The nonlinear interaction of real estates and economic growth in China

Abstract

This paper provides a model for verifying the effects of real estate, because real estate industry has a fairly important position in the Chinese economy. This paper uses the nonlinear optimized techniques to estimate EGARCH(1,1)-GED model. Due to autocorrelation, kurtosis and volatility clustering, this paper adopt the EGARCH(1,1)-GED model. This paper uses monthly data of gross domestic products, housing prices, interest rates, exchange rates, consumer prices and stock price index, and the analysis period is 18 years from January 2000 to December 2017, The empirical findings are as follows. First, the rise in housing prices increases both the return and volatility of GDP growth of China. The empirical findings that changes in housing prices have a greater impact on GDP growth of China than changes in interest rates are consistent to prior studies. Second, we found that changes in new housing prices have a relatively greater impact on economic growth than changes in existing housing prices. This empirical result is a new one that has not been found in previous studies. Third, changes in real interest rates have a relatively greater impact on GDP growth in China than changes in normal interest rates. Fourth, in contrast to the significant impact of Beijing’s housing prices on economic growth, the housing prices in Hong Kong has shown insignificant impact on GDP growth in China. According to these findings, real estate development has an effect in the GDP growth of China. In light of the empirical results, China’s policy authorities should monitor the price trends of the new housing prices and make efficient management accordingly.