Political Economy of Crop Insurance

by Levi Russell

Last week my (co-authored) article on the political economy of crop insurance in the next farm bill (coauthored with Art Barnaby of Kansas State University) was published in Choices Magazine. I thought I'd reproduce the theme overview here and link to all 4 articles for those who are interested.

The Farm Bill, passed every four or five years, is a large piece of legislation which includes agricultural, food, conservation, and rural development programs. The most recent bill, passed in 2014, made significant cuts to commodity programs and increased budgeted spending on crop insurance. This change shifts the focus of farm risk management toward crop insurance, making it an even more important part of a producer’s toolkit. Looking ahead to the next farm bill in 2018/2019, this focus on crop insurance will likely continue.

The articles in this issue anticipate three discussions surrounding crop insurance’s role in the next farm bill: the political economy of crop insurance by Barnaby and Russell, economic evaluation of crop insurance’s role in the safety net by Zacharias and Paggi, and crop insurance’s role in specialty crop agriculture by Paggi.

Barnaby and Russell examine three crop insurance alternatives which are likely to be proposed in the debate over the next farm bill:

 1. Replacing crop insurance with a free, area-based disaster program,
 2. Making modifications to existing policy which would significantly reduce support to  farmers and jeopardize the private delivery system, and
 3. Complete elimination of the safety net.

The article summarizes the political factors and their interaction with the economic effects of these proposals.

Zacharias and Paggi identify the key considerations for improving crop insurance’s role in the farm safety net. Among these are regional and commodity-specific considerations, government budget constraints, and interactions between crop insurance and other titles in the farm bill. They emphasize the importance of developing appropriate metrics for evaluating the simultaneous performance of crop insurance and commodity programs and conclude with a research agenda for examining these issues.

Paggi discusses the broader role of crop insurance as a risk management tool for specialty crop producers. Specialty crops are of interest due to the increase in specialty crops’ share of the total crop insurance liability over the last 15 years. Paggi details the connection between crop insurance and specialty crops and provides a discussion of factors affecting the future of this connection.

Finally, Woodard addresses the elasticity of demand for crop insurance issues.  This key value will determine the maximum achievable size of any cuts in USDA’s share of the crop insurance premium and still maintain a politically acceptable level of farmer participation in crop insurance needed to prevent any future ad hoc disaster program.  It is critical for policy makers to understand the impact of elasticity of demand to prevent unintended consequences by making Federal budget cuts to crop insurance.  All budget cuts are not equal so how those cuts, if any, are made is extremely important.

Given the important role of crop insurance in the future of the farm safety net, political and economic factors affecting policy decisions are particularly of interest. This issue provides a first look at the conversations policy makers, industry representatives, and academic economists will have leading up to the next farm bill.

Coase and Hog Cycles

by David Williamson

If you read this blog, then you're probably familiar with Ronald Coase's work on the importance of transaction costs. But did you know that Coase devoted a substantial portion of his early career to criticizing the Cobweb Model? He actually wrote 4 separate articles on the subject between 1935 and 1940, but not one makes Dylan Matthew's list of Coase's top-five papers. This work is actually really fascinating in the context of economic intellectual history, so here is a quick summary!  

The 1932 UK Reorganization Commission for Pigs and Pig Products Report

It all started when the UK Reorganization Commission for Pigs and Pig Products claimed in a 1932 report that government intervention was needed to stabilize prices in the hog industry. The Commission found that hog prices followed a 4-year cycle: two years rising and two years falling. The Commission explained this cyclical behavior using the Cobweb Model. In this model, products take time to produce. So, to know how much to produce, firms have to guess what the price will be when their product is ready to bring to the market. If producers are systematically mistaken about what prices will be, this could lead to predictable cycles in product spot prices.

The Cobweb Model

How forecasting errors can lead to cycles in product prices is illustrated in the figure below. Suppose we begin time at period 1 and hog producers bring Q1 to the market to sell. Supply is essentially fixed this period because producers can't produce more hogs on the spot, so the price that prevails on the market will be P1. Since this price exceeds the marginal cost of production (represented by S), the individual producers wish they had produced more. Now, when the producers go back home to produce more hogs, they have to guess that the price will be when their hogs are ready to sell. Suppose it will take 2 years to produce more hogs. The UK Reorganization Commission argued that hog producers will assume the price of hogs next period will be the same as it was this period (in other words that producers had "static" expectations about price). That means, in this context, hog producers think the price of hogs in 2 years will still be P1. So each producer will individually increase production accordingly. However, when the producers return to the market in 2 years, they will find that everyone else increased production too and that quantity supplied is now Q2. As a result, the price plummets to P2 and the producers actually lose money. Not learning their lesson, the hog producers will again go home and assume that the price next period will be P2 and collectively cut back their production to Q3. Hopefully you see where this is going, even if the hog producers don't. The price will go up again in 2 years and then down again in 2 more. Thus, we have a 4-year cycle in hog prices. How long will this cycle continue? That depends on the elasticities of supply and demand. If demand is less elastic than supply, as was believed to be the case in the hog market, then the price swings will continue forever and only get bigger as time goes on.

Source: Wikipedia

Coase Takes the Model to the Data

The Cobweb Model is really clever, but does it actually capture the reality of the hog market? Coase and his co-author Ronald Fowler tried to answer that question by evaluating the model's assumptions. First, are hog producer expectations truly static? Expectations cannot be observed directly, but Coase and Fowler (1935) used market prices to try and infer whether producer expectations were static. It didn't seem like they were. Second, does it really take 2 years for hog producers to respond to higher prices? Coase and Fowler (1935) spend a lot time discussing how hogs are actually produced. They found that the average age of a hog at slaughter is eight months and that the period of gestation is four months. So a producer could respond to unexpectedly higher hog prices in 12 months (possibly even sooner since there were short-run changes producers could also make to increase production). So why does it take 24 months for prices to complete their descent? Even if we assumed producers have static expectations, shouldn't we expect the hog cycle to be 2 years instead of 4?  

This evidence is hard to square with the Cobweb Model employed by Reorganization Commission, but Coase's critics were not convinced. After all, if it wasn't forecasting errors that were driving the Hog Cycle, then what was? "They have, in effect, tried to overthrow the existing explanation without putting anything in its place" wrote Cohen and Barker (1935). Coase and Fowler (1937) attempted to provide an explanation, but this question would continue to be debated for decades.

The Next Chapter

Ultimately, John Muth (1961) proposed a model that assumed producers did not have systematically biased expectations about future prices (in other words that they had "rational" expectations). Muth argued this model yielded implications that were more consistent with the empirical results found by Coase and others. For example, rational expectations models generated cycles that lasted longer than models that assumed static or adaptive expectations. So a 4-year hog cycle no longer seemed as much of  a mystery. I'm not sure what happened to rational expectations after that. I hear they use it in Macro a bit.  Anyways, if you are interested in a more detailed summary of Coase's work on the Hog Cycle, then check out Evans and Guesnerie (2016). I found this article on Google while I was preparing this post and it looks very good.

References

Evans, George W., and Roger Guesnerie. "Revisiting Coase on anticipations and the cobweb model." The Elgar Companion to Ronald H. Coase (2016): 51.

Coase, Ronald H., and Ronald F. Fowler. "Bacon production and the pig-cycle in Great Britain." Economica 2, no. 6 (1935): 142-167.

Coase, Ronald H., and Ronald F. Fowler. "The pig-cycle in Great Britain: an explanation." Economica 4, no. 13 (1937): 55-82.

Cohen, Ruth, and J. D. Barker. "The pig cycle: a reply." Economica 2, no. 8 (1935): 408-422

Muth, John F. "Rational expectations and the theory of price movements."Econometrica: Journal of the Econometric Society (1961): 315-335.

Beef Trade and the TPP

by Levi Russell

As one of my colleagues recently pointed out at an Extension meeting, both major-party candidates are (at least claiming to be) anti-international-trade. It's true that trade restrictions would be harmful to many segments of the U.S. agriculture sector, including beef. I ran across a great article in Beef Magazine last month that shows the U.S.' top trade partners. The chart below is lifted from the article.

As you can see, Australia is responsible for a substantial proportion of beef (not cattle) imports into the U.S. Our exports go primarily to Asian markets and our geographical neighbors. The article goes into some detail about the recent change in fresh beef imports from Brazil. The new policy is a tariff-rate-quota; details are available in the article and in this video.

Since I strive to tell the other side of the story as fairly as possible, I thought I'd link to what I believe is the most sophisticated argument against the Trans Pacific Partnership I've read. I recommend reading it, even if you are pro-TPP.

Legal and Economic Implications of Farm Data

by Ashley Ellixson

Discussions of farm data are a hot topic not only in today’s agricultural industry but also across the legal field.  I recently authored an article that describes the legal and economic concerns surrounding data ownership, privacy rights, and possible recourse in event of intentional data breach.  The publication aims to answer the questions around “who owns farm data?”, “what happens when farm data is misappropriated?” and “what can I do to protect my farm’s data?”  These questions and many more are swirling around industry, legislatures, and farm organizations.  

Until the law defines farm data or a court speaks to the protections of such data, experts in the field can only suggest best management practices (both at the farm-level and the legal liability level). From the farm perspective, not only the law but the relative value of farm data will direct the optimal choice for damages, if any. Damages may be realized as loss of local bargaining power or a direct cost to the farmer; however, only time will tell. This collaborative effort between Kansas State University and University of Maryland can be found on the AgManager.info website.  

Ashley Ellixson, J.D., LL.M. 

Guest Contributor

@Legally_Ashley

E-mail

Precision Agriculture Implications for Farm Management: Farmland Leasing Example

By Terry Griffin

In the US, most farmland is owned by the farmer. However, substantial percentages are owned by someone other than the farmer. In the most recent USDA Census of Agriculture, 62% of farmland was owned by the farmer-operator. The percentage of rented farmland has ranged from 35% in the 1960’s to nearly 43% in 1992. Rented farmland proportions are higher in the Delta, Corn Belt, and Plains states than the rest of the country (USDA Census of Agriculture 2012). Therefore, a primary focus of farm management has been on acquiring and maintaining control of farmland; and an important topic that precision agricultural technologies can be a useful tool.

During my precision agriculture presentations I have been discussing the value of data. In particular, the prevalence of farmers and service providers creating printed maps from yield, soil, and other data as the ultimate use of data was discussed. The value of these printed maps was debated. Upon stating that unused data has no value, I mentioned that printed yield maps usually end up with similarly very low values, but with a notable exception for farm management. One exception is that some landowners appreciate printed yield maps, especially when presented in a format such as framed like a picture suitable for hanging or as kitchen table place mats. Several participants at the meeting paused to make written notes, and several hallway conversations followed. Given the interest, it seemed worthy of a short write-up to share this idea.

Even though not all landowners would find value in receiving printed yield maps at the end of the year, many would cherish this and it ultimately could make the difference for a farmer to continue farming that tract. The overall farm management principle here is that farmers who get to know what makes their landowners happy can position themselves better to maintain and enhance that relationship (assuming some level of utility maximizing behavior). Some landowners view their investment just as that, an investment, and value the revenue stream only (i.e. profit maximizing). Others would enjoy telling their friends about their asset, the history, and current events expressed through a printed yield map, either framed or imprinted on a coffee mug or perhaps some other creative expression of it.

At a time when cutting-edge agricultural discussions include ‘big data’, telematics, and autonomous decision-making processes, there are still many opportunities to use precision agricultural technologies to improve basic farm management. In particular with the current economic farm environment of potentially increased financial stress, existing technology on the farm may aid in ways not previously considered. Other examples of using precision agriculture technology for farm management exist that will be discussed at a later time.

Farmer Hayek at the 2016 Southern Ag Economics Association Meetings

Four of us will either be presenting at the SAEA meetings next week or are authors on papers and posters. Here's a list of titles with links to abstracts and full papers!

Levi Russell

Price Impacts of Brahman Influence in South Texas

Profitability of Beef Cattle Best Management Practices in South Texas


Michael Langemeier

The Challenges of Precision Agriculture: Is Big Data the Answer?

Economic Threshold for Dynamically Optimal Late Blight Management


Gregg Ibendahl

Kansas Farm Profitability Persistence: Do Top Farms Remain Top Farms? (also with Terry Griffin)


Terry Griffin

Defining the Barriers to Telematics for Precision Agriculture: Connectivity Supply and Demand

Value of Internet Connectivity Uptime for Multiple Vehicles Using Automated Section Control

Applying Data Envelopment Analysis Methodology to Site-Specific Precision Agriculture Data

Farmers' willingness to pay for farmland based on machinery and precision technology adoption

Potpourri

Ag Econ Research & Extension
Jayson Lusk discusses an article on returns to publicly-funded agricultural research and extension. He also tackles the question: "Is ag econ academic research cited?" and answers in the affirmative.

Is Econ 101 Worthless?

David Henderson and Don Boudreaux respond to Noah Smith's contention that most of what we teach in Econ 101 is wrong.

Healthcare Reform
Two perspectives on recent developments related to Obamacare: one from Shikha Dalmia and another from Paul Krugman.

I, Pencil Revisited?
George Leef responds to a criticism of the famous essay "I, Pencil."

Regulatory Announcements
The Obama administration picks some interesting dates to announce new regulations.

A student gives a creative example of an externality.
David Henderson's student has a good understanding of Public Choice.

A new edition of Alchian and Allen's textbook.
Don Boudreaux lists some myths busted in a forthcoming edition of Alchian and Allen.