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Adoption of Environment-Friendly Agricultural Practices with Background Risk: Experimental Evidence

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Abstract

Agriculture is one of the economic sectors most exposed to exogenous risks such as climate hazards and price volatility on agricultural markets. Agricultural policies targeting the adoption of environment-friendly but potentially risk-increasing practices cannot ignore this challenge. Farmers have indeed to decide if they take the foreground risk associated with the adoption of environment-friendly practices, while simultaneously facing exogenous background risk beyond their control. Using a theoretical model and a public good experiment, we analyse the adoption of agri-environmental practices and the effect of agri-environmental subsidies in a context where risks are both foreground and background. While most of the literature on background risk focuses on its impact on individual decisions, we analyse the influence of background risk in a context of strategic uncertainty (contribution to a public good). The results highlight the potential synergies between greening the CAP and supporting risk management. We find that background risk discourages the adoption of green practices, although it affects all farmland independently from the farmer’s choice of practices (environment friendly or conventional). An incentive payment per hectare of land farmed with green practices increases the adoption of risk-increasing practices but is significantly less effective in the presence of background risk.

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  1. While, in theory, agri-environmental measures aim at compensating the total costs of implementing environment-friendly practices, it is not always the case in practice. First, because it provides a fixed payment to farmers, calculated on the average costs in a given region. As a result, some farmers, facing higher costs, have no incentive to contract such measures. Second, because additional costs, such as transaction or learning costs, are not always accounted for in the design of the payments. This increases the total costs for farmers, who, in turns, have no incentive to engage in such contracts (Ducos et al. 2009; Espinosa-Goded et al. 2013). While this is an important barrier to agri-environmental measures adoption, this is not the main focus of our paper. Here, we only consider payments that cover the full costs of implementation.

  2. Laboratory and field experiments have been designed to test whether background risk affects the risk behavior of individuals. Laboratory experiments conducted by Lusk and Coble (2008), Lee (2008) and Beaud and Willinger (2014) concluded that an individual exposed to background risk (whether fair or unfair) would be willing to take fewer foreground risk. With regards to field experiments, Harrison et al. (2007) find that increasing background risk increases risk aversion in the US rare coins market. In contrast, Bchir and Willinger (2013) found that Peruvians living in high-risk areas (due to volcano mudflows) are less risk-averse than those living with lower background risk levels, but their result holds only for low income individuals (no significant results for higher incomes). Herberich and List (2012) carried out an experiment similar to that of Harrison et al. (2007) comparing US farmers and students, but they find no conclusive results regarding the impact of background risk on risk aversion.

  3. There are many different risk taxonomies in the agricultural economics literature [see OECD (2009) for a review of the different classifications of agricultural risks]. For example, one can distinguish between output and price uncertainty, sometimes including other sources such as technological or policy uncertainty (Moschini and Hennessy 2001). Another useful categorization in dynamic context is that of «non-embedded risks», i.e. risks that are beyond control of the decision maker because all decisions are made initially, versus «embedded risks», i.e. risks that can be influenced by farmers’ adaptive behaviour due to sequential decisions (Hardaker et al. 1991; Dorward 1999; Ridier et al. 2016). While both taxonomies are certainly relevant, we rely here on another one to distinguish between background risk (which is beyond farmers’ control and affects all crops) and foreground risk (which only affects crops grown according to environment-friendly practices: Farmers may therefore choose to avoid the foreground risk by not engaging in such practices).

  4. Indeed, most environment-friendly practices do not provide access to different prices for the products since they cannot be labelled or certified or are not well-known by the consumers (Bazoche et al. 2013). Moreover, there is no consensus on the impact of environment-friendly practices on yields and yields variability, notably because yield level has many determinants interacting with each other (Lechenet et al. 2017). Finally, CAP direct payments are paid whatever the choice of practices made by a farmer (as long as the land is maintained in good agricultural and environmental conditions and the three greening requirements are fulfilled).

  5. Coyle (1999), Isik (2002) Serra et al. (2006) and Bontems and Nauges (2019) have also analyzed farmers’ production decisions in a mean–variance framework in the context of multiple risks [including background risk for Bontems and Nauges (2019)]. Our contribution extends the analysis of production decisions in a risky environment to a public good game context.

  6. The assumption of quasi-concavity for \(V\left( {\mu ,v} \right)\) implies that the second order condition \(\partial^{2} U/\partial g_{i}^{2} < 0\) holds.

  7. This assumption is realistic since, in the current CAP, the payments associated with agri-environmental contracts are set-up to cover up the opportunity cost of adopting green practices. Concerning the green payment, while its level was not chosen to compensate the opportunity cost of adoption greening requirements, it has been shown that it is higher than the compliance costs for a large majority of farmers (Louhichi et al. 2018).

  8. While in reality the ecosystem services can benefit a larger perimeter where several farmers are operating, we have used the smallest possible group (2) to simplify the experiment. There is much literature on the effect of group size on contributions in public good games. For instance, Isaac and Walker (1988) found no difference between groups of 4 and groups of 10 people. To our knowledge, there is no experimental evidence on the differences in the behaviours of individuals interacting in pairs (in a prisoners’ dilemma) and in groups of 4 persons.

  9. In treatments ForeOnly and BackOnly, the table with the individual payoff had 2 lines corresponding to the two possible outcomes of the draw. While in treatment Fore&Back, the table had 4 lines, corresponding to the four different outcomes combining the two draws.

  10. The main advantage of using random effects over fixed effects estimations is that it allows for covariates that are constant over time, such as the individual characteristics of the participants (Demidenko 2005).

  11. Moreover, according to proposition 3 (see Appendix A3), the contribution to environment-friendly practices decreases when the covariance between both risks increases. We could therefore assume that the reduction of the contribution to environment-friendly practices in the treatment Fore&Back would be even more pronounced if the experiment had been designed with positively correlated risks.

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Acknowledgements

The survey on which this paper is based was funded by Angers University in the context of the Project “Verdissement de la politique agricole européenne: étude expérimentale des réactions des agriculteurs”. However, the views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the University. The authors would like to thank S. Blondel for his contribution to the experimental design, B. Goujon for programming the on-line survey, M. Ghali for recruiting the subject at Ecole Supérieure d’Agricultures d’Angers, C. Nauges, D. Bougherara, S. Thoyer and R. Préget for commenting a previous version of the article, and Olivier Midler for english proof reading. Estelle Midler acknowledge fundings from the Alexander Von Humboldt foundation in the framework of the Alexander Von Humboldt professorship endowed by the German federal ministry of research and education. Philippe Bontems acknowledges funding from ANR under Grant ANR-17-EURE-0010 (Investissements d’Avenir program).

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  1. GRANEM n° 7456, Université d′Angers, 49036, Angers, France

    Marianne Lefebvre

  2. Alexander von Humboldt-Professorship of Environmental Economics, Osnabrück University, 49069, Osnabrück, Germany

    Estelle Midler

  3. Toulouse School of Economics, INRAE, University of Toulouse Capitole, 31000, Toulouse, France

    Philippe Bontems

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Lefebvre, M., Midler, E. & Bontems, P. Adoption of Environment-Friendly Agricultural Practices with Background Risk: Experimental Evidence. Environ Resource Econ 76, 405–428 (2020). https://doi.org/10.1007/s10640-020-00431-2

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