Comparing the views of the Italian general public and scientists on GMOs

You might recall the widely discussed 2015 study from the Pew Foundation comparing attitudes of the general public to that of scientists. The headline finding that captured public attention was the following:

“A majority of the general public (57%) says that genetically modified (GM) foods are generally unsafe to eat, while 37% says such foods are safe; by contrast, 88% of AAAS scientists say GM foods are generally safe. The gap between citizens and scientists in seeing GM foods as safe is 51 percentage points. This is the largest opinion difference between the public and scientists [out of more than a dozen issues].”

In a new paper with Gioacchino Pappalardo and Mario D’Amico, we were curious about the extent to which this finding extrapolated to other countries that have purportedly been even more averse to GMOs. Gioacchino and Mario are with the University of Catania in Italy, so naturally, we extended this question to Italians. Our work was recently accepted for publication in the International Journal of Food Science and Technology. Here is the abstract:

“The gap between statements from scientific organizations about the safety of genetically modified (or GMO) food and public concerns about the technology is puzzling, raising questions about the extent to which expert opinion and scientific consensus can sway public opinion and whether scientific progress might be hindered by public opposition. This study sought to determine whether beliefs about GMO safety are high among experts in countries where there has been significant public opposition to the technology. Surveys conducted among 1,006 members of the Italian general public and 258 members of the Italian Association of the Agricultural Science Societies (AISSA) reveal that whereas 54% of our sample of the Italian general public believes GMOs are generally safe to eat, 81% of sample of the Italian agricultural scientists believe the same. Despite the gap in lay‐expert safety beliefs, results reveal greater similarity between scientists and the general public on topics related to beliefs about the impact of GM food on food prices, the developing world, and concentration in the agricultural supply chain.”

Market Shares and Substitution Toward Plant Based Meat

In the past, I’ve discussed research we’ve conducted on consumer demand for emerging plant-based meat alternatives vs. traditional meat (e.g., see here or here). Today, I’m happy to link to a new, extensive study on the topic conducted with Glynn Tonsor and Ted Schroeder at Kansas State for the Cattlemen’s Beef Promotion and Research Board.

There are a lot of interesting results stemming from four different experiments and multiple questions asked, but I’ll hit just a few highlights. Firs, along a variety of dimensions, consumers’ perceptions of beef are favorable relative to consumers’ perceptions of plant-based alternatives. For example, here is one series of questions.

Second, if given a pair-wise choice between a beef burger and a Beyond Meat burger at the same price, roughly a quarter of consumers choose the Beyond Meat option. Interestingly, the choice wasn’t much affected by whether we provided nutrition facts panels, ingredient lists, or whether the beef burger was organic, as shown below.

Another experiment, framed in a foodservice environment, explored how choices for beef burgers were affected by a Beyond Meat alternative vs. a Chicken Wrap. Short story: Introducing a Beyond Meat alternative has about the same impact as introducing a Chicken Wrap.

Finally, we conducted some simulated shopping choices (in both food service and grocery framings) to estimate own- and cross-price elasticities of demand for plant-based alternatives and traditional meat options.

As it turns out this sort of analysis is quite timely. On February 2, Impossible announced a 20% price reduction. Here is our estimated demand elasticities for all consumers and segmented by people we classify as regular meat consumers vs. those wo do not regularly consume meat (those who classified their diet as vegetarian, vegan, flexitarian, or other).

As the table above shows, a 1% drop in Impossible Burger’s price would lead to a 0.14% reduction in purchases of Store-Brand ground beef at retail grocery (across all consumers). If we extrapolate that to a 20% decrease, that suggests the recently announced price change will lead to a a 2.8% decline in Store Brand ground beef.

This reduction comes almost entirely from consumers who are not regular meat eaters (cross-price elasticity of +0.26) vs regular meat consumers (cross-price elasticity of +0.05). In fact, within the regular meat consuming segment we would project the price drop in Impossible would result in nearly 3x the impact on Beyond Beef as Store Brand ground beef.

There is much, much more in the report. You can read the whole thing here.

Bacon Causes Cancer: Do Consumers Care?

That’s the title of a new working paper I’ve co-authored with Purdue PhD student, Xiaoyang He. The answer to the question is: “yes,” retail bacon prices and sales fell following the pronouncement that processed meat was classified as a carcinogen; however, we did not find the same for other processed meat categories, ham and sausage. Maybe all those headlines like “The great bacon freak-out” and “Eating just one slice of bacon a day linked to higher risk…” really served to focus people’s attention. Here is the abstract:

“In October 2015, the International Agency for Research on Cancer (IARC) released a report classifying processed meat as a type 1 carcinogen. The report prompted headlines and attracted immediate public attention, but the economic impacts remain unknown. In this paper, we investigate the impacts of the IARC report on processed meat prices and purchases using retail scanner data from U.S. grocery stores. We compare changes in prices and sales of processed meat products to a constructed synthetic control group (using a convex combination of non-meat food products). We find a significant decrease in bacon prices and revenues in the wake of the IARC report release, but we find no evidence of a demand reduction in ham and sausage. At the same time, we find beef sales and revenue increased significantly after the report, while beef price significantly fell.”

That bacon prices fell alongside the volume sold is a clear signal that consumer demand for bacon fell as a result of the IARC report.

As we discuss in the paper, a key challenge with identifying the effects of the IARC report rests in constructing a counter-factual prediction of what would have happened to prices and sales of processed meat products had the IARC report not been released. We cannot use data from an unaffected location because the media reports were widely distributed across the U.S. Instead, we use statistical methods (the so-called synthetic control method) to identify alternative food products as controls. We describe the approach as follows:

“The synthetic control method sidesteps this problem and uses a combination of candidate controls instead. We Nielsen retail scanner data to determine the effect of the IARC report on processed meat markets. This data contains weekly information regarding sales, price, and revenue for processed meat categories as well as categories that are included in the synthetic control group. We use the data from 2014 to 2016, which includes approximately one year of data before and one year of data after IARC report released date. The post-IARC time period is long enough to determine, if any impact exists, how long it lasts.”

In essence we use the the estimated relationship among dozens of possible grocery item prices and bacon prices prior to IARC report release to predict what bacon prices would have been had the report release not occurred. Here is the calculation of actual and counter-factual bacon prices ($/oz) before and after the report release:

After a few weeks of bacon prices remaining above their predicted values, bacon prices ultimately averaged 6.5% lower than what we predict would have occurred had the IARC report not been released.

You can read the whole thing here.

Resetting the Table: Straight Talk About the Food We Grow and Eat

That’s the tile of Robert Paarlberg’s latest book, set to be released on February 2. I talked to Rob a bit about the project a couple years ago when he was in Indiana interviewing a few farmers for background research. I should note Rob is a West Lafayette native, and his father Don Paarlberg was a faculty member in the Agricultural Economics Department at Purdue, in addition to serving in a variety of government roles including Assistant Secretary of Agriculture under Eisenhower.

Here is my “blurb” for Resetting the Table.

““In Resetting the Table, Robert Paarlberg fact checks the most central myths of the modern food movement. Paarlberg’s firm grasp on the realities of modern agriculture lend credence to his insights on how we might take meaningful steps toward solving our dietary and environmental ills. He argues that food policy, rather than farm policy, should serve as the focal point of action. In doing so, he offers valuable straight talk to commercial farmers and highlights the critical importance of continued innovation and entrepreneurship in agricultural production. This is a must read book for anyone interested in understanding where their food comes from and the policies that affect how we eat”

You might also check out a review of the book in the Wall Street Journal, where Paarlberg’s book is reviewed alongside Mark Bittman’s predictably polemical new release entitled Animal, Vegetable, Junk.

Food Insecurity among College Students

Previous research has reported shockingly (dare I say, unbelievably) high rates of food insecurity among college students. For example, here is one 2019 study reporting “60 percent of students had experienced food insecurity within the past thirty days or housing insecurity/homelessness within the past year.” Frankly, I’ve found these results a bit hard to believe given overall food insecurity rates in the U.S. are less than 10% and the data showing that young adults from wealthier households are more likely to go to college than those from poorer households. None of this is to say there isn’t any food insecurity on campus, or that we shouldn’t undertake some efforts to reduce the problem; however, we need more thoughtful discussion about what, precisely, is being measured in these studies. Particularly, when we see that 26% of college students on unlimited meal plans show up as food insecure according to traditional measures.

Thus, I was pleased to see this paper by Brenna Ellison and colleagues just released in the journal Food Policy. As they describe, there are high stakes to getting the estimates of food insecurity right:

“A growing body of research among college students has estimated remarkably high levels of food insecurity when compared to food insecurity estimates from the general population over the past decade, with recent literature reviews reporting average prevalence rates of 33–51% compared to 9.8% among U.S. adults. Given these high rates of food insecurity, policymakers at the state- and federal-levels are considering legislation to better understand and ultimately alleviate food insecurity in the college student population. Further, the National Postsecondary Student Aid Study will soon collect national surveillance data on college student food insecurity. However, emerging research suggests that existing food insecurity measurement tools may not perform as expected when used with college students. Indeed, there is no food insecurity measure that has been validated for use with college students.”

As they go on to discuss, a big issue is that food security is primarily measured in this country with a set of 18 survey questions, like “I worried whether my food would run out before I got money to buy more.” Importantly, the official government statistics on food security don’t even ask people these questions if people’s income is sufficiently high (it is assumed high income households are, by definition, food secure). Previous research has shown one can get MUCH higher food insecurity measures if you ignore these income thresholds. Ellison et al. write:

“To date, only one study has attempted to test the use of screeners in the college population (Nikolaus et al., 2019b), with results indicating that using the two-item screener produces substantially lower (13–15 percentage points lower) food insecurity rates. A recent study in the general population found similar results, with significantly higher prevalence rates of food insecurity without the use of screening protocols (Ahn et al., 2020). It should be noted that the income screener is not easily adapted to the college population due to the challenging nature of estimating income for college students, as they may have financial resources from the federal government (e.g., Pell grants), scholarships, parents/family, or other social supports in addition to any individual income. Therefore, alternative screening procedures may need to be considered to reduce respondent burden among the college population in the future.”

The authors argue for more work to derive food insecurity measures specifically designed (and validated) for college students rather than just assuming general population surveys “work” for students as well. College students are a unique population:

“For college students who are emerging adults, the ongoing transition from their parents’ households to other housing arrangements may also pose challenges for the use of “household” phrasing in questionnaires. Without clarification, students may interpret this as their parents’ households (in which they still may reside for extended periods of time) rather than their current housing situation. Students may also question whether they should include roommates, partners, or others as members of their “household” (Ames and Barnett, 2019). It is also possible that students experience housing insecurity and lack a “household” altogether (Goldrick-Rab et al., 2018).”

The whole paper has solid advice on next steps in designing appropriate food insecurity measures for college student populations.