Affordable levels of house prices using fuzzy linear regression analysis: the case of Shanghai

Abstract

The house prices in China have been growing nearly twice as fast as national income over the last decade. Such an irrational soaring of house prices, not only puts the Chinese economy in danger, but also the country’s social interconnectedness and stability are at risk. Under this background, assuming that the affordable level of house prices from a consumer perspective is an uncertain parameter, which can be modelled, respectively, as symmetric and asymmetric triangular fuzzy number, several types of fuzzy linear regression models are introduced. A survey for the city of Shanghai was conducted, where three major policy and an equal number of non-policy variables have been selected to facilitate the analysis. The results derived show that the real estate tax policy had a key role for retaining the house prices in Shanghai in short run, whereas the two non-policies variables, annual household income and housing size, have even greater influence on consumers than policy variables. Additionally, it was observed that the family population and the affordable level of house prices are correlated negatively.