金融

Vol.6 No.4 (October 2016)

中国城市不动产价格泡沫之比较探讨
China’s Housing Bubbles and the Driving Factors—A Comparison of Three Cities

 

作者:

黄 斐 , 林左裕 :政治大学,台湾 台北

 

关键词:

不动产价格泡沫基本价值资本还原率 Housing Bubble Fundamental Value Capitalization Rate

 

摘要:

在中国大陆贷款利率及不动产相关税负长期偏低之下,住宅产品的投资需求不断上升,使得房价一路高涨。截至2010年,中国大陆推出一系列以抑制房价为主要目的的宏观调控政策。由于中国大陆地幅辽阔,各地的不动产市场因受各种因素影响而发展各异,因此本文选择了北京、上海、广州三个具区域发展代表性的重点城市作为研究对象。本文以基本价值与市场价格间的差距作为泡沫程度的估计,计算这三个城市2007年至2012年的房价泡沫情况。藉由这三个城市的不动产市场泡沫情况,通过共整合分析来探讨中国城市不动产价格泡沫的影响因素。实证结果显示,人均可支配收入、金融机构各项信贷总额都与不动产价格泡沫具有正向关系,不动产价格泡沫则对其本身具有负面影响,而抵押贷款利率与不动产价格泡沫先是正向而后转为负向的关系。研究结果建议政府在针对不同城市之房价泡沫处理上,宜针对城市的特性对症下药,方可能得到预期的政策效果。

The long-term low interest rates for mortgages and the real estate related taxes in China conti-nuously encouraged the investment demand for housing products, and consequently resulted in high housing prices. Chinese government launched a series of housing regulation to dampen the over-heating real estate market since 2010. Given that China has a vast territory of great variety, the impact of these policy tools on different local real estate markets may vary. The purpose of this study aims to explore the real estate bubbles and the determinants in Beijing, Shanghai and Guangzhou. We measured the housing bubbles in these cities from 2007 to 2012 by comparing the fundamental values with market prices. Based on the estimated housing bubbles, we then applied the Cointegration analysis to further explore the factors contributing to the housing bubbles in three cities. The empirical results show that disposable income and total mortgage loans of financial institutions are positively related to China’s housing bubbles. In addition, the impact of loan interest on housing bubbles was positive first and then turns negative with respect to the magni-tude of increasing rates. Results of this study suggest that macro policy tools to curb bubbles should consider different characteristics of cities for plausible policy results.

文章引用:

黄 斐 , 林左裕 (2016) 中国城市不动产价格泡沫之比较探讨 。 金融, 6, 130-147. doi: 10.12677/FIN.2016.64014

 

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