Consumer Demand for Redundant Food Labels

That’s the title of a new working paper co-authored with Lacey Wilson. Here is the abstract:

“Previous studies, as well as market sales data, show some consumers are willing to pay a premium for redundant or superfluous food labels that carry no additional information for the informed consumer. Some advocacy groups have argued that the use of such redundant labels is misleading or unethical. To determine whether premiums for redundant labels stem from misunderstanding or other factors, this study seeks to determine whether greater knowledge of the claims - in the form of expertise in food production and scientific literacy - decreases willingness to pay for redundant labels. We also explore whether de-biasing information influences consumers’ valuations of redundant labels. An online survey of 1,122 U.S. consumers elicited preferences for three redundantly labeled products: non-GMO sea salt, gluten-free orange juice, and no-hormone-added chicken breast. Respondents with farm experience report lower premiums for non-GMO salt and no-hormone-added chicken. Those with higher scientific literacy state lower premiums for gluten-free orange juice. However, after providing information about the redundancy of the claims, less than half of respondents who were initially willing to pay extra for the label are convinced otherwise. Over 30% of respondents counter-intuitively increase their premiums, behavior that is associated with less a priori scientific knowledge. The likelihood of “overpricing” redundant labels is associated with willingness-to-pay premiums for organic food, suggesting at least some of the premium for organic is a result of misinformation.”

The figure below shows a key result. People place a $0 premium on non-GMO salt, gluten-free orange juice, and hormone-free chicken have significantly higher scientific literacy scores than people who place positive or negative premiums on these redundantly labeled products.

Malthusian Inversion

I’ve noticed several articles in the past few weeks talking about slowing or even falling population growth. This article in the Economist discussed the fact that South Korea’s fertility rate is now below replacement level (i.e., fewer babies are being born than there are parents), and their figure shows the strong negative correlation between income (or GDP) of a country and a country’s fertility rate. The richer we get, it seems the fewer babies we want or need. Then, came this opinion article in the New York Times a couple days ago about the “Chinese Population Crisis,” in which Ross Douthat argues, “Unlike most developed countries, China is growing old without first having grown rich.”

We’ve all probably been adequately exposed to the concerns and problems associated with over-population from the writings of Malthus to Ehrlich’s Population Bomb. Less well appreciated are the benefits and costs associated with a falling population. For one take on the potential concerns, see this 2013 piece by Kevin Kelly entitled the “Underpopulation Bomb.” He states the problem as follows:

“This is a world where every year there is a smaller audience than the year before, a smaller market for your goods or services, fewer workers to choose from, and a ballooning elder population that must be cared for. We’ve never seen this in modern times; our progress has always paralleled rising populations, bigger audiences, larger markets and bigger pools of workers. It’s hard to see how a declining yet aging population functions as an engine for increasing the standard of living every year.”

A smaller population would no doubt produce some benefits. Probably the most obvious benefit is that a smaller population would lessen human’s demands on our environment and natural resources. There is already evidence of this de-materialization. Check out Andrew McAfee’s book More from Less, where he argues that technology has led us past peak demand for many natural resources.

Among the adverse consequences, however, of falling population is likely to be downward pressure on farm incomes. The Malthusian concern implied a large population that was incapable of sufficiently feeding itself. For humanity writ large, this outcome would have been a tragedy. Farmers (or at least land owners), however, would have likely benefited from this dire outcome. More people demanding more food would have driven up food prices, land prices, and farm income. Innovation and productivity growth, fortunately, prevented the hunger problems that would have accompanied a rising population.

One crude way to see whether population growth is out-pacing the effect of innovation is to look at the long-term trend in food and agricultural prices. Here is a graph I created based on USDA data on three major commodity crop prices over time. The long-term trend is negative, suggesting innovation has outpaced the effects of population and income growth.

Lower prices seems bad for farmers, but if they are able to sell more output using fewer resources, they also benefit (see this paper by Alston for some discussion on the farmer benefits and costs from innovation). Still, it is probably safe to say that farmers and the agricultural sector have largely come to expect a rising world population to support demand growth and offset some of the downward pressure on prices. Population projections suggest that expectation may not hold out into the future.

Indeed, research by my Purdue colleagues Uris Baldos and Tom Hertel suggests the effects of population on crop prices is likely to be much lower than what we’ve experienced in the past. They consider the effect of three factors on crop prices and production: population, income, and innovation. From 1960 to 2006, their findings indicate that the effect of innovation pushed down crop prices more than rising income and population pushed up prices, leading to an overall fall in prices, consistent with the graph above. What do they predict for the future based on expected trends in innovation, population, and income? Falling prices. They predict that, going out to 2050, the price increasing effects of population will be about half what they were from 1960 to 2006. Thus, rather than the Malthusian population bomb, we seem to be heading to a sort of Malthusian inversion.

It’s also important to note that population growth will be unevenly distributed across the world. Data and projections from the United Nations show very different anticipated population trends in low-, middle-, and high-income countries. Here is a figure I created based on their data. In 1950, population was 45%, 70%, and 82% lower than it is today in high-, middle-, and low-income countries. By 2010, the UN is projecting population will be 3%, 23%, and 220% higher in high-, middle-, and low-income countries.

The implications for U.S. farmers are many fold. For one, demand growth (at least from population growth) is likely to occur outside this country, highlighting the importance of trade. Within the U.S., rising income, and demand for quality, may play an increasingly important role in supporting farm incomes in the years to come. Finally, flat or declining population, along with innovation, have the potential to have positive environmental outcomes, and it will important to think about appropriate farm policy in light of these trends.

What to Expect in 2020

My colleagues and I have pulled together the 2020 Outlook issue of the Purdue Ag Econ Report. Contributions include:

• Our Long, Slow, Steady Expansion Should Continue by Larry DeBoer

• Trade and trade policy outlook for 2020 by Russell Hillberry

• 2020 Outlook: Farm Policy by Roman Keeney

• Food Price Inflation is on the Rise Globally but Steady at Home by Jayson Lusk

• Farmland Market Outlook for 2020 by Todd Kuethe and Craig Dobbins

• Increase in Indiana cash rent seems unlikely in 2020 by Criag Dobbins and Todd Kuethe

• More milk, consolidation continues, but still an improved 2020 price outlook by Nicole Widmar

• 2020 Purdue Crop Cost & Return Guide by Michael Langemeier and Craig Dobbins

• 2020 Corn Price Outlook by James Mintert and Mindy Mallory

• 2020 Soybean Price Outlook by James Mintert and Mindy Mallory.

Check out the whole thing here.

Food Environment or Preferences?

Do poorer people eat unhealthily because they don’t have access to grocery stores and fresh fruits and vegetables (and are more easily able grab fast food or convenience store options), or is it because their preferences for healthy food differs from higher income households? In a sense, this is a question of nature vs. nurture applied to healthiness of food consumption, and it is a lively debate related to questions about food deserts, convenience store regulations, zoning, and more.

This interesting and rigorous paper (gated version here) on the topic by Hunt Allcott, Rebecca Diamond, Jean-Pierre Dube, Jessie Handbury, Ilya Rahkovsky, and Molly Schnell was recently published on the topic in the Quarterly Journal of Economics. I blogged about this paper a couple years ago, but I mentioned again now that it’s been revised and put through the rigors of the peer-reviewed process, and because the implications are quite important. Here’s the abstract:

“We study the causes of “nutritional inequality”: why the wealthy eat more healthfully than the poor in the United States. Exploiting supermarket entry and household moves to healthier neighborhoods, we reject that neighborhood environments contribute meaningfully to nutritional inequality. We then estimate a structural model of grocery demand, using a new instrument exploiting the combination of grocery retail chains’ differing presence across geographic markets with their differing comparative advantages across product groups. Counterfactual simulations show that exposing low-income households to the same products and prices available to high income households reduces nutritional inequality by only about ten percent, while the remaining 90 percent is driven by differences in demand. These findings counter the argument that policies to increase the supply of healthy groceries could play an important role in reducing nutritional inequality.”

These findings suggest efforts to eliminate food desserts or to constrain offerings of convenience stores are likely to have minimal effects. This paper shows, like some of my work, that higher- income households tend to eat healthier than lower-income households. Want lower income people to eat healthier? Then, we probably need to think about ways to increase their incomes. Another possible solution, albeit difficult to successfully and cost-effectively implement, is nutrition and health education.

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.