Towards a holistic approach to sustainable risk management in agriculture in the EU: a literature review

From Firenze University Press Journal: Bio-based and Applied Economics (BAE)

Linda Arata, Università Cattolica Del Sacro Cuore, Piacenza, Italy

Simone Cerroni, University of Trento, Trento, Italy

Fabio Gaetano Santeramo, University of Foggia, Foggia, Italy

Samuele Trestini, University of Padova, Padova, Italy

Simone Severini, Università degli Studi della Tuscia

Although risk concerns all economic activities, agriculture is one of the most concerned sectors, due to its exposure to a plethora of risky phenomena such as weather, pests and diseases, changes in prices and government poli-cies, instability of global markets, and other factors (Moschini and Hennessy, 2001; Hardaker et al., 2015; Komarek et al., 2020). Furthermore, the multi-faceted risks farmers must cope with are very likely to occur simultaneously, producing a compounded negative effect (Hardaker et al., 2004).Risk in agriculture causes wide volatility in farmers’ income and well-being and in turn it influences the decision-making process. Experiencing negative events reduces farmers’ willingness to invest and innovate (Sckokai and Moro, 2009). This, in turn, may negatively affect farms’ productivity and competitiveness (Vigani and Kathage, 2019) and push farms out of the business. The negative consequences may also be reflected in the value chain (Cafiero, 2008) and transferred to all stakeholders of the agro-food sys-tem. Major and unexpected events such as the COV-ID-19 pandemic and the food/energy crises induced by the war in Ukraine have unrevealed the vulnerability of the global food supply. By threatening the status of global food security, these major shocks have induced unprecedented policy responses in all advanced econo-mies, as well as in developing countries (European Par-liament, 2022; OECD, 2020; Santeramo and Kang, 2022). Over the years, risk in agriculture has been increasing in width and depth, unveiling the need for improving Risk Management (RM), as recognized by the Euro-pean Commission (2017) “[…] it is important to set up a robust framework for the farming sector to successfully prevent or deal with risks and crises, with the objective of enhancing its resilience and, at the same time, providing the right incentives to crowd-in private initiatives”. R M refers to the actions taken to manage potential prob-lems induced by risky events, to reduce their detrimen-tal consequences, and to increase the chances of success of the business (Kahan, 2013). In this sense, RM can be a key factor in enhancing the resilience of farms and related farming systems (Spiegel et al., 2020) and sev-eral scholars call for improving and enlarging the scope of RM to do so (Finger et al., 2022). Unfortunately, the state of knowledge on RM in agriculture is still incom-plete, and the current approaches to RM are too simple, partial, and inappropriate to successfully help cope with multi-faced global challenges: changes in climate, more frequent extreme weather events, unstable and volatile markets, food security and food safety threats. Improv-ing the state of knowledge on RM is important: success-fully managing risks helps in finding the right balance among productivity, environmental care, market resil-ience to climate change, and capability to secure safe and quality food.This paper reviews the extant literature on the anal-yses of agricultural RM, highlights progress and gaps, and advices on promising areas of research. This exer-cise is per se a very useful contribution to developing a holistic approach to analysing RM. More generally, we hope this piece will stimulate the debate on this relevant topic. While we are aware that some recent literature reviews exist, especially on specific topics (e.g., Komarek et al., 2020), we believe that our paper makes a twofold contribution to the extant debate. First, our overview of the literature focuses on five research questions: i) why evidence on RM is often controversial; ii) how farmers behave in selecting among available RM instruments; iii) why some of these instruments are underutilised; iv) how to assess the impacts of innovative RM tools to (further) improve their design; v) how agricultural policy meas-ures aimed at increasing the environmental sustainabil-ity of the sector could affect risk and, consequently, RM choices. These questions are answered in the subsequent sections. This review also highlights areas where further analyses are needed. Second, we use a holistic approach to the topic. Since RM in agriculture is a complex phe-nomenon, several RM actions are available, and farm-ers’ decisions are affected by spatially and temporally heterogeneous factors, a holistic approach seems needed (Figure 1). RM decisions are strongly influenced by the context in which farmers operate. Several dimensions are relevant to define the context, including not only farm structural and productive characteristics, but also the markets and the environment in which farmers operate. Regarding the markets, the complexity and interconnec-tion of the global agri-food sector have imported new risks into the sector or emphasized old ones. Regarding the environment, there is a vast literature pointing out the effect of climate change on the risks farmers are fac-ing (e.g., Sorvali et al., 2021). A growing body of litera-ture has also shown that farmer’s behavioural factors do affect the farmer’s RM choices and therefore such factors cannot be ignored. Furthermore, the farm sector in the EU is heavily affected by policies. On the one hand, EU rural development policies support the adoption of spe-cific RM tools providing subsidies to reduce the cost of adoption. On the other hand, farm production is con-strained by pieces of legislation aimed at reducing the use of inputs with a harmful effect on the environment. However, often these inputs (e.g., pesticides in the case of pests, and irrigation in the case of drought) have also an effect on agricultural risk, thus their imposed reduction is likely to influence RM choices. The policy context is evolving in this area: the recently released Farm-to-Fork strategy (F2FS) and the CAP reform (European Com-mission, 2018) have set very ambitious environmental targets for EU agriculture (reduction of 50% and 20% in the use of pesticides and fertilisers respectively, by 2030). This will have consequences on the risk faced by farmers because the use of chemicals is intimately related to risk in agriculture and its management (Möhring et al., 2020). Studying the impact of policies targeted to environmen-tal objectives on the farmer’s risk and the uptake of RM tools is worthy to be addressed. Farmers are the ultimate decision-makers in terms of risk management strategies. As economic agents they can take several actions to man-age risk including the adoption of specific RM tools (San-teramo, 2019; Cai, de Janvry and Sadoulet, 2020), chang-es in production mix and diversification, subscription of production contracts, use of risk decreasing input such as pest control chemicals and irrigation (Cerroni, 2020). Their actions are however influenced by risk preferences (Iyer et al., 2020), and other behavioural factors. The lit-erature on the influence of other behavioural factors (i.e., subjective probabilities, risk perception and preferences, ambiguity attitudes, loss aversion and time preferences) on farmers’ decisions to uptake RM tools (Colen et al., 2016) is scant (Coletta et al., 2018; Cerroni, 2020; Čop et al., 2023). Similar considerations apply to the attitude toward innovations and the ability to gather and process information. In the end, this oversimplified framework (and logi-cal flow) advocates for a holistic approach to the analysis of RM also realizing that the current state of agricultural RM is constantly evolving, and it needs to be adapted to novel challenges. Our literature review is an attempt to approach the study of RM by adopting a holistic view: the methods adopted in the analysis of RM in agriculture, the behavioural factors affecting RM adoption, innovative RM tools, the relationship between agricul-tural risk and input use and between different policies directly or indirectly affecting risk and RM in agriculture.

DOI: https://doi.org/10.36253/bae-14492

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