Abstract

This study used administrative records for 50,067 applications and 34,914 benefit spells in South Carolina for the 

period October 1996-November 2007 to examine households’ applications to and participation in the Supplemental 

Nutrition Assistance Program (SNAP). We modeled application resolutions where the possible outcomes were 

acceptance, denial due to income ineligibility, denial due to a failure to provide sufficient information, and denial for 

other reasons. For cases with successful applications, we modeled the durations of participation spells to distinguish 

among exits that result from missed recertifications, financial ineligibility, incomplete or missing information, and 

other reasons. The results indicate that a household’s application and participation history affect its subsequent application 

success and program tenure. Applicants with recent SNAP program experience are more likely to have their applications 

accepted than other applicants. Among the applicants with recent program experience, the way in which a previous 

spell ends helps to predict how their next application will be resolved and how their next participation spell will end. 

Households face an increased risk of having a SNAP participation spell end for financial ineligibility if an earlier 

participation spell ended for that reason. Similarly, households face an increased risk of having their applications 

denied or participation spells end for information deficiencies if an earlier spell ended that way.

Acknowledgments

The authors thank Teo Gamishev for his help in preparing the administrative data used in this analysis. An earlier 

version of this report was presented at the 13th Annual Welfare Research and Evaluation Conference in Washington, 

DC, on June 3, 2010. The authors thank John Kirlin, David Stevens, Laura Tiehen, Parke Wilde, and conference 

participants for helpful comments. 

By David C. Ribar and Christopher A. Swann, 

University of North Carolina at Greensboro

Applying for and Staying on the 

Supplemental Nutrition Assistance 

Program in South Carolina

Contractor and Cooperator Report No. 65

February 2011

This study was conducted by University of North Carolina at Greensboro under 

a cooperative research agreement with USDA’s Economic Research Service 

(ERS) Food Assistance and Nutrition Research Program (FANRP): agreement 

number 43-3-AEM-5-80097 (ERS project representative: Laura Tiehen). The 

views expressed are those of the authors and not necessarily those of ERS 

or USDA.
Applying for and Staying on the Supplemental

Nutrition Assistance Program in South Carolina

David C. Ribar

Department of Economics

P.O. Box 26165

University of North Carolina at Greensboro

Greensboro, NC 27402-6165

+1 336 334-3904

dcribar@uncg.edu

Christopher A. Swann

Department of Economics

P.O. Box 26165

University of North Carolina at Greensboro

Greensboro, NC 27402-6165

+1 336 334-4502

chris_swann@uncg.edu
iii

Applying for and Staying on the Supplemental

Nutrition Assistance Program in South Carolina

Executive Summary:

In this report we examine the processes associated with households applying to and 

maintaining participation in the Supplemental Nutrition Assistance Program (SNAP; formerly, 

the Food Stamp Program) using case records from South Carolina. Program take-up is a major 

issue for the SNAP and other assistance programs. Currently, only two-thirds of the households 

that appear to be financially eligible for the SNAP actually participate. Previous analyses of 

SNAP participation using household-level administrative data have focused on the length of 

spells of benefit receipt once households have joined the program. However, these studies have 

overlooked the processes by which households begin receiving benefits. This report addresses 

this problem and extends the existing literature by jointly examining how applications to the 

SNAP in South Carolina are resolved (i.e., whether applications are accepted and whether 

rejected households re-apply), the length of subsequent participation spells for accepted cases, 

and the reasons why participation spells end.

We examine electronic case management records from South Carolina covering the 

period from October 1996 until November 2007. The records contain case-level data on the 

dates and resolutions of applications, the start and end dates of participation spells, reasons for 

spell closures as well as demographic characteristics and geographic locations of households. 

The analysis data set contains information for 50,067 applications and 34,914 SNAP spells. 

In our sample of SNAP applications, approximately one third were rejected or otherwise 

unsuccessful. Some of the rejected applications came from households that were determined to 

be financially ineligible, but many more (about five out of every nine applications that were 

rejected) were turned down because of incomplete or insufficient information. Similarly, when 

we examine why SNAP participation spells end, roughly half of households stop receiving 

benefits because they fail to complete periodic recertifications and another sixth of households 

lose benefits because of incomplete or insufficient information. Only a fifth of households that 

stop receiving benefits do so because of a formal determination of financial ineligibility.

To examine characteristics that lead to these outcomes, we estimate joint models of 1) 

SNAP application resolutions and 2) subsequent participation spells for those with accepted 

applications. Jointly modeling these processes allows for the possibility that successful 

applications constitute a non-random sample of all applications. The model of application 

resolutions is specified as a multinomial logit model where the possible resolutions are 

acceptance, denial due to income ineligibility, denial due to a failure to provide sufficient 

information, or denial for other reasons. Each outcome depends on the past application behavior 

and other observable case characteristics. For cases with successful applications, the resulting 

participation spell is modeled using a discrete-time, competing-risk hazard model. We 

distinguish among SNAP exits that are the result of missed recertifications, financial ineligibility, 

incomplete or missing information, or other reasons. The hazard for each type of exit depends 

on the duration of the spell, past application behavior, and observed characteristics. 
iv

The estimation results indicate that a household's application and participation history 

affect its subsequent application success and program tenure. We find that applicants who have 

recently completed a participation spell are more likely to be successful in their applications than 

other applicants. Among the applicants with recent program experience, the way in which a 

previous spell ends partly predicts how their next application will be resolved and how their next 

participation spell will end. Households face an increased risk of having a SNAP participation 

spell end for financial ineligibility if an earlier participation spell ended for that reason. 

Similarly, households face an increased risk of having their applications denied or participation 

spells end for information deficiencies if an earlier spell ended that way. 

Estimates from the models also indicate that households’ resources and needs are 

associated with both application resolutions and subsequent participation spells, mostly in ways 

that we would expect. Households with higher levels of earnings are more likely to have their 

SNAP applications rejected and their SNAP spells end than households with lower levels of

earnings. The rejections and closures are especially likely to occur because a determination of 

financial ineligibility. At the same time, households with greater needs are less likely to have 

their applications rejected and to have SNAP spells end. Program benefits are also associated 

with program tenures and the reasons for case closures. SNAP participants with higher benefits 

are less likely than other households to miss their recertifications, to provide incomplete or 

insufficient information, or have spells end for other reasons. 

Additionally, the results indicate that unobserved characteristics that affect application 

resolutions also affect subsequent participation spells. The results are mostly consistent with 

“positive selection” in the sense that characteristics that increase the risk of an application being 

turned down for a given reason also increase the risk of a household exiting the program for that 

same reason.
1

Applying for and Staying on the Supplemental

Nutrition Assistance Program in South Carolina

1. Introduction

Policymakers and program officials have long recognized that administrative procedures 

and practices are important determinants of households’ movements into and out of the 

Supplemental Nutrition Assistance Program (SNAP, formerly the Food Stamp Program).1

Research has begun to quantify the impacts of these policies and procedures. For 

instance, Bartlett et al. (2004) found that a host of factors including office hours and policies, 

supervisor attitudes, fingerprinting requirements, and Able-Bodied Adults Without Dependents 

(ABAWD) work requirements and time limits affected application behavior. Ribar et al. (2008, 

forthcoming) and Staveley et al. (2002) found that exits from the SNAP occur mainly at 

recertification due dates, and Ribar and Edelhoch (2008) found that exits for administrative 

reasons, including missed recertifications and documentation problems, accounted for two-thirds 

of SNAP exits. 

 The 

federal and state governments are partners in the SNAP, with the federal government setting 

general rules for the program, paying the entire cost of benefits and about 50 percent of state 

administrative costs and the states administering the program. In their role as administrators, 

states have considerable latitude in a number of areas including establishing and running SNAP 

offices, developing and reviewing initial applications, and setting recertification intervals. States 

may also obtain waivers from the federal government to alter other features of their programs.

Burdens associated with administrative procedures are often discussed as a reason why 

some economically disadvantaged (otherwise eligible) households fail to take advantage of 

 1 The Food Stamp Program was renamed the Supplemental Nutrition Assistance Program on October 1, 2008. 

Throughout this report, we refer to the SNAP, although the former name applied during the period of the study.
2

available program assistance.2

This report investigates the processes by which households enter and leave the SNAP. 

Unlike most research on SNAP behavior, we examine potential SNAP cases at the time that they 

apply and investigate the resolution of those applications. Among households with successful 

applications, we then examine how long the subsequent SNAP participation spells last and the 

reasons why those spells end. We investigate these issues, using electronic case management 

records for households with children from South Carolina covering the period from October 

1996 until November 2007. The records contain case-level data on the dates and resolutions of 

applications, the start and end dates of participation spells, the reasons for spell closures as well 

as demographic characteristics and geographic locations of households. The analysis data set 

contains information for 50,067 SNAP applications and 34,914 program spells. 

 Cunningham and Castner (2009) estimate that only two-thirds of 

households that were financially eligible for the SNAP participated in 2007. Although 

administrative procedures are important for program integrity and for making sure that only truly 

needy families receive assistance, they may hinder program performance if they discourage 

eligible households from participating. Along the same lines, analyses of these procedures are 

valuable because they can highlight areas where program performance might be improved.

We estimate joint models of SNAP application resolutions and subsequent participation 

spells. Jointly modeling these processes allows for the possibility that successful applications 

constitute a non-random sample of all applications. The model of application resolutions 

distinguishes among applications that were accepted, denied because of financial ineligibility, 

denied because a failure to provide sufficient information, or denied or withdrawn for other 

reasons. We consider the roles that past application and program behavior play in these 

outcomes. For households with successful applications, we model the resulting SNAP 

 2 Moffitt (1983) also discusses how stigma might reduce program participation.
3

participation spells, using a discrete-time, competing-risk hazard framework. Our model 

measures how long households remain on the SNAP and distinguishes among exits that result 

from missed recertifications, financial ineligibility, incomplete or missing information, or other

reasons. As with the application outcomes, we also consider how previous application and 

program experiences affect program spells. 

The estimates from our descriptive and multivariate analyses reveal that households' 

SNAP application and participation experiences are predictive of their subsequent experiences. 

For example, SNAP applicants who have recently completed a participation spell (i.e., with 

recent program experience) are more likely to be successful with their applications than those 

who have not recently participated. Among the applicants who do have recent program 

experience, however, the way in which their previous spell ended helps to predict the reasons 

why their application might be denied and the reasons why their next participation spell ends. 

Applicants face an increased risk of having their application denied for financial ineligibility or 

having a SNAP participation spell end for financial ineligibility if an earlier participation spell 

ended for that reason. Similarly, applicants face an increased risk of having their applications 

denied or participation spells end for information deficiencies if an earlier spell ended that way. 

These findings may be especially valuable to program managers and caseworkers because they 

all involve characteristics that can be ascertained from case files. In addition, results from our 

multivariate models indicate that unobservable characteristics account for some of these 

associations; however, the results also indicate that there are direct associations even after 

accounting for observable and unobservable characteristics. 

The remainder of this report is organized as follows. In Section 2, we review the research 

that has examined SNAP policies, focusing on the small set of studies that have investigated 
4

entry and exit processes. In section 3, we discuss the electronic case records that are the source 

of our empirical analyses; we also describe how we constructed an analysis data set from these 

records. We report results from descriptive analyses of the data in Section 4. In Section 5, we 

describe our multivariate statistical methodology. Results from the multivariate models are 

reported in Section 6, and conclusions are offered in Section 7.

2. Background

SNAP participation and ultimately SNAP caseloads are determined by a series of 

processes and events. As a first step, a needy household must apply for benefits, which usually 

entails completing an application with roughly the same level of detail as a simplified tax form 

and providing supporting documentation.3

 3 South Carolina and some other states allow disabled adults to use their application for disability assistance as their 

application for the SNAP. South Carolina also offers simplified applications to households with elderly members.

 Once an application is submitted, the state agency 

that administers the SNAP reviews it and typically requires an in-person interview with a 

caseworker. Based on the application, supporting materials, and interview, the state agency 

determines whether the household qualifies for benefits and can participate in the program. If 

the application is rejected because of incomplete information or for some other procedural 

reason, the household may reapply. If the application is approved, the household begins 

participating and receiving benefits. Thereafter, the household must comply with the program’s 

rules and remain eligible to continue receiving benefits. If the household stops complying with 

program rules, decides to stop receiving benefits, or loses eligibility because of a change in its 

economic circumstances or living arrangements, its SNAP case is closed, and the household 

returns to the pool of non-applicants. From this overview, we can immediately see that there are 

many steps in the process, that each step involves interactions of household and program 

characteristics, and that the steps can be repeated within and across spells of benefit receipt.
5

Little of this structure is reflected in food stamp or SNAP caseload research. Many

caseload studies simply examine the incidence of program participation, either by modeling the 

aggregate number of people or households receiving benefits (Danielson & Klerman 2006, 

Kabbani & Wilde 2003, Kornfeld 2002, Wallace & Blank 1999, Wilde et al. 2000, Ziliak et al. 

2003) or by modeling the incidence of receipt among individual households (Currie & Grogger 

2001, Farrell et al. 2003, Fraker & Moffitt 1988, Haider et al. 2003, Keane & Moffitt 1998). 

These studies generally abstract from the program details and further fail to distinguish between 

entry and exit processes.

Another line of research does consider program entry separately from program exit but 

examines these processes as simple bivariate outcomes or as rates and spells (Blank & Ruggles 

1996, Cody et al. 2005, Gleason et al. 1998, Hofferth 2003, Mills et al. 2001, Ribar et al. 2008, 

forthcoming, Staveley et al. 2002). These studies have been able to consider more program 

characteristics and other details. For example, Blank and Ruggles (1996) modeled eligibility 

spells. Gleason et al. (1998) considered “trigger events,” such as the loss of a job or a change in 

income that could change program status. Cody et al. (2005) examined entry (replacement) and 

exit rates among different types of households before and after welfare reform in the 1990s. 

Ribar et al. (2008, forthcoming) considered recertification intervals and program time limits.

Only a few studies have carefully investigated component processes. For instance, 

Bartlett et al. (2004) documented policies and practices in local food stamp offices, measured 

perceptions of these policies and practices among households that appeared to be eligible for 

assistance, and examined how these perceptions affected participation behavior. They found that 

many non-participating households believed themselves to be ineligible and that many 

households had misperceptions about program rules. Of the many rules and office characteristics 
6

that they documented, Bartlett et al. found that five mattered for getting people to complete 

applications: the operating hours of program offices, positive attitudes of office supervisors, 

fingerprinting of clients, arrangements for children while parents applied, and ABAWD time 

limits.

Ribar and Edelhoch (2008) investigated the different reasons why people left the SNAP. 

As with the present research, they used program records from South Carolina that included the 

administrative reasons for program exits, which they grouped into five broad categories: missed 

recertifications, financial ineligibility, failures to provide verifiable information, other losses of 

eligibility, and voluntary exits. They found that half of program exits were associated with 

missed recertifications and that another sixth were associated with problems in supplying 

information. Some of these “paperwork” exits occurred among households that were likely to be 

found ineligible; however, some of the exits also occurred among households in very unstable 

and distressed circumstances.

Our report extends these previous process studies. As with the study by Bartlett et al. 

(2004), we carefully examine how SNAP applications are resolved. In particular, we examine 

whether applications are approved or rejected for reasons of financial ineligibility, incomplete 

information, or other reasons. As with the study by Ribar and Edelhoch (2008), we also use 

administrative data to examine participants’ program spells and reasons for exiting the SNAP. 

We extend these earlier studies, however, by modeling application and subsequent participation 

behavior jointly (thereby addressing potential selectivity among participants) and by examining 

how earlier application and participation outcomes affect subsequent outcomes. For example, 

we consider whether “paperwork” problems in the application stage predict subsequent 

paperwork problems as households continue their participation. 
7

3. Data

The data for our empirical analyses of SNAP applications and participation come from 

electronic case management records from South Carolina covering the period from October 1996 

until November 2007.4

Due to the large number of SNAP cases in South Carolina and the amount of information 

in the case histories, we reduced the analysis extract by initially drawing a 1-in-11 random 

sample of longitudinal cases. Cases are groups of people, typically households, that together 

receive SNAP benefits. The state of South Carolina constructs internal identifiers that allow 

such cases to be tracked over time, including across different episodes of application and benefit 

receipt. Thus, our extract represents a random sample of available histories, including all of the 

applications and program spells associated with a household over the study period.

 The records cover the universe of households that applied to the state’s 

SNAP over the period. They contain a wealth of household- and person-level information, 

including the dates and resolutions of applications, the starting and ending dates of participation 

spells, demographic characteristics of households, geographic identifiers, and benefit and 

reported income amounts during each month of program receipt. We use these records to form 

an analysis file with observations of 1) applications and their resolutions and 2) participation 

spells for the approved applications. 

5

We then make four additional restrictions to the data. First, we limit the analysis to 

households where children are present at the time of application and in which the case head was 

 4 The records were provided on a confidential basis through agreements with South Carolina’s Department of Social 

Services and Office of Research and Statistics. Records included internal identifiers but excluded external 

identifiers such as names, social security numbers, addresses, or phone numbers. 

5 The size of our random sample was constrained primarily by our computing and data transfer capabilities. 

Reviewers have noted that the analytic properties of our extract could be improved by using a stratified sampling 

approach. However, because of the structure of the South Carolina data files, this approach requires pre-processing 

several enormous files, a task that was beyond our computing capabilities. 
8

between the ages of 18 and 59 and no other adults were over the age of 59.6

 Second, we restrict 

the analysis to households in which the head of the case was white or black. Only five percent of 

cases were identified as being of another race or ethnicity, leaving us with too few cases to 

examine these groups. Third, we drop observations with missing, incomplete, or inconsistent 

information about participation, household characteristics, or case-head characteristics. In terms 

of the longitudinal case histories, we effectively right-censor the history at the first instance of 

problematic data. Fourth, we drop observations from the longitudinal history for a case if there 

is a change in the identified case head, a procedure that also effectively right-censors the 

longitudinal history. Our final analysis data set contains 50,067 SNAP applications and 460,931

monthly observations from 34,914 spells of benefit receipt.

Applications. The data contain information on 28,495 applications by blacks and 21,572 

for whites. The approval rate is approximately 69 percent for both groups. For every application 

that is denied or withdrawn, the administrative records give a reason. There are 27 detailed 

codes that are used at least once in our records.7

• because the household was determined to be ineligible because its income or assets were too 

high,

 We grouped the codes into three broad 

categories: applications that were unsuccessful 

• because the household failed to provide information or provide verifiable information, or

• because of some other reason, including voluntary withdrawal.

 6 Adult-only cases and cases with elderly recipients face different rules than other cases so restricting the data to 

households with children and with all adults younger than 59 years old allows us to focus on a single set of policies 

without having to attempt to control for policies specific to these other groups.

7 The SC Department of Social Services policy manual indicates that applications are resolved in one of four 

primary ways: approval by the caseworker, denial by the caseworker, denial by the administrative computer system, 

or withdrawal by the applicant. Caseworkers deny an application if the applicant fails to meet any of the eligibility 

criteria, fails to provide necessary information or participate in an interview, or cannot be located. Thus, our 

categorizations correspond to the broad categorizations in the policy manual. In situations where applicants fail to 

meet multiple criteria, only one code is entered by the caseworker even though other codes might also apply. Our 

multivariate analyses account for these “competing risks” of failure.
9

The detailed codes, our categorizations, and the relevant frequencies are reported in Appendix A. 

The tabulations of the reasons for denial reveal that just under one third of the denials—

32 percent among applications submitted by blacks and 30 percent among applications submitted 

by whites—occurred because the households reported or were found to have income or resources 

that made them ineligible. Over half of the denials (53 percent for blacks and 56 percent for 

whites) occurred because the household failed to provide sufficient or reliable information. 

Approximately 14 percent of the unsuccessful applications were denied on other grounds or were 

voluntarily withdrawn.

Figure 1 shows trends in application resolutions for our sample. We have adjusted the 

totals so that the counts of cases in Figure 1 represent the number of applications in South 

Carolina among households with adults 18-59 years of age and with children at the time of 

application. Although there is considerable seasonal variability, the number of successful 

applications to South Carolina’s SNAP generally trended downward over the last part of the 

1990s; this is consistent with the falling SNAP caseload in the state over the same period. 

Starting in the second half of 2000, applications began to increase as the economy in South 

Carolina deteriorated. After the economy stabilized in 2002, the number of applications fell 

slightly but remained above the levels from the late 1990s. Over time, there also appears to have 

been a modest increase in the acceptance rate of applications.

SNAP participation spells. From the accepted applications, we examine the subsequent 

spells of SNAP participation, which we measure in discrete, monthly intervals. SNAP 

participation spells in South Carolina can begin anytime during a month. However, once a spell 

begins, benefits are only paid once a month. Also, when a case is terminated, the official closing 

date almost always occurs at the end of the month. The timing of payments and case closings 
10

lead us to treat the participation spells as a series of discrete, monthly observations, with the 

initial and terminal observations for each spell corresponding to the first and last months of 

benefit receipt, respectively. 

Our data begin in October 1996. However, because our multivariate models condition on 

application and program experience during the preceding year, our analysis begins in October 

1997. Accordingly, we drop spells that are on-going, or left-censored, in October 1997 and only 

consider applications and new spells that begin on or after this date. The spells themselves 

should refer to continuous months of benefit receipt. However, the administrative records 

sometimes contain short breaks. In processing the data for each household, we smooth the 

information by combining spells of program participation that are separated by a month or less 

(that is, by ignoring short breaks). This kind of smoothing is common in event-history studies 

and is intended to eliminate artificial transitions associated with administrative “churning.” This 

treatment is also consistent with state policies that consider program receipt spells that resume 

within one month of a previous spell to be continuations of the earlier spells.

Reasons for exit. As with denied applications, the administrative records give a reason 

for closure of an on-going case. There are 33 detailed codes that are used at least once in our 

records.8

• missed its recertification,

 We grouped the codes into four broad categories: cases that ended because the 

household

• lost eligibility because its income or assets were too high,

• failed to provide information or provide reliable information, or

 8 As with the application denial codes, case closing codes can be generated automatically by failing to meet some 

time critical deadline (most often a recertification) or verification check, by caseworkers who detect some eligibility 

issue or encounter missing, incomplete or unverifiable paperwork, or by a voluntary withdrawal of the application. 

Multiple case closing codes could apply to a given spell exit, but only one will be recorded in the administrative 

system.
11

• lost eligibility because of some other reason or voluntarily quit.

The detailed codes, our categorizations, and the relevant frequencies are reported in Appendix B. 

The tabulations of the reasons for exit reveal that 52 percent of cases headed by blacks 

and 54 percent of cases headed by whites ended because the cases let their certification periods 

lapse without submitting any paperwork for a new certification. This replicates the findings of 

Ribar and Edelhoch (2008) that recertification is an important element in SNAP exits. The 

tabulations also indicate that about one fifth of the exits—22 percent among cases headed by 

blacks and 16 percent among cases headed by whites—occurred because the households either 

reported or were found to have a change in income or resources that made them ineligible. 

Approximately one sixth of cases ended because the household failed to provide sufficient or 

reliable information. Ten percent of cases headed by blacks and 13 percent of cases headed by 

whites lost their eligibility for some other reason including voluntary withdrawal.

Figure 2 shows trends in the numbers and types of exits for SNAP households in South 

Carolina with children and no elderly adults.9

 As opposed to applications, there was no initial 

downward trend in exits. Aside from seasonal variation, the numbers and types of exits were 

very similar from the beginning of our observation period until the middle of 2002. However, 

after South Carolina increased its recertification intervals for households with earnings in 2002, 

there was a marked decrease in exits associated with missed recertifications. In 2005, South 

Carolina shortened the recertification intervals for households without earnings. At that point, 

exits associated with missed recertifications increased. Over time, exits associated with 

determinations of financial ineligibility appear to have increased. Exits associated with 

information problems increased after 2002 but fell after 2005. 

Participation History

 9 Figure 2 includes exits among spells that were on-going in October 1997.

. The administrative records for South Carolina maintain the same 
12

identifiers for households across applications and program spells, allowing us to link program 

experiences longitudinally and thereby account for households’ application and participation 

histories. These histories may affect the outcome of application decisions and program spells. 

To account for past experience with the SNAP, we construct variables indicating whether the 

household applied within the past year and, if there were an application, the outcome and the 

number of months since the application. Additionally, we construct variables measuring the 

number of months since the most recent spell closure (if it occurred within the past year) and the 

reason for the closure. 

Control Variables

Unlike the demographic characteristics, data on income and earnings are not available for 

denied applications. Consequently, we merge in quarterly earnings data from South Carolina’s 

Unemployment Insurance (UI) system. The UI database contains earnings information for most 

private, non-agricultural employers. However, it overlooks government employment and some 

types of private-sector jobs, such as agricultural and domestic work. It also misses employment 

by people who commute out of the state to work. To make the units of the UI earnings data 

comparable to the income data from SNAP administrative data, we divide the quarterly UI 

earnings amounts by three.

. From the information on demographic characteristics, we construct 

measures of the number and age composition of the case members. We also construct variables 

for the age, sex, race, educational attainment, and marital status of the household member 

heading the case.

For each month that a case continues, the records indicate the benefits that the household 

received as well as all of the economic information that enters the benefit calculation, including 

gross reported earned and unearned income amounts. We use several of these variables in our 
13

descriptive and multivariate analyses, adjusting all dollar amounts to 2005 levels using the 

Consumer Price Index for All Urban Consumers.

The records also indicate the county of residence for the household, which allows us to 

link the administrative data to measures of the county unemployment rate to control for local 

economic conditions and measures of the population density to control for the level of 

urbanization. 

Several SNAP policies in South Carolina changed during the observation period of our 

study. One set of policies involved the recertification intervals for different types of cases. Prior 

to October 2002, cases with variable incomes (usually earnings) had to recertify their eligibility 

quarterly, while cases with fixed incomes such as TANF, disability payments, or retirement had 

to recertify annually. Starting in October 2002, South Carolina increased the recertification 

intervals for cases with variable earnings to six months, and starting in February 2005, the state 

reduced the recertification intervals for households with fixed incomes to six months. Our 

multivariate analyses of participation spells include controls for these policies.

South Carolina changed several other policies. For example, the state effectively 

exempted all vehicles from the calculation of household assets in fiscal year 2002. The state also 

adopted simplified income reporting requirements and simplified definitions of income. To 

account for these and other policy changes, the multivariate analyses include general sets of time 

controls.10

4. Descriptive analysis

Tables 1b and 1w list statistics describing the characteristics of SNAP cases from South 

 10 South Carolina also changed policies that were relevant to its adult-only caseload, including exempting some 

adults from work requirements and time limits and adopting simplified applications for elderly adults. Ribar and 

Edelhoch (forthcoming) examine the policies for and behavior of adult-only cases.
14

Carolina at the time of application for different application outcomes. Table 1b lists statistics for 

cases headed by blacks, while Table 1w lists statistics for whites. In each table, averages of the 

characteristics are calculated conditionally, depending on how the application was resolved.

The first rows present information about income. Because not all applications are 

complete, information on income from the case records is limited. Consequently, we use the 

sum of UI earnings recorded for all household members from the current quarter as an indicator 

for household earned income. As mentioned, to improve the comparability of the different 

income measures, we divide the quarterly UI earnings amounts by three to arrive at an 

approximate monthly equivalent. We also include a dummy variable that equals one if no 

earnings were recorded. As one would expect, applications that were denied for income reasons 

had relatively high UI earnings compared to other applications. Somewhat surprisingly, however, 

cases whose applications were denied for information reasons had lower average UI earnings 

than cases whose applications were approved. 

The second set of variables describes households’ application and program experiences 

over the year preceding the current application. The decision to focus on the most recent year 

was made in part to recognize that, like human capital, more recent experience is likely to play a 

larger role in current behavior than more dated experience. The empirical implication of the one 

year window is that individuals whose last closure or denial occurred one or more years ago are 

treated as if they have no experience with the FSP. The one-year window was selected after 

some initial specification analyses that indicated that longer window lengths did not add much 

explanatory power.

The statistics for the program experience measures indicate that black applicants were a 

little more likely to have been recent SNAP participants (i.e., to have experienced a case closure) 
15

than white applicants. Within each racial group, successful (approved) applicants were more 

likely to have participated in the SNAP during the last year than unsuccessful applicants. 

Among successful applicants with recent program experience, the distribution of case closure 

reasons is very similar to the overall distribution of closures from Appendix A. Applications that 

were denied for financial reasons were more likely than other applications to follow a case 

closure for similar reasons. Application resolutions do not appear to be strongly associated with 

other reasons for case closures.

The statistics for prior application experiences reveal that modest, yet nontrivial, 

proportions of applicant households had unsuccessful applications in the previous year. Such 

households were at slightly higher risk of having their current applications denied. The reasons 

for denials were predictive of subsequent denials. Households that were rejected for financial 

reasons had the highest incidence of prior financial rejections; households that were rejected for 

information reasons had the highest incidence of prior information rejections, and so on. These 

descriptive results suggest that prior application and program experiences are associated with 

current application success.

Tables 2b and 2w list statistics describing the characteristics of SNAP participation spells 

that ended for different reasons or that were right-censored (not observed to end). Table 2b lists 

statistics for cases headed by blacks conditionally by spell ending, while Table 2w lists similar 

statistics for cases headed by whites.

The rows at the top of each table describe economic circumstances of the cases, including 

the level of SNAP benefits and reported levels of earned and unearned income, at the beginning 

of the month in which the spell was last observed (that is, immediately preceding the spell 

termination). Consistent with the results reported by Ribar and Edelhoch (2008), these economic 
16

variables are associated with the reasons for exit. As we would expect, cases that were 

terminated for reasons of financial eligibility tended to have the lowest benefits and the highest 

reported incomes. Cases that failed to recertify also had relatively low benefits and relatively 

high incomes. These results suggest that these cases may have had lower incentives than other 

cases to comply with program rules and that some may stopped complying because they were 

financially ineligible. While low in a relative sense, the benefits for cases that failed to recertify 

were still substantial, which suggests that at least some cases were “leaving money on the table” 

and may have encountered high costs of program compliance. Cases that ended because they 

failed to provide sufficient information and cases that lost eligibility for other reasons had the 

highest benefits and lowest incomes on average, indicating that these cases were especially 

disadvantaged. 

The next rows list statistics associated with the cases’ program and application 

experiences in the year preceding the start of their current SNAP participation spells. The 

statistics indicate that each type of closure experience put households at an increased risk of 

repeating that closure experience. Cases that failed to recertify had relatively high rates of earlier 

failing to recertify; cases that closed for financial reasons had the most experience with this type 

of outcome, and so on.

The statistics for histories of unsuccessful applications indicate that such experiences 

were more common among SNAP cases that eventually closed because of missed 

recertifications, financial ineligibility, and information problems and less common among cases 

that eventually ended for other reasons. Experiences with applications that were turned down 

because of information problems were especially prevalent among cases that subsequently closed 

because of information problems and missed recertifications. Experiences with applications that 
17

were rejected for financial eligibility were most prevalent for cases that subsequently closed for 

this same reason. Once again, the descriptive evidence is consistent with previous program and 

application experiences predicting subsequent program behavior. 

5. Multivariate models

The descriptive analyses reveal that economic conditions, program variables, and 

application and program experiences are all unconditionally associated subsequent application 

and program behavior. To better isolate the independent influences of the different 

characteristics, we jointly estimate multivariate models of SNAP application resolutions and of 

subsequent participation behavior. We specify the model of application resolution outcomes as a 

multinomial logit. Let pj(t) be the probability of resolution outcome j (= 0, 1, 2, 3) for an 

application made by a household at time t where the outcomes are the application being 

accepted, denied for financial ineligibility, denied for a failure to provide information, and 

denied for other reasons, respectively. We assume that the resolution probability depends on a 

set of observed and possibly time-varying household characteristics, X(t), and a time-invariant 

unobserved household characteristic, η. Because we are estimating probabilities of resolution, 

actual resolution outcomes also implicitly depend on additional time-varying unobserved 

characteristics. We model the probability for the household’s application resolution as

( )

∑ ( ) =

+ δ + π η

δ + π η = 3

1

1 exp ( )

exp ( ) ( )

s

s s

j j

j

X t

X t

p t

(1)

where δi, i = 1,...,3 is a kx1 vector of coefficients to be estimated and πi, i = 1,...,3 is a scalar 

parameter to be estimated. 

Conditional on an application being approved, we observe a participation spell for the 

household. We estimate discrete-time competing-risk hazard models of different types of SNAP 
18

exits (see Allison 1982). The hazard rate, which refers to the probability that a spell of 

remaining in one situation ends at a given point in time conditional on the spell having lasted up 

to that time, is a standard tool for analyzing program behavior. Hazard models are especially 

useful in this regard because they account for the fact that some spells of program participation 

are not observed to their ends, because they either continue past the analyst’s observation 

window (in this case past November 2007) or are missing information at some point during their 

duration. The competing-risk framework further accounts for the fact that there are several 

reasons why a spell might end but that only one of those reasons is actually observed. For 

example, a spell that ended because of a missed recertification might have soon ended anyway 

for eligibility reasons.

We specify the discrete-time, competing-risk hazard model as a multinomial logit model 

with the different reasons for exit in any month as the explicit outcomes and with continuation in 

the spell as the omitted outcome. We model exits for four reasons: missed recertifications, losses 

of eligibility for income or resource reasons, failures to provide information, and all other 

reasons. Let hk(t) be the hazard of the household leaving the SNAP for reason k (= 1, 2, 3, 4) 

(and let h0(t) be the conditional probability of continuing on the program). The hazard for a 

particular type of exit depends on characteristics of the duration of the spell, T(t), as well as other 

observed and unobserved characteristics and is modeled as

hk (t) = exp(α kT (t) + βkX(t) + λkη)

1+ exp(α mT (t) + β m X(t) + λ mη) m=1

4

∑ (2)

where α k , βk , and λk are vectors of parameters to be estimated.

As mentioned, the application resolution and participation models are estimated jointly. 

Besides the observed explanatory variables, the models share a common unobserved component, 
19

η. The presence of this component allows for correlations across the models and for serial 

correlation in the unobserved determinants of the repeated outcomes for a model. In this way, 

we simultaneously account for selection from unobservables in application outcomes and for 

spurious duration dependence from unobservables in the participation analysis. We assume that 

η follows a discrete distribution with a finite number of potential outcomes. Our software 

estimates the points of support and probabilities for this distribution.

6. Multivariate estimation results

We estimate our models separately for white and black households. Coefficient estimates 

from our principal specifications for application resolutions appear in Tables 3b and 3w, and 

coefficient estimates from our principal specifications for program spells appear in Tables 4b and 

4w. As the row headings in the tables indicate, the explanatory variables in the application and 

competing-risk hazard models include measures of household economic resources, household 

demographic characteristics, and local economic and population characteristics. The competingrisk models of program tenures also include controls for SNAP benefits and quarterly, semiannual, and annual spell duration indicators that correspond to the likely ends of certification 

periods.

In addition to these measures, the models include other explanatory measures and 

controls, although we do not report detailed results.11

 11 Complete, detailed results are available upon request.

 In particular, our application and program 

tenure models include dummy variable controls (fixed effects) for the applicant’s county of 

residence and for the fiscal year of the observation. The county and fiscal year indicators are 

included to control for area and time differences in policies, procedures, economic conditions, 

attitudes, and other characteristics. The competing-risk models of program tenure also include 
20

36 monthly dummy variables that cover the first three years of a spell duration and four semiannual dummy variables that cover the next two years; thus, we essentially adopt a semiparametric specification for the spell duration, akin to a Cox proportional hazard model. The 

models for black and white households are estimated using a discrete distribution for the 

unobserved component, η, with four points of support. Specification tests support the inclusion 

of county and fiscal year fixed effects, general controls for the baseline duration pattern, and the 

control for a common unobserved component.

The estimates in the first two rows of Tables 3b and 3w indicate that households are at 

increased risk of having an unsuccessful application if they have high levels of UI-covered 

earnings or if they have no record of UI-covered earnings at all. The former result is consistent 

with households being less likely to be financially eligible for SNAP benefits and thus less likely 

to have their applications accepted. The latter result, regarding no UI earnings, may be 

indicative of less stable economic circumstances or of employment that is harder to verify. 

These results are similar across black and white households.

The estimates in the next five rows of Tables 3b and 3w describe the associations 

between households’ program experiences in the preceding 12 months and their application 

resolutions. For the most part, the estimates indicate that households that are attempting to rejoin 

the SNAP after a short absence are more likely to be successful than households attempting to 

rejoin after longer absences or with no program experience in the last 12 months.12

 12 The coefficient estimates for the program experience variables are difficult to interpret because they involve 

interactions between the “months since closure” and “reason for closure” coefficients. Consider a black household 

that experienced a closure because of a missed recertification three months before its current application. Its risk 

index for a financial denial would decrease by 0.668 (= (3 · 0.080) – 0.908) relative to a household that had not 

experienced a case closure in the last 12 months. The risk index for an information-related denial for the same 

household would decrease by 0.166, and the risk index for other types of unsuccessful resolutions would decrease by 

0.761.

 The lone 

exception to this pattern of results is for white applicants who experienced case closures for 
21

financial reasons – these applicants face increased risks of information-related denials but 

reduced risks of financially-related denials and “other” denials.

Among the households that had experienced closures in the last 12 months, closures for 

particular reasons generally increased the risks of denials for the same reasons. The pattern is 

especially noticeable for black households. For black households, experiences with financiallyrelated closures raised the odds of financially-related application denials; experiences with 

information-related closures raised the odds of information-related denials, and “other” closures 

raised the odds of “other” denials and withdrawals.13

The associations between previous and current application outcomes are both weaker and 

more varied than the associations between previous closures and current application outcomes. 

For example, a previous application denial for information reasons significantly reduces the 

chances of an information-based denial for whites, and previous experiences with “other” denials 

and withdrawals significantly reduce the chances of a current financial or information related 

denial for blacks or an information related denial for whites.

 For white households, these same 

associations appeared for financially-related closures and “other” closures but not for 

information-related closures. In general, the associations between closure reasons and 

application resolutions match those from the descriptive analyses.

Demographic characteristics are also associated with application resolutions. Very young 

applicants have relatively high risks of information-related denials and “other” denials. The risks 

of an information-related denial generally decrease with age up to age 40 then increase with age 

thereafter. Additional years of elementary and secondary schooling reduce the chances of an 

unsuccessful application; however, earning a high school diploma or general equivalency degree 

 13 These interpretations are based on the respective coefficients being the least negative of the “reason for closure” 

coefficients.
22

increases those chances. Married blacks are more likely to have their applications denied than 

never-married blacks. Married whites are also more likely to have applications denied for 

financial reasons but less likely to have applications denied for information or “other” reasons. 

Black and white households with more children, especially young children, are less likely to 

have applications denied, but households with more adults are more likely to have applications 

denied.

Patterns of application resolutions also differ depending local conditions. Black and 

white households in areas with high unemployment are less likely than households in other areas 

to withdraw their applications or have them denied for “other” reasons. Black households that 

apply to the SNAP in less densely-populated (rural) counties are less successful than those who 

apply in more populated (urban) counties. Whites living in rural counties also face an increased 

risk of denial for information reasons. Higher denial rates for information problems may reflect 

challenges faced by rural applicants in producing documents that verify income or other 

eligibility criteria.

The last rows of Tables 3b and 3w present estimates of the coefficients (factor loadings) 

for the time-invariant unobserved household characteristic, η. Recall that η enters both the 

application resolution model (1) and competing-risk model of SNAP participation/exits (2). 

Identification of the coefficients on η in the two models requires that one coefficient in one of the 

models be set equal to one. We normalized the coefficients in terms of characteristics that cause 

households to leave the SNAP because of missed recertifications (set λ1 in model (2) equal to 

one). With this normalization, the estimates from Tables 3b and 3w indicate that unobserved 

characteristics that cause households to miss their recertifications are positively associated with 

households having their applications denied because of information problems but negatively 
23

associated with having the applications denied for financial ineligibility. The estimates also 

provide some evidence that program spells are subject to selection on the basis of unobservables; 

in particular, unobservable characteristics that affect application resolutions also appear to affect 

participation outcomes.

We now turn to the estimates from the discrete-time, competing-risk hazard models of 

SNAP participation spells among successful applicants. MNL coefficient estimates are reported 

in Tables 4b and 4w. From left to right, the coefficients are from the MNL latent indices for 

exits due to missed recertifications (column 1), financial ineligibility (column 2), information 

problems (column 3), and other types of ineligibility and withdrawals (column 4).

The first five rows in each table list coefficients on the household benefit and income 

variables. For black households, higher SNAP benefits are estimated to reduce the risks of exit 

for all reasons and thus, unambiguously increase the length of SNAP participation spells. For 

white households, higher SNAP benefits are estimated to reduce the risks of exit for all reasons 

except financial ineligibility. The results are generally consistent with higher benefits providing 

incentives to comply with program rules and encouraging program participation. For black and 

white households, higher levels of earnings are estimated to increase the chances of missing a 

recertification or becoming financially ineligible but to decrease the chances of exiting for 

information problems or “other” reasons. Higher levels of unearned income have similar effects, 

except that they are estimated to reduce the risk of missing a recertification for whites and are 

estimated to have no effect for blacks. Households that begin their SNAP spells with no income 

whatsoever have higher rates of exit than other households, while households that have some 

earnings have lower risks of exit. The pattern of results for households with no income or with 

no earnings is similar to the pattern from the application model where the absence of resources 
24

increased the risks of denial.

The next five rows of Tables 4b and 4w list coefficients for households’ program 

experiences during the year preceding their current SNAP spell. Black households that had 

recently had a SNAP case closed for financial ineligibility are estimated to be at increased risk of 

having their current cases closed for the same reason. However, black households that had 

earlier SNAP cases closed because of missed recertifications, information problems, or other 

problems are at lower risk of having their current cases closed for financial reasons. For black 

households, a similar pattern appears for “other” closures—a recent experience with the same 

type of closure increases the risks of an “other” closure, but a recent experience with a missed 

recertification, a loss of financial eligibility, or an information problem decreases the risks. 

Estimates reveal these same general patterns for white households, with an exception that earlier 

experiences with financial closures are not predictive of current financial closures for whites. 

Estimates for white households also indicate that recent experiences with missed recertifications 

and closures for other reasons predict closures for information reasons in the current spell.

The next four rows of Tables 4b and 4w list coefficients for households’ application 

experiences prior to the application that led to their current spells. Black households that had 

earlier applications turned down because of financial ineligibility are estimated to face higher 

risks of having their cases closed for financial reasons but are estimated to face lower risks of 

having their cases closed for “other” reasons. Among white households, having an earlier 

application denied for financial reasons increases the chances that the current spell will end for 

the same reasons. However, having an application rejected because of information problems 

reduces the chances that a spell will end for those same (information) reasons.

The next 10 rows in Tables 4b and 4w list coefficient estimates on the controls for likely 
25

recertification months within spells—three- and 12-month intervals before October 2002, sixand 12-month intervals from October 2002 until January 2005, and six-month intervals 

thereafter—for households with and without earnings at the start of their certification periods. 

As with the findings of Ribar and Edelhoch (2008), the estimates indicate that households were 

more likely to leave the SNAP in months when recertifications were due than in other months. 

Households with earnings were especially likely to leave at the short interval dates (quarterly 

before October 2002 and semi-annually after that), while households without earnings were 

especially likely to leave at the long interval dates (annually before February 2005). At their 

recertification dates, households were at a substantially higher risk of leaving the SNAP because 

of a missed recertification but also at increased risk of leaving for other reasons, including 

financial ineligibility.

The estimates from Tables 4b and 4w also reveal that demographic and household 

characteristics are related to SNAP exits. Cases headed by women were generally less likely to 

exit than cases headed by men. For blacks, high school completion and more post-secondary 

years of schooling increased the chances of a SNAP spell ending because of a missed 

recertification or financial ineligibility, and college completion increased the chances of a spell 

ending for “other” reasons. For whites, high school completion and years of post-secondary 

education were also positively associated with exits for financial ineligibility. Increases in the 

number of children were generally negatively related to exits for missed recertifications and

financial ineligibility but positively related to “other” exits. Greater numbers of adults were 

positively related to most types of exits. Married-couple and ever-married households were also 

more likely to leave the SNAP than never-married households. 

The last rows in Tables 4b and 4w list coefficients on the unobserved factor, η. The 
26

estimates indicate that unobserved characteristics that increase the chances of a missed 

recertification also increase the chances of a case closure for information problems or of a 

closure for other reasons. However, for blacks, these same characteristics decrease the chances 

of a closure for financial ineligibility. The patterns of coefficients from these models and the 

application resolution models are consistent with positive selection. Specifically, unobserved 

characteristics that contribute to information problems in applications also contribute to 

information problems in subsequent participation spells, while unobserved characteristics that 

contribute to financial ineligibility rejections for applications also contribute to financial 

ineligibility closures in subsequent participation spells. 

7. Conclusion

In this report, we have used longitudinal, household-level program records from South 

Carolina’s Supplemental Nutrition Assistance Program to investigate two key processes that 

affect program participation. The first process is how applications to the SNAP are resolved, and 

the second is how resulting program participation spells end. Application resolutions have been 

mostly overlooked by previous studies, and no study has jointly examined application outcomes 

and participation spells together.

Nationally, only about two-thirds of households that appear to be eligible for the SNAP 

on the basis of their incomes and household sizes actually receive benefits under the program. 

Difficulties completing applications, supplying accompanying documentation, and providing 

continuing information—that is, difficulties with paperwork—could account for a substantial 

portion of this lack of take-up. In our sample of SNAP applications, approximately one third 

were rejected or otherwise unsuccessful. Some of the rejected applications came from 

households that were determined to be financially ineligible, but many more (about five out of 
27

every nine applications that were rejected) were turned down because of incomplete or 

insufficient information. Similarly, when we examine why SNAP participation spells end, 

roughly half of households stop receiving benefits because they fail to complete periodic 

recertifications and another sixth of households lose benefits because of incomplete or 

insufficient information. Only a fifth of households that stop receiving benefits do so because of 

a formal determination of financial ineligibility.

Completing paperwork takes some effort and motivation. For South Carolina’s SNAP, 

the necessary paperwork is similar to that of a simplified federal tax form. Undoubtedly, the 

reason why some households fail to complete applications, miss recertifications, and fail to 

supply other documentation is that they recognize or suspect that they are financially ineligible. 

However, it does not appear that financial ineligibility was the root cause of all of these 

outcomes. Indeed, households that had applications rejected for incomplete information had 

substantially lower amounts of UI-covered earnings than households with successful 

applications. Along the same lines, households that had their SNAP participation spells closed 

because of information deficiencies had higher average program benefits and lower average 

income levels than other households. These statistics suggest that the households had stronger 

financial incentives to comply with paperwork requirements, not weaker incentives.

Our report estimates multivariate models to identify the characteristics that are associated 

with successful applications and the reasons for application denials. We also estimate models 

that identify characteristics that are associated with program tenures and the reasons of case 

closures. Our models include standard economic measures—earnings, non-labor incomes, 

household sizes, and program benefits—that affect eligibility, the incentives to participate, or 

both and that have appeared in previous studies of caseload behavior. However, the models also 
28

include measures of households’ previous application and program experiences to help us see 

whether these characteristics are associated with households’ current application and program 

outcomes. We also estimate our models jointly in a way that allows us to control for 

unobservable characteristics that could mutually influence these outcomes.

Estimates from the models indicate that households’ resources and needs are associated 

with both application resolutions and subsequent participation spells, mostly in ways that we 

would expect. Other things held constant, households that we observe with higher levels of 

earnings are more likely to have their SNAP applications rejected than households with lower 

levels of earnings. The rejections are especially likely to occur because a determination of 

financial ineligibility. At the same time, households with more children (greater needs) are less 

likely to have their applications rejected. SNAP participants with higher levels of earnings are 

more likely than other participants to have their cases closed because of financial ineligibility 

and missed recertifications. However, higher earnings are associated with lower rates of exit for 

information problems and other reasons. Having more children in the household reduces the risk 

of a participation spell ending for eligibility reasons but increases the risk of a spell ending for 

some other reasons.

Program benefits are also associated with program tenures and the reasons for case 

closures. SNAP participants with higher benefits are less likely than other households to miss 

their recertifications, to provide incomplete or insufficient information, or have spells end for 

other reasons. These associations appear even after controlling for resources and needs, 

suggesting that the benefit itself provides an incentive to comply with program rules.

The more novel elements of our report involve examining how households’ application 

and participation histories are associated with their application and program spell outcomes. We 
29

do find evidence of these associations. Estimates from the multivariate models indicate that 

unobservable characteristics account for some of these associations. Thus, statistical controls for 

selection bias appear to be warranted. In particular, the results are consistent with positive 

selection in the sense that unobserved characteristics that contribute to one type of outcome at 

one time, such as an information problem with an application or participation spell, contribute to 

similar problems at other times. The estimates also indicate that unobserved characteristics that 

are positively associated with information problems and missed recertifications are negatively 

associated with financial ineligibility.

However, we also find that households' earlier SNAP application and participation 

experiences are predictive of their later experiences, even after controlling for other observable 

and unobservable characteristics. We find that applicants that have recently completed a 

participation spell are more likely to be successful in their applications than other applicants. 

This direct association could come about if households gain experience and familiarity with 

SNAP rules and procedures through the process of program participation. 

Among the applicants with recent program experience, the way in which a previous spell 

ends partly predicts how their next application will be resolved and how their next participation 

spell will end. Households face an increased risk of having a SNAP participation spell end for 

financial ineligibility if an earlier participation spell ended for that reason. Similarly, households 

face an increased risk of having their applications denied or participation spells end for 

information deficiencies if an earlier spell ended that way. Thus, while application and program 

experience may provide some general information about procedures, specific aspects of these 

procedures still appear to cause some clients repeated problems.

Our findings regarding program experiences indicate that there are opportunities for 
30

SNAP administrators and caseworkers to better target their assistance to applicants and clients. 

New applicants and clients seem to be especially prone to application denials and case closures. 

Also, applicants and clients who have experienced particular types of denials and case closures

appear to be at high risk of repeating those behaviors. These aspects of program experience are 

available through automated records and could, in principle, be shown to caseworkers as soon as 

a household applies. Households that appear to be at high risk for an unsuccessful program 

outcome could receive more information, more assistance at in-take, more follow up 

opportunities, or a combination of all of these.
31

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33

Table 1b: Characteristics of applicants by application outcome: cases headed by blacks

Approved

Income or 

assets too 

high

Failed to 

provide 

information

Other

denial or 

voluntary 

withdrawal

Case Income

UI Earnings 708.7 1333.7 437.8 683.3

UI Earnings Missing (%) 30.5 29.6 64.0 54.2

Previous Year Program History

Spell Closure in Past Year (%) 33.1 22.7 27.1 19.7

Months since Closure if positive 5.1 5.9 5.3 5.6

Spell Closed for Certification (%) 17.3 9.9 15.0 9.3

Spell Closed for Income (%) 7.6 9.8 4.2 4.3

Spell Closed for Information (%) 5.6 2.3 5.5 3.1

Spell Closed for Other/voluntary (%) 2.7 0.8 2.4 3.0

Denial in Past Year (%) 15.7 15.5 18.8 15.1

Months since Denial if positive 4.5 5.0 4.9 4.5

App. Denied for Income (%) 4.0 8.1 3.5 3.9

App. Denied for Information (%) 9.0 6.5 12.9 8.2

App. Denied for Other/voluntary (%) 2.7 0.8 2.4 3.0

PI Characteristics

Female (%) 94.4 92.4 93.9 94.1

Age 32.1 34.1 30.0 30.8

Education 11.7 11.8 11.5 11.3

Currently Married (%) 12.2 23.3 12.5 16.0

Formerly Married (%) 26.6 27.5 20.8 20.9

Case Composition

Number in case 3.4 3.5 3.3 3.3

Number of children 2.0 1.9 1.8 1.8

Number of Adults 1.4 1.6 1.5 1.5

Geographic Characteristics

County Unemployment Rate 6.1 6.1 5.5 6.0

County Population Density 2.1 2.0 2.3 2.0

Number of Applications 19,773 2,859 4,602 1,261

Notes: Authors’ calculations from South Carolina SNAP administrative records.
34

Table 1w: Characteristics of applicants by application outcome: cases headed by whites

Approved

Income or 

assets too 

high

Failed to 

provide 

information

Other

denial or 

voluntary 

withdrawal

Case Income 

UI Earnings 606.8 1080.9 380.9 644.8

UI Earnings Missing (%) 40.2 45.4 70.0 59.6

Previous Year Program History

Closure in Past Year (%) 28.3 16.8 25.1 16.0

Months since Closure if positive 5.2 5.8 5.4 5.7

Spell Closed for Certification (%) 15.6 8.5 14.5 8.3

Spell Closed for Income (%) 4.4 5.2 3.7 2.6

Spell Closed for Information (%) 5.5 2.3 4.7 2.7

Spell Closed for Other/voluntary (%) 2.7 0.8 2.2 2.4

Denial in Past Year (%) 13.4 12.5 15.7 13.7

Months since Denial if positive 4.6 5.0 5.3 4.9

App. Denied for Income (%) 3.0 5.8 3.2 4.0

App. Denied for Information (%) 7.7 6.0 10.3 7.3

App. Denied for Other/voluntary (%) 2.7 0.8 2.2 2.4

PI Characteristics

Female (%) 88.9 86.9 90.0 88.8

Age 31.7 32.7 30.1 30.5

Education 11.2 11.3 10.9 10.8

Currently Married (%) 33.7 47.8 32.4 33.0

Formerly Married (%) 39.4 29.8 33.0 29.0

Case Composition

Number in case 3.5 3.6 3.4 3.2

Number of children 1.9 1.8 1.8 1.6

Number of Adults 1.6 1.8 1.6 1.6

Geographic Characteristics

County Unemployment Rate 5.8 5.7 5.4 5.7

County Population Density 2.1 2.2 2.2 2.1

Number of applications 15,141 1,958 3,628 845

Notes: Authors’ calculations from South Carolina SNAP administrative records.
35

Table 2b: Characteristics at spell exit by reason for exit: cases headed by blacks

Missed 

recertification

Income or 

assets too 

high

Failed to 

provide 

information

Other loss 

of elig. or 

vol. exit

Censored 

Spell

Case Income and Benefits

Benefits 248.2 219.3 296.4 289.5 299.0

Reported earned income 605.3 725.7 330.1 282.9 441.1

Reported unearned income 288.7 368.3 283.4 306.5 279.5

Any earnings start of spell (%) 53.6 59.3 39.8 30.7 45.4

No income start of spell (%) 16.5 11.4 27.2 32.1 21.5

Previous year program historya

Months since closure if pos. 5.1 5.3 5.0 5.2 4.9

Spell closed for certification 20.6 11.1 16.0 13.0 18.4

Spell closed for income 5.9 13.5 5.7 4.9 8.2

Spell closed for information 5.9 4.2 7.5 4.0 5.5

Spell closed for other/voluntary 2.5 1.6 2.7 6.2 2.6

Months since denial if positive 4.5 4.7 4.4 4.5 4.6

App. denied for Income 3.5 7.0 3.3 2.5 4.4

App. denied for Information 10.8 7.1 11.3 8.2 8.7

App. denied for other/voluntary 2.5 1.6 2.7 6.2 2.6

Duration (months) 12.0 11.9 12.4 12.0 23.8

PI characteristics

Female (%) 94.5 94.3 93.5 93.3 95.2

Age 32.7 35.0 31.7 32.6 34.1

Education 11.8 12.0 11.7 11.7 11.9

Currently married (%) 11.2 19.1 10.2 11.9 8.5

Formerly married (%) 28.2 28.8 26.0 30.5 26.2

Case composition

Number of children 2.0 1.9 2.0 2.0 2.0

Number of adults 1.4 1.6 1.4 1.4 1.5

Geographic characteristics

County unemployment rate 6.0 6.5 6.1 6.4 6.6

County population density 2.1 2.0 2.2 1.9 2.2

Number of exits 8,174 3,515 2,540 1,543 4,001

Notes: Authors’ calculations from South Carolina SNAP administrative records. a Unless otherwise indicated, all program history variables are percents.
36

Table 2w: Characteristics at spell exit by reason for exit: cases headed by whites

Missed 

recertification

Income or 

assets too 

high

Failed to 

provide 

information

Other loss 

of elig. or 

vol. exit

Censored 

Spell

Case Income and Benefits

Benefits 280.4 253.6 316.5 307.6 314.0

Reported earned income 593.6 753.3 317.9 297.8 453.1

Reported unearned income 256.7 323.3 253.2 268.9 270.2

Any earnings start of spell (%) 51.5 59.0 35.1 31.2 45.7

No income start of spell (%) 20.8 14.1 33.3 35.1 23.8

Previous year program historya

Months since closure if pos. 5.3 5.5 4.9 5.2 5.0

Spell closed for certification 17.6 9.4 15.6 11.3 17.7

Spell closed for income 3.7 7.5 3.2 3.7 5.2

Spell closed for information 5.6 3.9 7.4 5.1 5.2

Spell closed for other/voluntary 2.6 1.4 3.4 5.0 2.2

Months since denial if positive 4.6 4.6 4.7 4.6 4.5

App. denied for Income 2.7 5.4 2.9 2.2 3.0

App. denied for Information 9.2 6.4 8.5 7.1 7.4

App. denied for other/voluntary 2.6 1.4 3.4 5.0 2.2

Duration (months) 10.8 9.3 9.2 8.9 18.5

PI characteristics

Female (%) 88.3 88.3 89.1 90.3 90.0

Age 32.4 33.7 31.3 31.8 33.4

Education 11.2 11.5 11.2 11.1 11.2

Currently married (%) 34.2 45.7 30.0 28.6 28.6

Formerly married (%) 41.6 34.7 43.2 43.9 40.4

Case composition

Number of children 1.9 1.9 1.9 1.9 1.9

Number of adults 1.6 1.7 1.6 1.5 1.6

Geographic characteristics

County unemployment rate 5.8 6.0 5.9 6.1 6.2

County population density 2.1 2.1 2.2 2.1 2.3

Number of exits 6,641 2,016 2,120 1,575 2,789

Notes: Authors’ calculations from South Carolina SNAP administrative records. a Unless otherwise indicated, all program history variables are percents.
37

Table 3b: Results from Multinomial Logit Application Model: Cases Headed by Blacks

Income or 

assets too high

Failed to 

provide info.

Other

ineligibility/ 

voluntary exit

Case income

UI earnings 0.104*** 0.041*** 0.073***

UI earnings missing 1.355*** 1.932*** 1.788***

Previous year program history

Months since closure 0.080*** 0.029** 0.066**

Spell closed for certification -0.908*** -0.253*** -0.959***

Spell closed for income -0.533*** -0.377*** -0.838***

Spell closed for information -1.154*** -0.113 -0.941***

Spell closed for other/voluntary -1.582*** -0.349** -0.461**

Months since denial 0.022 0.044*** -0.018

App. denied for income 0.172 -0.036 0.125

App. denied for information -0.189 -0.133 -0.205

App. denied for other/voluntary -0.489** -0.530*** 0.073

PI characteristics

Female 0.079 -0.038 0.210

Age spline, 18-21 years 0.206*** -0.146*** -0.422***

Age spline, 22-40 years 0.004 -0.043*** -0.030***

Age spline, 41+ years -0.002 -0.011 0.035***

Education spline, 0-12 years -0.119*** -0.057*** -0.072***

Education spline, 12+ years -0.003 -0.054 0.026

Completed high school or GED 0.596*** 0.236*** 0.036

Completed college -0.294 -0.202 -0.222

Currently married 0.416*** 0.029 0.297***

Formerly married 0.149** -0.080 -0.054

Case composition

Number of children 0-2 -0.430*** -0.252*** -0.283***

Number of children 3-5 -0.270*** -0.192*** -0.227***

Number of children 6-11 -0.289*** -0.156*** -0.188***

Number of children 12-14 -0.215*** -0.090** -0.223***

Number of children 15-17 -0.325*** 0.039 0.001

Number of adults 0.110*** 0.243*** 0.105**

Geographic characteristics

County unemployment rate 0.019 -0.020 -0.082**

County population density -0.451* -0.796*** -0.703**

πi (coefficients on unobserved factor, η) -0.472*** 0.464*** 0.133

Notes: The columns report estimated coefficients from a multinomial logit model of application 

resolutions that was estimated jointly with a competing-risk hazard model of SNAP exits (see 

text for details). In addition to the listed controls, the application resolution model included 

controls for fiscal year and county of residence. It was estimated using administrative records 

from South Carolina.

* Significant at .10 level. ** Significant at .05 level. *** Significant at .01 level.
38

Table 3w: Results from Multinomial Logit Application Model: Cases Headed by Whites

Income or 

assets too high

Failed to 

provide info.

Other

ineligibility/ 

voluntary exit

Case income

UI earnings 0.091*** 0.037*** 0.076***

UI earnings missing 1.502*** 1.852*** 1.735***

Previous year program history

Months since closure 0.065** 0.018 0.060*

Spell closed for certification -0.957*** -0.085 -0.877***

Spell closed for income -0.513*** 0.177 -0.782***

Spell closed for information -1.168*** -0.217* -1.038***

Spell closed for other/voluntary -1.556*** -0.264 -0.530

Months since denial 0.017 0.060*** 0.014

App. denied for income 0.233 0.035 0.213

App. denied for information -0.214 -0.222* -0.138

App. denied for other/voluntary -0.231 -0.412** 0.392

PI characteristics

Female 0.087 0.083 0.071

Age spline, 18-21 years 0.030 -0.163*** -0.275***

Age spline, 22-40 years -0.007 -0.037*** -0.030***

Age spline, 41+ years 0.026** -0.001 0.065***

Education spline, 0-12 years -0.072*** -0.029* -0.063***

Education spline, 12+ years -0.018 -0.134** -0.307**

Completed high school or GED 0.602*** 0.166*** 0.329***

Completed college 0.188 0.406 1.161*

Currently married 0.186** -0.205*** -0.244**

Formerly married -0.094 -0.279*** -0.425***

Case composition

Number of children 0-2 -0.244*** -0.334*** -0.509***

Number of children 3-5 -0.268*** -0.183*** -0.352***

Number of children 6-11 -0.218*** -0.165*** -0.311***

Number of children 12-14 -0.150*** -0.092* -0.227**

Number of children 15-17 -0.144** 0.016 -0.323***

Number of adults 0.232*** 0.220*** 0.056

Geographic characteristics

County unemployment rate 0.020 -0.023 -0.104**

County population density 0.309 -0.693** 0.642

πi (coefficients on unobserved factor, η) -0.470*** 0.655*** -0.151

Notes: The columns report estimated coefficients from a multinomial logit model of application 

resolutions that was estimated jointly with a competing-risk hazard model of SNAP exits (see 

text for details). In addition to the listed controls, the application resolution model included 

controls for fiscal year and county of residence. It was estimated using administrative records 

from South Carolina.

* Significant at .10 level. ** Significant at .05 level. *** Significant at .01 level.
39

Table 4b: Results from Discrete-Time Competing Risk Hazard Model of Food Stamp Exit 

for Specific Reason: Cases Headed by Blacks

Missed 

recertification

Income or 

assets too 

high

Failed to 

provide 

Information

Other

ineligibility/ 

voluntary 

exit

Case income and benefits

Benefits -0.237*** -0.045** -0.074*** -0.159***

Reported earned income 0.017*** 0.084*** -0.036*** -0.051***

Reported unearned income -0.001 0.094*** -0.024*** -0.037***

No income at start of spell 0.079* 0.023 0.337*** 0.420***

Any earnings at start of cert. period -0.291*** -0.287*** -0.284*** -0.445***

Previous year program history

Months since closure 0.020** 0.023* 0.007 0.020

Spell closed for certification 0.029 -0.444*** -0.111 -0.364***

Spell closed for income -0.131* 0.180** -0.035 -0.324**

Spell closed for information -0.035 -0.264** 0.081 -0.513***

Spell closed for other/voluntary -0.035 -0.466*** -0.032 0.514***

Months since denial -0.004 -0.001 -0.012 0.006

App. denied for income 0.046 0.298*** 0.094 -0.370*

App. denied for information 0.032 -0.056 0.061 -0.250*

App. denied for other/voluntary -0.173 0.131 0.089 0.126

Recertification months

Quarterly (before Oct. 2002) 2.220*** 0.560*** 0.286** 0.136

Semi-annual (Oct. 2002–Jan. 2005) 1.289*** 0.357** 0.829*** 0.296

Semi-annual (after Jan. 2005) 3.498*** 1.452*** 1.441*** 0.095

Annual (before Oct. 2002) 1.075*** 0.041 0.467** -0.929**

Annual (Oct. 2002–Jan. 2005) 2.133*** 0.858*** -0.412* -0.124

Earnings x quarterly (before Oct. 2002) 0.772*** 0.825*** 0.318** 0.084

Earnings x semi-ann. (Oct. 2002–2005) 2.169*** 1.468*** 0.391 0.449

Earnings x semi-ann. (after Jan. 2005) 0.361*** 0.914*** 0.635*** 0.799***

Earnings x annual (before Oct. 2002) -0.782*** -0.159 0.419** 0.895

Earnings x annual (Oct. 2002–2005) -1.815*** -0.934*** 0.306 -0.667

PI characteristics

Female -0.457*** -0.056 -0.529*** -0.253**

Age spline, 18-21 years -0.065 0.277*** -0.056 -0.215***

Age spline, 22-40 years -0.018*** 0.012*** -0.027*** -0.008

Age spline, 41+ years -0.028*** -0.011* -0.030*** -0.016

Education spline, 0-12 years -0.026 -0.046* -0.020 0.002

Education spline, 12+ years 0.090*** 0.134*** 0.034 0.030

Completed high school or GED 0.103** 0.490*** 0.069 -0.084

Completed college -0.023 0.087 -0.521 0.671**

Currently married 0.138** 0.346*** 0.138 0.470***

Formerly married 0.091** 0.001 0.082 0.286***

Case composition

Number of children 0-2 -0.093*** -0.252*** 0.008 0.198***
40

Number of children 3-5 -0.060** -0.334*** -0.011 0.180***

Number of children 6-11 -0.011 -0.318*** -0.002 0.137***

Number of children 12-14 -0.049* -0.271*** -0.060 0.063

Number of children 15-17 0.019 -0.273*** 0.029 0.016

Number of adults 0.080*** 0.043 0.180*** 0.075*

Geographic characteristics

County unemployment rate -0.026 -0.041* -0.032 -0.024

County population density -0.096 0.039 -0.396 -0.018

λi (coefficients on unobserved factor, η) 1.000 -0.153*** 0.631*** 0.183

Notes: The columns report estimated coefficients from a multinomial logit competing-risk 

hazard model of SNAP exits that was estimated jointly with a model of SNAP application 

resolutions (see text for details). In addition to the listed controls, the competing-risk hazard 

model included controls for the spell duration, fiscal year and county of residence. It was 

estimated using administrative records from South Carolina.

* Significant at .10 level. ** Significant at .05 level. *** Significant at .01 level.
41

Table 4w: Results from Discrete-Time Competing Risk Hazard Model of Food Stamp Exit 

for Specific Reason: Cases Headed by Whites

Missed 

recertification

Income or 

assets too 

high

Failed to 

provide 

Information

Other

ineligibility/ 

voluntary 

exit

Case income and benefits

Benefits -0.187*** 0.035 -0.048* -0.175***

Reported earned income 0.010** 0.086*** -0.036*** -0.055***

Reported unearned income -0.018*** 0.089*** -0.032*** -0.050***

No income at start of spell 0.157*** 0.054 0.332*** 0.293***

Any earnings at start of cert. period -0.506*** -0.221*** -0.432*** -0.361***

Previous year program history

Months since closure 0.028** 0.049** -0.034** -0.001

Spell closed for certification -0.082 -0.794*** 0.217** -0.349**

Spell closed for income -0.195* -0.118 0.083 -0.042

Spell closed for information -0.088 -0.560*** 0.198 -0.228

Spell closed for other/voluntary -0.141 -0.825*** 0.300* 0.328*

Months since denial 0.008 0.001 0.030 -0.005

App. denied for income -0.005 0.332** 0.048 -0.165

App. denied for information -0.124 -0.171 -0.300** -0.224

App. denied for other/voluntary -0.124 0.260 0.083 -0.042

Recertification months

Quarterly (before Oct. 2002) 2.589*** 0.421*** 0.289* 0.104

Semi-annual (Oct. 2002–Jan. 2005) 1.273*** -0.241 0.236 0.205

Semi-annual (after Jan. 2005) 3.849*** 1.429*** 1.023*** 0.395

Annual (before Oct. 2002) 1.122*** -0.195 0.259 -0.956

Annual (Oct. 2002–Jan. 2005) 2.607*** 1.246*** 0.020 -0.663

Earnings x quarterly (before Oct. 2002) 1.062*** 0.790*** 0.583*** 0.398**

Earnings x semi-ann. (Oct. 2002–2005) 2.678*** 1.663*** 0.617** 0.308

Earnings x semi-ann. (after Jan. 2005) 0.564*** 0.844*** 0.896*** 0.616**

Earnings x annual (before Oct. 2002) -0.876*** 0.038 0.031 -0.119

Earnings x annual (Oct. 2002–2005) -2.272*** -0.905** 0.202 0.366

PI characteristics

Female -0.348*** 0.110 -0.267*** 0.014

Age spline, 18-21 years -0.154*** 0.149* -0.125** -0.077

Age spline, 22-40 years -0.028*** 0.001 -0.028*** -0.018**

Age spline, 41+ years -0.023*** -0.007 -0.053*** -0.016

Education spline, 0-12 years -0.002 -0.010 0.033 -0.042*

Education spline, 12+ years 0.026 0.152*** -0.065 0.070

Completed high school or GED -0.037 0.321*** 0.006 0.055

Completed college 0.059 -0.038 0.381 0.332

Currently married 0.227*** 0.291*** 0.145* 0.181**

Formerly married 0.170*** 0.009 0.191*** 0.129*

Case composition

Number of children 0-2 -0.199*** -0.374*** 0.015 0.192***
42

Number of children 3-5 -0.021 -0.362*** -0.096* 0.146**

Number of children 6-11 -0.022 -0.303*** -0.024 0.175***

Number of children 12-14 0.049 -0.379*** -0.016 0.080

Number of children 15-17 0.114*** -0.226*** -0.023 0.110

Number of adults 0.050* 0.050 0.134*** 0.011

Geographic characteristics

County unemployment rate -0.036* -0.022 -0.048 0.047

County population density -0.253 0.244 0.201 -0.894**

λi (coefficients on unobserved factor, η) 1.000 -0.018 0.843*** 0.336**

Notes: The columns report estimated coefficients from a multinomial logit competing-risk 

hazard model of SNAP exits that was estimated jointly with a model of SNAP application 

resolutions (see text for details). In addition to the listed controls, the competing-risk hazard 

model included controls for the spell duration, fiscal year and county of residence. It was 

estimated using administrative records from South Carolina.

* Significant at .10 level. ** Significant at .05 level. *** Significant at .01 level.
43

Figure 1 - Number of Applications by Resolution

0

1000

2000

3000

4000

5000

6000

7000

Oct-97

Apr-98

Oct-98

Apr-99

Oct-99

Apr-00

Oct-00

Apr-01

Oct-01

Apr-02

Oct-02

Apr-03

Oct-03

Apr-04

Oct-04

Apr-05

Oct-05

Apr-06

Oct-06

Apr-07

Oct-07

Month

Approved Denied - Income Denied - Information Denied - Other

Figure 2 - Number of Exits by Type of Exit

0

500

1000

1500

2000

2500

3000

3500

4000

Oct-97

Apr-98

Oct-98

Apr-99

Oct-99

Apr-00

Oct-00

Apr-01

Oct-01

Apr-02

Oct-02

Apr-03

Oct-03

Apr-04

Oct-04

Apr-05

Oct-05

Apr-06

Oct-06

Apr-07

Oct-07

Month

Recertification Income Information Other
44

Appendix A. Detailed reasons for food stamp application denial by race of case head

Blacks Whites

Reason for denial Number Percent Number Percent

Income or assets too high 2,859 32.78 1,958 30.44

 IN: Income (net) meets/exceeds req. 2,139 24.52 1,482 23.04

 IE: Increase–earned income 409 4.69 270 4.20

 RE: Resources 237 2.72 155 2.41

 IU: Unearned income exceeds limits 74 0.85 51 0.79

Failed to provide reliable information 4,602 52.75 3,628

 FP: Failed to provide info. (S-Gen)

56.41

2,799 32.09 2,237 34.78

 FC: Failed to complete interview (S-Gen) 1,578 18.09 1,268 19.72

 FI: Failed to furnish information 208 2.38 99 1.54

 VR: Verification–failed to provide 17 0.19 24 0.37

Other loss of eligibility 1,261 14.43 844

 VW: Voluntary withdrawal

13.15

855 9.80 621 9.66

 HH: No eligible household members 139 1.59 58 0.90

 AE: Application opened in error 77 0.88 45 0.70

 VQ: Voluntary quit 52 0.60 25 0.39

 SH: Not separate FS household 50 0.57 31 0.48

 NR: Nonresident 38 0.44 33 0.51

 CL: Cannot locate 10 0.11 19 0.30

 CC: Opened/closed case with claim 12 0.14 3 0.05

 CH: Change in law/policy 6 0.07 1 0.01

 CD: Drug conviction 10 0.11 4 0.06

 WR: Work req.–refused/failed to comply 1 0.01 1 0.02

 DF: HH disqualified for fraud 3 0.03 0 0.00

 AB: ABAWD time limit expired 3 0.03 0 0.00

 ET: Failure to comply with E&T req. 3 0.03 0 0.00

 SP: Strike participation 1 0.01 0 0.00

 UA: Undocumented alien 1 0.01 0 0.00

 FE: Fail to accept reim. comp.–FS E&T 0 0.00 1 0.02

 DR: Disqualified–misrep. residency/ID 0 0.00 1 0.02

 FF: Fleeing felon–probation parole 0 0.00 1 0.02

Source: Authors’ calculations from South Carolina SNAP administrative records.
45

Appendix B. Detailed reasons for food stamp exits by race of case head

Blacks Whites

Reason for exit Number Percent Number Percent

Missed recertification 8,174 51.83 6,641 61.53

 MR: Failed to file MR 5,159 32.71 4,233 39.22

 CE: Closed–certification end (S-Gen) 3,015 19.12 2,408 22.31

Income or assets too high 3,515 22.29 2,016

 IN: Income (net) meets/exceeds req.

18.68

2,679 16.99 1,577 14.61

 IE: Increase–earned income 634 4.02 321 2.97

 IU: Unearned income exceeds limits 149 0.94 87 0.81

 RE: Resources 51 0.32 31 0.29

 LS: Lump sum ineligibility 2 0.01 0 0.00

Failed to provide reliable information 2,540 16.10 2,120

 FI: Failed to furnish information

19.64

1,468 9.31 1,347 12.48

 FP: Failed to provide info. (S-Gen) 692 4.39 417 3.86

 VR: Verification–failed to provide 162 1.03 217 2.01

 FC: Failed to complete interview (S-Gen) 168 1.07 103 0.95

 IM: Incompletely Verified MR 50 0.32 36 0.33

Other loss of eligibility 1,543 9.78 1,575

 NR: Nonresident

14.59

516 3.27 552 5.11

 VW: Voluntary withdrawal 393 2.49 433 4.01

 CL: Cannot locate 273 1.73 323 2.99

 HH: No eligible household members 128 0.81 107 0.99

 WR: Work req.–refused/failed to comply 15 0.10 8 0.07

 VQ: Voluntary quit 27 0.17 16 0.15

 ET: Failure to comply with E&T req. 41 0.26 23 0.21

 AE: Application opened in error 47 0.30 40 0.37

 AB: ABAWD time limit expired 17 0.11 4 0.04

 DE: Death 30 0.19 17 0.16

 CC: Opened/closed case with claim 24 0.15 18 0.17

 SH: Not separate FS household 13 0.08 15 0.14

 QC: Refused to cooperate with QC 8 0.05 2 0.02

 CH: Change in law/policy 9 0.05 1 0.01

 DF: HH disqualified for fraud 2 0.01 1 0.01

 FE: Fail to accept reim. comp.–FS E&T 3 0.02 7 0.06

 SS: SSN–refused/failed to furnish/apply 1 0.01 0 0.00

 CD: Drug conviction 0 0.00 3 0.03

 DR: Disqualified–misrep. residency/ID 0 0.00 1 0.01

 FF: Fleeing felon–probation parole 0 0.00 3 0.03

 RJ: Refused to accept a job 0 0.00 1 0.01

Source: Authors’ calculations from South Carolina SNAP administrative records.