Summary:
The rapidly increasing leverage ratio of China's household sector has attracted more and more attention in recent years. It is of great practical significance to analyze the current household sector leverage ratio and what causes it to increase. This paper analyzes the leverage ratio and debt paying ability of Chinese households using data from household loans and a survey on urban depositors. It also empirically studies the reasons for the rapidly increasing household leverage ratio using the regional household sector leverage ratio, calculated via regional household loans. The data demonstrate the continual rapid growth of China's household leverage ratio, which was 60.5% in 2018. The ratio has remained well above the household leverage ratios of other emerging countries. The household leverage ratio in China is lower than that of major European and American countries, but higher than that of Japan and the euro area. The household leverage ratio in China is close to the international warning line of 65%. All previous big increases in China's household leverage ratio were driven by the increase in household housing loans, which is very common during housing market expansion. Furthermore, the household leverage ratio has prominent structural problems. From the debt purpose perspective, household debt mainly consists of housing loans. From the borrower perspective, the amount of one loan contract increases as the distribution of debt becomes centralized. From the perspective of debt paying ability, some low-income households and aged populations are under greater debt pressure. From the assets and liabilities perspective, the average asset liability ratio of urban depositors in China is approximately 10% and relatively stable. However, most of the household sector's assets are concentrated in real estate. Thus, the financial asset liability ratio of China's household sector is high, reaching 37.9% in 2018. This paper uses provincial household loan data to compute provincial household leverage ratio data and then applies the panel data model to analyze the causes of the rapidly increasing household leverage ratio. The main control variables of the model include financial development factors, population age structure, income level, social security expenditure, urbanization level and income inequality. It uses yearly data, ranging from 2007 to 2017. The results of the model show that rapid increases in housing market price and housing sales have significant positive effects on the household leverage ratio. Financial development level, the tool variable of credit availability, also has a positive effect on the household leverage ratio. Age structure has significant effects, the old-age dependency ratio has a positive effect and the adolescent dependency ratio has a negative effect on the household leverage ratio. The data analysis and empirical study results show that the rapid increase in China's household leverage ratio is related to the fast growth of household income, the improving availability of consumption credit and the age structure of the Chinese population. They also indicate that the ratio is reasonable to some extent. However, some problems remain and require further attention, such as the uneven distribution of household leverage and the great debt pressure of some low-income households and aged populations. This paper raises four policy suggestions. First, in view of the currently uneven regional distribution of the household sector leverage ratio, it should be stabilized at the city level, not the national level. Second, housing market prices should be stabilized to prevent debt and housing loans from increasing. Third, government investment in social security should be increased to improve the debt-paying ability of low-income households and aged populations. Fourth, the management of personal loan insurance should be strengthened to ensure that borrowers' debt does not exceed their debt-paying ability. This paper's main contribution lies in its expansion of household sector leverage ratio research through the use of provincial rather than national data. Future research should further investigate the microeconomic mechanism underlying the macro household leverage ratio.
阮健弘, 刘西, 叶欢. 我国居民杠杆率现状及影响因素研究[J]. 金融研究, 2020, 482(8): 18-33.
RUAN Jianhong, LIU Xi, YE Huan. A Study on the Current Situation and Influencing Factors of the Household Leverage Ratio in China. Journal of Financial Research, 2020, 482(8): 18-33.
[1]郭新华、陈斌和伍再华,2015,《中国人口结构变化与家庭债务增长关系的实证考察》,《统计与决策》第4期,第96~99页。 [2]郭新华、赵醒和伍再华,2017,《中国省际区域家庭债务的空间关联及其解释》,《统计与决策》第17期,第96~100页。 [3]郭新华和李晓敏,2019,《中国家庭债务与房价之间的自增强效应——基于全面FGLS回归和分位数回归的实证分析》,《湘潭大学学报(哲学社会科学版)》第43卷第3期,第94~100页。 [4]李涛、王志芳和王海港等,2010,《中国城市居民的金融受排斥状况研究》,《经济研究》第7期,第15~30页。 [5]李扬、张晓晶和常欣等,2015,《中国国家资产负债表2015——杠杆调整与风险管理》,中国社会科学出版社,2015年8月第一版。 [6]刘向耘、牛慕鸿和杨娉,2009,《中国居民资产负债表分析》,《金融研究》第10期,第107~117页。 [7]孙丹和李宏瑾,2017,《居民杠杆率、房地产信贷与房价泡沫风险》,《金融发展评论》第1期,第30~41页。 [8]汪伟和艾春荣,2015,《人口老龄化与中国储蓄率的动态演化》,《管理世界》第6期,第47~62页。 [9]伍再华和张雄,2016,《城镇化视角下收入不平等与家庭债务变动——来自中国30个省市的数据》,《经济与管理》第3期,第39~45页。 [10]伍再华、叶菁菁和郭新华,2017,《收入不平等、社会保障支出与家庭借贷行为——基于CFPS 数据的经验分析》,《财经科学》第12期,第55~68页。 [11]杨朝军、王渊和周仕盈,2018,《我国居民部门资产结构是理性的吗?——基于现代资产组合理论的研究视角》,《上海交通大学学报(哲学社会科学版)》第26卷第1期,第63~73页。 [12]张荣霞、何影和史晓丹,2013,《民生类政府财政支出对居民消费影响的研究》,《软科学》第11期,第11~16页。 [13]周广肃和王雅琦,2019,《住房价格、房屋购买与中国家庭杠杆率》,《金融研究》第6期,第1~19页。 [14]Ando, A. and Modigliani, F., 1963,“The ‘Life Cycle’ Hypothesis of Saving: Aggregate implications and Tests”, American Economic Review, Vol. 53, No.1, Part 1(Mar 1963), pp.55–84. [15]Almeida, H., M. Campello and C. Liu, 2006, “The Financial Accelerator: Evidence from International Housing Markets”, Review of Finance, 10(3):321~352. [16]Aron, J.and J. Muellbauer, 2000, “Financial Liberalisation, Consumption and Debt in South Africa”, CSAE Working Paper Series, No.29(4):132~6. [17]Athreya, K., J. M. Sánchez, X. S. Tam and E. R. Young, 2016, “Bankruptcy and Delinquency in a Model of Unsecured Debt”, Federal Reserve Bank of St. Louis Research Division Working Paper, No.2012-042F. [18]Bernanke, B, M. Gertler and S. Gilchrist, 1996, “The Financial Accelerator and the Flight to Quality”, The Review of Economics and Statistics, 78(1):1~15. [19]Debelle, G., 2004, “Macroeconomic Implications of Rising Household Debt”, BIS Working Papers, No.153. [20]Guerrieri, V. and G. Lorenzoni, 2017, “Credit Crises, Precautionary Savings, and The Liquidity Trap”, The Quarterly Journal of Economics, 132(3):1427~1467. [21]Iacoviello, M., 2008, “Household Debt and Income Inequality, 1963-2003”, Journal of Money, Credit and Banking, 40(5):929~965. [22]Jacobsen, D. H. and B. E. Naug, 2004, “What Influences the Growth of Household Debt?”, Economic Bulletin, 3(3):191~201. [23]Oikarinen, E., 2009, “Interaction Between Housing Prices and Household Borrowing: The Finnish Case”, Journal of Banking and Finance, 33(4): 747~756. [24]Rajan, R.G., 2011, Fault Lines: How Hidden Fractures Still Threaten the World Economy, Published by Princeton University Press. [25]Sánchez, J. M., 2018, “The Information Technology Revolution and the Unsecured Credit Market”, Economic Inquiry, 56(2):914~930. [26]Sinai, T. and N. S. Souleles, 2005, “Owner-Occupied Housing as a Hedge against Rent”, Quarterly Journal of Economics, 120(2):763~789. [27]Tobin, James, 1971, “Wealth, Liquidity, and the Propensity to Consume”, Cowles Foundation Discussion Papers314, Cowles Foundation for Research in Economics, Yale University.