Abstract
A known trend in the housing market is that prices and trading volume correlate with each other and the correlation is built on the causal relationship between the two housing market variables. This paper investigates whether the price-volume causality can be used to enhance the forecasting power in the prediction of the price and the volume. Using Seoul and Busan housing market data for the period of Jan. 2006 to Mar. 2018, dynamic out-of-sample forecasting exercises were implemented in a recursive estimation scheme.BR The empirical results were as follows: Firstly, Johansson cointegration test showed that a long-run equilibrium relationship between price and volume holds for both cities. Secondly, Granger-causality of price to volume is strong while the causality of volume to price is weak. Thirdly, VEC model and VAR model deliver better forecasting performances than AR model, along with statistical significance. Fourthly, improvement of volume forecast prediction performance is much bigger as compared to the improvement in the price forecast. It is worth noting that higher Granger-causality leads to bigger forecasting power.
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