1. Conceptualising resilience for policymaking

By its very nature, agriculture is an industry where uncertainty is the rule rather than the exception. Producers face many different forms of risk in their decision-making processes, including production risk as a result of fluctuations in weather, market risk due to price volatility, institutional or political risks from disadvantageous changes in policy, and financial risk resulting from the need to borrow funds to finance operations. In today’s competitive market atmosphere, for many farmers, achieving success is highly dependent upon how well these risks are managed.

But the agricultural risk landscape is changing. Given likely projected climate change scenarios, farmers across the globe will have to adapt their operations to evolving physical circumstances, including higher average temperatures and the increased incidence of natural disasters that can be particularly devastating to the agricultural sector, such as droughts or more frequent high-intensity rain events (Hoegh-Guldberg et al., 2018[1]). Moreover, despite the support for improved risk management policies over the past few decades, the financial impact of natural disasters continues to rise (Bevere et al., 2018[2]). If this trend continues, some viable farmers may not be financially capable of dealing with the consequences of negative shocks, and governments will find themselves needing to intervene in order to prevent total market failure. Further on, the COVID-19 epidemic has reinforced that exogenous risks from outside the agriculture sphere can also cause substantial shocks to the sector, simultaneously impacting input markets, labour, logistics and consumer demand in unpredictable ways (Box 1.1).

Confronting this reality will require disciplined application of an holistic risk management strategy – specifically, ensuring that decisions are no longer made from a paradigm of reactivity, but from a “resilience” perspective instead, with the goal of either reducing the impact of events, or significantly reducing the likelihood of certain risks. To accomplish this, the resilience approach emphasises the importance of ex ante strategies, including risk awareness, contingency planning, innovation and evolution The approach also stresses the importance of considering systems instead of individuals, both to ensure that the decisions of individual actors are placed in context for the resilience of the food system, as well as to ensure the consideration of linkages and potential knock-on effects for the sector at large.

The resilience approach is increasingly applied for policy development in a variety of sectors. However, given the unique exposure of agriculture to risk and the cascading effects of agricultural shocks on rural areas and the food chain, it is worth first exploring how the concept can be applied to the agricultural sector. Toward that end, this chapter defines resilience for the agricultural context, details the different capacities that contribute to resilience, and provides context on integrating resilience thinking into policymaking for risk management.

Many countries aim to build the resilience of their farmers to a wide range of risks, from market volatility and more variable weather conditions, to pest and disease outbreaks and natural disasters. As a result, the concept of resilience is increasingly incorporated into agricultural policy frameworks. Despite this interest and the increasing use of the term, the concept lacks clarity. This ambiguity has various sources: the idea of resilience has been applied to and interpreted differently in various fields, such as ecology, engineering, and psychology (Keating et al., 2014[4]); resilient systems take many forms, and as such, resilience is highly contextual (Bahadur et al., 2015[5]); and resilience within even a single sector is multidimensional, with aspects of financial, social, cultural, and ecological resilience all relevant to agriculture. Even within the policy space, countries differ in their interpretations of the term, depending upon how the concept is positioned in their overall risk frameworks (OECD, 2014[6]). As such, definitions tend to be context specific (Box 1.2). The ambiguity of the term is also part of its attractiveness. The concept covers both the idea of preserving the system after a disturbance, and the idea of transforming the system into something new in response to disturbances and the evolving risk environment.

Nevertheless, the different definitions have common features, emphasising the ability of systems to function, recover and transform in the face of risk and disturbances. Following Box 1.2, resilience can be understood as “the ability to prepare and plan for, absorb, recover from, and more successfully adapt and transform in response to adverse events.”1 This definition is appropriate in the agricultural context, as it encompasses all possible adverse events (given that agricultural risk can come from production, market, or other sources), emphasises the multidimensional capacities needed to achieve resilience (in particular, absorbing the impacts of risks, recovering from them, and learning and adapting to them), and recognise that in the long-term, a system needs to be able to change in order to persist (through more successful adaptation or transformation).

In addition to being defined, resilience must also be placed in context – that is, in order to be a useful foundation for policymaking purposes, governments need to formulate a common understanding of resilience for whom (the target scale or unit of analysis), and resilience to what (the target source of risk), and recognise that in an operational sense, building resilience will likely involve targeted measures rather than a one-size-fits-all approach. With respect to agriculture, the relevant scale could be the field, farm, region, country, or even the global food system (Bullock et al., 2017[11]). When considering the target risk, policy makers will need to consider all disturbances, hazards and shocks that have potential negative impacts on the agricultural sector. These events should be deviations from a trend, and not trends themselves (for example, climate change is a trend, but not a risk, while more intense rainfall events as a result of climate change are a risk). Moreover, policy makers can consider resilience with respect to either a single risk (referred to as “specified resilience”, which would include, for example, resilience to floods or resilience to price volatility), or resilience to all risks (referred to as “general resilience”) (Anderies et al., 2013[12]). Some specified risks are more likely to be associated with known probabilities than others, but may increasingly have uncertain risk distributions as the risk environment shifts due to climate change. Rare events tend to be more uncertain because there is less information about their frequency and severity.

Improving resilience requires actors to both manage the consequences of shocks, and to anticipate and prepare for their occurrence – including for shocks whose probability of occurrence are highly uncertain – by reducing or managing exposure and reducing vulnerability2 through the building of resilience capacities. Exposure and vulnerability are important in this context because they will determine both the risk of a given event, and the magnitude of the impacts when the event occurs (IPCC, 2012[13]). To manage risk exposure and reduce vulnerability, the literature considers three capacities to be crucial for improved resilience: the capacity to absorb the impact of an adverse event; the capacity to adapt to an evolving risk landscape; and the capacity to transform – the type of farming system or even the agricultural sector itself – if the current system is no longer able to adapt to or recover from shocks (Box 1.3) (Béné et al., 2012[14]; Mitchell, 2013[15]; Douxchamps et al., 2017[16]; Tanner, Bahadur and Moench, 2017[17]; FAO et al., 2018[7]).3

The three capacities are closely related. For a farm, the capacity to absorb the impact of a shock is the ability to better manage exposure to an adverse event, reducing either the event’s probability and/or severity, or the farmer’s vulnerability when coping with the event’s impacts. The capacity to adapt means being able to change the farming system in response to current disturbances and in preparation for future events. The capacity to transform can be considered as an extension of the capacity to adapt, but implies a more extreme response in the form of deeper structural change (which may become increasingly necessary as systems approach biophysical thresholds under climate change) (Sinclair et al., 2014[22]). These three capacities are sometimes distinguished conceptually or temporally. For example, in the short-term, off-farm income may help a farmer to absorb the effects of a production shock caused by low rainfall in a given year and move forward without altering operations. However, faced with more variable climate conditions going forward, some type of change to the farming system may be called for in the medium-term (adaptation) or long-term (transformation) (Anderies et al., 2013[12]). All three capacities are needed for resilience, but the combination of measures that contribute to improved absorption, adaptation, or transformation will differ among farms, responding to the entrepreneurial allocation of their individual capacities and assets.

Applying a resilience lens to agricultural risk management implies an emphasis on planning and prevention to the extent possible, while also ensuring that farming systems remain flexible enough to respond to future uncertainty – a holistic management approach often referred to as “resilience thinking” (Folke, 2016[23]). At the farm level, resilience thinking can be considered as a form of human capital – decision-makers are able to take into account the entire risk landscape, consider the array of potential responses, and be aware of how those responses will affect operations at different points in time. Farmers are called on to not only bounce back from negative events, but also to prevent, experience, and learn from shocks in order to adjust their practices with a view toward long-term sustainability. At the policy level, resilience thinking means holistically considering the long-term implications of policies for the sector, taking preventative actions to mitigate systemic risks where possible, and ensuring that producers have the tools necessary to engender on-farm resilience while considering the possible implications and trade-offs for the sector at large.

There is no one stable, desirable state for either a farm or a country’s agricultural sector. But resilience thinking applied to policymaking means that the actions of today ensure that, although they may look different, the farm today and the farm of tomorrow will meet both individual and larger societal objectives.

In order to achieve greater resilience and use this concept as a lens for formulating risk management policy, policy makers will need to evaluate the risk landscape in a holistic way, considering a range of options as well as the potential trade-offs in promoting one approach over another, depending upon the target objectives of their resilience policy frameworks. In this respect, three dimensions should be considered – scale, source of risk, and time frame – with potentially significant implications for the kinds of policies needed, their budgetary impacts and likely trade-offs.

When considering the scale for resilience policy, the systems approach is commonly advocated, wherein resilience is considered holistically for the entire food system, to better account for interactive effects and minimise negative externalities (Kuhl, 2018[24]; Tendall et al., 2015[25]). This is, for example, the focus of the EU SURE Farm approach (Meuwissen et al., 2018[26]). This holistic approach is advocated because focusing on a lower scale of a country’s agro-food system may undermine resilience at a higher level, and may underestimate the importance of linkages to the sector’s overall resilience (Walker et al., 2004[27]; Bahadur, Ibrahim and Tanner, 2013[28]). Although farmers are the target actor of most agricultural risk management policies, it is important to consider the potential trade-offs of how policies applied at the farm level will affect the resilience of the sector as a whole (and vice versa) (Walsh-Dilley and Wolford, 2015[29]). This is best illustrated in terms of utilisation of common pool resources – an individual farmer may improve his or her resilience to water scarcity risks by drawing on an aquifer for irrigation, but this action may reduce the resources available for other producers. When such actions improve the well-being of the individual but damage the long-term resilience of the system, they become maladaptations – the individual is better off, but the system is worse off. At the same time, there may be some risks that warrant a more targeted approach if their impacts are nonlinear, or if targeting prevents more widespread diffusion of impacts. As an example, this targeted approach (hotspot approach) has been advocated by OECD when dealing with water risks (OECD, 2017[30]).

With respect to source of risk, when evaluating whether to pursue a policy targeting specific or general resilience, policy makers should be mindful that improving resilience solely in one area can cause the system to be less resilient in other ways (Sinclair et al., 2014[22]; Adger et al., 2011[31]). Moreover, when actors concentrate on addressing only specific shocks, they may reduce their options for dealing with unanticipated future shocks. Similarly, focusing on one frequently occurring shock may reduce the capacity to deal with less frequent ones (Folke, 2016[23]). In contrast, a focus on general resilience also involves a wide degree of uncertainty about risks that are unknown or not well-known, and this can be costly. When focusing on specific resilience, the source of the shocks is better defined, and, if the events are frequent enough, typically their probabilities and likely financial impacts are easier to analyse. In cases of general resilience, there are events for which no probability can readily be offered to inform risk management policy, complicating the quantification of expected benefits. In this situation, policy makers will be called to choose their level of resilience given existing budgets, policy frameworks and the existing uncertainties. It may be the case that certain investments in general resilience are at present too great to justify their cost (Carpenter et al., 2012[32]). In formulating plans for improved resilience, policy makers will have to prioritise and decide which risks are most relevant to their own agricultural sectors and more likely to generate market failures, and whether or not it is most cost-effective to promote strategies of general resilience or to instead target a more specific risk. This prioritisation is part of the holistic approach, and it should be re-evaluated over time when better information becomes available.

The final consideration required for resilience policymaking is the time frame. Implicit in the concept of resilience is the idea that systems should be able to persist or transform in the long-term despite repeated exposure to disturbances. However, improving resilience in the long-run may come at the expense of efficiencies in the short-run (Nelson, Adger and Brown, 2007[33]). Furthermore, it is possible that decisions taken to help cope with a risk in the short-term may increase exposure and vulnerability in the future (IPCC, 2012[13]; Carpenter et al., 2001[34]).

Even though resilience emphasises decision-making for the long-term, from a policy perspective this can be difficult to achieve – without proper incentives, decision-making processes tend to be biased toward the immediate future and neglect the long-term focus that resilience thinking implies (Carpenter et al., 2012[32]). These kinds of policy biases also apply to the scale and the source of risk. Governments tend to bias their policy responses in favour of risks that are better known or more visible in the media, and in favour of the actors and scales for which there is also more visibility. These behavioural biases apply as well to farmers and other actors, and they tend to favour baselines and trends from the past in risk perceptions, such that they can generate misalignments and maladaptations.

These biases can be somewhat ameliorated (and the possibility of implementing policies that increase future vulnerability can be reduced), by shifting towards ex ante thinking, including undergoing scenario analysis and implementing value-for-money policies that will have positive benefits over a wide range of potential futures. Ex ante thinking can be combined with an iterative assessment approach, which involves a periodic stocktaking of conditions to see if new information is available, and if practices or policies need to be adjusted as a result (Engle et al., 2014[35]). In this way, policy decisions can take into account both current conditions and the best and most cost-effective ways to ensure a viable future. A good resilience policy needs to be proactive in improving information and learning from experience. For example, scenario analysis can help to improve both policy analysis and design (Antón et al., 2012[36]; Antón et al., 2013[37]).

Based on this foundational understanding of resilience, its component dimensions, and the importance of context, the next chapter takes a deeper dive into the academic and policy literature for evidence of resilience-improving measures relevant to the OECD agricultural context.


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← 1. Definition based on National Research Council (2012[39]).

← 2. The IPCC defines exposure as, “The presence of people; livelihoods; environmental services and resources; infrastructure; or economic, social, or cultural assets in places that could be adversely affected,” while vulnerability is, “The propensity or predisposition to be adversely affected,” (IPCC, 2012[13]).

← 3. Different authors throughout the theoretical literature offer up their own suggestions for key resilience capacities. Even amongst authors that describe three capacities, the terminology can differ, with absorption sometimes referred to as “persistence” (Folke et al., 2010[38]) or “robustness” (Meuwissen et al., 2018[26]) instead, for example.

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