How Votes on GMO Labeling Change Concern for GMOs

At the annual meetings of the Agricultural and Applied Economics Association last week in Chicago, I saw an interesting presentation by Jane Kolodinsky from the University of Vermont.  She utilized some survey data collected in Vermont before and after mandatory labels on GMOs appeared on products in that state to determine whether consumers seeing GMO labels on the shelf led to greater or lower support for GMOs as measured by her surveys.  

I'm not sure if she's ready to make those results public yet, so I won't discuss her findings here (I will note I'm now working with her now to combine some of my survey data with hers to see whether the findings hold up in a larger sample).

Nonetheless, her presentation led me think about some of the survey data I collected over the years as a part of the Food Demand Survey (FooDS) project.  While I don't have enough data from consumers in Vermont to ask the same question Jane did, I do have quite a bit of data from the larger states of Oregon and Colorado, which held public votes on mandatory labeling for GMOs back in December 2014.  

In particular, I can ask the question: did the publicity surrounding the vote initiative on mandatory GMO labeling cause people to become more or less concerned about GMOs in general?

We have some strong anecdotal evidence to suggest that support for GMO labeling fell pretty dramatically in the months leading up to the vote.  For example, here are the results from several polls in California (including one data point my research with Brandon McFadden generated) on support/opposition to mandatory GMO labeling.  The figure below shows support for the policy was high but fell precipitously as the election campaigning began, and as we all know by now, the policy ultimately failed to garner majority support in California.

There is a similar pattern of support for mandatory GMO labeling in other states where the voter initiatives were held.  However, just because public support for a mandatory labeling policy fell as a result of campaign ads, this doesn't necessarily mean people thought GMOs were safer or more acceptable per se.  Indeed, many of the negative campaign ads focused on possible "paydays for lawyers" or inconsistencies in the ways the laws would be implemented, rather than focusing on the underlying technology itself.  

The Food Demand Survey has been conducted nationwide and monthly since May of 2013.  In November of 2014, two states - Colorado and Oregon - held widely publicized votes on mandatory GMO labeling.  These data can be used to calculate a difference-in-difference estimate of the effect of mandatory GMO labeling vote on awareness of GMOs in the news and concern about GMOs as a food safety risk.

The survey asks all respondents, every month, two questions of relevance here.  First, “Overall, how much have you heard or read about each of the following topics in the past two weeks” with response categories: 1=nothing; 2=a little; 3=a moderate amount; 4=quite a bit; 5=a great deal.  Second, we also ask, “How concerned are you that the following pose a health hazard in the food that you eat in the next two weeks” with response categories: 1=very unconcerned; 2= somewhat unconcerned; 3=neither concerned nor unconcerned; 4=somewhat concerned; 5=very concerned.  One of the 16 issues we ask about is "genetically modified food."

These data allow us to calculate a so-called difference-in-difference estimate.  That is - were people in CA and OR more concerned about GMOs than people in the rest of the country (this is the first difference) and how did this gap change during and after all the publicity surrounding the vote (this is the second and third difference)?  The "treated" group are the people in CA and OR while the "control" group consists of people in all other US states.

To analyze these question, I split the data into three time periods - "before" the vote (the months prior to September 2014), during the vote (Sep, Oct, Nov, Dec of 2014 and Jan of 2015) and after the vote (all the months after January 2015).  There were 485 "treated" people in CO and OR before the vote, 172 in these locations during, and 908 in these locations after (out of a total sample size of almost 49,000). 

In terms of awareness, here's what I found. 

Compared to people other parts of the U.S., people in CO and OR indeed reported hearing more about GMOs in the news during the ballot initiative vote than they did before and after (the increase in news awareness during the months surround the vote was statistically significant at the 0.01 level).

But, here's the key question.  Did the vote increase or decrease concern about GMOs as a food safety risk?  Apparently there was no effect.  The graph below shows, as compared to people in other states where there were no votes, there was actually a small increase in concern for GMOs in CO and OR in the months during the vote (however, the increase was not statistically significant, p=0.36), which then fell back down to pre-vote levels after the vote.  

So, despite evidence that the vote initiative on mandatory labeling led to an increase in awareness of GMOs in the news, it did not substantively affect concern about GMOs one way or the other.

ABC, BPI, and LFTB

A couple weeks ago, the lawsuit between BPI, the maker of lean finely textured beef (LFTB), aka "pink slime", and ABC news finally came to an end after the two parties agreed to an settlement for an undisclosed amount of money (here's one summary from CNN).

Here's another story from Inside Sources that touches on the economic impacts of the original ABC news coverage.  They reached out to me for comment and you can read a tad bit of what I had to say at the link above.  

Better yet, check out the chapter in my book 2016 Unnaturally Delicious entitled "Waste Not Want Not."  In that chapter, I talked about the history of BPI and it's founder Eldon Roth, the technology used in creating LFTB, some intriguing background on how BPI wound up in the documentary Food, Inc., and more.  Here are the law few paragraphs from that chapter.    

“It’s a bit hard to know what to make of all that transpired. To be sure, much of what was said about BPI was sensationalized. BPI didn’t use organ meats or bones or hoofs or hides or
“dog food.” The company used slightly fattier versions of same beef cuts that usually become roasts or ground beef. In fact, the day I visited BPI’s South Dakota plant, which is adjacent to a
Tyson packing facility, I was amazed at the beef entering BPI’s facility. The meat traveled on a conveyer belt in a tunnel that connects BPI and Tyson. A steer or heifer enters one end of the
Tyson facility, and a few hours later beef trimmings emerge at BPI without ever seeing the light of day. The trimmings consist of some small cuts of beef but there are also huge hunks of meat that looked almost identical to the briskets that I love to barbeque for get-togethers with friends and family. Lean finely textured beef is beef. That’s all. I suppose that’s why the company created a website called beefisbeef.com. No bone goes into the process. Big beef hunks go in one end and out the other end come three products: tallow, cartilage (which is the only waste), and lean finely textured beef.

I’ve visited a lot of food plants, and BPI’s was one of the most technologically advanced, safety-conscious plants I’ve seen. That a company that proactively invested millions in food safety measures found itself embroiled in controversy involving perceived (but unfounded) safety concerns is deeply ironic. What tarnished BPI’s reputation was no actual sickness or recall or outbreak; it was a series of TV shows and news stories.

But, given the information that consumers received, it is hard to fault them for their reaction. After all, best-selling authors and journalists have primed the public’s distrust of Big Food. In
an era when processed food has come to be seen as almost evil, “pink slime” struck a chord with consumers. Perhaps BPI should have required labeling of the beef that contained its products. Surely some of the public outcry arose from a feeling of having been deceived and of having no control over what is in our food. But from BPI’s perspective, what’s to label? “This product of ground-up beef parts contains more ground-up beef parts”? More fundamentally, BPI didn’t sell directly to consumers. Rather, the company sold to other processors, who sold to restaurants and grocery store chains. BPI was hardly in a position to force others to label products that contained lean finely textured beef.

So where does that leave us? Many shoppers, although I am not among them, no doubt want to avoid lean finely textured beef and are willing to pay a premium to purchase lean ground beef that does not contain it. There’s no harm in that.

But if we are really concerned about food waste, we probably need to change some of our narratives. We shouldn’t say we want companies to recycle and reuse and then turn around and vilify them for doing so.

The comedian Jon Stewart, who was more than willing to jump on the Big-Food-is-bad bandwagon, remarked that pink slime should instead be called “ammonia-soaked centrifuge-separated by-product paste.” He was working off a popular narrative. He could have instead featured the harm to a family owned business that was innovating to make food safer and more affordable by preventing food waste. But that’s not very funny.”

When Consumers Don't Want to Know

Since I first started working on the topic of animal welfare, I've had the sense that some (perhaps many?) consumers don't want to know how farm animals are raised.  While that observation probably rings intuitively true for many readers, for an economist it sounds strange.  Whether we're talking about GMO labeling, nutritional labels, country of origin labels on meat, or labels on cage free eggs, economists typically assume more information can't make a person worse off.  Either the consumer uses the information to make a better choice or they ignore it all together.    

There is a stream of literature in economics and psychology that is beginning challenge the idea that "more information is better."  One simple explanation for the phenomenon could be that consumers, if they know for sure they will continue to consume the same amount of a good, could be better off ignoring information because the information could only lower their satisfaction (perhaps because they'll feel guilty) for doing something they've already committed to doing.  In this paper by Linda Thunstrom and co-authors, 58% of consumers making a meal choice chose to ignore free information on caloric content, a finding that Thunstrom calls "strategic self ignorance" arising from guilt avoidance. 

Another possible explanation that I've previously published on is that, when people have limited attention, more information on topic A might distract people from a topic B, even though topic B ultimately has a larger impact on the consumers well-being.  

It may also be the case that people want to believe certain things.  They derive satisfaction from holding onto certain beliefs and will avoid information that challenges them.  These ideas and more are discussed by Russell Golman, David Hagmann and George Loewenstein in a nice review paper on what they call "information avoidance" for the Journal of Economic Literature.

A graduate student in our department, Eryn Bell, has been working with Bailey Norwood to apply some of these concepts to the topic of animal welfare.  They conducted a survey of 1,000 Oklahomans and asked them one of the two simple questions shown below.  Depending on how the question was asked, from 24% to 44% of respondents self declared that they would rather NOT know how hogs are raised.  The primary reasons given for this response were that farmers were trusted (a belief consumers may prefer to hold), that there are more important issues to worry about (limited attention), and guilt aversion. 

In the same survey, Bell and Norwood also included a set of questions based on some ideas I suggested.  The question gave respondents the option to see a picture of how sows are raised or to simply see a blank screen for a certain period of time.  People were divided into three groups that varied how long they had to see the blank screen.  The idea was that we could use the waiting time as a "cost", which would allow us to ask: how long are people willing to wait to NOT receive free information?  As it turns out, people weren't very sensitive to the waiting time.  Nonetheless, regardless of the waiting time, about a third of respondents preferred to see an uninformative blank screen as opposed to a more informative screenshot of sow housing.  These findings suggest at least some people, at least some of the time, would prefer not to know.  

Country of Origin Labeling and Cattle Imports

My post from back in November about the (lack of a) relationship between the repeal of mandatory country of origin labeling (MCOOL) and cattle prices seems to have been receiving a lot of attention lately.  A main driver seems to be that Tomi Lahren, a conservative journalist with a large social media following, again promoted the idea that MCOOL was a cause of declining cattle prices in a video interview with R-CALF's CEO.  For a summary of the controversy see this article by Carrie Stadheim in the Tri-State Livestock News. 

I won't re-adjudicate my original arguments as you can read them for yourself.  However, I do want to bring some data to bear on an additional claim that has been made in relation to MCOOL and cattle prices.  The article in the Tri-State Livestock News contains a quote that seems to be attributed to me, but I said nothing of the sort.  I presume, instead, the "he" in quote below is the R-CALF CEO.  Here's the quote:

““Without COOL…meatpackers can reach out and source live cattle and beef from 20 countries, bring it into the US, sell it to unsusepecting consumers with a US inspection sticker on it, even though it comes from a foreign source and consumers don’t know the difference,” he said.”

So, let's take a look at the implication of this argument.  We repeal MCOOL, and now meatpackers turn to the 20 countries and import more meat.  And, presumably, this caused the decline in cattle prices?

Well, here is USDA data on meat and veal imports to the US and on live cattle imports to the US.  The solid black line is the date of the repeal of MCOOL.

There was an uptick in live cattle imports right after repeal of MCOOL but then an even more dramatic decline.  Overall the above figure suggests no discernible impact of MCOOL on US imports of beef or cattle.  If I look at the total imports the first 11 months of 2015 prior to repeal of MOOL and compare it to the first 11 months of 2016 after the repeal of MCOOL (I use the first 11 months because the December 2016 data is not yet out), I find that, if anything, US imports of beef and cattle are, in fact, down after the repeal of MCOOL by 369 million pounds and by 297,290 head, respectively.   

Here's the thing.  Yes, it is true that: "meatpackers can reach out and source live cattle and beef from 20 countries, bring it into the US".  But, all those countries selling meat to the US can sell it instead to dozens and dozens of other countries instead.  And, why would these countries try to sell more meat to the US when prices are down in this country?  They wouldn't and the didn't.  

In any event, the point of all this isn't to argue for or against MCOOL.  Rather, I'm simply trying to make sure the claims being made about MCOOL mesh with the best evidence we have, and that evidence suggests that repealing MCOOL seems to have had very little effect on cattle prices.  Attention would be better focused on other issues to help ranchers and cattle producers who are currently experiencing financial hardship.  

The Benefits of Mandatory GMO Labeling

I ran across this post over at RegBlog which notes that the USDA will have to do a cost-benefit analysis of the new mandatory labeling law for GMOs.  The post relies heavily on this paper by Cass Sunstein written back in August.  Sunstein's article discusses the fact that regulatory agencies typically do a very bad job at quantifying the benefits of mandatory labeling policies (and identifying when or why those benefits only apply to mandatory rather than voluntary labels).

Sunstein argues that, in theory, consumer willingness-to-pay (WTP) is the best way to measure benefits of a labeling policy.  I wholeheartedly agree (and have even written papers using WTP to estimate the benefits of GMO labels) but I want to offer a couple important caveats.  

The issue in ascertaining the value of a label isn't whether consumers are willing a premium for non-GM over GM food.  Rather, as emphasized in this seminal paper by Foster and Just, what is key is whether the added information would have changed what people bought.  If you learn a food you're eating contains GMOs (via a mandatory label) but you're still unwilling to pay the premium for the non-GMO, then the the label has produced no measurable economic value.  Thus, a difference in WTP for GMO and non-GMO foods is a necessary but not sufficient condition for a labeling policy to have economic value.  

The Foster and Just paper outlines the theory behind the value of information.  Here's the thought experiment.  Imagine you regularly consume X units of a product.  Some new information comes along that lowers your value for the product (you find out it isn't as safe, not as high quality, or whatever).  Thus, at the same price, you'd now prefer to instead consume only Y units of the product.  The value of the information is the amount of money I'd have to give you to keep consuming X (the amount you consumed in ignorance) in spite of the fact you'd now like to consume only Y.  Given an estimate of demand (or WTP) before and after information, economists can back out this inferred value of information.      

But, here is a really important point: this conception of the value of information only logically applies in the case of so-called "experience" goods - goods for which you know afterward whether it was "high" or "low" quality.  Just and Foster's empirical example related to a food safety scare in milk.  In their study, people continued to drink milk because they didn't know that it had been tainted.  By comparing consumer demand (or consumer WTPs) for milk before and after the contamination was finally disclosed, the authors could estimate a value of the information.  In this case, the information had real value because the people would really have short and long term health consequences if they kept consuming X when they would have wanted to consume Y.

It is less clear to me that this same conceptual thinking about the value of information and labels applies to the case of so-called "credence" goods.  These are goods for which the consumer never knows the quality even after consumption.  Currently marketed GMOs are credence goods from the consumers' perspective.  Unless you're told by a credible source, you'll never know whether you ate a GMO or not.  So, even if a consumer learned a food was GMO when they thought it was non-GMO, and wanted to consume Y instead of X units, it is unclear to me that the consumer experienced a compensable loss.  

Expressing a view with which I'm sympathetic, Sunstein also notes that mandatory labels on GMOs don't make much sense because the scientific consensus is that they don't pose heightened health or environmental risks.  Coupling this perspective with the credence-good discussion above reminds me a bit of this philosophical puzzle published by Paul Portney back in 1992 in an article entitled "Trouble in Happyville".  

“You have a problem. You are Director of Environmental Protection in Happyville, a community of 1000 adults. The drinking water supply in Happyville is contaminated by a naturally occurring substance that each and every resident believes may be responsible for the above-average cancer rate observed there. So concerned are they that they insist you put in place a very expensive treatment system to remove the contaminant. Moreover, you know for a fact that each and every resident is truly willing to pay $1000 each year for the removal of the contaminant.

The problem is this. You have asked the top ten risk assessors in the world to test the contaminant for carcinogenicity. To a person, these risk assessors - including several who work for the activist group, Campaign Against Environmental Cancer - find that the substance tests negative for carcinogenicity, even at much higher doses than those received by the residents of Happyville. These ten risk assessors tell you that while one could never prove that the substance is harmless, they would each stake their professional reputations on its being so. You have repeatedly and skillfully communicated this to the Happyville citizenry, but because of a deep-seated skepticism of all government officials, they remain completely unconvinced and truly frightened - still willing, that is, to fork over $1000 per person per year for water purification.”

What should the Director do?  My gut response to this dilemma is the same as what my Ph.D. adviser Sean Fox wrote in a chapter for a book I edited a few years ago:

“It’s a difficult question of course, and the answer is well beyond both the scope of this chapter and the philosophical training of the author.”