New Published Research

I've had several new papers published in the last month or so that I haven't had a chance to discuss here on the blog.  So, before I forget, here's a short list.

• What to Eat When Having a Millennial over for Dinner with Kelsey Conley was published in Applied Economic Perspectives and Policy.  We found Millennials have higher demand for cereal, beef, pork, poultry, eggs, and fresh fruit and lower demand for “other” food, and for food away from home relative to what would have been expected from the eating patterns of the young and old 35 years prior.  I'd previously blogged about an earlier version of this paper.
• A simple diagnostic measure of inattention bias in discrete choice models with Trey Malone in the European Review of Agricultural Economics. Measuring the "fit" of discrete choice models has long been a challenge, and in this paper, we suggest a simple, easy-to-understand measure of inattention bias in discrete choice models. The metric, ranging from 0 to 1, can be compared across studies and samples.
• Mitigating Overbidding Behavior using Hybrid Auction Mechanisms: Results from an Induced Value Experiment with David Ortega Rob Shupp and Rudy Nayga in Agribusiness.  Experimental auctions are a popular and useful tool in understanding demand for food and agricultural products. However, bidding behavior often deviates from theoretical predictions in traditional Vickrey and Becker–DeGroot–Marschak (BDM) auction mechanisms. We propose and explore the bidding behavior and demand revealing properties of a hybrid first price‐Vickrey auction and a hybrid first price‐BDM mechanism. We find the hybrid first price‐Vickrey auction and hybrid first price‐BDM mechanism significantly reduce participants’ likelihood of overbidding, and on average yield bids closer to true valuations. 

GMO labels - not as bad as I thought

Science Advances (the open-access version of Science Magazine) just published a paper I co-authored with Jane Kolodinsky from the University of Vermont.  I suspect the paper's findings may raise a few eyebrows, as we find that opposition to GMOs in Vermont fell relative to that in the rest of the U.S. after mandatory labeling was adopted in that state.

Some background context might be useful here.  Several years go, I was decidedly in the camp that thought imposition of mandatory labels would cause people to be more concerned about GMOs because it would signal that something was unsafe about the technology.  Prominent scholars such as Cass Sunstein have argued the same.  A few years ago, Marco Costanigro and I put this hypothesis to the test in a paper published by Food Policy, and we found little evidence (in a series of survey-based experiments) that the label per se neither increased or decreased aversion to GMOs.  So, I was less convinced that this particular argument against mandatory GMO labeling was valid, but I was still unsure.  

Then, last summer at the annual meetings of the Agricultural and Applied Economics Association (AAEA), I saw Jane present a paper based on survey data she collected in Vermont before and after mandatory labels went into place there.  Her data suggested opposition to GMOs fell at faster rate after mandatory labels were in place.  Despite my findings in Food Policy, I remained dubious and Jane and I went back and forth a bit on the robustness of her findings. 

I'd been in enough conversations with Jane to know that we had different philosophical leanings about the desirability of GMOs, but this was an empirical question, so we put our differences aside and decided to join our data and put the hypothesis to the test.  Through the Food Demand Survey (FooDS), I had been collecting nationwide data on consumer's concerns about GMOs, and I suggested we combine our two sets of data and do a true "difference-in-difference" test: Did the difference in concern among consumers in VT and the result of the US increase or decrease after mandatory labeling was adopted in VT?

Our article in Science Advances has the result:

“This research aims to help resolve this issue using a data set containing more than 7800 observations that measures levels of opposition in a national control group compared to levels in Vermont, the only U.S. state to have implemented mandatory labeling of GE foods. Difference-in-difference estimates of opposition to GE food before and after mandatory labeling show that the labeling policy led to a 19% reduction in opposition to GE food. The findings help provide insights into the psychology of consumers’ risk perceptions that can be used in communicating the benefits and risks of genetic engineering technology to the public.”

One important caveat should be mentioned here.  Our result does NOT suggest people will suddenly support GMOs once mandatory labels are in place.  Rather, our findings suggest that people will be somewhat less opposed than they were prior to labels.  I mention this because in the wake of my paper with Marco in Food Policy some of the media's interpretation of our results (such as that of the New York Times editorial board), could have been construed as suggesting that imposition of mandatory labels would not cause economic harm.  That may or may not be true.  But, this new study suggest that labels per se may in fact reduce opposition.

It was great to work with Jane on this project, and for me it was a good lesson to test your beliefs, particularly when there are theoretical reasons that could support the opposing point of view.

I'll end with a key graph from the paper.

Future Food Demand

Will we be able to produce enough food to feed a more populated and likely richer world in 2050?  The answer to this question depends not just on what technologies we develop but also on what people in different parts of the world will want to eat in 2050.  A new paper by Christophe Gouel and Houssein Guimbard in the American Journal of Agricultural Economics takes data from consumption of 7 categories of food in over 100 different countries to explore how food demand changes with income and population, and then they use these estimates to project future food demand given estimates of income and population growth.  

First, they show that as incomes rise, demand for oils and fats and for animal-based food increases. 

The following graph (from their appendix) shows the projected changes in global demand for different types of food on out to 2100.

Here is a summary of their findings:

“The main results of our projections to 2050 are that (a) food demand will increase by 47%, representing less than half of the growth experienced in the four decades before 2010; (b) this growth will come mainly from developing countries because in high-income countries, food demand is already at high per capita levels and population growth will be low; (c) growth in starchy staples will be small at 19%, supported by population increases because per capita consumption is predicted to decrease while demand for animal-based food will double, thereby increasing the global share of animal-based calories from 17% in 2010 to 23% in 2050; and (d) these projections present large uncertainties that are neglected in related studies: under alternative plausible futures for GDP and population, demand for animal-based calories increases between 74% and 114%.”

New findings on agricultural productivity

The American Journal of Agricultural Economics has recently published several new and important papers on agricultural productivity.  Whether agriculture is becoming more or less productive is a critical question as it relates to sustainability (are we getting more while using less?), food security (can food production outpace population growth?), and consumer well-being (are food prices expected to rise or fall?). 

These papers focus on "total" or "multifactor" productivity rather than just yield.  Yield is a partial measure of productivity - it is the amount of output per unit of one input: land.  One can increase yield by adding more of other inputs such as water, fertilizer, labor, etc.  What we want is a measure of how much output has increased once we have accounted for uses of all inputs, and this is total or multifactor productivity.

The first paper by Matthew Andersen, Julian Alston, Phi Pardey, and Aaron Smith is worrisome.  They write:

“In this paper we have used a range of data and methods to test for a slowdown in U.S. farm productivity growth, and the evidence is compelling. The results all confirm the existence of a surge and a slowdown in productivity but with some variation in timing, size, and statistical significance of the shifts. ... Over the most recent 10 to 20 years of our data, the annual average rate of MFP [multifactor productivity] growth was half the rate that had been sustained for much of the twentieth century. More subtly, and of equal importance, the past century (and more) of statistics assembled here suggest the relatively rapid rates of productivity growth experienced during the 1960s, 1970s, and 1980s could be construed as aberrations (along with the relative rapid rates of growth experienced during a period spanning WWII), with the post-1990 rates of productivity growth now below the longer-run trend rate of growth.”

The second paper by Alejandro Plastina and Sergio Lence provides a deeper understanding behind the causes of productivity growth.  They present a straightforward way to decompose multifactor productivity into six different factors: technical change, technical efficiency, allocative efficiency, returns to scale, output price markup, and the input price effect.    They write:

“Technical change is the major driver of TFP growth over the long run, and there is evidence that technical progress in the 1990s and 2000s was much slower than in the 1970s. This is a relevant result for policy makers, and begs the question of what is actually causing the slowdown in technical change. This is the first study to show technical regress in the agricultural sector during the farm crisis of the 1980s.

Another novel result is that annual changes in TFP bear no significant correlation with annual rates of technical change but instead are highly correlated with the markup effect, followed by the returns to scale component and allocative efficiency change. These findings suggest that evaluating the effects of research, extension, and other variables on each of the components of our measure of TFP change (rather than solely on an aggregate TFP index) can shed light on the actual channels through which those variables affect agricultural productivity growth in the United States and therefore contribute to policy design.”

Finally, there is Julian Alston's fellow's address from last year's AAEA meetings.  In addition to providing an excellent literature review, he makes several important points.  He argues that agricultural research is significantly under-funded relative to the benefits it provides in increased productivity:

“Evidence of remarkably high sustained rates of social payoffs to both private and public investments in agricultural R&D testify to a significant failure of government to fully address the underinvestment problems caused by the market failure. Moreover, if anything, in high-income countries like the United States, agricultural R&D policies seem to be trending in the wrong direction, making matters worse.”

and

“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.4 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—an order of magnitude greater than the annual $1–5 billion social cost of $20 billion in farm subsidies.”

Alston also points out that the main beneficiaries of productivity growth are consumers, and the farmers may or may not benefit.  He writes:

“It seems inescapable that the agricultural innovations that made food much more abundant and cheaper for consumers did so to some extent at the expense of farmers as a whole—more than offsetting the effects of growth in demand for output from the sector. This finding is reinforced when we pay attention to the details of the timing. Specifically, the periods of the most rapid decline (or slowest growth) in [net farm income] seem to coincide with the periods of most rapid increase in farm productivity—the 1940s to 1980s, especially 1950–1980, as identified by Andersen et al. (2018)—consistent with the hypothesis that agricultural innovations have reduced net incomes for U.S. farmers as a group.”

This suggests something of a paradox.  Farmer groups have often been some of the biggest supporters of agricultural research and are proponents of productivity growth, while consumers have been skeptical if not hostile toward many productivity-enhancing technologies on the farm.  Yet, it is likely food consumers that have received the lion's share of the benefits from increases in agricultural productivity through greater food security and lower food prices.  

Wizards and Prophets

I've been reading Charles Mann's latest book Wizards and Prophets, which was released earlier this year.  Overall, I've enjoyed the book.  The subtitle, "Two Remarkable Scientists and Their Dueling Visions to Shape Tomorrow's World" is an apt description for much of the content, which describes food, agricultural, and environmental problems through the lens of Norman Borlaug and William Vogt.  The history is informative, and Mann gives a fair comparison of the underlying philosophical differences, which he attributes to Borlaug and Vogt, driving much of the debate today around food, agriculture, and the environment. 

I am very much in the "Borlaug-wizard camp" (which advocates for innovation, science, research to solve food security and environmental problems) but I came away with a better appreciation for the Vogt-ian, prophet point of view (focused on resource constraints, ecological limits, need to reduce consumption, etc).  

While I thought the book was well done and well worth reading, Mann gets one aspect of this debate wrong.  Because I've seen other writers make the same mistaken point, it's worth delving into a bit.

Throughout the book, Mann refers to the Borlaug way of thinking as "top down" and the "hard way," and he contrasts this with Vogt's approach which he depicts as "bottom up", "localized", etc.  This is exactly backward. 

Mann aptly describes a core belief among the prophets: that there are finite resources on earth and just like any other species, we will grow exponentially until we exhaust our resources, and then our population and civilization will collapse. The analogy is a jar filled with few fruit flies given a fixed amount of food.  Initially, the flies have ample resources and they multiple rapidly.  However, at some point the population becomes too large for the fixed food supply, and the population collapses.  The fruit fly population follows something like an S-shaped curve over time.

Moving from flies to people, the issue is typically described in a Malthusian manner.  As the graph below shows, as we add more labor to a fixed amount of land, diminishing marginal returns kick in and the amount of food available per worker eventually falls.

If this resource-constrained view is a core belief, how do you solve the problem?  Adherents to this point of view typically urge folks to consume less or use less resource-intensive systems/products or to constrain population in some way.  But, most individuals don't want less.  Particularly folks in the developing world - they want to have and consume the things those us in the developed world enjoy, whether it be meat, air conditioning, ipads, or MRIs.  Yes, persuasion may result in a few people cutting back, but not on a scale that matches the magnitude of the problem.  Thus, the only fully effective way for the prophets to accomplish their goal (preventing catastrophic collapse) is to force or constrain the population to adopt outcomes few individuals would choose on their own.  Thus, the call for policies to mandate a cap on the number of children one can have (as occurred in China), restrictions of resource use, taxes, bans, etc. In other words, top-down planning is required to constrain growth and population, which is often manifested in "one size fits all" or highly non-localized policies.  Just recall of all the clamoring by Vogt-type adherents when Trump decided to pull out of the Paris accord that had global (i.e., non-local) prescriptions to fight climate change [note: I'm not advocating for or against the Paris accord, only noting that it is non-local and more-or-less top-down).  

The wizardly Borlaug view, by contrast, operates via entrepreneurial innovation and individual decisions of whether to adopt or not.  When Borlaug worked for the Rockefeller foundation, he/they had no "power" to force individual farms to adopt their new seeds and production practices, rather as Mann himself reveals, the early Mexican adopters took on the new seeds precisely because they saw for themselves via Borlaug's demonstration plots that they could achieve higher yields.  Yes, the types of seeds and production practices developed by Borlaug et al. spread far and wide, but it is was largely because they "worked" not because it was mandated from on high.  And, the adoption was much more adapted to local conditions than Mann lets on.  Producers in different locations ultimately used different varieties, different irrigation and fertilization techniques, etc.  As time has gone on, precision agriculture has led to even more localization of management decisions.  

The promise and hope of the Wizard is that innovation can get us off the curve shown in the graph above and move us to a new, higher outcome, as shown below. 

This isn't a denial of resource constraints, it is a recognition that innovation allows us to get more with the same or fewer or even different resources.  But, for those innovations to be adopted, they must pass the market test.  Real life-farmers and consumers need to choose to adopt them (or not). This is precisely the opposite of top-down.

Here's what I wrote a while back when Nassim Taleb referred to GMOs as a "top down" technology. 

“Taleb makes reference to the Hayek bottom-up vs. top-down planning. He says GMOs are the top-down sort. I’m not so sure. Real life farmers and people have to be willing to buy varieties that have the GMO traits. No one is forcing that outcome. It is true that competition will limit - to some extent - the diversity of plants and genetics that are observed because some plants aren’t tasty or aren’t high enough yielding. But most plant breeders keep all kinds of “ancient” varieties precisely for the purpose of trying to breed in new traits to today’s varieties (and folks working on synthetic biology are creating their own, new strands of DNA, creating new diversity). Geography also increases diversity. Iowa grows a lot of corn, Oklahoma doesn’t because it isn’t our comparative advantage. I see little reason to believe that a single GMO variety will perform well in all locations. So, yes individual companies are planning and creating new varieties, but it is all our local knowledge of what works in our places and conditions that determine whether particular genetics offered by a particular company are used. We do not have a seed czar or a DNA czar. ”