Factors affecting farmers’ participation in China’s group guarantee lending program

Abstract

Purpose – Based on a survey of 897 farm households, the purpose of this paper is to build a framework using cluster analysis to explain how farmers make decisions on joining group guarantee, and analyzes factors influencing their decisions using multinomial and binary Logit regressions. Design/methodology/approach – The approach of combining cluster analysis with Logit regression is an innovative approach to survey assessment. In addition, by design the authors have identified the four mutually exclusive groups of borrowers combining Group Guarantee membership and actual formal borrowing. Findings – An extremely important observation according to the data is that most farmers appear to be part of group guarantees only because they have to in order to get access to formal credit products. 87.21 percent of the people who belong to groups and utilize the formal credit products belong to this category because their lenders have made participation in groups compulsory for access to credit. This may ration farmers’ willingness to even apply for credit. It also indicates a preference on the part of older and more risk-averse respondents to avoid participation in group guarantees. Out of financial characteristics the total loan holdings appears to be the only significant indicator of participation in group guarantees. Furthermore the results indicate that informal and formal credit appear to be replaceable for farmers. Research limitations/implications – The survey is confined only to the counties investigated. China is very diverse in its agricultural economies and many RCCs operate under different guidance and rules from those investigated here. Hence, while the authors can claim that the results are indicative, the authors cannot claim that they will hold generally. Practical implications – Based on group guarantee loan mechanism and survey data analysis of 897 farm households, this paper analyzes influencing factors affecting farmers’ participation in group guarantees from microcosmic level, so as to provide some reference to further perfect micro credit operation mode and mechanism. Social implications – The results indicate that the Group Guarantee mechanism, while beneficial to some, may not hold global appeal for Chinese farmers. In the future RCCs may want to consider alternative approaches to loan security than placing the burden of guarantee on farmers’ family and friends. Originality/value – The approach of combining cluster analysis with Logit regression is an innovative approach to survey assessment. In addition, by design the authors have identified the four mutually exclusive groups of borrowers combining Group Guarantee membership and actual formal borrowing.

The relation between entrepreneurship and rural poverty alleviation in China

“…This is indicative that rural agriculture still serves as a major source of employment for the teeming youth in China. This finding is in contrast with that of Kong et al (2015), who found that many rural areas in China have been deserted by the youth due to rural-urban migration. This finding, therefore, implies that farmer entrepreneurship can help reduce youth unemployment.…”

Heterogeneous choice in the demand for agriculture credit in China: results from an in-the-field choice experiment

“…Although the evidence that risk rationing among Chinese farmers is low (Verteramo-Chiu et al, 2014), these results indicate that the demand for collateral or guaranteed loans will be lower than credit loans. This is consistent with the findings of Kong et al (2015). We can infer that the demand for credit loans will be more elastic than the demand for collateral or guarantee loans.…”

“…Policies put in place by lenders to address risk and asymmetric information can also have demand side effects. Kong et al (2015) investigated the group guarantee and found that, generally, farmers did not form group guarantees voluntarily but were required to do so by the lender. Older farmers were less likely to borrow under a group guarantee or voluntarily join a group guarantee as guarantor; guarantors in a group guarantee are more likely to be risk takers or not too risk adverse; farmers who mistrust lenders are less likely to join a group guarantee.…”

Smallholder preferences and willingness-to-pay measures for microcredit

“…Generally, the main microcredit attributes that have been used to explain the preferences of poor households are interest rate, repayment schedule, loan size and collateral method (Boucher et al, 2008;Tsukada et al, 2010;Sagamba et al, 2013;Kong et al, 2015). Interest rate, which is the price of financial service, has received the most attention ( Janvry et al, 2010;Rashid et al, 2011;Khandker and Koolwal, 2016;Tan and Lin, 2016).…”