Abstract

The essay utilizes a unique dataset of 30 Chinese provinces and municipal cities residential selling prices from 1998 to 2013, and examines the herding behavior. Using a least squares method and quantile regression method, we study the herding effect of China housing market at both national and cities levels. Results show that herding formation is stronger in increasing markets than that in decreasing markets. But when the markets are turning turbulent, in the high quantile regression, there is herding activity in decreasing markets. Our results also support the asymmetry of herding behavior in increasing and decreasing markets. By examining the financial crisis on the level of herding behavior, investors in China residential housing markets tend to herd before the crisis, and there is no herding behavior during and after financial crisis by quantitle regression. This study is important for three main reasons. Firstly, although the existing theoretical and empirical studies have investigated abnormal increasing price of China housing market, to the best of author knowledge, we are the first to apply this method to investigate herding phenomena in China housing market, which this essay focuses. Secondly, due to China residential housing market unique characteristics, this study makes a first attempt to examine the herding behavior by using quantile regression. Thirdly, our studies of this paper extend our knowledge of China real estate market to practitioners, academia and policymakers.

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