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This study investigates important factors that should be used by lenders in risk‐rating their farm customers. These factors predict actual farm performance and debt repayment ability. Linear and logistic regression models are used to identify the debt‐to‐asset ratio as a major predictor of repayment ability. In addition, the rate of asset turnover and family living expenses are strong predictors of farm performance. The results are tested over several time periods to verify the robustness of the predictors.

A credit risk model suitable for agricultural lenders is identified. The model incorporates sector correlations and is applied to the loan portfolio of an agricultural credit association to create a distribution of loan losses. The distribution is used to derive the lender’s expected and unexpected losses. Results of the analysis indicate that the association is more than adequately capitalized based on 1997S2002 data. Since the capital position of the association is lower than that of most other associations in the Farm Credit System, this raises the issue of overcapitalization in the System.

The Government of Uganda has put in place the Plan for the Modernization of Agriculture as part of its poverty reduction program. That program incorporates the improvement of households’ access to formal financial services as one of its main components. To examine the program, this study uses primary data to determine the savings and portfolio allocation behavior of households with and without access to formal financial services. Findings reveal no significant difference between both types of households in the marginal propensity to save out of long‐run income. The precautionary demand for liquidity and the desire to avoid risk are important factors shown to influence portfolio allocation decisions by households.

Loan migration analysis is conducted using a large data set of loan risk ratings in the Farm Credit System. We find path dependence and limited support for a trend reversal pattern. There is evidence that the magnitude of migrations reported in previous credit score proxy studies overstates trend reversal in agricultural loans rated by lenders. Our results indicate that retention rates of agricultural loan risk ratings are quite high. Small loans are less likely to migrate than medium and large‐sized loans, and unseasoned loans are more likely to migrate than seasoned farm loans

Lenders, regulatory agencies, and investors have increased their demand for credit risk exposure information to appropriately price risk and evaluate risk migration patterns that affect institution safety and soundness. This review provides a synthesis of the advances in credit risk assessment made through journal articles and other professional reports. Contributions in three primary areas are considered: (a) how the credit risk assessment problem has been defined and redefined over time in response to the changing information needs of lenders and regulators, (b) how methodological innovations have improved credit assessment procedures, and (c) how the efficiency of financial markets has changed due to the evolution of credit risk assessment. The paper concludes with a discussion of how transactional and relationship lending approaches are expected to evolve in the future and whether measures can be developed to more accurately assess factors such as management capacity and commitment to repay.

The purpose of this paper is to determine if there are positive microeconomic effects from a state‐funded loan participation program on farm productivity and investment behavior.

The authors take the approach that access to credit solves a liquidity problem. If a credit constraint exists it results in a suboptimal allocation of resources and a reduction in farm output and profitability. A two‐stage regression model approach is used to analyze farmer survey and loan application data. In the first stage, a probit regression model is used to identify the farmers who are likely to be credit rationed. In the second stage, switching regression models are used to observe the effect of credit rationing on farm productivity and on farm investment behavior.

It is found that there are liquidity effects of credit constraints for a significant share of the beginning and low‐resource farmers who participated in the state‐funded farm loan program. After controlling for various farm and farmer characteristics, the estimated productivity and investment demand equations imply that a 1 percent increase in credit received by credit constrained farmers under the state program increased their gross income by about 0.49 percent, and their investments in depreciable assets by about 0.33 percent.

This paper is the first to apply the switching regression model to a state‐funded farm loan program for the purpose of evaluating the financial impacts on farmer participants.

The purpose of this paper is to investigate the relationship between loan default and loss given default (LGD) in an agricultural loan portfolio. The analysis employs a simulation model approach to evaluate the role that systematic and non‐systematic risks play in determining the economic capital requirements under different agricultural economic conditions.

The authors employ the theoretical approach suggested by Miu and Ozdemir to assess the role of LGD in the banking industry. A Monte Carlo simulation model is developed using Excel and calibrated to an agricultural credit association using historical data. The simulation model is used to evaluate the mark‐up to economic capital that is implied by increasing credit risks due to cyclical changes in farm real estate values.

The paper demonstrates that historical systematic risks due to the correlation between probability of default (PD) and LGD through the business cycle can result in a significant mark‐up in the economic capital required by an agricultural lender. Using historical land price changes as the driver of systematic risk, the authors show that the correlations between changing PD and land values and between the PD and LGD provide evidence of how sensitive credit risk exposure is to these parameters.

This paper is the first application of the Miu and Ozdemir model of systematic risk to an agricultural lending institution. The model approach can be adapted by farm lenders to evaluate their changing economic capital requirements through an economic cycle in agriculture.

The purpose of this paper is to investigate how to incorporate market price risk into investment decisions. The investigation focuses on investments to expand ethanol production facilities. The model is used to determine if such a real option approach can explain recent changes in the level of plant investment activity.

The paper demonstrates how real option analysis and Monte Carlo simulation can be used to evaluate ethanol plant investments by using available historical industry and market price data. We focus on existing small‐to‐medium, dry milling plants and the real option to expand the scale of operations. The binomial option pricing model is used to identify optimal strategies.

Increasing profitability and volatility appear to favor the strategy of investing during 2005‐2007. However, when the prices of corn and natural gas rise and plant profitability declines during 2007‐2008, the best strategy is increasingly to either postpone the investment or reject the decision to expand.

This paper is a first application of real option analysis to ethanol plant expansion decisions. The methodology used in the paper can be adapted by analysts, investors, and lenders in the ethanol industry to improve their investment analyses.

Reports the findings of a study which examined the attitudes of East and West German managers to the process of strategic industrial change following German reunification. Acknowledges the importance of organizational and national culture, specifically in relation to the process of strategic management, and notes a number of dissimilarities between the perceptions of the two nationalities towards the changes. Their perceptions provide an indicative insight into the combined organizational/national cultures within which each group was socialized. Makes suggestions for possible future research in this area.