Yearly Archives: 2020

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.

334. Making video lectures

Universities around the world have moved to online teaching in response to Covid-19. Many university teachers who have done little or no online teaching are having to upskill rapidly. Here, I share my three top tips for making effective video lectures. 

Pre-recording lectures is not the only option for online teaching, but it’s a good option in some cases. My first major experience of this was making a MOOC (a free online course on Agriculture, Economics and Nature) back in 2015. I read a lot at the time about how to make a good online course, and it paid off as we’ve had around 20,000 people enrol in the course, with overwhelmingly positive feeback.

After that, with my co-teacher Ben White, we decided to convert the lectures for our first-year environmental economics course to pre-recorded videos. We found that the great majority of students were not attending lectures anyway, just watching the videos of the slides (plus audio) that were are recorded automatically. We were sure we could produce videos that would be far better for the students than those lecture-capture videos.

It was quite a bit of work, but I feel it has been worth it. The student-survey scores for the online version of our course have consistently been high.

So what would I advise to somebody who is now getting into pre-recording their lectures?

1. Break the lecture into multiple short videos

This is so important that I was tempted to do the cliched thing and include it as my tip 1, tip 2 and tip 3. The capacity to break the lectures into multiple mini lectures that the students can watch at the speed they choose is a big advantage over a traditional stand-and-deliver lecture. It would seem quite odd to stop a 45-minute face-to-face lecture 5 or 6 times to re-boot the audience’s attention, but it is highly acceptable in a pre-recorded video format.

I include a little piece of music at the start of each lecture part, which provides an additional signal to students that they need to re-engage their attention. At the end of each part I also ask a question to get them to think about what they’ve just heard.

When I’ve asked students how they watch the videos in our unit, most of them say they watch all the videos for one lecture topic one after another, but they still are very positive about the way it is broken into mini-lectures. The fact that there is a question, then a new video starts, then there is music, helps them to keep engaged for longer.

My feeling is that this is likely to be exceptionally important in the current situation, where students are getting all their lectures by staring at a screen. If we just present them with a series of normal-length lectures, it’s soon going to be incredibly difficult for the students to stay awake.

 

2. Use an external microphone

If you use the built-in microphone in your computer to record your lecture, it will probably sound boomy, echo-y and hollow. In bad cases, it may even be difficult for the students to understand you. Using an external microphone that is located close to your mouth can make a huge difference to the listening experience of your students. It doesn’t even have to be a great quality microphone to make a difference. Even a pretty cheap headset with a microphone will probably be much better than the computer’s microphone. But there are lots of better quality USB microphones available if you are keen. Personally, I use this.

The other thing you can do to further improve sound quality is to record in a room without too many hard surfaces. Carpet, curtains, soft furniture, table cloths, wall hangings, etc. can all help.

3. Moderate your pace, explain well, give examples and tell stories

Cheating a bit here: four tips in one. A disadvantage of pre-recording lectures is that you can’t see the faces of your students, so you may fail to realise that you are moving through material too quickly, you are not explaining it well enough, or you are getting too conceptual and failing to give examples. Given that a video is less personal than a face-to-face lecture, it may pay to make it more personal by including more stories and anecdotes.

The other thing I’ve usually done to make it personal is video myself speaking to the camera (which is just my iPhone) as I record the lecture. The video of me speaking is then displayed in the bottom right corner of the slide, and occupies about one-sixth of the screen space. I’m sure this makes a difference to the student experience, but it is somewhat more time consuming to create the videos, and if you are rushing to get prepared, it might be something you choose to explore later.

In case you are interested, I use Camtasia for all my recording of slides and my video editing. It’s a fantastic program.

I upload all my all my lecture videos onto YouTube as unlisted videos (so nobody can find them if I don’t provide the link) and I organise all the mini-lectures into the right sequence using the Playlist facility in YouTube.

p.s. Here is a new free book that many people might find useful: Take Control of Working from Home Temporarily

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 https://doi.org/10.1071/WF18192

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.

331. Conservation opportunities on uncontested lands

Not all agricultural land is productive and valuable. Looking for low-value land might be a useful strategy when seeking to increase the area devoted to conservation. In addition to being relatively cheap to purchase, it may be relatively unlikely to strike problems with social or political opposition.

I’m part of a team of researchers that is looking at this issue, led by Eve McDonald-Madden from the University of Queensland. We have a new open-access paper out in Nature Sustainability that presents a framework for thinking about whether and when restoring low-value, or “uncontested”, agricultural land for conservation purposes is likely to be a good idea.

In the paper, we talk about the different costs that are involved in acquiring and restoring a piece of land. They include the purchase price of the land, which reflects its long-term economic productivity, the transaction costs involved in acquiring the land, and the cost of restoring the land to an improved ecological condition.

We suggest that these costs are likely to be related systematically to the opportunity cost of the land for agriculture (that is, the amount of income that would have to be given up if the land was converted away from agricultural production), but that the patterns may vary.

If the reason for some land having a very low opportunity cost is that it is highly degraded and therefore unproductive, the restoration cost may be particularly high. Restoring the most degraded lands is more difficult and more expensive. In that case, it might be better to seek to acquire and restore land that is degraded, but not so extremely degraded.

If the reason for agricultural land having a low opportunity cost is low market prices for agricultural outputs, rather than land degradation, then there is no reason to expect this land to be especially expensive to restore, potentially making it an attractive target for restoration. Although, not necessarily. Whether the purchase price would be particularly low depends in part on farmers expectations about future prices, not just current prices.

In some situations, acquiring land involves particularly high transaction costs. This might be the case, for example, if there is social and political oppositon to conversion of agricultural land to conservation land. As a generalisation, we might expect that to be less of an issue if the land is degraded and unproductive for agriculture.

Another example of high transation costs could be the effects of corruption. “If corruption is socially normalized, this may lead to low levels of trust, with the result that parties incur high costs for negotiation, contracting and monitoring an agreement. If legal institutions are weak, the cost of enforcing an agreement could be very high.” In this case, even though the land might be cheap, the overall cost might mean it is better to look in a less-corrupt country for land to restore.

Recognising those complexities, we are using spatial data to try to identify cost-effective opportunities for investing in restoration of land.

Further reading

Xie, Z., Game, E.T., Hobbs, R.J., Pannell, D.J., Phinn, S.R., and McDonald-Madden, E. (2020). Conservation opportunities on uncontested lands, Nature Sustainability 3, 9–15. Journal web page (open access)