Given the wide range of effects associated with the economic activities of agrifood systems (see Figure 1) and the many different stakeholders affected, integrating all of the hidden costs and benefits into decision-making processes is not an easy task. First, there is a lack of political will and resistance to change. Decision-makers face conflicting objectives, and addressing the hidden costs of agrifood systems can require significant changes to current production and consumption practices, which may meet with resistance from governments, businesses, producers and consumers, who may prefer the status quo for fear of high transition costs or changes in habits, culture or traditions. Policymakers may also have vested interests in maintaining the status quo.
Another reason for resistance to change is the fact that trade-offs may arise. For example, the use of agrochemicals to increase production can reduce poverty, but also lead to ecological degradation over time.37 This makes policy decisions even more complicated. There is also concern about the distributional impacts of the transition to new patterns of production and consumption. The fear that marginalized and poorer groups will be disproportionately affected could make such changes unpopular among policymakers who want to prioritize the reduction of poverty and food insecurity.38 Already, these groups bear the greatest burdens of climate change and biodiversity loss,39, 40 of health problems41 and of scarcity of resources.42, 43 Therefore, transforming agrifood systems to address key environmental stresses and health problems can involve trade-offs with improvements in social equality.
A lack of political will and resistance to change can also be driven by a dearth of sufficient data and information. As shown in Figure 1 and Figure 2, flows and impacts are numerous and many of them are difficult to quantify, while others are qualitative in nature. There is, thus, the problem of data availability and quality. A related issue is under-reporting, such as that of exploited labour along the value chain (for example, incarcerated and undocumented individuals), which causes estimates of underpayment and child labour to be particularly low. 44 Even if there is a willingness to tackle such problems, collecting such data requires resources, skills and capacities that are often not available.
An associated challenge is quantifying the costs of policy change, in other words, estimating the abatement costs for comparison with the benefits of reducing hidden costs.45 Generally, the policy change is justified when the abatement costs are lower than the benefits of the change, so knowing the abatement cost is important to help guide policy direction, as this may be used to inform who will bear the costs. This raises the issue of valuing costs in a way that is practical, so that busy decision-makers – especially policymakers – can move beyond a short-term focus and adopt them at scale. However, estimating abatement costs can be an expensive exercise, as such estimates typically have a high degree of uncertainty, especially when it comes to the distributional impacts (who will pay the costs and who will reap the benefits, either directly or indirectly). Therefore, such analysis is often not performed in the first place, or if it is, it is not given much weight in decision-making, as it is hard to make a robust decision based on data with a high degree of uncertainty.
Another challenge in accounting for the hidden costs and benefits of agrifood systems is the scope, which relates to the geographical, temporal and product boundaries. Agrifood systems encompass complex networks of suppliers, processors and distributors, which makes it difficult to trace the origin of impacts along the way and, hence, those accountable for them. The costs generated can also relate to multiple resources (natural, human, social and produced), which, in turn, have critical interdependencies between them. This poses the challenge of which indicators to use to assess hidden costs and benefits. Many flows and impacts, such as biodiversity loss and social networks, are difficult to quantify (Figure 2), and therefore difficult to incorporate into valuation and decision-making. The impact of many of these hidden costs will also depend on the socioeconomic, spatial and temporal context. For example, the impact of agrifood systems on freshwater will depend on the level of water scarcity or on the water source.
Addressing these challenges will require the use of recent advances in technology and evaluation approaches, which have expanded options and reduced the resources needed to store, communicate, validate and process information.15 It is important to invest in data collection to reduce the degree of uncertainty and improve robustness. Reporting on uncertainties can be insightful in terms of where more information and data are needed to shore up results, to make them more reliable for decision-making. There will be little progress on agrifood systems transformation if methods to improve abatement costing languish. Investing resources in achieving the disclosure of relevant information should also be prioritized.46
