340. COVID-19 and environmental economics

The flood of writings on COVID-19 across all academic disciplines is quite overwhelming. I’m partly to blame; apart from the Policy Forum article we published in Science in May, I’m involved in two special issues of research journals on the subject. There is also a follow up to the Policy Forum article soon to be submitted. 

The first of the special issues to be published is in Applied Economic Perspectives and Policy. I have a paper in there with Vic Adamowicz from the University of Alberta, on the topic “What Can Environmental Economists Learn from the COVID‐19 Experience?”

Here’s the abstract:

The responses of policy makers, individuals, and businesses to COVID‐19 contrast with typical responses to environmental issues. In most countries, governments have been willing to act decisively to implement costly restrictions on work and personal life, to a degree that has never been observed for an environmental issue. A number of possible lessons for environmental economists are identified. In addition to valuing natural environments, people also place a high value on social interactions. These two values may interact. Adaptation can substantially reduce the cost of restrictive policies and should be considered when policy proposals are being evaluated. Preparation for an emergency can substantially reduce its costs by allowing a more rapid response. The development of new technologies can play a key role in reducing externalities. As well, the effectiveness of policies that deliver public goods can be enhanced by credible leaders who provide clear, compelling, and consistent information, emphasizing both the private and public benefits of compliance.

And here’s part of the conclusion:

COVID-19 as a policy issue shares a number of features with the environmental issues that are commonly addressed by environmental economists. In both cases, costs of various types are created by policy responses, and policy makers have needed to make judgements about whether those costs are too large to be worth bearing. Public compliance with policies is needed to generate both public goods and private benefits. Communication and leadership matter in fostering that compliance. Scientific advice and evidence is critically important in making decisions about the design of effective policies. Technology development can be a key element in the policy response. Decisions have to be made in the face of uncertainty about the severity of the issue being addressed and about the performance of alternative management responses. Difficult trade-offs are needed between the disease or environmental issue, on the one hand, and economic or social issues on the other. And spread of a disease or pest or environmental problem provides a potential market-failure rationale and justification for coordinated policy response that places restrictions or costs on individuals and businesses to avert other larger costs.

Despite these close parallels, some clear differences in policy decisions and outcomes are apparent. Governments have been willing to adopt stronger, more costly and more rapid policy actions for COVID-19 than are typically seen for environmental issues. In most countries, public support for these policies has been stronger and more united than for any environmental issue, resulting in high levels of compliance despite high private costs. Uncertainty has been acknowledged and addressed more explicitly, both through adaptive management and through approaches to disease modelling. Science has played a central and trusted role, with scientific advice being actively sought and acted on by politicians.

The whole paper is open access:
https://onlinelibrary.wiley.com/doi/10.1002/aepp.13077

Further reading

Pannell, D.J. and Adamowicz, W.L. (2020). What Can Environmental Economists Learn from the COVID-19 Experience? Applied Economic Perspectives and Policy (forthcoming). Journal web page

Shea, K., Runge, M.C., Pannell, D., Probert, W., Shou-Li, L., Tildesley, M. and Ferrari, M. (2020). Harnessing the power of multiple models for outbreak management, Science 368(6491), 577-579. Journal web page

339. Assuming that farmers maximise profit

Agricultural economists building models of agricultural production often use simplistic assumptions about what motivates farmers. The simplest possible assumption — that farmers maximise profits — is still quite commonly made in agricultural economic models. Can this ever be defended? 

One of the papers in the recent AEPP Special Issue of papers on adoption of agricultural innovations is on this topic. The paper is by Alfons Weersink from the University of Guelph and Murray Fulton from the University of Saskatchewan. You can hear my interview with Alfons about the paper here. My conversation with Alfons is available as an episode of the AEPP podcast series.

They point out that many motivations other than profit maximisation have been identified in research about the uptake of new practices by farmers. Other factors that influence them can include risk, leisure, family, social norms, peer pressure, environmental concerns, and altruism.

Weersink and Fulton also picked up a table from an old Pannell Discussion (PD103) in which I suggested that the factors that influence adoption of new practices are likely to vary in different stages of the adoption process. Early on in the process, when farmers are learning from others about the practice, social, cultural and personal factors are likely to play a relatively large role. Later in the process, when farmers have personal experience in using the practice on their own farm, the influence of outsiders will be reduced to some extent. Influences like social norms could still play a role, but the farmer is no longer primarily relying on outsiders for their information.

The finding that farmers are more complex than we might like to assume is reinforced by research in the booming  field of behavioural economics. This has identified a large number of biases that affect people’s decision making. Some relate to the way our brains process information, and some are more about our responses to social situations. This work tells us that farmers will often diverge from profit-maximising behaviour even if they think that’s what they are going for.

Having read the Weersink and Fulton paper a few times (in the course of editing the special issue), it got me thinking about the role of profit in adoption of innovations. Here are some further thoughts.

I think that the main thing driving long-term adoption of a practice is its relative advantage (how well it enhances the achievement of the farmer’s goals). An important element (but, as I said, not the only element) of relative advantage for most farmers is the effect of the practice on profit. There is plenty of evidence that, although various factors influence farmers’ decisions, profit remains one of the main ones. It doesn’t mean that farmers are motivated by wealth for its own sake, but they seek to make money for what it allows them to do.

At the same time, the cognitive biases identified by behavioural economics don’t seem to me to be so large that profit-motivated farmers would make decisions that are really poorly correlated with their objectives.

If I was putting a number on it, I’d say that for Australian farmers, profit explains something like 70% of the variation in adoption between different practices. We can potentially do a more sophisticated analysis to get a more accurate understanding of adoption, but even if we don’t, a 70% understanding is likely to be very useful.

Economists should think carefully about whether some other factor is likely to overwhelm considerations of profit, but in most cases profit at least gives a useful indication of the broad trend in behaviour. If a scientist, an extension agent or a policymaker wants to know whether a new practice or technology is likely to be adopted by farmers, an analysis of its effect on farm profits is bound to be a useful first step.

Why not just include those other motivations in the economic models, to pick up some of the remaining 30%? Because it is much more difficult. The big advantage of modelling profit is that it can relatively easily be quantified, whereas most of the other factors can’t.

So, in summary, my view is that basing agricultural economic models on profit maximisation is often not a crazy thing to do, because it is relatively easy and reasonably useful.

Like all of the papers in the special issue, Alfons and Murray’s paper is free to access.

Further reading

Streletskaya, N.A., S.D. Bell, M. Kecinski, T. Li, S. Banerjee, L.H. Palm-Forster, and D.J. Pannell. 2020. Agriculture Adoption and Behavioral Economics: Bridging the Gap. Applied Economic Perspectives and Policy 42(1), 54-66.

Weersink, A. and M. Fulton. 2020. Limits to Profit Maximization as a Guide to Behavior Change. Applied Economic Perspectives and Policy 42(1), 67-79.