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ESTIMATING THE LIMITED IMPACT OF CHINA’S ANTI-SPECULATORY HOUSING PURCHASE LIMIT POLICY XIAOYU CHEN, MATER OF PUBLIC POL

ESTIMATING THE LIMITED IMPACT OF CHINA’S ANTI-SPECULATORY HOUSING PURCHASE LIMIT POLICY XIAOYU CHEN, MATER OF PUBLIC POLICY PROGRAM, MICHIGAN STATE UNIVERSITY. ABSTRACT. CASES.

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ESTIMATING THE LIMITED IMPACT OF CHINA’S ANTI-SPECULATORY HOUSING PURCHASE LIMIT POLICY XIAOYU CHEN, MATER OF PUBLIC POL

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  1. ESTIMATING THE LIMITED IMPACT OF CHINA’S ANTI-SPECULATORY HOUSING PURCHASE LIMIT POLICY XIAOYU CHEN, MATER OF PUBLIC POLICY PROGRAM, MICHIGAN STATE UNIVERSITY ABSTRACT CASES Chinese housing prices have increased rapidly in the past 15 years. The high housing prices have been the hottest spot in Chinese society and the heaviest burden for those involved. The trend has caused the attention of the Chinese government. In order to suppress the trend Chinese government has implemented a series of policies among which Housing Purchase Limit Policy (HPLP) is the most controversial and the most aggressive. This paper will put forward two hypotheses about how HPLP will influence Chinese housing prices and provide evidences of four case cities with different HPLP (Hangzhou, Shenzhen, Changsha, and Chongqing) to support the hypotheses. HYPOTHESIS EVIDENCES Evidence 1 for Hypothesis 1: The slope of housing prices trend line after HPLP was implemented is much smaller than the slope before. Hypothesis 1: HPLP will stabilize the increasing rate of housing prices. HPLP will immediately reduce the demand generated by speculation. See graph 1, the demand Q will decrease to Q’ and price P will decrease to P’. However, in the long run, the housing price will increase again. One the one hand, the relatively low price will incentivize the rigid demand to buy houses so that the demand will increase again. On the other hand, the real estate companies will also reduce housing supply. K1=12.099 K1=3.48 K1=7.724 K2=-15.586 K2=1.436 K2=5.525 K3=3.695 K3=-0.221 K3=1.505 Evidence 2 for Hypothesis 1: When running a regression with the relative variables : Rate, Real Estate Rate, CPI, Population, GDP, Real Estate Index, putting HPLP as dummy, the outcome shows that HPLP is statistically significantly negative influence housing price P P S’ *population+*pgdp+*hplp+*CPI+*REIndex+*Rate+*RRate; Coef(hplp)=-.1053889; t=-14.42; P>|t|=0 S S P P’’ P P’ P’ Evidence 1 for Hypothesis 2: By introducing the new variable Hangzhou *HPLP, when running the regression of difference in difference between Hangzhou and Changsha, the outcome shows there is a significant difference between HPLP in Changsha and HPLP in Hangzhou. HPLP in Hangzhou is therefore more effective. D’’ D D’ D’ Q’ Q Q’’ Q’ Q Q Graph 1 Graph 2 D Evidence 2 for Hypothesis 2: By Separately running the regression of Hangzhou and Changsha, both of the HPLP negatively influence housing prices, however, the HPLP in Hangzhou is statistically significant while the HPLP in Changsha is not statistically significant. Hypothesis 2: More Aggressive Policy More effectively affects Housing Price HPLP varies in different places. The four cases which we chosen are HPLP in four cities with different aggressive level. Q CONCLUSION ACKNOWLEDGEMENT Josh Sapotichne, Assistant Professor, Ph.D. Valentina Bali, Associate Professor, Ph.D. Peilei Fan, Associate Professor, Ph.D. By statistically analyze the data, we can conclude that we fail to reject Hypothesis1 and Hypothesis 2. The Housing Purchase Limit Policy in China effectively reduced the increasing rate of housing prices in the short term. The HPLP varies in different cities, and the more aggressive policy is more effective. When HPLP is a public policy based on the strong administrative power of the Chinese government, it can only effectively negatively influence housing price in the short run. However, in the long run, HPLP cannot dismiss the rigid demand and the adjustment of real estate companies. In the certain situations, such as in 2011, HPLP is a good way to control housing prices. But to make Chinese real estate market well developed, other related policies and regulations are also needed.
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