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In this study, the authors examined demand-side credit in rural China with the aims of understanding attribute preferences and the willingness of farmers to pay for credit.

The authors implemented an in-the-field discrete choice experiment (DCE) using a D-optimal block (6 × 9 × 3) design applied to 420 farm households across five Chinese provinces (Shandong, Sichuan, Shaanxi, Jiangsu and Henan) in the summer and fall of 2018. The DCE included six attributes including the interest rate, term of loan, type of loan, type of repayment, type of institution and mobile banking services.

Conditional and mixed logit results indicated a downward sloping credit demand curve with variable elasticity across regions. Provincial willingness-to-pay (WTP) indicators suggested that farmers were willing to pay a premium for long-term ( 0.03–0.687%) and low collateral credit loans ( 0.79–2.93%). Also, four of five provinces indicated a preference for loan amortization rather than lump-sum payment. Interestingly, in comparison to the Agricultural Bank of China (ABC), only farmers in Shandong, Sichuan and Shaanxi indicated a preference for rural credit cooperatives (RCCs)/banks and the Postal Savings Bank of China (PSBC). Another quite surprising result was bank services, in our case, access to mobile banking did not appear to induce WTP for agricultural credit. While conditional and mixed logit regression coefficients were similar (and therefore robust), the authors found that there was substantial heterogeneity across attribute preferences on term of loan, type of loan and amortization. Preferences for type of lender and mobile banking were generally homogenous. This result alone suggested that lenders should consider offering a suite of credit products with different attributes in order to maximize the potential pool of borrowers. While there were some differences across provinces, farmers appeared to be indifferent to lenders, and it did not appear that offering banking services such as mobile banking had any bearing on credit decisions.

This paper presents a first step in using in-the-field choice experiments to better understand rural finance in China. Although the sample size satisfies conventional levels of significance and rank conditions, the authors caution against attributing results to China as a whole. Different provinces have different institutional structures and agricultural growing conditions and economies and these effects may differentially affect WTP for credit. Although by all indications farmers were aware of credit, not all farmers, in fact a minority, actually borrowed from a financial institution. This is not unusual in China, but for these farmers, the DCE was posed as hypothetical. Likewise, the study’s design was based on a generic credit product typical of rural China, and the authors caution against making inferences about other products with different attributes and risk structures.

This study is motivated by the rapidly changing dynamic in China's agricultural economy. With specific reference to new laws and regulations about the transfer of land use rights (LURs), China's agricultural economy is undergoing significant and rapid change which will require better understanding by policy makers, lenders and practitioners of the changing credit needs of farmers, including the new and emerging class of commercial farmers.

To the best of the authors’ knowledge, the authors believe that the result provided in this paper present the first use of in-the-field DCE and are the first to be reported in either the English or Chinese literature on rural credit product design.

This paper investigates the relationship between climate finance and climate ergodicity. More specifically the paper examines how climate ergodicity as measured by a mean-reverting Ornstein–Uhlenbeck process affects the value of climate-linked bonds.

Bond valuation is evaluated using Monte Carlo methods of the Ornstein–Uhlenbeck process. The paper describes climate risk in terms of the Hurst coefficient and derives a direct linkage between the Ornstein–Uhlenbeck process and the Hurst measure.

We use the Ornstein–Uhlenbeck mean reversion relationship in its OLS form to estimate Hurst coefficients for 5 × 5° grids across the US for monthly temperature and precipitation. We find that the ergodic property holds with Hurst coefficients between 0.025 and 0.01 which implies increases in climate standard deviation in the range of 25%–50%.

The approach provides a means to stress-test the bond prices to uncover the probability distribution about the issue value of bonds. The methods can be used to price or stress-test bonds issued by firms in climate sensitive industries. This will be of particular interest to the Farm Credit System and the Farm Credit Funding Corporation with agricultural loan portfolios subject to spatial climate risks.

This paper examines bond issues under conditions of rising climate risks using Hurst coefficients derived from an Ornstein–Uhlenbeck process.

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 determine the effects of the 2018–2020 China–US trade war on US farm bankruptcies as filed under Chapter 12. The key task is to identify the economic factors affecting farm bankruptcies generally, and to then control for the trade war impacts including the Market Facilitation Program (MFP), floods, agricultural conditions and the health of agricultural finance leading into the trade war.

Results were obtained using ordinary least square regression and panel fixed effect model using bankruptcy rates and number as the dependent variable. Independent variables included market effects, credit conditions, yield variation, trade impacts, 2019 flooding, macroeconomic conditions and regional fixed effects. The authors use cubic splines to interpolate annual and quarterly data to a monthly base.

Based on a fixed effect model, the authors find that all other things being equal the China–USA trade war would have had a significant impact on Chapter 12 farm bankruptcies, increasing the bankruptcy rate by 25.7%. The flooding in 2009 had minor effects of increasing the rate by only 0.05%. The overall impact will, however be substantially lower than the 25.7% because of the MFP. The MFP variables (binary) had mixed effects and its true impact is unknowable at this time; however, the authors also find that a 1% increase in the producer price index decreases bankruptcy rates by 2.62% and farm bankruptcy numbers by 3.70%. Likewise a 1% increase in GDP reduces bankruptcies by 3.25%. These suggest that the MFP program will have likely reduced farm bankruptcies considerably than what would have occurred in their absence. The authors also find that states heavily dependent on trade faced lower market uncertainty. Broader economic factors (net charge-offs of farm loans held by insured commercial banks, US real GDP, the average effective interest rate on nonreal estate farm loans) affect farm bankruptcy.

The authors use monthly bankruptcy statistics, however not all data were available in monthly measures requiring interpolation using cubic spline functions to approximate monthly changes in some variables. Although the MFP had mixed effects in the model, the mid- to longer-term effects may be more impactful. These longer-term effects (and even shorter-term effects through 2020) are complicated by the coronavirus disease 2019 (COVID-19) pandemic, which will require a different identification strategy than that employed in this paper.

The analysis and results of this paper are, to the authors' knowledge, the first to investigate the impact of the China–US trade war on Chapter 12 farm bankruptcy filings. The use of cubic splines in the interpolation of agricultural data is also a technical innovation.

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.

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.

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.

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.

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.

The purpose of this paper is to investigate the market microstructure related to the Farm Credit System (FCS), Commercial Banks (CB) and Farm Services Administration (FSA). The commercial banks frequently call out the FCS as having an unfair advantage in the agricultural finance market place due to tax exempt bonds, and an implied guarantee of those bonds. This paper addresses the issue by examining the interrelationships since 1939, while addressing the historically distinctive roles that the FCS, CB and FSA have played in the US agricultural credit market.

There are two components to our model. The first is the estimation of short and long run credit demand elasticities, as well as land elasticities. These are estimated from a dynamic duality model using seemingly unrelated regression. The point elasticity measures are then used as independent variables in least square regressions, combined with farm specific and related macro variables, for the Cornbelt states. The dependent variable is the year-over-year changes in paired FCS, CB and FSA loans.

The genesis of the FCS was to provide credit to farmers in good and bad years. Therefore, we expected to see a countercyclical relationship between FCS and CB. This is found for the farm crisis years in the 1980s but is not a continuous characteristic of FCS lending. In good times the FCS and CB appear to compete, albeit with differentiated market segmentation into short- and long-term credit. The FSA, which was established to provide tertiary support to both the FCS and CB, appears to be responding as designed, with greater activity in bad years. The authors find the elasticity measures to be economically significant.

The authors conclude that the market microstructure of the agricultural credit market in the US is important. Our analysis applies a broader definition of market microstructure for institutions and intermediaries and reveals that further research examining the economic frictions caused by comparative bond vs deposit funding of agricultural credit is important.

The authors believe that this is the first paper to examine agricultural finance through the market microstructure lens. In addition our long-term data measures allow us to examine the economics through various sub-periods. Finally, we believe that our introduction of credit and land demand elasticities into a comparative credit model is also a first.

This paper investigates Chinese agricultural insurance agents willingness to offer (WTO) livestock insurance based on the variations of eight main attributes of livestock insurance.

This study implements discrete choice experiments (DCE) with actual insurance agents who design, sell and operate livestock insurance in China. The choice experiment of this study is based on the D-optimal approach, a six-block design, with 15 cards per block and two choices per card. The sample size was 211. Econometrics results are based on conditional and mixed logit models.

The authors find that the subsidy effect is enormous; a one level increase of subsidy leads to 3.166 times higher probability to offer. This subsidy effect is important as it confirms the endogenous structure between price and quantity in insurance offering, where subsidy does not only incentivize demand but also the supply. Another main factor of insurance investigated is the impact of different coverage types on agents' WTO. The authors find that agents prefer mortality insurance the most, followed by revenue insurance and profit insurance, while Index-Based Livestock Insurance (IBLI) is the least preferred to offer. Agents' knowledge about these newer types of insurance supports their WTO as well; thus, proper education is necessary to promote the more advanced types of livestock insurance.

A limitation is that in the presence of COVID 19, and administrative issues at the local level, the sample was not randomly drawn. Nonetheless, the authors believe that there is enough diversity across participants, insurers and provinces and have done sufficient robustness checks to support results and conclusions.

This study provides further validation for the DCE research method that could potentially be applied to different analyses: using choice experiments to study insurers and reveal their preferences, through combinations of various levels of core attributes for insurance products. The findings and contribution are critical to the reform and improvement of livestock insurance in China and for insurance markets more broadly. The authors find that insurers do not place equal weights or values on insurance product attributes and do not view types of insurance equally. In other words, while farmers may hold different preferences about the type of insurance they demand, the results suggest that insurers also hold preferences in the type of insurance they sell.

So far as the authors are aware, this is the first DCE designed around the supply of insurance products with the subjects being insurance agents, marketers and executives.

The purpose of this paper is to provide a review of major historical developments in agricultural finance, with particular emphasis on agricultural credit. It reviews the development of Raiffeisen and related banks that emerged in Germany and Europe throughout the nineteenth century and how the cooperative banking system made its way into the banking system of the USA in the early twentieth century. The paper emphasizes the role of the state in the developing of agricultural credit, especially with respect to farm mortgages, securitization, and bond structures.

This paper presents a historical synthesis of historical literature on agricultural credit.

This paper shows the direct linkage between the developments in Raiffeisen credit cooperatives and the Farm Credit System (FCS) and details the emergence of the land banks, farm credit banks, agricultural bonds and the role of joint-stock banks in agricultural credit policy.

In total, 2016 marks the 100th anniversary of the passing of the 1916 Federal Farm Loan Act which set in motion the USs’ first Government Sponsored Enterprise and catalyzed the formation of the FCS as it operates today to provide credit to farmers and rural communities on a cooperative basis. Although there are a few wonderful books written on certain aspects of the FCS the story of how the FCS was initiated and the many struggles it faced up to the 1933 Act has not been told often enough. This paper tells the story of the evolution of agricultural credit that ultimately led to the formation of the FCS.

The purpose of this paper is to examine the relationships of technical training and the peer effects of technical training with farmers' pesticide use behaviors.

This study uses survey data from 300 peanut growers in Zoucheng County, Shandong, China, in 2016 and employs spatial econometric models to examine the relationships of technical training and the peer effects of technical training with farmers' pesticide use behaviors.

This paper reveals that important peer effects can be channeled through technical training and that these peer effects are sufficiently significant to encourage neighboring farmers to reduce the amount of pesticide use, to transform the structure of pesticide use, and to increase the usage amount of low-toxicity, low-residue pesticide use per hectare. The estimated parameters for the peer effects from technical training are significantly larger than those from technical training alone, which suggests that the technical training of neighboring farmers plays a greater role than technical training for farmers individually.

The research finds that technical training within smaller, localized, groups can induce previously unobservable spillover effects, and this provides a scientific, theoretical and empirical justification for agricultural technology extension that can lead to a rapid, effective transformation of applying new agricultural technologies in an environmentally sensitive and economically sustainable manner.

One of the particular problems facing agribusiness firms is the relationship between commodity price risk (a source of business risk) and debt repayment ability (a source of financial risk). This study examines the use of commodity‐linked loans applied to agricultural credits. A commodity‐linked loan is a credit instrument whose payoff is contingent on the value of an underlying commodity or portfolio of commodities. The payoff structure includes an option (call or put) rider that provides a payoff if the commodity price rises above or drops below a preset strike price. The payoff is applied directly to the loan. This study introduces the general concept, reviews the literature, and develops and applies a particular model. Simulation results illustrate the interrelationship between options payoffs, strike prices, volatility, and downside financial risk reduction.