A Study on the Persistence of Housing Price Inflation Considering Model Uncertainty

Abstract

Since the fluctuations in housing market have significant effects on financial and real economy, it is important to understand the statistical property of housing price data. In case of Korea, the frequent changes in government policy stance and the rapid developments in economic structure (such as population and the development of capital market) are very likely to have affected the statistical property of housing price inflation. The persistence of housing price inflation is defined as the speed of the price adjustment in response to a shock in housing market. This study analyzes how the persistence of housing price inflation in Korea has changed over time. The main feature of this study is that model uncertainty is considered in analyzing the fluctuation of the persistence. In general, empirical analysis proceeds as follows: (1) Most plausible model is selected based on data, and (2) parameters are estimated. To expound the persistence of a time-series data, we need to include autoregressive variables. Since we utilize small sample of data for the analysis, it is possible that an incorrect lag structure is selected and hence inappropriate implication is drawn. Therefore, we explicitly consider the model with various autoregressive structures in the estimation process to deal with the issue of model uncertainty. For the estimation, Gibbs sampling based on the method of Kuo and Mallick (1998) is utilized. The results of the empirical analysis indicate that the persistence of housing price inflation is stronger around the rising trend in terms of the cycle and in the Seoul metropolitan area in terms of region. Since 1988, three major upturns in housing market have been observed. The persistence of housing price begins to rise more rapidly just before the beginning of the upturns and to decline after the end of it. Regionally, the fluctuations in the persistence are greater in the Seoul metropolitan area than in the six local metropolitan area.