Category Archives: Behaviour

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

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.

332. Farmer behaviour and agricultural policy

An understanding of farmers’ adoption of new practices is central to the design of effective and efficient agricultural policies. Aspects of agricultural policy that can be enhanced by good information about adoption include the design of the policy, the targeting of policy effort, and the assessment of additionality. 

In PD330 I advertised a new Special Issue on adoption of agricultural innovations in the journal Applied Economic Perspectives and Policy. There is an audio interview with me about the Special Issue available here.

One of the papers, by Roger Claassen and me, focuses on the relevance to agricultural policy of understanding farmers’ decisions about taking up new practices.

One simple reason for this relevance is that much agricultural policy is concerned with getting farmers to do something they are not already doing or would not otherwise do. Examples of such policies include the following:

  • Programs of agricultural extension to encourage farmers to adopt a new technology that is believed to be more productive than the existing technology farmers are using (e.g., a higher-yielding crop variety);
  • Programs that pay farmers to adopt a practice that generates public benefits (such as protecting or planting vegetation that provides habitat for wildlife);
  • Policies that fund agricultural research, with the intent of generating information or technologies that will be beneficial for farmers or the community; and
  • Policies that use regulations to constrain the behaviour of farmers (such as regulations on clearing of native vegetation).

Since all these policies are about influencing the behaviour of farmers, of course it makes sense that their design and implementation could be enhanced if the designers had a good understanding of what influences the behaviour of farmers. Sometimes policy makers do take this seriously, but not always. I’ve been critical of Australian agri-environmental policies, for example, for often being making overly optimistic assumptions about what farmers will do if we just provide them with some information or pay them a little bit.

In practice, some practices are more attractive to farmers than others. Zero till is used by about 90% of Western Australian farmers, but a practice like variable-rate precision agriculture is used by only a minority. Any one practice is more attractive to some farmers than to others due to varying local conditions, such as rainfall or soil types. Being able to predict variations in adoption would be very helpful to policy makers for targeting their resources. Having a sense of which practices can potentially be adopted, and where, is one of the factors that ought to influence where policies like extension or incentive payments are applied.

Another policy concept that is tangled up with farmer behaviour is additionality. As we say in the paper:

A conservation action (and the resulting environmental gain) that is supported by a payment is additional if the farmer would not have taken the action if he or she had not received the payment. Environmental gains that flow from nonadditional actions cannot be attributed to the incentive program.

If the additionality of a proposed agri-environmental payment scheme is too low, it’s not worth running the scheme. Most farmers were going to adopt the practice anyway, so any incentive payment to them is just a gift, making no difference to environmental outcomes. Policies to promote some practices have high additionality (e.g. filter strips or cover crops in the U.S.) while others have much lower additionality (e.g. conservation tillage in the U.S.).

Assessing additionality is essentially about predicting behaviour. In fact, for programs that aren’t in place yet, assessment of additionality required two predictions about behaviour: what will farmers do if the program does offer them the proposed incentive scheme, and what will they do if there is no incentive payment scheme. The difference between those two predictions tells you the additional change that is attributable to the scheme.

Even assessing an incentive scheme that is already well established requires a sort of prediction. You can observe what farmers are doing with the scheme in place, but to assess additionality you still need to estimate what they would have done in the absence of the scheme.

For all these reasons, an ability to understand and predict farmers’ adoption of new practices is critically important to agricultural policy makers if they want their policies to be effective and efficient.

Further reading

Pannell, D.J. and R. Claassen. 2020. The Roles of Adoption and Behavior Change in Agricultural Policy. Applied Economic Perspectives and Policy 42(1), 31-41.

330. Adoption of agricultural innovations Special Issue

I’m the guest editor for a new Special Issue of the journal Applied Economic Perspectives and Policy. The theme of the issue is “Adoption of Agricultural Innovations” and it includes 11 papers by some of the world’s leading researchers on this topic.

There is an audio interview with me about the Special Issue available here.

The papers are intended to provide reviews or syntheses of key issues related to farmers’ adoption of new practices and technologies. Each paper focuses on a particular aspect of the literature, and the collection as a whole provides an excellent introduction to this enormous body of research.

A particularly nice feature is that all the papers in the issue are open access, meaning that anybody can read them without needing a subscription to the journal. You can access the issue here.

You can hear a brief interview with me providing background and an overview of the Special Issue. The interview is available as an episode of the AEPP Podcast.

Another one of the podcast episodes is another interview related to the Special Issue. In that one I interview Leah Palm-Forster about one of the papers that she and I helped to co-author, called “Agricultural Adoption and Behavioral Economics: Bridging the Gap”. In that paper we talk about the similarities and differences between those two related bodies of research literature, and about possible connections that could be made between them.

Further reading

Here’s a list of all the articles in the issue.

Pannell, D.J. and Zilberman, D. 2020. Understanding adoption of innovations and behavior change to improve agricultural policy. Applied Economic Perspectives and Policy 42(1), 3-7.

Norton, G.W. and J. Alwang. 2020. Changes in Agricultural Extension and Implications for Farmer Adoption of New Practices. Applied Economic Perspectives and Policy 42(1), 8-20.

Heiman, A., Ferguson, J. and D. Zilberman. 2020. Marketing and Technology Adoption. Applied Economic Perspectives and Policy 42(1), 21-30.

Pannell, D.J. and R. Claassen. 2020. The Roles of Adoption and Behavior Change in Agricultural Policy. Applied Economic Perspectives and Policy 42(1), 31-41.

Chavas, J.-P. and C. Nauges. 2020. Uncertainty, Learning and Technology Adoption in Agriculture. Applied Economic Perspectives and Policy 42(1), 42-53.

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.

Montes de Oca Munguia, O. and Llewellyn, R. 2020. The Adopters Versus The Technology: Which Matters More When Predicting or Explaining Adoption? Applied Economic Perspectives and Policy 42(1), 80-91.

Huffman, W.E. 2020. Human Capital and Adoption of Innovations: Policy Implications. Applied Economic Perspectives and Policy 42(1), 92-99.

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.

Rola-Rubzen, F., T.R. Paris, J. Hawkins and B. Sapkota. 2020. Improving Gender Participation in Agricultural Technology Adoption in Asia: From Rhetoric to Practical Action. Applied Economic Perspectives and Policy 42(1), 113-125.