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An Estimatable DCDP Model of Search and Matching in Real Estate Markets

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  • Stuart J. Fowler
  • Jennifer J. Wilgus

Abstract

The primary purpose of this study is to introduce an estimatable model of search and matching in real estate markets. A benefit of developing such a theory is so we may better understand the structure that determines these choices. The DCDP model that we propose produces the following results. First, the model is able to replicate several salient features of real estate markets. Second, the estimation method is able to accurately and efficiently recover the structural demand and supply functions of the buyers and sellers.

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File URL: http://capone.mtsu.edu/berc/working/match1.pdf
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Bibliographic Info

Paper provided by Middle Tennessee State University, Department of Economics and Finance in its series Working Papers with number 201105.

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Date of creation: Sep 2011
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Handle: RePEc:mts:wpaper:201105

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Web page: http://www.mtsu.edu/~berc/working/Economics_Working_Papers.html
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Related research

Keywords: Real Estate; Search and Matching; Structural Estimation; MCMC; and Gibbs-Sampler;

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  1. John Geweke, 1992. "Priors for macroeconomic time series and their application," Discussion Paper / Institute for Empirical Macroeconomics 64, Federal Reserve Bank of Minneapolis.
  2. John F. Geweke & Michael P. Keane, 1996. "Bayesian inference for dynamic choice models without the need for dynamic programming," Working Papers 564, Federal Reserve Bank of Minneapolis.
  3. Genesove, D. & Mayer, C.J., 1994. "Equity and Time to Sale in the Real Estate Market," Working papers 94-02, Massachusetts Institute of Technology (MIT), Department of Economics.
  4. Susumu Imai & Neelam Jain, 2005. "Bayesian Estimation of Dynamic Discrete Choice Models," 2005 Meeting Papers 432, Society for Economic Dynamics.
  5. Michael P. Keane & Kenneth I. Wolpin, 2009. "Empirical Applications of Discrete Choice Dynamic Programming Models," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(1), pages 1-22, January.
  6. Tripathi, Gautam, 2000. "Econometric Methods," Econometric Theory, Cambridge University Press, vol. 16(01), pages 139-142, February.
  7. Houser, Daniel, 2003. "Bayesian analysis of a dynamic stochastic model of labor supply and saving," Journal of Econometrics, Elsevier, vol. 113(2), pages 289-335, April.
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