Repeat Sales Regression on Heterogeneous Properties

Posted: 27 Nov 2012

See all articles by Liang Peng

Liang Peng

Smeal College of Business, The Pennsylvania State University

Multiple version iconThere are 2 versions of this paper

Date Written: November 27, 2012


This paper proposes a generalized repeat sales regression (GRSR) that uses repeat sales from the entire market, in which properties may have heterogeneous value appreciation processes, to estimate price indices for not only the entire market, but also submarkets or customized portfolios of properties that only have small numbers of value observations. Monte Carlo simulations provide strong evidence that the GRSR indices more accurately measure the index for the entire market as well as individual property value appreciation than conventional RSR indices. This paper also proposes a Chi-square test to detect the heterogeneity in property value appreciation across submarkets/portfolios, and use simulations to show that the test is powerful in small samples. This paper finally illustrates the applicatioin of the GRSR using a historical dataset of the Chicago housing market from 1970 to 1986.

Keywords: Repeat sales regression, Heterogeneity, EM algorithm, Chi-square test, Monte Carlo simulation

JEL Classification: C12, C13, C15, C43

Suggested Citation

Peng, Liang, Repeat Sales Regression on Heterogeneous Properties (November 27, 2012). Journal of Real Estate Finance and Economics, Vol. 45, No. 3, 2012. Available at SSRN:

Liang Peng (Contact Author)

Smeal College of Business, The Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

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