u t c o m e variables m a y differ since not every person avoiding unemploy-

592 • C. Stephan

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J

(G'H'ZA 'Z HG)

1

(3.35)

as shown by Mutl (2005). By applying the GMM estimator, one has to face several problems. First the estimator for the variance of the parameter vector is severely downward biased in finite sample if a two-step estimator is used. A procedure for correcting this finite sample bias is derived by Windmeijer (2005). Windmeijer (2005) proves that the additional variability of using a first step estimator in order to compute the weighting matrix has to be taken into account. As this study does not account for spatial effects, this would be an interesting research topic. Second, an iterated version of the GMM estimator could be used. As shown by Das et al. (2003) and Kelejian et al. (2004) by Monte Carlo studies considering cross sectional datasets, the iterated version rarely leads to a loss of efficiency, but can increase precision in certain cases. Kelejian et al. (2004) explicitly suggest to iterate the

Dynamic Panel Data Models with Spatial Correlation • 623

estimators, if their finding can be confirmed in the case of dynamic panel data models remains to be shown. Third, inversion of the weighting matrix A can create considerable numerical problems. For example Arellano and Bond (1998) use the Moore-Penrose pseudo-inverse in the case where the n u m b e r of the m o m e n t conditions is large relative to the n u m b e r of cross sections. A f u r t h e r problem in using G M M m e t h o d s for estimating dynamic panel data models are the large n u m b e r of instruments. Even t h o u g h it is desirable to use many m o m e n t conditions f r o m an asymptotic perspective, in finite samples the estimator is f o u n d t o p e r f o r m poorly w h e n using all available m o m e n t conditions. O k u i (2005b) discusses this p r o b l e m explicitly for dynamic panel data models. H e assumes strictly exogenous regressors, takes the m o m e n t conditions given by Arellano a n d Bond (1991) into account a n d leaves spatial issues out. H e proposes t w o m e t h o d s for choosing the relevant m o m e n t conditions: First, he derives the mean squared error as a f u n c t i o n of the used orthogonality conditions. The n u m b e r of m o m e n t conditions is t h a n chosen as a minimizer of t h a t function. A second procedure is based on O k u i (2005a), where the m o m e n t conditions are classified as m a i n and additional m o m e n t conditions. The m e a n squared error is than derived as a function of the weights given to the additional m o m e n t conditions. Again this function is minimized according to this weight. A generalization of this m e t h o d s for usage of a systems estimator, w e a k exogenous regressors and spatial m e t h o d s would be an interesting field for f u t u r e research.

4

Empirical application

T h e aim of the empirical application is t o analyze the effectiveness of various measures of active labour m a r e k t policy (ALMP) in G e r m a n y on the regional level. As C a l m f o r s (1994) notes, active labour m a r k e t policy affects not only participants but also non-participants due to indirect effects. At the regional level, unintended negative effects like displacement, deadweight a n d substitution effects should be taken into account. We use for the analysis the labour m a r k e t flows as the o u t c o m e variable and therefore the matching function as theoretical a p p r o a c h . 4.1 The augmented matching function

T h e possible existence of deadweight losses a n d substitution effects represent t w o m a j o r problems in the evaluation of A L M P on a micro level. D e a d w e i g h t losses are caused by people w h o participated in the p r o g r a m m e but w o u l d also have been hired w i t h o u t the labour m a r k e t p r o g r a m m e . Substitution effects arise if an employer just replaces a w o r k er or job-seeker w h o did not participate in a p r o g r a m m e with a person w h o did participate, so that n o new job creation takes place. Beside this negative substitution effect there is also the possibility of a positive one. As almost every microeconometric evaluation study of A L M P shows, participants reduce during the p r o g r a m m e participation their search intensity - this is k n o w n as lock-in effect. However, if this increases the chances for non-participants of finding a job, the n u m b e r of outflows during a m o n t h are not affected in spite of the lock-in effect at the individual level. In order t o t a k e these problems into account, one has t o focus on aggregated outcomes in addition t o the analysis at the individual level. We measure the success of A L M P by using the variation in the participation in these p r o g r a m m e s across regions over time. We look whether this variation has an impact on the o u t f l o w s f r o m u n e m p l o y m e n t into regular (unsubsidised) employment in a region. T h e traditional econometric methodology assumes that the observations for different

624 • R. Hujer, P.J.M. Rodrigues, and K. Wolf

cross-sections are independent of each other. However, because we use regional data this assumption can hardly be justified. First, economic conditions affecting one region are very likely to affect neighbouring regions as well. Second, individuals that are searching for work, typically do not restrict their search to one labour office district; they extend their search to other districts, too. T h e same reasoning applies to employers that have a vacancy. Both examples clearly show that labour market conditions are correlated between regions. Thus, we conclude that the assumption of independent observations across cross sections is invalid and specify and estimate econometric models with spatial dependencies, this means we estimate a matching function augmented by spatial effects and indicators of the labour market programme intensities. We follow the specification o f the matching function augmented by spatial effects derived in Burda and Profit ( 1 9 9 6 ) . In their model, job seekers take j o b offers in neighbouring regions into account when forming their decisions. Expected benefits and search costs are assumed to depend on the distance between the residential region and the region where the j o b offer takes place. T h e model assumes that changes in unemployment exit probabilities in region i depend on the changes of the labour market conditions in all neighbouring regions. Burda and Profit ( 1 9 9 6 ) and Burgess and Profit ( 2 0 0 1 ) model these spatial dependencies by including a spatial lag of the unemployed and the vacancies in the neighbouring regions into the matching function. Furthermore, we follow the specification used in Boeri and Burda ( 1 9 9 6 ) and include an indicator for the intensities of active labour market policies in the region into the equation. T h e augmented matching function is given by the following log-linear equation 1 5 In m i t = / ? ! + (Tiln m ^ . j ) +yS 2 ln w, (i _i) + / ? 3 l n o.-^d +yS 4 ln u i { t _ x ) + / ? s l n u* (( _ 1} S

(4-1) where tnu denotes the outflows from unemployment into unsubsidised employment in region i that take place between t — 1 and t. w,( t -i) and v ^ - i ) denote the number of j o b seekers (i.e. unemployed and participants of A L M P ) and vacancies at the end of t — 1, respectively. T h e terms lnwL j j and are the spatial lag of the unemployed and the w u vacancies, respectively. T h e spatial lags are given by = ij i(t-\) and w v vi*(f~i) = ij i(t-1)- We use two specifications for the weights wtj. In the first version, the weights are chosen to be unity if the region i shares a c o m m o n border with region / and zero otherwise (Binary). In a second version we set the weights according to a function based on the distance (D, ; ) between the centres of the regions, w,t = exp(—tjDij) {Distance). We set w,j = 0 if the distance between the regions exceeds 7 0 0 km, and, following the discussion in M o l h o ( 1 9 9 5 ) , we set rj = 0 . 0 2 . Furthermore, we do not consider any region to be a neighbour to itself, i.e. Wij = 0 if i = j. The term / ( L ) = y\L + fjL2 + . . . 4 - f Li is a polynomial in the lag operator. The term Ina $ i t contains the indicator for the intensity of the s-th active labour market programme. The terms /?s denote scalar unknown parameters and v,t the error term.

15

Since the elements for the b o u n d a r y regions m a y c h a n g e if n e w observations are added, the o b s e r v a tions are assumed t o f o r m triangular a r r a y s (see Anselin 2 0 0 3 ) . T h e r e f o r e it is c o m m o n p r a c t i c e in theoretical papers t o denote this dependence o n the sample size by indexing the variables with N . W e will suppress this dependence in order t o simplify n o t a t i o n .

Dynamic Panel Data Models with Spatial Correlation • 625

4.2 Data The empirical analysis is mainly based on process data of the Federal Employment Agency. In particular, it is possible to use an integrated database which contains detailed information about registered unemployed, participants in programmes and recipients of unemployment benefits. Additional data about employees is taken from the employment statistics of the Federal Employment Agency which comprises all employees subject to social security. Our analysis is constrained to Western Germany. Because of quite large differences in the labour market situation between the eastern and western part of Germany it is not possible to pool the data. We use monthly data between January 2003 and December 2004 for the 141 local employment agencies. In the following we describe our data in more detail. One of the most important questions in every evaluation study concerns the appropriate outcome measure for quantifying the success of a treatment. According to Social Security Code III, the aim of almost all measures is the re-integration of participants into a regular job. This objective corresponds to the theoretical framework of the augmented matching function. In contrast to many other studies, we are able to distinguish between subsidised and non-subsidised jobs. In our analysis, starting a subsidised job is not regarded as a success. Thus, the dependent variable is outflows of unemployed individuals into regular, non-subsidised employment during one month (period t — 1 until t). We obtain this information from a comparison of the unemployment statistics with the employment statistics. In Germany ALMP includes various discretionary measures. For our analysis we group them into four categories: (1) Further vocational training and retraining (FbW) (2) Shortterm within-firm training measures (TMF) and short-term remaining training measures (TMR) (3) Job creation schemes (JCS) (4) Wage subsidies (BBL). 16 In our study we use the stock of participants in the different programmes at the end of a month (t — 1) as well as their lags as explanatory variables. The programmes FbW, JCS and BBL are included with six lags, whereas only two lags are included for the training measures, since the latter programme has a significant shorter duration than the former ones. According to the theory of matching and the existing literature we include the number of job seekers (registered unemployed and programme participants) and the number of (registered) job vacancies at the end of t — 1 as explanatory variables. Furthermore, we include some indicators to control for the regional composition of the job seekers. We use the share of elderly (UE 0 U) and young (UEYOUNG) unemployed, the share of short (UEshor and long term (U£/OMg) unemployed and the share of German unemployed (UEGER). Finally, we include the share of unemployed people without vocational training (UEWOT)- AS already mentioned we use the dependent variable lagged by one period as an additional explanatory variable to account for adjustment processes.

16

As we use outflows from unemployment into regular employment as a criterion for treatment success, measures promoting self-employment are excluded because their objective is clearly not the integration into non-subsidised employment.

626 • R. Hujer, P.J.M. Rodrigues, and K. Wolf

4 . 3 Empirical results Table 1 s h o w s the estimation results for the two-step estimation of the a u g m e n t e d matching function. T h e s t a n d a r d errors for the spatial estimation are c o m p u t e d using a s y m p totic analysis, w h e r e a s the s t a n d a r d errors of the system estimation are c o m p u t e d by the finite s a m p l e m e t h o d given in Windmeijer ( 2 0 0 5 ) . As can be seen by the results given in the table, the e s t i m a t o r s can differ substantially if spatial correlation is t a k e n into a c c o u n t . A s can be seen for e x a m p l e in the estimated coefficient for the training m e a s u r e s . T h e p a r a m e t e r for the first lag of the training measures within f i r m s ( T M F ) w h e n a c c o u n t i n g for spatial correlation is reduced by a f a c t o r Table 1 Estimation results for the augmented matching function. All parameter values are twostep estimators. For the System estimation the standard errors are calculated by the finite sample correction method given in Windmeijer (2005)

Variable

Endg(- 1) Sp L ag u Sp L ag v

Unem (- 1) Vac(- 1) FBW(- 1) FBW(~ 2) FBW{- 3) FBW(- 4) FBW(- 5) FBW(~ 6) TMF(- 1) TMF(- 2) TMR(~ 1) TMR(- 2) JCS(- 1) JCS(- 2) JCS(- 3) JCS(- 4) JCS(- 5) JCS(- 6) BBL(- 1) BBL(- 2) BBL(- 3) BBL(- 4) BBL(- 5) BBL(- 6) UEoid UEyoung UEWOT UEger

UEshor UE/ong P

Spatial Estimator Binary Distance Par. Par. t-Val. t-Val. 0.403 22.075 0.405 22.890 2.167 0.145 0.719 0.519 - 2.033 - 0.891 - 13.367 - 3.180 0.872 18.105 17.825 0.836 0.020 1.783 0.015 1.305 - 0.075 - 1.851 - 0 . 1 2 4 - 2.900 1.049 - 0.027 - 0.464 0.065 0.065 1.099 - 0.015 - 0.247 - 0.043 - 0.721 - 0.055 - 0.858 0.029 0.468 0.075 1.138 - 0 . 0 1 7 - 0.390 - 0 . 0 1 8 - 0.403 - 0 . 0 1 0 - 0 . 4 1 6 - 0.037 - 1.417 - 0.029 - 1.167 - 0.021 - 0 . 8 1 2 - 0 . 0 3 1 - 3.002 - 0.033 - 2.998 0.009 0.900 0.007 0.690 - 0.008 - 0.549 - 0.009 - 0 . 6 1 6 - 0 . 0 1 9 - 0.932 - 0.021 - 0.964 - 0.007 - 0.329 - 0 . 0 1 4 - 0.658 1.325 0.017 0.845 0.029 - 0.008 - 0.396 - 0.001 - 0.054 0.000 - 0.034 - 0.009 - 0.578 0.017 - 0.001 - 0.026 0.001 -0.140 -2.001 -0.160 -2.123 0.000 - 0 . 0 0 5 0.000 - 0.004 1.190 0.100 1.411 0.091 - 0 . 1 3 3 - 1.881 - 0.092 - 1.210 0.148 3.157 0.126 2.540 0.031 0.446 0.068 0.951 - 0.039 - 0.970 - 0.042 - 1.017 - 0 . 1 3 1 - 2.283 - 0.055 - 0.952 10.405 0.773 8.965 0.883 1.599 0.097 2.782 0.054 - 0.799 - 14.298 - 0.904 - 16.095 0.565

0.408

System Estimator Binary Distance Par. t-Val. t-Val. Par. 0.370 11.198 - 0.001 - 0.021 0.010 0.324 0.897 10.397 - 0.022 - 0.953 - 0.070 - 1.250 0.096 0.813 - 0.287 - 2.541 0.101 0.538 0.006 0.033 0.173 2.014 - 0.073 - 2 . 3 6 1 - 0.040 - 1.055 - 0.047 - 2.643 - 0 . 0 1 1 - 0.584 0.008 0.401 - 0 . 1 1 8 - 3.045 0.007 0.154 0.148 2.782 - 0 . 0 1 1 - 0.229 - 0.066 - 1.900 0.099 1.135 - 0.451 - 2.660 0.073 0.364 -0.187 0.959 0.279 1.881 0.076 0.640 - 0 . 1 7 7 - 1.685 0.147 1.978 - 0.090 - 0.988 1.107 8.079 - 0.040 - 0.666 - 1.022 - 11.913 -

11.092 0.363 0.028 0.619 -0.012 -0.172 10.748 0.901 - 0.013 - 0.607 - 0.068 - 0.995 0.327 0.046 - 0.247 - 1.967 0.104 0.558 0.062 0.012 1.548 0.150 - 0.072 - 2.237 - 0.039 - 0.971 - 0.048 - 2 . 8 7 2 - 0 . 0 1 5 - 0.789 0.609 0.012 - 0 . 1 2 8 - 3.077 0.026 0.001 3.051 0.158 - 0.008 - 0 . 1 6 4 -0.064 -2.110 1.224 0.080 - 0.303 - 1.908 0.082 0.015 - 0.262 - 1.542 0.291 1.885 0.667 0.085 - 0 . 1 5 5 - 1.277 2.708 0.166 - 0.075 - 0 . 7 1 5 7.207 1.108 - 0.055 - 0.930 - 1.070 - 11.478 -

Dynamic Panel Data Models with Spatial Correlation • 627

of 7 w h e n we assume a binary weighting scheme between the regions. A also significant difference, although with less magnitude, is given by the p a r a m e t e r estimator for the first lag of the remaining training measures (TMR).

5

Conclusion

In this paper we have presented an estimation method for dynamic panel d a t a models with spatially correlated errors and/or spatial lags. In section 3, we described the estimation by G M M methods. O n e of the advantages of this estimator lies in the possibility t o derive the m o m e n t conditions f r o m economic theo r y 1 7 A f u r t h e r advantage is that the researcher does not need to m a k e a distributional assumption a b o u t the error term. Since this assumption rarely has a theoretical basis, it is usually m a d e arbitrarily and therefore should be avoided. The problem of identifying p a r a m e t e r s for time-invariant regressors for models in which the regressors are correlated with the individual effects can also be tackled with G M M methods. T h e solution t o this problem lies in the application of system G M M m e t h o d s derived in Arellano a n d Bover (1995) and Blundell and Bond (1998). Moreover, due to the linearity of the moment conditions, the estimator poses n o m a j o r numerical problems and is c o m p u t a t i o n ally feasible for large N . A problem arising f r o m the implementation of this estimator is the large n u m b e r s of instruments. T h e existence of a large n u m b e r of instruments has n o negative effects f r o m an asymptotic perspective, but can cause serious biases in finite samples. Solutions t o these problems can be f o u n d , e.g., in O k u i (2005b) for dynamic panel d a t a models w i t h o u t spatial correlations.

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17

See Hall (2005) for some examples in deriving moment conditions from theoretical considerations.

628 • R. Hujer, P.J.M. Rodrigues, and K. Wolf

Baltagi, B.H., D. Li (2004), Prediction in the panel data model with spatial correlation. Pp. 2 8 3 2 9 6 in: L. Anselin, R.J. Florax, S.J. Rey (eds.), Advances in Spatial Econometrics. Springer, Berlin. Baltagi, B.H., S.H. Song, W. Koh (2003), Testing panel data regression models with spatial error correlation. Journal of Econometrics 117: 1 2 3 - 1 5 0 . Beck, N., K.S. Gleditsch, K. Beardsley (2005), Space is more than geography: Using spatial econometrics in the study of political economy. Working Paper. Beck, T., R. Levina, N . Loayza (2000), Finance and the source of growth. Journal of Financial Economics 58: 2 6 1 - 3 0 0 . Bell, K.P., N.E. Bocksael (2000), Applying the generalized-moments estimation approach to spatial problems involving microlevel data. The Review of Economics and Statistics 81: 7 2 - 8 2 . Besley, T., A. Case (1995), Incumbent behavior: Vote seeking, tax-setting, and yardstick competition. American Economic Review 85: 2 5 - 4 5 . Blundell, R., S. Bond (1998), Initial conditions and m o m e n t restrictions in dynamic panel data models. Journal of Econometrics 87: 1 1 5 - 1 4 3 . Blundell, R., S. Bond, F. Windmeijer (2000), Estimation in dynamic panel data models: Improving on the performance of the standard g m m estimators. Pp. 5 3 - 9 2 in: B.H. Baltagi (ed.), Nonstationary panels, panel cointegration and dynamic panels. Advances in Econometrics, Volume 15, Elsevier Science. Boeri, T., M . Burda (1996), Active labor market policies, job matching and the Czech miracle. European Economic Review 40: 8 0 5 - 8 1 7 . Bond, S. (2002), Dynamic panal data models: A guide to micro data methods and practice. Cemm a p Working Paper cwp09/02, The Institute for Fiscal Studies. Buettner, T. (1999), The effects of unemployment, aggregate wages, and spatial contiguity on local wages: A investigation with german district level data. Papers in Regional Science 78: 47-67. Burda, M . C . , S. Profit (1996), Matching across space: Evidence on mobility in the Czech Republic. Labour Economics 3: 2 5 5 - 2 7 8 . Burgess, S., S. Profit (2001), Externalities in the matching of workers and firms in britain. Labour Economics 8: 3 1 3 - 3 3 3 . Calmfors, L., P. Skedinger (1995), Does active labour-market policy increase employment? Theoretical considerations and some empirical evidence f r o m Sweden. O x f o r d Review of Economic Policy 11: 9 1 - 1 0 9 . Case, A.C., H.S. Rosen, J.R.J. Hines (1993), Budget spillovers and fiscal policy interdependence: Evidence from the states. Journal of Public Economics 52: 2 8 5 - 3 0 7 . Cliff, A.D., J.K. O r d (1973), Spatial autocorrelation. Pion, London. Cliff, A.D., J.K. O r d (1981), Spatial processes. Pion, London. Das, D., H . H . Kelejian, I.R. Prucha (2003), Finite sample properties of estimators of spatial autoregressive models with autoregressive disturbances. Papers in Regional Science 8 2 : 1 - 2 6 . Elhorst, J.P. (2001), Dynamic models in space and time. Geographical Analysis 33: 1 1 9 - 1 4 0 . Eliste, P., P.G. Fredriksson (2004), Does trade liberalization cause a race-to-the-bottom in enviromental policies? A spatial econometric analysis. Pp. 3 8 3 - 3 9 6 in: L. Anselin, R.J. Florax, S.J. Rey (eds.), Advances in spatial econometrics. Springer, Berlin. Hall, A.R. (2005), Generalized M e t h o d s of M o m e n t s . O x f o r d University Press, N e w York. Hansen, L. (1982), Large sample properties of generalized method of moments estimators. Econometrica 50: 1 0 2 9 - 1 0 5 4 . H a u s m a n , J.A., W.E. Taylor (1981), Panel data and unobserved individual effects. Econometrica 49: 1 3 7 7 - 1 3 9 8 . Holtz-Eakin, D., N . Whitney, H . Rosen (1988), Estimating vector autoregressions with panel data. Econometrica 56: 1 3 7 1 - 1 3 9 5 . Hsiao, C. (2003), Analysis of panel data. Cambridge University Press, Cambridge. Hsiao, C., M . Pesaran, A. Tahmiscioglu (2002), M a x i m u m likelihood estimation of fixed effects dynamic panel data models covering short time periods. Journal of Econometrics 109: 1 0 7 150.

Dynamic Panel Data Models with Spatial Correlation • 629

Hübler, O. (2006), Multilevel and nonlinear panel data models. Allgemeines Statistisches Archiv 90: 121-136. Hujer, R., C. Zeiss (2004), Macroeconomic impacts of job creation schemes on the matching process in West Germany. Working Paper, J.W.Goethe-University, Frankfurt. Islam, N. (1995), Growth empirics: A panel data approach. Quarterly Journal of Economics 110: 1127-1170. Kapoor, M., H.H. Kelejian, I.R. Prucha (2007), Panel data models with spatially correlated error components. Journal of Econometrics 140: 97-130. Keane, M., D. Runkle (1992), On the estimation of panel data models with serial correlation when instruments are not strictly exogenous. Journal of Business and Economic Statistics 10: 1-9. Kelejian, H.H., I.R. Prucha (1998), A generalized spatial two-stage least squares procedure for estimating a spatial autoregressive model with autoregressive disturbances. Journal of Real Estate Finance and Economics, 17: 99-121. Kelejian, H.H., I.R. Prucha (1999), A generalized moments estimator for the autoregressive parameter in a spatial model. International Economic Review 40: 509-533. Kelejian, H.H., I.R. Prucha, Y. Yuzefovitch (2004), Instrumental variable estimation of a spatial autoregressive model with autoregressive disturbances: Large and small sample results. Pp. 163-198 in: J. LeSage, R. Pace (eds.), Spatial and spatiotemporal econometrics, Advances In Econometrics, Vol. 18, Elsevier, New York. Lee, L.F. (2002), Consistency and effciency of least squares estimation for mixed regressive, spatial autoregressive models. Econometric Theory 18: 252-277. Mankiw, G.N., D. Romer, D.N. Weil (1992), A contribution to the empirics of economic growth. Quarterly Journal of Economics 107: 407—438. Mätyäs, L., P. Sevestre (eds.) (1996), The econometrics of panel data. Advanced studies in theoretical and applied econometrics, Vol. 33, Kluwer Academic, Dordrecht, 2. ed. Molho, I. (1995), Mirant inertia, accessibility and local unemployment. Economica 62: 123132. Mundlak, Y. (1978), On the pooling of time series and cross section data. Econometrica 46: 6 9 85. Mutl, J. (2005), Dynamic panel data models with spatially correlated innovations. Ph.D. thesis, University of Maryland. Nickeil, S. (1981), Biases in dynamic models with fixed effects. Econometrica 49: 1417-1426. Okui, R. (2005a), Instrumental variable estimation in the presence of many moment conditions. Working Paper, University of Pennsylvania. Okui, R. (2005b), The optimal choice of moments in dynamic panel data models. Working Paper, University of Pennsylvania. Windmeijer, F. (2005), A finite sample correction for the variance of linear effcient two-step gmm estimators. Journal of Econometrics 126: 25-51. Prof. Dr. Reinhard Hujer is Professor of Statistics and Econometrics at the J.W.Goethe-University of Frankfurt a . M . and Research Fellow of the IZA, Bonn and ZEW, Mannheim. Address: Fachbereich Wirtschaftswissenschaften, Goethe-Universität Frankfurt a.M., Mertonstraße 17, 60054 Frankfurt a . M . , Germany. E-Mail: [email protected] Paulo J. M. Rodrigues is Research Assistant at the Chair of Derivatives and Financial Engineering, Fachbereich Wirtschaftswissenschaften, Goethe-Universität Frankfurt a . M . , HoF, Grüneburgplatz 1, 60323 Frankfurt a . M . , Germany. E-Mail: [email protected] Katja Wolf is Research Assistant at the Institute for Employment Research in Nürnberg. Institut für Arbeitsmarkt- und Berufsforschung (IAB), Regensburger Straße 104, 90478 Nürnberg, Germany. E-Mail: [email protected]

Jahrbücher f. Nationalökonomie u. Statistik (Lucius & Lucius, Stuttgart 2008) Bd. (Vol.) 228/5+6

Assessing the Rationality of Survey Expectations: The Probability Approach By Jorg Breitung, Bonn* JEL C42, C53, D84 Rational expectations, survey data, probability model.

Summary This paper considers popular methods for the quantification of survey expectations. We investigate the asymptotic properties of two variants of the probability approach originally suggested by Carlson and Parkin (1975). It is argued that the traditional method can be interpreted as an instrumental variable estimator that suffers from a severe loss of efficiency if the mean of the target variable is close to zero. The regression approach advocated by Pesaran (1984) can be seen as a special case assuming that expectations of survey participants are uniformly distributed. Applying alternative variants of these approaches to the ZEW survey of expected changes in the inflation rate demonstrates that the regression variant of the Carlson-Parkin methodology yields the best fit to the realized changes of the inflation rate. It turns out, however, that even the best performing quantification method fails to fulfill the requirement of rational expectations, as the variance of the expectation error is significantly reduced by including additional variables such as the lagged inflation rate.

1

Introduction

It is widely acknowledged that expectations of market participants play an important role in the theoretical and empirical analysis of the agent's behavior. A leading example from "labormetrics" is the modern version of the wage curve or the "expectation augmented Phillips curve" (e.g. Hall/Taylor 1993, Roberts 1997). M o r e recently, the theory of N e w Keynesian macroeconomics stresses the role of expectations by formulating forward looking behavioral equations such as the forward looking Taylor rule (cf. Gali 2003 for a recent overview). An obvious empirical challenge encountered in such a framework is, however, the measurement of the agents' expectations. This issue is often sidestepped by imposing the assumption of rational expectations. In this case, the unobserved expectations can be replaced by realizations and the parameters are estimated by IV or G M M , where lagged values of the variables are used as instruments. Needless to say that the notion of rational expectations is a quite ambitious concept, as it assumes

* Roughly 2 0 years ago, when I started my doctoral studies in Hannover, Olaf Hubler suggested to me analyzing the informational content of survey expectations. His suggestion has initiated my first t w o papers on the dynamic properties of qualitative survey responses (Breitung 1988, 1989). I wish to thank Olaf for his outstanding support and encouragement during these years. Together with Knut Gerlach and many other colleagues, he has created an extremely stimulating and enthusiastic working atmosphere at the Institute of Quantitative Economics. I also wish to thank an anonymous referee for helpful comments and suggestions.

Assessing the Rationality of Survey Expectations: The Probability Approach • 631

that economic agents are able to compute conditional expectations of the future values of the variables given all available information at a particular point in time. For example, from psychological experiments, it is well known that individuals tend to update their expectations too conservatively, in the sense, that the weights attached to new information are too low compared to what Bayes' formula would imply. Such shortcomings have led many researchers to consider alternative concepts that allow for model uncertainty and learning. An obvious way to study expectation formation of market participants is to use survey data, where participants are asked to reveal their expectations of some variables of interests. However, respondents often feel overstrained when they are asked to give a precise value for economic growth within the next six months, say. Therefore, it has become standard to ask the participants to just indicate the tendency of the variable, that is, whether they expect the variable to increase, decrease, or stay at its current level. Survey participants feel much more comfortable with such a qualitative assessment. An obvious problem with this approach is, however, that the qualitative data has to be translated into a quantitative indicator that can be considered to represent the average of individual expectations. Another problem is that expectations may differ substantially across respondents. This heterogeneity in expectations is in particular relevant for surveys such as the ifo-Konjunkturtest, where participants reveal their expectations about the firm specific situation. Anderson (1952) has suggested the balance statistic (the difference between the relative frequencies of the "increase" and "decrease" categories). Theil (1952) and Carlson and Parkin (1975, henceforth: CP) have suggested simple probability models to estimate the mean of the individual expectations. Refinements of this approach were suggested by Fishe and Lahiri (1981), Bachelor (1981), Seitz (1988) and Dasgupta and Lahiri (1992) inter alia, but the original approach of CP is still the dominant method in practice. An alternative approach was suggested by Pesaran (1984). His method is denoted as the regression approach as it is based on a (possibly nonlinear) least squares regression of the target variable on the response frequencies. Kukuk (1994) proposed an empirical framework for assessing the rationality of survey expectations if the realisations are measured in form of qualitative variables. For a more comprehensive account of the literature, see the recent surveys of Nardo (2003) and Pesaran and Weale (2006). In Section 2, the traditional CP methodology is reconsidered. It is argued that the original estimator of the underlying indifference thresholds that separates the "no change" from the "up" or "down" categories can be seen as an instrumental variable estimator that can be highly inefficient relative to the regression estimator. Furthermore, the regression estimator can easily be extended to allow for asymmetric thresholds. In Section 3 it is shown that the regression approach suggested by Pesaran (1984) can be embedded in the probability approach by assuming a uniform distribution of the expectations. An empirical application is considered in Section 4. Using data from the Financial Market Survey of the ZEW, the expectations of 350 financial experts are analyzed. Applying five variants of the probability and regression approach, we find that the regression variant of the CP methodology provides the best fit to the realized 6-months ahead changes of inflation rates. However, a simple time series model based on a first order autoregressive representation clearly outperforms the measures of survey expectations in terms of insample fit and predictive ability.

632 • J. Breitung

2

The CP methodology

Following CP (1975) we assume that at time period t (f = 1 , . . . , T ) the individual i (i = 1 , 2 , . . . , N ) has formed the expectation y?t for variable yt that typically refers to a future realization of a macroeconomic variable. For example, in Section 4 yt refers to the six months ahead changes in logarithms of the inflation rate. It is important to note that our framework focuses on individual expectations about an aggregated variable (e.g. the change in inflation rate derived f r o m the consumer price index). This is an important difference to the ifo business survey (Konjunkturtest), say, where the participants report the expected price change of the goods produces in their own firm. Suppose that yejt is drawn independently from a normally distributed population with expectation ¡it and and variance of. The respondent reports an increase if yeu > oo, the limiting distributions Vf(6cp-Ô)

±

of the estimators

result as

Nioyj2/^)

Vf(ôls-ô)^N(0yuô2/^). Proof: For the original CP estimator we have

The central limit theorem for martingale difference sequences implies oyj

(=i

and by using the law of large numbers, we obtain T

plim

T"1

Vz

t

=/7/