Agricultural Marketing and Price Analysis

About 10 years ago, Bailey Norwood and I published an undergraduate textbook entitled Agricultural Marketing and Price Analysis.  The book was originally published by Prentice-Hall. Over the years, we'd considered revising and updating various portions of the book, but the publishers were never appeared interested in releasing a second edition.    

Now, Waveland Press was secured the rights to publish the textbook (their site for the book is here).  For now, this is just a reprint of our original version, but they've agreed to put out a new edition in the future as well.  Bailey and I will probably pick up a couple co-authors who have been using the book in class.  More on that in a year or two when a new edition is set to drop. 

For now, you can enjoy the new cover.

Or, if you can read Greek, you can also buy that translation here. 

How to Feed the World

That's the title of a new book edited by Jessica Eise and Ken Foster that was just released last week.  The book is a collection of essays primarily from my colleagues in the Department of Agricultural Economics here at Purdue, but it includes contributions from Purdue faculty in other academic disciplines as well.  I had the privilege of writing the afterward.  

Here is the table of contents:

Chapter 1. Inhabitants of Earth- Brigitte S Walforf
Chapter 2. The Green, Blue, and Gray Water Rainbow- Laura C Bowling and Keith A Cherkauer
Chapter 3. The Land that Shapes and Sustains Us- Otto Doering and Ann Sorensen
Chapter 4. Our Changing Climate- Jeff Dukes and Thomas W Hertel
Chapter 5. The Technology Ticket- Uris Baldos
Chapter 6. Systems- Michael Gunderson, Ariana Torres, Michael Boehlje, and Rhonda Phillips
Chapter 7. Tangled Trade- Thomas W Hertel
Chapter 8. Spoiled, Rotten, and Left Behind- Ken Foster
Chapter 9. Tipping the Scales on Health- Steven Y Wu
Chapter 10. Social License to Operate- Nicole J Olynk Widmar
Chapter 11. The Information Hinge- Jessica Eise
Chapter 12. Achieving Equal Access- Gerald Shively

Gains to Chinese Agricultural Research and Extension

Last week, Nature published this piece on a massive study conducted by Chinese agricultural researchers.  Accompanying the piece was a summary/editorial describing the study:

“Running from 2005 to 2015, the project first assessed how factors including irrigation, plant density and sowing depth affected agricultural productivity. It used the information to guide and spread best practice across several regions: for example, recommending that rice in southern China be sown in 20 holes densely packed in a square metre, rather than the much lower densities farmers were accustomed to using.

The results speak for themselves: maize (corn), rice and wheat output grew by some 11% over that decade, whereas the use of damaging and expensive fertilizers decreased by between 15% and 18%, depending on the crop. Farmers spent less money on their land and earned more from it — and they continue to do so.”

The project appears to have created substantial economic benefits.  The authors of the study write:

“Direct profit, calculated from increased grain output and reduced nitrogen fertilizer use, was US$12.2 billion (Table 1), which does not include relevant environmental benefits associated with reductions in reactive nitrogen losses and in GHG emissions. On the basis of the rough estimates, the cost:benefit ratio would be 1:226. ”

The cost-benefit ratio is in some ways over- and in other ways under-estimated.  The benefits are over-estimated in the sense that it does not appear it takes into consideration the fact that greater grain production will dampen prices (it is also unclear how the benefits and costs are discounted or not over time).  The benefits are under-estimated because they do not include any of the environmental improvements.  

It is useful to contrast these findings with the rather large research on the value of agricultural R&D and extension investments in the U.S.  Jin and Huffman calculated the rate of return on spending on agricultural extension in the U.S. at 100%.  More broadly, Julian Alston gave the fellow's address at this this year's AAEA meetings on precisely this topic, and his remarks were recently published in the American Journal of Agricultural Economics.  He writes:

“Our estimates (Alston et al. 2010a, 2011) indicate that U.S. federal and state government expenditure on agricultural research and extension generates benefit-cost ratios of at least 10:1 (more likely 20:1 or 30:1)—evidence of a serious underinvestment. Pardey and Beddow (2017), echoing Pardey, Alston, and Chan-Kang (2013), suggested that a reasonable first step would be to double U.S. public investment in agricultural R&D—an increase of, say, $4 billion over recent annual expenditures. A conservatively low benefit-cost ratio of 10:1 implies that having failed to spend that additional $4 billion per year on public agricultural R&D imposes a net social cost of $36 billion per year”

Given the lower level of development in China, it is certainly possible to imagine that the rate of return on investments in agricultural research and extension being higher than is the case in the U.S.  But, can the benefit cost ration really be 10 times higher in China than the U.S. (226:1 vs. 20:1)?  One interesting thing about Chinese study in Nature is that, if I read correctly, it didn't entail development of any new genetics, pesticides, etc; rather it seemed to largely entail the application of previously developed "science" and practices to the particular geographies in question, and as such, the costs might have been much lower than in situations where new technologies are being created. 

In a sense, the shows an enormously high value to "better information."  This contrasts with perspectives such as this one by David Pannell, who argues that better technologies are much more impactful than "better information."  One way to reconcile this seeming paradox is that that the "information" conveyed to the Chinese farmers was to use better technologies and practices that were already known to exist.  Here in the developed world, the knowledge/technologies are likely already more widely dispersed.  

I'll end with this quote from Alston's paper, who articulated the value of increased productivity in a createive way:

“Clearly agricultural productivity growth is enormously valuable. Of the actual farm output in 2007, worth about $330 billion, only one-third (i.e., 100/280 = 0.36) or about $118 billion could be accounted for by conventional inputs using 1949 technology, holding productivity constant. The remaining two-thirds (i.e., 180/280 = 0.64) or about $212 billion in that year alone, is attributable to the factors that gave rise to a 180% increase in productivity since 1949—including improvements in infrastructure and inputs (if not captured already in the indexes), as well as new technology, developed and adopted as a result of agricultural research and extension, and other sources of innovations.”

Understanding the Impacts of Food Consumer Choice and Food Policy Outcomes

The journal Applied Economics Perspectives and Policy just published a special issue in which  agricultural and applied economists provide their thoughts on how we might help tackle some of society’s most difficult problems and challenges.  I co-authored one of the articles with Jill McCluskey.  Here's the abstract:

“The food consumer plays an increasingly prominent role in shaping the food and farming system. A better understanding of how public policies affect consumer choice and how those choices impact health, environment, and food security outcomes is needed. This paper addresses several key challenges we see for the future, including issues related to dietary-related diseases and the efficacy of policies designed to improve dietary choices, trust in the food system, acceptance of new food and farm technologies, environmental impacts of food consumption, preferences for increased food quality, and issues related to food safety. We also identify some research challenges and barriers that exist when studying these issues, including data quality and availability, uncertainty in the underlying biological and physical sciences, and the challenges to welfare economics that are presented by behavioral economics. We also identify the unique role that economists can play in helping address these key societal challenges.”

Other contributions in the special issue include:

• "Agricultural and Applied Economics Priorities for Solving Societal Challenges" by Jill McCluskey, Gene Nelson, and Caron Gala
• "Economics of Sustainable Development and the Bioeconomy" by David Zilberman, Ben Gordon, Gal Hochman, Justus Wesseler
• "Sustaining our Natural Resources in the Face of Increasing Societal Demands on Agriculture: Directions for Future Research" by Madhu Khanna, Scott Swinton, Kent D Messer
• "Climate Change as an Agricultural Economics Research Topic" by Bruce McCarl and Tom Hertel
• "Big Data in Agriculture: A Challenge for the Future" by Keith Coble, Ashok Mishra, Shannon Ferrell, and Terry Griffin
• "The Economic Status of Rural America in the President Trump Era and beyond" by Stephan Goetz, Mark Partridge, Heather Stephens
• "Food Insecurity Research in the United States: Where We Have Been and Where We Need to Go" by Craig Gundersen and James Ziliak
• "The Farm Economy: Future Research and Education Priorities" by Allen Featherstone
• "A Research Agenda for International Agricultural Trade" by Will Martin
• "Energy Economics" by Wally Tyner, and Nisal Herath

An unplanned shock to beef quality supply

In economics, it's tough to separate correlation from causation because the world is a messy place with lots of things changing at the same time.  As a result, empirical economists are always on the lookout for natural experiments, or situations where there was some random, unanticipated "shock" to the market that can help us get closer to an experimental setting, where we know a change in X was not due to a change in Y.  

I was reading through the latest edition of Meatingplace magazine, and was surprised to see a story about an event that provides precisely the sort of unplanned "shock" that we are always looking for. In particular, about eight years, ago, the USDA started using cameras (rather than people) to determine meat quality.  The two main quality grades are Choice (more marbled (or fattier), higher quality) and Select (leaner, lower quality).  

Apparently in June 2017, the USDA issued an update to USDA's camera grading system that "appeared to inaccurately assess the degree of marbling on some carcasses - allegedly grading some Choice that should have been Select." The USDA issued a new update to the cameras in October in 2017 to correct the problem. One analysis, quoted in the article, estimates that about 12,000 cattle were inadvertently graded Choice rather than Select (a 2.4% increase according to the article, if I'm reading it right).

So, we have an unplanned, unanticipated "shock" to the beef quality market that shifted the supply of high quality meat and reduced the supply of lower quality meat.  This is illustrated by the two vertical lines in the figure (the lines are vertical because the supply is fixed in the short-run: you can't take Choice carcass and turn it into a Select one once the animal has been removed from feed).  If demand curve slopes downward, then this unanticipated increase in supply of Choice (and reduction in Select) quantity, should reduce the price premium for Choice over Select.  And in-fact, because the shock to supply is completely exogenous (it had nothing to do with demand but with a camera update), we should be able to use the natural experiment to estimate the slope of the relative demand curve for high quality beef (or the so-called elasticity of demand).  

Here is data from the USDA on the difference in price between Choice and Select beef, or the so-called Choice-to-Select spread, over the time period of interest (in particular, this is the difference in boxed beef cutout values measured in dollars per hundredweight - or cents per pound).    

Just as one would expect, the increase supply of Choice relative to Select led to a reduction in the price premium charged for Choice relative to Select.  Of course, these raw data might be misleading - what if there is a seasonal pattern in which the Choice-to-Select spread falls every year from June to October?  To address this concern, I downloaded the last 10 years of data on the Choice-to-Select spread and found that the observed Choice-to-Select spread from mid June to late October in 2017 was $4.34/cwt lower than would be expected even after controlling for seasonality (month of the year), year, and a time trend.  This works out to about a 31% lower Choice-to-Select spread than would have expected during this time had it not been for the grading camera update (assuming there aren't other confounds I'm not controlling for).  

So, good news, it appears, the demand curves do indeed slope downward.  We can also go further if we take the aforementioned 2.4% change in quantity at face value that came from the Meatingplace article.  The price flexibility of demand (this is roughly the inverse of the elasticity of demand) for Choice (relative to Select) is given by the percent change in price over quantity, or -31%/2.4% = -12.9%.  So for every 1% increase in the quantity of Choice vs. Select supplied, there is a 12.9% reduction in the Choice-to-Select price spread.