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.

Dealing with Lazy Survey Takers

A tweet by @thefarmbabe earlier this week has renewed interest in my survey result from back in January 2015, where we found more than 80% of survey respondents said they wanted mandatory labels on foods containing DNA. For interested readers, see this discussion on the result, a follow-up survey where the question was asked in a different way with essentially the same result, or this peer-reviewed journal article with Brandon McFadden where we found basically the same result in yet another survey sample. No matter how we asked this question, it seems 80% of survey respondents say they want to label foods because they have DNA.

All this is probably good motivation for this recent study that Trey Malone and I just published in the journal Economic Inquiry. While there are many possible reasons for the DNA-label results (as I discussed here), one possibility is that survey takers aren’t paying very close attention to the questions being asked.

One method that’s been around a while to control for this problem is to use a “trap question” in a survey. The idea is to “trap” inattentive respondents by making it appear one question is being asked, when in fact - if you read closely - a different question is asked. Here are two of the trap questions we studied.

About 22% missed the first trap question (they did not click “high” to the last question in figure 2A) and about 25% missed the second question (the respondent clicked an emotion rather than “none of the above” in question 2B). So far, this isn’t all that new.

Trey’s idea was to prompt people who missed the trap question. Participants who incorrectly responded were given the following prompt, “You appear to have misunderstood the previous question. Please be sure to read all directions clearly before you respond.” The respondent then had the chance to revise their answers to the trap question they missed before proceeding to the rest of the survey. Among the “trapped” respondents, about 44% went back and correctly answered the first question, whereas about 67% went back and correctly answered the second question. Thus, this “nudge” led to an increase in attentiveness among a non-trivial number of respondents.

After the trap questions and potential prompts, respondents subsequently answered several discrete choice questions about which beer brands they’d prefer at different prices. Here are the key findings:

“We find that individuals who miss trap questions and do not correctly revise their responses have significantly different choice patterns as compared to individuals who correctly answer the trap question. Adjusting for these inattentive responses has a substantive impact on policy impacts. Results, based on attentive participant responses, indicate that a minimum beer price would have to be substantial to substantially reduce beer demand. ”

In our policy simulations, we find a counter-intuitive result - a minimum beer price (as implemented in some parts of the UK) might actually increase alcohol consumption as it leads to a substitution from lower to higher alcohol content beers.

In another paper in the European Review of Agricultural Economics that was published back in July, Trey and I proposed a different, yet easy-to-interpret measure of (and way to fix) inattention bias in discrete choice statistical models.

Taken together, these papers show that inattention is a significant problem in surveys, and that adjusting results for inattention can substantively alter one’s results.

We haven’t yet done a study of whether people who say they want DNA labels are more or less likely to miss trap question or exhibit other forms of inattention bias, but that seems a natural question to ask. Still, inattention can’t be the full explanation for absurd label preferences. We’ve never found inattention bias as high as the level of support for mandatory labels on foods indicating the presence/absence of DNA.

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.

Want non-GMO? How much more will it cost?

The journal Food Policy just released a new paper I co-authored with Nicholas Kalaitzandonakes and Alexandre Magnier entitled, "The price of non-genetically modified (non-GM) food." 

As retailers consider reformulating products or how they'll respond to new mandatory labeling laws, it is important to consider how these decisions may affect the prices consumers pay for foods that avoid GMOs.  The matter is increasingly of note because sales of non-GMO products have significantly risen over time (below is a graph from the paper showing the trend in sales of breakfast cereal making non-GMO claims).

In the paper, we used a U.S. national sample of grocery store scanner data from the years 2009- 2016 to investigate the prices stores charged for 144 different salad and cooking oil products (or Universal Product Codes, UPCs), 1,288 tortilla chip UPCs, 2,227 breakfast cereal UPCs, and 5,626 ice cream UPCs. We picked these product categories because they represent classes of products for which the potential impact of changes in the raw ingredients on the final retail price might be large (i.e., soybean or corn oil for which the supply is primarily GMO) to small (i.e., ice cream where the value share of GMO crops and their derivatives (e.g. corn syrup) is probably less than 5%).

Here's a short summary:

“we use hedonic modeling to estimate the retail price premiums consumers paid during the 2009–2016 period for non-GM and organic foods in four product categories: breakfast cereal, tortilla chips, salad and cooking oil, and ice cream. There are almost 11,000 ready-to-eat foods in our sample, 1350 of which are labeled as non-GM or organic. We selected these four product categories for their differences in the value shares of GM ingredients and hence their potential differences in reformulation costs. We show that the estimated price premiums for non-GM and organic foods in these four product categories are in line with the expected added costs for supplying such products. ”

The key results are summarized in the table below:

We write:

“The estimated price premiums paid by US consumers over the 2009–2016 period, 9.8% to 61.8% for non-GM products and 13.8% to 91% for organic products in the four categories examined here, are orders of magnitude higher than those projected by economic impact analyses of proposed mandatory GM labeling produced in recent years ”

and

“Perhaps the most important conclusion to be drawn from our results is that non-GM foods are more costly than GM foods, and policies that encourage food companies to shift toward non-GM ingredients are likely to increase food costs. Our results therefore suggest that there is a pressing need for further research in order to clarify the added costs consumers may have to pay under mandatory disclosure of GM ingredients and how such added costs might be distributed.”