What's going on inside people's heads when they see controversial food technologies?

That was the question I attempted to answer with several colleagues (John Cresip, Brad Cherry, Brandon McFadden, Laura Martin, and Amanda Bruce) in research that was just published in the journal Food Quality and Preference.

We put people in an fMRI machine and recorded their neural activations when they saw pictures of (or made choices between) milk jugs that had different prices and were labeled as being produced with (or without) added growth hormones or cloning.  

What did we find?

“Our findings are consistent with the evidence that the dlPFC is involved in resolving tradeoffs among competing options in the process of making a choice. Because choices in the combined-tradeoff condition requires more working memory (as multiple attributes are compared) and because this condition explicitly required subjects to weigh the costs and benefits of the two alternatives, it is perhaps not surprising that greater activation was observed in the dlPFC than in the single-attribute choices in the price and technology conditions. Not only did we find differential dlPFC activations in different choice conditions, we also found that activation in this brain region predicted choice. Individuals who experienced greater activation in the right dlPFC in the technology condition, and who were thus perhaps weighing the benefits/costs of the technology, were less likely to choose the higher-priced non-hormone/non-cloned option in the combined-tradeoff condition.”

and

“Greater activation in the amygdala and insula when respondents were making choices in the price condition compared to choices in the combined-tradeoff condition might have resulted from adverse affective reactions to high prices and new technologies, although our present research cannot conclusively determine whether this is a causal relationship. In the price condition, the only difference between choice options was the price, and the prices ranged from $3.00 to $6.50, an increase of more than 100% from the lowest to the highest. Such a large price difference could be interpreted as a violation of a social norm or involve a fearful/painful/ threatening response, which, as just indicated, has been associated with activity in the amygdala and insula. Kahneman (2011, p. 296) argues that these particular brain responses to high prices are consistent with the behavioral-economic concept of loss aversion, in this case, a feeling that the seller is overcharging the buyer.”

The punchline:

“Estimates indicate that the best fitting model is one that included all types of data considered: demographics, psychometric scales, product attributes, and neural activations observed via fMRI. Overall, neuroimaging data adds significant predictive and explanatory power beyond the measures typically used in consumer research.”

Some recent writings

A few pieces I've put out in the last week or two:

1) In Defense of Frankenfoods.  Milken Institute Review.  An excerpt:

“While it is possible to be pro-biotechnology without being pro-Monsanto, such a nuanced position is difficult to maintain in the current atmosphere. It seems that many suffer from what might be called Monsanto Derangement Syndrome, buying into all sorts of conspiracy theories. Yet genetically engineered foods are no more synonymous with Monsanto than hamburgers are with McDonald’s. When anti-Monsanto became de facto anti-biotechnology, many left-leaning commentators chose to swim with the tide. Thus emerged a (justifiable) belief that many on the left were anti-science on the issue of biotechnology. In the words of journalist Keith Kloor (writing for Slate), opponents of genetically engineered food “are the climate skeptics of the left.” Although there is some truth to this observation, the political reality is more complex.”

2) Consumer Acceptance of Controversial New Food Technologies: Causes and Roots of Controversies with Jutta Roosen and Andrea Bieberstein in Annual Review of Resource Economics. An excerpt: 

“The dread/control framework may partly explain aversion to new food technologies, particularly in our modern society. In most developed countries, only a very small fraction of the population makes a living by farming. That many consumers today have little connection to and knowledge of modern production agriculture means that new practices adopted by farmers are likely to seem foreign, unknown, and—from the consumer’s perspective—uncontrollable (Campbell & Fitzgerald 2001, Gupta et al. 2011). It has been argued that many consumers have a “romantic” notion of farming (Thompson 1993) and that agricultural literacy is “too low” in the population (Pope 1990). Empirical research suggests that agricultural literacy is loweramong urban children than among rural children (Frick et al. 1995). Thus, when consumers become aware of a new technology—e.g., lean, fine-textured beef or Roundup Ready soybeans—it may be interpreted as a signal of dread and of unknown risk, which Slovic (1987) argues is most aversive and prone to
elicit public panic.”

3) New Tool (FooDS) Identifies Consumers' Views on Food Safety with Susan Murray in Choices.  An excerpt:

“Figure 4 plots the FooDS price expectations index for beef, pork, and chicken against the same-month price data from the BLS on ground chuck, all pork chops, and boneless chicken breasts. For the first two meats, the correlations—a statistical measure of association, with 1.00 being a perfect correlation—between price expectations and actual prices are 0.72 and 0.83, showing a high correspondence between consumer expectations and actual prices. The correlation for chicken, however, was only -0.26. This latter result likely arises because actual prices for beef and chicken have trended up over this time period while chicken prices have not. However, consumers do not differentiate much between meat categories in their price expectations; the correlations among price expectations for beef, pork, and chicken are all above 0.89.”

Might consumers interpret GMO labels as a warning label?

Opponents of mandatory labeling of GMO foods often argue that requiring mandatory labels could mislead consumers - making them think there is a safety risk when the best science suggests the opposite.  This is no minor issue, as citizens in Oregon and Colorado will vote on mandatory labeling initiatives this November (previous voter initiatives in California and Washington narrowly failed; legislation in Vermont has already passed).  

Here, for example, is an unlikely critic of mandatory GMO labeling, Cass Sunstein (Obama's former "regulatory czar") writing for Bloomberg.com:

“... GM labels may well mislead and alarm consumers, especially (though not only) if the government requires them. Any such requirement would inevitably lead many consumers to suspect that public officials, including scientists, believe that something is wrong with GM foods — and perhaps that they pose a health risk.”

I have made related arguments in the past, and have even published some prior academic work giving some empirical evidence backing the concern.  However, the evidence is far from conclusive.

Marco Constanigro at Colorado State University and I decided to investigate the issue more directly in a couple studies we conducted last year, which are now published in the journal Food Policy.  

Our research strategy sought to determine whether consumers who were exposed to foods that had GMO labels subsequently indicated higher levels of concern than people who hadn't been shown such labels.  

In the first study, we used apples as the context.  Respondents were randomly assigned to one of three groups.  One group (the control) made choices between apples that did not mention GMOs at all - that had a decoy attribute: ripening with ethylene.   Another group made choices with mandatory ("contains") GMO labels, and another group with voluntary ("does not contain") labels.  The following shows examples of choices we presented to people in the control and treatment groups.

After making several choices between apples like this with different labels, then we asked each set of consumers a bunch of questions about how safe they thought it was to eat GMOs, how concerned the were about GMOs relative to other issues, etc.

Here's the first key result: There was no consistent statistically significant difference in the average level of concern for GMOS expressed by people shown different labels.  That is, the mere presence of the GMO label did not lead to a greater level of concern about GMOs.

However, we can also study the actual apple choices that people made, and use those choices to infer aversion to GMOs.  And here, another set of interesting results emerges:  Consumers' willingness-to-pay to avoid GMOs is more than twice as high in the presence of mandatory "contains" GMO labels as compared to voluntary "does not contain" GMO labels.  Also, willingness-to-pay to avoid ethylene ripening (a common, and heretofore uncontroversial, industry practice) is as high as that to avoid GMOs.

In the second study, respondents were divided into one of two groups.  The first control group was shown an unaltered box of cheerios and was simply asked to click on the areas of the box they found most and then least appealing.  A second treatment group did the same but for a box of cheerios that had, in small print on the bottom left-hand-side of the package the label "partially produced with genetic engineering."   After looking at these packages, we then asked each set of respondents a series of questions about how safe they thought it was to eat GMOs, how concerned the were about GMOs relative to other issues, etc.  The idea is that if GMO labels signal safety then those people who say the mandatory label should subsequently indicate a higher level of concern than those who did not see such a label.

Here are "heat maps" associated with the initial the results where we simply asked people to click on the areas they found most/least desirable.  The top pictures show the clicks for most desirable and the bottom pictures the clicks for the least desirable (clearly people in the GMO treatment noticed the GMO label and found it unappealing):

Here's the key result: There was no statistically significant difference in the level of concern for GMOS expressed among people shown the box with the GMO label vs. the group shown the box without the GMO label.  

Thus, neither study supported our hypothesis that the mere presence of GMO labels would lead people to believe GMOs are more or less safe.  

Here's how we concluded the paper:

“We interpret the evidence as suggesting (at least in the context of our studies) that any signaling effects, should they exist, are likely small and below the ability to consistently detect given our sample sizes of approximately 200 participants per treatment. Nevertheless, we do not believe the results completely rule out the possibility of a signaling effect.

A true labeling mandate imposed by law may well send a different signal about the nature of scientific and public concern than labels shown by researchers on a survey. It is likely impossible for a researcher to impersonate governmental authorities (and the media and culture surrounding a “real world” label implementation) required to fully reproduce the potential signaling effect of a labeling requirement. Our approach – exposing consumers to GM labels via a choice experiment or modified packaging – only simulates exposure to GM labels in a market-like setting, and it must be acknowledged that “real world” effects are possibly more pronounced.

There are at least two other reasons to believe that some forms of signaling are alive and well. First, study 1 reveals that mandatory “contains” labels generated significantly higher implied willingness-to-pay to avoid GE food than voluntary “does not contain” labels. The differences in responses to mandatory vs. voluntary labels may result from the asymmetric negativity effect, which may in turn result from differences in what these two labels signal about the relative desirability of the unlabeled product. The differences in the “contains” vs. “does not contain” may also send different signals and change beliefs about the likelihood that the unlabeled product is GE or non-GE. Second, in study 1 we found aversion to our “decoy” attribute – ethylene ripening – in the control that is on par with aversion to GE food. During fruit storage, atmospheric ethylene is often controlled to slow or accelerate the ripening process (see Sinha et al., 2012), but we are not aware of any significant controversy over its use. Ethylene is a natural plant hormone, and many consumers use the same mechanism when they put a banana in a fruit bowl to induce ripening. Should produce ripened with ethylene also be required to be labeled? Did the mere presence of the attribute on our survey signal consumers that it is an attribute that should be avoided?”

Who are the vegetarians?

One of the challenges researchers face in trying to learn about the characteristics of vegetarians is that there are so few of them.  I've seen estimates that put the percentage of vegetarians in the US population as high as 13%, but most estimates are closer to 5%.  That means that if one does a survey that has 1,000 respondents (which is a pretty typical sample size for pollsters), you'll only have about 50 vegetarians in the sample - hardly a large enough sample size to say anything meaningful.

We've been running the Food Demand Survey (FooDS) for 19 months now, and each monthly survey has over 1,000 respondents.  I took the first years' data (from July 2013 to July 2015), which consists of responses from over 12,000 individuals.  This sample is potentially large enough to begin to make some more comprehensive statements about how vegetarians might differ from meat eaters in the US.

Applying weights to the sample that force the sample to match the population in terms of age, gender, region of residence, etc., we find that 4.2% of respondents say "yes" to the following question: "Are you a vegetarian or a vegan?", which means that 95.8% say "no".  

There is some sampling variability from month-to-month, but overall, the trend in the percentage of respondents declaring vegetarian/vegan status has remained relatively constant, and if anything, has trended slightly downward over time.

So, how do self-declared vegetarians/vegans differ from meat eaters?  The following table shows differences/similarities in socio-economic and demographic characteristics.

Some of the biggest differences appear for age, race, overweight status, and politics.  Vegetarians tend to be younger, less white, skinnier, and more liberal than meat eaters.  Two unexpected results are that vegetarians indicate a much higher rate of food stamp participation (which is a bit surprising since the share of households with >$100K in income is higher for vegetarians than meat eaters) and a much, much higher rate of food-borne illness.  

In our survey, we also measure respondents' "food values" (for detail on the approach, see this academic paper we published).  This approach requires people to make trade-offs (they cannot say all issues are most important).  Respondents are shown a set of 12 issues and are asked to place 4 (and only 4) of them in a box indicating they are the most important issues when buying food, and to also place 4 (and only 4) issues in a box indicating they are the least important issues when buying food.  We measure relative importance by subtracting the share of times an item appears in the least important box from the share of times it appears in the most important box.  Thus, relative importance is on a scale of +1 to -1, and average scores across all 12 items must to sum to zero.  

Meat eaters tend to rate taste and price as relatively more important food values than vegetarians.  Vegetarians tend to rate animal welfare and the environment as more important food values than meat eaters.  Even still, vegetarians rate nutrition, taste, price, and safety as more important food values than animal welfare or the environment.  

The survey also shows people a list of 16 issues and respondents indicate how concerned they are about each issue (1=very unconcerned to 5=very concerned).  As the table below shows, vegetarians are more concerned about all issues than are meat eaters, even an issue like GMOs which is (at present) primarily a plant issue.  The difference in level of concern between vegetarians and meat eaters is particularly large for gestation crates, battery cages, and farm animal welfare.  

Given some previous discussion on the economics of Meatless Monday, I ran some statistical models to determine whether vegetarians tend to spend more or less on food than meat eaters.  

Without controlling for any differences in income, age, etc. that were found in the initial table above, I do not find any statistically significant differences in spending patterns.  Meat eaters report spending about $94/week on food eaten at home and vegetarians report spending about $3 less (a difference that isn't statistically significant); meat eaters report spending about $46/week on food eaten away from home (e.g., at restaurants) and vegetarians spend about $9.80 more (a difference that isn't statistically significant).  Even after I control for differences in income, age, etc., I do not find any significant differences in food expenditures between vegetarians and meat eaters.  The biggest determinants of food spending is income (high income individuals (>$100K in income) spend $35/week more away from home than low income (<$40K in income)) and household size (larger households spend more).  Younger people spend about the same as the older on food a home, but spend more eating out than do the old.  

A short lesson on experimental auctions

One of the most robust findings from the research on what consumers are willing to pay for non-market goods (for example, foods made with new technologies that are not yet on the market) is that people tell researchers they are willing to pay more than they actually will when money is actually on the line.  One review showed, for example, that people tend to overstate how much they are willing to pay in hypothetical settings by a factor of about three.  That means if someone tells you on a survey that they're willing to pay $15, then they'd probably only actually pay about $5.

One way to deal with this problem of hypothetical bias is to construct experimental markets where real money and real products are exchanged.  The key is to use market institutions that give consumers an incentive to truthfully reveal their values' for the good up for sale.  I wrote a whole book with Jason Shogren on the subject of using experimental auctions for this purpose a few years back.

I recently filmed a short primer on the consumer research method for an on-line course being created by my colleague Bailey Norwood.  He graciously put it up online for anyone's viewing pleasure.