Practical Study Of Elasticity Of Housing Demand In Shanghai

Since 1999, Shanghai housing market has experienced high-speed development more than 10 years. The financial crisis in 2008 created a tragedy to our national housing market; however, Shanghai housing market was outstanding. New high-price has always been born. Basing on data from CRIC, the average price in 2007 increased 7.53% compared with the previous year, at 9,262 yuan/m2, and the transaction area was 32,577,990m2, increasing 31.26% more than last year; it was the first time in 2008 that Shanghai housing market reached 10.000- yuan/m2-level, at 10,181 yuan/m2, increasing 9.93% comparing than previous year. But influenced by financial crisis, transaction area decreased at 38.37%. However, Shanghai housing market revived quickly after crisis. The average price got 12,647 yuan/m2, comparing than last year, which created a historical level. Besides, the transaction area reached 61.84%. All in all, Shanghai housing market has realized a quick-jumping increase.Because of the increasingly high price, the government operated series of policies to eliminate bubbles that were created by speculation. Even so, passion still stayed at the market. The average price increased 30%2 compared than previous. Besides, data from CRIC shows that transaction area of Shanghai housing market was 2,147,070 m2, increasing 24.41% comparing than previous year. The paper discusses why the price increased but the demand was still hot at this market basing on inner rules of real estate market, as well as, on the condition that the increasing price, the situation of the separate area was different, and the area trait was obvious.Basing on elasticity theory, the paper made use of the practical methods starting with the present situation. Importantly, the paper set a model to calculate elasticity of price and income of demand of Shanghai and her preventative districts. On calculation of price elasticity of demand of Shanghai real estate, the paper used OLS; on calculation of income elasticity of demand, pool data model is used. Considering the data resource, Xuhui District, Minhang District, Baoshan District, Qingpu District and Fengxian District were selected. Conclusions were got as follows:first, the elasticity of demand of Shanghai real estate market was lack. The price elasticity and income elasticity are 0.901 and 0.676 separately. Specially, the price elasticity of demand is positive showing that wealth effect is higher than budget constraint effect created by increased price. Meanwhile, this market contains speculation; second, the price elasticity of Xuhui District, Minhang District, Baoshan District, Qingpu District and Fengxian District are 0.475,3.304,2.044,-3.162,-1.031 separately, and income elasticity are 0.237,1.113,1.252,1.080,1.006 separately; third, the price elasticity of demand shows obvious area trait:the central district is lack of elasticity, but the suburbs are rich of elasticity. Importantly, the elasticity of central and close-to-town suburb is positive, compared with far-to-town suburb. However, the income elasticity of demand shows less area trait:the central area is lack of elasticity, but the suburbs are rich of elasticity, which the numerical values are similar. Besides, to understand the market quite well, this paper considered the total residents income, total Shanghai real estate price and people from out of Shanghai into the model, I got some very interesting results.According to the practical conclusions, the paper gives 5 suggestions:first, the government ought to satisfy people's housing demand; second, taxes transformation should be paid attention to stop price turning higher; third, different policies should be made basing on the different areas; four, the government should continue to operate Purchase Restriction Order to make the price stable; five, the government may decrease personal income tax at the propose of increasing people's income. Besides with introduction and literatures, the paper also contains five parts:first, making a general analysis of traits of real estate and its market; second, making an analysis of present situation of Shanghai real estate market; third, using OLS to calculate the price elasticity and income elasticity; four, using pool data model to calculate price elasticity and income elasticity of representative districts; five, making conclusions and policy suggestions.