Category Archives: Behaviour

227 – ‘Disadoption’ after a project ends

22 October, 2012 – 8:35 am

There are various programs and projects around the world that aim to encourage farmers to adopt a new practice of one sort or another. It’s not uncommon to observe farmers participating in such projects, but then reverting to their old practices once the project ends. What are the implications of this?

If a program has a limited life, it is usually most realistic to assume that funding for projects will be temporary. Examples include Australia’s national natural resource management programs (Caring for our Country, the Natural Heritage Trust, and the National Action Plan for Salinity and Water Quality) which provided one-off funding for projects, usually three years or less. Assuming that we want benefits from these programs to be enduring (which we surely do), we would seek to avoid the sort of scenario I outlined above, where farmers abandon the new practices once the flow of program money ends.

This implies that these programs should be careful in targeting their resources to promotion of practices that that are expected to provide positive net benefits to the target farmers. That is, they are practices that, once the farmers learn about them, will be attractive enough to be continued without ongoing support.

This sort of thinking seems to me to have been completely absent from the above programs, and from many other temporary programs around the world. For example, last week I attended an interesting workshop on Conservation Agriculture in Africa and South Asia, and there seem to have been many examples in that space of temporary ‘adoption’ that was abandoned once projects ended.

Once this has occurred, the logical response is to cease any further efforts to promote the activity, unless you have strong reasons to expect that the circumstances have changed significantly. Examples of relevant changes could include: a new version of the practice has been developed that will perform better for these farmers, a policy barrier to its adoption has been removed, or commodity prices have changed in a way that makes the practice more attractive.This sort of ‘disadoption’ actually gives us powerful insights into the practice that was being promoted. The farmers have tried out the practice in their own context, and decided to stop doing it, so they are making a relatively well-informed judgement that the practice does not suit them. This is clearer and more powerful than simply observing that a practice has never been adopted in an area. If it has never been tried out, you probably can’t be sure that it wouldn’t work if it was tried. But if it has been tried and then abandoned, you can be relatively sure about it.

Unfortunately, this sort of common-sense response often doesn’t occur. In the national salinity program we found cases where farmers had been paid repeatedly to ‘adopt’ perennial pasture, but had ‘disadopted’ it each time. In Africa, relatively untargeted promotion of Conservation Agriculture has persisted despite it being well known that ‘adoption’ often evaporates once programs end.

A key understanding is that participation in these sorts of programs does not actually constitute adoption. From the farmer’s perspective, it’s really a case of farmers trialing the practice to see if it works sufficiently well for them. (That’s why I’ve put ‘adoption’ in quotes above.) The benefit of the program is that it allows farmers to make better-informed decisions about adoption, whether or not those decisions are to adopt the practice.

The other implication is that funding that would have been spent on promoting non-adoptable practices should be diverted to other uses. That could include promoting those practices to farmers who have been carefully assessed as being likely to adopt after trialing, or focusing on ways to improve the attractiveness of the practices, instead of promoting them in their current form.

223 – Leadership

2 September, 2012 – 8:45 pm

Strong, inspiring, visionary leadership can have a huge influence on people, pulling them together and changing their direction. But is it the only thing that can achieve that? And is it necessarily a good thing?

I participated in a very interesting discussion about leadership this week. One of the participants was a radio astronomer who had been involved in the successful bid for the Square Kilometre Array project in Western Australia – a massive undertaking. She said that a key factor in getting radio astronomers to overcome their differences and unify behind the bid was a small number of outstanding leaders in the discipline. Most people in the discussion were agricultural scientists, and they were discussing whether agricultural scientists could also get a large, visionary national project funded in Australia and what could be learnt from the SKA experience.

One of agriculturalists argued that leadership is not just important for change, it is essential — that you generally don’t see big changes occur across a large group of people where the change propagates from the bottom up. That was quite thought provoking, and at the time I couldn’t think of a counter example.

Later on I identified a couple of economics-related examples where major changes regularly happen without any leadership at all. One is our adoption of new technologies. Think of Steve Jobs and Apple. No doubt, Jobs was the archetype of a strong, inspiring, visionary leader within Apple, and had a huge influence on the company and its staff. But outside the company, it was different. We didn’t all buy ipods, iphones, ipads and ikettles because we were inspired and led by Steve Jobs. (Well, maybe a few did, but mostly not.) We did it because these are great products, and perhaps because Apple has a cool reputation. Millions of us changed our behaviour towards purchase of Apple products, and that in turn further influenced our behaviour in myriad ways, but there was no unifying leader that directly influenced us to change in these ways.

Another example is the behaviour of people in markets. Markets can have a major influence on the behaviour of people by the simple mechanism of pricing. If there is a shortage of a product (say, wheat), the price is bid up. This encourages more producers to produce wheat, and it encourages consumers of wheat to cut back on their wheat consumption, so the shortage is addressed. The wonder of the market is that there is no leadership required for this to happen. It occurs efficiently and reliably through the aggregation of many individual decisions.

Could these examples provide a different way (other than by leadership) to bring agricultural scientists together, to push them in a particular new direction? Perhaps it would be possible to think about the incentives that scientists face and influence their behaviour by modifying those incentives. That might mean that we wouldn’t need inspiring leadership, but I think we would still require strong leadership with a clear vision to arrange for the new incentives to be put in place. So for this particular type of change, my feeling is that the comment was right; leadership is crucial.

My other thought about this, though, is that we should be careful what we wish for. The directions that leaders take us in are not necessarily good ones. In the agricultural context, I’d point to the history of salinity in Australia. The profile of salinity as a problem for agriculture (as well as for water, biodiversity and infrastructure) grew through the 1980s and 1990s, culminating in the creation of the National Action Plan for Salinity and Water Quality in 2000. A small number of high-profile scientist leaders/advocates were pivotal in the creation of this $1.4 billion program. It was the one of the biggest environmental programs in Australia’s history, and its creation must have seemed like a huge success for those who had been pushing for it. But in fact the program was fundamentally misconceived. It would have needed to be designed and delivered in entirely different ways to have any chance of meeting its objectives. In the wake of its obvious failure, resources for salinity management and salinity research have almost completely dried up. So the apparent major success of getting a huge national program established was actually the beginning of the end of the issue as a national priority.

213 – The environmental planning fallacy

30 April, 2012 – 5:33 am

Psychologists studying the way that people plan projects have found that they are often way too optimistic – they think the project will take less time, or cost less, or achieve greater change, or that the change is worth more, relative to what is realistic based on experience with other similar projects. We have observed exactly these tendencies in environmental planning, and seen that they create serious (but often unrecognised) problems for managers wishing to prioritise environmental projects.

Psychologists Daniel Kahneman and Amos Tversky made very successful careers out of studying the biases that commonly occur in people’s thinking, culminating in Kahneman being awarded the Nobel Prize for Economics in 2002 (Tversky would surely have shared the award if he had still been alive). Kahneman’s recent book for a general audience, ‘Thinking, Fast and Slow’ (Kahneman, 2011), includes very enlightening and entertaining information about the various biases.

Daniel Kahneman

The bias towards optimistic planning they called the ‘planning fallacy’. In his book, Kahneman provided a variety of striking examples. Here’s one that’s not unusual:

‘A 2005 study examined rail projects undertaken worldwide between 1969 and 1998. In more than 90% of the cases, the number of passengers projected to use the system was overestimated. Even though these passenger shortfalls were widely publicized, forecasts did not improve over those 30 years; on average planners overestimated how many people would use the new rail projects by 106%, and the average cost overrun was 45%’ (Kahneman, 2011).

Although we know these things occur, understanding of the reasons why they occur is not so clear-cut. Suggestions include that:

planners focus on the most optimistic scenario, rather than using their full experience;
simple wishful thinking;
biased interpretation of poor past results;
underestimating or overlooking the variety of risks that could affect the project.

When people plan environmental projects, exactly the same sorts of things occur. In observing existing environmental plans, or helping people to develop new ones, my collaborators in the INFFER project and I (Pannell et al., 2012) have often observed the phenomenon. It’s so common that we’ve developed our own term for it: the ‘culture of hope’. Unfortunately, overly optimistic claims about projects tend not to get picked up by funding programs when they are evaluating project proposals (e.g., Pannell and Roberts, 2010).

To illustrate the problem, we often observe that people who develop an environmental project frequently seem to be overly positive in their perceptions about the following variables.

The value of the environmental assets that the project will protect or enhance
The level of cooperation and behaviour change by landholders
The various risks that might cause the project to fail (some of which tend to be ignored completely, not just understated)
The cost of the project in the short term
The longer-term costs, beyond the initial project (also commonly ignored)

With the combined effects of these biases and omissions, it’s common for the assumptions in the plan for an environment project to make it look dramatically better than it really is. I reckon the implied benefit: cost ratio could be exaggerated by a factor of 10 or more in many cases we’ve seen. So the likelihood that decision making will be messed up, with adverse consequences for the environment, is very high.

Although the biases might sometimes result from people trying to game the system to get support for their pet project, that is certainly not the only cause. The psychologists have shown that optimistic biases occur even when people are not trying to distort things. It’s human nature.

From an economist’s perspective, this matters because it is not possible to judge whether an environmental project is worth investing in if the assumptions made about it are inaccurate. From an environmentalist’s perspective, there is a serious risk that funders will end up supporting those projects that have been exaggerated the most, rather than the projects that will really deliver the most valuable environmental outcomes.

Having observed this phenomenon from the earliest days of developing INFFER (before we had even heard of the ‘planning fallacy’), we developed several strategies to try to counter it.

Explicit questions about negative factors that tend to be ignored. When people are completing our Project Assessment Form, we require responses to questions about a range of specific risks, and about long-term funding, so that they can be factored into the project assessment.

Logical consistency checks. We ask them to check whether the answers to some later questions are logically consistent with their answers to specific earlier questions. This helps to flush out some biased responses.

Review of assumptions by independent experts. Kahneman and Tversky found that we are much better at being realistic when judging other people’s projects, rather than our own. Our system includes a facility for independent reviewers to provide comments on particular assumptions, and we use this extensively when supporting people to develop projects.

Feasibility assessment. For large projects, we recommend that a feasibility assessment should be included as the first phase of project funding, with further funding depending on the results of the feasibility assessment. This process should involve collection of additional information about those aspects of the project that were most uncertain in the project-assessment phase, followed by revision of the original assessment.

Even with all of these measures, I don’t think we eliminate the planning fallacy problem, but I do think we reduce its impacts quite a bit.

It’s interesting to observe that most environmental managers are quite oblivious to the problem. Some of them view our measures to try to counter it as unnecessary inconveniences. The measures mean that our process is more involved than the simpler processes many environmental managers are used to, so there is some resistance to using it.

Despite this, our experience shows that it’s crucial to include these measures to counter the planning fallacy. Without them, the project plans developed are of little value to decision makers who genuinely wish to support projects that will deliver the best environmental outcomes with the available resources.

203 – Predicting adoption of new farming practices

17 January, 2012 – 9:24 am

Predicting adoption of new practices by farmers is important for researchers, extension agents and policy makers. A new tool to assist with this difficult task has been released.

My most successful published paper, in some respects, is a review of the published research literature on landholder adoption of conservation practices (Pannell et al., 2006). It was a really enjoyable paper to write, partly because it was done with an outstanding team of collaborators. The level of interest in the paper has been remarkable, and this has led me and the co-authors to deliver a range of other activities and outputs on the topic, including a couple of national workshops (www.ruralpracticechange.org) and a book (Pannell and Vanclay, 2011).

One thing you couldn’t do based on the review paper alone is predict the level and speed of adoption for a particular farming practice that hadn’t already been studied in detail. In fact, there doesn’t seem to be any tool or framework anywhere that will predict adoption of agricultural practices (not just conservation practices) in a quick and easy way.

The only real option has been to undertake detailed surveys of potential users of the practice, but that’s a big job.

It struck me that this was an important information gap. There are lots of situations where people do need to predict adoption of new farming practices.

Examples include:

agricultural scientists wondering whether to research a particular agricultural technology
agricultural extension agents wondering whether a new agricultural practice is worth promoting
policy officers developing a program to encourage uptake of new practices

In each case, there is a lot of value in knowing whether or not the technology or practice is potentially adoptable by farmers. If not, it would be better to save the resources involved in researching or promoting something that will never be taken up. In part because of the lack of a suitable tool, there are many examples of research or extension or policy programs that have wasted resources on proposed farming practices that were never going to be adopted.

Recognising the need, and the existing knowledge gap, a team of researchers from the Future Farm Industries CRC (all of whom had been involved in the book, the workshops and/or the review paper) decided to try to develop a simple tool to predict adoption of agricultural practices. The team, consisting of Rick Llewellyn (CSIRO), Perry Dolling (Department of Agriculture and Food WA), Roger Wilkinson (Department of Primary Industries Victoria), Mike Ewing (CRC FFI) and me, obtained funding from the CRC to employ a research fellow, Geoff Kuehne (CSIRO).

We started by developing a framework that specified how all the different bits of information would fit together. Then we quantified the model and tested it against available real-world data, where we could find it. It performed pretty well!

We’re calling the tool ADOPT (Adoption and Diffusion Outcome Prediction Tool). It provides a step-by-step approach to evaluating and predicting the likely level of adoption of specific agricultural innovations. Predictions are made in response to the answers to a series of 22 questions, which the user responds to with a particular innovation and a particular target population of potential adopters in mind.

The 22 questions cover issues relating to the innovation and the target population. In each case, the questions explore the relative advantage of the innovation and its trialability.

After a couple of years work, we have decided to release a test version of the tool to anybody who wants to have a go with it. If you’re interested, download the tool from http://www.csiro.au/ADOPT, and let us know what you think.

197 – The Danish fat tax

10 October, 2011 – 8:41 pm

About a week ago, Denmark introduced a new tax on fat in foods, in an effort to improve the health of Danes. The general idea is consistent with the sort of thing that environmental economists often recommend for other bad things, like pollution (e.g. a carbon tax). But is it sensible in this case? I have my doubts.

My daughter is currently living in Denmark and struggling a bit with the high cost of living there. So a further cost increase is the last thing she wants.

The system involves a tax of 16 kroner ($A3.00) per kilogram of saturated fat. Economists recognise two effects of this sort of tax: (a) it makes fatty foods more expensive relative to other goods, so people change how they allocate their income between alternative purchases (a “substitution effect”), and (b) as a result of having to pay the tax, people have less disposable income, and this leads to a reduction in their consumption of all goods, including of fatty foods (an “income effect”). Both result in less consumption of the good that’s being taxed, although the substitution effect is far more important in practice.

So the idea sounds OK, but it’s worth asking, would the approach really work in this case? The effectiveness of such a tax depends mainly on how responsive people are to the prices of the goods in question. It’s well known that responsiveness to price (which economists refer to as “price elasticity”) varies a lot between different goods.

Consumer demand for fat in foods strikes me as the sort of thing that is unlikely to be responsive to price. My reasoning includes that:

Fat is only one ingredient of a food, so changes in the cost of fat would have a less than proportionate effect on the cost of the food as a whole.
In developed countries, food is only a small proportion of our total expenditure. If its price goes up a bit, it would be possible to cope without greatly altering one’s consumption patterns.
People already know that fat is bad for them, but they still choose to buy fatty foods, basically because they taste good. I would not have thought that a modest increase in prices would change that much.

There is some empirical evidence to support my feeling that increasing the price of fat won’t change behaviour much. For example, Chouinard et al. (2007) find that a tax on milk in the USA in order to reduce fat consumption would have to be enormous to have much impact. For example, they say that “a 50 percent tax only lowers fat intake by 3 percent.” That’s a 50 percent tax on the milk as a whole, not just the fat component. Whole milk is about 3.3 percent fat. By my rough calculation, a 50 percent tax on milk would be about 10 times bigger than the new Danish tax, for a really small impact.

Similarly, Brownell et al. (2009) also concluded that moderate sized taxes on soft drinks basically have no impact on consumption.

Although it wouldn’t change behaviour much, these taxes would collect plenty of revenue. Indeed, if revenue collection was the aim, fat might be the ideal target for a tax, specifically because people would keep buying it, even with the tax.

This means that there is potentially an important negative consequence of the tax: it would have a disproportionately large impact on people with low incomes. They spend a larger proportion of their income on food, so the tax would have a larger proportional impact on them. Actually it might have a larger absolute impact on them, because the incidence of obesity is higher among low income groups, so presumably they spend more on fat. Chouinard et al. (2007) argued that “these fat taxes are unattractive because they are extremely regressive, and the elderly and poor suffer much greater welfare losses from the taxes than do younger and richer consumers.”

Ineffective and regressive doesn’t sound like a good tax to me.

A third problem is the specific way that this tax is designed. Apparently, the level of the tax is based on the amount of fat used in making the product, rather than the amount in the end product. If that’s true, it seems ridiculous. If the point is to improve health, why would you want to tax fat that people aren’t actually eating?

Finally, I would imagine that the system would have quite high transaction costs, such as costs of administration, reporting, monitoring, enforcement, learning, and so on. If the system would really work, they could be worth bearing, but probably not in this case.

On a more positive note, it may be that revenue from the tax could be used for other purposes that would contribute to improved health outcomes, such as research or health education. I suspect that this is the most likely route for the system to generate worthwhile benefits, although, of course, governments could use the existing tax collection system to invest in those things and thereby avoid the regressive nature of this tax.

David Pannell, The University of Western Australia

Category Archives: Behaviour

227 – ‘Disadoption’ after a project ends

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213 – The environmental planning fallacy

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203 – Predicting adoption of new farming practices

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