Trends in National School Lunch Program

Back in 2010, the U.S. Congress passed the Healthy, Hunger-Free Kids Act. The Act, championed by Michelle Obama, provided funding for free and reduced price school lunches and breakfasts, introduced a variety of new nutritional guidelines, and provided incentives for schools to offer healthier options.

The law went into effect at the beginning of the 2012-2013 academic year. There was a fair amount of initial push back. A video from these Kansas students protesting the calorie restrictions has been viewed more than a million times, and other students took to social media with photos of the new lunches using the hashtag #ThanksMichelleObama. This CNN article from 2017 provides some background and also reports on the efforts of a large school food service industry association to roll back some of the guidelines.

The new guidelines may well have generated some positive health benefits for students who ate school lunches. But, how have these policies potentially affected participation in the National School Lunch Program (NSLP)? Students are not required to eat the school-provided NSLP lunches. Students can bring food from home, go off campus, or find other substitutes at school.

I downloaded some data from the US Department of Agriculture (USDA), Food and Nutrition Service (FNS). These data show that in 2017, 4.89 billion lunches were served under the NSLP, with 73.6% being free or reduced price and the remaining 26.4% of students paying full price. How have these statistics changed over time?

As the figure below shows, there was a nearly linear increase in the number of lunches served each year in the NSLP right up until 2010, after which there was a slowdown and then a slow decline.

The effects can be seen even more dramatically by converting the data in the above figure to annual percentage changes in the number of NSLP meals served. From 1990 to 2008, the school lunch program grew every year. Since 2011, the program has gotten smaller every year except in 2016. In the six years prior to the law’s enactment in 2010, there was an average annual increase of 1.4% in the number of NSLP meals served, but in the six years since the law’s enactment (from 2012 to 2017), there was an annual average decrease of -1.2% in the number of NSLP meals served.

The data also suggest another interesting dynamic at play. Below is the percent of NSLP meals that are free or reduced priced. Throughout most of the 2000’s just under 60% of NSLP meals were free or reduced price. Since then, there has been a fairly steady increase in the share of meals that are subsidized. Given that the increase started prior to the enactment of the 2010 Healthy Hunger-Free Kids Act, it is likely that other factors (such as the Great Recession) were playing a role. However, there has continued to be an increase in the share of NSLP meals that are free or reduced price well after the recession ended.

These data show there are fewer meals being served that fall under the National School Lunch Program umbrella and that students who pay full price have increasingly chose to eat meals not governed by the program.

The figures presented above do not causality prove that the 2010 Healthy, Hungry-Free Kids Act led to the decline in the meals served under the USDA National School Lunch Program, but they are interesting trends about which I was previously unaware.

Market Impacts of GMO Labeling

Readers might recall the result from the study Jane Kolodinsky and I published in Science Advances earlier this year. We found that the provision of mandatory labels in Vermont appears to have reduced opposition to GMOs in that state. However, as I noted at the time,

“Our result does NOT suggest people will suddenly support GMOs once mandatory labels are in place. ”

Indeed, the data suggest consumers will still want to avoid products with GMO labels, which provides incentives for food retailers and manufacturers to find ways to avoid GMO ingredients.

Colin Carter and Aleks Schaefer just published an interesting new study in the American Journal of Agricultural Economics, which powerfully shows that mandatory GMO labels are already having significant market impacts. They found a creative way to explore this issue by focusing on the market for sugar. They provide the following background:

“In the United States, sugar is produced from both sugarcane and sugarbeets. Sugarcane stalks are milled to produce raw sugar. Raw cane sugar is then sent to a refining facility to be transformed into refined sugar. Sugbarbeets, in contrast, have no raw stage; they are processed from beet to refined sugar in one continuous process. The U.S. market share for beet (cane) sugar is approximately 58% (42%). Almost all U.S. sugarbeet production is GE, while cane sugar is GE-free. However, sugar derived from beets is chemically identical to sugar derived from cane.”

This summary data they provide on prices of sugar from cane and beet sources suggests “something” change around the same time as the Vermont mandatory GMO labeling law.

Source: Carter and Schaefer, American Journal of Agricultural Economics

Here are the main findings.

“Our analysis supports the explanation that the divergence in U.S. prices for refined cane and beet sugar was the result of Vermont’s mandatory GE labeling. The divergence occurred on or around July 2016— the month the Vermont Act took effect.

Counterfactual price estimates generated by a regression model suggest that GE food labeling initiatives generated a small premium for cane sugar and a price discount for beet sugar of approximately 13% relative to what prices would have been in the absence of such legislation.”

These changes in raw ingredient prices will ultimately have impacts on retail food prices. All this is suggests that mandatory labels aren’t a free lunch.

No, Farm Policy Doesn't Have Much to Do with Obesity

Yesterday, David Ludwig and Kenneth Rogoff, prominent pediatrician and economist respectively, published an article in the New York Times about obesity.  The following is a passage from the piece.  

“Farm policies have made low-nutritional commodities exceptionally cheap, providing the food industry with enormous incentive to market processed foods comprised mainly of refined grains and added sugars. In contrast, vegetables, whole fruits, legumes, nuts and high-quality proteins are much more expensive and, in “food deserts,” often unavailable. ”

The authors have already taken a bit of a beating about this on Twitter from the agriculturally-literate-intelligentsia. Why?  Because these sentences give the incorrect impression that farm policy is a major contributor to obesity.  That's not saying farm policies aren't inefficient, only that they do not have the effects many people claim they do.

Why would farmers support policies that would make commodities "exceptionally cheap" and thus lower their profits?  Yes, there are some policies that likely increase production beyond what would happen in an un-distorted market, but there are other policies that reduce production.  Take corn, for example, which is the largest agricultural crop in the U.S. in terms of value of production.  The existence of subsided crop insurance subsidies and commodity programs might increase the tendency to produce more than would otherwise be the case, but ethanol policies from the EPA re-direct much of that production to fuel rather than food. Moreover, there are countervailing policies such as the Conservation Reserve Program (CRP), which remove land from production.  In addition, sugar policies push the price of sugar up, not down.  

The authors also point to processed food as another big evil, but in so doing they (correctly) undercut the argument that farm policy is a major culprit.  How so?  Well, for every $1 we spend on food, only about $0.15 results because of the cost of the farm product.  The other 85% of the cost is from transportation, processing, packaging, marketing, retailing, etc.  As a result, changes in farm commodity prices have relatively small impacts on retail prices.  

Fruits and vegetables are indeed more expensive than many commodity crops, but that's because of biology not policy (see more on that here and here).  Here's what I wrote in one of those posts:

“why do we grow so much corn, soy, and wheat in the U.S.? A primary answer is that these plants are incredibly efficient at converting solar energy and soil nutrients into calories (they’re the best, really the best). Moreover, these calories are packaged in a form (seeds) that are highly storeable and easily transportable - allowing the calories to be relatively easily transported to different times and to different geographic locations. Contrast these crops with directly-human-edible fruits/vegetables like kale, broccoli, or tomatoes. These plants are poor converters of solar energy to plant-stored energy (i.e., they’re not very calorie dense), and they are not easily storeable or transportable without processing (mainly canning or freezing), which requires energy.”

If you don't believe me, there is a long literature by agricultural economists on this subject.  See this book by Julian Alston and Abby Okrent or these papers in American Journal of Agricultural Economics or Journal of Health Economics, the later of which was co-authored with Brad Rickard.  Other papers take entirely different approaches but arrive at the same conclusion.  See this paper in Food Policy by Corey Miller and Keith Coble or this one by Alston, Sumner an Vosti, also in Food Policy.

As for the efficacy of the other policies proposed by Ludwig and Rogoff, I'm skeptical of their efficacy in truly affecting obesity.  See this paper I recently published in Applied Economic Perspectives and Policy or my 2013 book, The Food Police.

Farmer's Share of the Retail Dollar - Enough Already

Every so often, the people seem to get excited about the farmer’s share of the retail dollar – particularly when USDA updates the figures or a news article mentions the issue.  A couple months ago, for example, the National Farmer’s Union issued a press release decrying the fact that farmers “only” receive 14.8 cents of every dollar consumers spend on food.  About the same time, the Food Tank put out this tweet.

For every dollar consumers spend on food, only 7.8 cents goes to farmers pic.twitter.com/NZrqJ6OVsw

— Food Tank (@foodtank) May 15, 2018

The widespread implication seems to be that a lower share of the retail dollar is an unambiguous sign that farmers are worse off.  But one has very little to do with the other.  Let me try to illustrate with an example.   

Suppose there are two countries where the farmer’s share of the retail dollar differs dramatically.  In Country A, the share is only 10% and in Country B, the share is 90%.  So, when a consumer spends $1 on food, the farmer in Country A receives 10 cents and the farmer in Country B receives 90 cents.  On a dollar-spent-on-food basis, it thus looks like a farmer would much prefer to live in Country B than Country A.  But, let’s dig a little deeper.

Suppose the farmers in our two countries actually produce the same value of agricultural output.  To make the math easy, let’s say farmers in Country A produce $100 billion worth of ag output and farmers in Country B do the same. 

What are consumers in the two countries spending on food?  By definition, consumers in Country A are spending $100 billion/0.1 = $1,000 billion and consumers in country B are only spending $100 billion/0.9 = $111.11 billion. By definition, for a fixed value of ag output, a smaller value for the farmer's share of the retail dollar implies a larger total food economy. As I'll show in a minute, it matters a lot if you're selling into a $1 trillion market or a $111 billion market.

Why might consumers in Country A spend so much more on food than consumers in Country B despite the same volume of ag output in both countries?  Well, it could be there is more market power with greedy agribusinesses and retailers siphoning off profits in Country A than B (that seems to be the common layman’s interpretation).  But, it could also be that consumers in Country A have the preferences or ability to pay more for better packaging, increased food safety, better working conditions in food processing, more convenience (they pay the processor or a restaurant to do more of the preparation for them), etc.

So, what happens if there is a 10% increase in consumer demand for food in both Country A and Country B?  This could happen, for examples, if the populations increase in each country or if the respective food industries run advertisements or there are post-farm innovations that increase quality. 

Now, let’s construct a very simple economic model (such as the one we use in this paper), where, in both countries, the elasticity of demand is -0.8 and the elasticity of supply is 0.2, and the farm product is supplied to the retail sector in fixed proportions. 

In this situation, a 10% increase in consumer demand in country A (with only a 10% farmer’s share of the retail dollar) will increase farmers' profits by $29 billion.  However, in country B, where farmers “get” a full 90% of the retail dollar, that same 10% increase in consumer demand only increases farmers' profits by $8.8 billion.  So, for the same percentage increase in consumer demand, farmers in country A are more than 3x better off than farmers in country B despite the fact that their share of the retail dollar is only 10% instead of 90%. 

So, here’s a fundamental lesson: a small share of a big number can be much higher than a larger share of a smaller number.

Now, none of this means that one cannot construct scenarios in which producers are worse off when the farmer’s share of the retail dollar falls.  That’s easy to do too.  But, as I’ve shown here, I can easily do the opposite. 

The point?  Changes in the farmer’s share of the retail dollar are meaningless insofar as telling us whether farmers are better or worse off. 

Don't believe me?  Listen to other agricultural economists.  Here is Gary Brester, John Marsh, and Joseph Atwood and colleagues writing in a 2009 journal article:

“We have empirically demonstrated that [the farmer’s share of the retail dollar] statistics and, by construction, farm-to-retail marketing margins, are not reliable measures of changes in producer surplus (welfare) given exogenous shocks to various economic factors … In fact, little or no accurate information is conveyed by [farmer’s share of the retail dollar] statistics … Consequently, these data should not be used for policy purposes.”

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.