Category Archives: Agriculture

327 – Heterogeneity of farmers

Farmers are highly heterogeneous. Even farmers growing the same crops in the same region are highly variable. This is often not well recognised by policy makers, researchers or extension agents.

The variation between farmers occurs on many dimensions. A random sample of farmers will have quite different soils, rainfall, machinery, access to water for irrigation, wealth, access to credit, farm area, social networks, intelligence, education, skills, family size, non-family labour, history of farm management choices, preferences for various outcomes, and so on, and so on. There is variation amongst the farmers themselves (after all, they are human), their farms, and the farming context.

This variation has consequences. For example, it means that different farmers given the same information, the same technology choices, or facing the same government policy, can easily respond quite differently, and they often do.

Discussions about farmers often seem to be based on an assumption that farmers are a fairly uniform group, with similar attitudes, similar costs and similar profits from the same practices. For example, it is common to read discussions of costs and benefits of adopting a new farming practice, as if the costs and the benefits are the same across all farmers. In my view, understanding the heterogeneity of farm economics is just as important as understanding the average.

Understanding the heterogeneity helps you have realistic expectations about how many farmers are likely to respond in particular ways to information, technologies or policies. Or about how the cost of a policy program would vary depending on the target outcomes of the program.

We explore some of these issues in a paper recently published in Agricultural Systems (Van Grieken et al. 2019). It looks at the heterogeneity of 400 sugarcane farmers in an area of the wet tropics in Queensland (the Tully–Murray catchment). These farms are a focus of policy because nutrients and sediment sourced from them are likely to be affecting the Great Barrier Reef. “Within the vicinity of the Tully-Murray flood plume there are 37 coral reefs and 13 seagrass meadows”.

Our findings include the following.

  • Different farmers are likely to respond differently to incentive payments provided by government to encourage uptake of practices that would reduce losses of nutrients and sediment.
  • Specific information about this can help governments target their policy to particular farmers, and result in the program being more cost-effective.
  • As the target level of pollution abatement increases, the cost of achieving that target would not increase linearly. Rather, the cost would increase exponentially, reflecting that a minority of farmers have particularly high costs of abatement. This is actually the result that economists would generally expect (see PD182).

Further reading

Van Grieken, M., Webster, A., Whitten, S., Poggio, M., Roebeling, P., Bohnet, I. and Pannell, D. (2019). Adoption of agricultural management for Great Barrier Reef water quality improvement in heterogeneous farming communities, Agricultural Systems 170, 1-8. Journal web page * IDEAS page

320 – Fixed costs and input rates

Optimal input rates (e.g. of fertilizer to a crop) are not affected by fixed costs. I had an interesting discussion with a Canadian poultry farmer last month, who needed to be convinced of this fact.

In Canada last month I gave a seminar at the Ontario Ministry of Agriculture, Food and Rural Affairs on water pollution from agricultural fertilizers, and how an understanding of the economics of fertilizer application can help identify cost-effective policy strategies for reducing pollution.

One thing I talked about was the economics of applying too much fertilizer (more than would be in the farmer’s own financial interests).

One attendee at the seminar was a poultry farmer (who was also a scientist) who later wanted to talk to me about a reason for increasing input rates that I had not mentioned. The reason he suggested was that, by increasing input rates a farmer can increase his or her production, and even if the resulting increase in revenue is not enough to cover the additional input costs, it helps to dilute the fixed costs of production over a larger value of outputs, making the farmer better off overall.

He said that this is an idea that is common amongst poultry farmers, at least in Ontario. The problem is that it’s completely wrong. There is no way that increasing input rates above the level that maximises the difference between revenue and input costs can make a farmer better off, even if it does mean that the average fixed costs per unit of output is lower.

A simple numerical example will make this clear.

Fixed costs ($/ha)Fertilizer cost ($/ha)Yield (tonne/ha)Revenue ($/ha)Net revenue ($/ha)Average fixed cost ($/tonne)
5001.122017045.45
50201.530023033.33
50401.836027027.77
50602.040029025.00
50802.0541028024.39
501002.0841626624.04
501202.142025023.81

In this example, there is a production cost of $50/ha which is not affected by the rate of fertilizer used. In this sense it is “fixed”.

As the rate of fertilizer applied increases, the input cost goes up, and so does the crop yield, although it increases at a decreasing rate.

The net revenue is the difference between the revenue and the total costs (fixed costs plus fertilizer costs). Given this pattern of revenue and costs, the fertilizer rate that maximises net revenue is the rate corresponding to a cost of $60/ha (the fourth row of numbers in the table), giving a net revenue of $290/ha. This is the fertilizer rate that maximises profit to the farmer.

The last column shows the fixed cost per unit of production. Because the yield keeps increasing at fertilizer rates above the economic optimum, the fixed cost per unit of production keeps falling. The lowest fixed cost per unit of production is in the last row of the table, but this clearly doesn’t have the highest profit.

When you are considering the optimal level of an input, the only costs that matter are the costs that vary as you vary the level of the input. Fixed costs cannot possibly affect the optimal rate of an input because they are fixed. They stay the same at all input rates. The fact that average fixed costs per unit of output might fall at higher input rates is completely irrelevant.

I think I convinced the Canadian poultry farmer. He said he was going to talk to his other farmer friends about it.

Although boosting an input rate loses a farmer money, in many cases the amount lost will be quite small unless the input rate is especially high (due to “flat payoff functions” – see Pannell 2006). That may be why the error has not been detected by the farmer or his friends. The loss may be too small to be noticeable.

To the extent that farmers think that diluting fixed costs is a good idea, explaining to them that it is pointless may help to reduce some farmers’ tendency to apply too much fertilizer. If successful, this may contribute to reducing water pollution.

Further reading

Pannell, D.J. (2006). Flat-earth economics: The far-reaching consequences of flat payoff functions in economic decision making, Review of Agricultural Economics 28(4), 553-566. Journal web page * Prepublication version here (44K). * IDEAS page

Pannell, D.J. (2017). Economic perspectives on nitrogen in farming systems: managing trade-offs between production, risk and the environment, Soil Research 55, 473-478. Journal web page

319 – Reducing water pollution from agricultural fertilizers

I gave a talk to the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) on July 16, 2019, exploring ways to reduce water pollution from agricultural fertilizers.

Many methods have been proposed to reduce water pollution from agricultural fertilizers. The list includes use of nitrification inhibitors, land retirement, vegetation buffer strips along waterways, flood-plain restoration, constructed wetlands, bioreactors, cover crops, zero till and getting farmers to reduce their fertilizer application rates.

Last year, while I was at the University of Minnesota for several months, I reviewed the literature on these options and came to the conclusion that the option with the best prospects for success is reducing fertilizer application rates. It’s the only one of these options that is likely to be both effective and cheap.

In my talk, I made the case for agencies who are trying to reduce pollution to focus on reducing fertilizer rates.

In brief, I identified three key reasons why there are untapped opportunities to reduce fertilizer rates.

1. Some farmers apply more fertilizer than is in their own best interests. Surveys in the US suggest that something like 20 to 30% of American farmers could make more profit if they reduced their rates. If it was possible to identify these farmers and convince them of this, it would be a rare win-win for farmers and the environment.

2. Even those farmers who currently apply fertilizer close to the rates that would maximize their profits could cut their rates without sacrificing much profit. Within the region of the economically optimal rate, the relationship between fertilizer rate and profit is remarkably flat. New estimates by Yaun Chai (University of Minnesota) of this relationship for corn after corn in Iowa indicate that farmers could cut their rates by 30% below the profit-maximizing rate and only lose 5% of their profits from that crop. For corn after soybeans, the equivalent opportunity is for a 45% cut!

3. Some farmers believe that applying an extra-high rate of fertilizer provides them with a level of insurance. They think it reduces their risk of getting a low yield. However, the empirical evidence indicates exactly the opposite. When you weigh up the chances of an above-average yield and a below-average yield, higher fertilizer rates are actually more risky than lower rates. In addition, price risk interacts with yield risk to further increase the riskiness of high rates.

I think there is a real opportunity to explore these three factors in more depth and try to come up with policy approaches that could deliver reduced fertilizer usage in a highly cost-effective way. Some of it would just be about effective communication (e.g. the design of “nudges”, as popularised in behavioural economics) while some might require a modest financial commitment from government or industry. One idea is to offer something like a money-back guarantee to those farmers who agree to reduce their rates by a specified amount. If they lose money as a result, they get compensation. Because of the flatness of the fertilizer-profit relationship, the payments required would usually be very small.

I recorded the presentation to OMAFRA, and it’s available here.

Further reading

Pannell, D.J. (2006). Flat-earth economics: The far-reaching consequences of flat payoff functions in economic decision making, Review of Agricultural Economics 28(4), 553-566. Journal web page * Prepublication version here (44K). * IDEAS page

Pannell, D.J. (2017). Economic perspectives on nitrogen in farming systems: managing trade-offs between production, risk and the environment, Soil Research 55, 473-478. Journal web page

316 – Resources for agri-environmental schemes

I’ve been asked to present a talk in Ireland in two weeks, on the topic “The Design of Effective Agri-Environment Schemes”. In putting the talk together, it struck me that I (with help from colleagues) have developed quite a few resources in this space, so I’ve collected them on a new web site to make them easily accessible.

Agri-environmental schemes (or programs or policies) aim to reduce the adverse impacts of agriculture on the environment. There are many such schemes around the world, but often they are not very efficient or effective. We could often do a lot better if we did a smarter job of designing and implementing these schemes.

Not that it’s easy. There are so many aspects to consider: the effectiveness of different practices at reducing environmental damage, their attractiveness (or otherwise) to farmers, the mechanisms to be used to promote the best practices, the costs and risks of different approaches, which environmental issues are the priorities, and so on. In my view, most designers of agri-environmental schemes don’t appreciate what a difficult task they are trying to do, and make do with relatively quick and dirty approaches to the design.

The resources I’ve included on the web site address a wide range of relevant issues, including:

  • Lessons from past agri-environmental schemes
  • The selection of appropriate policy mechanisms
  • Measuring environmental values
  • Ranking projects, including the choice of an appropriate metric
  • Additionality
  • Understanding and predicting farmers’ adoption of new practices
  • Dealing with uncertainty and including systems for learning from experience
  • The need to pull off that together in a coherent framework

It includes journal articles, books, reports, frameworks, computer tools, web sites, and blog posts, plus links to my free online course on “Agriculture, Economics and Nature”.

Overall, if an organisation wanted to design and deliver an agri-environmental scheme that would really deliver outcomes, they could benefit greatly from the material on this site. The URL is www.resources4aes.net.

Further reading

Pannell, D.J. (2008). Public benefits, private benefits, and policy intervention for land-use change for environmental benefits, Land Economics 84(2): 225-240. Full paper (140K) * IDEAS page

312 – The economics of nitrogen in agriculture

The global challenge of feeding seven billion people would be more difficult without nitrogen fertilizer, but it causes pollution of rivers, lakes and coastal waters around the world, and it contributes to emissions of greenhouse gases. It increases the profitability of individual farmers, but it is over-applied in many cases, wasting money and needlessly worsening environmental problems.

These are, in large part, economic issues. In a recent paper I attempted to summarise the large and diverse research literatures on the economics of nitrogen in agriculture. Here are some of the key points.

At the farm level

The production function for nitrogen (N) fertilizer (the relationship between yield and the rate of nitrogen fertilizer) always exhibits diminishing marginal returns – it flattens out at higher fertilizer rates. In dry conditions, yield may even fall at high N rates.

The rate of nitrogen fertilizer that maximises expected profit is less than the rate that maximises expected yield, sometimes much less.

Here’s a really neat tool that shows the relationships between N, yield and profit for corn in the US. http://cnrc.agron.iastate.edu/

Visual effect of nitrogen fertilizer on corn

Risk

N fertilizer affects the riskiness of cropping. For two reasons, higher N rates are more risky (i.e. profits are more variable at higher N rates). One reason is that the grain price is itself risky. Since profit depends on grain price times yield, and yield usually increases with increasing N rate, the more N you apply, the more variable your profit will be. In addition, yield also tends to be slightly more variable at higher N rates.

Flat payoff functions

There always exists a range of fertilizer rates that are only slightly less profitable than the profit-maximising rate (i.e. a range where the payoff function is relatively flat), and in most cases, that flat range is wide. This means that the farmer has flexibility in choosing the fertilizer rate. If a lower rate would better satisfy another objective (e.g. risk reduction), the farmer can choose that rate with little sacrifice of profit. If regulators require a moderate reduction in fertilizer rate below the farmer’s economic optimum, the cost to the farmer will be small. Flat payoff functions also mean that the benefits of precision-agriculture technologies that spatially adjust fertilizer rates within a field will usually be small.

Nitrogen pollution

Typically, the marginal cost to farmers of nitrogen emissions abatement is low for low levels of abatement but increases at an increasing rate as the required level of abatement increases. As a result, modest targets for abatement can often be achieved at low cost, but ambitious targets can be extremely costly.

Spatial targeting of abatement effort (both at the regional and international scales) can generate much larger benefits than untargeted policies, although these additional benefits are likely to be offset to some degree by increased costs required to run a targeted program (costs of information and administration).

Policies intended to increase farmers’ incomes can have the unintended consequence of increasing nitrogen pollution by increasing the incentive to apply fertilizer.

Further reading

Pannell, D.J. (2017). Economic perspectives on nitrogen in farming systems: managing trade-offs between production, risk and the environment, Soil Research 55, 473-478. Journal web page

Gandorfer, M., Pannell, D.J. and Meyer-Aurich, A. (2011). Analyzing the Effects of Risk and Uncertainty on Optimal Tillage and Nitrogen Fertilizer Intensity for field crops in Germany, Agricultural Systems 104(8), 615-622. Journal web page ♦ IDEAS page

Schilizzi, S. and Pannell, D.J. (2001). The economics of nitrogen fixation, Agronomie 21(6/7), 527-538.

Pannell, D.J. and Falconer, D.A. (1988). The relative contributions to profit of fixed and applied nitrogen in a crop‑livestock farm system, Agricultural Systems 26(1), 1‑17. Journal web page ♦ IDEAS page

Pannell, D.J. (2006). Flat-earth economics: The far-reaching consequences of flat payoff functions in economic decision making, Review of Agricultural Economics 28(4), 553-566. Journal web page ♦ IDEAS page