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Tiebout Sorting and Neighborhood Stratification

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  • Patrick Bayer
  • Robert McMillan

Abstract

Tiebout’s classic 1956 paper has strong implications regarding stratification across and within jurisdictions, predicting in the simplest instance a hierarchy of internally homogeneous communities ordered by income. Typically, urban areas are less than fully stratified, and the question arises how much departures from standard Tiebout assumptions contribute to observed within-neighborhood mixing. This paper quantifies the separate effects on neighborhood stratification of employment geography (via costly commuting) and preferences for housing attributes. It does so using an equilibrium sorting model, estimated with rich Census micro-data. Simulations based on the model using credible preference estimates show that counterfactual reductions in commuting costs lead to marked increases in racial and education segregation and, to a lesser degree, increases in income segregation, given that households now find it easier to locate in neighborhoods with like households. While turning off preferences for housing characteristics increases racial segregation, especially for blacks, doing so reduces income segregation, indicating that heterogeneity in the housing stock serves to stratify households based on ability-to-pay. Further, we show that differences in housing also help accentuate differences in the consumption of local amenities.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 17364.

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Date of creation: Aug 2011
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Publication status: published as Tiebout Sorting and Neighborhood Stratification , Patrick Bayer, Robert McMillan. in Fiscal Federalism , Cullen and Gordon. 2012
Handle: RePEc:nbr:nberwo:17364

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  1. Patrick Bayer & Fernando Ferreira & Robert McMillan, 2007. "A Unified Framework for Measuring Preferences for Schools and Neighborhoods," Working Papers 07-27, Center for Economic Studies, U.S. Census Bureau.
  2. Patrick Bajari & Matthew E. Kahn, 2003. "Estimating Housing Demand with an Application to Explaining Racial Segregation in Cities," NBER Working Papers 9891, National Bureau of Economic Research, Inc.
  3. Epple, Dennis & Romano, Richard E, 1998. "Competition between Private and Public Schools, Vouchers, and Peer-Group Effects," American Economic Review, American Economic Association, vol. 88(1), pages 33-62, March.
  4. Nechyba, Thomas J, 1999. " School Finance Induced Migration and Stratification Patterns: The Impact of Private School Vouchers," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 1(1), pages 5-50.
  5. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
  6. Holger Sieg & V. Kerry Smith & H. Spencer Banzhaf & Randy Walsh, 2004. "Estimating The General Equilibrium Benefits Of Large Changes In Spatially Delineated Public Goods," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(4), pages 1047-1077, November.
  7. Anas, Alex & Kim, Ikki, 1996. "General Equilibrium Models of Polycentric Urban Land Use with Endogenous Congestion and Job Agglomeration," Journal of Urban Economics, Elsevier, vol. 40(2), pages 232-256, September.
  8. Epple, Dennis & Romano, Richard E, 1996. "Public Provision of Private Goods," Journal of Political Economy, University of Chicago Press, vol. 104(1), pages 57-84, February.
  9. Patrick Bayer & Robert McMillan & Kim Rueben, 2004. "An Equilibrium Model of Sorting in an Urban Housing Market," NBER Working Papers 10865, National Bureau of Economic Research, Inc.
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Cited by:
  1. Haavio, Markus & Kauppi , Heikki, 2011. "Owner-occupied housing as an investment, regional house price cycles and residential sorting," Research Discussion Papers 24/2011, Bank of Finland.
  2. Li, Guo & Mroz, Thomas A., 2013. "Expected income and labor market choices of US married couples: A locally weighted regression approach," Regional Science and Urban Economics, Elsevier, vol. 43(6), pages 985-995.

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