This paper introduces an equilibrium framework for analyzing residential sorting, designed to take advantage of newly available restricted-access Census microdata. The framework adds an equilibrium concept to the discrete choice framework developed by McFadden (1973McFadden ( , 1978, permitting a more flexible characterization of preferences than has been possible in previously estimated sorting models. Using data on nearly a quarter of a million households residing in the San Francisco Bay Area in 1990, our estimates provide a precise characterization of preferences for many housing and neighborhood attributes, showing how demand for these attributes varies with a household's income, race, education, and family structure. We use the equilibrium model in combination with these estimates to explore the effects of an increase in income inequality, the findings indicating that much of the increased spending power of the rich is absorbed by higher housing prices.

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Notes: Center Discussion Papers are preliminary materials circulated to stimulate discussions and critical comments. Terms of use: Documents in EconStor mayThe authors would like to thank Fernando Ferreira (University of California, Berkeley) for outstanding research assistance, as well as Pedro Cerdan and Jackie Chou for help assembling the data. We would also like to thank Debbie Reed, Steve Ross, Jon Sonstelie, Chris Udry, Junfu Zhang and seminar participants at Johns Hopkins, UCLA, and Yale for helpful comments. We are grateful to the California Census Research Data Center for providing access to the data and to Ritch Milby in particular. All output included in this paper has been subject to thorough disclosure analysis by Census Bureau officials and meets stringent standards to safeguard confidentiality. Financial support from the Public Policy Institute of California is gratefully acknowledged. Please send correspondence to any of the authors: patrick.bayer@yale.edu, mcmillan@chass.utoronto.ca, or rueben@ppic.org This paper can be downloaded without charge from the Social Science Research Network electronic library at: http://ssrn.com/abstract=428742An index to papers in the Economic Growth Center Discussion Paper Series is located at: http://www.econ.yale.edu/~egcenter/research.htm What Drives Racial Segregation? New Evidence Using Census MicrodataPatrick Bayer, Robert McMillan, and Kim Rueben AbstractThis paper sheds new light on the forces that drive residential segregation on the basis of race, assessing the extent to which across-race differences in other household characteristics can explain a significant portion of observed racial segregation. The central contribution of the analysis is to provide a transparent new measurement framework for understanding segregation patterns. This framework allows researchers to characterize patterns of segregation, to decompose them in meaningful ways, and to carry out partial equilibrium counterfactuals that illuminate the contributions of a variety of non-race characteristics in driving segregation. We illustrate our approach using restricted micro-Census data from the San Francisco BayArea that provide a rich joint distribution of household and neighborhood characteristics not previously available to the research community. In contrast to findings in the prior literature, our analysis indicates that individual household characteristics can explain a considerable fraction of segregation by race, explaining...

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This paper documents the changing pattern of wage differentials between state and local government employees and their piiv ate sector counterparts during the 1979-1992 period. While the relative wages of women employed in the two sectors changed very little during this period.the relative wages of men employed in the state and local sector rose nearly 8%. There is substantial heterogeneity in the changes in relative wages of public and private sector employees during the 1980s. For highly educated workers, private sector wages rose significantly faster than public sector wages, while for those with at most a high school education, the public sector wage premium increased. We present both least squares and quantile regression estimates of the public sector premium. While the level of this premium is sensitive to our choice of quantile, the change in the premium, and the estimated pattern across skill levels, is not substantially affected by varying the quantile.