Guangwen He

The 7 Cs of rural credit in China

Purpose - The purpose of this paper is to provide an overview of the farm and rural credit system in China. To do this the authors use the so-called “7 Cs” of credit (these include: Credit, Character, Capacity, Capital, Condition, Capability, and Collateral) and for each “C” provide some aspect of importance related to agricultural finance. Design/methodology/approach - This paper is largely based on a survey of 897 farm households in Shaanxi and Gansu provinces, and extensive interviews of agricultural lenders conducted in the summer and fall of 2009. These data are used in simple form and in regression form to explain a variety of credit issues in China. Findings - A number of key factors related to credit delivery and demand are found. First, using the 7 Cs as a guide proved to be very fruitful for disentangling the many institutional and cultural facets affecting rural credit in China. Under “Character” the authors discuss the cultural characteristics of the Chinese farmer in terms of informal lending and borrowing; under “Capacity” the authors discuss the challenges of delivering credit to farms with limited resources; under “Condition” the authors discuss group guarantees and credit worthy villages, credit rationing and insurance and incomplete markets; under “Capability” the authors discuss income inequality and challenges in economies of scale and size; and for “Collateral” the authors discuss the implications of lack of collateral and limitations on farm economic growth due to the collectivization of land and the potential for agricultural lending from the transferability and mortgagability of land or forestry use rights. Research limitations/implications - Although the assessment provides a great deal of breadth and depth across many credit-related issues in China, it is not an exhaustive study. Agricultural and rural credit in China is very complex and in many instance under developed. The survey results from Shaanxi and Gansu tell a story that is consistently told throughout China, but the authors would caution against using the data to characterize farm credit across China as a whole. Social implications - Large swaths of China have either no or very rudimentary credit services. Even in areas where credit is in supply there are issues of poverty that could be aided with credit access and delivery. In order to improve livelihoods through credit institutions, it is important to understand rural credit in many dimensions. This paper takes a step in that direction. Originality/value - Despite the importance of rural credit in China, it is largely understudied and not well understood. This paper makes progress in providing such an understanding. Our reasoning for using our unique approach is that by understanding the 7 Cs of credit one comes to understand the elemental characteristics of the credit decision from the lenders point of view but in a way that takes into account conditions at the farm level. The 7 Cs provide an objective approach to credit assessment that balances both the supply of and demand for credit.

Chinese Rural Cooperative Finance in the Era of Post-Commercialized Rural Credit Cooperatives

Rural credit cooperatives have become increasingly commercialized over the last decade. However, this does not spell the end of cooperative finance in rural China. Various new cooperative credit organizations have sprung up in recent years with endorsement from the central and local governments. They are designed to meet the wide-ranging credit demand of rural households and microenterprises that are increasingly left behind by formal credit institutions. Rural mutual aid funds (nongcun zijin huzhushe) are a cornerstone of cooperative finance in rural China, filling in the market gap left behind by commercialized financial institutions.

Incentive Mechanisms, Loan Decisions and Credit Rationing: A Framed Field Experiment on China's Responsibility System for Rural Credit

Incentive mechanisms are important attributes to financial decision-making. A framed field experiment was conducted to test loan decision behaviors. It showed that lenders’ risk-aversion and behavioral responses resulted in credit rationing under certain incentive schemes. In the experiment, loan officers from Rural Credit Cooperatives (RCCs) in Shandong, China were recruited to evaluate randomly selected loan applications and make lending decisions. All the loan files were previously approved with known performance and repayment status. Each loan officer was randomly assigned to one of two incentive groups. One was analogous to pure Personal Responsibility System (PRS), which provided bonuses to loan officers for approved loans that were in performance and imposed penalties on non-performing loans (NPLs). And the other was PRS with additional penalties for Type II error (i.e. rejecting loans that would have been good). The two groups were further randomized over prior knowledge about probability distribution of the application pool. Results showed that PRS made a risk-averse loan officer inclined to reject loans to avoid risk of penalty. This side effect generated credit rationing, increased Type II error in loan classification and lowered the interest returns of RCCs. Providing prior information about the application pool helped to increase decision accuracy. In theory, this study extended the incentive mechanism design under uncertainty to a behavioral scope. In practice, it can lead to increased profitability in financial institutes, alleviated credit rationing and stabilized credit supply in the market.

Incentive mechanisms, loan decisions and policy rationing: A framed field experiment on rural credit

Purpose - The purpose of this paper is to investigate whether negative incentives in the pay-for-performance mechanism would trigger loan officers to strategically reject potentially good loans. If so, what is the feasible solution to alleviate the problem. Design/methodology/approach - A framed field experiment was conducted to test loan decision behaviors using loan officers from Rural Credit Cooperatives in Shandong, China. A 2 by 2 between-subject design was adopted to generate variation in incentives and prior information about credit risks. Findings - Results showed that loan officers did ration credit by rejecting more loans when facing risks of personal income loss. However, providing risk information about the application pool boosted the approval rate and offset the behavioral responses by a roughly same magnitude. Research limitations/implications - Findings in this study suggest that certain institutional settings can result in credit rationing via strategic loan misclassification. Further, information sometimes generates similar effects as those costly incentives or mechanisms that are not implementable in practice. Originality/value - This study adopted an innovative monetized experimental design that allows researchers to examine the (otherwise unobservable) trade-offs between Type I and Type II error in loan misclassification as incentives change. In addition, an anchoring prior information treatment is used to solicit the relative power of almost costless information and costly monetary incentives, and to point out a potentially feasible solution.