The risks confronted by grain and cotton farmers are of particular interest, given the changing role of the Government after passage of the 1996 Farm Act. With the shift toward less government intervention in the post-1996 Farm Act environment, a more sophisticated understanding of risk and risk management is important to help producers make better decisions in risky situations and to assist policymakers in assessing the effectiveness of different types of risk protection tools. In response, this report provides a rigorous, yet accessible, description of risk and risk management tools and strategies at the farm level. It also provides never-before-published data on farmers' assessments of the risks they face, their use of alternative risk management strategies, and the changes they would make if faced with financial difficulty. It also compares price risk across crops and time periods, and provides detailed information on yield variability.

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Managing Risk in Farming: Concepts, Research, and Analysis

Precision agriculture (PA) technologies have been commercially available since the early 1990s. However, not only has the pace of adoption in the US been relatively modest but a surprisingly large number of producers are not familiar with these technologies. Using farm level survey data, this study quantifies the role that awareness plays in the decision to adopt PA technology and allows us to explore the potential for public or private information programs to affect the diffusion of PA. PA adoption and awareness are modeled as jointly determined dichotomous variables and their determinants are estimated using a two-stage (i.e. instrumental variable) logistic specification. The first-stage logit model indicated that operator education and computer literacy, full-time farming, and farm size positively affected the probability of PA awareness while the effect of age was negative. Grain and oilseed farms (i.e. corn, soybean, and small grains) and specialty crop farms (i.e. fruits, vegetables, and nuts) as well as farms located in the Heartland and Northern Great Plains regions were most likely to be aware of PA technologies. The second-stage PA adoption logit model, which included an instrumental variable to account for the endogeneity of awareness, revealed that farm size, full-time farming, and computer literacy positively influenced the likelihood of PA adoption. Grain and oilseed farms were the most likely types of farms to adopt PA as were farms in the Heartland region. Awareness, as defined in this study, was not found to be limiting the adoption of PA, suggesting that farmers for whom the technology is profitable are already aware of the technology and that a sector-wide public or private initiative to disseminate PA information would not likely have a major impact on PA diffusion.

Farm and operator characteristics affecting the awareness and adoption of precision agriculture technologies in the US

Supply chain risk management is a large and growing field of research. However, within this field, mathematical models for agricultural products have received relatively little attention. This is somewhat surprising as risk management is even more important for agricultural supply chains due to challenges associated with seasonality, supply spikes, long supply lead-times, and perishability. This paper carries out a thorough review of the relatively limited literature on quantitative risk management models for agricultural supply chains. Specifically, we identify robustness and resilience as two key techniques for managing risk. Since these terms are not used consistently in the literature, we propose clear definitions and metrics for these terms; we then use these definitions to classify the agricultural supply chain risk management literature. Implications are given for both practice and future research on agricultural supply chain risk management.

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Agribusiness supply chain risk management: A review of quantitative decision models

Recent developments in agriculture have stirred up interest in the concept of “sustainable” farming systems. Still it is difficult to determine the extent to which certain agricultural practices can be considered sustainable or not. Aiming at identifying the necessary attributes with respect to sustainability in Dutch dairy farming in the beginning of the third millennium, we first compiled a list of attributes referring to all farming activities with their related side effects with respect to economic, internal social, external social, and ecological sustainability. A wide range of people (i.e., experts and stakeholders) were consulted to contribute to our list of attributes. Our consultation showed that only one attribute was selected for economic and internal social sustainability: profitability and working conditions, respectively. The list for external social sustainability contained 19 attributes and the list for ecological sustainability contained 15 attributes. To assess their relative importance, the same experts and stakeholders ranked the attributes for external social and ecological sustainability by using a questionnaire. The most important attributes for external social sustainability were food safety, animal health, animal welfare, landscape quality, and cattle grazing. For ecological sustainability they were eutrophication, groundwater pollution, dehydration of the soil, acidification, and biodiversity. The present method for identifying and ranking attributes is universal and, therefore, can be used for other agricultural sectors, for other countries, and for other time periods.

Identifying and ranking attributes that determine sustainability in Dutch dairy farming

Costs and benefits of livestock systems and the role of market and nonmarket relationships

Financial management in agriculture.

limiting the business risk to which farmers are exposed. Some approaches to business risk modification involve insurance, government programs, weather modification, and innovations of individual farmers: technological, to limit the probability of disease and insect damage; and market, to limit the probability of adversity through price fluctuations. It is recognized that the introduction or modification of risk in the production process affects the pattern of resource allocation and in turn the level of production (Dillon, pp. 102-48, Just, Wiens, and Wolgin). We suggest that there is also a financial response to business risk modification. The differentiation is important in that business risk and financial risk may well be trade-offs in the risk behavior of farmers. Thus, a decline in business risk would lead to the acceptance of greater financial risk, reducing the effects of the diminished business risk on total risk.

Concepts of Business and Financial Risk

Credit risks are unanticipated variations in costs and availability of credit that arise from forces in financial markets or from lenders' responses to risks in agricultural markets and farmers' creditworthiness. An extension of mean-variance portfolio theory shows how credit risks combine with other financial and business risks to determine total risk. Empirical evidence from lender surveys about risks shows that farmers' credit is positively correlated with changes in farm income, although the correlation is stronger for capital credit than for operating credit, and that variability in fund availability from rural banks has contributed to high credit risks.

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Farmers' Credit Risks and Liquidity Management

This paper uses quadratic programming to calculate the variance-efficient mean income path and associated lower income bounds and suggests a way to select an optimum farm plan under risk based on the farmer's own self-assessed income-risk preference function. An empirical example from a Midwest corn-soybean farm is presented.

A Practical Way to Select an Optimum Farm Plan Under Risk

EACH firm has a financial component as well as nonfinancial components The financial component includes claims held and debts owed, values reported in a balance sheet of the firm A less evident part of the financial component is liquidity of the firm: access to financial assets and terms on which such access may be gained Profit-seeking managers are willing to pay for liquidity in more or less tangible terms The most tangible, perhaps, is found in insurance The second is in choices made that favor liquid relative to illiquid assets and flexibly managed debts relative to inflexible debt commitments A third is in reservation of "credit"-credit defined as the capacity to borrow Unused credit, like balance sheet assets that are liquid, constitute a reserve of liquidity that can be called upon to counter the effects of failure in expectations Though not included in the balance sheet, liquidity also has value In this article, I outline the effects of liquidity value, in the form of "credit," on production organization of the firm and stress the fact that the values are attached to the unused portion of "credit" To exchange credit for a loan generates a cost in the tangible form of interest The exchange also entails a loss of liquidity How costly it is to lose liquidity depends upon the total credit available to the entrepreneur and alternative sources of liquidity In any event, I argue that "credit" is an asset which can be managed-made to grow, decline, and change in structureand that the results are important for production organization of the firm t Ideas contained in this article were assembled in seminars which I conducted at the Universities of Sydney, Melbourne, Adelaide, and Western Australia (Perth) and Australian National University in 1967 However, their origin is in research conducted earlier at the University of Illinois Thanks are due especially to G D Irwin, D E Neuman, and L F Rogers for early testing of the utility of the notion of lender preferences and to staff and students at the various universities for criticisms on the broader frame of reference in which this article is cast Finally, I am grateful for comments from two anonymous Journal reviewers

C. B. Baker

Papers

Financial management in agriculture.

Concepts of Business and Financial Risk

Farmers' Credit Risks and Liquidity Management

A Practical Way to Select an Optimum Farm Plan Under Risk

Credit in the Production Organization of the Firm