收入结构与中国农户借贷约束研究

发布时间：2018-09-04 13:00

【摘要】：尽管在理论和实践上都表明金融发展和收入增长存在着相互影响的关系，但不可否认的是实现农村经济社会的发展稳定，关键在于促进增加农村居民人均可支配收入，进而通过跨期配置金融资源和分散风险来缓解预算约束。中国社会科学院农村发展研究所发布的报告显示，截至2012年底，中国的城市化率已达到51.27%，城镇人口第一次超过了农村人口，但是我国农业现代化的发展仍大大落后于工业化和城镇化的快速步伐，当下农业的国民经济基础地位仍不牢固，城市和乡村割裂的二元结构矛盾仍然突出，农村的发展仍然是中国特色新型工业化、信息化、城镇化、农业现代化“四化”同步协调发展的重点和难点。本文将采用微观计量方法深入研究农户收入结构对农户借贷约束的影响机理，并研究获得信用社的贷款证对农户借款满足率的影响，为优化农户收入结构、缓解借贷约束提出一些“言之有物”的对策建议，这对当下的农村金融改革具有一定的政策价值和实践意义。本文利用2009年“北大一花旗”中国农村金融调查数据，基于收入结构和农户借贷约束的分析框架，在进行描述性统计基础上，通过利用Logit模型分析不同收入结构对农户不同借贷约束是否有异质性影响和采用倾向得分匹配法克服样本选择偏误，实证研究了获得农村信用社的贷款证对农户借贷满足率的影响，经过分析得出以下结论：第一，工资性收入、农业生产和自营工商业收入比重越高的农户受到的借贷约束越小；相对于生产性借款来说，农户面临的非生产性借贷约束相对较高。第二，获得农村信用社的贷款证能提高农户借款满足率，，从而降低农户受到的借贷约束。为此，一方面需要国家大力促进增加农户可支配收入，特别是着力提高政府补助收入和财产性收入等收入在农户家庭纯收入中的比重，优化农户收入结构；另一方面，进行农村金融改革，通过增加网点数量等方式扩大农村金融机构覆盖面，增加农户金融产品和服务可及性。
[Abstract]:Although it is shown theoretically and practically that financial development and income growth are interacted, it is undeniable that the key to achieving the stability of rural economic and social development lies in promoting the increase of the per capita disposable income of rural residents. Furthermore, the budget constraints can be alleviated by the allocation of financial resources and the diversification of risks. According to a report released by the Institute of Rural Development of the Chinese Academy of Social Sciences, by the end of 2012, China's urbanization rate had reached 51.27 percent, with the urban population surpassing the rural population for the first time. However, the development of agricultural modernization in our country still lags behind the rapid pace of industrialization and urbanization, and the basic position of the national economy of agriculture is still not firm, and the contradiction between the dual structure of urban and rural areas is still prominent. The development of rural areas is still the focus and difficulty of the coordinated development of new industrialization, informatization, urbanization and agricultural modernization with Chinese characteristics. In order to optimize the income structure of farmers, this paper will deeply study the influence mechanism of farmers' income structure on farmers' borrowing constraints by using micro-econometric method, and study the influence of obtaining credit cooperatives' loan certificates on the rate of farmers' borrowing satisfaction. This paper puts forward some countermeasures and suggestions for easing the constraint of lending and lending, which has certain policy value and practical significance for the current rural financial reform. Based on the data of 2009 China Rural Finance Survey, based on income structure and farmers' lending constraints, this paper carries out descriptive statistics. By using Logit model to analyze the heterogeneity of different income structure on farmers' different lending constraints and to overcome the sample selection bias by using the tendency score matching method. This paper empirically studies the effect of obtaining the credit card of rural credit cooperatives on the rate of farmers' loan satisfaction, and draws the following conclusions: first, wage income, The higher proportion of agricultural production and self-employed industrial and commercial income, the smaller the lending constraints, and the higher the non-productive lending constraints compared with the productive loans. Second, obtaining the credit card of rural credit cooperatives can improve the rate of farmers' loan satisfaction, thus reducing the lending constraints to farmers. Therefore, on the one hand, it is necessary for the state to vigorously promote the increase of household disposable income, especially to increase the proportion of government subsidy income and property income in the household net income, and to optimize the structure of peasant household income, on the other hand, To carry out rural financial reform, expand the coverage of rural financial institutions by increasing the number of networks, and increase the accessibility of financial products and services to farmers.
【学位授予单位】：湘潭大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F323.8;F832.43

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