A New Hedonic Regression for Real Estate Prices Applied to the Singapore Residential Market

This paper develops a new hedonic method for constructing a real estate price index that utilizes all transaction price information that encompasses both single-sale and repeat-sale properties. The new method is less prone to specification errors than standard hedonic methods and uses all available data. Like the Case-Shiller repeat-sales method, the new method has the advantage of being computationally efficient. In an empirical analysis of the methodology, we fit the model to all transaction prices for private residential property holdings in Singapore between Q1 1995 and Q2 2014, covering several periods of major price fluctuation and changes in government macroprudential policy. Two new indices are created, one from all transaction prices and one from single-sales prices. The indices are compared with the S&P/Case-Shiller index. The result shows that the new indices slightly outperform the S&P/Case-Shiller index in predicting the price of single-sales homes out-of-sample. However, they underperform the S&P/Case-Shiller index in predicting the price of repeat-sales homes out-of-sample. The empirical findings indicate that specification bias can be more substantial than the sample selection bias when constructing a real estate price index. In a further empirical application, the recursive method of Phillips, Shi and Yu (2014) is used to detect explosive periods in real estate prices of Singapore. The results confirm the existence of an explosive period from Q4 2006 to Q1 2008. No explosive period is found after 2009, suggesting that the ten successive rounds of cooling measures implemented by Singapore government have been effective in changing price dynamics and preventing a subsequent outbreak of explosive behavior in Singapore real estate market.