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Journal of Integrative Agriculture  2021, Vol. 20 Issue (9): 2552-2568    DOI: 10.1016/S2095-3119(20)63557-2
Special Issue: 农业经济与管理合辑Agricultural Economics and Management
Agricultural Economics and Management Advanced Online Publication | Current Issue | Archive | Adv Search |
Do credit constraints affect households’ economic vulnerability? Empirical evidence from rural China
PENG Yan-ling1, Yanjun REN2, LI Hou-jian1  
1 College of Economics, Sichuan Agricultural University, Chengdu 611130, P.R.China
2 Department of Agricultural Markets, Leibniz Institute of Agricultural Development in Transition Economies, Halle (Saale) 06120, Germany
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减贫仍然是发展中国家面临的主要挑战之一,在中国这样一个转型经济体中这一问题表现得尤为突出。基于反贫困的视角,文章利用2014年中国农村家庭收入调查 (CHIPs) 的数据,探讨和检验了正规信贷约束和非正规信贷约束对农户家庭经济脆弱性的影响。在有序probit模型的基础上运用控制函数方法纠正信贷约束的潜在内生性问题。研究结果显示,正规信贷约束和非正规信贷约束对农村家庭经济脆弱性具有稳健的显著积极影响,并且相对于非正规信贷约束而言,正规信贷约束的积极影响更大。进一步地,文章运用似不相关回归识别了信贷约束影响农村家庭经济脆弱性的作用机制。我们发现健康、信任、人均金融资产水平以及人均收入水平在信贷约束对农户家庭经济脆弱性的影响中发挥部分中介作用。其中,健康和人均收入水平发挥了主要的中介作用。据此,政策制定者应从金融供给侧和需求侧着手来提高农户信贷可得性以降低农户家庭经济脆弱性,特别地,政策制定者亦可通过提升农村居民健康水平和人均收入水平以达到降低农户家庭经济脆弱性之目的

Poverty alleviation is still one of the major challenges in developing countries, especially in transitional economy like China.  From the perspective of anti-poverty, this paper examines the impact of formal credit constraints (FCCs) and informal credit constraints (IFCCs) on economic vulnerability (EV) using the data from the China Household Income Project (CHIP) survey for 2013 (CHIPs 2013) of rural households.  The potential endogeneity problem of credit constraints (CCs) is addressed by applying the control function approach within an ordered probit model.  The results show that both FCCs and IFCCs have a robust positive and significant impact on the EV of rural households and that the impact of FCCs is greater than that of IFCCs.  To identify the potential mechanisms through which CCs affect EV, the seemingly unrelated regressions are used and the potential intercorrelation among these mechanisms is examined.  We find that the impact of CCs on EV is partly mediated by health, trust, per capita financial assets and per capita income, whereby health and per capita income contribute to most of the total indirect effect.  Thus, policies focus on supply-side and demand-side to improve credit accessibility could reduce rural households’ EV, especially through its positive effect on health and per capita income.
Keywords:  credit constraints        economic vulnerability       causal mediation mechanisms        rural China  
Received: 07 April 2020   Accepted:
Fund: This research was funded by the National Natural Science Foundation of China (71903141 and 71661147001), the National Social Science Fund of China (20AJY011), the Humanities and Social Sciences of Ministry of Education  of China (18YJC790125), and the China Postdoctoral Science Foundation (2019M653834XB).  This research uses data from CHIPs 2013.  All errors are
Corresponding Authors:  Correspondence LI Hou-jian, E-mail:   
About author:  PENG Yan-ling, E-mail:;

Cite this article: 

PENG Yan-ling, Yanjun REN, LI Hou-jian. 2021. Do credit constraints affect households’ economic vulnerability? Empirical evidence from rural China. Journal of Integrative Agriculture, 20(9): 2552-2568.

Ali D A, Deininger K, Duponchel M. 2014. Credit constraints, agricultural productivity, and rural nonfarm participation: Evidence from Rwanda. The World Bank.
Azam M S, Imai K S. 2009. Vulnerability and poverty in Bangladesh. School of Economics Discussion Paper. University of Manchester, Manchester, UK.
Bhuiyan M F, Ivlevs A. 2019. Micro-entrepreneurship and subjective well-being: Evidence from rural Bangladesh. Journal of Business Venturing, 34, 625–645.
Boucher S R, Carter M R, Guirkinger C. 2008. Risk rationing and wealth effects in credit markets: Theory and implications for agricultural development. American Journal of Agricultural Economics, 90, 409–423.
Briguglio L. 1995. Small island developing states and their economic vulnerability. World Development, 23,1615–1632.
Briguglio L, Cordina G, Farrugia N, Vella S. 2009. Economic vulnerability and resilience: Concepts and measurements. Oxford Development Studies, 37, 229–247.
Chaudhuri S, Jalan J, Suryahadi A. 2003. Assessing household vulnerability to poverty from cross-sectional data: A methodology and estimates from Indonesia. Working Paper. Columbia University, New York.
Chetty R, Stepner M, Abraham S. 2016. The association between income and life expectancy in the United States 2001–2004. The Journal of American Medical Association, 315, 1750–1766.
Collins D, Rutherford J, Rutherford S, Ruthven O. 2009. Portfolios of the Poor: How the World’s Poor Live on $2 a Day. Princeton University Press, USA.
Cutter S  L, Boruff B J, Shirley W L. 2003. Social vulnerability to environmental hazards. Social Science Quarterly, 84, 242–261.
Dercon S, Hoddinott J, Woldehanna T. 2005. Shocks and consumption in 15 Ethiopian villages, 1999–2004. Journal of African Economies, 14, 559–585.
Do X L, Siegfried B. 2016. Does credit access affect household income homogeneously across different groups of credit recipients? Evidence from rural Vietnam. Journal of Rural Studies, 47, 186–203.
Fang Y, Zou W. 2013. Ability investment, health shock, and poverty vulnerability. Economic Perspectives, 7, 36–50.
Fischer E, Qaim M. 2012. Linking smallholders to markets: Determinants and impacts of farmer collective action in Kenya. World Development, 40, 1255–1268.
Gaiha R, Imai K. 2008. Measuring vulnerability and poverty estimates for rural India. Working Paper. United Nations University, World Institute for Development Economics Research, Helsinki, Finland.
Gilligan D, Harrower S, Quisumbing A. 2005. How accurate are reports of credit constraints. Reconciling theory with respondents’ claim in Bukidnon, Philippines. Basis Collaborative Research Support Program Working Paper. University of Wisconsin-Madison, USA.
Glewwe P, Hall G. 1998. Are some groups more vulnerable to macroeconomic shocks than others? Hypothesis tests based on panel data from Peru. Journal of Development Economics, 56, 181–206.
Greene W H. 2012. Econometric Analysis. 7th ed. Upper Saddle River, Prentice Hall, NJ.
Guirkinger C. 2008. Understanding the coexistence of formal and informal credit markets in Piura, Peru. World Development, 36, 1436–1452.
Hoddinott J, Quisumbing A. 2003. Methods for micro-econometric risk and vulnerability assessments. The World Bank Social Protection Discussion Papers. Washington, DC. pp. 1–53.
Huang X. 2013. To what extent the health cause of poverty vulnerability. Statistics & Information Forum, 28, 54–62.
Huong N, Yao S, Fahad S. 2019. Assessing household livelihood vulnerability to climate change: The case of Northwest Vietnam. Human and Ecological Risk Assessment: An International Journal, 25, 1–15.
Imbens G, Wooldridge J. 2007. Control function and related methods. NBER Working Papers (Summer Lecture Ser. 6). National Bureau of Economic Research, Cambridge.
Jha R, Kang W, Nagarajan H K, Pradhan C K. 2012. Vulnerability as expected poverty in rural India. ASARC Working Paper. Australia South Asia Research Centre, Australian National University. Australia.
Jia X, Heidhues F, Zeller M. 2010. Credit rationing of rural households in China. Agricultural Finance Review, 70, 37–54.
Kamanou G, Morduch J. 2002. Measuring vulnerability to poverty. NYU Wagner Working Paper, No. WP1012. pp. 1–36.
Khandker S. R, Faruqee R. 2015. The impact of farm credit in Pakistan. Agricultural Economics, 28, 197–213.
Krishnan P, Patnam M. 2013. Neighbours and extension agents in Ethiopia: Who matters more for technology adoption? American Journal of Agricultural Economics, 96, 308–327.
Kumar C S, Turvey C G, Kropp J D. 2013. The impact of credit constraints on farm households: Survey results from India and China. Applied Economic Perspectives and Policy, 35, 508–527.
Ligon E, Schechter L. 2003. Measuring vulnerability. The Economic Journal, 486, 95–102.
Li C, Lin L, Gan C E C. 2016. China credit constraints and rural households’ consumption expenditure. Finance Research Letters, 19, 158–164.
Li Q H, Li R, Wang S G. 2012. The credit rationing of Chinese rural households and its welfare loss. Journal of Quantitative & Technical Economics, 8, 35–48. (in Chinese)
Li R, Li Q, Huang S, Zhu X. 2013. The credit rationing of Chinese rural households and its welfare loss: An investigation based on panel data. China Economic Review, 26, 17–27.
Li R, Zhu X. 2010. Econometric analysis of credit constraints of Chinese rural households and welfare loss. Applied Economics, 42, 1615–1625.
Li X, Dong Q, Rao X, Zhao L. 2007. Approach and application of rural household’s vulnerability. Chinese Rural Economy, 4, 32–39. (in Chinese)
Liao C, Fei D. 2019. Poverty reduction through photovoltaic-based development intervention in China: Potentials and constraints. World Development, 122, 1–10.
Long S J.1997. Regression models for categorical and limited dependent variables. Advanced Quantitative Techniques in the Social Sciences. SAGE Publications, USA. p. 7.
Lusardi A, Mitchell O S. 2014.The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52, 5–44.
Lyons A, Grable J, Zeng T. 2017. Impacts of financial literacy on loan demand of financially excluded households in China. ADBI Working Papers 923. Asian Development Bank Institute, Tokyo.
Magnan N, Spielman D J, Lybbert T  J, Gulati K. 2015. Levelling with friends: Social networks and Indian farmers’ demand for a technology with heterogeneous benefits. Journal of Development Economics, 116, 223–251.
Moore J D, Donaldson J A. 2016. Human-scale economics: Economic growth and poverty reduction in north-eastern Thailand. World Development, 85, 1–15.
Morduch J, Haley B. 2002. Analysis of the effects of microfinance on poverty reduction. NYU Wagner Working Paper. New York. pp. 10–14.
Moser C.1998. The asset vulnerability framework: Reassessing urban poverty reduction strategies. World Development, 26, 1–19.
Nasri A, Zhang L. 2019. Multi-level urban form and commuting mode share in rail station areas across the United States: A seemingly unrelated regression approach. Transport Policy, 81, 311–319.
Ogutu S O, Qaim M. 2019. Commercialization of the small farm sector and multidimensional poverty. World Development, 114, 281–293.
Peng G, Liu F, Lu W, Liao K, Tang C, Zhu L. 2018. A spatial-temporal analysis of financial literacy in United States of America. Finance Research Letters, 26, 56–62.
Stiglitz J E, Weiss A. 1981. Credit rationing in markets with imperfect information. American Economic Review, 71, 393–410.
Su L, Kong R. 2018. Does farmland mortgaging promote farmer’s entrepreneurial decisions? China Soft Science, 12, 140–156. (in Chinese)
Thang T V. 2018. Household vulnerability as expected poverty in Vietnam. World Development Perspectives, 10–12, 1–14.
Turvey C G, Kong R. 2010. Informal lending amongst friends and relatives: Can microcredit compete in rural China? China Economic Review, 21, 544–556.
Verkaart S, Munyua B G, Mausch K, Michler J D. 2017. Welfare impacts of improved chickpea adoption: A pathway for rural development in Ethiopia? Food Policy, 66, 50–61.
Wooldridge J M. 2015. Control function methods in applied econometrics. Journal of Human Resources, 50, 420–445.
World Bank.1990. Vietnam Development Report 1990: Poverty. Technical Report. PUB8507. World Bank.
Xiao S. 2019. Research on rural health poverty alleviation in the context of precision poverty alleviation policy in China. MSc thesis, Nanjing University, Nanjing. p. 5. (in Chinese)
Xing C, Li X. 2019. On targeted poverty alleviation in Ethnic region from the perspective of structural poverty. Journal of Minzu University of China (Philosophy and Social Sciences Edition), 46, 99–112. (in Chinese)
Yang L, Li M, Wang S. 2018. Does poor-village mutual fund reduce household vulnerability? Journal of Agrotechnical Economics, 6, 57–70. (in Chinese)
Yang W, Sun B, Wang X. 2012. Measurement and decomposition of household’s vulnerability in rural China. Economic Research Journal, 4, 40–51. (in Chinese)
Zhang J, Zhu W, Wang Y. 2016. On the relation between economic vulnerability and household’ consumption. Economic Perspectives, 8, 126–135.
Zhao J M, Peter J B. 2014. Effects of credit constraints on rural household technical efficiency: Evidence from a city in northern China. China Agricultural Economic Review, 6, 654–668.
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