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.

The New GMO Labeling Law

Last week, the USDA finally released its proposed rule outlining the ways in which it may implement the National Bioengineered Food Disclosure Standard (NBFDS) (i.e., the a mandatory labeling law for GMOs) that was passed by the US Congress and signed into law back in the summer of 2016.  At the point, this is still a proposed rule: public comments are still being accepted until July 3, 2018.  

As I wrote at the time of its passage, the mandatory labeling bill was not particularly popular with the "anti" or "pro" GMO crowds.  I won't rehash all the issues involved or re-cover all the arguments for and against mandatory labeling (as an aside, I am amazed at how often I still see people citing my result on consumer preferences for DNA labels; I suppose that's a least one mark of success when people unknowingly cite your own research results to you as something you need to know!).  Here, I want to point out a few things that were news (at least to me) in the proposed rule.

• One of the controversial facets of the original bill was that it allowed for disclosure of genetically engineered ingredients via a QR code (this is an issue we have researched - e.g., see here).  In addition to the QR code or a text disclosure, it appears companies might be able to also use one of several different types of labels (I am not aware of any publicly available research on consumer perception of these labels).  Here are some of the examples proposed:

• It also appears that a food may only have to be labeled if it actually contains genetically engineered (or shall i now say "bioengineered") ingredients that contain recombinant DNA.  Why does this matter?
  • Sugar and oil don't contain DNA.  Tests for recominant DNA are likely to come back negative even if applied to oil from derived from bioengineered corn or soy or if applied to sugar from bioengineered sugar beets.  As such, foods using oil or sugar derived from GE crops  may not ultimately be subject to the mandatory disclosure.
  • Other biotechnologies, such as gene editing, don't utilize recombinant DNA, and as such may not ultimately fall under this mandatory labeling law.
• What will be the tolerances or thresholds that would trigger mandatory labeling?  The proposed rule didn't say for sure but offered several options:
  • A) disclosure is required if more than 5% of any ingredient (by weight) is bioengineered; 
  • B) disclosure is required if more than 0.9% of any ingredient (by weight) is bioengineered; 
  • C) disclosure is required if more than 5% of the entire product (by weight) is bioengineered.
  • It should be noted that these different thresholds are likely to imply VERY different costs of compliance; a 0.9% threshold is likely to be more than 5x more costly than a 5% threshold, and individual ingredient thresholds will be much more costly than total product thresholds.  
• There are many exceptions, for examples for small manufacturer, for certain enzymes,  and for animal products derived from animals fed bioengineered feed.

Impacts of health information on perceived taste and affordability

The journal Food Quality and Preference just released a new paper I co-authored with Jisung Jo, a former student who now works at the Korea Maritime Institute.

Here is the motivation for the work:

“One of the key mechanisms policy makers have utilized to encourage healthier eating is the provision of information via nutritional labels. However, research has shown that the provision of health information does not necessarily increase consumption of healthy foods ... A possible reason for the largely ineffectual impact of nutritional labeling might be because health information not only updates consumers’ health perceptions but also affects other perceptions, such as taste and affordability, which are the primary drivers of consumer purchase behavior ”

In other words, if you see a new labeling indicating a food is healthier than you previously thought, do you now think it will be less tasty?  Or more expensive?  

To explore this issue, we surveyed consumers in three different countries (US, China, and Korea).  We showed consumers a picture of a food item and asked them to rate the item, on simple scales, in terms of perceived taste, health, affordability, and purchase intention.  We did this for 60 diverse food items. Then, the ratings of all 60 foods was repeated after the subjects had received information about each food item’s healthiness, which was conveyed via a "traffic light" labeling system (green=healthy, yellow=medium healthiness, red=unhealthy).   Here's an example of one of the questions asked before and after the information:

Unsurprisingly, the provision of "green" labels tended to increased perceived healthiness and the provision of "red" labels tended to reduce perceived healthiness.  Of more interest is how these labels affected perceptions of taste, affordability, and ultimately purchase intentions.  

Unexpectedly, we found that providing information that a food was healthier than people previously thought tended to increase perceived taste.  People also tended to think items that are less healthy than previously thought will ultimately be less expensive.

We created the following graph to look at how projected changes in purchase intentions (after provision of health information) would change if one ignores the fact that health information also affects perceived taste and affordability.

“Across all scenarios and in all three countries, we find that negative health information has the biggest effects on purchase intention changes. Intriguingly, the average purchase intention in scenario B is larger than that in scenario A. The values for scenario D are the same as the actual average of purchase intention (since they are just the model evaluated at the mean effect changes of all variables included in the model). Comparing the purchase intention changes as one moves from scenario A to D shows the effect of ignoring integrated health-taste-affordability perceptions.”

Overall, this research underscores the need to understand how labels which convey health information might also alter other perceptions related to taste and affordability.

A primer on USDA food assistance programs

With the help of my colleagues and the leadership of Maria Marshall and Kami Goodwin, the Department of Agricultural Economics at Purdue has a new effort to educate and provide analysis around food and farm policy issues.  We are calling it: Policy Briefs by the Purdue Agricultural Economics Department. Here's a short summary from the new website:

“We are pleased to launch Policy Briefs by the Purdue Agricultural Economics Department. We aim to provide short insights, readable for the general public, on policy issues that are national in scope with an Indiana flare. We were initially motivated by the need to provide timely analysis in the lead up to 2018 Farm Bill discussions. However, the breadth of expertise in our department and the ongoing policy discussions related to farm, food, environment, trade, and development issues warrants a longer view and broader scope. The plan is to add new briefs on a monthly basis, although we may add more frequent contributions when more timely information is needed. We hope to enrich policy debates by providing data and context, quantifying impacts, and offering alternatives. ”

If you click on the link to the site, you'll see a couple short pieces by Roman Keeney explaining the Farm Bill and providing some background context for upcoming Farm Bill debates.  We also recently added a post by yours truly providing a short primer on USDA food assistance programs.  I provide an overview of programs like SNAP (aka "food stamps"), WIC, and school lunch, provide some history, look at the effects of SNAP, and outline some of the proposals to change SNAP.  All that in only about 1,000 words!

Here are the first two paragraphs from the piece:

“Looking just at spending, the U.S. Department of Agriculture (USDA) and the Farm Bill might be more aptly described as the U.S. Department of Food Assistance and the Food Assistance bill. In 2017, the USDA is estimated to spend about 77% of its $133 billion in outlays on food assistance programs.

USDA food assistance programs are administered by the Food and Nutrition Service (FNS), and the largest program administered by FNS is the Supplemental Nutrition Assistance Program (SNAP), historically known as “food stamps.” About 70% of the FNS budget authority is allocated to SNAP. The next largest programs, representing about 21% and 6% of FNS budget authority, are Child Nutrition Programs (CNP) and the Women, Infants, and Children (WIC) programs. The CNP primarily delivers free and reduced-price breakfasts and lunches to school children. In December 2017, about 22 million school children participated in the free or reduced lunch program and about 12.6 million participated in the free or reduced breakfast program. The WIC program primarily targets women who are pregnant or who have infant children by providing coupons for infant formula, milk, cheese, and other staple foods. There were about 6.9 million WIC participants in December 2017. SNAP and CNP are entitlement programs (i.e., every person who meets eligibility criteria is allowed to participate), but WIC is a discretionary program whereby the federal government grants a specific dollar amount to be spent each year.”

Oh SNAP!

Multiple sources today reported an item in the president's budget that would replace a portion of the Supplemental Food and Nutrition Assistance Program (SNAP, aka "food stamps") with physical food deliveries.  Here is Politico: 

“The proposal, buried in the White House’s fiscal 2019 budget, would replace about half of the money most families receive via the Supplemental Nutrition Assistance Program, also known as food stamps, with what the Department of Agriculture is calling “America’s Harvest Box.” That package would be made up of “100 percent U.S. grown and produced food” and would include items like shelf-stable milk, peanut butter, canned fruits and meats, and cereal.”

The proposal is being pitched as a government version of Blue Apron that will save taxpayers hundreds of millions of dollars.  SNAP and consumer advocacy groups have expressed concern with the proposal; I haven't seen any overt advocates of the plan outside the administration.  

Economists have long favored unconditional (e.g., cash) to in-kind (e.g., food) transfers.  The basic idea is that an individual consumer has a better idea of what they'll like than an administrator deciding which foods to put in a box.  In other words, for the same budget, a consumer will be happier with cash than an equivalent dollar amount of food because the former provides more flexibility and freedom than the later.  This value of flexibility could, of course, be offset if the administrator could acquire foods at a substantially reduced price compared to the average food consumer.  But, this presumes the government administrators are more skilled in food acquisition than the Amazons, Walmarts, and Krogers of the world (or that these companies are taking in excess profits that could be passed directly to consumers).

There is another aspect to this issue that doesn't seem to be getting much attention.  In particular, at least for some people, it doesn't matter if you give them food or SNAP.  Here is Southworth writing in 1945 when earlier versions of SNAP were being debated:  

“‘If a family would buy two pounds of beans anyway, giving it up to two pounds of beans as a consumption subsidy merely relieves it of the necessity of that much expenditure on its own behalf. In effect, its income is increased by the value of two pounds of beans, and it may spend some or none of this increased income on additional beans”

In short, if a household already plans to buy beans, it doesn’t matter whether the household is given beans or an equivalent amount of cash – the final outcome is the same.

But, what if the household wanted rice and not beans?  Providing them beans means they are a little less happier than they would have been with an amount of cash (or SNAP benefits) equal to the beans that they then could use to buy rice.  

Maybe the idea is that this version of the SNAP program would be more beneficial to U.S. farmers. But, these aid programs are hardly efficient forms of farm support.  As I found in one analysis, for every $1 spent by taxpayers on SNAP, farmers benefit by only $0.01.  If the idea is to support farmers, we'd be better off just sending them the dollar.  

In the end, the purported benefits seem to hinge critically on the government's ability to deliver food at a price low enough that offsets the value of the loss of flexibility for the aid recipient.