Spatial wage disparities can result from spatial differences in the skill composition of the workforce, in nonhuman endowments, and in local interactions. To distinguish between these explanations, we estimate a model of wage determination across local labour markets using a very large panel of French workers. We control for worker characteristics, worker fixed effects, industry fixed effects, and the characteristics of the local labour market. Our findings suggest that individual skills account for a large fraction of existing spatial wage disparities with strong evidence of spatial sorting by skills. Interaction effects are mostly driven by the local density of employment. Not controlling for worker heterogeneity leads to very biased estimates of interaction effects. Endowments only appear to play a small role.Keywords local labour markets, spatial wage disparities, panel data analysis, sorting Disciplines Economics | Real Estate Comments• At the time of publication, author Gilles Duranton was affiliated with the University of Toronto.Currently, he is a faculty member at the Real Estate Department at the University of Pennsylvania. Abstract Spatial wage disparities can result from spatial dierences in the skill composition of the workforce, in non-human endowments, and in local interactions. To distinguish between these explanations, we estimate a model of wage determination across local labour markets using a very large panel of French workers. We control for worker characteristics, worker xed eects, industry xed eects, and the characteristics of the local labour market. Our ndings suggest that individual skills account for a large fraction of existing spatial wage disparities with strong evidence of spatial sorting by skills. Interaction eects are mostly driven by the local density of employment. Not controlling for worker heterogeneity leads to very biased estimates of interaction eects. Endowments only appear to play a small role.Key words: local labour markets, spatial wage disparities, panel data analysis, sorting jel classication: r23, j31, j61 a We are grateful to Lionel Fontagné, Vernon Henderson, Francis Kramarz, Thierry Magnac, Gianmarco Ottaviano, Barbara Petrongolo, Diego Puga, Jean-Marc Robin, Sébastien Roux, Jon Temple, Dan Treer, two anonymous referees, and especially Henry Overman for fruitful discussions, advice and encouragements. We also acknowledge France Guérin, Francis Kramarz and Sébastien Roux's kind and ecient help with the data. Seminar and conference participants in Bogotá, Bristol, Brown, CREST, Kiel, Lille, LSE, Marseille, Paris, Philadelphia, Rome, Royal Holloway, Stockholm, Stoke-Rochford, Toronto, UCL, and Villars also provided us with very useful feed-back.

The empirics of agglomeration economies* We propose an integrated framework to discuss the empirical literature on the local determinants of agglomeration effects. We start by presenting the theoretical mechanisms that ground individual and aggregate empirical specifications. We gradually introduce static effects, dynamic effects, and workers' endogenous location choices. We emphasise the impact of local density on productivity but we also consider many other local determinants supported by theory. Empirical issues are then addressed. Most important concerns are about endogeneity at the local and individual levels, the choice of a productivity measure between wage and TFP, and the roles of spatial scale, firms' characteristics, and functional forms. Estimated impacts of local determinants of productivity, employment, and firms' locations choices are surveyed for both developed and developing economies. We finally provide a discussion of attempts to identify and quantify specific agglomeration mechanisms.JEL Classification: J31, R12 and R23

Does productivity increase with density? We revisit the issue using French wage and TFP data. To deal with the 'endogenous quantity of labour bias (i.e., urban agglomeration is consequence of high local productivity rather than a cause), we take an instrumental variable approach and introduce a new set of geological instruments in addition to standard historical instruments. To deal with the 'endogenous quality of labour bias (i.e., cities attract skilled workers so that the effects of skills and urban agglomeration are confounded), we take a worker fixed-effect approach with wage data. We find modest evidence about the endogenous quantity of labour bias and both sets of instruments give a similar answer. We find that the endogenous quality of labour bias is quantitatively more important. Disciplines Real EstateThis working paper is available at ScholarlyCommons: http://repository.upenn.edu/real-estate_papers/21Estimating agglomeration economies with history, geology, and worker effects Pierre-Philippe Combes * † University of Aix-MarseilleGilles Duranton * ‡ University of TorontoLaurent Gobillon * § Institut National d'Etudes DémographiquesSébastien Roux * Centre de Recherche en Économie et Statistique February 2008ABSTRACT: Does productivity increase with density? We revisit the issue using French wage and TFP data. To deal with the 'endogenous quantity of labour' bias (i.e., urban agglomeration is consequence of high local productivity rather than a cause), we take an instrumental variable approach and introduce a new set of geological instruments in addition to standard historical instruments. To deal with the 'endogenous quality of labour' bias (i.e., cities attract skilled workers so that the effects of skills and urban agglomeration are confounded), we take a worker fixed-effect approach with wage data. We find modest evidence about the endogenous quantity of labour bias and both sets of instruments give a similar answer. We find that the endogenous quality of labour bias is quantitatively more important.

Summary. The spatial mismatch hypothesis (SMH) argues that low-skilled minorities residing in US inner cities experience poor labour market outcomes because they are disconnected from suburban job opportunities. This assumption gave rise to an abundant empirical literature, which is rather supportive of the SMH. Surprisingly, it is only recently that theoretical models have emerged, which probably explains why the mechanisms of spatial mismatch have long remained unclear and not properly tested. This article presents relevant facts, reviews the theoretical models of spatial mismatch, confronts their predictions with available empirical results and indicates which mechanisms deserve further empirical tests.