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金融研究  2021, Vol. 497 Issue (11): 79-96    
  本期目录 | 过刊浏览 | 高级检索 |
收入差距、信贷约束与房价变动
陈金至, 温兴春, 宋鹭
南京审计大学政府审计学院,江苏南京 211815;
对外经济贸易大学金融学院,北京 100029;
中国人民大学国家发展与战略研究院,北京 100872
Income Gaps, Credit Constraints, and House Price Fluctuations
CHEN Jinzhi, WEN Xingchun, SONG Lu
School of Government Audit, Nanjing Audit University;
School of Banking and Finance, University of International Business and Economics;
National Academy of Development and Strategy, Renmin University of China
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摘要 本文通过构建一个异质性代理人模型,刻画了收入差距通过信贷渠道影响房价的作用机制。研究表明,收入差距的缩小提升了低收入者的收入占比,使该类人群获得了更多的外部融资进行购房,由此产生了两方面效应:(1)信贷约束放松降低了住房流动性溢价,从而对房价产生负向影响;(2)收入上涨增加了住房边际效用较高的低收入者对房价正向影响的权重,从而使住房需求上升的效应抵消了此前的负向影响,最终促进房价上涨。通过对1970-2017年44个国家的进一步分析发现,相比于高收入者收入的下降,低收入者收入占比的上升在放松信贷约束和提升房价方面具有更显著的作用。据此本文认为:一方面要通过增加住房供给来化解城市化率提升与高房价之间的内在矛盾;另一方面,在经济增速放缓的时期,缩小收入差距,推动以“人”为核心的高质量城市化,并引导信贷资源向低收入群体倾斜是当前促进国内大循环、稳定社会融资规模和房地产市场的重要手段。
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陈金至
温兴春
宋鹭
关键词:  收入差距  信贷约束  房价  异质性代理人模型    
Summary:  Income gaps, credit constraints, and housing prices are long-established and prominent topics of social concern. International Monetary Fund (IMF) figures from September 2020 report a record high global real house price index of 167.26 (using the first quarter of 2000 as the base period). The data show a rising trend in 47 of the 63 sampled countries and regions. Furthermore, since the U.S. subprime mortgage crisis, many scholars have investigated the potential relationships between income gaps and credit constraints. Numerous papers show that relaxation of credit constraints contributes significantly to rising house prices. Although this finding raises a natural question of how income gaps influence house prices through credit channels, this question is rarely mentioned in the literature.
Theoretically, because different income groups have different housing demands, changes in income distribution should significantly affect house prices through the amplification effect of credit leverage. Therefore, this paper aims to establish a general framework to interpret house price changes through the channel of income gaps affecting credit constraints. It shows that income gaps, credit constraints, and house prices are closely related. Specifically, an income gap reduction improves the relative income levels of low-income groups, which relaxes their credit constraints for house purchases. The relaxation of credit constraints makes the (aggregate) housing liquidity premium decrease. However, low-income groups have higher housing marginal utility, and access to external financing increases the housing market weight of low-income groups that have rising incomes. Thus, relaxation of credit constraints raises the housing marginal utility for society as a whole, which offsets the negative impact that liquidity premium decreases have on house prices, and ultimately increases house prices overall. This paper's findings are further supported by empirical analysis of cross-country panel data, which shows that the rising share of income going to low-income groups has significantly stronger effects on credit constraints and house prices than does growth in the incomes of high-income groups.
This paper makes three main contributions. First, existing explanations of the effects of income gaps on housing prices are mainly based on static analyses; because our model introduces the effects of credit constraints, this paper incorporates dynamic characteristics. Second, previous studies often use representative agent models to investigate the relationships between credit constraints and house prices. This paper enriches the research dimension by including analysis of heterogeneous agents. Third, the literature mainly studies the relationships between income gaps and house prices directly from the empirical level but does not conduct in-depth analysis of the transmission mechanism. In contrast, the construction of this paper's heterogeneous agent model enables a clear description of the transmission mechanisms between income gaps, credit constraints, and house prices. Importantly for policy makers, our results provide new insights into the factors that cause house prices to rise.
Finally, this paper has real-world importance. At present, China's real estate market trends are different in first-and second-tier cities than they are in third-and fourth-tier cities. CREIS data show approximately 10% growth in the land supply and transaction volumes of China's first-and second-tier cities in 2020. In contrast, the data show the land supply and transaction volumes of China's third-and fourth-tier cities decreasing by half in the same year. China's real estate market is deeply tied with bank credit, government revenue, and social investment. If the market encounters a sudden and severe decline, it will inevitably lead to serious systemic financial risks. As far as the current situation is concerned, the proposal of “six priorities and stability in six areas” shows the Chinese central government's concern about the population's livelihood, employment, financial stability, and investment expectations. Narrowing the income gap is itself an important means to protect the basic population's livelihood. This paper shows the further importance of narrowing the income gap to expand the scale of society's use of financing, prevent house prices from collapsing, and stabilize investment expectations. With particular relevance to the “Gray Rhino” real estate market, which is characterized by slowing economic growth and exhaustion of land resources, mechanisms should be considered to prevent the systemic financial risks caused by a “hard landing” of the real estate market. Management of the real economic function of the real estate industry is particularly important at present because the industry has the characteristics of large-scale, long industrial chains, growing employment, and increasing fiscal contributions. Relative to some short-term policies, more analysis should be applied to the basic aspects of income distribution and its influence on the domestic market and the domestic economic cycle.
Keywords:  Income Gap    Credit Constraints    House Price    Heterogeneous Agent Model
JEL分类号:  E10   E25   R31  
基金资助: * 本文感谢国家社会科学基金重大项目(20&ZD118)、国家自然科学基金面上项目(71873134)、国家自然科学基金青年项目(72103037)的资助。感谢匿名审稿人的宝贵意见,文责自负。
通讯作者:  宋 鹭,经济学博士,研究员,中国人民大学国家发展与战略研究院,E-mail:songlu@ruc.edu.cn.   
作者简介:  陈金至,经济学博士,讲师,南京审计大学政府审计学院,E-mail:freeman_eco@126.com.
温兴春,经济学博士,讲师,对外经济贸易大学金融学院,E-mail:wenxingchun2020@163.com.
引用本文:    
陈金至, 温兴春, 宋鹭. 收入差距、信贷约束与房价变动[J]. 金融研究, 2021, 497(11): 79-96.
CHEN Jinzhi, WEN Xingchun, SONG Lu. Income Gaps, Credit Constraints, and House Price Fluctuations. Journal of Financial Research, 2021, 497(11): 79-96.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2021/V497/I11/79
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