On Crop Biodiversity, Risk Exposure, and Food Security in the Highlands of Ethiopia

This paper investigates the effects of crop genetic diversity on farm productivity and production risk in the highlands of Ethiopia. Using a moment-based approach, the analysis uses a stochastic production function capturing mean, variance, and skewness effects. Welfare implications of diversity are evaluated using a certainty equivalent, measured as expected income minus a risk premium (reflecting the cost of risk). We find that the effect of diversity on skewness dominates its effect on variance, meaning that diversity reduces the cost of risk. The analysis also shows that the beneficial effects of diversity become of greater value in degraded land.     

Self‐protection from weather risk using improved maize varieties or off‐farm income and the propensity for insurance

We investigate how self‐protection from the adoption of Improved Maize Varieties (IMV) and off‐farm income affects risk premiums for smallholder maize producers in Uganda. To unbundle these effects, we specify the cost of risk to explicitly capture four risk components—mean, variance, skewness, and kurtosis. Using unique plot‐level panel data for Uganda, we estimate and test moments of a flexible production function based on an expanded form of the Johnson S_U family distribution and proceed to simulate the degree of responsiveness of risk premiums and welfare estimates to marginal changes in the share of land under IMV and off‐farm income. Scenarios of joint adoption of IMV accompanied with low and high application of inorganic fertilizer, and the effect of off‐farm income when there is high and low supply of farm labor are examined. Results show that the use of IMV and off‐farm income substantially reduces risk premiums and the individual effect is much higher under low fertilizer application and high supply of farm labor, respectively. Thus implying that self‐protection is likely to reduce the propensity for index insurance especially if its design fails to consider the reduction in downside risk.     

Technological change and risk management: an application to the economics of corn production

The paper investigates the linkages between technological change and production risk, with an application to corn. The effects of technology on risk exposure are analyzed. We define technological progress to be risk‐increasing (risk‐decreasing) if it increases (decreases) the relative risk premium. The analysis is applied to panel data from Wisconsin research stations. Conditional moments (including mean, variance and skewness) of corn yield, grain moisture and corn profit are estimated for different sites. We investigate how the trade‐off between expected return and the risk premium varies over time and over space. The empirical results indicate that technological progress contributes to reducing the exposure to risk as well as downside risk in corn production, although this effect varies across sites. They also stress the role of the relative maturity of corn hybrids as a means of managing risk.     

The Determinants of Firm Profitability Differences in EU Food Processing

This paper decomposes the variance in EU food industry return‐on‐assets into year, country, industry and firm effects using a hierarchical linear model (HLM). The HLM approach accounts for some of the methodological drawbacks of conventional approaches of variance decomposition such as anova and components of variance and additionally allows the estimation of the impact of covariates within each effect level. The results for selected EU countries show that firm effects are far more important than industry structure in determining food industry profitability. In particular, firm size and industry concentration are drivers of profitability while firm risk and age as well as industry growth have a negative influence.     

Mitigating rice production risks from drought through improving irrigation infrastructure and management in China

Rice, China's most important food crop, is highly dependent on irrigation, but an increasing number of extreme drought events have challenged rice production in many regions. This paper investigates the role of local irrigation infrastructure in improving farmers' ability to respond to drought and its effectiveness in mitigating the drought risk in rice production in China. The analysis relies on a moment‐based specification of the stochastic production function, capturing mean, variance and skewness effects. Using household survey data from 86 villages in five provinces, we jointly estimate farmers' adaptive irrigation decisions and their effects on rice yield and production risk. Our econometric analyses show that irrigation infrastructure in villages contributes to enhancing farmers' irrigation capacity in adapting to drought, and increased irrigation leads to a significant increase in mean yield and a reduction in exposure to risk as well as downside risk in rice production. The paper concludes with policy implications.     

Risk and marketing behavior: pricing fed cattle on a grid

A seven‐year comparative study of grid pricing versus average pricing of slaughter cattle was conducted to evaluate carcass quality market signals. The primary objectives of the study are to determine: (1) if market signals sent through the grid pricing system indicate an improvement in the grid incentive mechanism over time, (2) how changes in the grid premium and discount structure associated with carcass quality affect the market risk premium, and (3) if changes in price risk (variance) affect producer marketing decisions. An Exponential‐Autoregressive‐Conditional‐Heteroskedasticity‐in‐Mean (EARCH‐in‐Mean) modeling procedure was adopted. Empirical results suggest that the grid premium and discount structure is slowly adjusting carcass quality market signals to encourage marketing on a grid and discourage marketing by the pen. The inclusion of the conditional variance in the empirical model indicates that variance associated with the carcass quality risk premium adds financial risk associated with the adoption of grid pricing.     

Modelling outcome‐related risk in choice experiments

In this study, we introduce information on outcome‐related risk as an additional attribute in a choice model of preferences for a land‐based climate change mitigation project. We provide a comprehensive comparison of different model specifications arising from different behavioural assumptions about the way that respondents process information on outcome‐related risk within the choice task. We find significant differences between several specifications in terms of both model fit and WTP estimates. The behavioural assumptions made when choosing a particular model specification, and reasons that motivate them should be made explicit, and consequences of using different specifications should not be ignored.     

Valuing options for reserve water in the Fitzroy Basin*

Option values may be an important component of non‐use values when development options for environmental assets are considered. These are values that the community might hold for maintaining options to make future choices about allocating resources. However, option values are very difficult to define, at both theoretical and practical levels, and there has been a retreat over the past decade to the more inclusive concept of option prices. In the present paper, estimates of option values are reported for retaining unallocated water in reserve rather than using it for current development. The use of option values rather than option prices is justified on the basis that the focus is on non‐use values, and demand and supply uncertainties have been minimised. These values have been assessed through a series of nine choice modelling surveys that have been conducted over a 3‐year period in the Fitzroy River Basin in central Queensland. The results are then extrapolated to the case study areas within the basin to assess whether unallocated water should be held in reserve or used for development.     

Worth the Risk? The Behavioural Path to Well‐Being

There is increasing interest in the ‘economics of happiness’, reflected in the volume of articles appearing in mainstream economics journals exploring the major determinants of self‐reported well‐being. We contribute by exploring the factors influencing how satisfied farmers are with their quality of life. We find that farm income, subjective perceptions relating to the adequacy of household income, debt, health and personal characteristics such as age and relationship status are significantly associated with farmers’ self‐reported life satisfaction. While significantly associated with farm income, farm structural variables such as farm size, farm type and the presence of a farm successor were not found to be significantly related with life satisfaction. Our results also suggest that farmers who are more risk averse enjoy significantly lower levels of both life satisfaction and farm income than their more risk seeking or risk neutral counterparts. We suggest that, in the same way that risk aversion inhibits farmers from making choices that could lead to an increase in their income, it may also constrain farmers (and the wider public at large) from engaging in certain types of behaviours that could lead to an increase in their self‐reported quality of life. Finally, we find that while farm income is significantly related to self‐reported life satisfaction, the direct correlation between these variables is weak, suggesting that farmer life satisfaction can be distinct from business success.     

On the Role of Risk Versus Economies of Scope in Farm Diversification With an Application to Ethiopian Farms

This article investigates the economics of farm diversification. The analysis assesses economies of diversification using a certainty equivalent measure. It identifies two components: one associated with expected income, and one associated with risk exposure. This integrates two lines of research explored in previous literature: economies of scope and risk management. We examine the roles played by complementarity, scale and concavity effects in economies of diversification. The approach is applied to diversification decisions made on Ethiopian farms, with a focus on production uncertainty. The econometric analysis finds large complementarity benefits, providing incentives to diversify. But this is tempered by (non)‐concavity effects that provide incentives to specialise. The analysis also documents how risk affects diversification, including both variance and skewness effects. It provides new insights on economic tradeoffs between farm diversification and specialisation.     

Evaluating the Potential of Index Insurance Schemes to Reduce Crop Yield Risk in an Arid Region

We evaluate yield risk reduction through weather index, area yield index and farm yield insurance contracts for wheat farms in Kazakhstan by employing data from 1980 to 2002. We use the usual mean variance (MV) approach and also a second‐degree stochastic dominance (SSD) criterion. While MV is not necessarily consistent with the expected utility (EU) theory, SSD results only in a minimum but EU‐consistent benefit from insuring. Differences in the estimation results for both approaches underline the advantage of applying both criteria to analyse the risk‐reducing potential of crop insurance. Bootstrapping results show that none of the analysed insurance schemes provides statistically significant risk reduction for every single farm. In addition, weather‐based index insurance is found to provide less risk reduction than area yield insurance based on the rayon (county) yield. Moreover, rayon yield index insurance can reduce yield risk more effectively for Kazakhstan's wheat producers than farm yield insurance with a low strike yield.     

Adoption of climate‐smart practices and its impact on farm performance and risk exposure among smallholder farmers in Ghana

Increased climate variability during the last four decades has made the agricultural environment in many developing countries more uncertain, resulting in increasing exposure to risk when producing crops. In this study, we use recent farm‐level data from Ghana to examine the drivers of individual and joint adoption of crop choice and soil and water conservation practices, and how adoption of these practices impacts on farm performance (crop revenue) and exposure to risks (skewness of crop yield). We employ a multinomial endogenous switching regression model to account for selectivity bias due to both observable and unobservable factors. The empirical results reveal that farmers’ adoption of crop choice and soil and water conservation leads to higher crop revenues and reduced riskiness in crop production, with the largest impact on crop revenues coming from joint adoption. The findings also show that education of the household head, access to extension and weather information influence the likelihood of adopting these practices. Thus, enhancing extension services and access to climate information and irrigation can reduce gaps in adoption of soil and water conservation and crop choice, considered as climate‐smart practices that will eventually improve crop revenues and reduce farmers’ exposure to climate‐related production risks.     

Warming temperatures will likely induce higher premium rates and government outlays for the U.S. crop insurance program

Likely climate change impacts include damages to agricultural production resulting from increased exposure to extreme heat. Considerable uncertainty remains regarding impacts on crop insurance programs. We utilize a panel of U.S. corn yield data to predict the effect of warming temperatures on the mean and variance of yields, as well as crop insurance premium rates and producer subsidies. While we focus on corn, we demonstrate that the subsidy impacts are likely to carry over to other major program crops. We find that warming decreases mean yields and increases yield risk on average, which results in higher premium rates. Under a 1°C warming scenario, we find that premium rates at the 90% coverage level will increase by 39% on average; however, there is considerable statistical uncertainty around this average as the 95% confidence interval spans from 22% to 61%. We also find evidence of extensive cross‐sectional differences as the county‐level rate impacts range from a 10% reduction to a 63% increase. Results indicate that exposure to extreme heat and changes in the coefficient of variation are large drivers of the impacts. Under the 1°C warming scenario, we find that annual subsidy payments for the crop insurance program could increase by as much as $1.5 billion, representing a 22% increase relative to current levels. This estimate increases to 3.7 billion (57%) under a 2°C warming scenario. Our results correspond to a very specific counterfactual: the marginal effect of warming temperatures under current technology, production, and crop insurance enrollments. These impacts are shown to be smaller than the forecasted impacts under a commonly used end‐of‐century general circulation model for even the most optimistic CO₂ emissions projection.     

Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates

Accurate modeling of skewness is needed to increase the actuarial fairness of crop insurance. We test Day's conjecture that crop yield skewness becomes negative as nitrogen rates increase and determine how well a linear response stochastic plateau (LRSP) production function matches the pattern of observed skewness using four long‐term nitrogen experiments. Stillwater wheat is consistent with Day's conjecture, but the skewness for Lahoma and Altus wheat yields as well as Altus cotton yields are not. The LRSP assumes normal random effects and can explain only a small part of observed skewness, so a new LRSP with skew‐normal random effects is introduced, which comes closer to explaining the observed skewness and should increase the accuracy of nitrogen rate recommendations. Negative skewness reduced optimal nitrogen rates and positive skewness increased optimal nitrogen rates.     

Myopia and saliency in renewable resource management

An important challenge in managing renewable resources is to understand why owners and managers sometimes make decisions that deplete resources and future earnings, such as when graziers allow pastures and land condition to be degraded. In this paper, we test two potential reasons for unsustainable management practices, myopia and salience, with each explaining why resource managers may exhibit impatience in harvest decisions. Myopia is associated with decision makers placing lower weight on future outcomes than would be implied by their pure time preference. Salience is associated with overweighting of consumption ‘now’, implying inconsistency in time preferences. To test for these effects on renewable resource management, an incentivised, dynamic field experiment was carried out with rangeland grazing enterprise owners in north‐eastern Australia that related management choices with uncertain rainfall events to both profits and land condition over time. Results demonstrate that respondents exhibiting myopia/salience in their choices tended to achieve lower cumulative scores in the experiment, as well as lower land conditions on their properties as measured with remote sensing data. Our results explain why there may be persistent optimisation failures by resource owners that reduce both profits and environmental outcomes.     

An Empirical Examination of the Timing of Land Conversions in the Presence of Farmland Preservation Programs

Using a panel of parcel-level data we estimate a hazard model and find strong evidence that the mere existence of an option to preserve farmland delays decisions to convert farmland to developed uses by about six years, a reduction in median conversion time of 12 to 43% depending on parcel size. Where such delays allow local governments to improve infrastructure or implement stricter growth control measures, benefits of a preservation option may be even more long term. Also, increases in the variance of returns to development tended to slow conversion for parcels with all but the highest lot capacities.     

Use of Compliance Rewards in Agri‐environmental Schemes

Ensuring that farmers comply with the terms of agri‐environmental schemes is an important issue. This paper explores the use of a ‘compliance–reward’ approach under heterogeneous net compliance costs with respect to cost‐share working lands programmes such as the Environmental Quality Incentives Program (EQIP) in the United States. Specifically, we examine the use of a reward under asymmetric information and output price uncertainty. We examine two possible sources of financing under the assumption of budget neutrality: (i) funds obtained by reducing monitoring effort; and (ii) money saved by reducing the number of farmers enrolled. We discuss the advantages and disadvantages of each source of funding and analyse these numerically for both risk‐neutral and risk‐averse farmers. We also examine the trade‐off between increased expenditure on monitoring effort and compliance rewards when additional budgetary resources are available. We show that under certain conditions a compliance reward can increase compliance rates. For risk‐averse farmers, however, conditions that ensure a positive outcome become more restrictive.     

A Composed-Error Model for Estimating Pest-Damage Functions and the Impact of the Western Corn Rootworm Soybean Variant in Illinois

We describe a composed-error model for estimating pest-damage functions. The composed-error model, originally developed to account for statistical noise when estimating technical efficiency, removes the effect of experimental errors when estimating the variance of yield loss from pest damage. As a result, the estimated variance of yield loss is often less than for a conventional model, which has economic implications when the analysis incorporates risk aversion. We find that, depending on the level of risk aversion, the western corn rootworm soybean variant reduces farmer certainty-equivalent returns 16–26% more with a conventional model than with the composed-error model.     

Depressed demand for crop insurance contracts,and a rationale based on third generation Prospect Theory

When actuarially fair insurance for a major risk is available then standard economic theory posits that those subject to the risk should insure. In agriculture, it is common for producers to decline contract offers where presubsidy premiums just cover average losses and subsidies are substantial. This paper seeks to shed light on why demand is curtailed. In a mail survey of U.S. corn and soybean producers we solicited Willingness to Pay (WTP) for actuarially fair insurance at different coverage levels. We find demand to be so low that median WTP is no larger than fair premium when adjusted down by current subsidy rates, which pay for one half or more of most premium charges. WTP as a share of the fair rate is especially low when risk of loss is high. There is limited evidence that respondents appreciate the convex relationship between coverage level and expected indemnity payoff. Third generation Prospect Theory is shown to be consistent with observed findings. In particular, a strong distaste for paying premium can be rationalized by loss aversion. Furthermore, when high revenue outcomes are more likely than not, that is, negative skewness, then higher loss aversion, greater decision weight distortions and greater risk aversion will decrease WTP.