Forecasting Sales and Price for Existing Single-Family Homes: A VAR Model with Error Correction

In recent years researchers have begun exploring the relationships between the real estate market and other related markets. For example, Case and Shiller (1990) find that price changes and excess returns of single-family housing can be predicted by a number of information variables. Using the Granger equilibrium model Goebel and Ma (1993) find that mortgage rates and general interest rates are cointegrated after 1980. Schnitzel (1986), on the other hand, finds that deposit rates Granger-cause mortgage rates for Savings and Loans (S&L) during the period of 1970–78. Over the period 1978–84, however, he finds that it is mortgage rates that determine deposit rates. Less work has been done in exploring the fundamental relationship between sales and price for existing single-family homes. It is particularly interesting to investigate this housing market as it represents the biggest portion of home sales in the United States. The VAR model with error correction obtained here can help to analyze and predict the demand for existing single-family homes. Moreover, since residential investment has a timing lagged effect, forecasting the housing demand also appears to be important for policy makers. In this study, we concentrate on the time-series behavior and relation between sales volume and median sales price. The sales and price data are for the existing single-family houses in the United States. We find that the levels of sales and price have unit roots. That is to say, the two real estate series are not stationary. Their first-order differences are, however, stationary. Further, we find that sales and price are cointegrated. That is, they tend to move together and converge in the long run. Following Engle and Granger (1987), therefore, we construct a VAR model with error correction to examine the Granger causality relationship between sales and price. We find that sales affect price JOURNAL OF REAL ESTATE RESEARCH 1