Production risk,risk aversion and the determination of risk attitudes among Spanish rice producers

Agricultural production is subject to risk and the attitudes of producers toward risk will influence input choices insofar as these affect production risk. Risk attitudes in turn may be affected by certain socioeconomic characteristics of producers. Using 2004 survey data from a cross‐section of 130 Spanish rice farms, we estimate risk‐aversion coefficients of farmers and investigate the influence of a series of socioeconomic variables on their risk attitudes. Our results show that farmers exhibit risk‐averse behavior and that risk attitudes are related to a series of socioeconomic characteristics. In particular, the belief that the farm will continue after the producer retires is found to increase the degree of risk aversion, while age is found to have nonlinear effects on risk aversion. Off‐farm income, especially from nonagricultural activities, is found to reduce risk aversion. Neither the educational level of the producer nor the presence of dependents on the household is found to have an effect on risk preferences. Regarding the production technology, we find that land, labor, and fitosanitary products are risk‐reducing inputs, whereas capital, seeds, and fertilizer all increase risk.     

AN APPROACH TO THE ECONOMETRIC ESTIMATION OF ATTITUDES TO RISK IN AGRICULTURE*

A simple model is developed relating the debt and asset portfolio of the farm to the production decision, which leads to a small non-linear system of equations. The system is estimated with time-series cross-sectional data from Australian broadacre agriculture using non-linear three-stage least squares. This gives a new method of estimating risk aversion coefficients by using actual behaviour of farmers in a realistic economic environment, rather than games played in artificial situations. Australian farmers are found to be risk averse, and the partial coefficient of risk aversion decreases with wealth and increases with income. The results are consistent with the results of studies by Binswanger in India and elsewhere using a completely different method. This consistency suggests that the partial risk aversion coefficient is a relatively robust measure of attitudes to risk.     

Introducing socioeconomic characteristics into production analysis under risk

A theoretical framework is developed to study the effects of socioeconomic factors on farmers' risk attitudes and production decisions. No maintained assumptions about the individual's utility are required. A key element in this framework is the categorization of socioeconomic factors by their effect on the farmer's risk attitudes. A simple methodology for this categorization, based on the equivalence between the Arrow–Pratt measure of risk aversion and the probability of winning demanded, is proposed. The latter is illustrated with data collected in a survey of 180 Israeli farmers from 20 villages.     

The effects of EU agricultural policy changes on farmers' risk attitudes

This analysis utilises a model of production under risk estimatedon Finnish farm-level data to measure farmers' risk attitudesin a changing policy environment. We find evidence of heterogeneousrisk preferences among farmers, as well as notable changes overtime in farmers' degree of risk aversion. This result is dueto the increase in the non-random part of farm income generatedby the policy change after Finland's European Union accession.The analysis confirms the assertion that agricultural policiesthat are decoupled from production do affect input use and cropmix through their effect on farmers' risk attitudes.     

Managing basis risk with multiscale index insurance

Agricultural index insurance indemnifies a farmer against losses based on an index that is correlated with, but not identical to, her or his individual outcomes. In practice, the level of correlation may be modest, exposing insured farmers to residual, basis risk. In this article, we study the impact of basis risk on the demand for index insurance under risk and compound risk aversion. We simulate the impact of basis risk on the demand for index insurance by Malian cotton farmers using data from field experiments that reveal the distributions of risk and compound risk aversion. The analysis shows that compound risk aversion depresses demand for a conventional index insurance contract some 13 percentage points below what would be predicted based on risk aversion alone. We then analyze an innovative multiscale index insurance contract that reduces basis risk relative to conventional, single‐scale index insurance contract. Simulations indicate that demand for this multiscale contract would be some 40% higher than the demand for an equivalently priced conventional contract in the population of Malian cotton farmers. Finally, we report and discuss the actual uptake of a multiscale contract introduced in Mali.     

Farmers’ risk preferences and pesticide use decisions: evidence from field experiments in China

China faces health and environmental problems associated with the use of agricultural chemicals, including pesticides. While previous studies have found that risk aversion affects pesticide use in China, they have focused primarily on commercial cotton farmers. In this study, we consider the case of smaller, semisubsistence and subsistence farmers in a poor and landlocked province of China (Yunnan). We use a field experiment to measure risk aversion and collect detailed data on farm production and input use to specifically ask whether risk aversion affects pesticide use, and whether this effect differs for subsistence farmers producing exclusively for home consumption versus semisubsistence farmers who produce both for home and the market. We find that risk aversion significantly increases pesticide use, particularly for subsistence farmers and for market plots by semisubsistence farmers. Further, this effect of risk aversion significantly decreases with farm size for subsistence farmers, but not for semisubsistence farmers, implying that pesticide use may be used to ensure sufficient food supply for home consumption. Finally, we find barriers to the use of pesticides for subsistence farmers, both in terms of financial constraints and economies of scale. This finding implies that risk‐mitigation strategies, such as crop insurance, may not target food security concerns of subsistence farmers. Given these different motivations for pesticide use, policymakers may wish to consider effective tools to support rural food security for farmers in the poorer regions of China in order to decrease pesticide use.     

Estimation and use of risk aversion coefficient for traditional dryland agriculture in western Sudan

This paper explores the importance of including risk when modeling subsistence-oriented agriculture in a developing nation. The specific objective is to measure the degree of risk aversion for typical farmers in the smallholder traditional agriculture of the Sudan. The procedure followed is to impute the farmer's risk aversion coefficient through a mathematical risk programming technique. Imputed farmers' risk aversion coefficients were used to validate the model specified and identify, for further analysis, a single risk optimal farm plan for each of the different farm situations studied.     

Potential demand for hedging by Australian wheat producers

The potential for hedging Australian wheat with the new Sydney Futures Exchange wheat contract is examined using a theoretical hedging model parametised from previous studies. The optimal hedging ratio for an ‘average’ wheat farmer was found to be zero under reasonable assumptions about transaction costs and based on previously published measures of risk aversion. The estimated optimal hedging ratios were found by simulation to be quite sensitive to assumptions about the degree of risk aversion. If farmers are significantly more risk averse than is currently believed, then there is likely to be an active interest in the new futures market.     

Risk-Taking Preferences of Farmers in Northern Thailand: Measurements and Implications

Risk-taking preferences were elicited from small semi-commercial farmers in Northern Thailand using an experimental procedure that included real monetary payoffs of meaningful magnitudes. A total of five sets of lotteries with increasing payoffs were offered. The farmers were found to be risk averters, and their preferences conformed to the hypothesis of increasing (nondecreasing) partial relative risk aversion. Using regression analysis, farmers' expected variation of rice yields and farm size were found to be directly related to a decrease in risk aversion, while the extent of multiple cropping, availability of non-land household assets, and tested mathematical ability were found to be indirectly related to a decrease in risk aversion. The variables expected variation of rice prices, farmers' age, and tested abstract ability scores were not related to risk-taking preferences.     

Are we risking too much? Perspectives on risk in farm modeling

Risk and uncertainty have been extensively studied by agricultural economists. In this paper we question (a) the predominant use of static frameworks to formally analyse risk; (b) the predominant focus on risk aversion as the motivation for considering risk and (c) the notion that explicitly probabilistic models are likely to be helpful to farmers in their decision making. We pose the question: for a risk‐averse farmer, what is the extra value of a recommendation derived from a model that represents risk aversion, compared to a model based on risk neutrality? The conclusion reached is that for the types of the decision problems most commonly modelled by agricultural economists, the extra value of representing risk aversion is commonly very little.     

Should farmers invest in financial assets as a risk management strategy? Some evidence from New Zealand*

This study explores the potential for risk reduction by New Zealand farmers through the diversification of their farm asset portfolios to include financial investments such as ordinary industrial shares, government bonds and bank bills. Low correlations between rates of return on farm and these financial assets suggest that significant reduction of income variability might follow their inclusion in farmers’ portfolios. Stochastic efficiency analysis is used to analyse alternative portfolios of ordinary shares, government bonds and bank bills and New Zealand farmland, using coefficients of absolute risk aversion derived from a negative exponential utility function. The results suggest that those farmers showing high degrees of risk aversion would gain utility by including financial assets in their portfolios. Deregulation of the New Zealand economy in the 1980s appeared to reduce the potential gains from diversification. Bonds rather than ordinary shares are the main contributors to portfolios which maximise utility for individuals classified as ‘somewhat’ risk averse.     

Comparing risk attitudes of organic and non-organic farmers with a Bayesian random coefficient model

Organic farming is usually considered to be more risky thanconventional farming, but the risk aversion of organic farmerscompared with that of conventional farmers has not been studied.Using a non-structural approach to risk estimation, a Bayesianrandom coefficient model is used to obtain individual Arrow–Prattcoefficients of absolute risk aversion for a sample of Dutchorganic and non-organic arable farmers. The model is estimatedusing Gibbs sampling. The results indicate that organic farmersare significantly less risk averse than their non-organic colleagues.     

Estimation of farmers' risk attitude: an econometric approach

An econometric procedure for estimating Arrow-Pratt coefficients of risk aversion is derived. The model of farmers allocating land among different crops, and time between leisure and labor, allows for testing Arrow's hypotheses of decreasing absolute risk aversion and increasing relative risk aversion. The empirical results support these hypotheses.     

Risk, uncertainty, and learning in adoption of a crop innovation

Risk and uncertainty have often been suggested as causes of poor adoption of rural innovations, but empirical evidence has been scarce. This study focuses on a new crop‐type, chickpeas, in Western Australia to gather such evidence. The empirical models developed are based on a theoretical framework that conceptualizes adoption as a dynamic decision process involving information acquisition and learning‐by‐doing by growers who vary in their managerial abilities, risk preferences, and their perceptions of the profitability and riskiness of the innovation. Learning encompasses improvements in skill as well as reductions in uncertainty. An annual face‐to‐face survey of over 100 farmers was conducted over 3 years, eliciting the farmers' risk attitudes and their subjective distributions of yields and prices. Two limited dependent variable models, Tobit and Probit, are used to estimate the empirical model. There is a high degree of goodness‐of‐fit for both models. The study provides strong empirical support for the primarily economic character of the adoption decision, and highlight the importance of economic risk in the process. The two risk‐related factors with greatest impact on the adoption decision were risk aversion and relative riskiness of the innovation. Risk aversion tended to reduce adoption, and to do so to a greater extent as relative riskiness and scale increased. Results also reveal the key role that trialing of the innovation plays in adoption.     

A NOTE ON DECREASING ABSOLUTE RISK AVERSION AMONG FARMERS IN NEPAL

Attitudes toward risk are explored for a sample of rice growers on small farms in Nepal, in the context of the subjective expected utility maximisation model. Farmers are found to be generally averse to risk, with diverse levels of absolute risk aversion that tend to diminish as wealth increases, both for individuals and in a cross-sectional sense. Relative risk aversion is argued to be the most comparable measure for contrasts of attitudes toward risk.     

Sustainable agricultural practices,environmental risk mitigation and livelihood improvements: Empirical evidence from Northern Ethiopia

Using sustainable agriculture practices has various economic, social and environmental benefits. Determining the attitude of farmers toward risk is an important first step in understanding their behaviour and coping strategies to mitigate environmental risks. This paper investigates the dual impacts of some agricultural practices on agricultural yields and farmers’ livelihoods considering sustainable farmland. Cross-sectional data is collected from farmers in six rural villages in Tigray region, Northern Ethiopia using structured questionnaires. Results show that education, labour supply, agricultural extension services, attitudes, social capital, risk mitigation attitudes, farming experience and soil conditions are factors that significantly affect farmers’ decisions to adopt these practices. The practices are adopted either in isolation or jointly of integrated sustainable practices that increase crop production, household income and asset. Therefore, government and other development actors should promote their adoptions especially in drought-prone, degraded and water-stressed areas     

Risk aversion in agricultural water management investments in Northern Ghana: experimental evidence

Sub‐Saharan Africa (SSA) is one of the regions in the world most affected by food price volatility and production variability. Poor small‐scale farmers in this region are particularly vulnerable to this variability. As a result, households may be reluctant to adopt new agricultural water management (AWM) technologies when they involve more risk than what they mitigate. Despite risk's role in AWM investments, there have been few attempts to estimate the magnitude and nature of risk aversion in relation to this type of farm decisions. To partially close this gap, this article uses an experimental approach applied to 137 households in Northern Ghana. We find that more than 70% of households are moderately or slightly risk averse. This contrasts with other studies in SSA, where most household decision‐makers exhibit severe to extreme risk aversion. We also find that households that stand to lose as well as gain something from participation in games are less risk averse than households playing gains‐only games. This result suggests that most farmers’ current wealth put them at risk of falling into a poverty trap. Thus, the losses from the riskiest investments on AWM technologies may fall more heavily on the poor, suggesting that additional efforts be given to the creation of viable insurance mechanisms.     

More reasons why farmers have so little interest in futures markets

The use by farmers of futures contracts and other hedging instruments has been observed to be low in many situations, and this has sometimes seemed to be considered surprising or even mysterious. We propose that it is, in fact, readily understandable and consistent with rational decision making. Standard models of the decision about optimal hedging show that it is negatively related to basis risk, to quantity risk, and to transaction costs. Farmers who have less uncertainty about prices and those with a diversified portfolio of investments have lower optimal levels of hedging. If a farmer has optimistic price expectations relative to the futures market, the incentive to hedge can be greatly reduced. And finally, farmers who have low levels of risk aversion have little to gain from hedging in terms of risk reduction, in that the certainty‐equivalent payoff at their optimal hedge may be little different than the certainty equivalent under zero hedging. These reasons are additional to the argument of Simmons (2002) who showed that, if capital markets are efficient, farmers can manage their risk exposure through adjusting their leverage, obviating the need for hedging instruments.     

Assessing farmers’ risk preferences and their determinants in a marginal upland area of Vietnam: a comparison of multiple elicitation techniques

We examine the consistency of risk preference measures based on eight hypothetical elicitation methods and a lottery game applied to smallholder farmers in a marginal upland environment in Vietnam. Using these measures, we identify influencing factors of risk aversion via regression analysis, whereby unlike previous studies, we include several proxies of social capital such as social networks and norms. Data were collected from household heads and spouses separately in a random sample of 300 households. Although correlations between most of the various risk preference measures are all statistically highly significant, most are weak. On average, respondents have a high degree of risk aversion and specific characteristics—gender, age, idiosyncratic shocks, education, social norms, network‐reliance with extended family, and connections to local authorities—are significant determinants of risk preferences across most elicitation methods, whereas others—the household's dependency ratio, wealth, and covariate shocks—are significant in a few methods only. The explanatory power of the models is limited, indicating that other factors are likely to be of greater importance in determining risk preferences. The results can help target safety nets, encourage investments, and lead to the development of more applicable methods for assessing risk preferences of smallholders in developing countries.     

Estimating Technical Efficiency and Production Risk under Contract Farming: A Bayesian Estimation and Stochastic Dominance Methodology

We investigate production risk, technical efficiency and risk attitudes amongst contract and independent farmers. We use a Bayesian parametric approach and stochastic dominance quantile regression methods to compare technical efficiency and risk attitude of smallholders in Nepal. Using farm‐level data, we find that contract farmers appear to show lower inefficiency and lower production risk. Additionally, contract and independent farmers can increase output by reducing the scale of operation. Regardless of the commodity produced and farming arrangement (contract or independent production), we find that labour, land and other inputs are risk‐augmenting, while the role of capital is mixed. We find a second order stochastic dominance (SSD) for lentils, and first order stochastic dominance (FSD) for tomatoes, ginger and HYV paddy seed commodities. Finally, contract farmers are more risk averse than independent farmers, regardless of the commodity produced.