Abstract:
This paper proposes a method based on heterogeneous stochastic frontier model with the data of bank outlets to quantitatively identify rural credit supply inefficiency. On this basis and by using the survey data of “Shanghai University of Finance and Economics Thousand Villages Survey”, we classify the samples according to the possibility of supply-type or demand-based credit suppression in a certain area, and empirically study the effects of Credit Inhibition Type on the effectiveness of rural credit support policies. Our empirical results show that, the main reason that restrains credit activities in rural China is the demand-based credit suppression caused by the risk. The credit inhibition type can significantly affect the effectiveness of rural credit support policies. In order to improve the effectiveness of credit support policy in the supply-based credit suppression regions, it is necessary to increase the credit availability by increasing the banking network density, while reducing lending rates or increasing bank tolerance for loan risk may not be desirable. However, reducing lending rates and increasing bank risk tolenrance is very effective in boosting the effectiveness of credit support policies in the demand-based credit suppression regions. Conclusions draw in this paper provide strong evidence for formulating appropriate credit policies in the rural area.
马文杰, 徐晓萍. 信贷抑制类型识别及政策影响:千村调查证据[J]. 金融研究, 2018, 459(9): 19-36.
MA Wenjie, XU Xiaoping. Identification of Credit Suppression and Policy Implications: Evidence from Thousand Village Survey. Journal of Financial Research, 2018, 459(9): 19-36.
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