Consumer beliefs about healthy foods and diets

That’s the title of a new article I just published in the journal PLoS ONE. This is an exploratory/descriptive study with the aim of probing consumer’s perceptions of the term “healthy” in relation to food. The study is motivated by the fact that the FDA regulates the use of the term on food packages, and is in the process of reconsidering the definition. Here are some of the key results:

“Consumers were about evenly split on whether a food can be deemed healthy based solely on the foods’ nutritional content (52.1% believing as such) or whether there were other factors that affect whether a food is healthy (47.9% believing as such). Consumers were also about evenly split on whether an individual food can be considered healthy (believed by 47.9%) or whether this healthiness is instead a characteristic of one’s overall diet (believed by 52.1%). Ratings of individual food products revealed that “healthy” perceptions are comprised of at least three underlying latent dimensions related to animal origin, preservation, and freshness/processing. Focusing on individual macronutrients, perceived healthiness was generally decreasing in a food’s fat, sodium, and carbohydrate content and increasing in protein content. About 40% of consumers thought a healthy label implied they should increase consumption of the type of food bearing the label and about 15% thought the label meant they could eat all they wanted.”

One part of the analysis focuses on parsing out the correlations between the healthiness rating consumers placed on different types of foods . Below are three dimensions of 15 food’s healthiness ratings as determined by factor analysis.

Here’s the portion of the text describing these results:

“The first factor (explaining 54% of the total variance), shown on the vertical axis of the bottom panel of Fig 3 shows all animal products with high values and other non-animal products with lower values, suggesting consumers use animal origin as a primary factor in judging whether a food is healthy. A second factor (explaining 31% of the total variance), illustrated on the horizontal axis of the top panel of Fig 3, has canned and frozen fruits and vegetables with the highest values, bakery and cereal items, candy, and fresh fruits and vegetables with mid-to-low values, and animal products with the lowest values, which seems to suggest consumers use degree of preservation as another dimension of healthiness. Finally, the third factor (explaining 22% of total variance), illustrated on the vertical axis of the top panel and the horizontal axis of the bottom panel of Fig 3, indicates freshness or degree of processing is another dimension to healthiness evaluations. These results indicate that healthiness is not a single unifying construct, but rather consumers evaluate healthiness along a number of different dimensions or factors. A food, such as beef or fish, can be seen as scoring high in some dimensions of healthy but low in another.”

There’s a lot more in the article.

Senate Hearing on Livestock and Poultry Issues

Yesterday I had the opportunity to testify before the U.S. Senate Committee on Agriculture, Nutrition, and Forestry in a hearing about livestock and poultry. A video of the entire hearing is here. My written testimony is also at the link. For convenience, I’ve also reproduced it below.

Chairman Roberts, Ranking Member Stabenow, and Members of the Committee, thank you for inviting me here today.  I serve as Distinguished Professor and Head of the Agricultural Economics Department at Purdue University, and I will focus my remarks on six economic issues currently facing livestock and poultry industries: global protein demand and trade, mandatory price reporting, competition, labor, animal disease, and the need for innovation.

 Population and income are two key drivers affecting demand for meat and poultry. Slow population growth and concerns about an economic slowdown indicate the potential for depressed meat demand in this country.  Health, environment, and animal welfare criticisms, coupled with emerging plant- and lab-based competitive alternatives, are also significant headwinds. 

 These factors suggest that meat demand growth is largely expected to occur outside the United States.  Having access to consumers in other countries has become increasingly important to the livelihood of U.S. livestock and poultry producers. The U.S. exported about 12% of beef, 22% of pork, and 16% of poultry production last year.  It is in this context that trade agreements are important to help open markets for US producers to allow products to flow to consumers who value them most.

 Some U.S. producers have expressed concerns about the competition from imports, but the U.S. is a net exporter of meat and poultry products, and the types and qualities of meat we import tend to differ from what we export. There have been some calls to renew Mandatory Country of Origin Labeling (MCOOL).  Congress repealed MCOOL for beef and pork in 2015 to avoid more than $1 billion in retaliatory tariffs after a protracted legal battle with other countries before the World Trade Organization.  Our survey and experimental research suggests many consumers indicate they are willing to pay premiums for U.S. meat products; however, research also shows few consumers were aware of actual origin labels when grocery shopping, and analysis of grocery store scanner data did not reveal any significant changes in consumer demand for beef or pork after the implementation of MCOOL.  Meat demand indices indicate, if anything, beef and pork demand has increased after the repeal of MCOOL.  Cattle prices fell shortly after the repeal of MCOOL, but this is largely explained by an increase in cattle inventory that happened to coincide with the labeling policy change.  To the extent consumers are truly willing to pay a premium for U.S. labeled meat that exceeds the costs of tracing and labeling, there remain opportunities for private entities to take advantage of this market opportunity.

 The current authority for Livestock Mandatory Reporting (LMR) is set to expire in 2020.  LMR was designed to improve transparency, facilitate market convergence, and reduce information asymmetries.  Despite these laudable goals, academic research on impacts of LMR is mixed.  Shortly after its initial passage in 1999, surveys of cattle producers suggest expectations about the impacts of LMR may have been overly optimistic.  Some concerns have been expressed that LMR might facilitate rather than curtail anticompetitive behavior among packers.  However, evidence indicates LMR helped facilitate integration of regional markets.  It is important for LMR to continue to modernize and be agile in response to the pace of change in the industry.  One challenge is the dwindling share of cattle and hogs sold in negotiated or cash markets, which typically serve as the base price in formula contracts.  There are significant benefits to formula contracts and more producers are voluntarily choosing this method of marketing over the cash market, but questions remain about the volume of transactions needed in the cash market to facilitate price discovery.  A benefit of LMR is the massive amounts of data provided to economists and industry analysts to help understand these and other market dynamics.   

 Last month, price dynamics following a fire at a packing plant in Western Kansas renewed discussion about packer concentration and potential anti-competitive behavior. Concerns about anti-competitive behavior in general must be evaluated on a case-by-case basis, and details about this particular case are still emerging in light of simultaneous market dynamics that were also at play.  Available evidence to date suggests the observed reduction in cattle prices and the increase in wholesale beef prices following the fire are not inconsistent with a model of competitive outcomes. An unexpected reduction in processing capacity reduces demand for cattle, thereby depressing cattle prices. The need to bring in additional labor to increase Saturday processing and temporarily re-purposing cow plants for steers and heifers involves additional costs that pushed up the price of wholesale beef.  These price dynamics are not surprising and are generally what would be expected from the fundamental workings of supply and demand. 

 In general, a lack of availability of labor at processing facilities and in transportation have proved significant hurdles for the sector.  When processors are unable to secure sufficient workforce to operate facilities at capacity, there is the potential to reduce demand for livestock and poultry, which has much the same price effects witnessed after the Kansas fire.  

 I also urge the committee to pay close attention to emerging animal disease issues. African Swine Fever (ASF) in China has had a decimating impact on their hog herd and has increased their pork prices by almost 50%. The significant disruption to the Chinese hog supply has reverberated through global agricultural markets, reducing demand for U.S. soybeans and inducing substitution toward alternative proteins such as beef and poultry. While U.S. hog producers have been able to increase exports to China as a result of ASF, exports are not what they could have been had China not raised tariffs on pork.  It appears that ASF is spreading beyond China.  My calculations suggest that if an outbreak of ASF similar in relative magnitude to the one in China were to occur here, U.S. pork producers could lose about $7 billion/year and U.S. consumer harm would be at least $2.5 billion/year.  ASF is not the only animal disease concern, and an outbreak of foot mouth disease, discovery of bovine spongiform encephalopathy (BSE), or a return of avian influenza or Newcastle disease could have similar devastating impacts.  Thus, there is a need for additional funding for research to combat foreign animal disease. 

 There is also a need for funding to improve the productivity of the livestock and poultry sectors. Productivity growth is the cornerstone of sustainability.  For example, had we not innovated since 1970, about 11 million more feedlot cattle, 30 million more market hogs, and 7 billion more broilers would have been needed to produce the amount of beef, pork, and chicken U.S. consumers actually enjoyed in 2018.  Innovation and technology saved the extra land, water, and feed that these livestock and poultry would have required, as well as the waste and greenhouse gases that they would have emitted.  Investments in research to improve the productivity of livestock and poultry can improve producer profitability, consumer affordability, and the sustainability for food supply chain. 

What Food Policies do Consumers Like and Dislike?

I have a new working paper with Vincenzina Caputo in which we elicit consumers’ preferences for 13 different food policies. Here’s our main motivation (references removed for readability).

“A variety of food policies have been proposed, and in some cases enacted, in an effort to improve public health, environmental outcomes, or food security. Proposed actions include a spectrum of policies ranging from fiscal incentives/disincentives, bans, labelling programs, and passive policies such as subsides and investments in education. What food policy proposals do consumers prefer? While there have been numerous studies aimed at calculating the welfare effects of individual food policies it is difficult to easily ascertain the relative preferability of numerous policy options, even those that have the same objective (e.g., “fat taxes” and nutritional education both aim to improve public health). ”

We conducted a nationwide survey of 1,056 U.S. consumers who were asked to indicate the relative desirability of the following food policies.

Rather than use a traditional approach, where respondents are not required to make trade-offs between policies (e.g., people can approve of all policies or rank all policies as “very important”), we used the “best worst scaling” approach that requires respondents to make trade-offs. The approach requires respondents to answer a series of questions like the one below, where for each question, they have to indicate their most and least preferred policies.

The results are analyzed using a choice model that allows for preference heterogeneity. The main outcomes are below, reported as “preference shares” - i.e., the percent of people predicted to choose each policy as most preferable. Results indicate the highest levels of support for investments in agricultural research and requirements of food and agricultural literacy standards in public education. Fat, calorie, and soda taxes are the least popular. These preference shares provide a measure of intensity of preference in a population. Funding for agricultural research is 14%/8% = 1.75 times more preferable than symbolic nutritional labeling.

While the above results are useful in providing intensity of relative preferences, they do not indicate whether people would actually vote in favor of a policy. The table below shows the results of that question; the results largely align with the best-worse scaling approach. Fewer than one-third of respondents are in favor of these three tax policies.

There are a number of significant demographic correlates with policy preferences. Some are not surprising. For example, Nutrition Assistance (or SNAP) is more desirable to lower income vs. higher income households and Democrats vs. Republicans. As another example, soda taxes are less desirable among lower income households.

Funding for agricultural research was generally supported across all demographic categories except for age: older individuals were more supportive of funding for agricultural research than younger individuals.

Reducing Food Waste - Where's the Incentive?

In recent years, there has been a lot attention being focused on reducing food waste. While I have argued for more nuance than one often sees in popular exhortations to reduce waste, the issue is important: it would be nice to find ways to save all the resources that go into producing food that ultimately winds up in the garbage.

A number of discussions over the past couple months have led to an aspect of this problem that hasn’t received much attention. Namely, what is the incentive of food producers and manufacturers to reduce waste? Or, what are the most effective mechanisms to reduce waste?

One way of reducing waste is what we might call the “demand side” strategy. Try to convince consumers to consume all of what they buy and throw out less. Our stomachs and pantries are only so large, and as a result, this presumably means consumers would ultimately buy less food. In economic terms, this leads to a downward shift in demand, which results in lower prices and less food sold. For producers, this is certainly a bad outcome: selling less food at lower prices means lower revenues and profits. From the perspective of a food producer, all they care about is whether the product sells. What you do with it after you buy it is of little consequence to the seller. As such, one might wonder how much incentive food producers and sellers have to reduce waste, at least via this demand side strategy. To boot - we don’t know for sure whether consumers are better or worse off. They pay lower prices but also buy less food, and as a result the impacts on consumers is ambiguous.

A different way to try to reduce food waste might be called a “supply side” strategy. One challenge with popular conceptions of food waste is that they seems to imply there are large inefficiencies in food supply chains. That some people seem to indirectly imply that farms, food manufacturers, and grocers are losing or throwing out food that they could profitably sell. To be sure, there are likely some inefficiencies in the food supply chain, but food and ag are tend to be competitive, low margin businesses which makes it hard to believe they’re leaving dollar bills lying around that they could easily pick up. To incentivize these firms to reduce waste, loss, and spoilage, something has to change to reduce the cost of preservation. That “something” is likely investment in research and the creation of technologies that enable farms and food manufacturers to affordably make use of food that might otherwise have been unsalable. An old example might be the advent of canning or refrigerated rail cars. More modern examples might include better grain storage bins or storage management practices, vacuum packaging, high pressure pasteurization, etc.

In economic terms, these technologies can be conceptualized as shifting the supply curve downward shift - i.e., lowering the marginal cost of delivering a given quantity of food to the market. Such a shift would lower the price of food while enabling more more food to be sold. Consumers are definitely better off: they get to have more food at lower prices. Whether producers as a group are better off from the supply shift depends on how sensitive producers and consumers are to price changes, but producers who are early adopters of the new technology are almost certainly better off.

Whether the demand-side or supply-side strategy leaves “society” better off (at least as defined by producer profits and consumers’ economic well-being) is not completely predictable because it depends on relative elasticities of supply and demand for the foods in question, among other factors. Ignoring any externalities from food that is thrown out, I would generally expect the “supply side” strategy to be better: we know it makes consumers better off and likely makes producers better off too (though not always). But, it ultimately results in more food being sold and potential (and perhaps ironically) more consumer waste. So, the big unanswered question is the nature and size of the “externality” of food thrown away.

Why don't we vote like we shop?

Readers of this blog will know I’ve been interested in the divergence of voting and food shopping behavior for some time (e.g., see here, here, or here). Much of this interested was prompted by the stark example provided by Proposition 2 in California back in 2008, when about 64% of Californian’s went to the polls and outlawed the production of a good they routinely bought (caged eggs) resulting in a so-called vote-buy gap. I think it was Glynn Tonsor who I first heard refer to the outcome as an unfunded mandate: voters required producers to adopt costlier production practices for which shoppers had already revealed they were unwilling to provide sufficient compensation in the marketplace.

While we know this phenomenon exists, it isn’t clear why. Along with Glynn Tonsor, Bailey Norwood, and Andrew Paul, we set out to tackle this question by conducting some real-food, real-money experiments. The resulting paper is now forthcoming in the Journal of Behavioral and Experimental Economics.

What did we do? We recruited people to participate in a series of decision making exercise, where they first made a shopping choice. The shopping choice options were: A) a more expensive cookie made with cage free eggs, B) a less extensive cookie made with conventional eggs, C) a snack without animal products, or D) refrain from buying anything. Then, in a second step, people were placed into groups (of small or large size), where they voted on whether to ban option B (the cookie made from conventional eggs) for the people in their group. Finally, if the vote passed, people re-chose from the constrained set of options. This basic set-up was repeated in several conditions that varied information, group size, and more to test different reasons for vote-buy gap.

The first result is that we can replicate the vote-buy gap in our experimental setting. We note:

“approximately 80% of the individuals who chose snacks with caged eggs when shopping subsequently voted to ban snacks with caged eggs. The finding rules out the suggestion that the vote-buy gap is an illusion or statistical artifact, as it can be re-created in an experimental lab setting at an individual level. ”

As the above results suggests, we are immediately able to rule out one explanation for the vote-buy gap - something we call the non-buyer hypothesis. The non-buyer hypothesis suggests the vote-buy gap is something of an illusion because, proverbially speaking, apples (voters) are being compared to oranges (shoppers). In the “real world”, many consumers of eggs are voters; however, not all voters are egg consumers. For example, individuals who are vegan do not buy eggs, but they may vote in favor of initiatives similar to that of Proposition 2. But, in our study we can compare each individual’s shopping choice to their own vote, and as the foregoing quote indicates, 80% of people switch.

We find a bit of support for the following, which is tested by giving one group more salient information about which options used cage and which used cage free eggs:

“Knowledge Hypothesis: The vote-buy gap is caused by the fact that consumers themselves believe, or perceive that other consumers believe, that they are buying cage-free eggs when in fact they are buying cage eggs; better, more salient information about housing practices when shopping will reduce the vote-buy gap.”

But, even in the condition where clear-transparent information was given about the types of eggs used to make each cookie, the share of people who voted to ban cage eggs was 15 to 20 percentage points higher than was the market share of purchased snacks made with cage free eggs.

I was personally most excited to test two hypotheses that related to group size (people voted in groups of roughly five or fifty). Here were those hypotheses, both of which suggest greater likelihood of voting “yes” to ban snacks with cage eggs in larger groups as compared to smaller groups.

“Public Good Hypothesis: The vote-buy gap is caused by the fact that more animals and people are impacted by a ban than the impact of a single shopping choice for cage-free eggs; as the size of the group affected by a vote increases, individuals are more likely to vote in favor of the initiative if it has a desirable public good component, thereby increasing the vote-buy gap.

Expressive Voter Hypothesis: The vote-buy gap is caused by the fact that in large groups, an individual’s vote is unlikely to be a deciding factor, privileging expressive preferences over instrumental preferences; as a group size increases, and the likelihood that an individual’s vote is consequential and decisive falls, individuals are more likely to vote in favor of the initiative, thereby increasing the vote-buy gap.”

Both hypotheses conjecture that the vote-buy gap will be larger in large groups than small groups. However, our data shows that when moving from small to large groups, the vote-buy gap is actually larger in the small groups than the large group, exactly the opposite of what is predicted.

In the end, we can be fairly confident the vote-buy gap is real and replicatable, but alas we still don’t have a good answer as for why. Here’s how we leave it in the paper:

“A residual hypothesis that remains if all others fail to explain the gap is inconsistent preferences. That is, people may have different preferences when shopping as compared to voting. This sort of preference inconsistency is at the heart of the so-called consumer vs. citizen phenomenon. The thought is that people adopt more public-minded preferences when in the voting booth but rely on more selfish motives when shopping privately. ... While this explanation is perhaps not intellectually satisfying, it is perhaps consistent with one long strain of economic thought, De gustibus non est disputandum, while contradicting another, fixed and stable preferences. ”

But, make no mistake: just because we don’t know the answer to the “why” doesn’t imply the vote-buy gap is inconsequential. Recall the unfunded mandate? Here’s what happened in our experiment.

“many individuals who originally chose to purchase a cookie decided, after the ban, to select “none” in their second selection when only higher-priced cookies were available. Depending on the treatment, anywhere from 21.74% to 43.38% of consumers who purchased cookies prior to the ban no longer did so after the ban. These lost purchases are precisely the worry of egg producers.”