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Maximum score estimates of the determinants of residential mobility: Implications for the value of residential attachment and neighborhood amenities

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  • Bartik, Timothy J.
  • Butler, J. S.
  • Liu, Jin-Tan

Abstract

This paper examines the determinants of the decision of low-income renters to move out of their current dwelling. Maximum score estimation is shown t be superior to ordinary discrete choice estimation techniques (probit, logit) for this problem, ad for similar discrete choices that require revering a previously optimal decision. The estimation reveals psychological costs of moving for typical low income renters of at least 8 percent of their income; these costs are even higher for older, longer tenure, or minority households. Policies that displace low income renters will have large social costs. In addition, the estimation results are used to calculate implicit household willingness to pay (WTP) for neighborhood amenities. This WTP based on mobility behavior is much greater than WTP estimates derived using hedonic methods, and is argued to be more accurate. This paper uses a semiparametric empirical technique to estimate the determinants of the decision of low-income renters to move out of their dwelling. These estimates show that low-income residents highly value remaining in their dwelling. In addition, these estimates are used to illustrate an alternative method to measure willingness to pay for neighborhood amenities. Moving decisions are usually examined with standard discrete choice models such as probit or logit (e.g., Venti and Wise (1984), or Weinberg, Friedman, and Mayo (1981). But the moving decision presents econometric difficulties for standard discrete choice models. As will be explained in section 1, because the household decision about moving is conditional on having previously preferred the original location, the disturbance term in mobility models is unlikely to follow the simple distributional forms required for probit or logit estimation. Maximum score estimation is an alternative estimation technique for discrete choice models that is robust to unusual distributions of the disturbance term. Although the theoretical properties of maximum score e

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Urban Economics.

Volume (Year): 32 (1992)
Issue (Month): 2 (September)
Pages: 233-256

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Handle: RePEc:eee:juecon:v:32:y:1992:i:2:p:233-256

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Web page: http://www.elsevier.com/locate/inca/622905

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References

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  1. Venti, Steven F. & Wise, David A., 1984. "Moving and housing expenditure: Transaction costs and disequilibrium," Journal of Public Economics, Elsevier, Elsevier, vol. 23(1-2), pages 207-243.
  2. Timothy J. Bartik & V. Kerry Smith, 1996. "Urban Amenities and Public Policy," Book chapters authored by Upjohn Institute researchers, W.E. Upjohn Institute for Employment Research, in: V. Kerry Smith (ed.), Estimating Economic Values for Nature: Methods for Non-Market Valuation, pages 271-318 W.E. Upjohn Institute for Employment Research.
  3. Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, Elsevier, vol. 3(3), pages 205-228, August.
  4. Bolton, R., 1989. "An Economic Interpretation Of A Sense Of Place," Department of Economics Working Papers, Department of Economics, Williams College 130, Department of Economics, Williams College.
  5. Manski, Charles F. & Thompson, T. Scott, 1986. "Operational characteristics of maximum score estimation," Journal of Econometrics, Elsevier, Elsevier, vol. 32(1), pages 85-108, June.
  6. Dunn, L. F., 1979. "Measuring the value of community," Journal of Urban Economics, Elsevier, Elsevier, vol. 6(3), pages 371-382, July.
  7. Dynarski, Mark, 1985. "Housing demand and disequilibrium," Journal of Urban Economics, Elsevier, Elsevier, vol. 17(1), pages 42-57, January.
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Citations

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Cited by:
  1. Quigley, John M., 2002. "Transactions Costs and Housing Markets," Berkeley Program on Housing and Urban Policy, Working Paper Series, Berkeley Program on Housing and Urban Policy qt6pz8p6zt, Berkeley Program on Housing and Urban Policy.
  2. Ross, Stephen L., 1998. "Racial Differences in Residential and Job Mobility: Evidence Concerning the Spatial Mismatch Hypothesis," Journal of Urban Economics, Elsevier, Elsevier, vol. 43(1), pages 112-135, January.
  3. Kamhon Kan, 2006. "Residential Mobility and Social Capital," IEAS Working Paper : academic research, Institute of Economics, Academia Sinica, Taipei, Taiwan 06-A005, Institute of Economics, Academia Sinica, Taipei, Taiwan.
  4. Van Ommeren, Jos & Koopman, Marnix, 2011. "Public housing and the value of apartment quality to households," Regional Science and Urban Economics, Elsevier, Elsevier, vol. 41(3), pages 207-213, May.
  5. Cragg, Michael & Kahn, Matthew, 1997. "New Estimates of Climate Demand: Evidence from Location Choice," Journal of Urban Economics, Elsevier, Elsevier, vol. 42(2), pages 261-284, September.
  6. Van Ommeren, Jos & Fosgerau, Mogens, 2009. "Workers' marginal costs of commuting," Journal of Urban Economics, Elsevier, Elsevier, vol. 65(1), pages 38-47, January.
  7. Ommeren, Jos van & Berg, Gerard J. van den & Gorter, Cees, 1998. "Estimating the marginal willingness to pay for commuting," Serie Research Memoranda, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics 0046, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
  8. Jos Van Ommeren & Mihails Hazans, 2008. "Workers' Valuation of the Remaining Employment Contract Duration," Economica, London School of Economics and Political Science, London School of Economics and Political Science, vol. 75(297), pages 116-139, 02.
  9. Wenli Li & Haiyong Liu & Rui Yao, 2009. "Housing over time and over the life cycle: a structural estimation," Working Papers, Federal Reserve Bank of Philadelphia 09-7, Federal Reserve Bank of Philadelphia.
  10. Daniel Aaronson, 1998. "The effect of school finance reform on population heterogeneity," Working Paper Series, Federal Reserve Bank of Chicago WP-98-11, Federal Reserve Bank of Chicago.
  11. repec:dgr:uvatin:2010085 is not listed on IDEAS
  12. Van Ommeren, Jos & Graaf-de Zijl, Marloes, 2013. "Estimating household demand for housing attributes in rent-controlled markets," Journal of Housing Economics, Elsevier, Elsevier, vol. 22(1), pages 11-19.
  13. Gregory Kordas, 2006. "Smoothed binary regression quantiles," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 21(3), pages 387-407.
  14. Florios, Kostas & Skouras, Spyros, 2008. "Exact computation of max weighted score estimators," Journal of Econometrics, Elsevier, Elsevier, vol. 146(1), pages 86-91, September.
  15. van Ommeren, Jos & Rietveld, Piet & Nijkamp, Peter, 1999. "Job Moving, Residential Moving, and Commuting: A Search Perspective," Journal of Urban Economics, Elsevier, Elsevier, vol. 46(2), pages 230-253, September.
  16. Teemu Lyytikäinen, 2008. "Studies on the Effects of Property Taxation, Rent Control and Housing Allowances," Research Reports, Government Institute for Economic Research Finland (VATT) 140, Government Institute for Economic Research Finland (VATT).
  17. Ji, Yonggang & Lin, Nan & Zhang, Baoxue, 2012. "Model selection in binary and tobit quantile regression using the Gibbs sampler," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 56(4), pages 827-839.

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