Category Archives: Economics

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.

337. Developing-country farmers: how are they different?

One of the papers in the recent AEPP Special Issue of papers on adoption of agricultural innovations is about how smallholder farmers in developing countries differ from larger and wealthier farmers, and how these differences affect the farmers’ responses to new agricultural practices and technologies. 

The paper is by Rick Llewelly from CSIRO in Australia and Brendan Brown from CIMMYT in Mexico, who have worked together on this issue for a number of years. You can hear my interview with Rick about the paper here. My conversation with Rick is available as an episode of the AEPP podcast series.

Here are a few of the differences that Rick and Brendan identify and discuss in their paper. The discussion is in the context of predicting adoption of a practice that is currently relatively new to farmers.

Greater heterogeneity

“In developing country settings there is greater potential for extreme differences between farms in scale, wealth, and resources, including the influence of tenure status.” In some cases, larger farmers are more able and more motivated to adopt a beneficial technology, while smaller farmers can tend to be left behind.

Higher discount rates

There is plenty of evidence that poorer farmers in developing countries tend to have higher discount rates, meaning that they give more weight to benefits in the short term than in the long term. This could be because of the high interest rates they have to incur when they borrow money, or because their poverty means that generating income in the short term has to take priority, even if it means missing out on large benefits in the long term. This is particularly a barrier to adoption of new practices if those practices involve relatively large up-front costs or the benefits take some years to be delivered.

Inability to capture the benefits

“In some cases, farmers may expect that future benefits from investments in an innovation will mostly accrue to the land owner rather than to themselves.”

Cultural norms

Cultural norms may conflict with the use of particular practices. For example, retention in the field of crop residues following harvest can be beneficial for later crops grown in that field, but in many parts of sub-Saharan Africa, “all land tends to be considered as communal grazing land in the noncropping seasons”. So if you are a crop farmer in one of these areas, it is not socially acceptable to stop other people’s livestock from grazing on your crop residues and destroying the benefit of having retained the residues. For more on this, see my paper Pannell et al. (2014), which is summarised in PD268.

Objectives other than profit

Some farmers rely strongly on their own production of food for their own family. “The need to account for farmers’ subsistence needs can add complexity to predicting adoption of new practices, particularly where subsistence farmers are also sometimes engaged in market-directed production”.

Relative to larger, wealthier farmers in developed countries, smallholder farmers are likely to be more risk-averse, so less inclined to adopt practices that are highly beneficial on average but relatively variable from year to year.

Smallholder farmers may give less consideration to generation of public environmental benefits than at least some farmers in developed countries do, and this too would influence which practices they are willing to adopt.

Factors related to learning about a new practice

In some cases, communication between developing-country farmers in different regions or different ethnic groups is less than we typically see within a more homogeneous population of farmers in a developed country. This can slow down the spread of beneficial new practices through the farming community.

There may be a lack of education needed to understand a particular practice, or a lack of required skills and knowledge, compounded by the poor quality of advisory support in some developing countries.

Clearly, there are a number of factors that can combine to make the adoption of new farming practices in developing countries unfold in rather different ways than we typically observe in developed countries. Scientists, extension agents and agricultural policy makers need to account for these factors when making judgements about what impact a research project, an extension campaign or a policy could have.

Further reading

Llewellyn, R. and B. Brown. 2020. Predicting adoption of innovations by farmers: how is it different in smallholder agriculture? Applied Economic Perspectives and Policy 42(1), 100-112.

Pannell, D.J., Llewellyn, R.S. and Corbeels, M. (2014). The farm-level economics of conservation agriculture for resource-poor farmers, Agriculture, Ecosystems and Environment 187(1), 52-64. Journal web site (access to the paper is free) ◊ On-line video presentation ◊ IDEAS page for this paper

336. Free time at home? Do this free course!

The Australian Government is encouraging people to utilize any unexpected spare time at home by up-skilling through study. I’ve got just the thing! My course on “Agriculture, Economics and Nature” is still available for free on Coursera

The course is an introduction to the economics of agriculture, including the connections between agriculture, the environment and natural resources.

It is designed to be a six-week requiring 2-3 hours per week. But if you have more time available than that, you can do it as quickly as you like.

Here’s the blurb from the web site

Sound economic thinking is crucial for farmers because they depend on good economic decision making to survive. Governments depend on economic information to make good policy decisions on behalf of the community. This course will help you to contribute to better decision making by farmers, or by agencies servicing agriculture, and it will help you to understand why farmers respond to policies and economic opportunities in the ways they do.

You can use this course to improve your skills and knowledge and to assess whether this is a subject that you’d like to study further. The course includes high-quality video lectures, interviews with experts, demonstrations of how to build economic models in spreadsheets, practice quizzes, and a range of recommended readings and optional readings. Assessment is by quizzes and a final exam.

The key economic principles that we’ll learn about can help us understand changes that have occurred in agriculture, and support improved decision making about things like agricultural production methods, agricultural input levels, resource conservation, and the balance between agricultural production and its environmental impacts. There are literally thousands of agricultural economists around the world who work on these issues, so there is a wealth of knowledge to draw on for the course.

Here is a brief video about the course.

About 20,000 people have enrolled in the course since it was first made available. The response has been overwhelmingly positive, as you can see from the feedback reported here.

Enrol now here, and I’ll see you on the discussion forum for the course.


335. Behavioural economics and adoption of agricultural innovations

Behavioural economics has become a thriving field of research over the past decade or so, but research by agricultural economists on farmers’ behaviour when adopting new practices has been going on for over 60 years. What is similar and different between these two fields of research?

I was listening to a presentation by David Zilberman from the University of California, Berkeley at a conference a few years ago, and he made a comment along the lines that agricultural economists had been studying behaviour for a long time before behavioural economics became popular. He was thinking about the large body of research on farmers’ adoption on new practices and technologies.

When I was putting together a recent special issue of Applied Economic Perspectives and Policy on adoption of agricultural innovations, I remembered David’s comment and thought that a paper about this would be a good inclusion. About that time I happened to visit the University of Alberta, and a conversation about this with Maik Kecinski (now at University of Delaware) led to a team of young economists (plus a not-so-young one: me) working together. The resulting paper, “Agricultural Adoption and Behavioral Economics: Bridging the Gap” by Streletskaya et al., is now out and is open access.

To get a brief overview of the paper, you could listen to a conversation with one of the co-authors, Leah Palm-Forster, who happened to be in Perth for the AARES conference last month, which luckily took place just in time to avoid most of the travel shut downs for Covid-19. My conversation with Leah is available as an episode of the AEPP podcast series.

The paper covers a lot of ground. Here I’ll just comment on some of the similarities and differences between the two fields of research. Clearly, both fields are interested in behaviour, both recognize the influence of individual characteristics, preferences, and beliefs on decision-making, and both study economic decisions. But they tend to ask somewhat different questions. Quoting from the paper:

“Agricultural adoption investigates which factors drive or inhibit uptake within a population over time, without necessarily seeking to identify and model behavioral mechanisms that influence adoption. Behavioral economics, on the other hand, seeks to identify and explain behavior that departs from what is predicted by traditional economics through the use of new theories and models of human behavior.”

“Furthermore, agricultural adoption research traditionally has highlighted the role of extrinsic factors such as social, economic, and political context in driving adoption. Behavioral economics, on the other hand, focuses on broadly unpacking the “black box” of human decision making and explores how human cognition and the manner in which tastes and preferences are formed drive decision-making, and how factors such as biases and other social influences impact economic behavior.”

“Agricultural adoption often analyzes field data available at the plot, county, regional and national levels for different types of producers in order to obtain insights about the drivers of new technology diffusion over time and adoption patterns across different farming populations. In the behavioral economics domain, … many laboratory and field experiments rely on smaller samples and consist of cross-sectional data.”

So, there are quite a few differences. But they don’t have to be different. These differences have just evolved organically, largely reflecting the different questions that the researchers were asking.

Researchers working on agricultural adoption are increasingly looking towards behavioural economics for ideas and methods, but I reckon there is also unrealised scope for cross-fertilisation in the other direction. I suspect that many behavioural economists don’t even realise that there is this other big body of research generating knowledge that is relevant to what they do.

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.

333. Reducing bushfire risks

All the world has seen media coverage of the extraordinary fires that Australia has endured this summer. They sparked an intense discussion and debate about what Australia should do to reduce bushfire risks going forward. What does our economic modelling of fire management say about that?

I had a direct stake in the fires. We have a small cabin in a coastal town an hour north of Perth, and before Christmas we had about a week of temperatures above 40°C (104°F), and a big fire threatened the town. It got to the point where they evacuated everybody, but thankfully the weather improved just enough and just in time for the firefighters to get it under control.

Over the past 8 years, I’ve been involved in a number of projects looking at the economics of bushfire risk mitigation in different contexts. We’ve done case studies in four Australian states (Western Australia, South Australia, Victoria, New South Wales) and in New Zealand.

The different studies analysed different combinations of fire management options. The one common element in all the studies was prescribed burning to reduce fuel loads, but in particular cases we also looked at land-use planning to exclude assets from high-risk areas, retrofitting of houses to make them more fire-resistant, fire breaks, and community education.

It was a mix of research and consulting projects, and some of it still needs to be published.

We found that the economics of bushfires are really complex and data-intensive, and often there is a lack of data to do a bullet-proof analysis. In some cases, we met some of the data needs using sophisticated fire simulation models, but in others, we relied on data synthesis and expert judgments.  Despite the variations in context and methods, we did learn some pretty clear lessons across the various analyses.

The results for prescribed burning were somewhat variable in different contexts, but overall, we found that the long-run benefits of prescribed burning tended to outweigh the costs in most cases.

Interestingly, though, we found that prescribed burning leads to reductions in average losses that are modest relative to the overall losses due to fires. These modest reductions in losses are worth pursuing – they exceed the costs of prescribed burning – but it means that we need to have realistic expectations about what prescribed burning can do for us. Especially in extremely bad (“catastrophic”) fire conditions, losses can still be large, even with the best possible prescribed burning strategy in place.

One of the questions we looked at was whether prescribed burning should be done close to properties or more distantly. Closer to properties has higher benefits, because it increases the chance that a recent prescribed burn will block the passage of a bushfire. But closer to properties also has higher costs, because of the need for additional fire-fighting crews and equipment to reduce the risk of prescribed burns escaping and doing more damage than they prevent. In a detailed analysis of this (Florec et al. 2019), we found that the costs of burning close to houses outweighed the benefits.

In the analysis we did for the Perth Hills, we found that strong land-use planning was the most cost-effective strategy. While it is easy to see the sense in that, it comes up against the reality that some people especially like to live in locations where the fire risk is especially high. We didn’t factor in the likely transaction costs to government in trying to impose a policy that a group of people is opposed to.

Another interesting finding was that a broad policy of retrofitting houses to reduce their likelihood of burning was not economically efficient. Such a policy imposes substantial costs on a large number of houses to avoid the loss of a much smaller number of houses, and we found that the numbers just don’t stack up. Interestingly, new houses in bushfire-prone areas of Western Australia are now required to meet high standards of fire resistance.

Finally, in one case where we had access to a fire simulation model, we looked at possible impacts of climate change on future losses from fires (in 2030 and 2090). In brief, the additional losses due to climate change were large, potentially very large. In the media discussions during and following the recent fires, some politicians were suggesting that bushfire risk is not a reason to pursue stronger policies to mitigate climate change; all we need to do is a better job of prescribed burning. While there certainly can be benefits from prescribed burning, our analysis shows that there is no way increased prescribed burning could come close to offsetting the worsening fire risk from even modest climate change. Indeed, increasing prescribed burning may not even be feasible following climate change, as climate change narrows the window of time within which prescribed burning can be done without excessive risk.

From a bushfire perspective, Australia would have a lot to gain from effective international action to mitigate climate change. This suggests that we should be playing a stronger role in the global climate policy process.

Further reading

Florec, V., Burton, M., Pannell, D., Kelso, J. and Milne, G. (2019). Where to prescribe burn: the costs and benefits of prescribed burning close to houses, International Journal of Wildland Fire