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The purpose of this paper is to determine the extent of risk rationing among potential rural borrowers in Mexico and China.

Using primary survey data from 730 farm households in the Shaanxi province of China and from 372 farmers in northeastern Mexico, the authors investigate factors associated with risk rationed, price rationed and quantity rationed farmers. The survey was instrumented to self-identify borrower typologies. In addition the authors created within the survey a discrete-choice credit demand build to determine borrower credit demand elasticities. The analysis applies a linear probability which the authors found to be consistent with multinomial and binary logit models.

The authors find in China the incidence of risk rationing in farmers to be 6.5, 14 percent for quantity rationed and 80 percent for price rationed. In Mexico, 35 percent of the sample is risk rationed, 10 percent quantity rationed and 55 percent price rationed. The results from China support the hypothesis that the financially poor are more likely to be quantity rationed; in Mexico, however, the level of education is found to be important in determining quantity rationed. In both countries, asset wealthy farmers are less likely to be risk rationed; however, income does not appear to have an impact. The paper provides evidence that the elasticity of demand for credit is different among the three credit rationed groups: risk rationed, price rationed and quantity rationed. Risk aversion and prudence are significantly correlated with risk rationing in China, while only risk aversion is significant in Mexico. The results suggest that efforts to enhance credit access must also deal with risk and risk perceptions.

Risk rationing is an important concept in the understanding of rural credit markets. The findings that only 6.5 and 35 percent of Chinese and Mexican farmers are in stark contrast to each other. For agricultural economies such as Mexico with a significant number of farmers being risk rationing, more effort should be put into financial education and financial practices, including perhaps the use of risk-contingent credit to remove collateral risk. As property rights in China evolve, and new laws are promulgated to permit borrowing against land use rights, the collateralization issue will become much more important in rural credit markets.

This paper is the first to investigate risk rationing in China and Mexico and one of the few research studies empirically investigating risk rationing. A comparative analysis of Mexico and China is enlightening because of the structural differences in the respective agricultural economies. The use of a credit demand build and the enumeration of individual credit demand elasticities is an original contribution to this literature.

Drought-related climate risk and access to credit are among the major risks to agricultural productivity for smallholder farmers in Kenya. Farmers are usually credit-constrained due to either involuntary quantity rationing or voluntary risk rationing. By exploiting randomized distribution of weather risk-contingent credit (RCC) and traditional credit, the authors estimate the causal effect of bundling weather index insurance to credit on uptake of agricultural credits among rural smallholders in Eastern Kenya. Further, the authors assess farmers' credit rationing, its determinants and effects on credit uptake.

The study design was a randomized controlled trial (RCT) conducted in Machakos County, Kenya. 1,170 sample households were randomly assigned to one of three research groups, namely control, RCC and traditional credit. This paper is based on baseline household survey data and the first phase of loan implementation data.

The authors find that 48% of the households were price-rationed, 41% were risk-rationed and 11% were quantity-rationed. The average credit uptake rate was 33% with the uptake of bundled credit being significantly higher than that of traditional credit. Risk rationing seems to influence the credit uptake negatively, whereas premium subsidies do not have any significant association with credit uptake. Among the socio-economic variables, training attendance, crop production being the main household head occupation, expenditure on food, maize labour requirement, hired labour, livestock revenue and access to credit are found to influence the credit uptake positively, whereas the expenditure on non-food items is negatively related with credit uptake.

The study findings provide important insights on the factors of credit demand. Empirical results suggest that risk rationing is pervasive and discourages farmers to take up credit. The study results also imply that credit demand is inelastic although relatively small sample size for RCC premium subsidy groups may be a limiting factor to the authors’ estimation.

By implementing a multi-arm RCT, the authors estimate the factors affecting the uptake of insurance bundled agricultural credits along with eliciting credit rationing among rural smallholders in Eastern Kenya. This paper provides key empirical findings on the uptake of RCC and the effect of credit rationing on uptake of agricultural credits, a field which has been majorly theoretical.

The purpose of this paper is to investigate the determinants of agricultural credit rationing by formal lenders in Ghana.

This study employed descriptive statistics, analysis of variance (ANOVA) and Heckman's two-stage regression model to identify types of rationing faced by farmers and investigate factors that influence agricultural credit rationing by formal financial institutions. Data used in this study are gathered through a survey of 595 farmers in seven districts within Brong Ahafo Region of Ghana.

The result reveals that farmers face three types of rationing. Evidence from the Heckman two-stage models shows that engagement in off farm income generating activities, increase in farm size, positive balances on accounts and commercial orientation of the farmers has the potential to reduce rationing of credit applicants by formal lenders.

The results provide information on the factors that need to be considered as important in an attempt to reduce agricultural credit rationing by formal lenders.

The value of this study is that farmers would use the results of this study to improve access to required amount of agricultural credit from formal financial institutions. The information would also benefit stakeholders in the agricultural sector, particularly youth in agriculture program organized by Ministry of Food and Agriculture in Ghana as how to improve access to credit and reduce rationing of program participants by formal financial institutions.

Lack of access to credit is commonly held responsible for slow agricultural and rural development in low- and middle-income countries. This paper aims to investigate the contribution of demand- and supply-side factors, particularly the role of risk rationing, on credit application and uptake in the case example of Kyrgyzstan.

Toward this aim, the study explores the determinants of credit behavior of 1,738 Kyrgyz sample farm households from 2013 to 2016 waves of the nationally representative “Life in Kyrgyzstan” (LIK) dataset along a hierarchical regression model, differentiating between factors influencing individual demand for credit and factors influencing supply for credit.

The results of our analysis indicate the relative importance of demand-side factors for credit applications, reflecting farmers' perceived risk of credit default and loss of collateral. Meanwhile, supply-side factors, such as real credit constraints and collateral requests, have a stronger influence on credit uptake rates and overall loan sums. These findings highlight the role of risk rationing for agricultural investment, suggesting a stronger focus of development policy on improving risk-sharing mechanisms for farmers, e.g. by developing the agricultural insurance sector.

The paper contributes novel evidence on the role of risk rationing in shaping the demand for formal credits for increasing agricultural and rural investment in low-income transition economies. Previous research has mostly focused on the role of credit supply, thus underrating the potential contribution of individual risk attitude, risk experience and risk sharing.

The purpose of this paper is to model credit rationing among farmers in rural developing areas, based on micro level data of Kano State, Nigeria.

A total of 835 households and 45 microfinance banks were utilized as the samples of the study which were selected using multi-stage stratified sampling technique. Multinomial logit model was used to estimate the factors that determine credit rationing among the rural farmers in Nigeria.

The result of the discrete choice model shows that farmers who are either being engaged in subsistence farming or trading have a significant effect on credit rationing with the greatest impacts found on the farm profit and farmers’ location.

This study failed to carry out a dynamic analysis regarding agricultural credit rationing. Also, it is well known that formal credit interacts with informal credit sector; nevertheless, this interaction was unaccounted for in this study. Therefore, future studies can expand the scope of this research to account for this interaction. In fact, investigating heterogeneity among credit providers will be an important topic in the future.

Clear and sound policies are required for the establishment of new agencies and financial institutions devoted to agricultural sector. Similarly, an integrated system of forward-looking policies based on tax and subsidy-regimes to augment desired incentives for private financial sector and NGOs to lend money to the farmers are needed.

Consistent with risk-balancing theory, the good story for farmers is that profit making farmers are less likely to be among the constrained borrowers. It turned out from the credit rationing model that urban farmers had a greater chance of being successful applicants in the Nigerian agricultural credit market. In comparison to farmers at periphery, urban residents are less likely to be associated with being constrained borrowers.

Why do lenders shrink back from full risk pricing in certain credit markets, even when a sophisticated system of credit scoring is already in place? Fear of bad publicity is the usual reason cited but this paper offers a complementary explanation which suggests that there may be an underlying financial process driving such behaviour. The key proposition of the paper is that risk pricing can cause adverse selection which has the potential to mitigate any positive benefits such a pricing strategy may bring to the lender. This explanation is developed by introducing risk pricing into the seminal Stiglitz and Weiss model and in so doing offers the first substantial link between the risk assessment and credit rationing literatures.

The purpose of this paper is to analyze determinants of farmers’ participation and credit rationing in microcredit programs using survey data from Ghana.

The authors use the Garrett Ranking Technique to analyze farmers’ reasons for participation or non-participation in credit programs, a probit regression model to estimate factors influencing farm households’ participation, and the Heckman’s sample selection model to identify factors influencing farm households’ probability of being credit rationed by microcredit programs.

The results reveal that farm households participate in credit programs because of improved access to savings services and agricultural loans. Fear of loan default and lack of savings are reasons for non-participation in credit programs. Furthermore, membership in farmer-based organizations (FBOs) and the household head’s formal education are positively associated with farmers’ participation in credit programs. The likelihood of farmers being credit rationed (i.e. their loan applications were either rejected or the amount of credit they applied for was reduced) is less likely among higher income farmers and members of FBOs such as farmer cooperatives and savings clubs.

The findings suggest that policy strategies aiming to improve access to savings and credit services should educate farmers and strengthen FBOs that could serve as entry points for financial service providers. Such market smart strategies have the potential to improve farmers’ access to financial services and reduce rural poverty.

Although existing studies have examined farmers’ participation in credit markets and credit rationing separately, the unique contribution of this paper is the analysis of participation in microcredit programs as well as the likelihood of farmers being credit rationed in Ghana.

Using a unique dataset of a commercial microfinance institution (MFI) in Tanzania, the purpose of this paper is to investigate first whether agricultural firms have a different probability to get a loan and whether their loans are differently volume rationed than loans to non‐agricultural firms. Second, the paper analyzes whether agricultural firms repay their loans with different delinquencies than non‐agricultural firms.

The authors estimate a Probit‐Model for the probability of receiving a loan, a Heckman‐Model to investigate the magnitude of volume rationing for all loan applications and an OLS‐Model to examine the loan delinquencies of all microloans disbursed by the MFI.

The results reveal that agricultural firms face higher obstacles to get credit but as soon as they have access to credit, their loans are not differently volume rationed than those of non‐agricultural firms. Furthermore, agricultural firms are less often delinquent when paying back their loans than non‐agricultural firms.

Even if the authors can show that access to credit and loan repayment is different for agricultural firms, the current regional focus of the MFI only allows for lending to agricultural firms in the greater Dar es Salaam area. Thus, these results might change in a rural setting. Besides general differences of the rural economic environment, the production type of agricultural firms might also differ in rural areas. Also, these results might change in different country contexts.

The findings suggest that a higher risk exposition typically attributed to agricultural production must not necessarily lead to higher credit risk. They also show that the investigated MFI overestimates the credit risk of agricultural clients and, hence, should reconsider its risk assessment practice to be able to increase lending to the agricultural sector. In addition, the results might indicate that farmers qualify less often for a loan as they do not fit into the standard microcredit product.

To the authors' knowledge, this is the first paper which simultaneously investigates access to credit and the repayment behavior of agricultural firms.

In order to improve the assessment of current lending policies for a microfinance institution (MFI) in Azerbaijan, the purpose of this paper is to analyse how lending conditions are adjusted based on knowledge gains during the loan relationship, with particular attention to delays in previous loans. Moreover, the paper examines what a lender can pre-determine from its own collected repayment records of clients. In addition, the repayment performances and lending policies between agricultural and non-agricultural clients are differentiated.

The analyses are based on a rich data set of an Azerbaijani MFI. For determining the influence of previous delays on the volume rationing in the following loan, the authors apply a generalized linear model. Subsequently, the probability of recidivism is analysed by means of a logit model.

The results confirm a positive relationship between delays in previous loans and repayment problems in present loans, which is increased by the severity of the previous delay. With respect to consequences, it is shown that the borrower with previous delays faces an increase in loan volume rationing in the subsequent loan. Moreover, the authors find that the consequences of previous delays do not differ significantly between farmers and other clients.

Until now, the consequences of repayment delinquencies in microfinance lending relationships have hardly been investigated. This study enhances the understanding of lending policies in microfinance by focussing on relationship aspects and by simultaneously differentiating between farming and non-farming clients.

The purpose of this paper is to evaluate the effects of access to formal credit on rural household technical efficiency in China.

Based on the rural household survey data in Weifang city, Shandong province in northern China, the authors apply recent developed bootstrapped DEA approach to investigate rural technical efficiency at the household level under the consideration of off-farm activities. Rural households are then identified as credit constrained and classified as supply-side and demand-side credit constraints by applying direct elicitation method. Finally, the authors apply a tobit regression to examine the effects of credit constraints on household technical efficiency.

Rural households in China not only suffer supply-side credit constraints, but also demand-side credit constraints resulted from the transaction costs and risk rationing. The tobit regression discloses that demand-side credit constraints impose significant negative impacts on household technical efficiency.

The authors clarify the definition of credit constraints and classify the credit constraints into supply-side and demand-side credit constraints. The results of this paper have significant policy implications for rural finance policies in China.