Abstract

This study develops a framework for differentiating true Food Stamp Program (FSP) impacts on food security from

those that arise because households with the most severe food-related hardships are more likely to participate in the

program. The framework hypothesizes that food spending improvements are the likely causal link between FSP

participation and enhanced food security. Since food stamp benefits diminish with income, the incremental effect of

FSP participation is also expected to diminish. Using data from the Current Population Survey Food Security

Supplements in a statistical framework that controls for household income, the study finds that FSP participants

have consistently higher at-home food spending and lower away-from-home-spending than comparable nonparticipants. For both groups, food security rises with income, but food security remains lower for program participants.

Because differences in food spending and food security do not disappear as income rises, the study concludes that

observed disparities are not likely to be true program impacts.

Household Food Security and

Tradeoffs in the Food Budget of

Food Stamp Program Participants

An Engel Function Approach

Contractor and Cooperator Report No. 38

March 2008

By Parke E. Wilde, Lisa M. Troy, and Beatrice L. Rogers, Tufts University

This study was conducted by Tufts University under a cooperative research

contract with USDA’s Economic Research Service (ERS) Food and Nutrition

Assistance Research Program (FANRP): contract number 43-3AEM-5-80088

(ERS project representative: Margaret Andrews). The views expressed are

those of the authors and not necessarily those of ERS or USDA.
Acknowledgments

This report benefited from excellent research assistance by Nyssa Schloyer Ackerley, 

project management by Anne Marie Golla and Margaret Andrews at USDA’s Economic 

Research Service (ERS), and comments and suggestions from Ted Macaluso at USDA’s 

Food and Nutrition Service (FNS) and from colleagues who attended presentations at 

ERS, the annual meeting of the American Agricultural Economics Association, and the 

Experimental Biology conference. The research was supported by the Food Assistance 

and Nutrition Research Program (FANRP) at ERS (Agreement Number 43-3AEM-5-

80088). All errors are the responsibility of the authors. 

Contact: 

Parke E. Wilde, Ph.D. 

Friedman School of Nutrition Science and Policy 

150 Harrison Ave. 

Boston, MA 02111 

617-636-3495 (tel) 

617-636-3781 (fax) 

parke.wilde@tufts.edu (email) 

ii
Contents 

Report Summary.............................................................................................................. iv 

I. Introduction .................................................................................................................. 1 

II. Background ................................................................................................................. 4 

III. Literature ................................................................................................................... 5 

IV. Theory......................................................................................................................... 9 

V. Data and Methods..................................................................................................... 15 

VI. Results: Preliminary Analysis of Household Budgets.......................................... 20 

VII. Results: Main Engel Responses for Four Categories of Outcomes. .................. 21 

VIII. Results: Food Stamps, Food Spending, and Food Security Jointly ................. 27 

IX. Discussion................................................................................................................. 28 

Sources............................................................................................................................. 31 

iii
Report Summary 

Using data from the federal government’s household food security survey, this study 

charted how increased income and FSP participation are associated with changes in food 

spending and food security outcomes. The analysis distinguished two possible 

contributions of food stamp benefits: increasing the household’s total resources and 

influencing the allocation of those limited resources in the direction of food goods. 

What Is the Issue?

Household food insecurity and hunger are important social concerns in the United States. 

The Economic Research Service reported that 10.9% of U.S. households had “low food 

security” status in 2006, based on self-reports of food-related hardship at some point 

during the year. This estimate included 4.0% that experienced “very low food security,” 

a more serious condition that is commonly accompanied by self-reports of hunger for 

some household members. 

In response to these social concerns, the U.S. Department of Agriculture (USDA) seeks 

to reduce and prevent food insecurity through improved access to federal nutritionassistance programs. The Food Stamp Program (FSP), the largest nutrition-assistance 

program, served 26 million people on average each month in 2005, providing $29 billion 

in targeted food benefits. 

 

Analysts have tried a wide variety of research designs to measure the effects of the FSP, 

but such research faces serious challenges. The difficulty is that households with more 

severe food-related hardships are more likely to participate in the program, so one cannot 

easily use participant / nonparticipant differences to identify true program effects. 

This study introduces two features that hold some promise for improving our ability to 

measure program effects: (a) it offers a modification to the traditional theory of consumer 

choice subject to a targeted benefit such as food stamps, highlighting differences in the 

empirical implications of true program effects and self-selection patterns, and (b) it 

estimates Engel functions separately for food that can be purchased with FSP benefits (athome food) and restaurant food that cannot be purchased with FSP benefits (away-fromhome food). 

What Did the Study Find?

At-home food spending (such as grocery spending) in a recent week was higher for FSP 

participants than for nonparticipants, even after controlling for total income. By contrast, 

away-from-home food spending (such as restaurant spending) in a recent week was lower 

for FSP participants than for nonparticipants. These results are what one would expect if 

food stamps enhanced households’ at-home food spending, making it less necessary for 

them to purchase food from restaurants. 

iv
Despite the raised at-home food spending in a recent week, participants perceived a 

modestly greater shortfall in their food budget than did nonparticipants, even after 

controlling for total income. Participants generally perceived slightly higher food needs 

on average, while they had little increase in “usual” food spending, perhaps because the 

increased spending for at-home food and the decreased spending for away-from-home 

food nearly cancelled each other out. This result suggests that, even after receiving FSP 

benefits, participants continue to perceive difficulty acquiring sufficient food resources. 

FSP participants had much higher rates of food insecurity compared with nonparticipants 

at the same levels of total income, presumably due to a self-selection pattern in which 

those households with greater hardship were more likely to seek program benefits for 

which they were eligible. While the national rate of “low or very low food security” 

among all U.S. households was about 11% in 2005, the comparable rates for FSP 

participants with the lowest levels of total income reached higher than 55% for all three 

household types in this study. 

A key hypothesis motivating this study was that the very poorest FSP participants, in 

terms of total income, would be most constrained in their household budget, and hence 

they would benefit from raised levels of at-home food spending supported by the 

maximum food stamp benefit, perhaps leading to lower rates of household food 

insecurity. This hypothesis could not be confirmed in this analysis. Instead, rates of food 

insecurity for low-income FSP participants are very high, reflecting serious hardship for 

the participant group. This self-selection pattern, in which households that experience 

hardship are more likely to participate in the Food Stamp Program, made it difficult to 

determine true program effects from the data and research design used in this analysis. 

High rates of food insecurity for low-income participant households were noted 

regardless of whether these households had above-average or below-average at-home 

food spending. Holding constant total resources, having above-average at-home food 

spending might nevertheless contribute to other food-related goals, such as improved diet 

quality, that were beyond the scope of this study. For most household types and total 

income levels, having above-median at-home food spending did not appear to suffice on 

its own to produce improved household food security. 

In conclusion, FSP participation is associated with suppressed away-from-home food 

spending and with enhanced at-home food spending. Yet, these higher at-home food 

spending levels do not automatically imply improved food security outcomes. Crosssectional comparisons of food security outcomes for participants and nonparticipants are 

dominated by self-selection effects. Holding constant total income, rates of food 

insecurity remain higher for program participants than for nonparticipants. 

How Was the Study Conducted? 

This study treated food spending as the main vehicle by which food stamp benefits 

influence household food security. It resuscitated, with modifications, the traditional 

economic theory of consumer choice between food and nonfood goods subject to a 

v
targeted food benefit such as food stamps. This traditional theory relies on a distinction 

between unconstrained (or inframarginal) households and constrained (or extramarginal) 

households. According to the theory, additional food stamp benefits should have a 

modest effect in raising food spending for unconstrained households and a large effect in 

raising food spending for constrained households. 

This theory, which dates to the 1940s, has in recent years not been accepted as the basis 

for research about the Food Stamp Program, because empirical evidence appeared to 

contradict one of its predictions (Fraker, 1990; Wilde and Andrews, 2000). Specifically, 

the evidence suggested that additional food stamp benefits had a comparatively large 

effect on food spending even for households that appeared to be unconstrained. This 

study therefore pursued a modified version of the traditional theory, in which the 

difference between constrained and unconstrained households is not a sharp binary 

distinction but rather a matter of degree. 

The study addressed two food spending outcomes and two food security outcomes. The 

food spending outcomes were: 

A. At-home food spending. Food spending in supermarkets, grocery stores, and 

convenience stores. 

B. Away-from-home food spending. Food spending in restaurants and 

cafeterias. 

The food security outcomes were: 

C. The self-perceived food spending gap. The difference between usual food 

spending and self-reported food spending needs. A positive gap indicates 

adequate food spending, while a negative gap indicates a self-perceived shortfall 

in food spending. 

D. Household food security. Based on responses to multiple food security 

survey items, USDA classifies households as being “food secure” or “food 

insecure.” Within the food insecure category, there are sub-categories for “low 

food security” and “very low food security.” The food security outcomes studied 

here include these food security status indicators and also the response 

frequencies for selected individual food security survey items. 

For each of these outcomes, there were three types of research questions: 

1. Response to total income. In an analysis conducted separately for FSP 

participants and nonparticipants, how does the outcome respond to increasing 

levels of total income (cash income plus any food stamp benefits)? 

vi
vii

2. Response to program participation status. In comparisons of households at 

the same level of total income, how does the outcome differ for FSP participants 

and nonparticipants? 

3. Distinguishing the program effect. In light of the (modified) theory of 

economic choice between food and nonfood goods, do the results appear more 

consistent with self-selection patterns, more consistent with true program effects, 

or does the direction of causation remain indeterminate? 

Data analyzed for this report come from the food security supplement to the Current 

Population Survey (CPS). The food security supplements contain approximately 55,000 

household observations per year. The U.S. Census Bureau collects labor market 

information on behalf of the Bureau of Labor Statistics (BLS) each month through the 

CPS. The Census Bureau also collects food spending and food security data on behalf of 

USDA in December only through the food security supplement. In this study, food 

security supplement data for December of 2001 to 2005 were combined. 

I. Introduction

Household food insecurity and hunger are important social concerns in the United States. 

The Economic Research Service reported that 10.9% of U.S. households had “low food 

security” status in 2006, based on self-reports of food-related hardship at some point 

during the year (Nord, Andrews, and Carlson, 2007). This estimate included 4.0% that 

experienced “very low food security,” a more serious condition that is commonly 

accompanied by self-reports of hunger for some household members.1

In response to these social concerns, the U.S. Department of Agriculture (USDA) seeks 

to reduce and prevent food insecurity through improved access to federal nutritionassistance programs (USDA, 2006). The Food Stamp Program (FSP), the largest 

nutrition-assistance program, served 26 million people on average each month in 2005, 

providing $29 billion in targeted food benefits (USDA, Food and Nutrition Service, 

2006). 

Measuring the effect of FSP participation. This study is one part of a broader research 

agenda to understand the impact of the Food Stamp Program on food security. Analysts 

have tried a wide variety of research designs to measure program effects (Wilde, 2007), 

but such research faces serious challenges. The difficulty is that households with more 

severe food-related hardships are more likely to participate in the program, so one cannot 

easily use participant / nonparticipant differences to identify true program effects. There 

has been some discussion of ethical random assignment research designs for measuring 

program effects, but these are some years away from development (Burstein et al., 2005; 

Wilde, 2007). 

The present study investigated the cross-sectional associations between cash income, FSP 

participation status, food stamp benefit amounts, and several household food spending 

and food security outcomes. Using data from USDA’s flagship food security survey, a 

supplement to the Current Population Survey (CPS), the study estimated and charted 

“Engel functions” for FSP participants and nonparticipants, which show how each 

outcome responds to total income (cash income plus food stamp benefits). The study 

charted how increased income and FSP participation are associated with changes in food 

spending and food security outcomes. The analysis distinguished two possible 

contributions of food stamp benefits: increasing the household’s total resources and 

influencing the allocation of those limited resources in the direction of food goods. 

Theoretical approach. This study treated food spending as the main vehicle by which 

food stamp benefits influence household food security. It resuscitated, with 

modifications, the traditional economic theory of consumer choice between food and 

nonfood goods subject to a targeted food benefit such as food stamps. This traditional 

theory relies on a distinction between unconstrained (or inframarginal) households and 

 

1

 Previously, USDA used the terms “food insecurity without hunger” and “food insecurity with hunger,” 

respectively, to describe the classifications for “low food security” and “very low food security.” USDA 

changed the terminology in the most recent annual food security report to be more precise and limited in 

using the word “hunger” (Nord, Andrews, and Carlson, 2006). 

1
constrained (or extramarginal) households. According to the theory, additional food 

stamp benefits should have a modest effect in raising food spending for unconstrained 

households and a large effect in raising food spending for constrained households. 

This theory, which dates to the 1940s, has in recent years not been accepted as the basis 

for research about the Food Stamp Program, because empirical evidence appeared to 

contradict one of its predictions (Fraker, 1990; Wilde and Andrews, 2000). Specifically, 

the evidence suggested that additional food stamp benefits had a comparatively large 

effect on food spending even for households that appeared to be unconstrained. This 

study therefore pursued a modified version of the traditional theory, in which the 

difference between constrained and unconstrained households is not a sharp binary 

distinction but rather a matter of degree. 

Our main study of food spending and food security outcomes was preceded by an 

investigation into the degree of constraint or extramarginality that is found in the 

household budgets of FSP participants with varying levels of total income. Our hope was 

that better understanding these features of the household budget might permit the analysis 

to distinguish self-selection patterns from true program effects. However, to foreshadow 

the results in later sections, the degree of constraint or extramarginality did not fall as 

total income rose to the extent one might expect. Similarly, participant / nonparticipant 

differences for several key outcomes did not diminish steadily as total income rose, as 

one might expect from our theory. 

As a consequence, like the non-experimental literature that preceded it, the results of the 

present non-experimental study testify to the strength of self-selection patterns. The most 

interesting results show strong positive associations between FSP participation and athome food spending, and yet negative associations between FSP participation and food 

security status, where all of these associations are measured holding constant real total 

income. 

Outcomes. The study addresses two food spending outcomes and two food security 

outcomes. The labels for these outcomes, A through D, are retained throughout this 

report. 

The food spending outcomes are: 

A. At-home food spending. Food stamp benefits may by law be spent only on 

food and beverages from authorized food retailers, such as grocery stores and 

supermarkets. While the nutrition education component of the Food Stamp 

Program has been growing in recent years, it is still dwarfed by the value of the 

food stamp benefits themselves, so at-home food spending remains the leading 

path by which the program is expected to influence other outcomes such as 

reducing food insecurity and hunger. 

B. Away-from-home food spending. Although food stamps in most cases may 

not be spent in restaurants and cafeterias, the program could still in principle 

2
affect away-from-home food spending by encouraging low-income households to 

acquire a higher fraction of their food in grocery stores. This possible substitution 

effect has been little studied. Yet, in light of contemporary nutrition concerns, 

encouraging less reliance on restaurant food could be an important benefit of the 

Food Stamp Program. 

The food security outcomes are: 

C. The self-perceived food spending gap. One way of evaluating the adequacy 

of household food spending is to ask the household respondent to report what 

level of food spending he or she perceives as sufficient. The food spending gap is 

the difference between usual food spending and this self-reported food spending 

need. A positive gap indicates adequate food spending, while a negative gap 

indicates a self-perceived shortfall in food spending. 

D. Household food security. The most important policy motivation for the 

federal government’s investment in the Food Stamp Program is to improve 

household food security. Based on responses to multiple food security survey 

items, USDA classifies households as being “food secure” or “food insecure.” 

Within the food insecure category, there are sub-categories for “low food 

security” and “very low food security.” The food security outcomes studied here 

include these food security status indicators and also the response frequencies for 

selected individual food security survey items. 

Research questions. For each of these outcomes, there are three types of research 

questions. The labels for these questions, 1 through 3, are retained throughout this report. 

The questions are: 

1. Response to total income. In a cross-sectional Engel-function analysis 

conducted separately for FSP participants and nonparticipants, how does the 

outcome respond to increasing levels of total income (cash income plus any food 

stamp benefits)? 

2. Response to program participation status. In cross-sectional comparisons 

of households at the same level of total income, how does the outcome differ for 

FSP participants and nonparticipants? 

3. Distinguishing the program effect. The challenge is that a positive 

association between FSP participation and an outcome such as at-home food 

spending could be due to the program’s beneficial effect, or it could be due to the 

self-selection pattern in which households with greater food needs are more likely 

to take the trouble to participate. In light of the (modified) theory of economic 

choice between food and nonfood goods, do the Engel-function estimates and 

participant-nonparticipant differences appear more consistent with self-selection 

patterns, more consistent with true program effects, or does the direction of 

causation remain indeterminate? 

3
II. Background 

Household food security measurement. The federal government has estimated the 

prevalence of household food insecurity since 1995 (Eisinger, 1998; National Research 

Council, 2006). “Food security” is defined as “access by all people at all times to enough 

food for an active, healthy life.” “Food insecurity” is defined as the absence of food 

security at the household level. Hunger is defined as “the uneasy or painful sensation 

caused by a lack of food” (Nord, Andrews, and Carlson, 2005). 

USDA measures the prevalence of these conditions each year using an 18-item battery of 

questions on a supplement to the Current Population Survey (CPS) and other nationally 

representative household surveys. The questions refer to problems of food insecurity and 

hunger that are attributable to resource constraints, not hunger due to weight-loss dieting 

or voluntary fasting. Ten of the items refer to conditions in all households, and 8 more 

items are asked only of households with children. 

Examples of comparatively mild symptoms of hardship in these questions include: 

“We worried whether our food would run out before we got money to buy more.” 

Was that often, sometimes, or never true for you in the last 12 months? 

“The food that we bought just didn’t last and we didn’t have money to get more.” 

Was that often, sometimes, or never true for you in the last 12 months? 

Examples of comparatively severe symptoms of hardship in these questions include: 

In the last 12 months, were you ever hungry, but didn’t eat, because you couldn’t 

afford enough food? (Yes/No) 

In the last 12 months, did you or other adults in your household ever not eat for a 

whole day because there wasn’t enough money for food? (Yes/No) 

USDA converts these questions into binary items, showing whether or not a household 

affirms the presence of a particular symptom of hardship, and sums the number of 

affirmative responses (0 to 10 for households without children; 0 to 18 for households 

with children). In the official terminology, households are classified as having “high 

food security” if they have fewer than 3 affirmative responses. They are classified as 

having “low or very low food security” if they have 3 or more affirmative responses. 

They are classified as having “very low food security” if they have 6 or more affirmative 

responses in households without children or 10 or more affirmative responses in 

households with children. 

Food Stamp Program (FSP). The Food Stamp Program is the nation’s largest federal 

nutrition assistance program and a centerpiece of the social safety net. It provides a 

4
targeted food benefit through an electronic card much like a bank debit card, which may 

be used to purchase foods and non-alcoholic beverages from authorized food retailers. In 

fiscal year 2005, the program served a monthly average of 25.7 million people, of whom 

half were children and 8 percent were elderly (Barrett, 2006). 

To be eligible for food stamp benefits, most households must have monthly gross income 

less than 130 percent of the federal poverty line ($2097 for a family of four in 2005), 

monthly net income after certain deductions less than the poverty line ($1613 for a family 

of four), and countable assets below a specified value. If the household is very poor, 

having a net cash income of zero, it receives the maximum benefit amount approximately 

equal to the monthly cost of the Thrifty Food Plan ($506 for a family of four in 2005). 

The maximum benefit for a family of four equals the Thrifty Food Plan for a family of 

four, and the maximum benefit for other household sizes is adjusted to account for 

household size and economy of scale in food purchases and preparation. For households 

with positive net cash income, the household’s food stamp benefit is reduced by 30 cents 

for each dollar of net cash income. This benefit formula generates an inverse relationship 

between a household’s cash income and its food stamp benefit amount. 

III. Literature 

Program effects on food spending. A thorough 2004 USDA literature review 

summarized the large body of research showing that food stamp benefits substantially 

raise food spending (Fox, Hamilton, and Lin, 2004). Two studies in the early 1990s used 

random-assignment research designs to compare food stamps with equivalent cash 

benefits, while two others used quasi-experimental designs (Fraker, Martini, and Ohls, 

1995), and dozens of earlier studies used nonexperimental regression approaches to 

estimate the marginal propensity to spend on food out of food stamps and cash 

(Levedahl, 1995; Fraker, 1990). 

Past research on food stamps and food spending faced several hurdles. The randomassignment experiments were compelling, in the sense of providing scientifically sound 

evidence about whether food stamps have distinct effects on food spending, but these 

studies were expensive. By contrast, the self-selection models required strong and not 

entirely plausible parametric distributional assumptions, and did not always in practice 

appear robust (Devaney and Fraker, 1989). 

The regression analyses frequently estimated the marginal effect of food stamps to be two 

or more times larger than the corresponding marginal effect of cash income on food 

spending (Fraker, 1990; Levedahl, 1995). This distinct food stamp effect seemed too 

high to be consistent with the traditional theory of consumer choice subject to in-kind 

government benefits, for reasons that are discussed below in section IV. Moreover, 

researchers became suspicious of the source of independent variation in food stamp 

benefits and cash income, given that the food stamp benefit formula seems at first to be a 

linear function of cash income (Wilde, 2001; Nord and Newman, 2004). 

5
Program effects on food security.2

 USDA’s 2004 literature review found some evidence 

that food stamps raise nutrient availability in household food supplies, while it found less 

consistent evidence that food stamps improve individual nutrient intake (Fox, Hamilton, 

and Lin, 2004). At the time that review was written, the literature measuring the effect of 

food stamps on food insecurity and hunger was sparse, but this literature has expanded 

more recently. 

There is a strong prima facie case that food stamps may alleviate hunger by providing 

valuable resources to very poor households. However, the main food security survey 

items ask about the occurrence of hardship at any time in the preceding 12 months, while 

food stamp benefits vary widely in amount, are posted only once monthly, and are largely 

spent during the first several days after acquisition each month (Wilde and Ranney, 2000; 

Shapiro, 2005). Hence, the magnitude of the food stamp effect is an important open 

empirical question. 

Only 65% of eligible people choose to participate (Cunnyngham, Castner, and Schirm, 

2007), and those who suffer from hunger are more likely to take the trouble to participate. 

As a consequence, even if one restricts attention to the population of households with 

income below 130 percent of the poverty line, the prevalence of very low food security is 

about twice as high among food stamp participants as among nonparticipant households 

(Figure 1). This self-selection or self-targeting pattern has been noted many times in the 

recent literature (Fox, Hamilton, and Lin, 2004; Nord, Andrews, and Carlson, 2005; 

Holben, 2006; Burstein et al., 2005). 

Efforts to address this problem with more complex statistical approaches have generated 

a series of interesting papers and articles that shed light on the self-selection pattern but 

do not in the end succeed in quantifying the effect of food stamps on food insecurity and 

hunger. This section reviews seven such research approaches. 

The first approach is to control for other observable variables while seeking to measure 

the effect of FSP participation in a regression model. However, several studies have 

found that prevalence of food insecurity or hunger remain much higher for participants 

than for nonparticipants even after including control variables in this fashion (Gundersen 

and Oliveira, 2001; Gibson-Davis and Foster, 2006). 

A second approach is jointly to model the effect of food stamps on food insecurity and 

vice versa using a system of simultaneous equations. This statistical methodology 

requires either a strong assumption about the distribution of the error terms or the 

presence of instrumental variables that strongly affect FSP participation but do not 

otherwise affect food insecurity. Using cross-sectional data from the Survey of Income 

and Program Participation (SIPP), Gundersen and Oliveira sought to measure the effect 

of food stamp participation on “food insufficiency,” a measure of food-related hardship 

based on a single survey question that predated USDA’s official food security 

measurement methods. Gundersen and Oliveira reported that the more complex 

statistical models removed the evidence of a statistically significant positive association 

 

2

 This literature review draws on Wilde (2007), with permission from the Journal of Nutrition. 

6
between food stamp participation and food insufficiency (Gundersen and Oliveira, 2001). 

More precisely, their simultaneous equations models found as large a positive association 

between program participation and food insufficiency as simpler models did, but the 

standard error was larger in the more complex models and hence the statistical 

significance disappeared (Gundersen and Oliveira, 2001, Table 3). Also using 

simultaneous equations, Jensen found that the random disturbances for equations 

describing program participation and food security status were correlated, such that a 

higher tendency toward FSP participation was associated with lower risk of food 

insecurity (Jensen, 2002). Using data from the Survey of Program Dynamics (SPD), 

Huffman and Jensen found that being food insecure with hunger strongly increased the 

likelihood of FSP participation, but “no evidence that the food assistance reduces food 

insecurity” (Huffman and Jensen, 2006). 

A third approach is to use longitudinal or panel data. Hofferth used data from the Panel 

Study of Income Dynamics (PSID) to measure the association between transitions in FSP 

participation status and food insecurity, but she concluded that most of the observed 

associations reflected variation in families’ unmet needs for food rather than a true effect 

of program participation (Hofferth, 2004). Using data from the SIPP and SPD, Ribar and 

Hamrick found that food stamp use in 1994-95 was associated with lower rates of exit 

from food insecurity by 1997, and hence their study “provides no evidence that food 

stamps alleviate food problems,” but they also noted the continued presence of 

unobservable factors and did not claim to have measured the causal impact of FSP 

participation (Ribar and Hamrick, 2003). With longitudinal data from the same CPS 

survey that provides federal statistics on food insecurity and hunger, Wilde and Nord 

found that using a fixed effects panel data model to control for time-invariant 

unobservable factors reduced but did not eliminate the appearance that FSP participation 

was associated with poorer food security status (Wilde and Nord, 2005). 

A fourth approach, pursued by Gibson-Davis and Foster (2006) using data from the Early 

Childhood Longitudinal Survey, is propensity score matching. This statistical technique 

estimates a model for the probability of program participation, then predicts the 

probability of participation for each person in the sample, and finally compares the food 

security status of matched participants and nonparticipants with similar predicted 

probabilities. The authors’ most reliable models indicated that food stamps did not affect 

the probability of being classified as food insecure, although they offered “tentative 

evidence” that food stamps reduced the level of food insecurity among those who are 

categorized as food insecure. The authors warned that establishing cause and effect with 

propensity score matching “might not be possible in some instances, given the magnitude 

of the selection effects.” 

A fifth approach, the dose-response approach, employs variation across participant 

households in the food stamp benefit amount to measure the response of food security 

status to an increasing dose of food stamps (Fox, Hamilton, and Lin, 2004). Some early 

research using this approach found a small but statistically significant association 

between higher benefit amounts and lower risk of food insecurity (Rose, Gundersen, and 

Oliveira, 1998). Other work using a dose-response approach is ongoing (Daponte and 

7
Stephens, 2004; Nord and Newman, 2004). Kabbani and Kmeid used a dose-response 

approach to study whether a household that experienced hunger in the previous year 

nevertheless reported food secure status in the most recent month (Kabbani and Kmeid, 

2005). Interpreting results from the dose-response approach requires careful attention to 

the nature of the program’s benefit formula, which implies that the poorest households 

generally receive the highest food stamp benefits. The source of variation in food stamp 

benefits conditional on cash income is not random, but rather it depends systematically 

on the household’s deductions (Wilde, 2001). As a consequence, it is difficult to 

distinguish the effect of a higher food stamp dose from the effect of lower cash income 

and differences in the household characteristics that influence deductions. 

A sixth approach exploits “natural experiments,” such as changes in program rules for 

some populations but not others, for use in a quasi-experimental research design. In the 

only such study we could find that directly addresses food stamps and food security, 

Bartfeld and Dunifon (2006) used hierarchical linear modeling to investigate the effect of 

multiple variables including the fraction of the state-level low-income population that 

participates in the Food Stamp Program. A model including interaction terms between 

this measure of participation and household-level income status found small but 

statistically significant beneficial effects of higher FSP participation for near-poor and 

low-income households, but not for poor households or higher-income households. In a 

study of a related “natural experiment,” Borjas found that immigrant populations whose 

program eligibility was restricted in the 1996 welfare reforms experienced a significant 

relative deterioration in food security status (Borjas, 2004). Two studies have used 

variation in weather -- a truly “natural” independent variable if ever there was one -- to 

assess the effect of heating and cooling costs on food security status (Nord and Kantor, 

2006; Bhattacharya et al., 2002), but it is difficult to conceive of natural events that 

would influence FSP participation in the same fashion that weather influences heating 

and cooling costs. 

The seventh and final approach would use a random-assignment research design to 

measure the effect of FSP participation on food security status. Influential studies in San 

Diego and Alabama in the early 1990s used a random-assignment design to measure the 

effect of “cashing out” food stamps on food spending (Fox, Hamilton, and Lin, 2004). 

Random-assignment research designs have been much discussed in the recent literature 

on food insecurity and hunger, but never implemented. Several authors use identical 

language to hold up random-assignment designs as the “gold standard” but then go on to 

describe them as unethical or infeasible for the current research question (Fox, Hamilton, 

and Lin, 2004; Burstein et al., 2005; Gibson-Davis and Foster, 2006). Burstein et al. 

(2005) do propose a random-assignment component as one part of a larger project on 

measuring FSP effects, and Wilde (2007) discusses some possible designs that would 

meet the ethical requirement of providing at least the current federal entitlement to all 

eligible study participants. 

In addition to the literature relating food stamps directly to food security, reviewed here, 

there is also a growing body of research relating food security status to weight status 

(Townsend et al., 2001; Wilde and Peterman, 2006; Sarlio-Lahteenkorva and Lahelma, 

8
2001) and relating FSP participation to weight status (Gibson, 2003; Jones and Frongillo, 

2006; Chen, Yen, and Eastwood, 2005). These studies do not seek to measure the effect 

of food stamps on food security status. 

Research on food spending and food security jointly. There is a smaller body of work 

that, like this study, emphasizes food spending as the leading vehicle by which food 

stamps influence household food security. Jensen (2002) observed, “Dating as far back 

as Engel’s work, poverty has been closely tied to food expenditures.” The original 

Federal poverty line was established as a multiple of the estimated minimal food 

spending requirement. In addition to survey questions about actual and usual food 

spending, the food security supplement to the CPS asks respondents for their own 

estimate of their household’s minimal food spending needs. Such self-reported spending 

requirements can be used to assess poverty thresholds (Blaylock and Smallwood, 1986; 

Andrews, Nord, and Kabbani, 2001; Jensen, 2002). 

Using data from the food security supplement to the CPS, Nord and Newman (2004) 

estimated the cross-sectional relationships between the food stamp benefit level, usual 

food spending from all sources, and the risk of having very low food security. The 

authors noted that that participant / nonparticipant comparisons without dose-response 

analysis have trouble accounting for self-selection issues, while dose-response analysis 

that includes both cash income and FSP benefits on the right-hand side raises a concern 

about the source of independent variation in these two variables (a concern that is 

discussed in Wilde, 2001). Faced with this challenge, Nord and Newman retained the 

FSP benefit variable and omitted the cash income variable in key models of food 

spending and food security outcomes. 

USDA’s annual report on household food security in 2003 noted a strong positive 

relationship between food spending and food security: the median food insecure 

household spent 4 percent less than the value of the Thrifty Food Plan on food, while the 

median food secure household spent 26 percent more than the value of the Thrifty Food 

Plan on food (Nord, Andrews, and Carlson, 2004). 

The combination of known findings about food stamps, food spending, and food security 

leaves a mystery. If food stamps raise food spending, and higher food spending is 

associated with improved food security, why is FSP participation associated with lower 

food security? This paradox could be reconciled if FSP participants have both higher 

food spending and higher self-perceived food needs, leading to lower food security status. 

This possibility is investigated empirically in this study. 

IV. Theory 

Overview. The traditional economic theory of consumer choice with a food stamp benefit 

dates to Southworth (1945). In this theory, a consumer’s total income is composed of 

cash income and food stamp benefits if she is a FSP participant. Her total income is just 

cash income if she is a FSP nonparticipant. Subject to the constraints on her resources, 

9
she makes her best possible choices about spending levels for a food good and a nonfood 

good, where the nonfood good represents a composite of all the other things a person 

could buy. 

The theory draws an important distinction between constrained or extramarginal FSP 

participants and unconstrained or inframarginal participants. Constrained participants 

receive more in food stamps than they would otherwise spend on food if their total 

income were all cash, so they choose to spend all their stamps on the food good and all 

their cash on the nonfood good. Unconstrained participants contribute some of their cash 

income to their food budget in addition to using food stamps for food. 

In the Southworth theory, food spending for constrained participants responds very 

sharply to a marginal increase in food stamp benefits. Every additional dollar of food 

stamps leads to an additional dollar of food spending. By contrast, food spending for 

unconstrained participants responds to increased food stamp benefits just as slowly as it 

would respond to an increase in cash income. Past research has estimated that lowincome Americans spend about 5 to 15 cents of each additional dollar of cash income on 

food. 

As noted previously in section III, many regression analyses of food spending have 

estimated the marginal effect of food stamp benefits to be two or more times larger than 

the marginal effect of cash income (Fraker, 1990; Levedahl, 1995; Wilde and Ranney, 

1996). This food stamp effect seemed too high to be consistent with the comparatively 

large number of participants who appeared unconstrained or inframarginal, in the sense 

of spending some of their own cash income on food. 

If the empirical observation is correct, there are several plausible explanations for this 

paradox:

• Households may spend some of their own cash income on food late in the month, 

after their food stamps have run out, even if they were effectively extramarginal 

(constrained) earlier in the food stamp month. In past research, food spending was 

typically measured on a 7-day or 14-day basis, food stamp benefits were typically 

measured on a 1-month basis, and household income was commonly measured for a 

1-month or 12-month period. Because food spending by food stamp recipients is 

sharply cyclical, these measurement differences made it hard to identify 

extramarginal households properly (Wilde and Ranney, 2000; Wilde and Andrews, 

2000). 

• Households may spend some of their own cash income on food away-from-home, in 

cafeterias and restaurants, even if their at-home food budget is essentially 

extramarginal. Program rules prevent food stamp spending in restaurants. For 

example, as welfare reforms of the 1990s have increased the labor market orientation 

of the Food Stamp Program, larger numbers of participants may occasionally 

purchase food away-from-home for work-related reasons. 

• One household member may spend some cash income on food, while another 

household member who controls food stamp benefits makes household budgeting 

decisions on an extramarginal basis. Breunig et al. (2001) argued that the “cashout 

10
paradox” -- the finding that even inframarginal households appear to spend food 

stamps differently from cash income -- may be explained by intra-household 

bargaining behavior in households with more than one adult. 

These explanations share a common feature. In each case, there may be cash spending on 

food in households that nevertheless behave in some respects extramarginally. Rather 

than try to model in detail all features of these three explanations, we suppose more 

simply that there is some minimum level of necessary cash spending on food, even in 

extramarginal households. For example, a household may have to spend cash on food 

late in the food stamp month, when benefits have run out. As another example, one 

household member may spend cash on food while another member carries the food stamp 

benefit card. In this modification of the traditional theory, we can be quite sure a 

household is constrained if its food spending falls equal to or below its benefit level, and 

we can be quite sure a household is unconstrained if its food spending exceeds its benefit 

level by a large margin, but we may think of the household as “partly” constrained to an 

unknown extent in intermediate cases. 

An Example. The traditional theory and the modified theory are presented formally in 

the next subsection, but for intuition, it may help to give an example. 

Suppose Household A has $400 in monthly cash income and $200 in monthly food stamp 

benefits. If the household had more simply owned $600 in cash, it would have spent 

$150 monthly on food, but it honors the FSP regulations and instead spends all of its FSP 

benefits on food. In the traditional theory, the analyst who observed the household’s 

monthly food spending ($200) and monthly food stamp benefit ($200) would 

immediately recognize the household as constrained or extramarginal. 

Now, suppose Household B also has $400 in monthly cash income and $200 in monthly 

food stamp benefits. Household B also would have spent $150 monthly on food, but it 

too honors the FSP regulations and instead spends all of its FSP benefits on food. 

Moreover, since the FSP benefits come in one lump each month, it economizes shopping 

time and transportation costs by spending these benefits in one large supermarket trip at 

the start of the month. Toward the end of the month, the household relies on 

nonperishable staples that were stored from the original shopping trip plus about $30 of 

cash spending on additional milk and vegetables from a smaller nearby grocery. In the 

traditional theory, the analyst who observed the household’s monthly food spending 

($230) and monthly food stamp benefit ($200) might incorrectly classify the household as 

unconstrained, even though the household is better described as constrained for most of 

the month. 

The traditional model of consumer choice. In the Southworth theory, consumer 

preferences over a food good (F) and a non-food good (X) are described by a utility 

function (U). Program participants have two kinds of resources, cash income (C) and 

food stamp benefits (B). Nonparticipants have only cash income. The sum of cash 

income and food stamp benefits is called total income (Y). 

11
Participants make rational choices subject to two resource constraints: 

• total spending cannot exceed total income, and 

• non-food spending cannot exceed cash income, because of rules forbidding food 

stamp spending on non-food goods. 

Mathematically, the function U is a utility function, quasi-concave and increasing in both 

arguments. The participant’s consumer choice problem is: 

(1) Maximize U(F,X), 

subject to F+X ≤ Y = C+B, (total income constraint) 

X ≤ C, (cash income constraint) 

 F ≥ 0, and X ≥ 0 (non-negativity constraints). 

The participant consumer is constrained or extramarginal if the cash income constraint is 

binding. For such a consumer, X = C, F = B, and no cash income is spent on food. If B

increases by some marginal amount, F will increase by the same amount. In this sense, 

for extramarginal households, the “food stamp effect” on food spending is very large. 

By contrast, the participant consumer is unconstrained or inframarginal if the cash 

income constraint is non-binding. For such a consumer, X < C, F > B, and the consumer 

contributes some of her own cash income to her food budget. F will increase by an 

identical amount in response to a marginal increase either in B or C. In this sense, for 

inframarginal households, the “food stamp effect” on food spending is comparatively 

small and it exactly equals the corresponding “cash income effect” on food spending. 

For participants, let f(Y) be the unconstrained Engel function, showing food spending as 

an increasing function of total income for an inframarginal consumer. The solution to the 

consumer problem (1) is a kinked food demand function, which may be expressed: 

(2) F = max[B,f(Y)] (for participants). 

This equation means that food spending equals B if the consumer is extramarginal, and 

food spending equals f(Y) if the consumer is inframarginal. 

Nonparticipants also make rational choices, but their food stamp benefit equals zero, so 

they face only the total income constraint and the non-negativity constraints. The cash 

income constraint is redundant. For nonparticipants, it is not possible to be 

extramarginal, so more simply: 

(3) F = f(Y) (for nonparticipants). 

The food stamp benefit formula. The last piece of information we need to illustrate the 

shape of the Engel function under the traditional theory is the structure of the food stamp 

benefit formula. The cash income amount (C in the preceding discussion) is called 

“gross income” in food stamp parlance. The food stamp benefit is based on “net 

12
income,” which equals gross income minus certain deductions. The deduction amount 

(D) equals the sum of a standard deduction, an earned income deduction, an excess 

shelter cost deduction and several smaller deductions. If these deductions exceed C, then 

net income equals zero, and the participant receives the maximum benefit (M). 

Otherwise, the participant receives the maximum benefit minus 30 percent of her net 

income. 

More formally, the benefit formula can be stated as a function of cash income: 

(4) B = min[M, M - 0.3 (C - D)]. 

In order to use this benefit formula in connection with Engel functions such as equations 

(2) and (3), we need to restate equation (4) as a function of total income (Y). Recalling 

that C = Y - B and substituting into equation (4), we get: 

(5) B = min[M, 1.4 M - 0.43 (Y - D)]. 

This equation is easier to understand when illustrated (Figure 2). For consistency with 

later figures, the horizontal access is total income (cash plus food stamp benefits) rather 

than cash income alone. At the left side of the figure, participants with the lowest level 

of total income receive the maximum food stamp benefit (M). Moving rightward as total 

income increases due to increases in cash income, the participant at first continues to 

receive the maximum benefit but then the benefit begins to fall. 

By looking at equation (2) and equation (5) together, we get a picture of the shape of the 

Engel function under the assumptions of the traditional theory (Figure 3). At the left side 

of the figure, representing the lowest level of total income, the household receives the 

maximum benefit and is constrained such that food spending equals this maximum 

benefit. Moving rightward as total income increases, the benefit decreases but the 

household is still constrained such that food spending equals the benefit. As total income 

increases yet further, the household becomes unconstrained as food spending begins to 

exceed the benefit amount. Finally, at the highest level of total income, the household is 

not eligible to participate in the Food Stamp Program. 

This Engel function for participants may be contrasted with the corresponding Engel 

function for nonparticipants (Figure 3). The nonparticipant household is never 

constrained by any food stamp benefit, so food spending simply increases steadily at all 

levels of total income. 

A modified theory. In the modified theory, there may be cash spending on food in 

households that nevertheless behave in some respects extramarginally. Suppose the 

minimum level of necessary cash spending on food is denoted α. We have described α

as representing cash spending on food late in the food stamp month when benefits have 

run out or cash spending on food by one member while another member carries the food 

stamp benefit card. The level of α would not be directly observable, but we presume the 

analyst has some general knowledge of its maximum possible value. 

13
The new cash income constraint in the participant’s consumer choice problem is: 

(6) X ≤ C-α. 

The revised solution to the consumer choice problem (1) is: 

(7) F = max[B+α,f(Y)]. 

In this revised theory, the analyst cannot tell whether the household is unconstrained just 

by checking whether the household contributed any cash income at all to the food budget. 

A small amount of cash spending on food could be consistent with either constrained or 

unconstrained status. It is only when the amount of cash spending on food exceeds what 

one might think is a reasonable value for α that the analyst can feel confident that the 

household is unconstrained. 

Just as in Figure 3 from the preceding subsection, it is possible to illustrate the Engel 

function under this modified version of the traditional theory (Figure 4). At the left side 

of the figure, representing the lowest level of total income, the household receives the 

maximum benefit and is constrained such that food spending equals this maximum 

benefit plus the additional amount α. Moving rightward as total income increases, the 

benefit decreases but the household is still constrained such that food spending equals the 

benefit plus α. As total income increases yet further, the household becomes 

unconstrained as food spending begins to exceed the benefit amount. Finally, at the 

highest level of total income, the household is not eligible to participate in the Food 

Stamp Program. 

Self-selection patterns. The preceding analysis applies to a particular household with 

fixed preferences for food and non-food goods. If participants and nonparticipants were 

selected randomly from the same general population, the model’s implications would 

only be a little more complicated when we allow for more realistic variation across 

households in food needs, preferences, deductions, and values for α. 

For example, if the line graphs in Figures 3 and 4 represented mean food spending levels 

at each level of total income -- rather than the food spending level for a single household 

-- the kinks in the Engel functions would not be quite as pronounced, but other features of 

the illustration would remain the same. In particular, the distinct effect of food stamp 

benefits on food spending would continue to appear pronounced at low levels of total 

income (toward the left of the figures), while spending levels would be the same for 

participants and nonparticipants at higher levels of total income (toward the right of the 

figures). 

The real problem arises in the very plausible case where program participation status is 

not random, but instead it depends on a household’s variable food needs or preferences. 

In particular, it seems likely that households with greater preferences for food or a higher 

14
degree of food-related hardship are more likely to take the trouble to participate in the 

Food Stamp Program. 

Figure 5 is a variant of Figure 3, with the new feature that participants are assumed to be 

self-selected from a subpopulation with a higher tendency to spend limited total income 

on food. Participants generally have higher food spending levels in Figure 5 than in 

Figure 3. Hence, participants are more commonly unconstrained in Figure 5 than in 

Figure 3. Only the participants with the very lowest levels of total income, at the left side 

of Figure 5, are so short of cash that they reserve their cash for non-food spending alone. 

Using theory for causal inference. The modified theory and the self-selection story offer 

two competing explanations for the paradoxical empirical finding that food stamps 

appear to have a distinctive large effect on food spending even for households that appear 

to be unconstrained or inframarginal under the assumptions of the traditional theory. 

Both of these competing explanations suggest that mean food spending may be higher for 

participants than for nonparticipants with comparable total income. 

Fortunately, the explanations differ sharply in their implications for the shape of the 

Engel functions for participants and the nature of participant / nonparticipant spending 

differences holding constant total income. Specifically, the modified theory predicts that 

beneficial participant / nonparticipant differences will narrow and even disappear as total 

income rises to the level where benefits become small and most households become 

inframarginal. By contrast, the self-selection story is consistent with participant / 

nonparticipant differences at all levels of total income, at least under the assumption that 

self-selection does not vary systematically with total income. 

The distinct implications of these competing explanations could in principle help the 

analyst to determine whether observed cross-sectional results are due to self-selection 

patterns or true program effects. In Section I of this report, we listed “distinguishing the 

program effect” as the third of three research questions to investigate for each of the 

outcomes studied. Such a determination is precisely what has proven difficult the recent 

empirical research on food stamps and food security. 

V. Data and Methods

Data analyzed for this report come from the food security supplement to the Current 

Population Survey (CPS). The U.S. Census Bureau collects labor market information on 

behalf of the Bureau of Labor Statistics (BLS) each month through the CPS. The Census 

Bureau also collects food spending and food security data on behalf of USDA in 

December only through the food security supplement. In this study, food security 

supplement data for December of 2001 to 2005 were combined. 

The food security supplements contain approximately 55,000 household observations per 

year (56,443 in December 2001, 56,967 in December 2002, 55,411 in December 2003, 

55,307 in December 2004, and 54,556 in December 2005). The supplements contained 

15
226,305 households with 1 to 6 household members and annual household income less 

than $75,000. Of these, we could determine FSP participation status for 223,452 

households. We excluded 49,586 households with missing values for the “control card” 

cash income variable (see subsection on cash income below) and also excluded 

households with high total income on an adult equivalent basis (see subsection on total 

income below). The final sample size with nonmissing values for FSP participation and 

all the required income variables was 173,146 household observations. 

 

FSP participation status. Households that reported receiving food stamp benefits in 

approximately the preceding month (November or December) were classified as 

participants. There is underreporting of FSP participation in the CPS, due partly to error 

and misreporting by respondents and partly to insufficient coverage in the CPS of some 

population groups that may have high rates of FSP participation. For example, in 

December 2005 the participants in the weighted CPS sample represented 6.3 million 

participant households, while program data from the Food and Nutrition Service report 

11.8 million participant households for that month. 

Households that did not receive food stamp benefits during the year were classified as 

nonparticipants. Just over 2,000 households that received food stamp benefits during the 

year, but not during the preceding month, were excluded. For purposes of this study, 

these latter households could not be classified as participants (because their food 

spending data applied to a recent week in which they did not have food stamp benefits), 

nor could they be classified as nonparticipants (because their food security data applied to 

the past year, in which they did have food stamp benefits). 

For FSP participant households, the food stamp benefit variable reported the household 

benefit amount for the most recent month in dollars. 

Cash income. The cash income variable in the CPS, known colloquially as the “control 

card income” variable, asked households to report their annual income in one of 14 

categories. Cash income was based on the combined income of all family members over 

the age of 15 years, including money earned from jobs, business, pensions, dividends, 

interest, social security payments, and any other income over the past 12 months. To 

convert the annual control card cash income to a continuous monthly cash income 

variable, the midpoint of the control card income categories was divided by 12. The 

control card cash income variable suffered from high rates of nonresponse: 18.4 percent 

refused the question and another 3.6 percent responded “don’t know.” 

Total income. Total income equaled the sum of monthly cash income plus monthly food 

stamp benefits. Because the research design sought to measure the association between 

total income and outcomes of interest without imposing a linear functional form or other 

parametric functional form by assumption, the main results use categories of real monthly 

total income per adult male equivalent (AME) as a key explanatory variable (the adult 

equivalent scale is discussed below). The categories were $0-249, $250-$499, ..., $2,250-

$2,499. Large samples of nonparticipants were available in each category of real total 

income. For participants, naturally, there were few or no observations in categories of 

16
real total income that much exceeded the gross income cutoff for food stamp eligibility. 

Using a standard of requiring at least 200 observations in each real total income category, 

the analysis retained participant households for the four poorest categories with income 

per AME less than $1000 in household types (a) single adults with children and (b) two 

adults with children, and for the six poorest categories with income per AME less than 

$1500 in household type (c) adults with no children. 

Household structure. Analyses were conducted separately for three household types: a) 

a single adult with one or more children (n=12,498 or 7.8 percent of weighted sample), b) 

two adults with one or more children (n=35,755 or 20.9 percent of weighted sample), and 

c) one or more adults with no children (n=116,978 or 66.5 percent of weighted sample). 

All other household compositions were excluded (n=7,915 or 4.8 percent of weighted 

sample). 

Inflation and adult male equivalent (AME) adjustments. Wherever economic variables 

in the analysis were reported in terms of “adult male equivalents” (AME), the variable 

was scaled on the basis of average daily energy needs for particular age and gender 

groups, as found in the 2005 Dietary Guidelines for Americans. This adjustment for 

energy needs does not account for variation in energy needs due to differences in physical 

activity or weight status. For example, the daily energy needs are 2200 calories for a 

male aged 31 to 50 years, 1800 calories for a female aged 31 to 50 years, and 1200 

calories for a child aged 4 to 8 years. A household with an adult male, and adult female, 

and a young child would have 1.00 + 0.82 + 0.55 = 2.37 AMEs. 

Monthly cash income, monthly food stamp benefit amount, and total income were 

deflated using the CPI for urban consumers to December 2003 dollars, to account for 

inflation. They were divided by the number of adult male equivalents (defined above) to 

put these household-level variables on a per-AME basis. Similar inflation and AME 

adjustments were made to the food spending variables discussed below. 

Food spending outcomes.

The outcomes are described here using labels A through D that correspond to the 

discussion in Secton I (p. 4). 

A. At-home-food spending. Total expenditures minus non-food item expenditures for 

purchases at supermarkets and specialty shops such as, meat markets, produce stands, 

bakeries, warehouse clubs, and convenience stores, including any purchases made with 

food stamps in the previous week. 

B. Away-from-home food spending. Total expenditures on food purchased at a 

restaurant, fast food place, or cafeteria, including children who may have bought food at 

the school cafeteria or vending machines in the previous week. 

Food Security outcomes. 

C. The self-perceived food spending gap. The food security supplement asked whether 

the household needed more or less than its current usual food spending to buy just 

17
enough food to meet household needs. The household could respond “no” to both 

questions if its current usual food spending exactly met its needs. If the household 

needed either more or less, a follow-up question asked the amount. We defined 

“minimum needed food spending” as usual weekly food spending plus or minus any such 

amount. 

The self-perceived food spending gap was defined as usual weekly food spending minus 

the minimum needed food spending. Hence, a positive self-perceived food spending gap 

indicated that usual food spending was more than adequate, and a negative self-perceived 

food spending gap indicated that food spending was less than adequate. 

 

D. Household food security measures: 

Food security status was reported in the CPS as a categorical variable, representing 

respectively the conditions of “high food security,” “low food security,” and “very low 

food security” on the basis of responses to 10 survey items (in households with children) 

or 18 survey items (in households without children) about symptoms of food-related 

hardship in the past 12 months. 

In addition to the main results for the 12-month food security measure, we analyzed a 

comparable 30-day measure that reflects responses to survey items about hardship in the 

most recent month. The 30-day food security status variable in the CPS for 2001-2004 

used three categories describing the conditions of “high food security or mild low food 

security,” “low food security,” and “very low food security.” The reason for the slight 

difference in terminology for the most secure category is that the survey items with 30-

day reference periods tended to address comparatively serious symptoms of hardship. In 

2005, USDA improved its method for reporting food security status on a 30-day basis, 

using a wider range of survey items with a 30-day reference period, but for this analysis 

we necessarily used the 2001-2004 data instead of just the 2005 data, due to sample size 

considerations. 

Thus, in this report, the 30-day category “very low food security” is a good 30-day 

analogue to the 12-month category with the same name. The 30-day category “low or 

very low food security” is slightly less inclusive than the 12-month category with the 

same name, necessarily omitting some households with marginally high levels of food 

security. 

Survey weights. All analyses used the CPS household weights for the food security 

supplement, which adjust for the complex sampling design to make the point estimates 

representative of the population of U.S. households. 

The CPS does not provide the stratum and cluster identifiers one would need to adjust 

standard errors for the complex sampling design. For most reported results, unadjusted 

and unweighted standard errors are reported in appendix tables. In USDA’s annual food 

security report for 2004, based on information from a jacknife replication method, the 

authors used a design effect of 1.6 as a rule of thumb, which implies that the real 

sampling variance of reported parameters would be 1.6 times as large as the reported 

18
unadjusted sampling variance, due to the complex survey design of the CPS (Nord et al., 

2005). This rule of thumb in turn implies that adjusted standard errors would be 26% 

higher than the unadjusted standard errors reported in the appendix to this report. Due to 

the large sample sizes available from the CPS for the five years from 2001 to 2005, we 

believe that, while having access to adjusted standard errors would be ideal, it makes 

little difference for the statistical inferences reported in this report. 

Analyses. First, in Section VI, a preliminary analysis of household budgets investigated 

the distribution of food stamp benefits at each level of total income, for participants. The 

purpose was to understand the empirical food stamp benefit formula as it worked in 

practice in this data set. The relationship between food stamp and cash income in this 

data set could differ from what one would expect based on the official benefit formula for 

several reasons, including the time mismatch between the underlying annual cash income 

data and the monthly food stamp benefit data, the lumpiness introduced by the categories 

of control card cash income, rounding error in reporting program benefits, and more 

fundamental misreporting of either cash income or benefit information. The preliminary 

analysis helped to understand the role and scope of food stamp and cash income within 

the household’s total income. 

In addition to the results reported in Section VI, we made several efforts to reconcile 

participants’ self-reported benefit amounts with the amounts that one would predict based 

on the benefit formula. Because one source of possible discrepancy was that cash income 

was reported for a 12 month period while FSP benefits were reported for a recent month, 

we replicated the analysis of the FSP benefit amount and the principal food spending 

outcomes while breaking out separately households that were participants for the full year 

or for just part of the year. However, the results were closely similar for these two 

groups of participants, so this did not reconcile the self-reported benefit and cash income 

amounts. 

Similarly, because one source of possible discrepancy was that our household types 

combine heterogeneous demographic structures, we attempted to create alternative 

household type categories that were more homogeneous (for example, a two-parent 

household type with exactly two adults and two children instead of the current category 

for two adults and one or more children; or, a household type with exactly two elderly 

adults living alone instead of the current category more generally for adults without 

children). Again, the results were closely similar to those reported in our main analysis 

in this report. 

Second, in Section VII, the project’s main analyses estimated Engel responses for the 

four types of outcomes (labeled A through D as on p. 4). For each outcome type, the 

analysis addressed the three research questions about Engel responses, participant / 

nonparticipant differences, and the possibility of discerning cause and effect. These 

research questions were described previously in Section I (labeled 1 through 3 as on pp. 

4-5). Each analysis was conducted separately for the three household types (labeled a 

through c as on p. 16). 

19
Third, in Section VIII, we investigated the role of food spending as the principal vehicle 

by which food stamps influence food spending. If at-home food spending serves as 

intended as a vehicle by which food stamp participation can improve household food 

security status, one might expect to find the highest food security status for households 

whose at-home food spending appeared to be raised. Whereas the preceding analyses 

treated food spending and food security as separate outcomes that respond to total income 

and program participation, this third section of results addressed food spending as both an 

outcome influenced by FSP participation and a contributor to food security status. We 

divided participant and nonparticipant households into two groups, based on whether 

their weekly food spending at-home was greater than or less than the median food 

spending level for all households. Then, we estimated Engel responses for low food 

security status separately for the “high food spenders” and “low food spenders” in each 

participation category. 

The resulting Engel functions show, while holding constant total income and program 

participation status, whether higher food spending contributes to higher food security. 

This analysis helps to distinguish whether food insecurity is fundamentally a problem of 

low food spending or whether it reflects a broader set of hardships. 

VI. Results: Preliminary Analysis of Household Budgets.

Descriptive statistics for participants and nonparticipants in the three household types are 

reported in Table 1. Because the nonparticipant sample includes households that were 

not nearly income-eligible for FSP participation, it is not surprising that the 

nonparticipant households were much better off in terms of both income and education. 

 

Among participants, household types (a) single adults with children and (b) two adults 

with children were poorer on average than household type (c) adults without children. 

The fraction of households with an elderly member was low for household types (a) and 

(b), but about half of households with type (c). 

Food stamps provided 24.1 percent of all income received by households in type (a) and 

16.0 percent of all income received by households in type (b), but only 10.4 percent of all 

income received by households in type (c). The average monthly benefit amount per 

AME fell from a high of $113.17 in the poorest type (a) to about $80 in household types 

(b) and (c). 

Within household types, mean benefits did not fall sharply as total income rose to the 

extent that one might expect. In Figure 6, the line graphs without diamonds show how 

the mean benefit amount varied with total income (see also Table 2). For comparison, 

the line graphs with diamonds illustrate the corresponding pattern estimated for 2001 to 

2004 from Quality Control (QC) data from the Food and Nutrition Service for the same 

years. The QC data are a more authoritative source of information about program 

benefits, but they could not be used for the main analyses in this study, which require 

survey questions about food spending or food security outcomes that are only available in 

20
the CPS. The mean benefit amount in the CPS data did not trend downward as total 

income increased. By contrast, the comparison mean benefit amount in QC data 

generally fell as total income rose. 

There are several reasons why the relationship between program benefits and total 

income in the CPS data might not precisely follow what one would expect from reading 

the official benefit formula or from comparable analyses with QC data. As noted in the 

methods section (Section V), these reasons include time mismatch between the 

underlying annual cash income data and the monthly food stamp benefit data, the 

lumpiness introduced by the categories of control card cash income, rounding error in 

reporting program benefits, and misreporting of either cash income or benefit 

information. As described in the methods section, we made several attempts to reconcile 

the self-reported benefit amounts with the self-reported cash income values, but all of 

these attempts yielded results that were substantially the same as those reported here, 

suggesting that the problem cannot be remedied with the current data source. 

Matters appeared somewhat better in the CPS data when we investigated the percentage 

of total income from FSP benefits, as total income rose (Figure 7 and Table 2). Food 

stamp benefits contributed a comparatively large fraction of total income for the poorest 

participants, and a smaller fraction of total income for near-poor participants who have 

income approaching the boundary for eligibility. Hence, one still finds that the relative 

role of the food stamp benefit becomes smaller in household budgets with more total 

resources. 

VII. Results: Main Engel Responses for Four Categories of Outcomes. 

A. At-home food spending. 

A1. Response to total resources. For nonparticipant households, in all three household 

types, actual weekly at-home food spending per adult equivalent (“at-home food 

spending,” for short) appeared to respond positively and steadily to increased total 

income (Figure 8 and Table 3). 

For participant households, at-home food spending appeared to respond positively and 

steadily to increased total income for two of the household types: (a) single adults with 

children and (c) adults without children. For the third household type, (b) multiple adults 

with children, at-home food spending first fell and then rose as total income increased. 

With that single exception, the Engel functions for at-home food spending were 

positively sloped as one would expect. To give a sense of the magnitude of the spending 

increase, for nonparticipants in household type (a) single adults with children, at-home 

food spending rose from about $32 per adult equivalent per week for the poorest group 

(with monthly total income per adult equivalent $0-250) to about $37 for a near-poor 

group (with total income $750-1000) to about $49 for a middle-income group (with total 

income $2250-2500). 

21
A2. Response to program participation status. In all three household types, holding 

constant total income, at-home food spending was higher for the participant group than 

for the comparable nonparticipant group (Figure 8 and Table 3). Without exception, the 

association between FSP participation and at-home food spending was positive. 

To give a sense of the large magnitude of the FSP participation association, for household 

type (a) single adults with children, at-home food spending ranged from $6 to $12 higher 

for the participant group. Taking the middle of that range as an example, a weekly $9 per 

AME increase in at-home food spending was as great as the increase one saw as a 

nonparticipant household’s income rises from deep poverty (with monthly total income 

per adult equivalent $0-250) to an income level above the boundary for food stamp 

eligibility (with total income per adult equivalent of around $1500). In other words, the 

participant/nonparticipant difference has as big an association with food spending as a 

large increase in income would have. 

A3. Distinguishing the program effect. For household types (a) single adults with 

children and (c) adults without children, the results failed to show the pattern that we 

hypothesized in the theory section would constitute evidence of a true program effect on 

food spending (Figure 8 and Table 3). The participant / nonparticipant differential was at 

least as great for those participants who were expected to be unconstrained (with 

comparatively high total income) as for those participants who were expected to be 

constrained (with comparatively low total income). In the framework of the theory 

section, these patterns were what one would expect if self-selection patterns were 

responsible for the participant / nonparticipant differences. 

For household type (b) multiple adults with children, the Engel function for participants 

first descended and then ascended as total income increases. Consequently, the 

participant / nonparticipant difference was greater for those participants who were 

expected to be constrained than for those participants who were expected to be 

unconstrained. In the framework of the theory section above, this pattern for household 

type (b) was what one would expect if true program effects were responsible for the 

participant / nonparticipant difference in at-home food spending. However, because this 

pattern is not corroborated by the other two household types, this does not provide very 

strong evidence of the direct effect of food stamps on food spending. 

One reason why the hypothesized causal relationship did not show up very strongly may 

be that the near-poor participant households were not as clearly unconstrained, and the 

poorest participant households were not as clearly constrained, as we hypothesized they 

might be. Using the measure of at-home food spending in a recent week, we can finally 

estimate the degree of constraint empirically. Figure 9 estimates the fraction of the 

sample that is extramarginal, using three increasingly permissive definitions of 

extramarginality: having weekly food spending below weekly benefits (where weekly 

benefits equal monthly benefits / 4.2), having weekly food spending below 1.2 times 

weekly benefits, and having weekly food spending below 1.4 times weekly benefits. As 

22
a function of total income, the fraction of the sample that was estimated to be constrained 

appeared fairly constant, instead of declining as total income increased. 

B. Away-from-home food spending. 

B1. Response to total resources. For both nonparticipant and participant households, in 

all three household types, actual weekly away-from-home food spending per adult 

equivalent (“away-from-home food spending,” for short) was much lower than the athome food spending levels reported in results section A above (Figure 8 and Table 4). 

For non-participant households, away-from-home food spending appeared in most cases 

to respond positively and steadily to increased total income. The single minor exception 

is that away-from-home food spending descended as total income increased for just the 

very poorest nonparticipants in household type (c) adults without children. 

For participant households, away-from-home food spending appeared to respond 

positively and steadily to increased total income for all three household types. 

In general, the Engel functions for away-from-home food spending were positively 

sloped as one would expect. To give a sense of the magnitude of the spending increase, 

for nonparticipants in household type (a) single adults with children, away-from-home 

food spending rose from about $5 for the poorest group (with monthly total income per 

adult equivalent $0-250) to almost $10 for a near-poor group (with total income $750-

1000) to about $17 for a middle-income group (with total income $2250-2500). 

B2. Response to program participation status. In all three household types, holding 

constant total income, away-from-home food spending was lower for the participant 

group than for the comparable nonparticipant group (Figure 8 and Table 4). For 

household type (c) adults without children, away-from-home food spending appeared to 

be greatly suppressed in the participant group, whereas the participant / nonparticipant 

difference was smaller but still noticeable for the other two household types. Without 

exception, the association between FSP participation and away-from-home food spending 

was negative. 

To give a sense of the modest magnitude of the FSP participation association, for 

household type (a) single adults with children, away-from-home food spending ranged 

from $1.90 to $3.60 lower for the participant group than for the nonparticipant group. A 

weekly $2.25 decrease in away-from-home food spending, for example, was equivalent 

to the decrease in food spending one saw as a nonparticipant household’s income fell 

modestly from poverty (with monthly total income per adult equivalent $500-750) to 

deep poverty (with total income $0-250). 

B3. Distinguishing the program effect. For all three household types, the appearance of 

suppressed away-from-home food spending in the participant group could indicate that 

FSP benefits encouraged at-home food spending at the expense of restaurant food 

spending (Figure 8 and Table 4). However, this suppression of away-from-home food 

23
spending was not systematically greater among participant households that one would 

expect to be constrained (with comparatively low total income), compared with 

participant households that one would expect to be unconstrained (with comparatively 

high total income in the near-poor range). 

C. The self-perceived food spending gap. 

The self-perceived food spending gap is the difference between the household’s usual 

food spending level and the spending level that the household reports would be adequate 

to meet its needs. 

The variable for weekly usual food spending per adult equivalent (“usual food spending,” 

for short) differs in a couple of respects from the at-home and away-from-home food 

spending variables discussed in the preceding subsections. First, usual food spending 

includes the sum of both at-home and away-from-home spending. Second, usual food 

spending reflects a typical weekly spending amount, whereas the results reported in the 

preceding subsections reflect actual food spending in the most recent week. 

The previous subsections noted that the association between FSP participation and food 

spending was very different for at-home and away-from-home food spending. In 

particular, FSP participation appeared to be associated with elevated at-home food 

spending and suppressed away-from-home food spending in the most recent week. 

Because usual food spending reflects the sum of these offsetting associations, the overall 

participant / nonparticipant differences in usual food spending are negligible and not 

directly helpful for understanding program effects (Figure 10 and Table 5). The usual 

food spending variable is addressed in this subsection only because of its role in the 

computation of the self-perceived food spending gap discussed below. 

Following the question about usual food spending, the household reported whether a 

minimum adequate level of food spending was lower or higher than usual food spending, 

and, if so, by what amount. These responses were used to construct a variable for selfperceived minimum required weekly food spending per adult equivalent (“minimum 

required food spending,” for short). While minimum required food spending for 

nonparticipants did rise as total income rose, the increase was not large (Figure 11 and 

Table 6). In general, nonparticipant households across a wide range of total income had 

fairly similar ideas on average about what amount of food spending was required. 

By contrast, for all three household types, minimum required food spending was higher 

for the participant group than for the nonparticipant group at the same level of total 

income. For household types (a) single adults with children and (b) multiple adults with 

children, this participant / nonparticipant difference was fairly small. For household type 

(c) adults without children, this participant / nonparticipant difference was larger. This 

pattern is consistent with the self-selection account of elevated food spending for 

program participants. The participant group appeared to have somewhat higher food 

spending needs. 

24
Results for the self-perceived food spending gap -- the difference between usual food 

spending and minimum required food spending -- is discussed in the remainder of this 

subsection (Figure 12 and Table 7). A negative value for the gap variable indicates selfperceived unmet needs. A positive value for the gap variable indicates usual food 

spending that exceeds self-perceived requirements. 

C1. Response to total resources. For nonparticipant households, in all three household 

types, the self-perceived food spending gap appeared to respond positively and steadily to 

increased total income (Figure 12). The minor exception is that, for household type (c) 

adults without children, the food spending gap was flat at low levels of total income. The 

general pattern of a rising food spending gap reflects the fact that the slope of the usual 

food spending function was steeper than the slope of the minimum required food 

spending function. In other words, even though minimum required food spending rose 

slightly as total income rose, usual food spending rose even faster, so higher income 

households were better able to exceed their food spending needs. 

Still focusing on nonparticipant households, it is interesting to note the total income level 

at which the food spending gap turned positive. Figure 12 illustrates this total income 

level as the horizontal value at which the food spending gap first crossed the horizontal 

axis. This total income threshold, which ranges from about $800 to $1400 per month per 

adult equivalent across the three household types, has been suggested by some as a type 

of poverty standard (Jensen, 2002; Andrews, Nord, and Kabbani, 2001). This total 

income threshold is the one at which nonparticipant households become able on average 

to meet their self-perceived requirement for food spending. 

For participant households, the food spending gap also appears to respond positively and 

steadily to increased total income. 

C2. Response to program participation status. In all three household types, holding 

constant total income, the food spending gap was lower (more negative) for the 

participant group than for the comparable nonparticipant group. For household types (a) 

single adults with children and (b) multiple adults with children, this participant / 

nonparticipant difference was comparatively small. For household type (c) adults 

without children, this participant / nonparticipant difference was larger. Without 

exception, the association between FSP participation and the ability to meet selfperceived food spending needs was negative. 

To give a sense of the large magnitude of the FSP participation association, for household 

type (a) single adults with children, the food spending gap ranged from $2.90 to $4.00 

lower for the participant group (which can be compared to usual food spending in the 

neighborhood of $40). For household type (c) adults without children, the 

participant/nonparticipant difference in the self-perceived food spending gap was even 

larger. 

As a consequence of the lower (more negative) food spending gap, the participant group 

in all three household types was on average unable to meets its self-perceived food 

25
spending even at the highest level of total income that participants achieved. In terms of 

the graphical illustration in Figure 12, the food spending gap function for participants 

never crossed the horizontal axis. In summary, holding constant total income, the 

participant group appeared less able than the nonparticipant group to meet its selfperceived food spending needs. 

C3. Distinguishing the program effect. The lower (more negative) food spending gap 

offered clear evidence of the self-selection pattern, in which households with greater food 

needs were more likely to participate in the program. Little hope of identifying the causal 

impact of FSP benefits on the food spending gap was provided by comparison of the 

participant/non-participant difference for participant households that one would expect to 

be constrained (with comparatively low total income) and those participant households 

that one would expect to be unconstrained (with comparatively high total income in the 

near-poor range). 

D. Household food security. 

D1. Response to total resources. As one would expect, for both nonparticipant and 

participant households, in all three household types, the 12-month prevalence for the 

“low or very low food security” and “very low food security” classifications appeared to 

fall as total income increased (Figure 13, Table 8, and Table 9). 

To give a sense of the large magnitude of the improvement in food security status, for 

nonparticipants in household type (a) single adults with children, the prevalence of “low 

or very low food security” status fell from about 40% for the poorest households (with 

total income $0-500) to 11% for a middle-income group (with total income $2250-2500). 

Similar results were seen when household food security status was defined based on 

survey questions with a reference period of the most recent 30 days (Figure 14, Table 10, 

and Table 11). Recall in these results that the 30-day category “very low food security” 

is a good analogue to the 12-month category with the same name, while the 30-day 

category “low or very low food security” is slightly less inclusive than the 12-month 

category by the same name, omitting some less-than-perfectly secure households with 

mild evidence of hardship. The 30-day food security status improved steadily as total 

income increased. 

D2. Response to program participation status. In all three household types, holding 

constant total income, the 12-month prevalence of “low or very low food security” status 

and “very low food security” status was dramatically higher for FSP participants (Figure 

13, Table 8, and Table 9). 

To give a sense of the large magnitude of the FSP participation association, for household 

type (a) single adults with children, the 12-month prevalence of “low or very low food 

security” status for near-poor participants (with monthly total income per adult equivalent 

$750-1000) was greater than the corresponding prevalence for any group of 

nonparticipants, even if they were in deep poverty (with total income $0-250). 

26
Likewise, using the 30-day measure, the prevalence of “low or very low food security” 

and the prevalence of “very low food security” were consistently higher for participants 

than for nonparticipants (Figure 14). In the case of household type (a) single adults with 

children, food security status was slightly worse for participants. In the case of 

household types (b) and (c), food security status was much worse for participants. 

D3. Distinguishing the program effect. The higher rates of food insecurity for program 

participants offered clear evidence of the self-selection pattern, in which households 

experiencing greater hardship were more likely to participate in the program (Figure 13, 

Table 8, and Table 9). Little hope of identifying the causal impact of FSP benefits on the 

food insecurity prevalence was provided by comparison of the participant/non-participant 

difference for participant households that one would expect to be constrained (with 

comparatively low total income) and those participant households that one would expect 

to be unconstrained (with comparatively high total income in the near-poor range). 

VIII. Results: Food Stamps, Food Spending, and Food Security Jointly 

The preceding section treated FSP participation and total income as explanatory 

variables, and it treated at-home food spending and household food security status 

separately as outcomes of interest. This section more explicitly treats at-home food 

spending as a vehicle by which resources and program participation might influence 

household food security status. 

As described in the methods section (Section V), we divided the participant and 

nonparticipant groups according to whether their at-home food spending was above or 

below the median value for all households. Thus, Figure 15 shows the cross-sectional 

relationship between rates of food insecurity and total income separately for “high food 

spenders” and “low food spenders” in the participant and nonparticipant categories. 

As in Section VII (D) previously, rates of food insecurity fell as total income rose. A 

single exception is just the highest part of the total income range for program participants 

in the household type (a) single adults with children. In general, greater total resources 

were strongly associated with improved household food security status. Likewise, as in 

Section VII (D) previously, FSP participation was associated with higher rates of having 

“low or very low food security.” 

 

However, for most household types and total income levels, food security status was not 

notably different for households with above-median and below-median at-home food 

spending (Figure 15). The similarity in food security status for high (above-median) and 

low (below-median) at-home food spenders was a consistent pattern for participant and 

nonparticipant groups in household types (b) and (c). The strong finding from this figure 

is that total income and program participation status appeared to matter much more than 

food spending level. In most cases, the rate of food insecurity differed only slightly for 

27
high food spenders and low food spenders, but was in all cases much higher for program 

participants than for nonparticipants. 

IX. Discussion

Implications for future research. Plotting Engel functions with total income (cash 

income plus food stamp benefits) as the key explanatory variable proved to be a fruitful 

way of comparing outcomes for participants and nonparticipants. In a sense, this 

approach combines appealing features of two approaches that have been most common in 

preceding research, participant/nonparticipant comparisons and regression analysis with 

cash income and FSP benefits as separate arguments. 

This Engel function approach can be closely tied to an economic model of household 

decision-making subject to a budget constraint with both cash income and a targeted food 

benefit. This theoretical model is an adaptation of the traditional neoclassical or 

Southworth approach (Section IV). Even though one cannot always classify a household 

deterministically as constrained (extramarginal) or unconstrained (inframarginal), one 

would still expect in general that the fraction of households who are constrained will be 

higher among those participants with the very lowest total income. 

In this study, as one would expect, FSP benefits represented a higher portion of the total 

budget for the poorest program participants. However, in the CPS data used here, the 

mean benefit amount did not fall with rising total income as one would expect based both 

on reading the official benefit formula and on separate estimates from Quality Control 

data (Section VI). Possible reasons include time mismatch between the underlying 

annual cash income data and the monthly food stamp benefit data, the lumpiness 

introduced by the categories of control card cash income, rounding error in reporting 

program benefits, and misreporting of either cash income or benefit information. This 

data limitation somewhat hindered this investigation’s hopes of using the modified 

theoretical model of household decision-making to generate new insight into the real 

effect of FSP participation, as distinguished from self-selection patterns. 

It remains an open question whether a similar analysis could achieve that hope using 

improved data. Because mismatch of reference periods is a leading candidate 

explanation for the difficulties encountered here, one recommendation is to collect survey 

data with the same monthly reference period for variables describing cash income, FSP 

benefits, food spending, minimum required food spending, and household food security 

status. Similarly, because respondent error in self-reporting cash income and FSP 

benefits is another candidate explanation for the difficulties encountered here, another 

recommendation for future research is to draw samples from a sampling frame of 

participants for whom the income variables can be corroborated from program records. 

The analysis supports a couple of other observations for future research. Because we 

found such divergent responses of at-home and away-from-home food spending to FSP 

participation, it seems advisable to continue to ask spending questions about these two 

28
resources separately. Indeed, an improvement in the CPS supplement instrument would 

retain the division between at-home and away-from-home food sources in the survey 

questions about usual food spending and minimum required food spending, making these 

questions more similar to the current questions about at-home and away-from-home food 

spending in the past week. This research confirms that the “food spending gap” between 

minimum required food spending and usual food spending may offer insight into the 

relationship between FSP participation, food spending, and food security. However, this 

insight was blurred in the present study by the fact that “usual” food spending from all 

sources appeared to have little association with FSP participation. That lack of 

association is not because food stamps have little relationship to food spending; rather, it 

appears to be because the positive association between FSP participation and at-home 

food spending was partially canceled by the negative association between FSP 

participation and away-from-home food spending. Because food stamps may only be 

used for at-home food spending, and had only a small association with combined food 

spending from all sources, a “food spending gap” based on the difference between 

minimum required at-home food spending and usual at-home food spending might have 

offered more clear information about program effects. 

Principal conclusions. This research permits us to draw several conclusions. 

First, at-home food spending in a recent week increased with total income (cash income 

plus food stamp benefits). This pattern was found for all three household types and for 

both participant and nonparticipant groups. See results section VII.A1. 

Second, at-home food spending in a recent week was higher for FSP participants than for 

nonparticipants, even after controlling for total income. This finding is consistent with a 

beneficial impact of food stamp participation on at-home food spending, related to the 

targeted nature of food stamp benefits and exceeding the effect that one would attribute 

simply to the increased total resources provided by food stamp benefits. See results 

section VII.A2. 

Third, away-from-home food spending in a recent week was lower for FSP participants 

than for nonparticipants. This finding is consistent with a potentially healthful impact of 

food stamps in promoting at-home food spending in place of away-from-home food 

spending. This result is notable, given that the program increases total household 

resources, and hence one could easily imagine the FSP would have tended to raise 

spending on any normal good. See results section VII.B2. 

Fourth, despite the raised at-home food spending in a recent week, FSP participants had 

little increase in usual food spending from all sources combined. Furthermore, the “food 

spending gap” between usual food weekly spending and self-perceived minimum 

required weekly food spending suggests that participants perceived a greater shortfall in 

their food budget than did nonparticipants even at the same low levels of total income. 

This observation of food budget shortfalls for FSP participants is corroborated by the 

food security outcomes discussed below. See results section VII.C2. 

29
Fifth, rates of food insecurity fell with increased total resources, as one would expect. 

This pattern was observed whether one looked at the rates of “low or very low food 

security” or just “very low food security,” and whether one used the 12-month or 30-day 

food security measures. It was observed for all three household types and for both the 

participant and nonparticipant groups. See results section VII.D1. 

Sixth, FSP participants had much higher rates of food insecurity compared with 

nonparticipants at the same levels of total income, presumably due to a self-selection 

pattern in which those households with greater hardship were more likely to seek 

program benefits for which they were eligible. While the national rate of “low or very 

low food security” among all U.S. households was about 11% in 2005, the comparable 

rates for FSP participants with the lowest levels of total income reached higher than 55% 

for all three household types. See results section VII.D2. 

A key hypothesis motivating this study was that the very poorest FSP participants, in 

terms of total income, would be most constrained (or extramarginal) in their household 

budget, and hence they would benefit from raised levels of at-home food spending 

supported by the maximum food stamp benefit, perhaps leading to lower rates of 

household food insecurity. This hypothesis could not be confirmed in this analysis. 

Instead, rates of food insecurity for low-income FSP participants are very high, reflecting 

serious hardship for the participant group. This self-selection pattern, in which 

households that experience hardship are more likely to participate in the Food Stamp 

Program, made it difficult to determine true program effects using cross-sectional data in 

this analysis. 

Seventh, the high rates of food insecurity for low-income participant households were 

noted regardless of whether these households had above-median or below-median athome food spending. Holding constant total resources, having above-median at-home 

food spending might nevertheless contribute to other food-related goals that were beyond 

the scope of this study, such as improved diet quality. However, for most household 

types and total income levels, having above-median at-home food spending did not 

appear to suffice on its own to produce improved household food security. See results 

section VIII. 

In conclusion, FSP participation is associated with suppressed away-from-home food 

spending and with an increase in at-home food spending beyond what can be attributed to 

the cash value of the program benefits. Yet, these higher at-home food spending levels 

do not automatically imply improved food security outcomes. Cross-sectional 

comparisons of food security outcomes for participants and nonparticipants are 

dominated by self-selection effects. Holding constant total income, rates of food 

insecurity remain higher for program participants than for nonparticipants. 

30
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[cited 2006 Sep 27]. Available from: 

http://www.whitehouse.gov/omb/expectmore/summary.10001007.2005.html. 

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Wilde PE. “The Food Stamp Benefit Formula: Implications for Empirical Research on 

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2000; 82:200-213. 
5

10

15

20

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Year

Prevalence of Very Low Food Security (%) 

Nonparticipants

All Low-Income Households

Food Stamp Program Participants

Figure 1. Changes over time in the prevalence of very low household food security for 

FSP participant households, low-income nonparticipant households, and all low-income 

households (below 130 percent of the poverty line). 

Source: Annual USDA food security reports (Nord, Andrews and Carlson, 2006). 
0

20

40

60

80

100

120

140

0 200 400 600 800 1000 1200 1400 1600 1800 2000

Monthly total income (cash plus food stamps)

Weekly FSP Benefit (monthly benefit / 4.2)

Figure 2. The food stamp benefit formula, showing average weekly food stamp benefits 

(monthly benefits / 4.2) at each level of total income (cash plus food stamps). 
0

20

40

60

80

100

120

140

0 500 1000 1500 2000

Monthly total income (cash plus food stamps)

Weekly Food Spending

Nonparticipant Participant (Southworth theory)

constrained unconstrained ineligible 

Figure 3. Engel functions for FSP participants and nonparticipants under the traditional 

Southworth theory, which stipulates distinct food spending behavior for constrained and 

unconstrained participants. 
0

20

40

60

80

100

120

140

0 500 1000 1500 2000

Monthly total income (cash plus food stamps)

Weekly Food Spending

Nonparticipant Participant (Southworth theory) Participant (adapted theory)

constrained unconstr. ineligible 

Figure 4. Engel functions for FSP participants and nonparticipants under the adapted 

theory, which is similar to the Southworth theory but allows for some cash spending on 

food even in constrained households. 
0

20

40

60

80

100

120

140

0 500 1000 1500 2000

Monthly total income (cash plus food stamps)

Weekly Food Spending

Nonparticipant Participant (Southworth theory) Participant (with self-selection)

constrained unconstrained ineligible 

Figure 5. Engel functions for FSP participants and nonparticipants under a model of 

self-selection, which is similar to the Southworth theory but allows participants to have 

higher preferences for food than nonparticipants have. 
(a) One adult with children 

0

20

40

60

80

100

120

140

160

0 200 400 600 800 1000 1200 1400

Real monthly total income per adult male equivalent

Real monthly food stamp benefit amount 

per adult male equivalent

(b) Two adults with children 

0

20

40

60

80

100

120

140

160

0 200 400 600 800 1000 1200 1400

Real monthly total income per adult male equivalent

Real monthly food stamp benefit amount 

per adult male equivalent

(c) No children 

0

20

40

60

80

100

120

140

160

0 200 400 600 800 1000 1200 1400

Real monthly total income per adult male equivalent

Real monthly food stamp benefit amount 

per adult male equivalent

y p q

Participants (QC) Participants (CPS)

Figure 6. Monthly food stamp benefits as a function of monthly total income (cash plus 

food stamps), in Quality Control data (QC) and the Current Population Survey (CPS) 
(a) One adult with children 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 200 400 600 800 1000 1200 1400

Real monthly total income per adult male equivalent

Real monthly food stamp benefit / real monthly total 

income per adult male equivalent 

(b) Two adults with children 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 200 400 600 800 1000 1200 1400

Real monthly total income per adult male equivalent

Real monthly food stamp benefit / real monthly total 

income per adult male equivalent 

(c) No children 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 200 400 600 800 1000 1200 1400

Real monthly total income per adult male equivalent

Real monthly food stamp benefit / real monthly total 

income per adult male equivalent 

y p q

Participants (QC) Participants (CPS)

Figure 7. Monthly food stamp benefits as a percentage of monthly total income (cash 

plus food stamps), in the Current Population Survey (CPS) and Quality Control data 

(QC). 
(a) One adult with children 

0

10

20

30

40

50

60

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Real weekly food spending (2003 dollars) 

per adult male equivalent

(b) Two adults with children 

0

10

20

30

40

50

60

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Real weekly food spending (2003 dollars) 

per adult male equivalent

(c) No children 

0

10

20

30

40

50

60

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Real weekly food spending (2003 dollars) 

per adult male equivalent

Nonparticipants (home) Nonparticipants (away) Participants (home) Participants (away)

Figure 8. Weekly food spending at-home and away-from-home as a function of monthly 

total income (cash plus food stamps), by FSP participation status. 
(a) One adult with children 

0%

10%

20%

30%

40%

50%

60%

70%

0 100 200 300 400 500 600 700 800 900

Real monthly total income (2003 dollars) per adult male equivalent

Percent at each constraint level

(b) Two adults with children 

0%

10%

20%

30%

40%

50%

60%

70%

0 100 200 300 400 500 600 700 800 900

Real monthly total income (2003 dollars) per adult male equivalent

Percent at each constraint level

(c) No children 

0%

10%

20%

30%

40%

50%

60%

70%

0 200 400 600 800 1000 1200 1400 1600

Real monthly total income (2003 dollars) per adult male equivalent

Percent at each constraint level

< mbenefit*100% < mbenefit*120% < mbenefit*140%

Figure 9. Percentage of participant households that appears to be extramarginal, using 3 

definitions of extramarginal: (i) food spending less than 100% of benefits, (ii) food 

spending less than 120% of benefits, and (iii) food spending less than 140% of benefits. 
(a) One adult with children 

0

10

20

30

40

50

60

70

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Real weekly usual food spending (2003 dollars) 

per adult male equivalent

(b) Two adults with children 

0

10

20

30

40

50

60

70

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Real weekly usual food spending (2003 dollars) 

per adult male equivalent

(c) No children 

0

10

20

30

40

50

60

70

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Real weekly usual food spending (2003 dollars) 

per adult male equivalent

Nonparticipants Participants

Figure 10. Weekly usual food spending as a function of monthly total income (cash plus 

food stamps), by FSP participation status. 
(a) One adult with children 

0

10

20

30

40

50

60

70

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Minimal weekly food spending (2003 dollars) for 

adequate food supply per adult male equivalent

(b) Two adults with children 

0

10

20

30

40

50

60

70

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Minimal weekly food spending (2003 dollars) for 

adequate food supply per adult male equivalent

(c) No children 

0

10

20

30

40

50

60

70

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Minimal weekly food spending (2003 dollars) for 

adequate food supply per adult male equivalent

Nonparticipants Participants

Figure 11. Weekly self-perceived minimum needed food spending as a function of 

monthly total income (cash plus food stamps), by FSP participation status. 
(a) One adult with children 

-15

-10

-5

0

5

10

15

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Difference between usual and minmal weekly food 

spending (2003 dollars)per adult male equivalent

(b) Two adults with children 

-15

-10

-5

0

5

10

15

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Difference between usual and minmal weekly food 

spending (2003 dollars)per adult male equivalent

(c) No children 

-15

-10

-5

0

5

10

15

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Difference between usual and minmal weekly food 

spending (2003 dollars)per adult male equivalent

Nonparticipants (home) Nonparticipants (away) Participants (home) Participants (away)

Figure 12. Difference between mean usual and self-perceived minimal weekly food 

spending (2003 dollars per week) necessary to meet food needs, as a function of total 

income (cash plus food stamps), by FSP participation status. 
(a) One adult with children 

0%

10%

20%

30%

40%

50%

60%

0 500 1000 1500 2000 2500

 Real monthly total income (2003 dollars) per adult male equivalent

Percent with low and very low food security

(b) Two adults with children 

0%

10%

20%

30%

40%

50%

60%

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Percent with low and very low food security

(c) No children 

0%

10%

20%

30%

40%

50%

60%

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Percent with low and very low food security

Nonparticipants (low or very low food security) Nonparticipants (very low food security)

Participants (low or very low food security) Participants (very low food security)

Figure 13. Percent classified as having “low or very low food security” and having 

“very low food security” in the past 12 months, as a function of total income (cash plus 

food stamps), by FSP participation status. 
(a) One adult with children 

0%

10%

20%

30%

40%

0 500 1000 1500 2000 2500

 Real monthly total income (2003 dollars) per adult male equivalent

Percent with low and very low food security

(b) Two adults with children 

0%

10%

20%

30%

40%

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Percent with low and very low food security

(c) No children 

0%

10%

20%

30%

40%

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Percent with low and very low food security

Nonparticipants (low or very low food security) Nonparticipants (very low food security)

Participants (low or very low food security) Participants (very low food security)

Figure 14. Percent classified as having “low or very low food security” and having 

“very low food security” in the past 30 days, as a function of total income (cash plus food 

stamps), by FSP participation status. 
(a) One adult with children 

0%

10%

20%

30%

40%

50%

60%

70%

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Percent with low or very low food security

(b) Two adults with children 

0%

10%

20%

30%

40%

50%

60%

70%

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Percent with low or very low food security

(c) No children 

0%

10%

20%

30%

40%

50%

60%

70%

0 500 1000 1500 2000 2500

Real monthly total income (2003 dollars) per adult male equivalent

Percent with low or very low food security

nonparticipants (high) nonparticipants (low) participants (high) participants (low)

Figure 15. Percent classified as having low or very low food security, as a function of 

total income (cash plus food stamps), by both food spending status (higher or lower than 

median food spending) and FSP participation status. 
Table 1: Characteristics1 for Food Stamp Program participants and nonparticipants 

Household type Single adult with children Two adults with children Adu

Participants 

Nonparticipants Participants Non- participants Particip

Number of households 2842 9656 2292 33463 Real total monthly income per AME (mean) 

468.75 1265.40 492.46 1177.54 7

Real monthly cash income per AME (mean) 

355.58 1265.40 413.81 1177.54 6

Real monthly food stamp benefit per AME (mean) 

113.17 0 78.65 0 

Number of household members (mean) 

3.1 2.6 4.2 3.9 

% households with one or more members elderly (age > 60 years) 

1.8 2.4 7.1 4.1 

% interviewees at least High School graduate or GED 

68.4 86.9 60.7 85.8 

1 Mean and percent using survey weights. Analysis restricted to household observations where real total income was not m
Table 2: Mean food stamp benefit as a function of mean total income according to self reports in the Current Popula

Mean benefit1

% of total 

income Mean benefit1

% of total 

income Mean benefit

94.7 48.7% 80.5 45.2% 53

- 118.8 34.7% 76.8 21.2% 9- 113.0 19.1% 75.8 12.7% 63- 117.1 13.8% 79.2 9.4% 8- -- -- -- -- 84- -- -- -- -- 83

1 Mean food stamp benefit amount (2003 dollars per month) per adult male equivalent, weighted.

2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

1,250 <1,500

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

1,000

Note: Table cells are excluded where sample size < 200. Standard errors for this table, without correction for complex survey 

in Appendix Table A1.

Total Income Category2

< 250

250 < 500500 < 750

<1,250

750 <1,000
Table 3: At-home food spending in previous week for Food Stamp Program participants and nonparticipants

At-home food s

pendin

g in 

previous wee

k 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 37.37 31.69 35.31 28.46 36.

250 - < 500 46.22 33.46 31.59 28.18 41.500 - < 750 42.16 33.32 32.91 28.98 41.750 - <1,000 45.60 37.12 35.07 31.10 46.

1,000 - <1,250 -- 37.85 -- 33.01 47.1,250 - <1,500 -- 41.44 -- 35.61 53.1,500 - <1,750 -- 40.74 -- 36.37 -- 1,750 - <2,000 -- 43.42 -- 37.71 -- 2,000 - <2,250 -- 45.40 -- 39.68 -- 

2,250 - <2,500 -- 49.46 -- 41.78 -- 

1 Mean at-home food spending (2003 dollars per week) per adult male equivalent, using survey weights.

2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 200. Standard errors for this table, without correction for complex survey 

in Appendix Table A2.
Table 4: Away-from-home food spending in previous week for Food Stamp Program participants and nonparticipan

Awa

y-from-home food s

pendin

g in 

previous wee

k 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 3.00 5.00 2.37 4.55 2.

250 - < 500 3.96 5.86 2.91 4.62 2.500 - < 750 5.00 7.28 4.37 5.88 3.750 - <1,000 6.09 9.64 6.13 8.06 3.

1,000 - <1,250 -- 10.56 -- 9.56 3.1,250 - <1,500 -- 12.76 -- 11.30 4.1,500 - <1,750 -- 14.29 -- 12.30 -- 1,750 - <2,000 -- 18.34 -- 13.75 -- 2,000 - <2,250 -- 17.31 -- 14.67 -- 

2,250 - <2,500 -- 17.44 -- 15.98 -- 

1 Mean away-from-home food spending (2003 dollars per week) per adult male equivalent, using survey weights.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 200. Standard errors for this table, without correction for complex survey 

in Appendix Table A3.
Table 5: Usual food spending for Food Stamp Program participants and nonparticipants

Usual food s

pendin

g

 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 38.21 37.16 32.22 32.51 36.

250 - < 500 42.17 39.22 30.97 32.03 42.500 - < 750 40.39 38.38 33.00 33.79 42.750 - <1,000 41.85 43.19 34.67 36.53 48.

1,000 - <1,250 -- 44.76 -- 38.69 51.1,250 - <1,500 -- 49.16 -- 41.89 51.1,500 - <1,750 -- 48.38 -- 43.33 -- 1,750 - <2,000 -- 52.95 -- 46.09 -- 2,000 - <2,250 -- 56.41 -- 48.44 -- 

2,250 - <2,500 -- 60.58 -- 50.93 -- 

1 Mean usual food spending food spending (2003 dollars per week) per adult male equivalent, using survey weights.

2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 200. Standard errors for this table, without correction for complex survey 

in Appendix Table A4.
Table 6: Self-perceived minimum required food spending for Food Stamp Program participants and nonparticipants

Minimal weekl

y food s

pendin

g for ade

quate food supply 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 48.24 44.58 39.56 36.13 51.

250 - < 500 50.22 44.28 36.90 35.41 56.500 - < 750 48.55 42.26 37.39 35.67 57.750 - <1,000 49.06 46.66 35.87 36.27 61.

1,000 - <1,250 -- 45.80 -- 36.63 63.1,250 - <1,500 -- 49.23 -- 38.20 60.1,500 - <1,750 -- 45.10 -- 38.44 -- 1,750 - <2,000 -- 51.05 -- 40.35 -- 2,000 - <2,250 -- 53.31 -- 41.74 -- 

2,250 - <2,500 -- 54.15 -- 43.36 -- 

1 Mean self-perceived minimum required food spending food spending (2003 dollars per week) per adult male equivalent, we2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 160. Standard errors for this table, without correction for complex survey 

in Appendix Table A5.
Table 7: The food spending gap, usual minus minimum required food spending for FSP participants and nonparticip

Usual minus minimum re

quired weekl

y food s

pendin

g

 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 -9.72 -6.40 -7.23 -3.41 -13.

250 - < 500 -8.24 -4.48 -6.30 -3.44 -13.

500 - < 750 -8.56 -4.54 -4.19 -2.10 -14.

750 - <1,000 -6.55 -3.70 -1.11 0.10 -13.

1,000 - <1,250 -- -1.40 -- 1.71 -12.

1,250 - <1,500 -- -1.34 -- 3.40 -9.

1,500 - <1,750 -- 2.89 -- 4.45 -- 1,750 - <2,000 -- 1.27 -- 5.50 -- 2,000 - <2,250 -- 2.44 -- 6.50 -- 

2,250 - <2,500 -- 4.86 -- 6.91 -- 

1 Usual minus minimum required food spending food spending (2003 dollars per week) per adult male equivalent, weighted.

2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 160. Standard errors for this table, without correction for complex survey 

in Appendix Table A6.
Table 8: Percent with low or very low food security in the past 12 months, for Food Stamp Program participants and 

Percent with low or ver

y low food securit

y in the 

past 12 months 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 55.4 39.5 57.3 33.9 59

250 - < 500 52.1 41.3 54.3 35.3 52500 - < 750 51.2 38.5 51.3 26.8 5750 - <1,000 51.2 32.3 37.5 19.2 44

1,000 - <1,250 -- 28.0 -- 12.0 431,250 - <1,500 -- 21.0 -- 8.0 471,500 - <1,750 -- 19.0 -- 5.0 -- 1,750 - <2,000 -- 18.0 -- 5.0 -- 2,000 - <2,250 -- 13.0 -- 4.0 -- 

2,250 - <2,500 -- 11.0 -- 2.0 -- 

1 Using survey weights.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 200. Standard errors for this table, without correction for complex survey 

in Appendix Table A7.
Table 9: Percent with very low food security in the past 12 months, for Food Stamp Program participants and nonpa

Percent with ver

y low food securit

y in the 

past 12 months 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 19.1 13.8 16.9 9.6 3

250 - < 500 15.9 10.0 16.7 8.5 28500 - < 750 15.1 10.4 13.3 5.0 27750 - <1,000 13.1 9.6 9.1 3.5 22

1,000 - <1,250 -- 7.0 -- 2.0 221,250 - <1,500 -- 5.0 -- 1.0 21,500 - <1,750 -- 6.0 -- 1.0 -- 1,750 - <2,000 -- 4.0 -- 1.0 -- 2,000 - <2,250 -- 4.0 -- 1.0 -- 

2,250 - <2,500 -- 3.0 -- 1.0 -- 

1 Using survey weights.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 200. Standard errors for this table, without correction for complex survey 

in Appendix Table A8.
Table 10: Percent with low or very low food security in the past 30 days, for Food Stamp Program participants and n

Percent with low or ver

y low food securit

y in the 

past 30 days 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 19.3 16.5 19.9 12.6 36

250 - < 500 21.4 18.4 20.8 11.4 28500 - < 750 16.6 14.8 16.3 8.2 30750 - <1,000 14.6 12.9 12.4 6.5 23

1,000 - <1,250 -- 12.0 -- 4.0 221,250 - <1,500 -- 9.0 -- 2.0 201,500 - <1,750 -- 8.0 -- 2.0 -- 1,750 - <2,000 -- 7.0 -- 1.0 -- 2,000 - <2,250 -- 7.0 -- 2.0 -- 

2,250 - <2,500 -- 5.0 -- 1.0 -- 

1 Using survey weights. This 30-day measure may undercount households with mild levels of food insecurity.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 160. Standard errors for this table, without correction for complex survey 

in Appendix Table A9.
Table 11: Percent with very low food security in the past 30 days, for Food Stamp Program participants and nonpart

Percent with ver

y low food securit

y in the 

past 30 days 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 12.3 11.5 11.6 7.4 23

250 - < 500 11.3 10.3 11.3 5.9 19500 - < 750 10.0 9.2 10.0 4.2 19750 - <1,000 8.4 8.3 8.5 3.4 15

1,000 - <1,250 -- 6.0 -- 2.0 151,250 - <1,500 -- 5.0 -- 1.0 121,500 - <1,750 -- 5.0 -- 1.0 -- 1,750 - <2,000 -- 4.0 -- 1.0 -- 2,000 - <2,250 -- 2.0 -- 1.0 -- 

2,250 - <2,500 -- 3.0 -- 1.0 -- 

1 Using survey weights. 2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 160. Standard errors for this table, without correction for complex survey 

in Appendix Table A10.
Table A1: Unadjusted standard errors for Table 2, mean food stamp benefit as a function of total income, Current Po

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2

SE of mean 

benefit1

SE of benefits as 

% of total 

income

SE of mean 

benefit1

SE of benefits as 

% of total 

income

SE of mean 

benefit1

< 250 1.74 0.725 1.76 0.858 2.

250 - < 500 1.44 0.487 1.14 0.344 1.500 - < 750 2.07 0.363 1.64 0.281 1.

750 - <1,000 3.96 0.476 2.46 0.294 1.

1,000 - <1,250 -- -- -- -- 2.

1,250 - <1,500 -- -- -- -- 5.

1 Mean food stamp benefit amount (2003 dollars per month) per adult male equivalent. Standard errors are unweighted.

2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale
Table A2: Unadjusted standard errors for Table 3, at-home food spending for FSP participants and nonparticipants

Standard error of at-home food s

pendin

g in 

previous wee

k 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 1.43 1.59 1.34 0.77 2.

250 - < 500 1.07 0.95 0.86 0.42 1.500 - < 750 1.39 0.72 1.14 0.30 1.750 - <1,000 2.48 0.86 1.75 0.30 1.

1,000 - <1,250 -- 0.90 -- 0.32 1.1,250 - <1,500 -- 0.93 -- 0.34 3.1,500 - <1,750 -- 0.98 -- 0.34 -- 1,750 - <2,000 -- 1.22 -- 0.49 -- 2,000 - <2,250 -- 1.53 -- 0.57 -- 

2,250 - <2,500 -- 1.70 -- 0.87 -- 

1 Standard error of at-home food spending (2003 dollars per week) per adult male equivalent, unweighted.

2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 200. 
Table A3: Unadjusted standard errors for Table 4, away-from-home food spending for FSP participants and nonpart

Standard error of awa

y-from-home food s

pendin

g in 

previous wee

k 

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 0.26 0.41 0.22 0.30 0.

250 - < 500 0.18 0.29 0.15 0.17 0.500 - < 750 0.28 0.28 0.30 0.13 0.750 - <1,000 0.67 0.37 0.53 0.14 0.

1,000 - <1,250 -- 0.33 -- 0.15 0.1,250 - <1,500 -- 0.43 -- 0.17 1.1,500 - <1,750 -- 0.53 -- 0.19 -- 1,750 - <2,000 -- 0.93 -- 0.27 -- 2,000 - <2,250 -- 0.74 -- 0.38 -- 

2,250 - <2,500 -- 0.98 -- 0.52 -- 

1 Standard error of away-from-home food spending (2003 dollars per week) per adult male equivalent, unweighted.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale

Note: Table cells are excluded where sample size < 200. 
Table A4: Unadjusted standard errors for Table 5, usual food spending for FSP participants and nonparticipants

Standard error of usual food s

pendin

g

 1

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 1.13 1.49 0.97 0.73 1.

250 - < 500 0.79 0.83 0.61 0.36 1.500 - < 750 1.05 0.60 0.90 0.28 1.750 - <1,000 1.92 0.71 1.10 0.26 1.

1,000 - <1,250 -- 0.74 -- 0.26 1.1,250 - <1,500 -- 0.85 -- 0.29 2.1,500 - <1,750 -- 0.92 -- 0.33 -- 1,750 - <2,000 -- 1.10 -- 0.44 -- 2,000 - <2,250 -- 1.26 -- 0.59 -- 

2,250 - <2,500 -- 1.67 -- 0.76 -- 

1 Standard error of usual food spending food spending (2003 dollars per week) per adult male equivalent, unweighted.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale
Table A5: Unadj. standard errors for Table 6, self-perceived minimum required food spending for FSP participants a

Standard error of selfperceived minimum re

quired weekl

y food s

pendi

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 1.92 1.78 1.32 0.94 2.

250 - < 500 1.05 1.08 1.02 0.47 1.500 - < 750 1.37 0.82 1.11 0.35 1.750 - <1,000 2.82 0.93 1.30 0.32 1.

1,000 - <1,250 -- 0.96 -- 0.31 2.1,250 - <1,500 -- 1.11 -- 0.33 3.1,500 - <1,750 -- 1.03 -- 0.39 -- 1,750 - <2,000 -- 1.38 -- 0.49 -- 2,000 - <2,250 -- 1.42 -- 0.68 -- 

2,250 - <2,500 -- 1.72 -- 0.94 -- 

1 Standard error of self-perceived minimum required weekly food spending (2003 dollars per week) per adult male equivalent

2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale
Table A6: Standard errors for Table 7, the food spending gap for Food Stamp Program participants and nonparticipa

Standard error of minimal weekl

y food s

pendin

g for ade

quate food sup

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 1.25 1.02 0.75 0.62 1.

250 - < 500 0.65 0.62 0.66 0.31 1.500 - < 750 0.81 0.54 0.67 0.21 0.750 - <1,000 1.57 0.60 0.79 0.18 0.

1,000 - <1,250 -- 0.56 -- 0.18 1.1,250 - <1,500 -- 0.68 -- 0.20 1.1,500 - <1,750 -- 0.60 -- 0.22 -- 1,750 - <2,000 -- 0.93 -- 0.30 -- 2,000 - <2,250 -- 0.81 -- 0.42 -- 

2,250 - <2,500 -- 0.92 -- 0.57 -- 

1 Standard error of mean self-perceived minimum required food spending food spending (2003 dollars per week) per adult maunweighted.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale
Table A7: Standard errors for Table 8, percent with low or very low food security in the past 12 months

Standard error of 

percent with low or ver

y low food securit

y in the 

past 12 

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 2.3 2.4 2.4 1.7 3

250 - < 500 1.4 1.7 1.6 1.0 500 - < 750 1.9 1.4 2.3 0.7 750 - <1,000 3.5 1.4 3.0 0.6 

1,000 - <1,250 -- 1.3 -- 0.5 21,250 - <1,500 -- 1.4 -- 0.4 31,500 - <1,750 -- 1.5 -- 0.4 -- 1,750 - <2,000 -- 1.5 -- 0.4 -- 2,000 - <2,250 -- 1.5 -- 0.5 -- 

2,250 - <2,500 -- 1.6 -- 0.5 -- 

1 Unweighted.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale
Table A8: Standard errors for Table 9, percent with very low food security in the past 12 months

Standard error of 

percent with ver

y low food securit

y in the 

past 12 mon

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 1.8 1.7 1.9 1.1 3

250 - < 500 1.0 1.0 1.2 0.6 500 - < 750 1.4 0.9 1.5 0.4 750 - <1,000 2.4 0.8 1.8 0.3 

1,000 - <1,250 -- 0.8 -- 0.2 1,250 - <1,500 -- 0.7 -- 0.2 21,500 - <1,750 -- 0.9 -- 0.1 -- 1,750 - <2,000 -- 0.9 -- 0.1 -- 2,000 - <2,250 -- 0.8 -- 0.2 -- 

2,250 - <2,500 -- 0.8 -- 0.2 -- 

1 Unweighted.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale
Table A9: Standard errors for Table 10, percent with low or very low food security in the past 30 days

Standard error of 

percent with low or ver

y low food securit

y in the 

past 30 

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 2.1 2.1 2.3 1.3 3

250 - < 500 1.3 1.5 1.5 0.8 500 - < 750 1.7 1.2 1.8 0.5 750 - <1,000 2.9 1.1 2.4 0.4 

1,000 - <1,250 -- 1.1 -- 0.3 21,250 - <1,500 -- 1.1 -- 0.2 31,500 - <1,750 -- 1.2 -- 0.2 -- 1,750 - <2,000 -- 1.2 -- 0.2 -- 2,000 - <2,250 -- 1.1 -- 0.3 -- 

2,250 - <2,500 -- 1.2 -- 0.4 -- 

1 Unweighted.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale
Table A10: Standard errors for Table 11, percent with very low food security in the past 30 days

Standard error of 

percent with ver

y low food securit

y in the 

past 30 da

Household typ

e Single adult with childre

n Two adults with childre

n Adult(s

Total Income Category2 Participants Non-participants Participants Non-participants Participants 

< 250 1.7 1.8 1.9 1.0 3

250 - < 500 1.0 1.2 1.2 0.6 500 - < 750 1.4 1.0 1.4 0.4 750 - <1,000 2.2 0.9 2.1 0.3 

1,000 - <1,250 -- 0.8 -- 0.2 1,250 - <1,500 -- 0.9 -- 0.2 21,500 - <1,750 -- 0.9 -- 0.2 -- 1,750 - <2,000 -- 0.9 -- 0.2 -- 2,000 - <2,250 -- 0.7 -- 0.3 -- 

2,250 - <2,500 -- 0.9 -- 0.3 -- 

1 Unweighted.2 Total income (2003 dollars per month) = (cash income per year/12 + food stamp benefits per month) per adult male equivale