United States 

Department of 

Agriculture

Economic

Research

Service

Economic

Research

Report

Number 85

October 2009

Mark Nord

Anne Marie Golla

Does SNAP Decrease 

Food Insecurity?

Untangling the Self-Selection Effect

0

5

10

15

20

25

-12 -10 -8 -6 -4 8 6 4 10 12

Very low food security 

before SNAP

-2 2 0

Intial receipt of SNAP benefits

Percent of households

Months

Very low food security 

while receiving SNAP
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Cataloging Record:

Nord, Mark

Does SNAP decrease food insecurity? :untangling the self-selection 

effect.

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

Economic Research Service); no. 85)

 1. Supplemental Nutrition Assistance Program (U.S.)—Evaluation. 

 2. Food relief--United States.

 3. Food security—United States—Measurement. 

 I. Golla, Anne Marie.

 II. United States. Dept. of Agriculture. Economic Research Service. 

 III. Title.

HV696.F6

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United States

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A Report from the Economic Research Service

Abstract

Self-selection by more food-needy households into the Supplemental Nutrition 

Assistance Program (SNAP, formerly called the Food Stamp Program) makes it diffi cult to observe positive effects of the program in survey data. This study investigates 

self-selection and ameliorative program effects by examining households’ food security 

month by month for several months prior to initial receipt of SNAP benefi ts and for 

several months after joining the program.Two-year panels are constructed by matching the same households interviewed in the Current Population Survey Food Security 

Supplement in 2 consecutive years using data from 2001 to 2006. Food security is 

observed to deteriorate in the 6 months prior to beginning to receive SNAP benefi ts and 

to improve shortly after. The results clearly demonstrate the self-selection by households 

into SNAP at a time when they are more severely food insecure. The results are consistent with a moderate ameliorative effect of SNAP—reducing the prevalence of very low 

food security among recent entrants by about one-third—although they do not conclusively demonstrate that extent of amelioration.

Keywords: food insecurity, food stamps, food security, hunger, very low food security, 

SNAP, longitudinal analysis

Mark Nord is a sociologist in the Food Economics Division, Economic Research Service, 

U.S. Department of Agriculture. Anne Marie Golla is an economist at the International 

Center for Research on Women (ICRW).

Acknowledgments

The authors thank Constance Newman and Mark Prell, Economic Research Service; 

Colleen Hefl in, Assistant Professor, Truman School of Public Affairs, University of 

Missouri; David Holben, Professor, School of Human and Consumer Sciences, Ohio 

University; James C. Ohls, retired, Mathematica Policy Research, Inc.; and Charles 

Hallahan, statistician, ERS, for their comments on the report. Also, thanks to Dale Simms 

and Wynnice Pointer-Napper of ERS for editing and design assistance.

Mark Nord, marknord@ers.usda.gov

Anne Marie Golla

Does SNAP Decrease 

Food Insecurity?

Untangling the Self-Selection Effect

Economic

Research 

Report

Number 85

October 2009
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Contents

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

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Previous Research on SNAP and Food Security. . . . . . . . . . . . . . . . . . . . 4

Needed: More Detailed Information on the Timing 

 of Food Insecurity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Data and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

 Two-Year Panel Construction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

 Identifying the Beginning of SNAP Spells. . . . . . . . . . . . . . . . . . . . . . . . 7

 Assessing Food Security During the 30 Days Ending 

 in Mid-December. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

 Analytic Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Findings. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Recommended citation format for this publication:

Nord, Mark, and Anne Maria Golla. Does SNAP Decrease Food Insecurity? 

Untangling the Self-Selection Effect. Economic Research Report No. 85, U.S. 

Dept. of Agriculture, Economic Research Service. Oct. 2009.
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Summary

The Supplemental Nutrition Assistance Program (SNAP), formerly the Food 

Stamp Program, is the largest Federal food assistance program, serving over 

28 million households monthly in 2008. This study examines households’ 

food security (their access to adequate food for active healthy living) month 

by month just prior to and just after SNAP entry in order to estimate the 

infl uence of benefi ts on the food security of recipient households.

What Is the Issue?

SNAP benefi ts are intended to increase the access of eligible low-income 

households to food and a nutritious diet—to improve their food security. 

However, it has proven diffi cult to demonstrate this positive effect or estimate its extent using household survey data. Food insecurity has always been 

found to be more prevalent in households enrolled in SNAP than in other 

low-income households. The hypothesized reason for this seeming anomaly 

is that food-needy households are more likely to enroll in SNAP, and that the 

initial difference in food security between SNAP participants and nonparticipants is greater than the ameliorative effect of the program. Researchers have 

used various statistical methods to untangle these opposite forces, but have 

not obtained consistent or convincing results. 

This report provides greater detail on the timing of food insecurity relative 

to a household’s fi rst receiving SNAP benefi ts (or beginning to receive them 

again after being off the program for a year or more). The extent of food 

insecurity in households month by month in the year prior to their enrolling 

indicates whether signup generally occured after a period of deteriorating 

food insecurity, as the self-selection hypothesis suggests. The prevalence of 

food insecurity among households in the months just after versus just before 

enrollment may refl ect the effect of SNAP benefi ts on food security. 

What Did the Study Find? 

Households’ food security deteriorated substantially beginning 7 or 8 months 

prior to SNAP entry and improved shortly after benefi ts began. The prevalence of very low food security among sample households increased from 

around 8 percent 1 year prior to entering SNAP to nearly 20 percent in 

the 4-6 months prior to entry. Within a few months of entering SNAP, the 

prevalence of very low food security declined to around 12 percent, where it 

settled for the fi rst 10 months on the program.

These patterns could not be observed either in cross-sectional or 1-year longitudinal analysis of the food security survey data. Only with fi ner-grained 

detail of the month-by-month analysis can the deterioration in food security 

prior to receipt of SNAP benefi ts and the improvement after be observed. 

These results clearly demonstrate the self-selection by households into SNAP 

at a time when they are more severely food insecure. The results are consistent with a moderate ameliorative effect of SNAP—reducing the prevalence 

of very low food security among recent entrants by about one-third—

although they do not conclusively demonstrate that extent of amelioration.
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How Was the Study Conducted?

Data for the study come from annual food security surveys from 2001 to 

2006 sponsored by USDA and conducted by the U.S. Census Bureau as 

supplements to the monthly Current Population Survey. The nationally representative samples included about 48,000 households in each year. Two-year 

panels were assembled by matching households that were interviewed in 2 

successive years. The primary analysis sample comprised 635 households 

that began receiving SNAP benefi ts in their second year in the survey but 

did not receive SNAP at any time during their fi rst year in the survey nor in 

January of their second year in the survey. 

The food security status of each household in the 30 days prior to each survey (conducted in mid-December) was based on the number of food-insecure 

conditions reported by one respondent in each household—conditions such 

as cutting the size of meals because there was too little money for food, or 

being hungry because there was too little money for food. Households were 

grouped by the month in Year 2 in which they began receiving SNAP benefi ts, and the prevalence of very low food security for each group was calculated for December of Year 1 and December of Year 2.

.
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Introduction

The Supplemental Nutrition Assistance Program (SNAP), formerly the Food 

Stamp Program, is the largest Federal food assistance program, serving over 

28 million persons monthly in 2008 with an average monthly benefi t of $102 

per person (USDA/Economic Research Service, 2009). SNAP benefi ts are 

intended to increase the access of eligible low-income households to food 

and a nutritious diet and can only be used to purchase food. Because of the 

program’s size and importance, there is substantial policy interest in assessing its effectiveness.

Early research on the impact of Food Stamp Program participation focused on 

food expenditures and the availability of nutrients (see Fox et al., 2004, for a 

review of this literature). More recently, researchers have examined the effect 

of SNAP on food security—a survey-based measure of households’ consistent 

access to adequate food—and food suffi ciency, a closely related condition.1

Identifying the impact of SNAP participation on food security has proved 

diffi cult. It is expected that SNAP benefi ts lessen the severity of food insecurity for participants. However, in cross-sectional surveys, food insecurity 

has always been found to be more prevalent among SNAP participants than 

among similarly low-income nonparticipants, even controlling as completely 

as data allow for income, employment, household composition, and other 

household characteristics. 

Self-selection by more food-needy households into the program has been 

hypothesized as the reason for this seeming anomaly. Participation in food 

assistance programs is voluntary, and it has been assumed that households 

with greater unmet food needs are more likely to participate. If the initial difference in food security between households that self-select into SNAP and 

those that do not is larger than the positive effect of SNAP benefi ts on food 

security, then the self-selection effect could account for the consistent fi nding 

of greater food insecurity in SNAP recipient households than in other lowincome households. However, untangling the self-selection and amelioration 

effects has presented great methodological diffi culties (see box, “Evaluating 

Program Effects: In Search of the Counterfactual”).

1 Prior to the development of the food 

security measures, the National Health 

and Nutrition Examination Survey 

(NHANES) and the Continuing Study 

of Food Intake by Individuals (CSFII) 

assessed the adequacy of households’ 

food access using a single question. 

Respondents were asked which of three 

statements best described the food 

eaten in their household: 

• “We always have enough to eat.”

• “Sometimes we don’t have enough 

to eat.”

• “Often we don’t have enough to 

eat.”

Households were classifi ed as food suffi cient if they reported that they always 

had enough to eat and food insuffi ent 

if they reported that they sometimes or 

often did not have enough to eat. 
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Evaluating a program such as SNAP involves estimating 

the effect of the program on food security, food spending, 

food intake, and other outcomes of interest. In concept, the 

“program effect” is the change in food security (or in some 

other condition) that is due to participation in SNAP. Other 

terms for the same concept are “treatment effect,” “participation effect,” and “ameliorative effect.” For any one participant, the program effect on food security is the difference 

between the participant’s (measurable) food security while in 

SNAP and the (inherently unmeasurable) food security that 

person would have experienced if they were not participating in the program. That is, the program effect is the difference between his/her actual condition and the counterfactual 

condition that would exist if he/she were not participating. 

The difference between the actual and counterfactual conditions, averaged across all participants, is an estimate of the 

average program effect on the food security of participants. 

By their nature, however, counterfactuals can never be 

known with certainty—precisely because they did not happen. The main challenge of program evaluation is to estimate 

counterfactuals using the best available approaches and data.

The gold standard for program evaluation is often considered to be the random assignment experiment. In such 

experiments, a large number of potential participants are 

each assigned at random to either a treatment group (which 

receives the program benefi t) or a control group (which does 

not). If assignment is random, statistical theory justifi es using 

the (measured) outcome of the control group as an estimate of 

the (nonmeasurable) counterfactual for the treatment group. 

Such experiments are widely used in medical research and 

in research on plants and animals. However, random assignment is not generally considered to be a suitable methodology 

for evaluating a program such as SNAP. The program is an 

entitlement, and eligible recipients cannot legally be denied 

access to benefi ts for the purpose of assessing its effects. 

Furthermore, random assignment experiments with human 

subjects may be considered unethical if it is already known 

that one of the two assignments (treatment versus control, 

or one of two treatments) is more benefi cial than the other.1

When data from a random assignment experiment are not 

available, so-called “natural experiments” can sometimes 

provide counterfactuals in survey data. In social science 

research, “natural” experiments do not, in fact, usually result 

from natural processes, but from changes in programs or 

policies that restrict or enhance program access for some 

groups. They are “natural” only in the sense that the changes 

were not made specifi cally for purposes of program evaluation. They are “experiments” in the sense that assignment to 

participation or nonparticipation (or, as is usually the case, 

to eligibility or ineligibility for program participation), while 

not random, does not depend entirely on decisions of individuals. For example, in the mid-1990s, the Personal Responsibility and Work Opportunity Reconciliation Act made 

certain groups of non-citizen immigrants ineligible for the 

Food Stamp Program and for certain other public assistance 

programs. Researchers examined conditions before and after 

the rule change among the subgroup of immigrants subject 

to the new restrictions. Food security after the rule change 

was considered to be a counterfactual for what food security would have been in the pre-rule-change period.2 Since 

conditions were compared for the entire group that was 

subject to the new restrictions (both participants and nonparticipants), this procedure directly estimated the average 

treatment effect on eligibles. From that estimate, the average 

treatment effect on participants was calculated. In this natural experiment, SNAP (then called the Food Stamp Program) 

was found to have a benefi cial effect on the food security of 

participants. Such natural experiments occur rarely, however, 

and often provide estimates for small subpopulations only.

In the absence of random assignment or natural experiments, researchers may attempt to estimate a counterfactual 

by applying statistical methods to survey data. The most 

straightforward of these methods uses multivariate regression methods to compare conditions among participants with 

conditions among eligible nonparticipants while statistically 

controlling for income, employment, and other relevant factors. This approach estimates the counterfactual food security 

for each participant by calculating the food security of nonparticipants with observable characteristics, such as income 

and employment, that are similar to those of the participant. 

Unfortunately, important factors that affect both food security and SNAP participation may not be observed in a particular survey, and some factors may be virtually impossible to 

observe or measure in any survey. Examples include actual 

food needs, local food prices, needs other than food that 

place unusual demands on resources, and informal sources of 

1However, random assignment experiments have been used to assess the effect of providing benefi ts that can only be used to buy food 

(i.e., food stamps, the predecessor of SNAP benefi ts) versus providing equivalent benefi ts in cash. In this case, the ethical concerns were 

met because there was ambiguity about which was the superior form of assistance. While these “cash out” experiments provided insight 

into the effect of the form of the benefi t, they did not assess the effect of receiving versus not receiving the benefi t.

2An adjustment was made for estimated changes that would have taken place in the absence of the rule changes based on changes that 

occurred among otherwise similar non-immigrants and immigrants not subject to the new restrictions.

Evaluating Program Effects: In Search of the Counterfactual

Continued on page 3
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fi nancial and nonfi nancial support. Regression methods, even 

in surveys with the most detailed data, have found SNAP participants to be more food insecure than their estimated counterfactuals. Most researchers believe that this counterintuitive 

result is attributable to biased estimates of counterfactuals 

due to unobserved conditions that affect both food insecurity 

and the decision to participate or not participate in SNAP.

Statistical methods that are more complex than singleequation regression attempt to simultaneously model the 

decision to participate in SNAP and the effect of participating. The objective is still to estimate a counterfactual, but the 

methods are designed to explicitly take into account factors 

affecting the decision to participate. These methods provide 

the strongest results when they include factors that directly 

affect SNAP participation but do not affect food security, 

except indirectly through their effect on participation. Such 

factors enable the methods to sort out factors infl uencing 

participation from those infl uencing food security. In practice, such factors can be diffi cult to fi nd in survey data. These 

methods have yielded widely differing results in different 

studies, and it is diffi cult to ascertain which results are reliable, given uncertainties about the underlying assumptions.

Panel data—data collected from the same household at two 

or more points in time—can overcome some of the problems caused by unobserved factors. In effect, a household’s 

food security during a period of nonparticipation is taken as 

the counterfactual for that same household at a time when 

they do participate. Regression methods are used to adjust 

for observed factors that vary over time for each household, 

such as income and employment. Since unobserved factors 

that do not change over time are the same for the actual and 

estimated counterfactual case, those factors do not distort 

the estimation of the counterfactual. However, even panel 

data methods cannot adjust for unobserved factors that do 

change over time. To date, such approaches have generally 

found higher food insecurity during periods of SNAP participation than during periods of nonparticipation, although 

the differences are smaller than differences between participants and nonparticipants in cross-sectional survey data.

Panel data methods used previously are similar to the method 

used in this study with one important exception—timing. Panels that have collected food security data in each interview 

have almost all been annual surveys. As seen in the present 

study, the deterioration in food security prior to entering SNAP 

generally occurs over a period of time shorter than a year.

The research reported in this study uses food security of 

SNAP participants in the months immediately preceding 

program enrollment as an estimate of the counterfactual—

what their food security would have been later, after SNAP 

enrollment, if these participants had not enrolled in the program. Like all estimates of counterfactuals, this study’s estimates may be inaccurate for any individual participant. The 

food security of some recent program entrants would have 

improved between the two times even if they had not joined 

the program. However, the food security of others would 

likely have deteriorated further had they not joined. The basis 

of this study’s method is the assumption that, averaged across 

households, food security in the period immediately before 

entering SNAP is a reasonable estimate of their later food 

security in the (counterfactual) absence of SNAP participation.

Continued from page 2
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Previous Research on SNAP 

and Food Security

Researchers have used various methods to attempt to control for unobserved 

differences between SNAP recipients and nonrecipients and for the associated self-selection bias. Multivariate regression or propensity matching techniques can control for observable differences between households. However, 

many important differences may be unobserved. Analyses using multivariate 

regressions continue to show a positive association between program participation and higher food insecurity (Jensen, 2002; see also a review of this and 

other early work on the effect of SNAP on food security in Fox et al., 2004). 

More recently, Gibson-David and Foster (2006) used a propensity score 

approach to analyze food security data provided by the Early Childhood 

Longitudinal Study. A limited model showed a higher probability of food 

insecurity for SNAP participants than for nonparticipants and no association 

of SNAP participation with the severity of food insecurity. However, a more 

extensive specifi cation using propensity scoring methods showed no association between SNAP participation and food insecurity and, among households 

with any measureable level of food insecurity, less severe food insecurity for 

SNAP participants than for nonparticipants.

Kabbani and Kmeid (2005) used a creative approach to conduct what was, 

in effect, a longitudinal analysis using cross-sectional survey data. Using 

Current Population Survey Food Security Supplement (CPS-FSS) data, they 

limited the analysis sample to households that had very low food security 

(a severe range of food insecurity) at some time during the 12 months prior 

to the survey. They then examined the association, within that subsample, 

between very low food security during the 30 days prior to the survey and 

receipt of SNAP benefi ts during the 30 days prior to the survey. They found 

no statistically signifi cant difference in the likelihood of very low food security between SNAP recipients and nonrecipients, but did fi nd a signifi cant 

association with the level of benefi ts. Among households with very low food 

security at some time during the 12 months prior to the survey, those that 

received higher SNAP benefi ts were less likely than those that received lower 

benefi ts to have very low food security in the 30 days prior to the survey.

Approaches that have attempted to explicitly account for selection have 

found inconsistent results. Gundersen and Oliveira (2001) used a simultaneous equations approach to jointly estimate food insuffi ciency and program 

participation using the 1991-92 Survey of Income and Program Participation 

(SIPP), administered by the U.S. Census Bureau. They found no statistically 

signifi cant relationship between SNAP participation and food suffi ciency. 

Huffman and Jensen (2003) expanded this work by including labor force 

participation and using a measure of food insecurity rather than food insuffi ciency. They found that being food insecure increased the likelihood of 

SNAP participation, but found no signifi cant effect of SNAP participation 

on the probability of having very low food security, although among participants increases in the size of the SNAP benefi t decreased the likelihood of 

very low food security. Yen et al. (2008) applied an instrumental variables 

approach to National Food Stamp Participants Survey data, using Statelevel policy differences as identifying variables. SNAP participation was 

found to reduce the probability of very low food security by about one-third. 
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Identifi cation in these models is typically problematic, depending on unverifi able assumptions about the functional forms of associations, distributions of 

errors, and the independence of identifying variables.

Unobserved time-invariant differences between households can be controlled 

by applying fi xed-effect models to longitudinal data. This has been found 

to reduce, but not remove, the self-selection bias; some of the unobserved 

heterogeneity appears to be within the same household over time rather than 

between households. Wilde and Nord (2005) used a 2-year panel constructed 

from the CPS-FSS to estimate a fi xed-effects model to control for timeinvariant household heterogeneity. The fi xed-effects estimate of the association between SNAP participation and food insecurity was smaller than a 

cross-sectional estimate, but was still positive, which was attributed to unobserved household-specifi c variation over time. Ribar and Hamrick (2003) 

used the 1993 panel of the SIPP combined with the Survey of Program 

Dynamics (SPD) to examine the dynamics of poverty and food security 

transitions. They found that SNAP participants were less likely than nonparticipants to exit from food insecurity, which they attributed to unobserved 

heterogeneity (i.e., self-selection bias). Hofferth (2004) analyzed withinhousehold changes in food security status for households with children 

between the 1997 and 1999 waves of the Panel Study of Income Dynamics 

(PSID). The analysis included SNAP participation as an explanatory variable 

but did not control for unobserved differences in households. Hofferth found 

that, although SNAP participants were more likely to be food insecure than 

nonparticipants, leaving SNAP was associated with a higher risk of becoming food insecure or remaining food insecure. 

A promising approach has been to take advantage of “natural experiments” to 

identify impacts of food assistance programs. Natural experiments are differences, among groups or over time, in access to food assistance programs that, 

while not random, are not caused by differences in food security. Borjas (2004) 

compared State-level changes in food insecurity in States with differing welfare 

policy toward immigrants of different types before and after the 1996 changes 

in the welfare system. He found convincing evidence that food security worsened among immigrant populations whose access to public assistance (including, but not limited to, food assistance) had been impeded. Bartfeld et al. (2006) 

compared the probabilities of food insecurity in households with children across 

States with different SNAP participation rates. Higher SNAP participation rates 

could indicate more outreach by State and county programs or higher social 

acceptability of receiving assistance, and these differences across States create a 

sort of natural experiment. Controlling for household demographic and economic 

characteristics and relevant State-level characteristics, food insecurity was found 

to be less likely in States with higher SNAP participation rates.

The inconsistent associations found between SNAP participation and food 

security do not demonstrate that the program has no effect. A fi nding of no 

effect in models that attempt to control for selection bias could mean that 

the SNAP is not working as intended or that selection bias has not been fully 

controlled in the analysis and is offsetting the positive effect of the program. 

Multivariate approaches may fail to control for unobserved differences, and 

simultaneous equation models generally depend on assumptions that cannot 

be tested.
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Needed: More Detailed Information 

on the Timing of Food Insecurity

The seeming intractability of the self-selection problem results, to a considerable extent, from a lack of information on when, exactly, households were 

food insecure relative to when they received SNAP benefi ts. Household 

fi xed-effect analyses such as that by Wilde and Nord (2005) eliminate the 

selection effects due to unobserved differences across households and demonstrate that those effects account for a substantial share of the higher food 

insecurity among SNAP participants in cross-sectional data. The hypothesized remaining selection effect—due to a household being more likely to 

enroll in SNAP when food insecurity is more severe—could be sorted out 

more reliably if the food security of households could be tracked week by 

week or month by month just before and after beginning to receive SNAP 

benefi ts. Competing hypotheses about the relationship between SNAP participation and food security predict different temporal patterns of food insecurity in the few months before and after beginning SNAP participation.

Hypothesis: SNAP benefi ts alleviate food insecurity. The observed positive 

association between SNAP receipt and very low food security is a result of 

selection bias. Under this hypothesis, food security would deteriorate over 

some period of time prior to initial receipt of SNAP benefi ts, then improve 

after households begin to receive benefi ts.

Counter-hypothesis #1: There is some selection effect, but SNAP participation has no substantial effect on food security. Under this hypothesis, food 

security would deteriorate prior to initial receipt of SNAP benefi ts, and not 

change systematically after beginning to receive benefi ts.

Counter-hypothesis #2: There is no selection effect; households apply for 

SNAP for reasons unrelated to food insecurity, and SNAP participation makes 

households more food insecure. Under this hypothesis, food security would not 

change systematically during the months prior to initial receipt of SNAP benefi ts. Then, after beginning to receive benefi ts, food security would deteriorate.2

Two changes introduced to the CPS-FSS in 2001 and 2002 allow testing 

of these hypotheses by examining the timing of food insecurity relative to 

the beginning of a spell of receiving SNAP benefi ts. Beginning in 2001, 

the CPS-FSS has been conducted in December of each year. Because of 

the design of the CPS (to which the CPS-FSS is a supplement), this survey 

schedule provides food security and SNAP data for each household in 2 consecutive years. Then, in 2002, the CPS-FSS began collecting information on 

which specifi c months households received SNAP benefi ts. 

For this study, data from the same households were linked between 2 survey 

years, and households that began receiving SNAP benefi ts in Year 2 were 

analyzed. Three pieces of information were brought together: households’ 

food security status in December of Year 1, the month in Year 2 that they 

began receiving SNAP benefi ts, and their food security status in December of 

Year 2. Combining these data across households that entered the program in 

different months during Year 2 provides a detailed trajectory of the average 

food security of households from 12 months prior to entering the program to 

about 10 months after entering the program.

2 Counter-hypothesis #2 seems 

improbable; no mechanism has been 

suggested by which receipt of SNAP 

benefi ts would cause food insecurity to 

worsen. The hypothesis is included for 

completeness, because it would account 

for the observed positive association 

between food insecurity and SNAP 

receipt. It predicts a distinct temporal 

pattern of food insecurity relative to 

beginning SNAP participation, so is 

empirically testable.
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Data and Methods

Data were provided by the December CPS-FSS for each year from 2001 

to 2006. The CPS-FSS is an annual supplement to the monthly Current 

Population Survey. It is administered by the U.S. Census Bureau and is nationally representative of the civilian, noninstitutionalized population. The sample 

size averaged about 48,000 households each year during the study period.

Two-Year Panel Construction

Households in the monthly Current Population Survey (core labor force) sample are interviewed in 4 consecutive months; a year later, they are interviewed 

again in the same 4 months. About equal numbers of new households enter the 

survey each month, so in a given month’s survey about half of the households 

were in the survey 12 months previously, and the other half will be in the survey 12 months later. The analysis sample was constructed by matching households in the CPS-FSS (conducted in December) across the 2 years that each 

household was in the survey. Five such matched samples were assembled and 

pooled, beginning with 2001-02 and ending with 2005-06. 

Two factors reduce the number of households that can be used for any 2-year 

panel analysis of the CPS-FSS. First, some households were interviewed in 

only one of the two years, or completed the supplement in only one of the 

two years. Second, the CPS is a sample of housing addresses; if a household 

interviewed in Year 1 moves out and another moves in, the new household is 

interviewed in Year 2.3 On average, the matched household fi le included 71 

percent of the households in the matchable half-samples.4

Previous research has found that households that do not match year to 

year—either because they moved or missed an interview in one of the two 

years—are more likely to be food insecure than those that do match (Wilde 

and Nord, 2005). The analysis sample, then, is biased somewhat toward more 

stable and more food-secure households. 

Identifying the Beginning of SNAP Spells

The CPS-FSS has, since its inception in 1995, collected data on whether 

households received SNAP benefi ts at any time during the previous 12 

months and at any time during the previous 30 days. Beginning in 2002, 

households that received SNAP benefi ts in the previous 12 months were 

also asked in which specifi c months they had received benefi ts.5 Response 

to this question allowed identifi cation of the fi rst month in which households 

received SNAP benefi ts—a key piece of information for the analysis. The 

primary analysis sample consisted of households that began receiving SNAP 

benefi ts in February or later in Year 2 and did not receive SNAP benefi ts at 

any time in Year 1 nor in January of Year 2. The restriction of no receipt in 

January of Year 2 was needed to avoid seam bias. (Seam bias is the overestimate, due to misreporting, of month-to-month changes between conditions 

in the fi nal month of one survey period and the fi rst month of the subsequent 

survey period.) This restriction avoids misclassifying as new recipients in 

January of Year 2 households that received SNAP benefi ts in Year 1, but 

failed to report them, and continued receiving benefi ts in Year 2.6 

3The CPS-FSS data identify 

households that move into a sampled 

address by incrementing the value of 

the variable HUHHNUM. Households 

in which HUHHNUM differed between 

Year 1 and Year 2 were omitted from 

the panel analysis sample. An additional very small proportion of 

households had the same HUHHNUM 

in the 2 years, but were clearly different 

households based on their age, race, or 

gender composition. They were also 

omitted from the analysis sample.

4See Wilde and Nord (2005) for 

further details on matching CPS-FSS 

households across years.

5The 2001-02 matched sample was 

usable even though specifi c month of 

receipt was not collected in 2001, since 

only 12-month SNAP receipt information was needed for Year 1 of each 

2-year panel.

6Analysis of month-to-month entries 

confi rmed the presence of substantial 

seam bias. SNAP “entrants” were a much 

larger proportion of total monthly recipients in January than in any other month. 
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The total sample of matched households from 2001-02 to 2005-06 numbered 84,724. However, beginning a SNAP spell is a relatively rare occurrence. Most households in the matched sample received no SNAP benefi ts 

in Year 2, and most of those that did had also received benefi ts in Year 1 or 

in January of Year 2. The primary analysis sample consisted, then, of the 

635 households that began receiving SNAP benefi ts between February and 

December of Year 2 after not receiving SNAP benefi ts in Year 1.

SNAP receipt is generally underreported in household surveys. Comparison 

with administrative records of the SNAP caseload (not shown) suggests that 

underreporting is quite serious in the CPS-FSS, but that the extent of underreporting is only slightly greater for months early in the year than for months 

late in the year (and therefore nearer the time of the December survey). It 

seems unlikely that underreporting would distort these results substantially. 

Only households that reported receiving SNAP benefi ts are in the analysis 

sample. Any random error in reporting month of fi rst receipt would weaken 

the observed associations. Any systematic bias in reporting month of fi rst 

receipt would simply compress or extend the reported versus actual time until 

(or since) fi rst receipt, but would not affect the association with food security 

in Year 1 or Year 2. The analytic results would be threatened only if reporting 

error on month of fi rst receipt was systematically associated with level of food 

insecurity or if underreporting of any receipt was systematically associated 

both with month of fi rst receipt and with level of food insecurity. These possibilities cannot be ruled out, but there is no obvious reason to expect them.

Assessing Food Security During

the 30 Days Ending in Mid-December

The other two key pieces of information needed for the analysis were measures 

of households’ food security in the 30 days prior to the survey in December of 

Year 1 and in December of Year 2—that is, households’ food security status 

prior to, and after, entering SNAP. This information, along with the specifi c 

month in Year 2 in which benefi ts were fi rst received, provided estimates of 

the average prevalence of very low food security in each month from 2 to 

12 months before households fi rst received SNAP benefi ts and from 1 to 10 

months after. Consider, for example, households whose fi rst receipt of SNAP 

was in March of Year 2. The percentage of those households that had very low 

food security in December of Year 1 is an estimate of the prevalence of this 

condition in households 3 months prior to entering SNAP. The percentage with 

very low food security in December of Year 2 is an estimate of the prevalence 

of this condition in households 9 months after entering SNAP (or re-entering 

after having been out of the program for a year or more).

Household food security—access by all household members at all times 

to enough food for active healthy living—is measured in the CPS-FSS by 

responses to a series of questions about food-related conditions and behaviors that typically occur in households when they are having diffi culty meeting their food needs (Hamilton et al., 1997a; Hamilton et al., 1997b; Bickel 

et al., 2000; Nord et al., 2007). The questions cover a wide range of food 

access problems, from worrying about running out of food to not eating for 

a whole day. Each question specifi es a lack of money or other resources to 

obtain food as the reason for the condition or behavior, so the measure is not 

affected by behaviors such as voluntary dieting or fasting. 
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Based on the number of food-insecure conditions reported, households are 

classifi ed as either food secure or food insecure. Food-insecure households 

are further classifi ed as having low food security or very low food security. 

Very low food security, the condition analyzed in this study, is a severe range 

of food insecurity characterized by reduced food intake and disrupted eating 

patterns of one or more adults due to inadequate resources for food. 

The standard food security measure, on which USDA’s annual food security 

reports are based, represents conditions over the 12-month period prior to the 

survey. This study uses an alternative measure of very low food security—

more temporally precise—based on households’ experiences over the 30-day 

period prior to the survey (Nord, 2002).7 The 30-day scale is based on the 

same concepts and statistical methods as the standard 12-month U.S. Food 

Security Scale. To minimize any measurement effects associated with the 

presence and ages of children, household food security was assessed using 

only the 7 adult-referenced items in the 30-day scale (Nord and Bickel, 

2002). That is, the scale that would normally be applied to households 

without children was used for all households. Households with and without 

children and with children in different age ranges might differ in seasonal 

patterns of likelihood of beginning receipt of SNAP (in relation to the school 

year, for example). Use of the adult 30-day scale obviates any confounding 

associations between food insecurity and timing of SNAP spells that could 

result from such patterns.

Analytic Methods

Descriptive analyses were based on cross-tabulations of the month of SNAP 

entry by food security status in Year 1 and, in a separate analysis, by food 

security status in Year 2. Single-month sample sizes were too small to 

provide reliable estimates of the prevalence of very low food security, so 

3-month rolling averages were also calculated for descriptive purposes.

To test the statistical signifi cance of the patterns observed in the descriptive statistics, the association between very low food security and number 

of months until SNAP entry (and, in a separate analysis, the number of 

months since SNAP entry) was estimated using logistic regression methods. With very low food security in Year 1 as the dependent variable, this 

analysis tested the hypothesis that the likelihood of very low food security 

increased as households neared the beginning of SNAP participation. With 

very low food security in Year 2 as the dependent variable, the analysis 

assessed whether the likelihood of very low food security changed as 

households were on SNAP for increasing number of months, and whether 

the change was signifi cant. In the logistic regression analyses, both linear 

and quadratic functional forms were estimated for months-until-programentry (and months-on-the-program).

To test the size and statistical signifi cance of change in food security from 

before to after initial receipt of SNAP benefi ts, the average prevalence 

of very low food security 1 to 6 months after beginning receipt of SNAP 

benefi ts was compared with that 2 to 6 months prior to program entry. 

Variances of these prevalence rates were calculated as P(1-P)/N, where P 

was the weighted prevalence rate and N was the unweighted number of 

cases in the denominator.

7 In December 2005, the CPS-FSS 

began collecting 30-day food security 

data for all questions that make up 

the 12-month scale. This supports a 

full-range 30-day scale. In this study, 

however, the same methodology was 

used for the 2005 and 2006 data as for 

2004 and earlier years so that measures 

would be consistent in all years.
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To provide context for these estimates, the prevalence of very low food security was also calculated for two groups of households outside of the primary 

analysis sample: those that received SNAP benefi ts in both years (N=2,527), 

and those that were income-eligible for SNAP but did not receive benefi ts in 

either year (N=4,268).

One factor that could have distorted the analytic results is that different types 

of households with different propensities toward very low food security might 

have different seasonal patterns of food insecurity and SNAP entry. As a check 

on this possible confounding factor, logistic models were also estimated with 

controls for household composition and annual household income. Substantial 

changes in the coeffi cients on months prior to fi rst receipt or months since fi rst 

receipt would indicate confounding by seasonal factors.

Variances of estimates were calculated in two ways. The fi rst method 

assumed no design effect and calculated variances based on the unweighted 

numbers of cases. The second method used a jackknife replication based on 

the fi ve independent 2-year matched samples.8 The jackknife method may be 

considered the more conservative, since it accounts for measurement error as 

well as sampling error.

Household sampling weights were used for all analyses. The key analyses 

were repeated without using case weights. Weighted analyses were also 

repeated using a broader measure of 30-day food insecurity that included as 

insecure households that affi rmed any of the adult-referenced questions.9 The 

results of both analyses were similar to those presented and the statistical signifi cance of key coeffi cients did not change.

8The jackknife estimation followed 

standard procedures for such analysis. Each of the fi ve 2-year matched 

samples was omitted from the analysis 

sample in turn, and the regression 

analysis was conducted using the 

remaining four samples. The mean of 

the estimated coeffi cient across the fi ve 

analyses was taken as the best overall 

estimate of the coeffi cient. The squared 

difference between that best estimate 

and the coeffi cient estimate from each 

analysis was summed across the fi ve 

analyses. The jackknife estimator for 

the variance of the coeffi cient estimate 

was then calculated as 4/5 times that 

sum of squared differences.

9This categorization identifi es some 

households with food insecurity less 

severe than those with very low food 

security, but it does not identify all 

food-insecure households. Prior to 

2004, 30-day information was not 

collected for the questions about less 

severe conditions that are needed to differentiate food-secure households from 

those with low food security.
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Findings

In these 2-year matched samples, as in earlier studies, very low food security 

was more prevalent among SNAP recipients than among income-eligible 

nonrecipients. Among households that received SNAP benefi ts in both 

years, the prevalence of very low food security was about 13 percent, compared with 6.3 percent among those that did not receive SNAP benefi ts in 

either year. Much of this difference could be attributed to self-selection 

across households, but not all of it. Households in the matched samples that 

received SNAP benefi ts in only one of the two years were somewhat more 

likely to have very low food security in the year they were in the program 

(12.2 percent) than in the year they were not in the program (11.2 percent).

In the main analysis sample—the 2-year panels of households that entered 

SNAP in Year 2—food security typically deteriorated in the 6 to 8 months 

prior to entering SNAP. The prevalence of very low food security 10 to 12 

months prior to program entry was around 8 percent—not far above the level 

of low-income households that did not receive SNAP benefi ts in either year 

(table 1; fi g. 1). For example, of the households that entered the program in 

November, 8.07 percent had very low food security 11 months earlier, in 

December of Year 1. The 3-month rolling average centered on November 

program entry was 8.21 percent. About 8 or 9 months prior to beginning 

SNAP participation, the prevalence began increasing. The 3-month rolling 

Table 1

Households in 2-year panels (2001-02 through 2005-06), by very low food security status 

and month of fi rst receiving SNAP benefi ts 

Month of 

fi rst receipt

Number of 

cases

(unweighted

December of Year 1 December of Year 2

Months 

prior 

to fi rst 

receipt

Number 

with very 

low food 

security

Weighted 

percent 

with very 

low food 

security 

3-month 

rolling 

average 

percent 

with very 

low food 

security

Months 

after fi rst 

receipt

Number

with very 

low food 

security

Weighted 

percent 

with very 

low food 

security 

3-month 

rolling 

average 

percent 

with very 

low food 

security

February 28 2 5 11.63 10 5 14.28

March 32 3 3 12.61 15.87 9 5 9.23 13.83

April 36 4 8 21.02 15.90 8 4 16.36 11.97

May 21 5 5 17.44 20.82 7 2 5.93 12.12

June 40 6 8 22.12 16.54 6 5 10.63 12.52

July 59 7 8 12.27 14.25 5 9 15.95 12.51

August 58 8 8 10.85 10.63 4 7 10.54 10.30

September 94 9 9 9.70 9.34 3 6 7.39 10.53

October 119 10 9 8.32 8.68 2 16 13.32 11.39

November 109 11 12 8.07 8.21 1 17 13.17 13.85

December 39 12 3 8.29 0 6 17.75

Total 635 78 11.21 82 12.22

Source: Calculated by the authors using Current Population Survey Food Security Supplement data from 2001, 2002, 2003, 2004, 2005, and 

2006. Data from 2 consecutive years were assembled for each household in the analysis sample by matching households in month-in-sample 

5-8 in 2002-06 to the same household in month-in-sample 1-4 in the previous year. Households that had moved between the two surveys were 

omitted. Households that received SNAP benefi ts at any time in Year 1 or in January of Year 2 were omitted.
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average peaked at about 20 percent 4-6 months prior to initial receipt of benefi ts, then declined somewhat before households actually began to receive 

SNAP benefi ts. 

The observed increase in food insecurity in the months prior to SNAP entry 

was statistically signifi cant. The predicted probability of very low food security, based on a logistic regression linear in log-odds, reached 20 percent 2 

months prior to beginning a SNAP spell. The coeffi cient on months prior to 

beginning SNAP was highly signifi cant (table 2, model 1). The probability of 

the null hypothesis under a two-tailed test was .015, but the hypothesis tested 

was directional, so a single-tail test would be appropriate, giving a probability of the null hypothesis of about .008. The jackknife variance estimate for 

this coeffi cient resulted in a single-tailed p value of .012.10 

Although the single-month estimates and 3-month rolling averages suggest 

that food security may have improved in the last few months prior to beginning receipt of SNAP benefi ts, that pattern was not statistically signifi cant. In 

the logistic regression model with months prior to beginning SNAP entered 

as a quadratic, the squared term was not statistically signifi cant (p=.289; table 

2, model 2). However, it was more nearly signifi cant based on the jackknife 

variance (p=.143), and it may be worthwhile to examine this pattern further 

in future research. Some households may begin to take other steps to address 

their deteriorating food security at about the same time that they begin to 

consider applying for SNAP.

The increase in very low food security prior to beginning a SNAP spell does 

not appear to refl ect differential timing of initial participation by different 

types of households. Adding controls for household composition and income 

resulted in a negligible change in the coeffi cient on months prior to begin10 The predicted probability of very 

low food security for 1 month prior to 

beginning food stamps is not shown 

in fi gure 1 because it would be an outof-sample estimate. A single-month 

estimate for 1 month prior to SNAP 

entry could not be generated due to the 

omission of households that apparently 

entered the program in January.

Figure 1

Prevalence of very low food security (adult, 30-day) before and after initial receipt of SNAP benefits

1Prevalence rates for households that received SNAP benefits in both years or in neither year are shown as constant levels for references. 

It is not meaningful to consider them in regard to a SNAP starting month.

Source: Calculated by the authors using Current Population Survey Food Security Supplement data from 2001, 2002, 2003, 2004, 2005, 

and 2006. Data from 2 consecutive years were assembled for each household in the analysis sample by matching households in monthin-sample 5-8 in 2002-06 to the same household in month-in-sample 1-4 in the previous year. Households that had moved between the 

two surveys were omitted. Households that received SNAP benefits at any time in year 1 or in January of year 2 were omitted.

Percent of households

0

5

10

15

20

25

-12 -10 -8 -6 -4 -2 8 0 10 12 2 4 6

Prior to entry, predicted, linear in log-odds

Prior to entry, 3-month rolling average

After entry, predicted, linear in log-odds

After entry, 3-month rolling average

Received SNAP 

both years(1)

Intial receipt of SNAP benefits

No SNAP either year, income 

<130% poverty(1)

Month (SNAP receipt begins at month 0)
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ning SNAP (table 2, model 3). The coeffi cient increased in magnitude very 

slightly compared with model 1 and remained highly signfi cant.

Once households began receiving SNAP benefi ts, the probability of very low 

food security declined within a month or two, although only by about onethird. The average prevalence of very low food security during the period 

from 1 to 6 months after fi rst receiving benefi ts was 11.7 percent, slightly 

below the level of households that received benefi ts in both years (fi g. 1). 

This was 6.0 percentage points lower than the prevalence during the period 

from 2 to 6 months prior to fi rst receipt (17.7 percent), and the difference 

was statistically signifi cant (p=.04). Changes over the fi rst year after program 

entry were not statistically signifi cant either in linear or quadratic formulation, or with controls for household composition and income (table 3). 

The estimates of very low food security after beginning a SNAP spell shown 

in fi gure 1 include a small proportion of households that entered SNAP during the year but left the program prior to December. Omitting those “leaver” 

households raised the mean prevalence of very low food security slightly, to 

almost exactly the level of households that were on the program in both years 

(analysis not shown). The time trend remained nonsignifi cant.

The association of very low food security in Year 1 with month of SNAP 

entry in Year 2 resulted primarily from differences in the likelihood of 

exiting very low food security. The patterns described above are based on 

Table 2

Logistic regression of very low food security in December of Year 1 on number of months 

to initial receipt of SNAP benefi ts (N=635)

 Model 1 Model 2 Model 3

Variable Coeff. p Coeff. p Coeff. p

Intercept -1.226 -1.930 -1.484 

Months prior to beginning SNAP -0.105 .015 .144 .548 -.111 .016

Square of months prior to beginning SNAP -.018 .289 

Two-parent with child (reference)1 

 Single female with child .780 .024

 Two or more adults, no child -.348 .437

 Male living alone .884 .059

 Female living alone .806 .059

One or more elderly in household -.920 .063

Income above 2 x poverty line (reference)2

 Income < 50 percent of poverty line .627 .145

 Income 50-75 percent of poverty line -.565 .332

 Income 75-100 percent of poverty line -.315 .539

 Income 100-125 percent of poverty line .955 .018

 Income 125-150 percent of poverty line -.504 .381

 Income 150-200 percent of poverty line .064 .885

 Income not reported -1.038 .204

Somers’ D .174 .184 .398

Model p based on Wald chi-square .015 .039 <.001

1Reference category for household composition also included a very small proportion of “single male with child” households and households with 

children in complex living arrangements such as children of a boarder, unmarried partner, or housemate of the household reference person.

2Annual income in Year 1.

Source: Calculated by the authors using Current Population Survey Food Security Supplement data from 2001, 2002, 2003, 2004, 2005, and 

2006. Data from 2 consecutive years were assembled for each household in the analysis sample by matching households in month-in-sample 

5-8 in 2002-06 to the same household in month-in-sample 1-4 in the previous year. Households that had moved between the two surveys were 

omitted. Households that received SNAP benefi ts at any time in Year 1 or in January of Year 2 were omitted.
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averages for all households that began receiving SNAP benefi ts in a given 

month. Among households entering SNAP in the fi rst 6 months of Year 2, 

the prevalence of very low food security declined from December of Year 

1 to December of Year 2. This implies that the number of households that 

exited very low food security exceeded the number that entered that status. 

On the other hand, among households entering SNAP in the last 6 months of 

the year, the prevalence of very low food security increased from December 

of Year 1 to December of Year 2, implying that the number of households 

that entered very low food security exceeded the number that exited that 

status. Analysis (not shown) of changes in the food security status of each 

household from December of Year 1 to December of Year 2 revealed that 

these patterns primarily refl ected differences in rates of exit from very low 

food security. The very-low-food-security entry rate (i.e., the percentage of 

households that were food secure or had only low food security in Year 1 and 

had very low food security in Year 2) differed little across groups of households that began receiving SNAP in different months. However, the verylow-food-security exit rate (the percentage of households with very low food 

security in Year 1 that were either food secure or had only low food security 

in Year 2) was higher for households that began receiving SNAP benefi ts 

early in Year 2 than for those that entered the program late in the year.

Table 3

Logistic regression of very low food security in December of Year 2 on number of months since initial 

receipt of SNAP benefi ts (N=635)

 Model 1 Model 2 Model 3

Variable Coeff. p Coeff. p Coeff. p

Intercept -1.936 -1.697 -2.016

Months since beginning SNAP -0.010 .828 -.174 .267 -.010 .828

Square of months prior to beginning SNAP .017 .273

Two-parent with child (reference)1

 Single female with child .495 .153

 Two or more adults, no child .160 .653

 Male living alone .528 .259

 Female living alone .859 .038

One or more elderly in household -.428 .273

Income above 2 x poverty line (reference)2

 Income < 50 percent of poverty line -.268 .575

 Income 50-75 percent of poverty line -.391 .437

 Income 75-100 percent of poverty line -.539 .300

 Income 100-125 percent of poverty line -.569 .274

 Income 125-150 percent of poverty line -.211 .678

 Income 150-200 percent of poverty line .070 .883

 Income not reported .465 .328

Somers’ D .009 .079 .210

Model p based on Wald chi-square .828 .537 .470

1Reference category for household composition also included a very small proportion of “single male with child” households and households with 

children in complex living arrangements such as children of a boarder, unmarried partner, or housemate of the household reference person.

2Annual income in Year 2. Analysis was repeated using annual income in Year 1; the coeffi cient on “months since beginning SNAP” was even 

smaller and the p value was .947.

Source: Calculated by the authors using Current Population Survey Food Security Supplement data from 2001, 2002, 2003, 2004, 2005, and 

2006. Data from 2 consecutive years were assembled for each household in the analysis sample by matching households in month-in-sample 

5-8 in 2002-06 to the same household in month-in-sample 1-4 in the previous year. Households that had moved between the two surveys were 

omitted. Households that received SNAP benefi ts at any time in Year 1 or in January of Year 2 were omitted.
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Conclusion

Month-by-month information on households’ food security reveals a substantial deterioration in food security beginning 7 or 8 months prior to initial 

receipt of SNAP benefi ts and suggests an ameliorative effect of the program. 

The prevalence of very low food security increased from around 7 or 8 percent 

12 months prior to entering SNAP to nearly 20 percent in the last few months 

prior to entry. Within a few months of program entry, the prevalence of very 

low food security declined to around 12 percent, where it remained with little 

change during the period observed (up to about 10 months on the program).

These patterns cannot be observed either in cross-sectional or simple longitudinal analysis. Cross-sectional analysis of the Current Population Survey 

Food Security Supplement (CPS-FSS) data for the years studied (2001-06) 

fi nds the familiar pattern of very low food security being higher among 

SNAP recipients (around 13 percent) than among income-eligible nonrecipients (6.3 percent). Simple panel analysis of households that entered the 

program in Year 2 (that is, panel analysis that does not take account of the 

month in which households began receiving SNAP benefi ts) fi nds that the 

prevalence of very low food security was slightly higher for households in 

the year they were in the program (12.2 percent) than for the same households in the year they were not in the program (11.2 percent). The deterioration in food security prior to SNAP entry and the improvement after entry 

can be observed only in the fi ner grained detail of month-by-month analysis. 

These results clearly demonstrate the self-selection by households into SNAP at a 

time when their food security has worsened. Household-fi xed effects analyses in 

earlier research had demonstrated that self-selection of more food-insecure households into SNAP accounted for some, but not all, of the consistently observed 

positive association between SNAP participation and food insecurity in crosssectional surveys. Self-selection based on time-variant factors within the same 

household—the higher likelihood of a household applying for SNAP at time when 

food insecurity is more severe—has been hypothesized as the cause of the remaining positive association, but the process had not been convincingly demonstrated 

by previous research, nor had its extent been estimated.

The results are also consistent with a moderate ameliorative effect of 

SNAP—reducing the prevalence of very low food security among recent 

entrants by about one-third. The only important threat to a causal interpretation (i.e., that SNAP benefi ts caused the decline in very low food security) is 

that entering SNAP could act as a marker, identifying households that have 

recently experienced unusually high levels of food insecurity. A variable that 

changes randomly in members of a population will regress toward the population mean for a subset of the population with above-average values on the 

variable at a point in time. Some households in this subpopulation, marked as 

more food needy by having applied for SNAP, may have subsequently experienced an improvement in food security due to processes unrelated to receipt 

of SNAP benefi ts. Such regression to the mean could account for some or 

all of the decline in very low food security after entering SNAP. Lacking a 

random assignment or natural experiment, however, these results provide, 

perhaps, the most credible estimate to date of the extent to which SNAP may 

reduce the prevalence of very low food security.
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References

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Account for State-to-State Differences in Food Security? Economic 

Information Bulletin No. 20. Economic Research Service, U.S. 

Department of Agriculture. www.ers.usda.gov/publications/eib20/. 

Bickel, G., M. Nord, C. Price, W.L. Hamilton, and J.T. Cook. 2000. Guide to 

Measuring Household Food Security, Revised 2000. Food and Nutrition 

Service, U.S. Department of Agriculture. www.fns.usda.gov/fsec/fi les/

fsguide.pdf

Borjas, G.J. 2004. “Food Insecurity and Public Assistance,” Journal of 

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