Analysis by regions

Liang and Gao (2007) have divided China’s 29 provinces into three regions by per capita GDP, among which the region with per capita GDP of more than RMB 20,000 is the eastern region, between RMB 12,000 to 20,000 is the middle region, and below RMB 12,000 is the western region. Based on this division method and geographic distribution, we made some slight adjustments of the regions that several provinces belong to. The dividing regions of each province are as follows (see map of China6 _{below). Eastern region contains 11 provinces and} cities. They are Beijing, Fujian, Guangdong, Hebei, Hainan, Jiangsu, Liaoning, Shandong, Shanghai, Tianjin and Zhejiang. Western region includes 11 provinces which consist of Inner Mongolia, Guangxi, Chongqing, Sichuan, Guizhou, Yunnan, Shaanxi, Gansu, Qinghai, Ningxia and Xinjiang. Anhui, Hubei, Heilongjiang, Henan, Hunan, Jilin, Jiangxi and Shanxi provinces constitute the middle region. Generally speaking, the house price distribution of Chinese provinces presents great differences: the eastern region’s is higher than the middle and western regions’. Therefore, this chapter will further analyze the influences that entrepreneurs’ confidence on house prices based on divided regions.

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We make estimation with fixed effect model in the regression analysis of divided regions. As shown in Table 3.6, Entrepreneur Confidence Index significantly influences house prices in the eastern and middle regions, When Entrepreneur Confidence Index increases by one percentage point in both eastern and middle regions of China, the corresponding house price increases by 0.65 and 0.68 percentage points respectively, while the influence is not so significant in the western region. This indicates that influences of entrepreneurs’ confidence on house prices will be constrained by local economic development levels. Entrepreneurs’ confidence will have a more significant influence on house prices with a higher economic development level and faster market process.

Besides, per capita GDP is the main factor that influences the house prices of the middle and western regions, but its impact on the eastern region is not remarkable, conforming to the conclusion of Li and Chand (2013). Li and Chand (2013) deemed the possible reason for this was that eastern region’s developed economy, large numbers of population migration and the relatively deficient land resources made supply factors like lands and construction costs play a more important role in the formation of house prices, whereas the influence of demand factors like per capita incomes was relatively weakened. This analysis is markedly different in comparison with the mentioned reason when Wang et al. (2014) explained why the explanatory ability of fundamentals for house prices is weaker in eastern cities, which (with a non-empirical analysis) held that inelastic urban housing supply would lead to the increase of the influence on housing premiums caused by the growth of population and income. This chapter holds that costs influence house prices significantly in the eastern region, and meanwhile, investment expectation also plays a part that cannot be neglected in developed regions. The high return expectation of asset investments will hasten more investment demands or produce more potential risks. For example, Wu et al. (2012) estimated that after experiencing the boom from 2007 to 2010, “even modest declines in expected appreciation would lead to large price decline of over 40% in market such as Beijing, absent offsetting rent increase or other countervailing factors” (p531).

There are two channels may provide further evidence for the judgment that the more developed market may be accompanied by a more intensive psychological impact. One piece of evidence is from stock market. By studied six stock markets: Canada, France, Germany, Japan, the United Kingdom, and the United States, Baker et al. (2012) noted that United States’ total

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sentiment index “receives the highest loading in the global index” because it is “widely considered the world’s bellwether market” (p278). Another piece of evidence comes from the volatility of China’s market house prices, which are important indicators of market sentiment. As shown in Figure 3.2, volatile degree is basically in accordance with the level of development, namely more developed province endured more severe fluctuation. There is only one exception province, Hainan, which is a relatively low developed eastern province but suffered number 4 volatility in the Figure. That is because Hainan is a famous tourist destination, and there are lots of property purchases for investment purposes. Investments are more likely to be affected by sentiment.

Table 3.6: Regression results of divided regions (explained variable: lnprice)

Eastern Western Middle

Variables FE FE FE lnindex 0.6497** -0.0577 0.6834*** (0.2918) (0.2408) (0.2164) lnrgdp_pop 0.2262 0.4464** 0.5002** (0.2100) (0.1862) (0.1981) lnconstruct 0.3297*** 0.4243*** 0.6103*** (0.1226) (0.1100) (0.1070) lnland_cost 0.1082*** 0.0524* 0.0513 (0.0380) (0.0294) (0.0501) lnfi -0.0326* 0.0028 -0.0066 (0.0182) (0.0082) (0.0083) lnurban -0.1777 0.6923*** 0.0022 (0.1641) (0.1661) (0.1688) lnunmarried 0.1478 0.1068 -0.0689 (0.1445) (0.1293) (0.1378) lninterest -0.1638 0.0007 -0.1499 (0.1853) (0.1435) (0.1217) year2008 0.2355*** -0.0224 0.0923** (0.0575) (0.0450) (0.0389) constant -0.3811 -2.4994* -4.5945** (2.1273) (1.4209) (1.7568)

Province Fixed Effecy Yes Yes Yes

F-test 11.80*** 8.78*** 6.41***

Observations 99 99 72

R-squared 0.8822 0.8838 0.9426

Note：*significance level is 10%; **significance level is 5%; ***significance level is 1%. FE: fixed effect

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The dummy variable of 2008 was also a factor that had significantly affected house prices of the eastern and middle regions, while the influence on the western region was not that striking, the reason for which might be that the eastern and middle regions were most affected by financial crisis and the government bailout was focused on the eastern and middle regions.