Ohio State is in the process of revising websites and program materials to accurately reflect compliance with the law. While this work occurs, language referencing protected class status or other activities prohibited by Ohio Senate Bill 1 may still appear in some places. However, all programs and activities are being administered in compliance with federal and state law.

CURA Awards Travel Grant to Jing Song

October 2, 2013

CURA Awards Travel Grant to Jing Song

photo of Atlanta

CURA has awarded Jing Song, PhD candidate in the Department of Economics, a travel grant to present "House Price Dynamics" at the 2013 North American Meetings of the Regional Science Association International in Atlanta this November.

Abstract:

This paper develops and estimates a model that explains several house price phenomena. The first one is a “stationarity-puzzle”: real house prices are trend stationary while real income, one of the most important factors identified in the literature as a determinant of real house prices, contains a unit root. Therefore, the challenge for a coherent house price model is to combine the different stationarity properties of house prices and income. Another phenomenon that has not been well explained in the literature is the short-run positive serial correlation (positive one-year autoregressive coefficient) and long-run mean reversion (negative five-year autoregressive coefficient) of house price changes. This paper modifies the dynamic spatial equilibrium model in Glaeser et al. (2012) by assuming a unit root process for income and considers both rational expectations and adaptive expectations to explain the above phenomena. I solve the model under both rational expectations and adaptive expectations. Separating Metropolitan Statistical Areas into a coastal group and an inland group, I estimate the model’s parameters. Next, house price series are simulated and the autoregressive coefficients of one-year and five-year changes as well as the unit root test statistic are calculated. The model with adaptive expectations fits the empirical features better than the one that assumes rational expectations: it generates positive one-year autoregressive coefficient, negative five-year autoregressive coefficient, and the unit root test rejects a unit root.