United States

Department of

Agriculture

Economic

Research

Service 

Economic

Research

Report

Number 68

December 2008

Experiments and Lessons 

From College Students

David R. Just, Brian Wansink, Lisa Mancino, 

and Joanne Guthrie

Behavioral Economic 

Concepts To Encourage

Healthy Eating in 

School Cafeterias
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Behavioral economic concepts to encourage healthy eating in school

cafeterias : experiments and lessons from college students.

(Economic research report (United States. Dept. of Agriculture. 

Economic Research Service) ; no. 68)

1. College students—Food. 2. Food preferences—Psychological

aspects. 3. School lunchrooms, cafeterias, etc.

I. Just, David R. II. United States. Dept. of Agriculture. Economic 

Research Service.

TX361.C6

Photo credit: Comstock.

www.ers.usda.go s.usda.gov

Recommended citation format for this publication:

Just, David R., Brian Wansink, Lisa Mancino, and Joanne Guthrie. Behavioral Economic 

Concepts To Encourage Healthy Eating in School Cafeterias: Experiments and Lessons 

From College Students, ERR-68. U.S. Dept. of Agriculture, Econ. Res. Serv. December 

2008.
United States 

Department 

of Agriculture 

www.ers.usda.gov 

A Report from the Economic Research Service

Abstract

Changing small factors that influence consumer choice may lead to healthier eating 

within controlled settings, such as school cafeterias. This report describes a behavioral 

experiment in a college cafeteria to assess the effects of various payment options and 

menu selection methods on food choices. The results indicate that payment options, such 

as cash or debit cards, can significantly affect food choices. College students using a card 

that prepaid only for healthful foods made more nutritious choices than students using 

either cash or general debit cards. How and when individuals select their food can also 

influence food choices. College students who preselected their meals from a menu board 

made significantly different food choices than students who ordered their meals while 

viewing the foods in line. 

Keywords: Behavioral economics, healthy eating, diet quality, food choices, school meal 

programs, experimental economics, ERS, USDA.

Acknowledgments

The authors greatly appreciate the thoughtful review suggestions from Jay Bhattacharya, 

Stanford University School of Medicine; Karen Cullen, Baylor College of Medicine; and 

Katherine Ralston, Economic Research Service (ERS). We also thank Linda Hatcher for 

editorial expertise and layout and Susan DeGeorge for the cover design.

David R. Just, Brian Wansink, 

Lisa Mancino, and Joanne Guthrie

Behavioral Economic 

Concepts To Encourage 

Healthy Eating in School 

Cafeterias

Experiments and Lessons 

From College Students

Economic

Research

Report

Number 68

December 2008
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Contents

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Introduction: What Are the Merits of Using Behavioral 

	 Cues To Influence Food Choice? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Behavioral Studies Show That When You Choose 

Can Affect Your Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

How You Pay Can Also Influence What You Choose . . . . . . . . . . . . . . . 4

Testing Our Hypotheses: Experiment Design, Sample, and Setting . . . 6

Experimental Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

The Effect of Pre-Selection on Food Choice, 

Diet Quality, and Expenditures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

The Effect of Payment Mechanism on Food Choice, 

Diet Quality, and Expenditures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Measuring Treatment Effects: How Much of the Variation in 

	 Food Choice Is Due to Payment Effect? . . . . . . . . . . . . . . . . . . . . . . . . 16

Possible Policy Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
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Summary

Poor diet quality, overconsumption, and inactivity can lead to poor health. 

Even with the plethora of weight-loss programs and diet books currently 

available, diet-related health conditions like obesity and diabetes continue to 

rise. Traditional economic analyses seem inadequate to explain why so many 

people choose risky health behaviors. Consequently, some researchers are 

turning to behavioral economics, which tries to explain why people act as 

they do and what incentives can modify behavior. 

What Is the Issue?

Experiments have shown that the eating environment, such as the social 

atmosphere, the presence and level of distractions, or even lighting, can affect 

people’s food choices and how much they eat. Some of those same cues 

can also be used to help individuals make healthier food choices. Finding 

successful ways to promote healthier food choices could be an important tool 

for the school meals programs, for example, which aim to strike a balance 

between meeting the dietary needs of students who are undernourished and 

encouraging healthy diets and body weight. Cafeteria administrators are in 

a unique position to control many of the elements that have been shown to 

influence food choice. By understanding how these behavioral interventions 

influence food choice and diet quality, managers of school and workplace 

cafeterias can devise possible strategies to promote healthy eating. This 

report describes a behavioral experiment in a college cafeteria, which 

assessed the effects of various menu selection methods and payment options 

on food choices. The experiment was designed to apply within the context of 

any cafeteria—whether college, work, or secondary school.

What Did the Study Find?

College students who preselected their meals from a menu board before 

seeing them did not always make healthier food choices than students who 

made their selections in line where they could see the food. In fact, viewing 

led to significantly greater consumption of healthier foods—salad and turkey 

sandwiches—and significantly less consumption of less healthy foods—

French fries and caffeine. Viewing brownies, however, also significantly 

increased brownie consumption. The impact of viewing different foods may 

have more to do with how attractive they are than how healthy they are.

Students who participated in the experiment could pay for their meals in one 

of three ways—cash, prepaid cards to be used for any menu item (unrestricted 

debit cards), or prepaid cards to be used for more healthful items only 

(restricted debit cards). Their payment method affected the amount of money 

they spent on meals. Those using cash spent more on average than those who 

used an unrestricted debit card. Students using the restricted debit card spent 

the least on less nutritious items, whereas those using the unrestricted card 

spent the most on these foods.

The payment option significantly affected the types of foods chosen as well. 

College students paying with cash made healthier food choices than those 

paying with an unrestricted debit card, who were significantly more likely to 

purchase a brownie and a soda but less likely to buy skim milk and healthful 

side items and desserts. Parting with cash appeared to force more cognizant 
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decisionmaking. Students using restricted cards made significantly healthier 

choices than students paying with either cash or unrestricted cards. In many 

cases, these differences were prominent and suggest that it is possible to 

change behavior by altering payment methods used for different foods.

Students using the unrestricted debit card consumed significantly more 

calories than students using either cash or the restricted card, with those using 

the restricted card consuming the fewest calories. Not only did the number of 

calories differ by payment method, the calories derived from healthful foods 

varied as well. Although those using the unrestricted card consumed the most 

calories, they consumed the least amount of calories from more nutritious 

foods. Those using the restricted card consumed the fewest calories overall 

but consumed more calories from more nutritious foods. Students using the 

restricted card also consumed significantly less added sugar, total fat, 

saturated fat, and caffeine than those who used the unrestricted card.

How Was the Study Conducted?

This report presents results from an experiment comparing the effects of 

various behavioral intervention strategies on the food choices of college 

students. Participants in the experiment were recruited from Cornell 

University. The experiment’s participants used three types of payment 

options and two different meal selection methods.
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Introduction: What Are the Merits

of Using Behavioral Cues To

Influence Food Choice?

Consistent overconsumption, poor diet quality, and inactivity are widely 

recognized as factors that can lead to severely poor health conditions. And 

the continued popularity of weight-loss programs and diet books indicate that 

individuals are interested in improving their own health and wellness. Public 

information programs like the Dietary Guidelines for Americans and mandatory nutrition labels have also been in existence for years. Yet the incidences 

of diet-related health conditions like obesity and diabetes continue to rise. So, 

why do poor diet and lifestyle choices persist among nearly all segments of 

the population?

Traditional economic analysis that emphasizes the role of prices, income, 

and time-consistent preferences seem to inadequately explain why so 

many people choose to take on these risky health behaviors. Consequently, 

more researchers are turning to behavioral economics, which identifies 

predictable and systematic contradictions to many standard assumptions of 

economics. For example, the idea of complete rationality is challenged by 

repeated observance of cognitive biases that can lead to systematic errors in 

decisionmaking.

A growing body of research also suggests that today’s food environment is 

replete with instances in which these biases can influence dietary choice. 

Other behavioral studies show that environmental factors seem to strongly 

affect the amount of food people eat. In particular, both the eating and food 

environments affect consumption volume by setting consumption norms (an 

indication of how much people should consume) and inhibiting monitoring 

accuracy. Thus, these subtle cues can have large impacts on consumption volume, often without the individual being aware of their effect (see 

Wansink, 2006, for a complete review of the literature on consumption 

volume and the eating environment).

Behavioral studies on dietary choice also suggest that subtle changes in 

the food environment may help to leverage some of these cognitive biases 

and offer novel ways for improving diets and health (Just, Mancino, and 

Wansink, 2007). A key advantage of behavioral interventions is that, in 

theory, they can be targeted to improve food choices among individuals who 

behave contrary to their own long-term health objectives without reducing 

the welfare of individuals who feel they do make optimal choices. As such, 

these changes have the added benefit of being less paternalistic (Camerer 

et al., 2003; Sunstein and Thaler, 2003). Another advantage of leveraging 

behavioral influences is that they may require only slight modifications to 

existing programs.

To gauge the efficacy of behavioral economic tools in shaping food choices 

and eating environments, this report summarizes the results of a behavioral 

experiment designed to apply within the context of a cafeteria—college, 

work, or secondary school. For these experiments, we focus on when diners 

select their meals and how they pay for them because these elements are 

common to most cafeterias. Understanding how slight modifications to 

payment and selection methods may influence food choice and diet quality 
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can be used to augment specific policies, such as work and school wellness programs that are meant to combat obesity and promote healthy eating 

among students or employees. 

For example, knowing how changes in payment options affect food choices 

can identify specific ways to help individuals make choices that are better 

aligned with their own dietary goals and intentions. Further, by understanding how expenditures may vary with payment and selection options, 

behavioral interventions can be designed to encourage better eating without 

necessarily reducing profitability. Note, however, that this is a small-scale 

study, the results of which should not be interpreted as widely generalizable. 

Pilot studies within cafeterias would be needed to accurately assess the full 

costs, benefits, and feasibility of the interventions discussed in this study. 

In the following section, we provide some background information on the 

theory and literature used to develop our research hypotheses. (For a more 

detailed treatment of the literature on behavioral economics as it relates to 

nutrition assistance programs, see Just, Mancino, and Wansink, 2007.) We 

then describe the experiment design, sample population, and findings. We 

conclude with implications for possible policy interventions and directions 

for future research.
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Behavioral Studies Show That When You 

Choose Can Affect Your Selection

One of the most widely documented anomalies in behavioral studies is that 

individuals tend to view the tradeoff between immediate consumption and 

future consumption as having a larger impact on satisfaction than if this same 

tradeoff were between two future adjacent periods (Laibson, 2004). This 

tendency implies that individuals are more sensitive to time delays that occur 

sooner rather than later. As such, one’s willingness to make sacrifices in 

terms of limiting salt, calories, and fat for better health in the future would be 

lower if one were considering limiting salt, calories, and fat right now versus 

limiting salt, calories, and fat tomorrow.

This behavior, sometimes referred to present-biased preferences, can cause 

a rift between long-term objectives and short-term desires and, in turn, may 

lead to seemingly inconsistent choices. Other behavioral studies have found 

that specific situations and behavioral cues may further bias preferences 

towards the present. For example, certain visceral influences, like feeling 

hungry or stressed, are also associated with more seemingly impulsive 

behavior (Loewenstein, 2004; Polivy et al., 1986). Simply seeing a food can 

also lead to unplanned consumption (Boon et al., 1998; Cornell, Rodin, and 

Weingarten, 1989). Distracting environments can also exacerbate presentbiased preferences and cause individuals to make less healthful choices (Shiv 

and Fedorikhin, 1999).

Behavioral studies, however, show that individuals who commit to their 

decision before being confronted with distractions, visceral influences, or the 

promise of immediate gratification are less likely to exhibit present-biased 

preferences. These studies also show that individuals can improve their 

longrun well-being through some commitment technology, such as 401k 

plans, that set limits on current consumption levels. For example, Thaler 

and Benartzi (2004) found that savings rates increased dramatically when 

employees were offered a plan where a specified fraction of their future pay 

increases were automatically diverted into a savings account. Applying this 

finding to school or work cafeterias suggests that allowing individuals to 

precommit to healthful meal options before they consume the food likely will 

improve the healthfulness of their meal choices. 
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How You Pay Can Also Influence What You Choose

In most cafeterias, individuals have the option of using cash or some form 

of credit, debit, or prepaid card. At colleges, students typically enroll in a 

specific, prepaid meal plan, where a meal card functions as a prepaid debit 

card or entitles students to a preset number of visits. It is becoming increasingly more common for parents to prepay for meals in high, middle, and 

grade schools as well, where students receive meal cards that are used to 

debit the account when they go through the cafeteria line each day. These 

prepaid cards are also used by students receiving free and reduced-price 

meals, minimizing any appearance of differences in payment between them 

and students who are paying full price (Bland, 2004). In most systems, the 

cash that parents deposit into these prepaid accounts can be used for a la 

carte items as well as meals provided by the U.S. Department of Agriculture 

(USDA), although some systems offer parents the opportunity to prohibit a la 

carte purchases. Students still have the option of paying cash.

This choice of using a prepaid card or cash presents individuals with two 

different payment options. While both are denominated in dollars, cash not 

spent on cafeteria meals can be spent on other items either immediately or 

sometime in the future. Alternatively, money on the prepaid account can 

be used only on food, until some date in the future when excess money is 

returned. Because the use of prepaid dollars is limited (both by time and 

choice), these dollars have less value to the consumer than cash in their 

pockets that can be used for anything at any time. Thus, putting $20 on a 

prepaid account may lead to greater food consumption than $20 in cash. This 

discount effect suggests that, compared with cash, prepayment cards may 

lead to greater spending on food and, thus, greater consumption volume. 

Prepayment is also a form of commitment device. Findings from the behavioral and experimental economics literature indicate that allowing individuals 

to prepay for certain items may also tighten the link between intentions and 

behaviors. Contrary to standard economic models, individuals exhibit a 

“flat-rate bias,” where they undervalue fixed costs, relative to variable costs 

(Thaler, 2004). For example, health club members typically choose to pay for 

their gym membership on a monthly or annual basis, even when a per use fee 

would have lower total costs (DellaVigna and Malmendier, 2002).

An implication of a flat-rate bias is that, when only certain items can be 

selected using prepayment, those items will be chosen with greater frequency 

compared with items that can be purchased only with cash. Thus, if only the 

more healthful menu items can be selected using prepayment, then 

individuals using this prepayment method would be more likely to make 

significantly healthier food choices. 

Behavioral studies show that individuals also tend to categorize their income 

into mental accounts, earmarking it for specific purposes or specifying that it 

be used within a certain timeframe (Thaler, 1980; Shefrin and Thaler, 2004). 

Mental accounting suggests that a prepaid card for only healthful menu items 

may also provide cues about how much money should be spent on healthful 

items. As such, the combined effect of flat-rate biases and mental accounting 

should increase the healthfulness of meals chosen by students who have 

prepaid for healthful menu items. 
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Another implication of a flat-rate bias is that, because of these different levels 

of valuation, if one has prepaid into a flexible lunch account, he or she is likely 

to be less sensitive to variations in price compared with students who pay with 

cash. Thus, prepayment can reduce awareness of the cost of foods, creating less 

discriminating consumers. If all foods in a school cafeteria are available for 

purchase on this account, people should behave differently, being more willing 

to spend extra money on unnecessary foods or to buy more food, in terms of 

portion sizes or variety, because prepaid funds are less fungible.

Finally, prepayment for all items may increase sensitivity to environmental 

factors by reducing the general level of cognition and encouraging impulse 

buying. Thus, students using an unrestricted prepaid card likely will spend 

more money on “frivolous” items compared with students using cash or 

restricted debit cards.
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Testing Our Hypotheses: Experiment 

Design, Sample, and Setting

Observations from behavioral economic literature on the relationship among 

food choices, the timing of these choices, and payment options suggest a 

number of hypotheses related to school meal environments. As such, the 

food choice experiments in this study were designed to test the following 

hypotheses:

• Individuals who preselect their meals from a menu board are likely to 

make healthier food choices than those who make their selection in line.

• Individuals using prepayment cards are likely to spend more on cafeteria 

meals than those who pay with cash. 

• Individuals using a restricted prepaid card will make healthier food 

choices than those using either cash or an unrestricted prepaid card.

• Individuals using an unrestricted prepaid card will spend less money on 

nutritious items than individuals using cash or restricted debit cards.

To test our hypotheses, the experiment included three types of payment 

options and two different selection methods (table 1). For selecting foods, 

individuals either chose their foods at the point of purchase or precommitted 

to a choice made beforehand from a menu. The menus used in these experiments listed the name of food and beverage choices within each category and 

their corresponding price (table 2). The three payment options were prepaid 

cards that could be used for any menu item (prepaid, unrestricted), prepaid 

cards that could be used for healthful items only (prepaid, restricted), and 

cash.

The menu items chosen for this experiment were typical of cafeteria menus 

and familiar to participants. Under each heading, we included an equal 

number of more nutritious (those with a green dot) and less nutritious 

options. Prices were taken from existing menus at Cornell University dining 

facilities and rounded to the nearest half dollar.

Participants for the experiments were recruited from Cornell University, 

primarily from an introductory business course (74.9 percent) and consisted 

Table 1

Experimental treatments

Prepaid

Unrestricted: Restricted:

All menu items Only healthful items

Treatments are eligible are eligible Cash only

Preselection: Sample size: 52 Sample size: 55 Sample size: 49

Foods are chosen 

off menu before 

consumption

Selection onsite: Sample size: 58 Sample size: 62 Sample size: 47

Foods are chosen 

in line

Source: Economic Research Service, USDA.
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mostly of freshmen business students. Of those reporting their age, 51 percent 

were ages 19 or younger. Additional participants walked on or were brought 

by other participants. A potential drawback of using a convenience sample of 

college students is that the results may not be widely generalizable to other 

population groups of interest. This drawback is especially problematic if the 

convenience sample does not regularly consume the goods or services in 

question. In this case, however, the goods in question were foods offered in 

a school cafeteria and that college students consume regularly. While college 

and high school students may behave differently in terms of social norms, it is 

not clear a priori how this would systematically affect food choices. In addition, cafeteria habits could be well ingrained by the time they reach college. 

That is, because students are used to the cafeteria context (in elementary, 

middle, and high school), they already have ingrained behavior that would 

not change much in the college context. Also, efforts were made to increase 

the realism of the study. The experimental sessions took place in a section of 

one of the dining facilities at Cornell University where the layout of the room 

and presentation of the food was closely controlled so that differences in 

behavior would not be ascribed to inadvertent changes in presentation. This 

section, which we refer to as the cafeteria, was separated from the rest of the 

eating facility by temporary walls made of opaque material.

All experimental procedures were reviewed and approved by Cornell 

University’s Institutional Review Board. Each participant was assigned to a 

prepayment treatment and asked to participate in two lunch sessions 1 week 

apart, the first sessions requiring the participant to preorder from a menu 

board without seeing the food and the second requiring them to order while 

viewing the food. A total of 191 students participated in the study—167 

participated in the first session, 156 participated in the second, which gave a 

total of 323 observed orders, where 109 were from students who participated 

in both sessions. The variation in participation allows us to discern how the 

design of the experiment may have influenced behavior. In particular, because 

those participating in both sessions always participated in the preorder condition first, this experience may have had some influence on behavior in the 

Table 2

Menu choices

Choices Item Price

Entrees Bacon cheeseburger $5.00

 l Chicken breast sandwich $5.00

 l Turkey sandwich $4.50

 Chicken fingers $4.00

Sides French fries $1.00

 l Baked potato chips $1.00

 l Salad $2.00

 Macaroni and cheese $2.50

Desserts l Peaches $1.00

 Brownie $1.50

Drinks l Skim milk $1.00

 Soda $1.00

 l Bottled water $1.50

l = More nutritious.

Source: Economic Research Service, USDA.
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second session. For example, having already tried some of the foods may have 

led one to choose based on taste recall rather than the aesthetics of the food.

A standard script was read to each group before entering the cafeteria. Each 

participant was given a combination of $20 in either prepayment money or in 

cash each time they participated. In both prepayment conditions, participants 

were given $10 on the prepaid card and $10 in cash to ensure that participants were not truly restricted in their lunch purchases. For example, a participant in the healthy card condition could have spent cash to purchase any 

combination of entrée, side, dessert, and drink. Rather, the healthy card only 

suggests a restriction by drawing attention to the tradeoffs between current 

and future consumption. In the cash condition, participants were given $20 in 

cash. To track individual purchases, all participants were given an identification card that was the size of a standard credit card.

Participants in the prepaid conditions were informed that the card would 

serve as a debit card upon which they had been given $10. They were 

informed that all cash not used that day could be kept and all money left on 

the card after the second week could be picked up at a separate location on 

campus after a specified date 2 weeks after the close of the experiment. All 

participants were informed that more money would be given for the second 

session and that balances on the debit cards would carry over. Finally, 

participants assigned to the prepayment—healthy session were given plastic 

cards (identical to standard credit cards) with circular green stickers placed 

on the nonmagnetic face. The menu they viewed had a similar green sticker 

placed next to each of the healthy items (table 2) as well as on the name 

plates placed in front of items in the cafeteria line. They were informed that 

the debit card could be used only for these items and that they could still use 

cash for other menu items.

Participants in the preselection condition were instructed to choose their food 

selections from the menu board and fill out an order card before entering the 

cafeteria. This order was then given to a researcher who would accompany 

the participant into the food line and give the order card to those preparing 

the food orders. Alternatively, when ordering from sight, participants would 

fill out the same card in line while viewing all the menu options. In this case, 

the cards were handed directly from the participant to those preparing the 

dishes. We tracked the orders of all participants and collected sociodemographic information by survey after lunch was completed.
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Experimental Results

In this section, we report the differences in food choices, calories consumed, 

nutrient intake, and total expenditures by selection method and payment 

mechanism. To measure actual consumption, each participant’s order was 

recorded. His or her plate was then weighed at the end of the meal. The 

difference between the average weight for each item and the end weight of 

each individual’s plate was then taken to be the amount consumed in grams. 

For each outcome—food choice, calories consumed, nutrient intake, and total 

expenditures—we first report the mean intake by treatment and whether the 

mean differed significantly from the other treatment(s). Summary statistics 

for the entire sample are reported in table 3. Here, more nutritious foods are 

defined as those that were included on the green-dotted menu (chicken breast 

sandwich, turkey sandwich, baked potato chips, salad, peaches, skim milk, 

and bottled water) and the less nutritious foods are those without a green dot 

(bacon cheeseburger, chicken fingers, French fries, macaroni and cheese, 

brownie, and soda).

Individuals were randomly assigned into different treatment groups, so mean 

differences should provide a meaningful measure of the treatment effect. 

Because each individual participated in both selection treatments, we can 

also measure within subject variation. However, we do not have multiple 

observations for individuals by payment method. If gender or bodyweight 

Table 3

Summary statistics—All treatments

Variable Definition and units Mean Standard deviation

Males Percent of sample 0.4829 0.5005

Weight Pounds 154.6 31.84

Body Mass Index Height/weight2 23.38 3.434

Hours since last eaten Hours 6.959 5.807

Bacon cheeseburger Percent of sample that chose menu item 0.1615 0.3686

Chicken breast sandwich Percent of sample that chose menu item 0.2671 0.4431

Turkey sandwich Percent of sample that chose menu item 0.2391 0.4344

Chicken fingers Percent of sample that chose menu item 0.1863 0.3900

Salad Percent of sample that chose menu item 0.1957 0.3973

Baked potato chips Percent of sample that chose menu item 0.2019 0.4020

Macaroni and cheese Percent of sample that chose menu item 0.1308 0.3378

French fries Percent of sample that chose menu item 0.2112 0.4088

Brownie Percent of sample that chose menu item 0.0590 0.2360

Peaches Percent of sample that chose menu item 0.2298 0.4214

Skim milk Percent of sample that chose menu item 0.1242 0.3396

Soft drink Percent of sample that chose menu item 0.2516 0.4346

Bottled water Percent of sample that chose menu item 0.4068 0.4920

Calories Calories consumed at that meal 633.3 296.0

Calories from more nutritious foods Calories from “healthy” (green-dotted) foods 276.4 232.3

Calories from less nutritious foods Calories from “unhealthy” foods 358.2 373.8

Added sugar Grams 7.138 6.937

Total fat Grams 27.23 17.03

Saturated fat Grams 7.572 6.173

Percent calories from fat Percent 37.04 20.86

Percent calories from caturated fat Percent 10.48 09.14

Sodium Milligrams 1,212 669.4

Caffeine Milligrams 10.37 17.64

Expenditures Dollars spent at that meal 6.508 2.214

Sample size 322

Source: Economic Research Service, USDA.
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are unevenly distributed within these treatments, mean comparisons may 

be misleading. For example, if more men are randomly assigned to the cash 

treatment group than to the restricted debit card group and men also eat more 

than women, the mean effect of the cash treatment would appear larger than 

it truly is. We then use propensity score matching to control for potentially 

confounding factors, such as gender and weight, to estimate the impact 

of each payment treatment on food choice, diet quality, and expenditures. 

However, table 4 shows that there were only small variations across treatment groups, so the effect of confounding factors is likely insignificant.

The Effect of Preselection on Food 

Choice, Diet Quality, and Expenditures

Preselecting foods before seeing them did not always lead to healthier 

food choices. Past studies found that precommitment mechanisms helped 

individuals assuage the effect of present-biased preferences to make decisions that were more harmonious with future well-being. However, in this 

experiment, we found that the effect of ordering in line while viewing the 

food was nuanced and not so simple as “viewing drives one to order less 

healthy foods.” In fact, viewing led to significantly greater consumption of 

salad and turkey sandwiches and significantly less consumption of French 

fries, chicken sandwiches, and caffeine. Viewing brownies increased their 

consumption significantly. Thus, viewing different foods can have a varied 

impact that may have more to do with how attractive they are than how 

healthy they are. Table 5 presents differences in average consumption for 

foods preselected while viewing a menu board and selected in line while 

viewing the food.

The Effect of Payment Mechanism on Food 

Choice, Diet Quality, and Expenditures

We find that the frequency with which certain foods are ordered significantly 

differs by payment type (table 6, figs. 1a-c). In particular, individuals using 

an unrestricted debit card are significantly more likely to purchase a brownie 

Table 4

Mean height, weight, gender, and hours since last eaten by treatment

Factors In line Menu board Cash Unrestricted card Restricted card

Males:

Mean 0.47 0.471 0.50 0.50 0.4615

Standard deviation (0.501) (0.501) (0.503) (0.502) (0.501)

Weight (pounds):

Mean 155.69 153.44 150.76 161.33 151.45

Standard deviation (32.10) (31.51) (29.25) (32.66) (32.36)

Body Mass Index:

Mean 23.41 23.34 22.78 24.29 23.00

Standard deviation (3.422) (3.448) (3.349) (3.445) (3.342)

Hours since last meal:

Mean 7.08 6.80 7.24 7.64 6.103

Standard deviation (6.038) (5.557) (5.745) (6.192) (5.421)

Sample size 167 152 95 109 117

Source: Economic Research Service, USDA.
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(about 25 percent more likely) and a soda (about 27 percent more likely) but 

less likely to buy skim milk (about 7 percent less likely) than those using 

cash. Individuals using the unrestricted card were also more likely to buy less 

healthful (though similarly priced) side items and desserts than those using 

cash. In general, a prepaid card may change an individual’s valuation of the 

dollar with respect to particular foods. However, note that very little difference is observed for entrees and both groups purchased water at about the 

same rate.

Behavior when using the restricted debit card was markedly different compared 

with behavior when using either cash or the unrestricted cards. In every 

case, except for the turkey sandwich and skim milk, green-dotted items were 

consumed significantly more under the restricted treatment. In many cases, 

these differences are prominent and suggest that it is possible to change 

behavior by altering payment methods used for different foods.

Comparing the restricted and unrestricted debit card treatments, the differences again are stark, with healthy items being consumed about twice as often 

in most cases. The restricted card cuts consumption significantly for most 

unhealthy items, the exceptions being the brownie and macaroni and cheese. 

However, these unhealthy items were seldom consumed under either treatment.

Table 5

Mean differences in consumption and expenditures by selection treatment

Within subject

differences

In line Menu board (in line–menu board)

Standard Standard Standard

Food choice Mean deviation Mean deviation Mean deviation

Bacon cheeseburger 0.1667 0.3739 0.1557 0.3637 0.0227 0.4534

Chicken breast sandwich** 0.3269 0.4706 0.2096 0.4082 0.1061 0.5133

Turkey sandwich** 0.1923 0.4114 0.2874 0.4539 -0.0758 0.5187

Chicken fingers 0.1987 0.4003 0.1737 0.3799 -0.0152 0.5240

Salad** 0.1474 0.3557 0.2395 0.4281 -0.0909 0.4532

Baked potato chips 0.2308 0.4227 0.1796 0.3850 0.0303 0.4613

Macaroni and cheese 0.1538 0.3620 0.1084 0.3119 0.0229 0.3816

French fries* 0.2500 0.4344 0.1737 0.3799 0.0455 0.4764

Brownie***,† 0.0192 0.1378 0.0958 0.2952 -0.0758 0.2930

Peaches 0.2179 0.4142 0.2395 0.4281 -0.0076 0.4004

Skim milk 0.1218 0.3281 0.1257 0.3502 0.000 0.3027

Soft drink 0.2243 0.4185 0.2754 0.4481 -0.0530 0.3771

Bottled water 0.4038 0.4922 0.4132 0.4939 0.0076 0.4539

Calories 643.99 295.44 623.23 297.04 -2.8230 258.72

Calories from more nutritious foods 282.99 239.22 270.84 225.75 14.4091 235.78

Calories from less nutritious foods 362.56 378.20 351.90 370.66 -13.8779 345.91

Percent Calories from fat 38.61 22.75 34.80 20.28 01.98 24.14

Percent calories from saturated fat 10.93 10.23 13.17 23.67 -2.87 24.90

Added sugar (grams) 6.50 6.10 7.74 7.61 -0.4918 5.6485

Total fat (grams) 26.35 17.59 26.17 16.48 1.7804 16.6218

Saturated fat (grams) 7.87 6.34 7.30 5.97 0.4212 6.7961

Sodium (milligrams) 1,246.65 704.14 1,179.98 635.25 45.7224 731.75

Caffeine (milligrams)** 9.11 16.95 11.56 18.24 -2.4688 14.8186

Expenditures (dollars) 6.14 2.40 6.41 2.03 0.00 1.6939

Sample size 156 167 132

*,**,***Mean of menu board and in-line selection differ by 10, 5, and 1 percent using within-subject variation.

†,‡Differences are significant at the 10- and 5-percent level after using the Bonferroni corrected p-values.

Source: Economic Research Service, USDA.
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Figure 1a

Variations in food choice by payment type—entrees

Mean selection rate

Source: Economic Research Service, USDA.

Cash Unrestricted debit card

0

5

10

15

20

25

30

35

40 Restricted debit card

(healthy food only)

Chicken

breast

sandwich

Turkey

sandwich

Bacon

cheeseburger

Chicken

fingers

Table 6

Differences in mean consumption and expenditures by payment method

Unrestricted Restricted

Cash card card

Standard Standard Standard

Food choice Mean deviation Mean deviation Mean deviation

Bacon cheeseburger++,^^^‡ 0.1771 0.3837 0.2364 0.4268 0.0769 0.2676

Chicken breast sandwich++,^^^† 0.2396 0.4291 0.1818 0.3875 0.3675 0.4842

Turkey sandwich^ 0.2500 0.4353 0.1818 0.4105 0.2906 0.4560

Chicken fingers+++‡,^^^‡ 0.2604 0.4412 0.2636 0.4426 0.0513 0.2215

Salad+++‡,^^^ 0.1146 0.3202 0.1455 0.3542 0.3077 0.4635

Baked potato chips+++‡,^^^† 0.0938 0.2930 0.1636 0.3716 0.3333 0.4734

Macaroni and cheese+ 0.1875 0.3924 0.1091 0.3132 0.1034 0.3059

French fries+,^^ 0.2292 0.4225 0.2727 0.4474 0.1368 0.3451

Brownie* 0.0313 0.1749 0.0909 0.2888 0.0513 0.2215

Peaches++,^^^‡ 0.1875 0.3924 0.1455 0.3542 0.3419 0.4764

Skim milk**,^^ 0.1563 0.3650 0.0545 0.2281 0.1624 0.3930

Soft drink***†,+,^^^‡ 0.2188 0.4156 0.4182 0.4955 0.1197 0.3260

Bottled water+++†,^^^ 0.3229 0.4700 0.3636 0.4832 0.5214 0.5017

Calories++,^^† 644.37 275.00 692.14 306.64 568.90 292.27

Calories from more 

nutritious foods**,+++‡,^^^‡ 248.88 198.27 192.36 222.97 377.14 230.83

Calories from less 

nutritious foods**,+++‡,^^^‡ 397.43 346.19 502.01 377.42 190.55 326.90

Added sugar (grams)***†,^^^ 6.0659 6.3776 9.0728 7.9937 6.2067 5.9092

Total fat (grams)+++ ‡,^^^‡ 30.4493 17.1860 30.0914 17.4616 21.8740 15.2179

Saturated fat (grams)+++‡,^^^ 8.8062 6.3338 8.2227 6.5460 5.9387 5.3173

Percent calories from fat+++†,^ 41.64 20.16 37.44 21.00 32.84 20.63

Percent calories from saturated fat++ 12. 23 09.15 10.42 92.13 09.08 08.88

Sodium (milligrams)*,+ 1,320.766 643.611 1,165.417 723.959 1,166.808 631.227

Caffeine (milligrams)***‡,+,^^^‡ 8.9144 16.7695 17.3058 20.1072 5.0487 13.3341

Expenditures (dollars)+,^^ $6.53 2.26 $6.33 1.96 $6.66 2.40

Sample size 96 110 117

*,**,***Mean of cash treatment and unrestricted card treatment differ by 10, 5, and 1 percent. +,++,+++Mean of cash treatment and restricted card 

treatment differ by 10, 5, and 1 percent. ^,^^,^^^ Mean of restricted and unrestricted card treatment differ by 10, 5, and 1 percent. †,‡Differences 

are significant at the 10- and 5-percent level after using the Bonferroni corrected p-values.

Source: Economic Research Service, USDA.
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The differences among food choices, by payment treatment, also led to 

significant differences in diet quality. In terms of calories, those using the 

unrestricted debit card consumed significantly more calories than either 

the cash or restricted treatment groups, with those using the restricted card 

consuming the fewest calories at that meal. Not only did the total number of 

calories differ by payment method, the calories derived from healthful foods 

varied as well (fig. 2). Although those using the unrestricted card consumed 

the most calories at lunch, they got the fewest calories from more nutritious 

foods. In comparison, those using the restricted card consumed the fewest 

calories overall but consumed more calories from more nutritious foods. 

Compared with the individuals who used the unrestricted card, those using 

the restricted card also consumed significantly less added sugar, total fat, 

saturated fat, and caffeine.

Figure 1b

Variations in food choice by payment type—sides

Mean selection rate

Source: Economic Research Service, USDA.

Cash Unrestricted debit card Restricted debit card

(healthy food only)

0

5

10

15

20

25

30

35

Salad Baked

potato

chips

Macaroni

and

cheese

French

fries

Figure 1c

Variations in food choice by payment type—desserts and sides

Mean selection rate

Source: Economic Research Service, USDA.

Cash Unrestricted debit card Restricted debit card

(healthy food only)

0

10

20

30

40

50

60

Brownie Peaches Skim milk Soft drink Water
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Our results show no greater spending when using unrestricted prepaid cards 

compared with using cash. In fact, individuals using cash spent more on 

average than those who used an unrestricted prepaid card (fig. 3). However, 

individuals using the restricted card spent the least on unhealthy items, 

whereas those using the unrestricted card spent the most on these foods. The 

maximum amount spent was $16.50, with an average of $6.51. In fact, only 

one participant from the combined cash and restricted card experiment spent 

more than the $10 given in cash. Thus, only this participant could have been 

constrained in his or her choice by the funds given. The average amount 

spent in either card treatment was $6.51, and less than 1 percent of individuals spent all of their money on the card in a single lunch.

Figure 2

Differences in caloric intake by payment type

Mean calories

Source: Economic Research Service, USDA.

Cash Unrestricted

debit

card

Calories

from less

nutritious

foods

Calories

from more

nutritious

0 foods

100

200

300

400

500

600

700

Restricted

debit card

(healthy

food only)

Figure 3

Differences in spending by payment type

Mean dollars

Source: Economic Research Service, USDA.

Cash Unrestricted

debit

card

Spending

on less

nutritious

foods

Spending

on more

nutritious

foods

Restricted

debit card

(healthy

food only)

0

1

2

3

4

5

6

7
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Figure 4 displays the cumulative distribution of spending by the three 

different payment methods. Comparing those using cash to those using the 

unrestricted debit card, the distributions are nearly identical, except that no 

one using the card spent above $10. One explanation for this result could 

be that the amount on the card suggested a limit on spending that would not 

otherwise exist, curbing the consumption of those on the upper tail. In fact, 

no individual spent any cash when given an unrestricted debit card. However, 

little weight should be placed on differences in the tails of distributions, and 

further tests would be needed to determine whether this result is robust to 

altered levels of card endowments.

When faced with the restricted debit card, individuals spent an average of 13 

cents more than they did when using cash. Unlike the unrestricted treatment, 

here we observe that the spending distribution for the restricted treatment 

diverges from the cash treatment, with more mass placed on the tails of the 

distribution. Again, we note that individuals using the card tended not to 

spend more than $10. In this case, the effect is clearly due to the spending 

norm suggested by the amount on the debit card. Most participants spent 

some cash in addition to the money spent on a debit card (on average $1.04).

Figure 4

Cumulative distribution of spending for cash and debit card treatments

Percent

Source: Economic Research Service, USDA.

0

20

40

60

80

100

0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00

Cash

Card

Restricted

Cash

Dollars spent
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Measuring Treatment Effects:

How Much of the Variation in Food 

Choice Is Due to Payment Effect?

Testing for differences in mean values among payment and preselection 

options suggests that these treatments do correlate with different food 

choices. However, it is important to recognize that other factors, such as an 

individual’s gender, Body Mass Index (BMI), or how long he or she had 

gone between meals, may also affect his or her food choices. Thus, for a 

more precise measure of the effect of each treatment, we use propensity 

matching scores to estimate how much expenditures and nutrient intake 

respond to each treatment, while holding these factors constant. In particular, 

we use the matching estimation procedure developed by Abadie, Drukker, 

Herr, Imbens (2004), which matches outcomes between treated observations to those in the control based on a vector of independent variables. 

Matches are determined by minimizing Euclidean distance, and a sample of 

nearest matches are drawn for estimation of the treatment effect. See Abadie, 

Drukker, Herr, and Imbens (2001) for details.

After controlling for these factors, we still find that our results hold (table 7). 

Namely, individuals using the unrestricted card consumed 95 more calories, 2 more grams of added sugars, 7 more grams of fat, 2 more grams of 

saturated fat, and 11 more milligrams of caffeine than individuals using the 

restricted debit card. Over time, these seemingly small differences could lead 

to substantial changes in diet quality, body weight, and health.

Table 7

Mean effect controlling for Body Mass Index, gender, and hours since last meal

Cash Cash Unrestricted

versus versus versus

unrestricted restricted restricted

Standard Standard Standard

Item Mean deviation Mean deviation Mean deviation

Calories 21.3002 52.3336 76.45016* 45.34302 94.4898** 48.8895

Calories from more nutritious foods 102.0725***‡ 34.5758 86.6949** 35.8072 198.0445***‡ 34.7789

Calories from less nutritious foods 123.1275** 56.9196 170.5736***‡ 52.2125 294.8636***‡ 54.7064

Added sugar 2.9611** 1.3731 0.3440 0.9638 2.2396* 1.2265

Total fat 2.3344 2.9570 8.4740***‡ 2.6522 6.8768***† 2.5082

Saturated fat 1.1275 1.1311 2.9113***‡ 0.9678 2.0220** 0.9455

Percent calories from fat 7.01* 4.02 9.82***† 3.56 6.38** 3.15

Percent calories from saturated fat 3.02* 1.86 3.77** 1.59 2.28* 1.41

Sodium 259.931** 124.093 193.369* 104.652 37.9986 105.659

Caffeine 9.6243***‡ 3.1801 4.3701* 2.3337 11.7405***‡ 3.0359

Expenditures 0.5038 0.4112 0.2252 0.3718 0.3853 0.3771

*,**,***Treatments differ by 10, 5, and 1 percent.

†, ‡Differences are significant at the 10- and 5-percent level after using the Bonferroni corrected p-values.
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Possible Policy Implications

While this study is on a small scale and the results should not be interpreted 

as widely generalizable, the results may have implications for environmental strategies for obesity protection. In particular schools may find these 

concepts useful as they strive to design wellness policies that would promote 

healthful food choices by students.

Schools participating in the National School Lunch Program (NSLP) receive 

cash and some commodities from USDA. In return, these schools provide 

free or reduced-price lunches to needy school children whose families meet 

the income cutoffs. National food consumption survey data indicate that 

many children choose foods high in saturated fat, sodium, and added sugars 

at the expense of fruits, vegetables, low-fat milk, and whole grains (Lin et al., 

2001). In response, today’s NSLP seeks to promote both adequate intake of 

healthful foods and limits on high-calorie, low-nutrient foods. Meals sold as 

part of the NSLP must meet Federal dietary standards, which include limits 

on fat and saturated fat (Oliveira, 2006; for a detailed account of the history, 

trends, and objectives of the NSLP, see Ralston et al., 2007).

However, most American schools choose to sell at least some foods and 

beverages that are not a part of the USDA school meal program (O’Toole 

et al., 2007). These foods and beverages are often labeled “competitive 

foods” because they compete with NSLP meals and have been criticized as 

being frequently high in calories, saturated fat, sodium, or sugars (O’Toole 

et al., 2007). A 2005 study of U.S. public schools found that, although less 

than half of all public schools have vending machines, nearly 80 percent of 

schools offer a la carte foods (Finkelstein, Hill, and Whitaker, 2008). This 

study also found that school food environments are less healthy among children in higher grade levels and that most secondary schools offer less nutritious foods through a la carte and vending machines sales. Competition with 

less nutritious options may result in decreased consumption of the healthier 

choices provided through USDA meals. The School Nutrition Dietary 

Assessment Study-III (SNDA-III) found that, although USDA school meals 

provided to all grade levels regularly include fruit or juice, only 32 percent of 

high school student participants reported consuming fruit at lunch compared 

with 55 percent of elementary school participants (Gordon et al., 2007).

To address current concerns about high-calorie, low-nutrient foods being sold 

in American schools, the Child Nutrition and WIC (Special Supplemental 

Nutrition Program for Women, Infants, and Children) Reauthorization Act of 

2004 (Public Law 108-265) required that every school district participating 

in the NSLP, as of school year 2006-07, have a local school wellness policy. 

It is intended to be a tool to address obesity and promote healthy eating and 

physical activity through changes in school environments. Each district’s 

wellness policy must provide assurances that school meals meet Federal 

guidelines; provide nutrition guidelines for all foods available at school; and 

specify goals for nutrition education, physical activity, and other school-based 

wellness activities. However, districts have flexibility as to the specific policies 

and guidelines they develop.

Suggested strategies for improving the choices of foods and beverages made 

by children and adolescents at school have included nutrition education, 
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restricting sales of some items, or manipulating prices of a la carte items to 

encourage healthful choices (Story et al., 2006). While such intervention 

policies have been shown to influence food choice, psychological and behavioral tools may be as equally effective as these more traditional interventions 

(Just, Mancino, and Wansink, 2007).

Our research findings suggest that allowing individuals, or in the case of 

younger school-aged children, their parents, to prepay for a restricted set 

of approved foods may result in increased consumption of healthful foods. 

Depending on the infrastructure of the cafeteria, offering a restricted card 

along with an unrestricted card may be possible. How closely the results 

of this experiment resemble those in an actual cafeteria setting will depend 

heavily on how well individuals understand the debit card system and its 

potential impacts on diet quality.

It may also be important to evaluate which foods should be displayed when 

ordering and which should be hidden until after ordering has taken place. 

This choice should be based on the visual appeal of the items and their 

nutritional content. Thus, it may be useful for cafeterias to monitor the 

specific reactions to the foods they consider placing prominently. This effect 

can be fine tuned by tracking how sales of each item change with changes in 

product placement.

A key advantage of leveraging behavioral influences is that they may only 

require slight modifications to existing programs. Also, administrators of 

school food services are in a unique position to control many of the elements 

that have been shown to influence food choice, such as the order and way 

in which foods are presented, when they can be selected, and the actual 

eating environment. Results of this experiment suggest that placing limitations on items that can be purchased with prepaid debit cards improves the 

healthfulness of food choices. An advantage of such a system is that it could 

allow parents significant control over their child’s purchases, without necessarily decreasing overall choice within a school. However, the interventions 

discussed in this study may be better suited for middle and high school meal 

programs. And of course, pilot studies within school cafeterias would be 

needed to accurately assess the full costs, benefits, and feasibility of these 

interventions.
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References

Abadie, Alberto, David Drukker, Jane Leber Herr, and Guido W. Imbens. 

2004. “Implementing Matching Estimators for Average Treatment Effects in 

Stata,” The Stata Journal 4(3):290-311, StataCorp LP.

Abadie, Alberto, David Drukker, Jane Leber Herr, Guido W. Imbens. 2001. 

“Implementing Matching Estimators for Average Treatment Effects in 

Stata,” The Stata Journal 1(1):1-18, StataCorp LP.

Bland, Karina. 2004. “Kids Using Debit Cards to Pay For School Lunch,” 

The Arizona Republic, August 30, 2004, accessed at https://www.

mylunchmoney.com/azcentral.htm

Boon, B., W. Stroebe, H. Schut, and A. Jansen. 1998. “Food for Thought: 

Cognitive Regulation of Food Intake,” British Journal of Health Psychology

3(1):27-40.

Camerer, Colin, Samuel Issacharoff, George Loewenstein, Ted O’Donoghue, 

and Matthew Rabin. 2003. “Regulation for Conservatives: Behavioral 

Economics and the Case of ‘Asymmetric Paternalism,’” University of 

Pennsylvania Law Review 151(3):1211-54.

Cornell, C.E., J. Rodin, and H. Weingarten. 1989. “Stimulus-Induced Eating 

When Satiated,” Physiology and Behavior 45(4):695-704.

DellaVigna, S., and U. Malmendier 2002. “Overestimating Self-Control: 

Evidence from the Health Club Industry,” mimeo, University of California, 

Berkeley.

Finkelstein, Daniel, Elaine Hill, and Robert Whitaker. 2008. “School Food 

Environments and Policies in U.S. Public Schools,” Pediatrics 122(1):

e251-e259.

Gordon, Anne, Mary Kay Fox, Melissa Clark, Renee Nogales, Elizabeth 

Condon, Philip Gleason, Ankur Sarin. 2007. School Nutrition Dietary 

Assessment-III: Vol. II: Student Participation and Dietary Intakes, prepared 

for U.S. Department of Agriculture, Food and Nutrition Service, Office 

of Research, Nutrition, and Analysis, Project Officer: Patricia McKinney, 

November.

Just, David, Lisa Mancino, and Brian Wansink. 2007. Could Behavioral 

Economics Help Improve Diet Quality for Nutrition Assistance Program 

Participants? Economic Research Report No. 43, U.S. Department of 

Agriculture, Economic Research Service, June.

Laibson, David. 2004. “Golden Eggs and Hyperbolic Discounting,” in 

Advances in Behavioral Economics, Colin F. Camerer, George Loewenstein, 

and Matthew Rabin (eds.), Russell Sage Foundation, Princeton, NJ: 

Princeton University Press, pp. 429-57.

Lin, Biing-Hwan, Joanne Guthrie, and Elizabeth Frazao. 2001. “American 

Children’s Diets Not Making the Grade,” FoodReview 24(2):8-17, U.S. 

Department of Agriculture, Economic Research Service.
20

Behavioral Economic Concepts To Encourage Healthy Eating in School Cafeterias: Experiments and Lessons From College Students / ERR-68

Economic Research Service / USDA

Loewenstein, George. 2004.“Out of Control: Visceral Influences on 

Behavior,” in Advances in Behavioral Economics, Colin F. Camerer, George 

Loewenstein, and Matthew Rabin (eds.), Russell Sage Foundation, Princeton, 

NJ: Princeton University Press, pp. 689-724.

Oliveira, Victor. 2006. The Food Assistance Landscape: FY 2006 Midyear 

Report, Economic Information Bulletin No. 6-3, U.S. Department of 

Agriculture, Economic Research Service, September.

O’Toole, Terrance P., Susan Anderson, Clare Miller, and Joanne Guthrie. 

2007. “Nutrition Services and Foods and Beverages Available at School: 

Results from the School Health Policies and Programs Study 2006,” Journal 

of School Health 77(8):500-21.

Polivy, J., C.P. Herman, R. Hackett, and I. Kuleshnyk. 1986. “The Effects of 

Self-Attention and Public Attention on Eating in Restrained and Unrestrained 

Subjects,” Journal of Personality and Social Psychology 50(6):1253-60.

Ralston, Katherine, Constance Newman, Annette Clauson, Joanne Guthrie, 

and Jean Buzby. 2007. The National School Lunch Program: Background, 

Trends, and Issues, Economic Research Report No. 61, U.S. Department of 

Agriculture, Economic Research Service, July. 

Shefrin, Hersh M., and Richard H. Thaler. 2004. “Mental Accounting, 

Saving and Self Control,” in Advances in Behavioral Economics, Colin F. 

Camerer, George Loewenstein, and Matthew Rabin (eds.), Russell Sage 

Foundation, Princeton, NJ: Princeton University Press, pp. 395-428.

Shiv, B., and A. Fedorikhin. 1999. “Heart and Mind in Conflict: Interplay of 

Affect and Cognition in Consumer Decision Making,” Journal of Consumer 

Research 26(3):278-92.

Story, Mary, Karen M. Kaphingst, and Simone French. 2006. “The Role 

of Schools in Obesity Prevention,” The Future of Children 16(1):109-42, 

accessed at http://www.futureof children.org.

Sunstein, Cass, and Richard Thaler. 2003. “Libertarian Paternalism Is Not an 

Oxymoron,” University of Chicago Law Review 70(4):1159-202.

Thaler, Richard H. 1980. “Towards a Positive Theory of Consumer Choice.” 

Journal of Economic Behavior and Organization 1:39-60.

Thaler, Richard H. 2004. “Mental Accounting Matters,” in Advances in 

Behavioral Economics, Colin F. Camerer, George Loewenstein, and Matthew 

Rabin (eds.), Russell Sage Foundation, Princeton, NJ: Princeton University 

Press, pp. 74-103.

Thaler, Richard H., and Shlomo Benartzi. 2004. “Save More Tomorrow 

(TM): Using Behavioral Economics To Increase Employee Saving,” Journal 

of Political Economy 112(S1):S164-S187, University of Chicago Press, 

February.
21

Behavioral Economic Concepts To Encourage Healthy Eating in School Cafeterias: Experiments and Lessons From College Students / ERR-68

Economic Research Service / USDA

U.S. Department of Agriculture, Food and Nutrition Service. 2007. USDA 

Web site accessed at http://www.fns.usda.gov/fsp/rules/Legislation/history.

htm on January 10, 2007.

Wansink, B. 2006. Mindless Eating: Why We Eat More Than We Think, New 

York: Bantam Dell.