Housing Market Dynamics: Evidence of Mean Reversion and Downward Rigidity

34 Pages Posted: 29 Jul 2012

See all articles by Andre Gao

Andre Gao

Federal National Mortgage Association (Fannie Mae)

Zhenguo (Len) Lin

Florida International University (FIU) - Hollo School of Real Estate

Carrie Fangzhou Na

Federal National Mortgage Association (Fannie Mae)

Date Written: 2009

Abstract

House prices often exhibit serial correlation and mean reversion. Using two large panel datasets, this paper analyzes the price dynamics in two significantly different types of markets, cyclical (or volatile) and non-cyclical (or tame), by applying the autoregressive mean reversion (ARMR) model. Our results show that cyclical markets have larger AR coefficients than non-cyclical markets. As a result, house prices in cyclical markets tend to have larger price cycles. We also find that the upward periods have AR larger coefficients than the downward periods. This demonstrates that house prices are likely to overshoot the equilibrium in appreciating markets while experiencing downward rigidity during periods of decline. The model developed in this paper can produce a forecast with rich house price dynamics across markets. The model can also be used to determine how house prices in overvalued markets will ultimately adjust.

Keywords: Housing Market Dynamics, Mean Reversion, Downward Rigidity

Suggested Citation

Gao, Andre and Lin, Zhenguo and Na, Carrie Fangzhou, Housing Market Dynamics: Evidence of Mean Reversion and Downward Rigidity (2009). Journal of Housing Economics, Vol. 18, 2009, Available at SSRN: https://ssrn.com/abstract=1636879

Andre Gao

Federal National Mortgage Association (Fannie Mae) ( email )

3900 Wisconsin Avenue, NW
Washington, DC 20016-2892
United States

Zhenguo Lin (Contact Author)

Florida International University (FIU) - Hollo School of Real Estate ( email )

Miami, FL 33199
United States
3057799248 (Phone)

Carrie Fangzhou Na

Federal National Mortgage Association (Fannie Mae) ( email )

3900 Wisconsin Avenue, NW
Washington, DC 20016-2892
United States

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