Food and Health: Behavioral Economics and Response to Intervention

Abstract

Food consumption meets each person’s immediate need for dietary energy each day, with foods selected in pursuit of various goals such as taste and enjoyment, convenience and social aspirations. Food consumption also has long-term impacts on a person’s future health, but a food’s appearance and its taste or smell convey little information and might even be misleading about those future impacts. The link between food and future health is particularly unclear for recently introduced packaged and processed foods or meals away from home that have new ingredients in unfamiliar combinations. Centuries of trial and error give people a variety of food traditions, while market forces create rapidly changing and diverse food environments influenced by a variety of policies and programs, some of which are influenced by recent scientific evidence. This chapter introduces the tools of behavioral economics used to understand preferences and guide intervention. Behavioral economics in general addresses psychological causes of preference reversals, whereby people contradict themselves with inconsistent choices due to systematic patterns such as loss aversion and present bias, and thereby do not reach the highest levels of wellbeing for their future selves. Food choice is a kind of health behavior for which both psychology and underlying biology play a central role, creating the need and opportunity for well-designed interventions to improve future wellbeing.

8.1 Behavioral Economics of Food Choices for Future Health

8.1.1 Motivation and Guiding Questions

Each person’s food preferences and habits are formed by trial-and-error experiences, modifying traditional culinary practices under new circumstances. Given what nutrition researchers have discovered about how foods affect our own future health, can we all alter our choices to improve health outcomes? And can we all do so in a way that also helps us achieve our other goals, such as the pleasures of eating, our social aspirations and need to save time for other activities?

Some of the obstacles to food choice for future health are familiar problems faced by any ongoing behavior that affects our future wellbeing. Psychological and cognitive constraints on decision-making create well-known patterns of behavior with preference reversals, for example eating a lot of salty chips or sweet biscuits for a snack and later wishing we had chosen an apple or banana instead. These self-contractions prevent us from reaching the highest attainable level of wellbeing in the long run for our future self. This section introduces some aspects of each person’s own individual psychology in decision-making, such as present bias and loss aversion, while the next section focuses on social psychology and the effect of other people on our decision-making.

Some psychological and cognitive influences on decisions can be addressed by the toolkit of behavioral economics. Like other fields of economics, we start with the idea that people have learned from experience and done the best they can, but then add constraints related to the difference between immediate choices for our present self and the interests of our potential future selves. For food economics, choices are influenced not only by the psychology of decision-making, but also by biological and physiological influences on appetite and food choice, mediated by hormones and other involuntary mechanisms. This section briefly introduces a few important influences on food choice, focusing on how taking account of both psychology and physiology factors in decision-making can be considered when planning how to meet our own food needs or designing interventions to help others improve their long-term health while also meeting other objectives.

By the end of this section, you will be able to:

• 1. Define preference reversals and explain their consequences for how a person's wellbeing can be understood by themselves or others;

• 2. Define loss aversion and status-quo bias, and describe its consequences for decision-making;

• 3. Define discounting and present bias, and describe its consequences for decision-making;

• 4. Describe how individuals and decision-makers in communities and the government can take account of behavioral factors to improve wellbeing over time.

8.1.2 Analytical Tools

This section introduces some insights from research in health behavior and psychology that can be incorporated into food economics, for the purpose of improving economic analysis and interventions in the food system.

Like other aspects of economics, our purpose in this section is to help explain, predict and assess everyday experiences, which Alfred Marshall described in 1890 as ‘the ordinary business of life’. We do this on the premise that each person can learn from experience and has chosen what we observe in pursuit of their wellbeing. Behavioral economics aims to take account of ordinary behavioral and psychological biases observed repeatedly in many populations, anticipating their effects to improve average outcomes in each community. Our goal is to identify patterns that can be addressed with the toolkit of economics such as taxes and regulation, in contrast to disorders that would be addressed with health services and medical intervention.

An important preface to this topic is that many readers will themselves have experienced disordered eating that can be life-threatening and calls for medical attention. Readers who have experience with any eating disorder will know that specialist care is often needed, may be available and should be sought as soon as possible. For some readers, it may be unhelpful to read this chapter of the book, because eating disorders or difficult relationships with food could potentially be worsened by discussing the psychology of food choice outside the context of specialist care. For others, it may be helpful to see how everyday influences on food choice can be understood and addressed using economic principles.

8.1.2.1 Cognition and Psychological Constraints on Decision-Making

The term cognition refers to mental processes by which people receive information, for example about the healthiness of foods, and translate that information into understanding, knowledge and actions. Cognition is closely linked to memory and emotions and interacts with autonomous biological factors such as hormonal responses to digestive processes and blood sugar, or involuntary responses to seeing or smelling different foods that can range from mouth-watering triggers of salivation to gag reflexes and impossibility of eating. Using cognition to guide food choice is difficult and requires anticipating many aspects of how the mind and body are likely to react in each future situation.

A cognitive bias is a systematic pattern that causes someone to seek out or process information in a way that does not accurately reflect conditions around us. One important pattern is confirmation bias, by which people seek and retain information that is consistent with our prior beliefs. Confirmation bias can sometimes be helpful, by giving us a heightened ability to find things we all care about. For example, if a farmer is scouting for insect damage in their fields, they may be well served by believing insects could be anywhere and looking only for them, even if that means not seeing other things.

A related concept is motivated reasoning, in which people seek logical explanations that serve our purpose. Again, this kind of cognitive bias can be useful, for example to avoid dangers, people would want to be skilled at thinking of worst-case scenarios, and to get along with other people it can be helpful to think of charitable explanations for their actions. Cognitive biases become harmful when they become excessive, leading to tunnel vision and believing only what people want to believe, and can readily influence food choice. False beliefs about nutrition and health can easily arise by coincidence, for example due to the longevity of a person or group with a specific dietary practice, and then persist for many decades due in part to confirmation bias and motivated reasoning.

An important kind of cognitive bias that can affect food choice and health behavior is overconfidence in one’s own ability to control events. In surveys around the world, many people routinely report that they are more skilled than others at everyday tasks and understate the probability that their own mistakes could cause them harm. We can readily see how having some people with that bias could be helpful, for example as the overconfident people are willing to take risks at their own expense to do things that could potentially help others.

A different aspect of nutrition and cognition concerns cognitive function, and a person’s ability to assimilate new information and draw conclusions of any kind. The brain itself runs on nutrients and uses more total energy in proportion to its size than other organs in the body. Our cognitive ability is lower when hungry, and many other kinds of stress may limit cognitive function. One of the most frequent sentiments that Amelia hears from patients who are working on intentional weight loss is how surprised they are when eating more frequently, such as three meals and two snacks per day, helps them lose weight. One of the reasons for this is that eating frequently provides our body’s cells with the nutrients they need to function well, and it is much easier for the body to manage the use of these nutrients if they are provided frequently and regularly in a predictable manner as opposed to between episodes of voluntary dietary restriction.

Deficiencies of specific micronutrients like iodine during fetal development have well documented links to cognitive development, and entire food groups could also play a role, for example due to the diverse phytochemicals in many fruits and vegetables, and polyunsaturated fatty acids in certain nuts and seeds, oils and seafood. When the impact of individual nutrients is isolated, supplementation or fortification such as use of iodized salt can lead to improved outcomes in the long run, but in most cases the role of nutrition in cognitive function has been associated with the same overall diet quality that is tied to immune function and cardiometabolic health generally.

Beyond cognition as such, a psychological or behavioral bias is a systematic pattern that causes someone to act in a way that is not consistent with their own future preferences. The two most fundamental patterns addressed in this section are loss aversion and the resulting status-quo bias, and time inconsistency in discounting also known as present bias. Status quo bias leads people to stay with what they already have instead of an alternative, even if cognition tells us that the alternative is likely to be better. Present bias operates over time and leads us to be more concerned with the immediate future (e.g., a one-day delay from today to tomorrow) than the more distant future (a one-day delay for an event or deadline next week or next month), even if cognition tells us that the two delays would be equally valuable.

Both status quo bias and present bias are related to risk aversion in ways that are potentially useful, especially to offset limitations to one’s own cognition such as confirmation bias and motivated reasoning. Status quo bias could be useful to avoid overly optimistic assessments of alternatives to what one already has, while present bias could reflect greater uncertainty about the more distant future. Both aspects of behavior relate to cognition through the challenges of risk perception, and the difficulty of assessing risks especially when small probabilities are involved. We will return to both biases after spelling out the basic challenge of using cognition and planned behavior to improve diets for health.

The evolving scientific evidence about dietary practices that would most improve long-term health for people in the U.S. is described in the scientific report of the advisory committee convened every five years to make recommendations in the Dietary Guidelines for Americans (DGAs). Similar reviews are conducted in other countries and done for a variety of specific topics. The public version of dietary guidelines then simplifies the key messages, with a larger role for political influence, but on the major aspects of food for health all these documents deliver consistent advice based on strong scientific evidence. The central question regarding behavioral biases is why people who learn about those guidelines and seek foods that would improve their future health might not act on that knowledge.

One reason for the difficulty of following dietary guidelines could be that the high-quality scientific consensus they embody is drowned out by other messages. Interest in food and nutrition leads to exaggerated media coverage of individual studies with low validity, and frequent sharing of false beliefs that appear attractive despite having been ruled out as inconsistent with the evidence. But even if people had sufficient cognitive ability to identify accurate guidance, it would still be a challenge to ensure that people’s everyday decisions about what to eat meets their long-term goals.

To some degree, the interests of our future self are already embodied in our present self’s autonomous impulses. Human physiology evolved and arose long before cognitive skills or language, driving even a newborn infant to eat in ways that promote their future health. One such imperative is energy balance, with autonomous signals such as GLP-1 or other hormones in the brain and body triggering efforts to maintain body mass through adequate intake to replenish energy expended through metabolism and physical activity. These mechanisms evolved in the past under different conditions and create difficult challenges for nutrition behavior today, with an important biological constraint being that weight gain can occur more readily than weight loss. Episodes of weight gain can be triggered by a wide range of causes, and the body then defends its new size. Evidence from GLP-1 agonists such as semaglutide clearly demonstrates the role of autonomous, involuntary processes regulating appetite and dietary intake, and the difficulty of achieving similar results through intention alone. Obesity can therefore be seen as a change in physiology for which interventions could focus on prevention and harm reduction, requiring intentional efforts in sha** the food environment, culture and technology to help align revealed preferences and effective demand with the needs of our future selves.

A useful way to address the alignment between our present and future selves is to consider aspects of food that we all can taste and feel soon after eating, in contrast to aspects of food whose consequences are felt much later in time. In this framework, the immediate aspects of food are its hedonic attributes, derived from the Greek word for pleasure. A hedonist is a person for whom only those immediate pleasures have any meaning. Behavioral economics enters the picture because people are not purely hedonistic, but also understand that food can serve an instrumental purpose leading to better or worse outcomes for us in the future, as shown in Fig. 8.1.

Fig. 8.1

Instrumental attributes versus hedonic values in consumption

The classification in Fig. 8.1 shows how each kind of food or health behavior might have different hedonic values from most enjoyable to most unpleasant, and have different instrumental values for one’s future self from most harmful to most beneficial. In the top-left quadrant are items that are immediately enjoyable but potentially harmful in some ways. An example is hot dogs or other cured meats and salty snacks, as well as sweets and candy, alcohol and so forth. In the top-right quadrant are items that are immediately enjoyable and beneficial in the long run, such as salad and other vegetables or fruits. The bottom row is items that have negative hedonic value. Some unpleasant things are harmful, such as rancid oil, but some things that most people consider unpleasant can be beneficial. The example given here is using dental floss for oral health, which is related to dietary intake and nutritional status.

Thinking about food and nutrition in this framework can help us identify the different kinds of actions to improve different aspects of food choice and nutrition. For items in the top-left quadrant, people need guardrails and other constraints, such as eating sweets only as dessert after an otherwise supportive meal. For the top right, people need steps that make beneficial foods even more enjoyable, such as more delicious and convenient ways of eating vegetables. The bottom left usually takes care of itself, and the greatest challenges are often in the bottom right. In some cases, a technological innovation can turn a chore into a pleasure, such as the development of better-tasting toothpaste, but the long history of dental floss suggests that some desirable things are not much fun for anyone. For those needs, each person may need to use conscious effort and slow thinking to set themselves up for success each day, creating the conditions for a daily routine that builds new habits.

8.1.2.2 Indifference Curves for More Healthful vs Less Healthful Foods

We can bring both physiology and psychology into our economic analysis of food choice using indifference curves. Each person’s preferences, drawn as a set of indifference curves that trace levels of wellbeing, can shift over time due to a person’s circumstances as shown in Fig. 8.2.

Fig. 8.2

Preferences can change, and turn towards more healthful or less healthful items

The sequence of indifference curves shown from left to right in Fig. 8.2 traces William’s food preferences over time. His food choices in the 1970s and 1980s involved a delightful range of after-school snacks. Some were already known to be less healthful such as grape soda, while for other foods the difficult news came later like the nitrates in beef jerky and trans fat in the packaged pastry that William would buy from vending machines. Most of these treats were guilty pleasures kept out of his parents’ sight, and they disappeared from William’s diet once his own children were born in the 1990s. Then after 2010, when William moved to teach in the School of Nutrition at Tufts, his diet shifted even further towards the dietary guidelines that his colleagues had helped write. Some of the shift involves greater awareness about epidemiological evidence, but much is due to peer pressure and daily reinforcement. Even in that new environment, however, preferences can shift and contradict themselves, with occasional eating days that feel just like high school.

An important insight from William’s own history is that having children changed his preferences in the 1990s, making him more concerned about his own future health. At any one point in time, each person’s own long-term wellbeing may be more influential or less influential on their decision-making. One way to understand this problem is to draw the different long-term preferences that a person might have instead of their actual choices, as illustrated in Fig. 8.3.

Fig. 8.3

Differences between long-term goals and actual behavior

The two panels in Fig. 8.3 show choices for less healthful foods on the left, and more healthful foods on the right. In each case the person’s revealed preferences and actual choice are shown in a solid dark curve and observed point. Each person typically knows more than any observer about what they need, so economists typically use the preferences revealed by actual choices to infer their wellbeing. For food choice, however, researchers have discovered effects on a person’s long-term wellbeing that differ systematically from revealed preferences and observed choices. For a person’s long-term health, they would consume less of the foods with less healthful attributes on the left panel, and more foods with more health-promoting attributes on the right panel.

The analytical diagrams in Fig. 8.3 can be called a dual-self model of decision-making, comparing each person’s present self at each moment in time to their own future self some years later. In fact, each person may have multiple future selves, each consistent with different long-term goals. The dotted gray curve shows a hypothetical set of preferences that targets only health, but that is unlikely to be a real set of preferences because people also want to enjoy life and pursue a variety of other goals in addition to health. The solid gray curve shows preferences consistent with overall long-term wellbeing, with a gray dot at the point of consumption where they have no regrets and would not change their past choices.

Many foods are neutral for health so there is little or no difference between the black and gray curves, but some foods have large gaps between what people consume and what they would prefer if they took their own long-term needs into account. Actual choices are always made by the present self so the gray dot cannot be observed directly, but Section 6.2 of this book introduced how choice experiments can be used to elicit preferences between hypothetical situations. For cost-effectiveness analysis of health interventions, choice experiments involving a series of disease scenarios are used to obtain weights on different conditions when counting quality-adjusted life years (QALYs), and similar rankings are elicited from external assessments of severity for disability-adjusted life years (DALYs). Similar methods could potentially be used to elicit a person’s long-term preferences regarding the long-term health consequences of different food choices, but behavioral biases can make it difficult for people to achieve those objectives.

8.1.2.3 Predictability, Preference Reversals and Behavioral Biases

The toolkit of behavioral economics concerns systematic inconsistencies in the preferences revealed by observed choices. These inconsistences would be illustrated by indifference curves that cross each other, such as the variation in William’s preferences for less healthful versus more healthful foods shown in Fig. 8.2. Often that variation is simply random, as in the panel on the right of that figure. Other variation is systematically associated with age or other demographic characteristics, as in the way that William’s preferences changed when he had children as shown on the left of that figure. Preference reversals can also be illustrated by any set of at least three choices, for example between a piece of fruit, a glass of fruit juice or a fruit-flavored soda. Given all three options, when William was a child, he often drank juice, then as a teenager he drank a lot of fruit soda, and as an adult he almost always eats whole fruit at home but sometimes gets soda as a treat when traveling.

The preference reversals addressed in behavioral economics are not the systematic changes associated with demographic characteristics, or random and unpredictable changes, but only the preference reversals that are stable and similar enough among diverse people to be characteristic of entire populations. Populations will differ in the extent to which they experience these preference reversals, and many different variants have been identified regarding preference reversals in specific situations. These situation-specific preference reversals are often discussed in terms of a particular aspect of the circumstances in which people make each decision, generally known as framing effects or choice architecture. Then within each context, the two most common types of systematic reversals are loss aversion and status-quo bias, or myopic discounting and present bias.

Staying with the example of choosing between a piece of fruit, fruit juice and fruit-flavored soda, the impact of framing effects would be that a shop or vending machine pictures of smiling people might lead William to choose fruit, a picture of happy athletes drinking soda after exercise might lead him to choose soda, and pictures of a tropical beach holiday might lead him to choose juice. Status quo bias would be that after William has been drinking juice for a while he is unwilling to switch to whole fruit and vice versa. Present bias would be if William knows that switching to whole fruit would be more health promoting for him, but prefers to switch tomorrow instead of today, and similarly again on future days he prefers to switch tomorrow and might not actually do it for a long time. In all these cases there is a preference reversal that could lead him to regret his past choices, making it difficult to achieve long-term goals. Each specific effect is discussed below in turn.

8.1.2.4 Framing, Labeling and Choice Architecture

The circumstances under which a choice is made often influence people’s preferences in systematic ways. For example, grocery stores typically put candy and other treats near the checkout lanes, in part to increase the likelihood that customers who would not otherwise buy those items will add them to their basket after meeting their planned food needs. That is an example of choice architecture, meaning that someone (in this case the store manager) has deliberately structured the customer’s options in a way that is designed to influence their choice. Other circumstances that can influence choices include how products are labeled and the framing around them using words or visual prompts.

When stores put candy by the checkout, many of the resulting sales are due to convenience rather than preference reversals. For example, some people may want to buy candy when planned purchases turn out to have been available at low prices, so it is convenient to make that choice at the end. Other shoppers might regularly plan to buy candy even before entering the store but prefer to pick it up at the end so they can eat it on their way home. Sales involve preference reversals when customers make impulse purchases that are later regretted, or the sales involve children who demand the candy only when they see it and parents have no other way to exit the store.

If candy near the checkout causes purchases that customers later regret, we can expect that those customers would prefer to shop at a store where candy is available only on a regular shelf inside the store, perhaps on a high shelf so children are not prompted to ask for it. Such a store might attract mindful shoppers who are aware of their vulnerability, but it would consistently have lower profits than a store that exploited the opportunity to prompt impulse sales and child-driven sales by placing candy at the checkout. For that reason, the policy remedy to limit consumers’ regret is government regulation or other initiatives that help consumers buy only the things that they want.

Governments routinely regulate choice architecture for many products, allowing them to be sold but only in certain ways. The example of candy at the grocery checkout is a convenient example because it is widely observed and easily understood, but the stakes are relatively low. Impulse sales of candy are not seen as a major cause of diet-related disease, and while this aspect of store layouts is challenging for many parents it is rarely among their greatest concerns. The most important longstanding regulation of choice architecture concerns when, how and where stores can sell alcohol, tobacco and other products with large negative externalities. For food sales, the main regulations involve what can be sold in or around schools, and only recently have government policies and other interventions come to address choice architecture for everyday nutrition of adults.

Interventions in choice architecture to nudge people towards buying more healthful food sometimes concern the sequence of decisions, for example using voluntary efforts to help people plan ahead of time and buy only what they actually want. Many people still use simple shop** lists to plan their purchases, but others adopt even more structured approaches such as meal planning and food logging to track what is eaten, increase awareness and avoid purchases that they would later regret. Amelia works on this by making grocery lists, eating a satisfying meal before doing grocery shop** and taking basically the same pathway through the grocery store every visit, but she finds these behaviors are often difficult to implement depending on the week. Advance planning can sometimes be encouraged within interventions, for example when nutrition assistance uses electronic benefit transfers that can be redeemed through online purchases in a phone app or website that encourages or requires making shop** lists in advance.

Regulations of the public food environment to improve food choice have long focused on information provision, such as the nutrition facts panel on the side or back of packaged foods, or calorie counts to indicate portion sizes on restaurant menus. In recent years, regulation of packaged and restaurant food marketing has generally shifted from that kind of numerical information to warning labels and other visual indicators, as well as updates to longstanding regulation of what words can be used to describe the contents of packaged foods, with quality standards for what can be sold under each product name.

Interventions in packaged food labeling include front-of-pack and front-of-shelf symbols such as the black stop signs required by law for potentially harmful foods in Latin America, or the traffic light symbols used in Europe and elsewhere. Traffic light symbols use the visual metaphor of red for foods to stop or limit, orange for foods to consume cautiously and green for foods to consume more often. Grocery retailers may also introduce their own ratings to position themselves as a customer-friendly enterprise, for example using a system of three to five stars to signal increasing levels of healthfulness.

Rules about the marketing of packaged food have addressed the words used in marketing for centuries. The oldest laws focused on basic foods, such as Britain’s Assize of Bread to regulate its content, weight and prices introduced by King John in 1202, and Germany’s beer purity laws introduced in 1516. Modern regulations about ingredients were introduced for all U.S. packaged foods in 1906 and has been repeatedly extended to cover a wider range of potentially misleading claims. For example, in 2022 the U.S. regulators proposed an update to what foods can be sold with the term ‘healthy’ on their labels, based on more recent evidence than the criteria used when the rule was first introduced in 1994.

The adoption of both mandatory rules and voluntary approaches to signaling the healthiness of foods relies on translating nutritional information into a discrete yes/no classification, a three- or five-point scale, or similar food ratings, as well as improved clarity about words like ‘healthy’. Economists can expect that changes in dietary patterns, along with new evidence about how each food affects consumers’ future health, will continue to drive demand for policies and programs that alter food marketing and choice architecture. Those efforts aim to help consumers get what they want and intend to buy. Limiting the degree of false advertising, deceptive claims and exploitative marketing can help reduce the frequency with which consumers regret their choices, but even when people know everything about their options economists have found at least two systematic sources of preference reversals: status quo bias and present bias, explained in turn below.

8.1.2.5 Loss Aversion and Status-quo Bias

One of the most consistent patterns of preference reversal for people everywhere is the asymmetry in valuation between things we already have and alternatives we might have instead. The psychologist Daniel Kahneman was awarded the economics Nobel Prize in 2002 for his work on this kind of behavioral bias, which was called prospect theory because it refers to the systematic undervaluation of prospective gains relative to the known losses of something a person already has. The central finding of prospect theory is known as loss aversion in settings where the choice is framed as loss versus gain, and known as status quo bias in settings where the choice is framed as what is versus what could be.

Status quo bias could be an important cause of inertia in food choice and the persistence of dietary habits and has a major effect on consumers’ willingness to pay for familiar versus new products. Some people are curious and interested in experimenting, but on average people have a persistent preference for things they already have (their ‘endowments’) instead of the prospect of something else as shown in Fig. 8.4.

Fig. 8.4

Endowment effect and status-quo bias: it is hard to give up what we know

The diagram in Fig. 8.4 is designed to illustrate how information about alternatives things can influence a person’s status quo bias. The vertical axis shows the price that would be paid for two equivalent items, for example a restaurant for pizza or other things shown by icons on the right side of the diagram.

Along the horizontal axis is the person’s factual knowledge that the pizza they know is actually the same as the alternative pizza, ranging from complete uncertainty about their equivalence to near certainty that they are equally valuable at the right extreme of the horizontal axis. The two curves trace prices they are willing to pay to acquire the thing, or to accept in exchange for the thing they already have.

The solid curve traces a typical person’s willingness to pay (WTP) for the thing, rising in factual knowledge about how good it is. In the case of a restaurant meal, a person’s willingness to visit a new place might depend on whether that restaurant appears crowded or has been favorably reviewed by other people. Then after visiting the place oneself, its value depends on how reliably successful that restaurant has been in meeting the person’s needs.

The dashed curve traces a person’s willingness to accept (WTA) an alternative version of the thing, in place of the one they already have. For example, if a person lives in an environment with a certain mix of amenities including its existing pizza restaurants, the dashed line shows the compensation they would need to accept a change in that environment or a move elsewhere. A high WTA means a lot of compensation would be needed.

As knowledge increases about the actual equivalence between what a person already has and the alternative they would have instead, we can imagine how the gap between WTP and WTA shrinks. In other words, efforts at quality assurance or certification and guarantees can help people be more willing to make a switch. People are attached to the things they already have, but one reason for that is that they do not have personal experience with the alternative. Free or discounted trial periods and money-back guarantees are widely used in private-sector marketing, and other kinds of quality assurance to build trust are often needed to help people gain the confidence to try new things.

The gap between WTP and WTA is a form of asymmetric information between potential buyers and sellers, introduced in Section 7.2 to help explain why insurance is available for only certain kinds of risk. As shown there, insurance provision is sustainable only when sellers can overcome both adverse selection from hidden information (whereby only the highest-risk customers would buy insurance) and also moral hazard from hidden actions (whereby people who buy insurance then engage in riskier behavior). For physical products like food, asymmetric information limits transactions in ways known as the market for lemons, after a study by George Akerlof published in 1970. His lemons were not fruit, but the name given to automobiles whose manufacturing defects were discovered by the car’s owner only after purchase. Akerlof showed how used cars could not be sold for prices above the low value of those lemons unless the sellers could somehow prove that their car is of higher quality than the worst lemon. A similar problem arises for food products and restaurant meals, where high-quality products can be sold at a sufficient premium to cover their cost of supply only if they are able to credibly signal their actual quality.

Later studies explored the various ways that sellers can provide signals that their product is of high quality, including setting a high price accompanied by visible commitments to brand reputation such as advertising, costly packaging and expensive retail environments. Potential buyers who observe that other people are repeat customers might then trust that the product is indeed worth its high price. The high cost for any seller to signal their own quality leads to demand for trusted intermediaries who set standards and do product testing for quality assurance, either privately for a fee or in the public sector. The importance of these quality signals for all kinds of markets led to the Nobel Prize in economics being awarded to George Akerlof, Michael Spence and Joseph Stiglitz in 2001. Subsequent studies building on their work have shown how interventions can facilitate transactions that would otherwise not occur, overcoming status-quo bias through lower cost ways to trust that products we have not yet tried are in fact of high quality.

8.1.2.6 Myopic Discounting and Present Bias

Everyone has some degree of time preference, preferring that good things occur sooner and that costs are paid farther out in the future. Each person’s choices between things now and things later reveal a discount rate, which is the percentage reduction in willingness to pay for a given delay. The role of discounting was introduced in Section 6.2 for the purpose of cost-effectiveness analysis from a public-sector perspective, and it also matters for individual choices.

For example, a typical discount rate for consumption might be 5% per year, implying that the person would require 105 units of something after one year in exchange for 100 of that thing now. Higher discount rates imply greater impatience, and a willingness to accept that requires more compensation in the future for giving up something today. Lower discount rates imply less time preference, and a discount rate of zero would apply to those rare choices in which a person might be indifferent between now and later.

Discount rates are positive in part because productive activities usually offer a positive return to savings and investment. Each individual and every community has some opportunities to put resources into production and earn some return on that activity. Positive returns to investment need not be financial. For example, a farmer might be able to set aside 100 units of grain as animal feed on their own farm, and thereby obtain products worth 105 units of grain after one year. The available investments are the person’s demand for savings, and their supply of savings is their willingness to give up consumption today for more in the future, leading to the discount rate we observe.

People may apply different discount rates to different decisions, for example due to differences in uncertainty about how much they will value each thing in the future. If a person is less certain about their valuation of something in the future, they will need larger average returns to offset our risk aversion. Different people will also differ in their discount rates, and that can be an important cause of differences in health behavior. A person who is more patient, with a lower discount rate, is more willing to give up something today in exchange for greater health and longevity in the future.

Differences in discount rates are an important factor in behavior. In some cases, higher discount rates for some people or some decisions are a kind of market failure that could be remedied by improved markets for savings and investments, or other measures to address risk and risk perception. For people whose high discount rates are due to lack of confidence that their sacrifices will be worthwhile, coaching and other ways to help people become more willing to invest in their future self can be a big step towards higher wellbeing over time.

The problem of myopic discounting and present bias is not simply that people are impatient and have high discount rates, it is that the percentage discount rate is larger for delays that occur sooner. In extreme cases, a person may be very high discount rates for goods now versus later, but not much difference between different degrees of delay. Those preferences are time inconsistent, because when the future comes it will be the present. For unpleasant things that would pay off later, a person might postpone it from now until tomorrow, and then do that repeatedly over time such that the thing is never done. Myopic discounting like this is called ‘present bias’ because the person lives in an eternal present, always regretting what they did yesterday.

The usual remedy for present bias is a commitment device, whereby people realize that they have present bias and commit to doing specific plans or programs in the future. Some commitment devices involve an individual’s own actions for themselves, for example when people buy exercise equipment that they put in the living room as a way of making actual use of it more likely in the future. Both authors of this book tried that, and it worked pretty well. A more popular type of commitment device that works even better is mutual accountability in groups, where people commit to telling each other whether they accomplished their goals, thereby serving as a kind of future self for each other. The ultimate such commitment device is government laws, in which people vote to commit the whole group to some course of action.

Myopic discounting could take many mathematical forms. An extreme case of present bias would involve an infinitely high discount rate from today to tomorrow, and no further discounting thereafter. More commonly, myopia is modeled as hyperbolic discounting. This functional form has a discount rate that declines continuously with distance from now, as illustrated in Fig. 8.5.

Fig. 8.5

Exponential and hyperbolic discounting

Along the vertical axis of Fig. 8.5 is the value of something received today, for example 100 units of something. Along the horizontal axis is the distance in time from now that this value might be received. The solid line is a time-consistent discount rate, for example 5% per year, such that after each year the next year’s value is 5% lower. In contrast, the gray line is hyperbolic in functional form, discounting delays from now to next year by more than the discount from next year to the following year. Such preferences are time inconsistent, setting up the person’s future self to regret their past decisions and again seek some kind of commitment device.

8.1.2.7 Social Preferences: Altruism and Behavior in Groups

Each individual’s preferences are influenced not only by their own circumstances, but also by what they see or are told about the lives of other people. That aspect of decision-making is known as social preferences. The most fundamental of all social preferences is altruism, defined as concern for the wellbeing of others. Almost all people are observed to have a significant degree of altruism in their preferences, as elicited in a variety of experimental settings as well as analysis of observed behavior such as time, money and other resources donated or spent caring for others. Altruistic impulses differ among aspects of wellbeing, and some of humanity’s most altruistic impulses include wanting others to have adequate access to food for health.

Altruistic behavior is influenced by many factors, starting with beliefs about whether each act of generosity will actually help the recipients. Ensuring access to sufficient food is an attractive way to help others in part because everyone needs to eat, and we are often able to observe whether food is needed and how aid related to food is being used. An important limit on altruism, however, is beliefs about how giving might affect the behavior of recipients, including concern that giving aid will lead to dependency. Some forms of assistance can be harmful, so an important role for economics has been to measure how people respond to aid in the short and long run.

Donor behavior is influenced not only by beliefs about how aid affects recipients, but also by its costs and benefits for the donor. Food is sometimes used as a vehicle for assistance when donors have more of it than they want, and even those who give food regularly will vary the amount based on its scarcity. Beyond the aid itself, an important aspect of social preferences related to altruism is signaling. Any visible action conveys information to other people, and providing assistance can be a valuable signal of friendly intent and mutual respect. In some cases, the signal is used to mask other actions, as when a person or organization accused of doing harmful things attempts to deflect the accusation through conspicuous acts of generosity. In other cases, the signal is a genuine effort at social coordination, as when people try to strengthen a community by sharing food. Recognizing that actions have mixed motives can help improved outcomes, first to avoid being misled by signaling, but also to help increase the extent to which charitable food assistance meets the real needs of recipients as well as donors.

Living in groups affects behavior and shape food systems in various ways beyond altruism. A first kind of effect is due to people taking cues from each other about how best to produce and consume food. The result can be a valuable wisdom of crowds, as when farmers share their experiences, so each imitates best practices, or a dysfunctional madness of crowds, as when people respond to news by hoarding food which itself creates scarcity. The economics of group behavior is introduced in Section 6.1 on social choice, but many other important patterns discovered in social psychology and sociology can be useful in food economics. These patterns include preferences for reciprocity and equity, often following moral principles to uphold rules of behavior that are valued in themselves, beyond the consequences of any one choice. This kind of group behavior often has deep roots identified by anthropologists regarding specific communities, providing the context-specific knowledge of local conditions needed for appropriate use of economic models.

8.1.3 Conclusion

People cannot see, taste or smell the degree to which a food is needed for our future health, so we all rely on past, personal trial and error and recent scientific research to provide guidance on what dietary patterns would best meet our long-term goals. Understanding what each of us should do is limited by a variety of cognitive limitations, including confirmation bias and motivated reasoning as well as overconfidence in our own abilities, all of which make it difficult to learn and retain accurate information about how each kind of food affects our future health.

Even those of us who know all about the latest scientific consensus on food and health may find it difficult to act on that knowledge, due to a variety of behavioral biases. Loss aversion leads many people to have a strong preference for the status quo over any changes, and myopic discounting leads us to be present-biased and unable to act in our own long-term interests. Behavioral economics shows how framing, labeling and choice architecture can be used to nudge our choices towards or away from those future interests and influence the degree to which people experience regret and achieve the population’s full potential. All these factors help shape existing food systems and create opportunities for interventions to improve outcomes over time.

8.2 Interventions for Behavior Change

8.2.1 Motivation and Guiding Questions

The previous section introduced some of the many systematic factors driving food choice relating to a person’s future health, based not only on direct costs and benefits for each individual, but also on a richer understanding of human decision-making informing the field of behavioral economics. Can interventions act on that understanding to help people reach a higher level of wellbeing? What are the effects of existing policies and programs, and could they be modified to improve food choice and diet quality?

This section includes discussion of policies that alter food prices, such as trade restrictions and taxes or subsidies on production and sales. Those are important determinants of behavior for society because they affect the entire market as discussed in Chapter 6. The focus in this section is on interventions serving specific groups, often based on their risk of food insecurity or diet-related diseases to address the disparities discussed in Chapter 7. Our focus is specifically on economic interventions that provide material benefits to the recipients, including monetary assistance as well as in-kind transfers of food or credits that can be redeemed for food in local markets.

Beyond economic interventions that alter prices or provide transfers, behavior-change interventions include a range of efforts at education and communication, from mass media and advertising to school and community-based programs, meal planning and self-monitoring with mobile phone apps and connected devices, group discussions and individual counseling. Government programs in health communication typically focus on promoting adherence to national dietary guidelines, while private initiatives often advocate for other goals. Total spending on all nutrition education is a small fraction of the advertising and marketing efforts of food companies themselves but can be effective when the information or advice is actionable and meets the user’s needs.

By the end of this section, students will be able to:

• 1. Use indifference curve and budget lines to explain and predict how people might respond to nutrition assistance and other programs;

• 2. Explain how policies that aim to alter price or preferences differ from programs that transfer material assistance using cash, vouchers or in-kind aid;

• 3. Explain how the recipient’s use of their own resources to obtain additional quantities of something affects how cash assistance differs from in-kind aid or vouchers for it; and

• 4. Explain how the impact of restricting use of a voucher for something depends on whether recipients also spend some of their own resources to obtain it in additional quantities.

8.2.2 Analytical Tools

The economics toolkit is built on predicting choices and assessing outcomes using a set of models like those drawn in Chapters 2–6. Analysts use formative research and prior knowledge to choose a model specification suited to the situation, then test the model’s predictions and quantify its parameters to the extent that data are available. Some testing and parameter estimation can be done with choice experiments that reveal individual willingness to pay and marginal rates of substitution, while a whole population’s preferences can sometimes be estimated statistically using a system of equations to obtain price and income elasticities of demand.

The analytical diagrams that help us explain and predict individual choice are particularly useful to analyze potential interventions, showing the three basic mechanisms through which a policy or program could alter diet quality, as shown in Fig. 8.6.

Fig. 8.6

Interventions can alter food choice towards more healthful items

As in our other analytical diagrams for individual choice, Fig. 8.6 places the thing of interest along the horizontal axis, in this case more healthful food, and other things on the vertical axis. The first panel shows a transfer of the healthful food itself, through an in-kind gift or voucher. In this scenario the transfer cannot be used for other things, so the diagonal expenditure line shifts only to the tight. The horizontal segment at the top of the new expenditure line indicates that the transfer cannot be used for other goods and services.

The second panel of Fig. 8.6 shows an intervention that makes the healthful food easier to obtain, due to a lower market price for each unit or easier access and use of the thing once it is acquired. That can help people consume more of the healthful food by rotating the budget line outwards. This type of intervention does not increase the purchasing power for all other goods but might result in an increased consumption of other goods too besides healthful food as we saw in Chapter 2 on consumer behavior.

Finally, the third panel of Fig. 8.6 shows how behavior-change programs as well as advertising, education, and prevailing cultural narratives about food can change consumer behavior by shifting the indifference curves themselves. In practice, programs that provide vouchers or change price are often accompanied by messaging campaigns, thereby changing both purchasing power and preferences at the same time, but using these diagrams allows us to distinguish between these mechanisms using different kinds of shifts and movements along indifference curves and expenditure lines.

Figure 8.6 shows three separate interventions, but actual policies and programs often combine multiple forms of intervention as discussed in Chapter 6. Many programs that provide transfers or alter prices to improve health also provide some behavior-change communication, and empirical studies often find that each is more effective when combined with the other. Combining vouchers and price changes with information is routinely done in the private sector when retailers or manufacturers provide coupons or discounts along with their advertising. The transfer or discount attracts the beneficiary’s attention and helps them act on the information provided, while the health communication or marketing content provides a narrative that makes the desired behavior meaningful and attractive.

8.2.2.1 Impacts of Vouchers and In-kind Transfers

Programs that aim to help particular groups may transfer physical items, such as nutrition assistance through a food pantry or a school meal program, or they may use coupons or vouchers and electronic transfers to help people buy those items from market vendors. Vouchers can be pieces of paper, or electronic benefit transfers such as the debit cards used in the SNAP program today, or the mobile phone accounts used to transfer money in many low-income countries.

The way that transferring a particular thing affects peoples’ use of it is illustrated in Fig. 8.7. The first panel of this figure shows the same scenario as the previous figure, but the second panel shows what might happen if the transfer were larger: at some point, sufficiently large transfers will provide all of what the recipient would want to consume of that item. And as shown in the third panel, in that situation the recipient might be able to reach an even higher level of indifference by trading away the transferred item for other things, as shown in Fig. 8.7.

Fig. 8.7

Effect of a transfer depends on peoples’ preferences

The left-hand panel of Fig. 8.7 shows the usual situation for a program like SNAP in the U.S., which as the name implies is designed to be supplemental for most recipients. SNAP beneficiaries are given a debit card that is recharged monthly with their benefit allotment, for the purpose of buying eligible foods and beverages at any licensed grocery outlet. At each store visit the recipient might use the SNAP card to redeem their benefits or use their own cash to buy other groceries. When recipients of the transfer also use some of their own cash on the transferred items, economics jargon describes the transfer as infra-marginal, meaning that the transfer is less than the last or ‘marginal’ unit that the recipient decides to consume in that period, based on their income, preferences and the prices they face.

The middle panel of Fig. 8.7 shows the usual situation for a program like WIC in the U.S., which is designed for most recipients to provide the entire allotment of the transferred items that they should consume each month. A program of this type is designed to be extra-marginal, meaning that it provides more of the product than people might choose if they were given its value in cash. Because the program provides more of those items than they would choose for themselves, recipients who had as much additional cash as the value of the transfer would consume more other things and less of the transferred item than intended by the program.

The difference between infra-marginal and extra-marginal transfers is readily observable based on how recipients use their own money once enrolled in the program. If they buy additional quantities of what is transferred, then even an in-kind transfer is like cash because its effect is to expand the total quantity of all things that the beneficiary can acquire. Consumption of the transferred good may not increase as much as the transfer, because it leads to a higher total income and expenditure and may lead to increased consumption of other things as well as what is transferred. Only in the case of extra-marginal programs will the quantity transferred determine what is consumed.

For many assistance programs, a central concern is whether recipients will attempt to trade away what is transferred or use it for other purposes. Figure 8.7 reveals that recipients have an incentive to do so only when the transfer is extra-marginal for them. In the WIC case, converting the transferred items into other things has so little value that very few beneficiaries even bother to try, but there are situations where a voucher or in-kind transfer so far exceeds the beneficiary’s marginal choice that they would prefer cash instead. On the other hand, as shown in the left panel of Fig. 8.7, most SNAP recipients have no incentive at all to use their benefits for ineligible goods, since they want and need the groceries on which they already spend some of their own cash, so it is in their own interest to use the program as intended.

8.2.2.2 Impacts of Limiting Redemption Options

Restricting benefit redemption to discourage use of less healthful items is another widely debated aspect of nutrition programs. In the U.S., for example, SNAP benefits can be redeemed for any food and beverage item in a typical grocery store. The only prohibitions are against alcohol, dietary supplements, and hot or prepared foods for immediate consumption, although waivers to allow hot or prepared food purchases were granted to help people cope during the COVID pandemic. Public health advocates have often argued that less healthful items should be restricted as well, starting with sugar-sweetened beverages.

The effects of limiting which foods can be obtained with nutrition assistance can be shown in our food-choice diagrams by placing that food along the horizontal axis as shown in Fig. 8.8.

Fig. 8.8

Effect of restricting how transfers are used depends on peoples’ preferences

In Fig. 8.8, the vertical axis shows all other things on which program benefits can be spent, and the horizontal axis shows the items that might be prohibited such as sugar-sweetened beverages. As before, the black lines show a recipient’s situation if they had only their own money to spend, and the gray lines show their situation with the program in place. The left side panel shows recipients with two different kinds of response to the program: the solid line indifference curve is an example of a recipient whose purchases of the less healthful items might rise a little, while the dashed indifference curves show a recipient whose purchases of it would rise a lot.

The central and right-side panels show the consequences of restricting redemption for each kind of person. Since the benefit can no longer be used to increase expenditure along the horizontal axis, the expenditure line cannot continue to the right of the person’s own available funds, cutting off the gray expenditure line with a vertical segment. This is exactly analogous to the horizontal segment of the gray expenditure line shown in the previous Fig. 8.8.

The central panel shows a person who consumes sufficiently little of restricted item, with or without the restriction, that they can afford their desired quantity with only their own money. As shown in the diagram, restricting their use of the EBT has no effect on affordability. For them, the only impact of the restriction is that they must remember to use their own money for the restricted item and use the benefits for other things instead.

The panel on the right shows someone who wants to consume an ‘extra-marginal’ quantity of the restricted item. Once the restriction is imposed, they can consume only as much as they can afford using their own cash. And as before, they may be able to reach a higher indifference level by converting some of their benefits into cash to buy more of the prohibited item, whereas previously they had no incentive to do so.

The analysis of transfer programs in Figs. 8.7 and 8.8 focused only on affordability. In practice these programs attract news coverage, social media activity and behavior-change communication that could alter preferences, which would be drawn as a shift in the indifference curves. Using analytical diagrams to distinguish among kinds of effects is useful for a wide range of program design and management decisions, revealing the economic mechanisms behind many everyday behaviors in food and nutrition. The diagrams play out the consequences of human agency and choice under each scenario, allow us to describe, predict and assess the consequences of each intervention in terms of what would be in any person’s best interests.

The diagrams presented here are qualitative, meaning that they show the direction and relative magnitudes of change even when no numbers are involved, and embody abstract principles applicable to all human behavior. A great deal of additional work is required to apply these principles in any case, and to translate the results back into communication with others about what each change might feel like, but using this framework reveals underlying similarities behind situations that might seem entirely different.

8.2.3 Conclusion

Interventions that act on new information about how foods affect health can be guided by economic models, using prior knowledge of the context to identify which model specifications are most appropriate, and what parameter values such as price or income elasticities would help predict the impact of each change. These models are particularly useful when considering interventions that provide vouchers or in-kind nutrition assistance, delivered by governments or private organizations. Using these methods, economists and health scientists can work together to address market and policy failures in ways that take account of cognitive and behavioral biases, leading to improved outcomes for populations currently facing high burdens of diet-related disease.