Abstract

This study examines the degree to which changes in entry and exit patterns into and out

of the Food Stamp Program (FSP) contributed to the FSP caseload growth of the early

1990s and to the decline of the late 1990s. A rise in the FSP entry rate was the driving

force behind caseload growth in the early 1990s. However, individuals tended to stay

longer in the FSP during this period than at other points of the 1990s, which also contributed to the growth. Caseload decline of the late 1990s was driven predominantly by

shorter participation length, although lower entry rates also contributed. The entry rate for

single mothers remained relatively constant over the 1990s, but participation length

declined in the late 1990s. Despite eligibility restrictions in the late 1990s, the entry rate

for noncitizens also remained fairly constant. While the entry rate for able-bodied adults

fell after time limits were imposed in the mid-1990s, their participation length appeared

unaffected by these limits, which may reflect the tendency for able-bodied adults to have

short participation spells even without time limits. Among all new entrants in the FSP in

the 1990s, more than half exited the program within 8 months and two-thirds exited within 1 year. Among individuals participating in the FSP for longer than 1 year, the typical

participation length declined over the 1990s.

United States 

Department 

of Agriculture

www.ers.usda.gov

Electronic Report from the Economic Research Service

July 2005

Contractor

and Cooperator

Report No. 8

Food Stamp Program 

Entry and Exit

An Analysis of Participation

Trends in the 1990s

By Scott Cody, Phil Gleason, Bruce Schechter, 

Miki Satake, and Julie Sykes, Mathematica Policy

Research, Inc.

ERS project representative: Kenneth Hanson, 

khanson@ers.usda.gov, 202-694-5427

Food Assistance 

and Nutrition 

Research Program

This report was prepared by the Mathematica Policy Research, Inc.,

under a cooperative agreement with the Economic Research

Service. The views expressed are those of the authors and not 

necessarily those of ERS or USDA.
ii

ACKNOWLEDGMENTS 

This work was conducted through a cooperative agreement research grant from the Food 

Assistance and Nutrition Research Program at the U.S. Department of Agriculture, Economic 

Research Service (ERS). Many people contributed in significant ways to the preparation of this 

report. We received valuable comments on methodology, substantive issues, and presentation 

from several staff at ERS, including Kenneth Hanson, Margaret Andrews, Mark Prell, and Parke 

Wilde. At Mathematica Policy Research, Jon Jacobson provided useful comments on the content 

of the report. Molly N. Cameron and Jim Cameron edited the report, and Donna Dorsey was 

responsible for production. 
iii

CONTENTS 

Chapter Page 

 EXECUTIVE SUMMARY ....................................................................................... viii 

 I INTRODUCTION .........................................................................................................1 

 A. STUDY OBJECTIVES AND RESEARCH QUESTIONS ................................3 

 B. SOURCES OF DATA.........................................................................................5 

 1. FSPQC ........................................................................................................6 

 2. SIPP............................................................................................................11 

 C. PREVIOUS RESEARCH..................................................................................13 

 D. OUTLINE FOR REMAINDER OF REPORT..................................................16 

 II FSP RATES OF ENTRY AND EXIT.........................................................................17 

 A. RESULTS FROM SIPP-BASED ANALYSIS .................................................17 

 B. RESULTS FROM FSPQC-BASED ANALYSIS.............................................25 

 C. ENTRY AND EXIT BY SUBGROUP.............................................................34 

 III TRENDS IN FSP PARTICIPATION SPELLS...........................................................39 

 A. ENTRY COHORT ANALYSIS .......................................................................40 

 1. FSPQC-Based Estimates............................................................................40 

 2. SIPP-Based Estimates................................................................................44 

 3. Subgroups ..................................................................................................48 

 B. CROSS-SECTIONAL COHORT .....................................................................51 

 1. FSPQC-Based Estimates............................................................................51 

 2. SIPP-Based Estimates................................................................................52 
iv

CONTENTS (continued) 

Chapter Page 

 IV CONCLUSIONS..........................................................................................................59 

 REFERENCES ............................................................................................................67 

 APPENDIX A: INCONSISTENCIES IN SIPP DATA...............................................69 
v

TABLES 

Table Page 

 1 MONTHLY CHANGE IN FSP PARTICIPANTS, 2002..............................................4 

 2 ADVANTAGES AND DISADVANTAGES OF FSPQC AND SIPP DATA..............7 

 3 EXAMPLE OF FSPQC UNDERSAMPLE OF INDIVIDUALS IN FIRST AND 

 SECOND MONTH OF RECEIPT: FEBRUARY 1996 ................................................9 

 4 SIPP PANEL INFORMATION...................................................................................12 

 5 DURATION OF PARTICIPATION SPELLS IN THE EARLY 1990s .....................14 

 6 AVERAGE MONTHLY FSPQC-BASED GROWTH, REPLACEMENT, 

 AND EXIT RATES, 1990 THROUGH 2002..............................................................19 

 7 DECOMPOSITION OF CHANGES IN FSPQC-BASED CASELOAD 

 GROWTH RATES.....................................................................................................24 

 8 AVERAGE MONTHLY SIPP-BASED GROWTH, REPLACEMENT, AND 

 EXIT RATES, 1990 THROUGH 1999 .......................................................................28 

 9 DECOMPOSITION OF CHANGES IN SIPP-BASED CASELOAD GROWTH 

 RATES ........................................................................................................................32 

10 PERCENT OF GROWTH RATE CHANGE EXPLAINED BY 

 REPLACEMENT RATES FOR VARIOUS ADJUSTMENTS TO 1996 SIPP 

 REPLACEMENT AND EXIT RATES.......................................................................34 

 11 ADJUSTMENTS TO 1996-BASED REPLACEMENT AND EXIT RATES 

 BY SUBGROUP..........................................................................................................36 

 12 OUTCOMES FOR FSP-EXITERS, 1990-1999..........................................................38 

 13 LIFE TABLE OF FSP PARTICIPATION SPELLS ENTRY COHORT 

 FSPQC-BASED ESTIMATES, 1990-1999 ................................................................42 

 14 COMPARISON OF PARTICIPATION SPELLS ENTRY COHORT 

 SIPP-BASED ESTIMATES, 1990-1999.....................................................................43 

 15 SIMULATED CASELOAD USING FSPQC-BASED EXIT RATES 

 1990 THROUGH 1993 VS. 1996-1999.......................................................................44 
vi

TABLES (Continued) 

Table Page 

 16 LIFE TABLE OF FSP PARTICIPATION SPELLS ENTRY COHORT 

 FSPQC-BASED ESTIMATES, 1990-1999 ................................................................46 

 17 COMPARISON OF PARTICIPATION SPELLS ENTRY COHORT 

 SIPP-BASED ESTIMATES, 1990-1999.....................................................................47 

 18 COMPARISON OF SPELL LENGTH DISTRIBUTIONS SIPP ESTIMATES 

 FOR ENTRY COHORT SUBGROUPS, 1990-1999 ..................................................49 

 19 COMPARISON OF SPELL LENGTH DISTRIBUTIONS SIPP-BASED 

 ESTIMATES FOR ENTRY COHORT SUBGROUPS, BY PERIOD .......................50 

 20 SURVIVOR AND EXIT RATES FOR FSPQC-BASED MARCH 1996 

 CROSS-SECTIONAL COHORT................................................................................53 

 21 SURVIVOR AND EXIT RATES FOR SIPP-BASED MARCH 1996 

 CROSS-SECTIONAL COHORT................................................................................53 

 22 SURVIVOR AND EXIT RATES FOR SIPP-BASED FEBRUARY 1991 

 CROSS-SECTIONAL COHORT................................................................................56 

 23 COMPARISON OF SPELL LENGTH DISTRIBUTIONS, FEBRUARY 1991 

 VS. MARCH 1996 SIPP-BASED ESTIMATES ........................................................56 
vii

FIGURES 

Figure Page 

 1 FSP PARTICIPATION, 1990-2002 ..............................................................................2 

 2 MONTHLY CHANGE IN FSP PARTICIPANTS, 2002..............................................2 

 3 AVERAGE MONTHLY FSPQC-BASED GROWTH, REPLACEMENT, 

 AND EXIT RATES, 1990-2002..................................................................................20 

 4 FSPQC-BASED REPLACEMENT AND EXIT RATES FOR FSP 

 PARTICIPANTS .........................................................................................................22 

 5 AVERAGE MONTHLY SIPP-BASED GROWTH, REPLACEMENT, AND 

 EXIT RATES, 1990-1999 ...........................................................................................30 

 6 SIPP-BASED REPLACEMENT AND EXIT RATES, 1990-199 ..............................31 

 7 SIPP-BASED AVERAGE GROWTH, REPLACEMENT, AND EXIT 

 RATES BY SUBGROUP, 1990-1999.........................................................................37 

 8 SURVIVOR RATES FOR CROSS-SECTIONAL COHORTS, 

 FEBRUARY 1991 AND MARCH 1996.....................................................................54 
viii

EXECUTIVE SUMMARY 

During the 1990s, the Food Stamp Program (FSP) caseload experienced periods of both 

substantial growth and substantial decline. Between 1990 and 1994, the caseload increased from 

20 million to 29 million participants—an increase of more than 44 percent. After 1994, the 

caseload fell by more than 12 million participants—a decline of 43 percent. In 1997 alone, the 

caseload fell by 12.5 percent. The period of decline ended in 2001, and by January 2004, the 

caseload had risen by about 38 percent. These trends coincided with significant changes in the 

national economy as well as major changes in FSP policies. 

Increases and decreases in the monthly number of FSP participants result from changes in 

rates of entry and exit. Caseloads can grow because individuals enter the program at a faster rate, 

because individuals exit the program at a slower rate, or both. Likewise, caseloads can decline 

because individuals exit at a faster rate, enter at a slower rate, or both. However, little is known 

about how these factors combined to influence FSP caseload trends in the 1990s. While caseload 

sizes changed in response to policy and economic changes, policymakers do not know the degree 

to which the response reflected a change in entry patterns versus a change in the length of time 

individuals participated in the program. Understanding whether caseload trends are driven by 

changes in entry or changes in exit is important both for judging the success of existing policies 

and for developing effective policies in the future. 

This study examines patterns in the rates of FSP entry and exit, and how those patterns 

contribute to the caseload trends of the 1990s. Specifically, we examine monthly replacement 

rates (defined as the number of new FSP entrants in a month divided by the previous month’s 

caseload) and exit rates (defined as the number of people participating in the previous month but 

not the current month divided by the previous month’s caseload). As another way of examining 

changes in exit rates, we examine changes in the length of participation spell: if participation 

spells tend to get shorter, then exit rates are increasing, but if participation spells tend to get 

longer, then exit rates are decreasing. 

The five research questions addressed in this study are: 

1. How did growth rates, replacement rates, and exit rates change over the course of 

the 1990s? 

2. Are the changes in the growth rates explained by changes in the replacement rate, 

changes in the exit rate, or both? 

3. How long did individual FSP participation spells tend to last? 

4. Have FSP spell lengths changed over time? 

5. Did replacement rates, exit rates, and spell lengths vary for FSP subpopulations, 

including the elderly, able-bodied adults, single mothers, and the working poor? 
ix

RESULTS 

This study examines patterns of FSP entry and exit for all participants and for various 

subgroups. We examine how rates of entry and exit changed and how those changes influenced 

caseload growth. This study also updates earlier estimates of participation spell patterns. We 

construct all estimates twice, using two sources of data: (1) the Food Stamp Program Quality 

Control (FSPQC) database and (2) the Survey of Income and Program Participation (SIPP). The 

results yield the following conclusions: 

• Caseload changes during the 1990s were driven both by changes in the rate that 

people entered the program as well as by the length of time that people participated. 

• Much of the caseload growth of the early 1990s was caused by increasing 

replacement rates, although lengthening participation spells also contributed to the 

growth. 

• Much of the caseload decline of the late 1990s was caused by shorter participation 

spells. In particular, participation spells among long-term participants were reduced 

substantially. 

• During the entire 1990 to 1999 period, more than half of new entrants exited the 

program within between six and eight months, and about two-thirds of new entrants 

exited within one year. 

• In any given month, the caseload consisted of a large portion of long-term 

participants. In March 1996, between one-third and one-half of participants were in 

the middle of spells longer than four and a half years (a substantial decline from 

earlier estimates which indicated that in 1992 one-half of participants were in the 

middle of spells longer than eight years). 

• Single mothers entered the FSP at a relatively constant rate throughout the 1990s. 

The length of time that single mothers participated in the FSP declined over the 

course of the 1990s. 

• Because able-bodied adults have always experienced short FSP participation spells, 

the time limits on FSP benefits imposed through welfare reform had only a minor 

impact on the length of their participation spells. 

• There is no evidence that the welfare reform changes of 1996, which denied 

eligibility to certain types of noncitizens, lowered rates of food stamp program entry 

among noncitizens. 

 The specific answers to the study’s five research questions are discussed below. Results are 

discussed across three distinct periods of caseload change, each about three years in duration and 

reflecting different stages of the caseload growth cycle. The first was a period of caseload 

growth from 1990 to 1993; the second was a period of some caseload decline between 1993 and 

1996; the third was a period of sharp caseload decline from 1996 to 1999. 
x

TABLE ES-1 

AVERAGE MONTHLY GROWTH RATES, REPLACEMENT RATES, 

AND EXIT RATES, 1990 THROUGH 1999 

FSPQC-Based Estimates SIPP-Based Estimates 

Average 

Growth 

Ratea

Average 

Replacement 

Rateb

Average 

Exit 

Ratec

Average 

Growth 

Ratea

Average 

Replacement 

Rateb

Average 

Exit 

Ratec

Overall -0.2 7.0 7.2 0.0 4.4 4.4 

Caseload Growth 

1990-1993 0.9 7.5 6.7 1.4 5.3 3.9 

Caseload Decline I 

1993-1996 -0.4 6.8 7.2 0.0 4.2 4.2 

Caseload Decline II 

1996-1999 -0.9 6.7 7.6 -1.3 3.8 5.1 

SOURCE: 1990-2002 FSPQC data; 1990-1996 SIPP panels (1996 SIPP-based estimates are adjusted). 

a

Reflects the average monthly percent change in the number of FSP participants. Computed as average 

monthly difference between the replacement rate and the exit rate. 

b

Computed as the average monthly number of new entrants as a percent of the previous months number of 

participants. 

c

Computed as the average monthly number of individuals that left the FSP as a percent of the previous 

month’s number of participants. 

Question 1: How did growth rates, replacement rates, and exit rates change over the course 

of the 1990s? 

Both FSPQC and SIPP data indicate that replacement rates fell and exit rates increased 

during the 1990s (Table ES-1). Replacement rates were at their lowest levels during the period of 

caseload decline in the late 1990s. Thus, as the caseload peaked and subsequently began to 

decline, there were fewer new entrants relative to the previous month’s caseload. At the same 

time, exit rates were at their highest during the decline, so relative to the previous month’s 

caseload, the number leaving the FSP each month grew. 

Replacement rates and exit rates tended to be higher in FSPQC than in SIPP analyses. In 

FSPQC data, the average replacement and exit rates for the 1990s were 7.0 and 7.2 percent, 

respectively. In SIPP, the rates for the same period were each 4.4 percent. A likely explanation 

for this difference is that the frequency of reported entry and exits increased in the 1996 SIPP 

panel. Changes to the survey implemented in 1996 may have led to changes in the way entries 

and exits were reported. At the same time, it is possible that FSPQC may slightly overstate entry 

and exit rates. Nevertheless, because FSPQC data are weighted to match administrative 

participation counts, these estimated growth rates are considered more reliable. 
xi

TABLE ES-2 

PERCENT OF CHANGE IN GROWTH RATE EXPLAINED BY CHANGES IN REPLACEMENT 

AND EXIT RATES, 1990 THROUGH 1999 

FSPQC-Based Rates SIPP-Based Rates 

Growth Rate Change 

Percent 

Explained by 

Change in 

Replacement 

Rate 

Percent 

Explained by 

Change in Exit 

Rate 

Percent 

Explained by 

Change in 

Replacement 

Rate 

Percent 

Explained by 

Change in Exit 

Rate 

Growth (1990-1993) to 

Decline I (1993-1996) 55.7 44.3 77.2 22.8 

Decline I (1993-1996) 

to Decline II (1996-

1999) 30.3 69.7 28.2 71.8 

Growth (1990-1993) to 

Decline II (1996-1999) 47.8 52.2 53.8 46.2 

Question 2: Are the changes in the growth rates explained by changes in the replacement 

rate, changes in the exit rate, or both? 

The rapid growth in FSP participation in the early 1990s changed to a slight decline in the 

mid 1990s. This shift can be explained more by a reduction in the rate people entered the 

program (the replacement rate) than by an increase in the rate that people exited the program 

(Table ES-2). However, the two data sources used in this study yield different estimates of the 

relative importance of changes in the rate at which individuals enter the program. According to 

FSPQC data, the fact that individuals entered the FSP at lower rates explains just over half of the 

shift between rapid growth and slight decline, while according to SIPP data, lower rates of entry 

explain 77 percent of the shift. 

The slight decline of the mid 1990s then changed to a rapid decline in the late 1990s because 

participants were exiting at higher rates (and thus had shorter participation spells). Both data sets 

estimate that rising exit rates explain more than two-thirds of the shift in growth rates between 

the mid-1990s and the late 1990s. These changes are particularly policy-relevant given that the 

steep decline followed the sweeping welfare reform changes of the Personal Responsibility and 

Work Opportunity Reconciliation Act of 1996 (PRWORA). During this period, the exit rates 

were higher than at any other point in the decade. 

But the overall conclusion for the 1990s is that neither the replacement rate nor the exit rate 

was solely responsible for explaining caseload changes. When we examine the relative roles of 

replacement and exit rate changes in the shift from the caseload growth period of 1990 to 1993 to 

the caseload decline period of 1996 to 1999, both FSPQC and SIPP indicate that the two factors 

have equal weight in explaining the caseload changes. As a result, policymakers should consider 
xii

the implications of policy and economic changes on both the rate at which people enter the 

program and on the length of time that they participate. 

Question 3: How long did individual FSP participation spells tend to last? 

According to both SIPP and FSPQC data, over half of all new entrants into the FSP exited 

the program by somewhere between six and eight months, and approximately two-thirds of new 

entrants exited by the end of one year in the program. Only about one out of every three new 

entrants participated in the program for longer than one year. Among those new entrants with 

spells longer than one year, the duration of their spells was estimated to be longer in SIPP data 

(where more than 20 percent of new entrants participated for over two years) than in FSPQC data 

(where just over 10 percent of new entrants participated for more than two years). 

Examining participation spells of new entrants tells only part of the story. While new 

entrants that become short-term participants cycle off of the program after a few months, new 

entrants that become long-term participants tend to accumulate on the caseload. Thus, in any 

given month, a large proportion of the caseload will be long-term participants. 

According to FSPQC data, half of all individuals participating in March 1996 were in the 

middle of participation spells longer than two years, and one-third of all participants had 

participation spells lasting longer than four and a half years. SIPP data estimate that the caseload 

that month had an even higher proportion of long-term cases. According to SIPP, half of the 

individuals participating in March 1996 were in the middle of participation spells lasting longer 

than four and a half years. Both data sources indicate that there were far fewer long-term 

participants in 1996 than in 1991, where prior studies using SIPP data estimate that half of 

participants were in the middle of participation spells lasting longer than eight years. The 

reasons for the substantial differences between FSPQC and SIPP estimates of participation spells 

in March 1996 are not fully understood. However, it is possible that the respective data 

collection methods lead FSPQC to underestimate participation spells and lead SIPP data to 

overestimate participation spells. 

Question 4: Have FSP spell lengths changed over time? 

 FSPQC data estimate that participation spells became shorter over the 1990s. According to 

FSPQC data, 25 percent of individuals that entered the program in the early 1990s exited by the 

end of their fourth month, and 50 percent by the end of their seventh month. In the late 1990s, 25 

percent of program entrants exited by their third month and 50 percent by their sixth month. 

While these differences may seem modest, the fact that at least 50 percent of new entrants were 

exiting faster led to substantial declines in the caseload. 

 SIPP data, on the other hand, estimate that participation spells were relatively constant over 

time. Among individuals who entered the FSP in the early 1990s as well as in the late 1990s, 

SIPP estimates indicate that the 25 percent exit by their fourth month and 50 percent exit by their 

eighth month. 
xiii

 

Among households with relatively long participation spells, both FSPQC and SIPP data 

estimate that spells became shorter over the 1990s, but the estimates differ on the magnitude of 

the decrease. According to FSPQC data, the 75th percentile spell length (the point at which 75 

percent of individuals who entered the program exit) fell from 13 months in the early 1990s to 12 

months in the late 1990s. According to SIPP data, the 75th percentile fell from 26 months to 16 

months. Some of this change may be driven by changes in the data, as rates of entry and exit 

experience an unexplained increase in later years of SIPP data. 

Question 5: Did replacement rates, exit rates, and spell lengths vary for FSP 

subpopulations? 

According to SIPP data, participation trends among single mothers are explained 

predominantly by the exit rate.1

 The replacement rate for single mothers stayed relatively 

constant during the 1990s. On the other hand, the exit rate was low during the growth of the 

early 1990s and was high during the declines of the late 1990s. Thus, compared with the rest of 

the FSP population, single mothers tended to enter the program at a more stable rate but the 

length of time they participated varied more. According to SIPP data, the exit rate explained 

57.6 percent of single mother caseload trends in the early 1990s and 63.6 percent in the late 

1990s. 

Compared with other subgroups, single mothers had relatively long participation spells. The 

median spell for the entire period was 11 months, which reflects a decline from 13 months in the 

early 1990s to 8 months in the late 1990s. 

Somewhat surprisingly, the replacement rate for noncitizens did not decline after the 

eligibility restrictions of PRWORA. The replacement rate for noncitizens in the 1996 to 1999 

period (4.7 percent) was almost the same level as in the 1990 to 1993 period (4.9 percent). The 

length of participation among noncitizens did change, however. The exit rate increased from 3.8 

percent in the early 1990s to 5.3 percent in the late 1990s, and the median participation spell fell 

from 12 months to 8 months among this population. 

Another group with eligibility restrictions is the group composed of able-bodied adults 

without dependents (ABAWDs). In 1996, welfare reform subjected ABAWDs to time-limited 

food stamp participation (unless they were meeting work requirements, ABAWDs could receive 

no more than three months of FSP benefits). The replacement rate for ABAWDs fell from 13.3 

percent in the early 1990s to 10.1 percent in the late 1990s, suggesting that ABAWDs potentially 

were deterred from entering the FSP. The exit rate for this population increased somewhat from 

10.5 percent in the early 1990s to 11.8 percent in the late 1990s. ABAWDs had the shortest 

participation spells of all subgroups examined, with half of all ABAWDs exiting by the end of 

their fourth month and three-fourths exiting by the end of their ninth month. Despite time limits 

1

 Subgroup analysis is conducted on SIPP data only. Subgroup analysis is not possible in the 

FSPQC because estimates are derived from repeat cross-section analysis. As a result, we cannot 

distinguish changes in status of existing caseload households (e.g., from non-working poor to 

working poor) from new entrant households. 
xiv

imposed through PRWORA, the short ABAWD participation spells remained relatively constant 

during the 1990s. This may reflect the fact that able-bodied adults always tended to have short 

participation spells, even without time limits. 

Caseload trends for the elderly are driven more by entry patterns than exit patterns—the exit 

rate among the elderly remained between 2.5 and 2.7 percent over the 1990s. Compared with 

other groups, the elderly had the longest participation spells. Among all new entrant elderly 

individuals during the 1990s, half had spells of 15 months or longer. Spells were longest during 

the early 1990s, when half of the elderly had spells of 20 months or longer. Participation spells 

for the elderly experienced the sharpest decline among all of the subgroups, with the median 

falling to 12 months in the late 1990s. 

Conclusion 

To conclude, caseload changes appear to be driven by changes in both the rate individuals 

entered the program and the length of time that they stay on the program. The caseload growth 

period of the early 1990s was driven predominantly by an increase in the rate individuals entered 

the program; the caseload decline of the late 1990s was driven predominantly by a shortening of 

the length of time individuals participated. Throughout the 1990s, about two-thirds of new 

entrants exit the program within one year. Participation spells for those participating for more 

than one year shortened over the 1990s, and there is some evidence that participation spells for 

those participating under one year also shortened. Among subgroups, single-mothers tended to 

enter at a constant rate but responded to economic and policy changes through changes in spell 

length. A similar pattern was observed for noncitizens. Participation spells for ABAWDs, who 

have always had short participation spells, appear to have been unaffected by time limits 

imposed in the 1990s. 
1 

I. INTRODUCTION 

During the 1990s, the Food Stamp Program (FSP) caseload experienced substantial growth, 

followed by an equally substantial decline. In the four years between 1990 and the caseload 

peak in 1994, the FSP caseload grew by almost 9 million individuals, an increase of over 44 

percent (Figure 1). Monthly growth rates were largest before 1992, when the caseload grew at 

an average of over 1 percent per month (Figure 2). Then, between 1994 and 2001, the caseload 

decreased by more than 12 million people. Caseload declines were sharpest in 1997, when the 

number of participants decreased by an average of more than 1 percent per month; the caseload 

fell by 12.5 percent that year. 

Researchers and policymakers have thoroughly examined the factors that influence FSP 

caseload changes. Economic conditions have a significant effect on caseload size. The 

economic recession of the early 1990s drove much of the increase in FSP participation during 

that period, while the strong economic growth of the late 1990s is credited with causing much of 

the decline. Though having a smaller overall impact on caseload size, changes in public policy 

also are responsible for caseload trends. Policies to increase participation rates in the early 1990s 

led to larger caseloads, while welfare reform in the late 1990s led to smaller caseloads. 

Despite a general agreement about which factors affect caseload size, little is known on how 

these factors influence participation decisions. The confusion arises because monthly changes in 

caseload size are a function of the decisions of nonparticipants to enter the program, as well as 

the decisions of participants to exit (or not exit) the program. If more people enter the program 

than exit from it, the caseload size will increase; if more people exit from the program than enter 

it, the caseload size will decrease. Different factors can influence entry and exit decisions in 

different ways, but researchers and policymakers can observe only the net effect. 
FIGURE 1

FSP PARTICIPATION, 1990 - 2002

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

1990199119921993199419951996199719981999200020012002

Persons (000s)

February, 2001 (16,500)

April 1994 (29,000)

FIGURE 2

MONTHLY CHANGE IN FSP PARTICIPANTS, 1990 - 2002

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

1990199119921993199419951996199719981999200020012002

SOURCE: FSPQC data for years shown (11 month moving average). Caseload Growth (Percent Change from Previous Month) Caseload Decline (Percent Change from Previous Month)

2
3

 This study examines changes in entry and exit rates over time, exploring the extent to which 

the caseload increases of the early 1990s and the declines later in the decade were caused by 

changes in entry rates versus changes in exit rates. We also examine trends in the length of time 

FSP participants received food stamps, and explore how these spell lengths varied among 

different subgroups of the population. 

A. STUDY OBJECTIVES AND RESEARCH QUESTIONS 

Research on the FSP often discusses the number of its participants in static terms. For 

instance, the most recent report on FSP participation from the U.S. Department of Agriculture 

(USDA) explains that, “in Fiscal Year 2002, [the FSP] served an average of 19 million people 

per month,” and that “over half (51.0 percent) of all food stamp participants were children, the 

majority of whom lived in single parent households” (Rosso and Faux, 2003). Discussing the 

FSP in static terms is the best way to obtain a “snapshot” understanding of the size and 

characteristics of program participants. To understand caseload trends, however, one must 

consider the program in dynamic terms as well. 

While the FSP served an average of 19 million people per month in 2003, the 19.1 million 

individuals participating in January 2002 were not entirely the same as the 18.7 million 

individuals participating in February 2002 (Table 1). Some of the participants in January exited 

the program before February, while other individuals who did not participate in January entered 

in February. The net effect of this entry and exit was a decline of 411,000 individuals. This 

suggests that at least 400,000 individuals left the program before February 2002, and it is likely 

that far more than 400,000 left and were replaced by new entrants. 
4

TABLE 1 

MONTHLY CHANGE IN FSP PARTICIPANTS, 2002 

Month (2002) 

Number of 

Participants (000s) 

Monthly Net Change 

(000s) 

Change from January 

(000s) 

January 19,094 

February 18,683 -411 -411 

March 18,938 +255 -156 

April 19,443 +505 +349 

May 19,302 -141 +208 

June 19,556 +254 +462 

July 19,426 -130 +332 

 The cumulative effect of monthly exits and new entrants into the FSP explains caseload 

trends. Between January and July 2002, more individuals entered the program than exited, 

leading to an overall net increase. 

Examining the changes in rates of program entry and exit can help to shed light on why the 

caseload is increasing or decreasing at any point in time. For this study, we measure entry 

patterns using the replacement rate (defined as the number of new entrants in a given month, 

expressed as a percent of the previous month’s total caseload), and we measure exit patterns 

using the exit rate (the number of individuals participating in the previous month but not in the 

current month, expressed as a percent of the previous month’s caseload). A caseload increase 

could be caused by an increase in the replacement rate, or by a decrease in the rate of exit. In the 

special case of a “steady state” in which the caseload size is the same from month to month, the 

number of individuals exiting the program would be replaced by an exact number of new 

entrants each month. If the caseload were to decline in one month, it would indicate that the 

number of exiters was greater than the number of new entrants. This could be because the exit 

rate increased, or because the replacement rate decreased. 
5

A separate measure of food stamp dynamics closely related to entry/replacement rates and 

exit rates is participation spell length. Some individuals who enter the FSP use the program as a 

short-term safety net, exiting in a matter of months. Other individuals stay in the program 

longer, receiving benefits for years. If individuals tend to stay in the program longer, the 

caseload will rise, all else remaining equal (in other words, the exit rate will decrease). 

Likewise, if individuals tend to stay on the program for shorter periods of time, the caseload will 

fall, all else being equal. Examining patterns in spell lengths can be equally useful in 

understanding caseload dynamics. 

 The objective of this study is to better understand recent trends in entry and exit into the 

FSP. The five research questions addressed in this study are: 

1. How did growth rates, replacement rates, and exit rates change over the course of the 

1990s? 

2. Are the changes in the growth rates explained by changes in the replacement rate, 

changes in the exit rate, or both? 

3. How long did individual FSP participation spells tend to last? 

4. Have FSP spell lengths changed over time? 

5. Did replacement rates, exit rates, and spell lengths vary for FSP subpopulations, 

including the elderly, able-bodied adults, single mothers, and the working poor? 

B. SOURCES OF DATA 

 We use two sources of data in this analysis: the Food Stamp Program Quality Control 

(FSPPQC) database and the Survey of Income and Program Participation (SIPP). The FSPQC 

data are useful because they contain a large sample of FSP participants. However, the FSPQC is 

not a longitudinal database, and unlike the SIPP, program exits cannot be directly observed. 

Table 2 compares the advantages and disadvantages of using the separate data sources for this 

analysis. 
6

 

 The separate disadvantages of the two data sets can lead to questions about the accuracy of 

the results. For this reason, we compare estimates between the two data sets. When both data 

sets lead us to a similar conclusion about participation patterns, we have increased confidence in 

the findings. When estimates differ, however, it is not always clear which estimates are more 

reliable. The remainder of this section describes the FSPQC and SIPP data sets. 

1. FSPQC 

The FSPQC is an administrative database compiled annually from an ongoing review of 

active FSP cases. The FSPQC is based on probability samples constructed within each of the 50 

states and the District of Columbia.2

 Because the purpose of the FSPQC is to determine whether 

each sampled household is eligible and is receiving the correct benefit amount, the database 

contains extensive information on household eligibility characteristics, including income 

sources, demographic characteristics and, most important for this analysis, the month that the 

household entered the FSP. 

Each state’s independent monthly sample of food stamp cases generally is proportionate to 

the size of the monthly participating caseload. Using weights designed to match the 

administrative participation totals, national estimates of the FSP population can be constructed 

each month. Our analysis uses FSPQC files from fiscal years 1990 through 2002. Monthly 

sample sizes range from 3,600 to 5,600 FSP households.3

2

 Data on Guam and the Virgin Islands also are collected but were not examined in this 

study. 

3

 Annual sample sizes range from 47,000 households in FY 2001 to 65,000 households in 

FY 1990. 
7

TABLE 2 

ADVANTAGES AND DISADVANTAGES OF FSPQC AND SIPP DATA 

Data Source Advantages Disadvantages 

FSPQC Large sample of FSP 

participants allows for 

analysis of monthly patterns 

Consistent collection of data 

allows for analysis over many 

years 

Caseload exits cannot be observed 

directly, and estimates are influenced by 

sampling variability in caseload entry 

estimates 

New entrant households are 

underrepresented in sample

SIPP Household entry into and exit 

from FSP self-reported 

Inconsistencies between 1996 panel and 

previous panels 

Underreporting of FSP receipt may bias 

results 

While the FSPQC data reflect a monthly cross section of the Food Stamp caseload, the data 

also can be used to deduce longitudinal patterns. Repeat cross-section analysis can be used to 

examine caseload changes from month to month and derive the number of individuals that exit 

based on the number of new entrants and on the total caseload change (Wilde, 2001). In a given 

month (Month A) the number of new entrants is simply the number of participants in their first 

month of FSP receipt (the Month A new entrant cohort). The change between the estimated 

number of people in their first month of receipt in Month A and the estimated number in their 

second month of receipt in the subsequent month (Month B) is the number of individuals of the 

Month A new entrant cohort that exit after one month of participation. The change in the 

estimated number in their second month (Month B) compared to their third month (Month C) is 

the number that exit after two months. Repeating this for all possible spell durations and for all 

entry cohorts yields estimates of caseload dynamics. 
8

 

Estimates of replacement and exit rates in FSPQC are subject to sampling variability 

because they are based on the distribution of characteristics in each month’s sample. In the 

FSPQC data, the total number of participants each month is not subject to sampling variability; it 

is equal to the number of participants known through the administrative totals. However, each 

month, the proportion of participants in their first, second, third, and subsequent months of 

participation is subject to sampling variability. Thus, if there are 4,000 total fewer participating 

households between Month A and Month B, and we estimate that there are 2,000 new entrant 

households, then we would estimate that there are 6,000 exiting households. The 4,000 net 

change in participation is not subject to sampling variability, but the estimate of 2,000 new 

entrants, and hence the estimate of 6,000 exiters, are subject to sampling variability. 

 While the FSPQC data are intended to be representative of the U.S. FSP population, they do 

not appear to be representative with respect to entry rates. Each month, there appear to be too 

few individuals in their first and second months of FSP receipt, based on the number of 

participants in subsequent months. For example, the number of individuals in their second 

month of FSP participation in March 1996 was 85.5 percent greater than the number in their first 

month in February 1996 (Table 3). If the FSPQC sample were representative, then the number in 

their second month of receipt in March would likely be less than or approximately equal to the 

number in their first month in February.4

 In many months, there is a similar undercount of 

4

 Since the February and March estimates of the number in their first and second month of 

participation were based on independently drawn random FSPQC samples, sampling variability 

could lead to a larger number in the second month of participation in March than in the first 

month of participation in February. However, given the size of the FSPQC samples, it is 

extremely unlikely that sampling variability alone would lead to the 85.5 percent increase that 

was observed over this period. 
9

TABLE 3 

EXAMPLE OF FSPQC UNDERSAMPLE OF INDIVIDUALS IN FIRST AND 

SECOND MONTH OF RECEIPT: FEBRUARY 1996 

Individuals 

First 

Month, 

February 

1996 

Second 

Month, 

March 

1996 

Third 

Month, 

April 1996 

Fourth 

Month, 

May 1996 

Fifth 

Month, 

June 1996 

Sixth 

Month, 

July 1996 

Original 808,392 1,499,438 2,030,031 1,480,563 1,088,369 928,740 

% Change 85.5 35.4 -27.1 -26.5 -14.7 

Adjusted 2,098,190 1,928,237 1,777,835 1,296,628 953,158 813,360 

% Change -8.1 -7.8 -27.1 -26.5 -14.7 

 Source: 1996 FSPQC data. 

people in their second month of participation. For example, the number of individuals in their 

third month of participation April 1996 was 35.4 percent greater than the number in their second 

month in March. 

The reason for the undercount of individuals in their first and second months of FSP 

participation is unclear. The undercount occurs in almost all months and, while the magnitude of 

the undercount varies, it occurs throughout the study’s observation period. Our theory is that 

there are some types of FSP cases that take longer to process. Since the FSPQC sample is pulled 

from case records, unprocessed records would not be pulled for this sample. In other words, it 

may be more accurate to think of the FSPQC sample as representative of all FSPQC cases whose 

records are completely entered into a state’s case records system at the time the sample is 

selected, as opposed to being representative of all FSPQC cases receiving benefits. 

For the purposes of estimating the length of participation spells, we used a weighting 

adjustment to correct for the undercount of individuals in their first and second months of FSP 
10

 

participation. We assumed that in each month, the cases sampled in their third month of FSP 

participation are representative of all FSP cases in their third month. Using exit rates computed 

in the SIPP for all individuals entering the FSP between 1990 and 1999, we assumed that 8.1 

percent of individuals exited between their first and second months of participation and that 7.8 

percent exited between their second and third months of participation.5

 Thus, we calculated the 

number of individuals in their second month of participation as: 

 p

2

t+1 = p3t+2/(1-.078) (1) 

Where, 

p

2

t+1 = the number of individuals in their second month of participation in month t+1 

p3

t+2 = the number of individuals in their third month of participation in month t+2

 We then calculated the number of individuals in their first month of participation as: 

 p

1

t = p

2

t+1/(1-.081) (2) 

Where, 

p

1

t = the number of individuals in their first month of participation in month t 

We rescaled the weights for all FSP participants so that the totals still summed to the same 

population targets (the total number of households receiving FSP benefits each month). Rescale 

factors were computed separately for each cohort of FSP entrants (where one cohort includes the 

individuals that begin their participation spell in month t, their second month in month t+1, their 

third month in month t+2, etc.).

 Given this methodology, which assumes a constant exit rate over time for cases in their the 

first and second month of participation, fluctuations in FSPQC-based replacement and exit rates 

actually measure fluctuations in the number of cases in at least their third month of FSP 

5

 See Table 16 in Chapter III. 
11

 

participation. While it is possible that the exit rates for first- and second-month participants 

would change over time, we feel that these changes would be small.6

 

2. SIPP 

The SIPP is a multipanel longitudinal survey of households conducted by the U.S. Bureau of 

the Census. The SIPP collects demographic and socioeconomic information on individuals over 

periods as long as 48 months to provide detailed monthly measures of household composition, 

labor force behavior, income, and program participation. The SIPP sample is nationally 

representative and includes an oversample of low-income households. 

 For this analysis, we used all five of the SIPP panels that started in the 1990s (the 1990, 

1991, 1992, 1993, and 1996 panels). Table 4 presents basic reference period and sample size 

information for each panel. 

Each SIPP panel consists of multiple interview waves that are four months apart. During 

each interview, respondents are queried about their income and program participation status 

during the previous four months. Respondents also are queried about their program participation 

activities prior to the start of the panel. This information can be combined to track the FSP 

participation patterns of each household over multiple years. Sample weights are used to 

construct national estimates of participation patterns. 

For the 1990 through 1993 SIPP panels, the Census Bureau used the longitudinal nature of 

the data to impute missing information for many individuals. If, for instance, an individual 

missed one wave of SIPP interviews, but participated in the previous and subsequent waves,

6

 Estimates of the levels of replacement and exit rates are sensitive to the assumed exit rates 

for first- and second-month participants. However, because the assumptions are based on the 

best available data, and because, in general, the assumptions yield a replacement rate that is 

above the exit rate during periods of FSP growth and below during periods of decline, we feel 

these are the most defensible assumptions. 
12

TABLE 4 

SIPP PANEL INFORMATION 

Reference Period 

Panel Sample Sizea No. of Waves Start End 

1990 61,900 8 January 1990 August 1992 

1991 40,800 8 January 1991 August 1993 

1992 56,300 10 January 1992 April 1995 

1993 56,800 9 January 1993 December 1995 

1996 95,400 12 January 1996 December 1999 

a

Number of original sample members (people) in Wave 1. 

missing data would be imputed based on reported data in the adjacent waves. For the 1996 

panel, the Census Bureau reduced the number of variables for which these longitudinal edits 

were constructed. We developed our own longitudinal edits for the 1996 panel. 

 Our analysis uses data from all five SIPP panels active during the 1990s. In months where 

the panels overlap, we used data from all active panels and adjusted weights according to the 

Census Bureau’s recommended adjustments (U.S. Department of Commerce, 2001). We used 

the data from the longitudinal panel files (which, for the 1990 through 1993 panels include 

longitudinal edits of key data) and monthly weights obtained from the core-wave files. Monthly 

weights are assigned to all individuals responding to the survey for a given month, and the 

weights sum to the U.S. population that month. This allows us to use more SIPP observations 

since, unlike longitudinal weights, monthly weights are assigned to people regardless of whether 

they are absent from the survey in other months. Variation in monthly estimates can be 

explained in part by variation in a household’s monthly weight over time. 

In comparing the 1996 panel with previous panels, we discovered that FSP entry and exit in 

the 1996 panel was significantly more volatile than those of earlier panels. In the 1996 panel, 
13

unadjusted replacement and exit rates were uniformly higher between one and two percentage 

points. (See Appendix A for more details.) It is unclear what caused the increase in volatility. 

For the analysis presented in this report, which relies on changes in entry and exit rates over 

time, we needed to remove the one-time shift in volatility. To do this, we adjusted the 1996 

SIPP-based rates downward by our estimate of the shift in volatility. In the end, it turns out that 

some of the estimates produced in this report were extremely sensitive to our estimate of the size 

of this shift. This sensitivity is discussed more in Chapter II. 

C. PREVIOUS RESEARCH 

Gleason et al. (1998) use data from the 1991 SIPP panel (covering 1991 and 1992) to 

calculate FSP-participation spell dynamics. They estimate that among all households that enter 

the FSP at some point in time, most exit the program relatively quickly. Over 50 percent of 

households exit in or before nine months of participation. However, this does not mean that 50 

percent of all individuals participating at a given point in time will have participation spells of 

nine months or less. In a given month, the FSP consists of not only those short-term spells 

(lasting only several months) that began within the last several months, but also it includes all 

long-term spells that started within the last several years. Gleason et al. examined all households 

participating in February 1991 and determined that 50 percent were in the middle of a 

participation spell lasting more than 96 months (8 years). 

Table 5 presents the median participation spells of all FSP participants and of participants in 

key subgroups as estimated by Gleason et al. Estimates for the entry cohort reflect the 

participation patterns of all individuals that entered the FSP during the 1991 SIPP panel. 

Estimates for the cross-sectional cohort reflect the participation patterns of all individuals 

participating in February 1991 (subgroup spell lengths were not estimated for the cross-sectional 

cohort). 
14

TABLE 5 

DURATION OF PARTICIPATION SPELLS IN THE EARLY 1990s 

Entry Cohorta 

Cross-Sectional 

Cohortb

FSP Population 

Median Spell 

Length 

(Months) 

Median Spell 

Length 

(Months) 

Total FSP 9 >96 

Individuals in households with: 

Pure elderly/disabled 12 n.a. 

Female head and children 19 n.a. 

Noncitizens 8 n.a. 

Able-bodied adults, no children 4 n.a. 

Income below poverty 13 n.a. 

Black or Hispanic household head 12 n.a. 

White or other household head 8 n.a. 

Source: Gleason et al., 1998 (based on 1991 SIPP Panel). 

a

Entry cohort includes all individuals who enter the FSP during the analysis period. 

b

Cross-sectional cohort includes all individuals participating in February 1991. 

Gleason et al. concluded that the increase in the FSP caseload between the late 1980s and 

early 1990s was driven by an increase in the average spell length (that is, a decrease in the exit 

rate) as opposed to an increase in the entry rate. The median participation spell length for new 

entrants—nine months—was longer than the estimate by Burstein (1993) for the late 1980s—six 

months. Similarly, Gleason et al. found that the fraction of food stamp entrants who ended up 

staying in the program for at least two years increased from one-fifth to one-third between the 

late 1980s and the early 1990s. The rate at which non-participants entered the FSP remained 

relatively steady during this period. 

These findings are consistent with other studies. Martini and Allin (1993) found that the 

percentage of FSP participants with spells longer than two years was greater among those who 
15

entered the program in the early 1990s than among those who entered in the late 1980s. Bartlett 

et al. (1995) estimated that the median participation spell in the early 1990s was eight months. 

 Gleason et al. examined the determinants of FSP entry and exit and concluded that economic 

circumstances and household structure were the most important factors. In particular, the 

authors found that: 

• The most significant trigger event for entry into the FSP was a decrease in household 

earnings. 

• Individuals who were working when they entered the FSP participated for shorter 

periods of time. 

• For individuals who were not working, the longer they were out of work, the longer 

they participated in the FSP. 

• FSP participants receiving cash welfare tended to participate longer than other FSP 

participants. 

• Food stamp recipients in female-headed households with children remained on the 

program longer than other recipients. 

Wilde (2001) conducted a repeat cross-section analysis of FSPQC data from 1990 to 1999 to 

examine trends in FSP replacement and exit rates. He estimated that the median spell length of 

new entrants was 7 months, and that that the proportion of the caseload in the midst of a spell 

exceeding 24 months ranged from about 37 percent in 1990 to 53 percent in 1999. In contrast 

with Gleason et al., Wilde attributed changes in the caseload trends of the 1990s to changes in 

the entry rate, as opposed to changes in the exit rate (i.e., participation spell length). 

 A key goal of this study is to update the estimates of the length of participation spells using 

both SIPP and FSPQC data. Using both sets of data, we estimate median spell lengths for both 

entry and cross-sectional cohorts, and for the entire FSP as well as key subgroups. 
16

D. OUTLINE FOR REMAINDER OF REPORT 

Chapter II of this report examines FSP replacement and exit rates. Using both FSPQC- and 

SIPP-based estimates, we explore the degree to which caseload changes in the 1990s were driven 

by changes in the replacement rate versus changes in the exit rate. Chapter III examines the 

length of time FSP participants take part in the program. Again, estimates are constructed using 

both FSPQC and SIPP data. In Chapter IV, we examine what conclusions we can draw from the 

FSPQC- and SIPP-based analysis. 
II. FSP RATES OF ENTRY AND EXIT 

To analyze trends in FSP entry and exit, we computed monthly replacement rates and exit 

rates. Replacement rates reflect the number of individuals entering the program relative to the 

previous month’s caseload. Exit rates reflect the number of individuals leaving the program as a

percentage of the previous month’s caseload. Formally, the definitions of these rates are: 

Replacement 

Rate (rt

): Number of new entrants e in month t divided by total participants p in 

month t-1 

rt= et /pt-1 (3) 

Exit Rate (nt

): Number of exiters x in month t (i.e., participants in month t-1 not 

participating in month t ) divided by total participants p in month t-1 

nt = xt /pt-1 (4) 

 

Combined, these rates reveal how the caseload changes over time. In each month t, the total 

number of participants p can be calculated as: 

pt = pt-1 - xt + et (5) 

And the growth rate can be computed as: 

gt = rt - nt (6) 

In this chapter, estimates derived from the FSPQC and SIPP data are discussed separately. 

A. RESULTS FROM FSPQC-BASED ANALYSIS 

The FSPQC data identify each household’s date of entry into the FSP. Therefore, in each 

month of FSPQC data, we can compute an estimate of new entrants—those individuals who 

17 
began receiving food stamps that month.7

 The number of new entrants in a given month, divided 

by the previous month’s total caseload size, is the replacement rate for that month. 

Computing the exit rate in FSPQC data is more difficult. Because the FSPQC data do not 

provide estimates of non-FSP participants, we cannot directly observe the number of individuals 

that exit each month. Instead, we rearrange equation (5) to compute the number of exiters as: 

xt = pt-1 + et - pt (7) 

As a result of this computation, any errors in estimating replacement rates in FSPQC will also

affect exit rates. 

For this analysis, we computed average annual growth, replacement, and exit rates for each 

year from 1990 to 2002. We examined these rates for four key periods of caseload change, each 

about 3 years in duration and reflecting different stages of the caseload growth cycle: 

1. Caseload Growth I: Between August 1990 and July 1993, the number of 

individuals participating in the program increased by more than 37 percent. 

2. Caseload Decline I: Between August 1993 and July 1996, the number of 

individuals participating in the program declined by 14 percent. 

3. Caseload Decline II: Between August 1996 and November 1999, the number of 

individuals participating in the program declined by more than 25 percent. 

4. Caseload Growth II: After December 1999, the FSP caseload began growing 

again, increasing almost 15 percent by June 2002.

Growth rates and replacement rates were highest during the first caseload growth period in 

the early 1990s (see Table 6 and Figure 3). In an average month of this period, 7.5 percent of the 

previous month’s caseload was replaced by new entrants, and 6.7 percent of the previous 

 7

 As discussed in the previous chapter, the number of new entrants is not representative, but 

we make adjustments to improve the estimate of new entrants each month. 

18 
TABLE 6 

AVERAGE MONTHLY FSPQC-BASED GROWTH, REPLACEMENT, 

AND EXIT RATES, 1990-2002 

Period 

Average 

Monthly

Growth Rate 

Average 

Monthly

Replacement 

Rate 

Average 

Monthly 

Exit Rate 

Caseload Growth I: 1990-1993 

 August 1990 – July 1991 1.4 8.3 6.9

 August 1991 – July 1992 0.5 7.3 6.8

 August 1992 – July 1993 0.8 7.0 6.2

 Overall 0.9 7.5 6.7 

Caseload Decline I: 1993-1996 

 August 1993 – July 1994 -0.3 7.1 7.4

 August 1994 – July 1995 -0.5 6.4 6.9

 August 1995 – July 1996 -0.2 7.0 7.3

 Overall -0.4 6.8 7.2 

Caseload Decline II: 1996-1999 

 August 1996 – July 1997 -1.3 6.5 7.7

 August 1997 – July 1998 -1.1 6.4 7.5

 August 1998 – October 1999 -0.6 7.0 7.6

 Overall -0.9 6.7 7.6 

Caseload Growth II: 1999-2002 

 November 1999-October 2000 0.0 6.6 6.6

 November 2000-October 2001 0.4 7.0 6.6

 November 2001-June 2002 0.9 6.8 6.0

Overall 0.3 6.8 6.4 

Overall 1990-1999 -0.2 7.0 7.2

Overall 1990-2002 0.0 7.0 7.0

Source: FSPQC data for years shown. 

 

19 
FIGURE 3 

AVERAGE MONTHLY FSPQC-BASED GROWTH, REPLACEMENT, AND EXIT RATES, 

1990-2002 

0.9

-0.4

0.3

7.5

6.8 6.7 6.8 6.7

7.2

7.6

6.4

-0.9

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

Growth Rate Replacement Rate Exit Rate

1990-1993 1993-1996 1996-1999 1999-2002

SOURCE: FSPQC data for years shown

month’s caseload exited the program. This led to an average monthly growth rate of 0.9 percent. 

The growth rates were highest in the 1991-1992 period. 

During the caseload decline between 1993 and 1996, the average monthly replacement rate 

fell to 6.8 percent, while the average monthly exit rate increased to 7.2 percent, and the caseload 

declined by an average of 0.4 percent per month. In the late 1990s, during the second period of 

caseload decline, the average monthly replacement rate was slightly lower at 6.7 percent, while 

the exit rate climbed to 7.6 percent. In this period, the caseload declined by an average of 0.9 

percent each month. 

20 
In 2000, the caseload began to climb again. During the second period of caseload growth, 

the average monthly replacement stayed about the same as in previous years—6.8 percent—but 

the average monthly exit rate declined to 6.4 percent, yielding an average monthly growth rate of

0.3 percent. 

To better understand caseload dynamics within each of the four analysis periods, we present 

the trends in replacement and exit rates in Figure 4. The trend lines are estimated through an 

ordinary least squares regression of the replacement and exit rates for each month. This reflects 

the within-period direction of the replacement and exit rates and it helps to illustrate the 

individual roles of entry and exit patterns in explaining caseload trends.

1. Caseload Growth I: During this period, the replacement rates fell sharply, 

approaching the exit rates. This contributed to the tapering of caseload growth at 

the end of the period. It should be noted that the exit rates also fell over this 

period, thus contributing to the overall caseload growth. 

2. Caseload Decline I: Replacement and exit rates were similar over this period. 

Exit rates remained relatively constant. The slight decline in replacement rates 

likely explains most of the caseload decline over this period. 

3. Caseload Decline II: During the late 1990s, exit rates were substantially higher 

than replacement rates. The exit rates were higher than at any other point in the 

1990s and remained relatively constant over the period. Replacement rates started 

at their lowest point during the 1990s, suggesting that the caseload declines were

driven both by higher rates of exit and lower rates of entry. 

4. Caseload Growth II: The most recent period of caseload growth appeared to be

driven both by increases in replacement rates and decreases in exit rates.

All of this information suggests that a combination of replacement and exit rate factors 

explained the caseload trends, with replacement rates playing a dominant role in the early 1990s 

and exit rates playing a dominant role in the late 1990s. To further understand how entry and 

21 
22 

FIGURE 4 

FSPQC-BASED TRENDS IN REPLACEMENT AND EXIT RATES, 1990-2002 

0.02.04.06.08.0

10.012.014.0

Jan-90 Jun-91 Oct-92 Mar-94 Jul-95 Dec-96 Apr-98 Aug-99 Jan-01 

Replacement and Exit Rates

Replacement RateExit Rate

Total Participants
exit patterns affect caseload changes from one period to the next, we decomposed changes in the 

average growth rates across these four periods. Given that the growth rate (gt) for a given period 

is equal to the replacement rate (rt

) minus the exit rate (nt), we can decompose the proportion of a 

change in the growth rate between periods t and t+1 that is due to a change in the replacement 

rate (r ́t+1) and the proportion due to a change in the exit rate (n ́t+1) as: 

 r ́t+1 = (rt+1 - rt) / (gt+1 - gt) * 100 (7) 

 n ́t+1 = (-nt+1 + nt) / (gt+1 - gt) * 100 (8) 

The results of this decomposition reflect the relative importance of replacement rate changes and 

exit rate changes in explaining changes in the growth rate from one period to another. For 

example, between 1990 and 1993, the FSP caseload grew at an average rate of 0.88 percent per 

month (Table 7). Between 1993 and 1996, the caseload fell at an average of -0.36 percent per 

month. The difference between these two growth rates was about –1.25 percentage points. 

Average replacement rates fell by –0.70 percentage points between these two periods, accounting

for 55.7 percent of the change in growth rates. The average exit rate increased by 0.55 

percentage points, accounting for 44.3 percent of the change in growth rates. This suggests that 

a decreasing replacement rate had somewhat more influence in explaining the shift from a period

of growth to a period of slight decline than did an increasing exit rate. 

The decomposition estimates presented in Table 7 support the finding that replacement rate

and exit rate changes both were responsible for the shift from the growth in the early 1990s to the 

declines in the mid- and late 1990s. In other words, caseloads stopped growing and started 

23 
TABLE 7 

DECOMPOSITION OF CHANGES IN FSPQC-BASED CASELOAD GROWTH RATESa

Analysis Periods 

Growth I to 

Decline I 

(90-93 to 93-96) 

Decline I to 

Decline II 

(93-96 to 96-99) 

Decline II to 

Growth II 

(96-99 to 99-02) 

Growth I to 

Decline II 

(90-93 to 96-99) 

Average Growth Rates 

 First period 0.88 -0.36 -0.93 0.88 

 Second period -0.36 -0.93 0.34 -0.93

 Change -1.25 -0.57 1.27 -1.82

Average Replacement Rates 

 First period 7.54 6.84 6.67 7.54 

 Second period 6.84 6.67 6.79 6.67 

 Change -0.70 -0.17 0.12 -0.87

Average Exit Rates 

 First period 6.66 7.21 7.60 6.66

 Second period 7.21 7.60 6.45 7.60

 Change 0.55 0.39 -1.15 0.94

Decompositionb

Percent of change in growth

rate explained by change in: 

Replacement Rate 55.7 30.3 9.0 47.8

Exit Rate 44.3 69.7 91.0 52.2

a

Rates presented in this table are the same as rates in Table 6, except the rates in this table are shown to the

second decimal place.

b

Decomposition percentages are based on rates that have not been rounded; therefore, they may not match the 

percentages implied by table estimates. 

declining because individuals entered at a slower rate and because those participating in the

program exited at a faster rate. On the other hand, an increasing exit rate explains over twothirds of the shift from the slight decline in the mid-1990s to the steep decline in the late 1990s, 

and a decreasing exit rate explains almost all of the shift from the steep decline in the late 1990s 

to the growth in the early 2000s. 

24 
The change from slight decline to steep decline are particularly policy-relevant because the 

steep decline followed the sweeping welfare reform changes of the Personal Responsibility and 

Work Opportunity Reconciliation Act (PRWORA) of 1996. During this period, the exit rates 

were higher than at any other point in the decade, and the shift in exit rates from the previous

period explained 70 percent of the change in growth rates. Thus, after PRWORA, caseloads

shrank predominantly because individuals exited the program at a faster rate. 

B. RESULTS FROM SIPP-BASED ANALYSIS 

Our SIPP-based analysis of entry and exit patterns uses the longitudinal aspect of the SIPP 

data. For each month of the analysis period, we identified the total number of individuals who 

reported that they were “covered” by food stamps. In SIPP, being covered indicates that 

someone in the individual’s household is authorized to receive food stamps and that the benefits 

are intended in part to cover that individual. The number of new entrants each month is defined 

as the number of individuals newly reporting coverage that month. The number of exiters is 

defined as the number of individuals reporting that they did not receive food stamps the month 

after reporting that they did receive them.

8

 

In identifying entry and exit, we followed the procedure used by Burstein (1993) and 

Gleason et al. (1998) of “closing up” gaps in participation. In particular, we assumed that 

sample members received food stamps in a given month if they received food stamps in the 

previous and subsequent months. While it is possible to have a one-month lapse in FSP 

 8

 Estimates for October 1995 through December 1995 were based on increasingly small 

sample sizes as SIPP rotation groups expired. As a result, initial estimates of replacement and 

exit rates portrayed extremely high volatility for those months. Using a centered moving 

average, we smoothed entry and exit rates for the October 1995 through January 1996 period. 

25 
participation, we believe that most of the one-month gaps in the SIPP data are due to problems 

with data reporting or editing. 

In this analysis, left-censored and right-censored FSP participation spells were not treated as 

changes in FSP participation status. A left-censored spell occurred when an individual reported 

FSP coverage in the first month that they entered the SIPP.9

 Similarly, a right-censored spell 

occurred when an individual reported FSP coverage in their last month of participation in the

SIPP sample. Since we did not know whether these individuals received food stamps in the

subsequent month, they were not treated as FSP exiters. 

The 1996 SIPP panel reflected a more volatile FSP than did earlier panels. Replacement and 

exit rates jumped by between one and two percentage points between the end of the 1994 panel

and the start of the 1996 panel, and this difference appears sustained throughout the 1996 

panel.10 To make trends consistent over time, we adjusted all 1996 SIPP-based replacement and 

exit rates downward. The size of the adjustment was determined by estimating the following

model: 

 (9) r

t t t r t = + α β + S φ + l φ + pt

γ + e

t xt t t x = + α βt S + φ + l φ + p γ + e

 

 (10) 

9

 While SIPP does ask individuals who respond to the first wave of SIPP interviews about 

recipiency, there are no recipiency history questions for individuals who enter the SIPP sample 

after the first wave. If an individual who enters the SIPP after the first wave reports FSP 

participation in their first month, it is not possible to tell if this person is a new FSP entrant. 

Hence, these individuals are not treated as new entrants. 

10 The reasons for the increased volatility in the 1996 panel are not completely understood. 

We chose to adjust the 1996 panel downward, versus adjusting earlier panels upward, because

other issues with the 1996 SIPP sample led us to question the reliability of the data (see 

Appendix A for more details). Because our analysis is concerned with trends, which panels are 

adjusted would not affect the overall conclusions. 

26 
where, 

 rt = the replacement rate in month t

 xt

 = the exit rate in month t

 St = an array of variables indicating the season in month t

 l = the average rate (replacement or exit) in the three months preceding month t t

 pt

 = a dummy variable identifying rates estimated from the 1996 SIPP panel 

These models were estimated over all SIPP-based rates from the caseload peak in August 1993 

to the caseload troth in May 1999.11 The coefficient γ is the estimate of the size of the shift in

entry and exit rates, and is equal to 1.8 percentage points for replacement rates and 1.2

percentage points for exit rates.12 These amounts were subtracted from all 1996 panel estimates. 

Table 8 presents the average annual growth rates, replacement rates, and exit rates from 

1990 to 1999. Overall, estimates of the number of FSP participants in the SIPP are lower than in 

the FSPQC, as are estimated replacement and exit rates. The rates are grouped into three

separate analysis periods. While the dates used to define these periods were the same as the first 

three periods examined with FSPQC data, the magnitude of the changes observed across these 

periods differed slightly from that in the FSPQC. 

1. Caseload Growth I: Between August 1990 and July 1993, the number of 

individuals participating in the program increased by over 41 percent (compared 

with 37 percent in the FSPQC).

2. Caseload Decline I: Between August 1993 and July 1996, the number of 

individuals participating in the program declined by 8 percent (compared with 14 

percent in the FSPQC).

3. Caseload Decline II: Between August 1996 and October 1999, the number of 

individuals participating in the program declined by more than 27 percent 

(compared with 25 percent in the FSPQC).

 11 The peak and troth dates are determined based on SIPP caseload estimates. 

12 Full regression results are presented in Appendix B. 

27 
TABLE 8 

AVERAGE MONTHLY SIPP-BASED GROWTH, REPLACEMENT, 

AND EXIT RATES, 1990 THROUGH 1999 

Period 

Average 

Monthly

Growth Rate 

Average 

Monthly

Replacement 

Rate 

Average 

Monthly 

Exit Rate 

Caseload Growth I: 1990-1993 

 August 1990 – July 1991 1.8 5.6 3.8

 August 1991 – July 1992 1.3 5.2 3.9

 August 1992 – July 1993 1.1 5.0 3.9

 Overall 1.4 5.3 3.9 

Caseload Decline I: 1993-1996 

 August 1993 – July 1994 0.3 4.4 4.1

 August 1994 – July 1995 -0.1 4.1 4.2

 August 1995 – July 1996 -0.2 4.2 4.4

 Overall 0.0 4.2 4.2 

Caseload Decline II: 1996-1999 

 August 1996 – July 1997 -1.7 3.7 5.4

 August 1997 – July 1998 -1.1 3.9 5.0

 August 1998 – October 1999 -1.0 3.9 4.9

 Overall -1.3 3.8 5.1 

Overall 1990-1999 0.0 4.4 4.4

Source: SIPP data for years shown. 

Note: Estimates are adjusted to account for increased volatility of 1996 SIPP panel estimates. See 

Appendix B for rates based on unadjusted data. 

As with replacement and exit rates computed in the FSPQC data, the replacement rates were

highest and exit rates lowest during the period of caseload growth in the early 1990s. The 

average monthly replacement rate during the caseload growth period was 5.3 percent, while the 

average monthly exit rate was 3.9 percent, yielding an average 1.4 percent increase in the 

caseload each month. Also similar to FSPQC, the replacement rates were lowest and exit rates 

highest during the period of steep caseload decline in the late 1990s. During this period, the 

28 
average replacement rate was 3.8 percent and the average exit rate was 5.1 percent, yielding an

average 1.3 percent decline in the caseload each month. In the 1993 to 1996 period, the caseload 

grew in the first and declined in the following two, yielding an average monthly growth rate of 0 

percent. Figure 5 shows the average rates over each of the three periods. 

Figure 6 presents the trends in FSP replacement and exit rates over the three analysis

periods. Again, the trend lines are estimated through an ordinary least squares regression. As 

with the FSPQC, these results suggest that both the replacement and exit rates play a role in

driving caseload trends, with the replacement rate changes affecting the caseload growth of the 

early 1990s and exit rate changes affecting the decline in the late 1990s. 

1. Caseload Growth I: As in the FSPQC data, SIPP-based replacement rates were 

highest at the start of the 1990s, contributing to the strong caseload growth 

observed during this period. Replacement rates fell over the period of caseload 

growth. Exit rates in the SIPP data increased slightly over the period of caseload 

growth. This suggests that the rate at which individuals entered the program 

played a primary role in explaining caseload growth in the later years of the 

caseload growth period. 

2. Caseload Decline I: Replacement and exit rates were similar over this period, 

with replacement rates falling slightly and exit rates increasing slightly. The

caseload decline likely is explained by both factors. 

3. Caseload Decline II: In the caseload decline of the late 1990s, the exit rate 

jumped substantially higher than in earlier periods while the replacement rate 

continued on a relatively flat trend. The sharp increase in exit rates likely 

explains much of the caseload decline over this period, but the low and decreasing 

replacement rate also contributed. 

We estimated the relative importance of replacement rate and exit rate changes in explaining

changes in growth rates across these three periods (Table 9). As with FSPQC data, the SIPP data

indicate that the shift from caseload growth in the early 1990s to steep caseload decline in the 

late 1990s was driven by a mix of changes in the replacement and exit rates. Relative to the 

FSPQC-based estimates, SIPP-based estimates indicate that changes in the replacement rate were 

29 
FIGURE 5 

AVERAGE MONTHLY SIPP-BASED GROWTH, REPLACEMENT, 

AND EXIT RATES, 1990-1999 

1.4

0.0

5.3

4.2

3.9 3.8

4.2

5.1

-1.3

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

Growth Rate Replacement Rate Exit Rate

1990-1993 1993-1996 1996-1999

30 
3 

FIGURE 6 

SIPP-BASED TRENDS IN REPLACEMENT AND EXIT RATES, 1990-1999 

0.02.04.06.08.0

10.012.014.0

Jan-90 Jun-91 Oct-92 Feb-94 Jul-95 Nov-96 Apr-98 

Replacement and Exit Rates

Replacement RateExit Rate

Total Participants
TABLE 9 

DECOMPOSITION OF CHANGES IN SIPP-BASED CASELOAD GROWTH RATESa

Analysis Periods 

Growth I to 

Decline I 

(90-93 to 93-96) 

Decline I to Decline 

II 

(93-96 to 96-99) 

Growth I to Decline 

II 

(90-93 to 96-99) 

Average Growth Rates 

First period 1.38 0.00 1.38

Second period 0.00 -1.27 -1.27 

Change -1.38 -1.27 -2.65 

Average Replacement Rates 

First period 5.27 4.20 5.27

Second period 4.20 3.84 3.84

Change -1.07 -0.36 -1.43

Average Exit Rates 

First period 3.89 4.20 3.89 

Second period 4.20 5.11 5.11 

Change 0.31 0.91 1.22 

Decompositionb

Percent of change in growth 

rate explained by change in: 

Replacement Rate 77.2 28.2 53.8 

Exit Rate 22.8 71.8 46.2 

 

a

Rates presented in this table are the same as rates in Table 6, except the rates in this table are shown to

the second decimal place.

b

Decomposition percentages are based on rates that have not been rounded; therefore, they may not

match the percentages implied by table estimates. 

more important in explaining the shift from caseload growth in the early 1990s to the slight 

caseload decline of the mid-1990s, because exit rates in the SIPP increased during the early

1990s. 

The SIPP results are sensitive to the assumption used to correct for the change in FSP entry

and exit volatility between the early SIPP panels and the 1996 SIPP panel. Small changes in the 

32 
adjustment would lead to large changes in the relative importance of replacement and exit rates

in explaining changes in growth rates (Table 10). The current regression-based adjustments 

subtract 1.8 percentage points from all replacement rates and 1.2 percentage points from all exit 

rates. Subtracting 2.0 and 1.4 percentage points respectively from the replacement and exit rates

leads us to conclude that the replacement rate changes explain 61.3 percent of growth rate 

changes between the early and late 1990s, compared with 53.8 percent under the basic regression 

adjustment. It is clear that some adjustment is needed given the fact that results estimated 

without an adjustment are nonsensical. However, the sensitivity of results to the size of the 

adjustment implies that the SIPP-based results should be viewed with caution. Until we can 

better understand why replacement and exit rates increased so drastically in the 1996 panel, we 

cannot accurately determine the relative roles that replacement and exit rate changes played in 

driving caseload changes over this period. 

C. ENTRY AND EXIT BY SUBGROUP 

Differences in entry and exit patterns among various subgroups can inform our

understanding of caseload dynamics. We estimated replacement and exit rates for these key 

subgroups: 

• Single mothers 

• The elderly 

• Noncitizens

• Able-bodied adults without dependents (ABAWDs) 

33 
34 

TABLE 10 

PERCENT OF GROWTH RATE CHANGE EXPLAINED BY REPLACEMENT RATES 

FOR VARIOUS ADJUSTMENTS TO 1996 SIPP REPLACEMENT AND EXIT RATES 

Adjustment to 1996 SIPP Replacement and Exit Rates 

No 

Adjustment 

Regression 

Adjustment 

+0.4 

Regression 

Adjustment 

+0.2 

Regression 

Adjustment

Regression 

Adjustment 

-0.2 

Regression 

Adjustment 

-0.4 

Adjustment 

Replacement 

Rate 0.0 -1.4 -1.6 -1.8 -2.0 -2.2 

Exit Rate 0.0 -0.8 -1.0 -1.2 -1.4 -1.8 

Percent of growth rate change explained by 

replacement rate change 

Growth I to 

Decline I 

77.2 77.2 77.2 77.2 77.2 77.2 

Decline I to 

Decline II 

-203.6 -3.3 12.5 28.2 44.0 59.8 

Growth I to 

Decline II 

-16.1 38.7 46.2 53.8 61.3 68.9 

Source: 1990 through 1996 SIPP Panels. 

 Subgroup estimates are based on SIPP data only.13 In constructing these estimates, 

subgroup status was determined in the month of entry for replacement rates and the month of exit 

 13 Given that the FSPQC data are not longitudinal, we cannot estimate meaningful entry and 

exit patterns for subgroups. In the FSPQC data, we can identify individuals’ characteristics each 

month, including the month of entry. However, because we only examine differences in the 

cross-sectional estimates from month to month, we cannot distinguish exits from the FSP while a 

member of a subgroup from changes in subgroup status while an FSP participant. Hence, the 

subgroup exit rates capture both types of changes, and the exit rates also are mitigated by any 

FSP participants whose status changes into the subgroup population. Moreover, our weighting 

adjustment used to account for the undersample of individuals in their first month of 

participation was not constructed with subgroup control totals or target proportions in mind. 

Hence, the weighting adjustment could lead to biased estimates. 
35 

 

for exit rates.14 Thus, an FSP participant who turned 60 while receiving food stamps is not 

considered an elderly new entrant since they were not elderly when they entered the program. 

Likewise, an ABAWD whose status changes to non-ABAWD but who continues to receive food 

stamps is not considered an ABAWD that exits. 

 As with the analysis of replacement and exit rates for all individuals, regression adjustments 

were needed in the 1996 SIPP panel to account for changes in volatility across panels. The 

adjustments created for each subgroup are listed in Table 11.15 

Figure 7 presents the average replacement and exit rates for subgroups in each of the three 

analysis periods. The results for each subgroup are: 

• Single Mothers. Single mothers had relatively stable average entry rates across the 

three periods. The average replacement rate was 3.6 percent in the early 1990s and 

3.5 percent in the late 1990s. The average exit rate, on the other hand, increased 

from 2.4 percent in the early 1990s to 4.6 percent in the late 1990s. This suggests 

that the decline in the number of single mothers participating in the FSP in the late 

1990s was driven by higher exit rates (shorter participation spells) among 

participants. 

• Elderly. Among the elderly, the average exit rate remained relatively constant over 

the 1990s. However, the replacement rate was cut in half, falling from about 3.1 

percent in the early 1990s to 1.5 percent in the late 1990s. As a result of fewer 

seniors entering the FSP, the elderly caseload declined in the late 1990s. 

• Noncitizens. The average replacement rate for noncitizens was similar during the 

caseload growth of the early 1990s and the caseload decline of the late 1990s. The 

average exit rate among noncitizens increased from 3.8 percent in the early 1990s to 

5.3 percent in the late 1990s. This suggests that the eligibility restrictions of welfare 

reform did little to change the rate at which noncitizens entered the program, but 

may have influenced how long they stayed in the program. 

14 The working poor subgroup is not examined in this section because of difficulties in 

distinguishing changes in employment status from caseload entry and exit. In Chapter III, we do 

examine the spell lengths of individuals that were working when the entered the FSP. 

15 As with the results for all individuals, decomposition estimates for subgroups are highly 

sensitive to these adjustments. As a result, we do not publish decomposition estimates here. 
36 

TABLE 11 

ADJUSTMENTS TO 1996-BASED REPLACEMENT AND EXIT RATES BY SUBGROUP

Replacement Rate Adjustment Exit Rate Adjustment 

Total FSP -1.8 -1.2 

Subgroup 

Single mothers -0.5 -0.2 

Elderly -1.9 -0.9 

Noncitizens -0.5 -1.1 

ABAWDs -2.4 -3.6 

• ABAWDs. As with the working poor, the ABAWD population is relatively small, so 

replacement and exit rates tend to be higher than those of other subgroups. Average 

replacement rates decreased from 13.3 percent in the early 1990s to 10.1 percent in 

the late 1990s. Average exit rates increased from 10.5 percent in the early 1990s to 

11.8 percent in the late 1990s. This suggests that declines among ABAWD 

participants were driven both by decreased entry in the program and faster exit from 

the program. 

In short, among these subgroups, only ABAWDs caseload trends appeared to be affected by 

a combination of changes in replacement rates and exit rates. Caseload changes for single 

mothers and noncitizens appeared to be driven by the changes in the exit rate, while caseload 

changes for the elderly appeared to be driven by changes in the replacement rate. 

In addition to examining replacement and exit rates for subgroups, we used SIPP data to 

examine some of the characteristics of individuals after exiting the FSP. In this analysis, we 

focused on whether there were changes in the characteristics and experiences of food stamp 

leavers between the early 1990s—during the period of caseload growth and before PRWORA 

was passed—and the late 1990s—during the period of caseload decline and after PRWORA was 

passed. The proportion of individuals exiting the FSP that had earnings did not change 

substantially over the 1990s (Table 12). Overall, fewer than one-third of people who exited the 
FIGURE 7 

SIPP-BASED AVERAGE GROWTH, REPLACEMENT, AND EXIT 

RATES BY SUBGROUP, 1990-1999 

1.38

0.00

5.27

4.20 3.89 3.84 4.20

5.11

-1.27

-6.00

-4.00

-2.00

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

Total FSP

1.2

0.4

3.6 3.1 3.5

2.4 2.7

4.6

-1.1

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Single Mothers

0.5 0.2

3.1 2.9

1.5

2.5 2.6 2.7

-1.2

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Elderly

1.1

-0.4

4.9

4.0

4.7

3.8 4.4

5.3

-0.5

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

Noncitizens

2.9

0.0

11.6

10.1 10.5

11.6

-1.7

13.3 11.8

-6.0

-4.0

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

ABAWDs

1990-1993 1993-1996 1996-1999 1990-1993 1993-1996 1996-1999

Growth Rate Replacement Rate Exit Rate

37 
38 

TABLE 12 

OUTCOMES FOR FSP-EXITERS, 1990-1999 

Percent of Individuals 

Exiting with Earnings 

Percent of Individuals Exiting 

Out of Poverty 

Caseload Growth I 

August 1990 – July 1993 29.2 61.5 

Caseload Growth II 

August 1993 – July 1996 30.8 59.9 

Caseload Decline I 

August 1996 – October 1999 30.2 56.1 

FSP have earnings. At the same time, the proportion of leavers with incomes above the federal 

poverty line decreased from an average of 61.5 percent in the early 1990s to an average of 56.1 

percent in the late 1990s. 
39 

III. TRENDS IN FSP PARTICIPATION SPELLS 

Analysis of changes in participation spell length can be used to examine changes in the exit 

rate. All else being equal, a higher exit rate means that individuals are staying in the FSP for 

shorter periods of time. Using both FSPQC and SIPP data, we have examined the length of FSP 

participation spells for different time periods of the 1990s. 

Our analysis examined spell length distributions for two different types of FSP cohorts. An 

“entry cohort” consists of all individuals who enter the FSP over a given period of time. 

Analysis of entry cohorts can be used to answer questions such as: For all people who entered 

the FSP between 1996 and 1999, what was the typical participation spell length? By definition, 

this analysis ignores individuals who entered the FSP prior to the analysis period. 

A “cross-sectional cohort” consists of all individuals participating in the FSP in one month. 

Analysis of cross-sectional cohorts can be used to answer questions such as: For all people 

participating in March 1996, what was the typical participation spell length? 

 In general, we would expect the typical spell length to be longer when measured for the 

cross-sectional cohort, because cross-sectional cohorts capture the cumulative effect on the 

caseload of long-term spells. In a given month, the FSP consists not only of those short-term 

spells (lasting only several months) that started within the last several months but also includes 

all long-term spells that started within the last several years. Thus, even if a small proportion of 

new entrants stay on the program for a long period of time, the cumulative effect of those cases 

means that in any given month a much larger share of the caseload is in the middle of a long 

participation spell. 
40 

A. ENTRY COHORT ANALYSIS 

1. FSPQC-Based Estimates 

We used life tables to examine the length of time individuals participate in the FSP. The life 

table (Table 13) presents the hazard rate, survivor rate, and cumulative exit rate for each spell. 

The hazard rate is the probability that a spell ends in a particular month, given that it has lasted at 

least until the beginning of that month. The survivor rate is the unconditional probability that a 

spell lasts more than a given number of months. The cumulative exit rate is the unconditional 

probability that a spell ends within a given number of months 

To construct life tables using FSPQC data, we used repeated cross-sectional analysis on a 

series of entry cohorts over the analysis period. For each month t in the analysis period, we 

calculated the number of new entrants in that month. Then, in each month t+1 to t+n, we 

estimated the number of individuals whose FSPQC record indicated that they entered in month t. 

Since the monthly samples are intended to be representative, decreases in the estimated number 

of cases with an entry month of t are assumed to reflect the number of cases that exited. The life 

table for the entry cohort is the sum of the exit patterns for all of the entry months of the analysis 

period. 

We used FSPQC files for 1990 through 2002. As a result, we do not have estimates of the 

number of cases that began during that period but ended after 2002. These “right-censored” 

cases are not considered to be exits from the FSP. 

The FSPQC entry cohort estimates include the weighting adjustment to account for the 

undersample of individuals in their first two months of participation, which we describe in 
41 

 

Section B of Chapter II. Our estimates do not, however, adjust for fact that the FSPQC data 

contain an oversample of individuals in their 11th month of FSP receipt.16 

Table 13 presents the participation spell life table based on FSPQC data. In FSPQC data, 50 

percent of new FSP entrants during the 1990s exited by the end of their sixth month. Threefourths of new entrants exited by the end of their 13th month, and less than 30 percent of new 

entrants had a participation spell that lasted longer than one year. Only 11.9 percent of new 

entrants had participation spells lasting longer than two years. 

The pattern of the hazard rate across participation spells appears to reflect the influence of 

certification periods on FSP exits. Certification periods—the amount of time a household can 

receive FSP benefits before having to go through a recertification process—tend to be 3, 6, or 12 

months (depending on household characteristics and state guidelines). The hazard rate was 

highest for participation spells that are equal to or slightly longer than 3, 6, or 12 months, which 

suggests that recertification is an influential trigger event for FSP exit. 

FSPQC data indicate that the length of participation spells declined somewhat over the 

1990s (Table 14). During the period of caseload growth in the early 1990s, the median 

participation spell was seven months. This fell to six months during the period of caseload 

decline in the late 1990s. Similarly, while 75 percent of new entrants left the program by the end 

of their 13th month in the early 1990s, 75 percent exited by the end of their 12th month in the late 

1990s. 

16 The number of individuals in their 11th month of participation often is substantially higher 

than the number in their 10th month during the previous calendar month. The reason for this 

oversample is unknown. This phenomenon has changed over time. During the 1990-1993 

period, the number of individuals in their 11th month was, on average, 21.5 percent greater than 

the number in their 10th. The number of 11th month cases was only 7.1 percent higher in the 

1993-1996 period, and was 11.2 percent higher in the 1996-1999 period. 
TABLE 13 

LIFE TABLE OF FSP PARTICIPATION SPELLS ENTRY COHORT 

FSPQC-BASED ESTIMATES 1990-1999

Month of Spell

Number of Spells at

Beginning of Month 

Number Exiting During

Following Month 

Survivor Rate 

(Percentage)

Hazard Rate 

(Percentage)

Cumulative Exit 

Rate (Percentage)

1 193,637,953 15,684,674 91.9 8.1 8.1

2 177,953,279 13,880,356 84.7 7.8 15.3

3 164,072,923 19,796,540 74.5 12.1 25.5 

4 144,276,384 18,507,197 65.0 12.8 35.0

5 125,769,186 9,860,313 59.9 7.8 40.1

6 115,908,874 20,608,250 49.2 17.8 50.8 

7 95,300,624 16,659,094 40.6 17.5 59.4

8 78,641,530 8,928,103 36.0 11.4 64.0

9 69,713,427 1,982,446 35.0 2.8 65.0

10 67,730,981 -3,388,405 36.7 -5.0 63.3

11 71,119,385 9,529,086 31.8 13.4 68.2

12 61,590,300 9,673,763 26.8 15.7 73.2

13 51,916,537 10,344,317 21.5 19.9 78.5 

14 41,572,220 5,734,125 18.5 13.8 81.5

15 35,838,095 1,224,719 17.9 3.4 82.1

16 34,613,376 2,977,526 16.3 8.6 83.7

17 31,635,849 1,569,177 15.5 5.0 84.5

18 30,066,673 730,918 15.1 2.4 84.9

19 29,335,755 1,696,138 14.3 5.8 85.7

20 27,639,617 -4,508,520 16.6 -16.3 83.4

21 32,148,137 4,624,057 14.2 14.4 85.8

22 27,524,080 -2,098,695 15.3 -7.6 84.7

23 29,622,775 1,917,945 14.3 6.5 85.7

24 27,704,829 4,670,093 11.9 16.9 88.1

25 23,034,736 2,404,273 10.7 10.4 89.3

26 20,630,463 1,256,434 10.0 6.1 90.0

27 19,374,030 697,622 9.6 3.6 90.4

28 18,676,408 -561,037 9.9 -3.0 90.1

29 19,237,444 2,170,316 8.8 11.3 91.2

30 17,067,129 681,022 8.5 4.0 91.5

Shaded areas reflect 25th, 50th, and 75th percentiles. 

42 
43 

TABLE 14 

COMPARISON OF PARTICIPATION SPELLS ENTRY COHORT 

FSPQC-BASED ESTIMATES, 1990-1999 

Period 

25 Percent of 

Individuals Exit in 

or Before Month 

50 Percent of 

Individuals Exit in 

or Before Month 

(Median) 

75 Percent of 

Individuals Exit 

in or Before 

Month 

Total Period 

August 1990 – October 1999 

3 6 13 

Caseload Growth I 

August 1990 – July 1993 

4 7 13 

Caseload Decline I 

August 1993 – July 1996 

3 6 13 

Caseload Decline II 

August 1996 – October 1999 

3 6 12 

These FSPQC-based estimates are consistent with the FSPQC-based decomposition 

estimates presented in Chapter II. According to FSPQC data, more than half of the caseload 

growth and two-thirds of the caseload decline in the 1990s could be explained by changes in the 

exit rate. The slight decline in the 25 percentile and median spell lengths could have affected 

caseload trends substantially. We simulated an FSP caseload by assuming a constant number of 

new entrants each month (1.5 million) and by using the FSPQC-based exit rates for the caseload 

growth and decline periods. The resulting caseload was 9.5 percent lower after seven months 

using exit rates from the period of decline than when using the exit rates from the period of 

caseload growth (Table 15). Differences in cumulative exit rates would be even larger after 

seven months, all else being equal. 
44 

TABLE 15 

SIMULATED CASELOAD USING FSPQC-BASED EXIT RATES 

1990-1993 VERSUS 1996-1999 

Caseload Growth 

(1990-1993) 

Caseload Decline 

(1996-1999) 

Monthly New Entrant Assumption 1.5 Million 1.5 Million 

Cumulative Exit Rate 

Month 1 7.6 7.6 

Month 2 10.8 10.8 

Month 3 16.5 26.2 

Month 4 25.7 37.8 

Month 5 29.1 46.2 

Month 6 42.0 54.3 

Month 7 53.7 60.9 

Caseload Size, End of Month 7 9,218,995 8,341,768 

Difference -- 877,226 

Percent Difference -- 9.5 

2. SIPP-Based Estimates 

SIPP data are well-suited for examining participation dynamics of new entrants because the 

longitudinal nature of the survey allows observation of households as they enter FSP as well as 

how long each FSP household participates in the program. 

We combined data from the five SIPP panels covering the 1990s to construct a life table for 

all individuals who entered the FSP during that period (Table 16). Data from spells that started 

before the analysis period (left-censored spells) were not included in the analysis. Data from 

spells that lasted as long as or longer than the SIPP panel (right-censored spells) were included in 

the life table, but when the SIPP panel ended, we did not consider these households as exiting the 

FSP. Instead, we used the information for the spell while it was active. For example, if a spell 
45 

 

was right-censored after 10 months, we used the information that the spell did not end within the 

first 10 months. To yield estimates similar in methodology to Gleason et al., we did not weight 

life table estimates.17 

During the overall period, the median spell length was eight months, meaning that of all the 

individuals who entered the FSP in the 1990s, one-half had a participation spell lasting eight or 

fewer months. Three-fourths of program entrants had a spell length that lasted 21 or fewer 

months. About one out of every five individuals who entered the FSP in the 1990s had a 

participation spell that lasted longer than two years. While the hazard rate had a large spike at 12 

months, potentially reflecting the influence of certification periods, it also had spikes at 4-month 

intervals. This may reflect the influence of “seam reporting” in the SIPP. SIPP interviews occur 

every four months, and seam reporting occurs when respondents report that they received food 

stamps in all four of the previous months when in fact they received food stamps for fewer than 

four of those months. 

Economic and policy changes during the 1990s appear to have combined to reduce the 

participation spells of longer-term participants—those receiving benefits for a year or more. 

During all three of the caseload periods, 25 percent of entrants left the program by the end of 

their fourth month and 50 percent left by the end of their eighth month (Table 17). However, 

those who did not exit by their eighth month were more likely to have had longer participation 

spells in the early 1990s than in the late 1990s. During the caseload growth of the early 1990s, 

half of those individuals who did not exit before their eighth month had spells lasting longer than 

17 The appropriate weight for life table estimates would be the SIPP longitudinal panel 

weight. However, because the probability of selection in SIPP is not associated with FSP 

participation spells, little analytical value is lost by examining unweighted estimates. 
46 

TABLE 16 

LIFE TABLE OF FSP PARTICIPATION SPELLS ENTRY COHORT, 

SIPP-BASED ESTIMATES, 1990-1999 

Month of Spell 

Number of Spells 

at Beginning of 

Month 

Number Exiting 

During Following

Month 

Survivor Rate 

(Percentage) 

Hazard Rate 

(Percentage) 

Cumulative Exit 

Rate (Percentage)

1 13,603 1,103 91.9 8.1 8.1 

2 12,147 946 84.7 7.8 15.3 

3 10,870 683 79.4 6.3 20.6 

4 9,902 1,884 64.3 19.0 35.7 

5 7,224 491 59.9 6.8 40.1 

6 6,561 445 55.9 6.8 44.1 

7 5,938 287 53.2 4.8 46.8 

8 5,516 684 46.6 12.4 53.4 

9 4,376 196 44.5 4.5 55.5 

10 4,056 199 42.3 4.9 57.7 

11 3,745 178 40.3 4.8 59.7 

12 3,486 360 36.1 10.3 63.9 

13 2,859 104 34.8 3.6 65.2 

14 2,678 102 33.5 3.8 66.5 

15 2,502 80 32.4 3.2 67.6 

16 2,366 197 29.7 8.3 70.3 

17 1,951 66 28.7 3.4 71.3 

18 1,821 59 27.8 3.2 72.2 

19 1,694 49 27.0 2.9 73.0 

20 1,612 101 25.3 6.3 74.7 

21 1,329 45 24.4 3.4 75.6 

22 1,231 48 23.5 3.9 76.5 

23 1,123 35 22.7 3.1 77.3 

24 1,052 66 21.3 6.3 78.7 

25 836 23 20.7 2.8 79.3 

26 766 15 20.3 2.0 79.7 

27 690 20 19.7 2.9 80.3 

28 634 37 18.6 5.8 81.4 

29 442 9 18.2 2.0 81.8 

30 393 16 17.5 4.1 82.5 

 

Shaded areas reflect 25th, 50th, and 75th percentiles. 

 
47 

TABLE 17 

COMPARISON OF PARTICIPATION SPELLS SIPP-BASED ENTRY COHORT 

ESTIMATES, 1990 THROUGH 1999 

Period 

Individuals 

at Risk of 

Exiting 

25 Percent of 

Individuals 

Exit in or 

Before Month 

50 Percent of 

Individuals 

Exit in or 

Before Month 

(Median) 

75 Percent of 

Individuals 

Exit in or 

Before Month 

Total Period 

August 1990 – October 1999 13,603 4 8 21 

Caseload Growth I 

August 1990 – July 1993 5,587 4 8 26 

Caseload Decline I 

August 1993 – July 1996 3,683 4 8 21 

Caseload Decline II 

August 1996 – October 1999 3,792 4 8 16 

26 months. In the late 1990s, on the other hand, half of those individuals participating longer 

than eight months left the program by the end of their 16th month.18

 Our estimates of the participation spells of new entrants in the early 1990s are slightly 

shorter than those estimated by Gleason et al. (1998) for new entrants in 1991 and 1992. Their 

estimates, which were based on just the 1991 SIPP panel, showed a 25th percentile participation 

spell of 4 months, a median of 9 months, and a 75th percentile of over 30 months. Because our 

estimates for this period included 1993 but the Gleason et al. estimates did not, this suggests that 

 18 Some of the decline in long-term participation spells observed over the 1990s may be 

explained by the increased FSP volatility observed in the 1996 SIPP panel. While volatility 

adjustments were made for entry and exit rates discussed in Chapter II, no such adjustments were 

made for the analysis of spell length. We expect that adjusting for this volatility would have a 

relatively small increase in the 75th percentile participation spell month in the Caseload Decline 

II period. 
48 

 

there were proportionately more long-term participants entering the FSP during 1991 and 1992 

than there were for the entire 1990 to 1993 period combined. 

FSPQC and SIPP provide relatively consistent estimates of the median spell length of new 

entrants. According to FSPQC data, the median spell length during the 1990s was seven months; 

according to SIPP data it was eight months. However, the two data sets differ in how the spell 

length distribution changed over time. In SIPP, the lower end of the distribution—reflecting the 

length of time that people with short participation spells stayed in the program—remained 

relatively constant over time, while the spell length of the long-term participants fell 

substantially. In FSPQC data, on the other hand, the spell lengths of all participants declined 

during the 1990s—even among those with the shortest participation spells. Another key 

difference between the data sets is the estimate of the 75th percentile spell length: 21 months in 

SIPP data compared with 13 months in FSPQC data for the entire analysis period. 

3. Subgroups 

We used SIPP data to estimate entry cohort participation spell distributions for subgroups of 

FSP participants.19 Subgroups were defined based on individuals’ characteristics only for the 

month that they entered the FSP.20 These estimates show that the elderly had the longest 

participation spells during the 1990s (Table 18). Of all elderly individuals entering the FSP in 

19 Subgroups cannot be estimated using FSPQC data, since individuals can move into and 

out of subgroups from month to month. As a result, changes in monthly subgroup estimates 

could be the result of entry and exit from the FSP or simply changes in subgroup status. 

20 This differs slightly from the approach for defining subgroups in the entry and exit rate 

analysis presented in the previous chapter. In that analysis, individuals who changed subgroup 

status after entering the FSP were not counted as an exit for that subgroup. In the analysis of 

participation spells, we were interested in how long individuals participated, given their 

characteristics at entry. Thus, individuals who changed subgroup status after entering the FSP 

were included in the spell length analysis. 
49 

TABLE 18 

COMPARISON OF SPELL LENGTH DISTRIBUTIONS BASED ON SIPP ESTIMATES 

FOR ENTRY COHORT SUBGROUPS 1990-1999 

Subgroup 

Number at Risk 

of Exiting in 

Month 1 

(n) 

25 Percent of 

Individuals Exit 

In or Before 

Month 

50 Percent of 

Individuals Exit In or 

Before Month 

(Median) 

75 Percent of 

Individuals Exit 

In or Before 

Month 

All Individuals 13,603 4 8 21 

Single Mothers 4,417 4 11 27 

Working Poor 4,738 4 6 14 

Noncitizens 928 4 9 24 

ABAWDs 1,151 2 4 9 

Elderly 1,454 5 15 n.a. 

n.a.= not applicable. The 75th percentile cannot be computed because more than 25 percent of cases 

did not exit before the end of the SIPP panel. 

the 1990s, 50 percent had spells lasting 15 months or longer. Single mothers also had long 

participation spells, with 50 percent participating for 11 months or longer and 25 percent for 27 

months or longer. 

 The working poor had participation spells that were shorter than those measured for the food 

stamp population as a whole: 50 percent of individuals who entered the FSP with earnings exited 

in or before their 6th month, and 75 percent exited by their 14th month. ABAWDs, who were 

faced with time limits on food stamp receipt after PRWORA, had the shortest participation 

spells: 25 percent exited in or before their second month of participation, and 50 percent exited 

in or before their fourth month. 

Participation spells for almost all subgroups shortened over the 1990s (Table 19). In 

particular, spells decreased the most among those long-term participants in each subgroup. The 

75th percentile participation spell for single mothers decreased from 27 months in the mid-1990s 
50 

TABLE 19 

COMPARISON OF SPELL LENGTH DISTRIBUTIONS: SIPP-BASED 

ESTIMATES FOR ENTRY COHORT SUBGROUPS, BY PERIOD 

Subgroup 

Number at Risk 

of Exiting in 

Month 1 (n) 

25 Percent of 

Individuals Exit 

in or Before 

Month 

50 Percent of 

Individuals Exit 

in or Before 

Month 

(Median) 

75 Percent of 

Individuals Exit 

in or Before 

Month 

Caseload Growth I 

August 1990 – July 1993 

All individuals 5,587 4 8 26 

Single mothers 1,836 5 13 n.a. 

Working poor 1,732 3 6 15 

Elderly 574 6 20 n.a. 

Noncitizens 362 4 12 28 

ABAWDs 453 2 4 9 

Caseload Decline I 

August 1993 – July 1996 

All individuals 3,683 4 8 21 

Single mothers 1,219 4 10 27 

Working poor 1,217 3 7 14 

Elderly 395 4 15 38 

Noncitizens 256 4 8 24 

ABAWDs 288 2 4 10 

Caseload Decline II 

August 1996 – October 1999 

All individuals 3,792 4 8 16 

Single mothers 1,178 4 8 17 

Working poor 1,620 4 6 12 

Elderly 414 4 12 36 

Noncitizens 266 4 8 14 

ABAWDs 372 3 4 9 

 n.a = not applicable. The 75th percentile cannot be computed because more than 25 percent of cases did not 

exit before the end of the SIPP panel.

 
51 

to 17 months in the late 1990s. Over the same period, the 75th percentile for the working poor 

decreased from 14 months to 12 months, and the 75th percentile for noncitizens decreased from 

24 months to 14 months. 

 Interestingly, despite time limits on FSP participation, the participation spells for ABAWDs, 

which already were short in the early and mid-1990s, did not decrease substantially after the time 

limits were imposed. Indeed, the 25th percentile participation spell length increased from two 

months to three months, possibly affected by the fact that the imposed time limit was three 

months. 

B. CROSS-SECTIONAL COHORT 

 The cross-sectional cohort includes all food stamp participants in a given month. We 

estimated their full participation spell length, including the months of participation prior and 

subsequent to the analysis month. We estimated life tables for a cross-sectional cohort that 

included all participants in March 1996, a period after the caseload peak but prior to the sharp 

caseload decline of the late 1990s. Ideally, we would have examined multiple cross-sectional 

cohorts, but the data limited our ability to do so. Our estimate needed to be early in the 1996 

SIPP so that we would have data to follow participation spells after the month in which the 

cross-sectional cohort was selected. We constructed both FSPQC- and SIPP-based estimates for 

March 1996. 

1. FSPQC-Based Estimates 

To estimate cross-sectional cohort life tables in FSPQC data, we used a method similar to 

that for computing life tables for the entry cohort. We first examined the start dates of the 

sample of individuals pulled for March 1996. Then, using FSPQC samples for subsequent 

months, we examined the changes in the number of people sampled who had the same start date. 
52 

For example, we examined the number of people participating in March 1996 who had started in 

January 1996. These individuals were in their third month of participation in March 1996. We 

could then see how many of these individuals exited after their third month by examining the 

sample of people in their fourth month in April 1996 (that is, the sample with a January 1996 

start date). The life table was computed by summing these changes over all possible start 

months. We used more than 60 months of FSPQC samples subsequent to March 1996 to 

compute the life table for the cross-sectional cohort. 

As expected, estimated participation spells were longer for the cross-sectional cohort than 

for the entry cohort. According to FSPQC data, 25 percent of the individuals participating in 

March 1996 were in the middle of a participation spell lasting one year or less, and 55 percent 

were in a spell lasting three years or less (Table 20). The median participation spell was 26 

months compared with 54 months estimated in SIPP (Figure 8). Earlier SIPP-based estimates by 

Gleason et al. (1998) estimated that the median cross-sectional spell length was more than eight 

years; according to FSPQC data, only 14 percent of the March 1996 caseload was in the middle 

of a participation spell lasting eight years or longer. 

2. SIPP-Based Estimates 

To construct SIPP-based estimates of the cross-sectional cohort life table, we included those 

“left-censored” spells that were excluded from the entry cohort. Using recipiency history 

questions asked at the start of the SIPP panel, we determined the first month that each leftcensored FSP unit began participating. We then followed all FSP units throughout the life of the 
53 

TABLE 20 

SURVIVOR AND EXIT RATES FOR FSPQC-BASED 

MARCH 1996 CROSS-SECTIONAL COHORT 

Spell Length 

(Years) 

Individuals at Risk of 

Exiting 

Survivor Rate 

(Percent) 

Cumulative Exit Rate 

(Percent) 

0.5 25,848,647 84.8 15.2 

1.0 21,958,401 73.9 26.1 

1.5 19,178,218 58.5 41.5 

2.0 15,210,431 52.7 47.3 

3.0 13,738,893 44.2 55.8 

4.0 11,551,769 33.8 66.2 

5.0 8,848,435 31.4 68.6 

6.0 8,238,278 24.5 75.5 

7.0 6,463,023 18.8 81.2 

8.0 4,972,691 14.2 85.8 

9.0 3,786,810 11.6 88.4 

10.0 3,101,462 9.7 90.3 

TABLE 21 

SURVIVOR AND EXIT RATES FOR SIPP-BASED 

MARCH 1996 CROSS-SECTIONAL COHORT 

Spell Length 

(Years) 

Individuals at Risk of 

Exiting 

Survivor Rate 

(Percent) 

Cumulative Exit Rate 

(Percent) 

0.5 4,768 91.7 8.3 

1.0 4,358 83.8 16.2 

1.5 3,967 75.6 24.4 

2.0 3,573 69.5 30.5 

3.0 3,279 60.3 39.7 

4.0 2,830 52.8 47.2 

5.0 2,382 46.9 53.1 

6.0 1,892 42.2 57.8 

7.0 1,584 37.8 62.2 

8.0 1,333 34.7 65.3 

9.0 1,116 30.8 69.2 

10.0 928 28.7 71.3 
54 

FIGURE 8

SURVIVOR RATES FOR CROSS-SECTIONAL COHORTS

FEBRUARY 1991 AND MARCH 1996

0.0

25.050.075.0

100.0

0 1 2 3 4 5 6 7 8 9 10 11 12 1

Years

Survivor Rate March 1996-SIPP

(Median = 4.5 Years)

February 1991 -SIPP(Median = 8.75 Years)

March 1996-FSPQC(Median = 2.0 Years)
55 

 

panel until they exited the FSP. As with the entry cohort, all SIPP-based estimates were 

unweighted, which is similar to the methodology used by Gleason et al. (1998).21

Participation spells for the March 1996 cross-sectional cohort were substantially shorter than 

those estimated by Gleason et al. for February 1991. To ensure that our current approach was 

consistent with their earlier approach, we replicated the February 1991 estimates using the same 

methods used to produce the March 1996 cross-sectional estimates (Table 22). As with the 

Gleason et al. estimates, the median participation spell for the February 1991 cohort was more 

than eight years, about twice the median for March 1996. When we compare the quartiles of the 

distribution, as well as the plot of the distribution (Table 23 and Figure 5), it is clear that 

participation spells were shorter at all points of the distribution in 1996 than in 1991. 

The shorter participation spell estimates for the cross-sectional cohort are relatively 

consistent with trends observed for the entry cohort, where participation spells decreased 

significantly for long-term recipients. If new entrants were more likely to have short 

participation spells, then it follows that the distribution of spells in any given month would 

reflect proportionately fewer of the longest term recipients. However, because the new entrant 

cohort distribution of participation spells for short-term participants remained virtually 

unchanged during the 1990s, we would expect the 1996 and 1991 cross-sectional distributions to 

be more similar among short-term participants. 

Differences between the 1991 and 1996 SIPP panels could help to explain the differences in 

cross-sectional estimates. These differences, which are discussed more in Appendix A, could 

have led to systematic differences between the samples of FSP participants in February 1991 and 

21 As with Gleason et al., we needed to impute FSP start dates for children because SIPP 

does not ask recipiency history questions of individuals under 15. In general, we set the start 

date as equal to the date that the child’s parent entered the FSP unit, or the date that the child 

entered the household, if later. 
56

TABLE 22 

SURVIVOR AND EXIT RATES FOR SIPP-BASED FEBRUARY 1991 

CROSS-SECTIONAL COHORT 

Spell Length 

(Years) 

Individuals at Risk of 

Exiting 

Survivor Rate 

(Percent) 

Cumulative Exit Rate 

(Percent) 

0.5 2,134 94.1 5.9 

1.0 2,006 88.4 11.6 

1.5 1,879 81.5 18.5 

2.0 1,734 77.4 22.6 

3.0 1,646 71.6 28.4 

4.0 1,198 64.7 35.3 

5.0 898 61.2 38.8 

6.0 743 58.4 41.6 

7.0 610 54.2 45.8 

8.0 489 52.1 47.9 

9.0 421 49.4 50.6 

10.0 345 46.9 53.1 

TABLE 23 

COMPARISON OF SPELL LENGTH DISTRIBUTIONS 

FEBRUARY 1991 VS. MARCH 1996 SIPP-BASED ESTIMATES 

Period 

25 Percent of 

Individuals Exit in 

or Before Month 

50 Percent of 

Individuals Exit in or 

Before Month 

(Median) 

75 Percent of 

Individuals Exit in 

or Before Month 

February 1991 

31 

(2.6 years) 

105 

(8.75 years) 

201 

(16.8 years) 

March 1996 

19 

(1.6 years) 

54 

(4.5 years) 

137 

(11.4 years) 

 
57

 

March 1996. For instance, in the 1991 panel, the questions concerning pre-panel recipiency 

history were asked in Wave 2. Four months after the respondent’s first SIPP interview, they 

were asked when they started the FSP spell that was active during or before that first interview. 

These questions were asked in Wave 1 of the 1996 panel. Because 1991 SIPP sample members 

were asked to recall information over a longer period of time, this could have led to reporting 

errors regarding spell lengths. In particular, it could have caused respondents with relatively 

short participation spells to report the spells as being one or two months longer than they actually 

were.

22

Another apparent difference between the two panels is that the 1996 panel appeared to have 

included a more volatile sample of FSP participants. Our estimates of replacement and exit rates 

discussed in Chapter II were adjusted to account for this volatility; this is explored in more detail 

in Appendix A. The volatile sample could have led to more individuals reporting short 

participation spells in1996. 

22 It should be noted, however, that Gleason et al. (1998) identified some evidence that prepanel recipiency history questions in the 1991 panel led respondents to under-estimate their 

participation spells, relative to other FSP participants. 

59

IV. CONCLUSIONS 

Studying patterns of FSP entry and exit can improve our understanding of how long 

individuals participate in the FSP. This analysis also can provide a better understanding of how 

policy and economic factors affect caseload trends. In this study, we set out to measure these 

trends using two key data sources: FSPQC and SIPP. 

 Using two data sources provides increased support for our conclusions when the estimates 

from the two data sources are consistent. In comparing the results of the FSPQC- and SIPPbased estimates, we draw the following general conclusions: 

• Caseload changes during the 1990s were driven both by changes in the rate that 

people that entered the program as well as in the length of time that people 

participated. 

• Much of the caseload growth of the early 1990s was caused by increasing 

replacement rates, although lengthening participation spells also contributed to the 

growth. 

• Much of the caseload decline of the late 1990s was caused by shorter participation 

spells. In particular, participation spells among long-term participants were reduced 

substantially. 

• More than half of new entrants exited the program within between six and eight 

months, and about two-thirds of new entrants exited within one year. 

• In any given month, the caseload consisted of a large portion of long-term 

participants. In March 1996, between one-third and one-half of participants were in 

the middle of spells longer than four and a half years (a substantial decline from 

earlier estimates which indicated that in 1992 one-half of participants were in the 

middle of spells longer than eight years). 

• Single mothers tended to enter the FSP at a relatively constant rate. The length of 

time that single mothers participated in the FSP declined over the course of the 

1990s. 

• Because able-bodied adults have always experienced short FSP participation spells, 

the time limits on FSP benefits imposed through welfare reform had only a minor 

impact on the length of their participation spells. 
60

• There is no evidence that the eligibility restrictions of welfare reform led to lower 

rates of program entry among noncitizens. 

 In the remainder of this chapter, we use the FSPQC- and SIPP-based results to answer the 

research questions we raised in Chapter I. 

Question 1: How have replacement and exit rates changed over the course of the 1990s? 

FSPQC and SIPP data indicate that replacement rates fell and exit rates increased during the 

1990s. Replacement rates were at their lowest levels during the period of caseload decline in the 

late 1990s. Thus, as the caseload peaked and subsequently began to decline, there were fewer 

new entrants relative to the previous month’s caseload. At the same time, exit rates were at their 

highest during the decline. Relative to the previous month’s caseload, the number leaving the 

FSP each month grew. 

Both replacement and exit rates are higher in the FSPQC than in the SIPP analyses. In 

FSPQC data, the average replacement and exit rates for the 1990s were 7.0 and 7.2 percent, 

respectively. In SIPP, the replacement and exit rates for the same period were both 4.4 percent. 

The higher rates in FSPQC data could be explained partly by the weighting adjustment we 

performed to adjust for the undersample of individuals in their first month of participation. 

However, if this explains some of the difference between the SIPP and FSPQC rates, it is likely 

to be only a small part. The adjustment achieved a replacement rate-exit rate equilibrium that 

was consistent with observed caseload trends. A smaller adjustment would lead to even higher 

exit rates, and a larger adjustment would lead to even higher replacement rates. 

 A more plausible explanation is that SIPP underestimated volatility in the 1990 through 

1993 panels. The 1996 panel estimated replacement and exit rates to be 1.5 percentage points 

higher than in the earlier panels. We adjusted the 1996 panel estimates downward to be 

consistent with those of the earlier panels, implicitly assuming an error in the 1996 panel 
61

estimate. However, it could be that changes in the 1996 panel estimates led the replacement and 

exit rates to be more accurate, not less accurate. Specifically, computer-assisted interview 

techniques may have led to more accurate entry and exit reporting. This would imply that the 

true entry and exit rates were closer to the FSPQC-based estimate of 7.0 percent. Unfortunately, 

without a better understanding of the problems with the 1996 and earlier SIPP panel estimates, 

we do not know which estimates of replacement and exit rates were more accurate. 

Question 2: How have the changes in replacement and exit rates combined to affect 

caseload levels? 

The replacement and exit rates both play a large role in explaining caseload trends. In the 

early 1990s, caseloads grew in large part because the replacement rate was higher than usual. 

But longer participation spells also contributed to the growth. In the late 1990s, high exit rates 

helped to drive much of the caseload decline, but low replacement rates also played a role in 

explaining caseload trends. 

In decomposing the changes in growth rates across analysis periods, both datasets indicate 

that the falling replacement rate played a major role in explaining the shift from caseload growth 

in the early 1990s to caseload decline in the mid-1990s. According to FSPQC data, a rising exit 

rate during the early 1990s helped end the period of caseload growth. 

Both datasets indicate that rising exit rates explain more than two-thirds of the shift from the 

slight decline of the mid-1990s to the steep decline of the late 1990s. These changes are 

particularly policy-relevant because the steep decline followed the sweeping welfare reforms 

introduced by PRWORA. During this period, the exit rates were higher than at any other point 

in the decade, and the shift in exit rates explained 70 percent of the change in growth rates. 

Thus, after PRWORA, caseloads shrank predominantly because individuals exited the program 

at a faster rate. 
62

The overall conclusion for the 1990s is that neither the replacement nor the exit rate was 

solely responsible for explaining caseload changes. When we examine the relative roles of 

replacement and exit rate changes in the shift from the caseload growth period of 1990-1993 to 

the caseload decline period of 1996-1999, both FSPQC and SIPP data indicate that the two 

factors had equal weight in explaining the caseload changes. As a result, policymakers should 

consider the implications of policy and economic changes on both the rate at which people enter 

the program and on the length of time that they participate. 

Question 3: How long did individual FSP participation spells tend to last? 

According to FSPQC and SIPP data, more than half of all new entrants into the FSP exited 

the program by between six and eight months, and approximately two-thirds of new entrants 

exited by the end of one year in the program. Thus, about one out of every three new entrants 

participated in the program for longer than one year. The participation spells of long-term 

participants were estimated to be substantially longer in SIPP data than in the FSPQC data. 

 At any given point in time, the FSP caseload has accumulated a large number of long-term 

recipients. However, estimates of the cross-sectional distribution of spell lengths differ between 

SIPP and FSPQC data. Among all individuals participating in March 1996, SIPP data suggest 

that half were in the middle of participation spells lasting four and a half years or longer, while 

FSPQC data indicate that only one-third of the caseload was in the middle of spells of at least 

four and a half years. In FSPQC data, the median participation spell for March 1996 participants 

was just over two years. While it is unclear why the estimates from these separate sources differ, 

it appears that the estimated median participation spell of eight years for a cross-section of FSP 

participants is no longer an accurate depiction of the FSP dynamics. 
63

Question 4: Have FSP spell lengths changed over time? 

 FSPQC estimates that participation spells shortened over time. The 25th percentile 

participation spell declined from four months in the early 1990s to three months in the mid- and 

late 1990s. The median participation spell declined from seven months to six months. SIPP 

data, on the other hand, estimate that short-term participation spells were constant over time. 

According to SIPP data, during each of the three periods examined in the 1990s, the 25th

percentile and median spell lengths were four and eight months, respectively. For each data 

source, the trends in participation spell lengths are consistent with earlier estimates of the 

influence of changes in the exit rate. 

Among households with relatively long participation spells, both FSPQC and SIPP data 

estimate that spells became shorter over the 1990s, but the estimates differ on the magnitude of 

the decrease. According to FSPQC data, the 75th percentile spell length among program entrants 

fell from 13 months in the early 1990s to 12 months in the late 1990s. According to SIPP data, 

the 75th percentile fell from 26 months to 16 months. 

Question 5: Did replacement rates, exit rates, and spell lengths vary for FSP 

subpopulations? 

Participation patterns have varied substantially by subgroup. For this analysis, subgroup 

estimates were based on SIPP data only. 

Participation trends among single mothers are explained predominantly by the exit rate. The 

replacement rate among single mothers stayed relatively constant during the 1990s. On the other 

hand, the exit rate was low during the growth of the early 1990s and was high during the declines 

of the late 1990s. Thus, compared with the rest of the FSP population, single mothers tended to 

enter the program at a more stable rate, but the length of time they participated varies more. 
64

According to SIPP data, the exit rate explained 57.6 percent of single mother caseload trends in 

the early 1990s and 63.6 percent in the late 1990s. 

Compared with other subgroups, single mothers had relatively long participation spells. The 

median spell for the entire period was 11 months, which reflects a decline from 13 months in the 

early 1990s to 8 months in the late 1990s. 

Somewhat surprisingly, the replacement rate for noncitizens did not decline after the 

eligibility restrictions of PRWORA. The replacement rate among noncitizens in the 1996 to 

1999 period (4.7 percent) was at almost the same level as in the 1990 to 1993 period (4.9 

percent). The length of participation among noncitizens did change, however. The exit rate 

increased from 3.8 percent in the early 1990s to 5.3 percent in the late 1990s, and the median 

participation spell fell from 12 months to 8 months among this population. 

ABAWDs are another group with eligibility restrictions. In 1996, welfare reform subjected 

ABAWDs to time-limited food stamp participation: unless they were meeting work 

requirements, ABAWDs could receive no more than three months of FSP benefits. The 

replacement rate for ABAWDs fell from 13.3 percent in the early 1990s to 10.1 percent in the 

late 1990s, suggesting that ABAWDs were deterred from entering the FSP. The exit rate for this 

population increased from 10.5 percent in the early 1990s to 11.8 percent in the late 1990s. 

ABAWDs had the shortest participation spells of all subgroups examined, with half of all 

ABAWDs exiting by the end of their fourth month and three-fourths exiting by the end of their 

ninth month. Despite time limits imposed through PRWORA, the short ABAWD participation 

spells remained relatively constant during the 1990s. 

Caseload trends for the elderly are driven more by entry patterns than exit patterns—the exit 

rate among the elderly remained between 2.5 and 2.7 percent over the 1990s. Compared with 

other groups, the elderly had the longest participation spells. Among all new entrant elderly 
65

individuals during the 1990s, half had spells of 15 months or longer. Spells were longest during 

the early 1990s, when half of the elderly had spells of 20 months or longer. Participation spells 

for the elderly experienced the sharpest decline among all of the subgroups, with the median 

falling to 12 months in the late 1990s. 

For the working poor (food stamp participants with earnings), exit rates typically were high 

because employment is a trigger for FSP exit. Among individuals entering the FSP with 

earnings, the median participation spell remained relatively constant—at about six months— 

during the 1990s. 

67

REFERENCES 

Bartlett, Susan, Nancy R. Burstein, and Elise C. Pan. “Evaluation of Expedited Service in the 

Food Stamp Program.” Report submitted to the U.S. Department of Agriculture, Food and 

Consumer Service. Cambridge, MA: Abt Associates, Inc., June 1995. 

Burstein, Nancy R. “Dynamics of the Food Stamp Program as Reported in the Survey of Income 

and Program Participation.” Report submitted to the U.S. Department of Agriculture, Food 

and Nutrition Service. Cambridge, MA: Abt Associates, Inc., 1993. 

Dynarski, Mark, Anu Rangarajan, and Paul Decker. “Forecasting Food Stamp Program 

Participation and Benefits.” Report submitted to the U.S. Department of Agriculture, Food 

and Nutrition Service. Princeton, NJ: Mathematica Policy Research, Inc., 1991. 

Gleason, Philip, Peter Schochet, and Robert Moffitt, “The Dynamics of Food Stamp Program 

Participation in the Early 1990s.” Report submitted to the U.S. Department of Agriculture, 

Food and Nutrition Service. Princeton, NJ: Mathematica Policy Research, Inc., April 1998. 

Gleason, Philip, Carole Trippe, Scott Cody, and Jacqueline Anderson, “The Effects of Welfare 

Reform on the Characteristics of the Food Stamp Population.” Report submitted to the U.S. 

Department of Agriculture, Economic Research Service. Washington, DC: Mathematica 

Policy Research, Inc., March 2000. 

Kornfield, Robert, “Explaining Recent Trends in Food Stamp Program Caseloads.” Report 

submitted to the U.S. Department of Agriculture, Economic Research Service. Cambridge, 

MA: Abt Associates, Inc., March 2002. 

Martini, Alberto, and Susan Allin. “Did the Characteristics of Food Stamp Program Entrants 

Change During the 1990–1991 Recession?” Report submitted to the U.S. Department of 

Agriculture, Food and Nutrition Service. Washington, DC: Mathematica Policy Research, 

Inc., 1993. 

Rosso, Randy and Melissa Faux, “Characteristics of Food Stamp Households, Fiscal Year 2002,” 

report submitted to the U.S. Department of Agriculture, Food and Nutrition Service. 

Washington, DC: Mathematica Policy Research, Inc., December 2003. 

U.S. Department of Commerce, Economics and Statistics Administration, U.S. Census Bureau, 

Survey of Income and Program Participation Users’ Guide (Supplement to the Technical 

Documentation. Third Edition. Washington, DC, 2001. 

Wilde, Parke, “Food Stamp Program Entry and Exit in the 1990s.” Washington, DC: U.S. 

Department of Agriculture. Paper Presented to Association of Public Policy Analysis and 

Management Fall Research Conference, November 2001. 

69

APPENDIX A

INCONSISTENCIES IN SIPP DATA

The Census Bureau made significant changes to the SIPP in the 1996 panel to improve the 

accuracy of SIPP-based estimates. Key changes included:

• Using a single 4-year panel instead of overlapping 32 month panels

• Increasing sample sizes

• Oversampling households from areas with high poverty populations

• Introducing computer-assisted interviewing 

• Changing questions concerning program participation

In comparing 1996 SIPP data with earlier estimates, we identified several key

inconsistencies that could affect SIPP-based estimates of FSP participation. The source of these 

inconsistencies is not clear. They may have resulted from changes in sampling methods, 

sampling targets, interview questions, or data processing. Indeed, it is unclear whether these 

changes actually improved or decreased accuracy.

In this appendix, we present our analysis of SIPP discrepancies to make other users aware of 

the differences, not necessarily to provide evidence about the problems’ causes. We summarize 

three key inconsistencies found in the SIPP: (1) changes in the proportion of adults among FSP 

participants, (2) changes in FSP participation volatility, and (3) changes in the number of new 

entrant FSP households with earnings. 

The differences across panels suggest that the 1996 SIPP sample of FSP participants differed 

systematically from the other samples, but it is unclear which sample was more accurate. There 

are some problems that lead us to suspect the accuracy of the 1996 panel (discussed in Section A, 
70

below). In general, users of the data should exercise caution when comparing FSP

characteristics across panels. 

A. CHANGES IN THE PROPORTION OF FSP ADULT PARTICIPANTS

Weighted estimates of the proportion of FSP adults shifted in the 1996 panel. In the 1990 

through 1993 panels, the proportion of the FSP population that was age 18 or older generally was 

between 46 and 48 percent, consistent with FSPQC-based estimates. However, in the 1996 

panel, the proportion that was of adult age increased to between 53 and 55 percent (Figure 

A.1).23

This shift in proportion was driven both by an increase in the number of adult FSP

participants and a decrease in the number of child participants (Figure A.2). Between the end of 

the 1993 panel and the start of the 1996 panel, the number of adults increased by between 

500,000 and 1 million per month, while the number of children decreased by about 2 million per 

month (Table A.1).24 At the same time, the total number of FSP participants decreased by about 

1.5 million per month. 25

 

23 Similar trends are observed in unweighted data. The unweighted proportion of the

caseload that is adult averaged 47.3 in the last six months of the 1993 panel and 51.4 in the first 

six months of the 1996 panel.

24 A similar inconsistency is identified in data on Aid to Families with Dependent

Children/Temporary Assistance for Needy Family (AFDC/TANF) recipients. According to 

administrative data, the percentage of adult AFDC recipients was 32.6 percent, 31.9 percent, and 

31.4 percent in 1994, 1995, and 1996, respectively. In the 1996 SIPP panel, AFDC/TANF the 

level of adult participants was approximately 38 percent for most of the 1996 panel (Figure A.3). 

However, unlike estimates of the FSP adult proportion, the estimate of the AFDC/TANF adult 

proportion fell back to about 28 percent in late 1998.

25 Administrative data show that the caseload decreased by less than 300,000 during the

same period.
71

FIGURE A.1

PROPORTION OF FSP PARTICIPANTS THAT IS ADULT AGE 18 OR OLDER

40.0

45.0

50.0

55.0

60.0

Jan92

Apr92

Jul92

Oct92Jan93

Apr93

Jul93

Oct93Jan94

Apr94

Jul94

Oct94Jan95

Apr95

Jul95

Oct95Jan96

Apr96

Jul96

Oct96Jan97

Apr97

Jul97

Oct97Jan98

Apr98

Jul98

Oct98Jan99

Apr99

Jul99

Oct99

Percent

FSPQC Data

SIPP Data

1996 Panel
72

FIGURE A.2

ADULT AND CHILD FSP PARTICIPANTS IN SIPP

7,000

8,000

9,000

10,000

11,000

12,000

13,000

14,000

Jan92

Apr92

Jul92

Oct92

Jan93

Apr93

Jul93

Oct93

Jan94

Apr94

Jul94

Oct94

Jan95

Apr95

Jul95

Oct95

Jan96

Apr96

Jul96

Oct96

Jan97

Apr97

Jul97

Oct97

Jan98

Apr98

Jul98

Oct98

Jan99

Apr99

Jul99

Oct99

Participants (000s)

Children

Adults

1996 Panel
73

TABLE A.1

MONTHLY SIPP-BASED FSP ESTIMATES,

AUGUST 1995 – MAY 1996

Month

Total U.S. 

Population 

(000s)

Individuals 

with Food 

Stamps 

(000s)

Adults with 

Food Stamps 

(000s)

Children 

with Food 

Stamps 

(000s)

Percent of 

Total 

Population 

with Food 

Stamps

Percent of 

Food Stamp 

Recipients 

Adult

Percent of 

Food Stamp 

Recipients 

Children

1993 Panel

August 1995 263,122 23,358 10,757 12,601 8.9 46.1 53.9

September 1995 263,281 23,213 10,779 12,434 8.8 46.4 53.6

October 1995 263,556 23,769 11,065 12,704 9.0 46.6 53.4

November 1995 263,657 22,921 10,464 12,457 8.7 45.7 54.3

December 1995 263,915 23,704 10,871 12,832 9.0 45.9 54.1

1996 Panel

January 1996 263,864 21,053 11,065 9,988 8.0 52.6 47.4

February 1996 264,058 21,583 11,345 10,238 8.2 52.6 47.4

March 1996 264,254 22,039 11,550 10,489 8.3 52.4 47.6

April 1996 264,426 22,423 11,802 10,622 8.5 52.6 47.4

May 1996 264,617 22,070 11,605 10,465 8.3 52.6 47.4

Average 

 Aug – Dec 95 263,506 23,393 10,787 12,606 8.9 46.1 53.9

 Jan – May 96 264,244 21,834 11,473 10,360 8.3 52.6 47.4

 Difference +738 -1,559 +686 -2,245 -0.6 +6.4 -6.4

SOURCE: 1993 and 1996 SIPP panels.
74

FIGURE A.3

PERCENT OF AFDC/TANF RECIPIENTS THAT IS AGE 18 OR OLDER

20.0

30.0

40.0

50.0

60.0

Jan-96

May-96

Sep-96

Jan-97

May-97

Sep-97

Jan-98

May-98

Sep-98

Jan-99

May-99

Sep-99

Jan-00

Percent
75

The change in the adult FSP proportion appears to have been driven partially by errors in 

SIPP processing. In the 1996 panel, there was a sharp increase in the number of households with 

children in which one or more adults were covered by food stamps, but the children of those 

adults were not covered. Among households with children and with adults covered by food 

stamps, 87.7 percent (unweighted) had all children covered by food stamps before the 1996 panel 

(Table A.2). That proportion fell to 81.6 percent in the 1996 panel, with a concurrent increase in 

both the proportion of households in which some but not all children were covered and in which 

no children were covered.

The cause of this change in coverage is unknown. We speculate that in processing the 1996 

panel of SIPP data, algorithms used to assign FSP status to children under 15 were not working 

as intended. 

If this is the case, then a basic algorithm to impute FSP participation among children could 

be used to improve FSP-based estimates in the 1996 panel. We constructed a simple algorithm 

to assign FSP coverage to children. 26 In households where a parent was covered by food stamps, 

we assigned food stamp coverage to all of their children not already flagged as being covered. 

Applying this algorithm to all panels, we saw a small increase in the number of children covered 

in the pre-1996 panels and a large increase in the 1996 panel, bringing all panels to about the 

same proportions (Table A.3). Pre-1996 estimates of the proportion of FSP households with 

children in which all children were covered increase from 87.7 percent to 91.8 percent, and 

1996-based estimates increased from 81.6 percent to 91.9 percent. This algorithm likely overcorrected for the problem—as reflected in the pre-1996 data—because there may have been 

 

26 This algorithm was not used in constructing estimates of replacement and exit rates in the 

body of this report.
76

TABLE A.2

ADULT AND CHILD FSP COVERAGE IN THE SIPP

Percent of All Households with Children and with

Some or All Adults Covered by FSP 

Unweighted Weighted

All Children 

Covered 

 Some But 

Not All 

Children 

Covered 

All Children 

Not Covered 

 All Children 

Covered 

 Some But Not 

All Children 

Covered

 All Children 

Not Covered

1992 and 1993 Panels

1992 87.6 8.5 4.0 88.2 8.1 3.7

1993 88.3 7.7 4.0 89.0 7.4 3.6

1994 88.0 7.5 4.4 89.3 7.0 3.8

1995 86.9 7.3 5.9 88.6 6.7 4.7

1996 Panel

1996 82.0 9.3 8.7 83.4 8.3 8.3

1997 81.4 9.2 9.5 81.6 8.9 9.5

1998 81.4 9.7 8.9 82.3 9.1 8.7

1999 81.6 8.4 10.0 83.0 8.0 9.0

Average

 1992-1995 87.7 7.7 4.6 88.8 7.3 3.9

 1996-1999 81.6 9.2 9.3 82.5 8.6 8.9

SOURCE: 1992, 1993, and 1996 SIPP Panels.
77

TABLE A.3

ADULT AND CHILD FSP COVERAGE IN THE SIPP REVISED 

WITH IMPUTED FSP COVERAGE FOR CHILDREN

Percent of All Households with Children and with

Some or All Adults Covered by FSP 

Unweighted Weighted

All 

Children 

Covered 

 Some But 

Not All 

Children 

Covered 

All 

Children 

Not

 Covered 

 All Children 

Covered 

 Some But Not 

All Children 

Covered 

 All Children 

Not Covered

1992 and 1993 Panels

1992 91.9 5.2 3.0 92.4 4.9 2.7

1993 92.4 4.8 2.8 93.2 4.3 2.5

1994 91.8 5.0 3.2 93.0 4.4 2.6

1995 91.0 4.8 4.2 92.3 4.2 3.5

1996 Panel

1996 91.7 4.9 3.4 92.1 4.6 3.3

1997 91.8 4.5 3.7 92.3 4.2 3.5

1998 91.9 4.7 3.4 93.0 4.0 2.9

1999 92.0 3.8 4.1 93.1 3.3 3.6

Average

 1992-1995 91.8 4.9 3.3 92.7 4.5 2.8

 1996-1999 91.9 4.5 3.7 92.6 4.0 3.3

SOURCE: 1992, 1993, and 1996 SIPP Panels.
78

some circumstances in which children living with parents covered by the FSP were not

themselves covered by the FSP. 

Problems with FSP coverage flags for children in the 1996 panel do not explain the entire 

shift in the FSP adult proportion. When we examined the proportion of FSP adult participants 

after implementing our imputation algorithm, the proportion in 1996 was between 50 and 52 

percent, still several percentage points higher than in earlier SIPP panels or in FSPQC data 

(Figure A.4).

The remainder of the shift in the adult proportion likely resulted from differences in the 

sample of individuals reporting FSP participation between the pre-1996 and 1996 panels. This 

can be seen by looking at the unweighted proportion of adults in the SIPP (Table A.4). These 

differences may reflect changes in the ability of the 1996 SIPP sample to capture FSP

participants, or changes in the way that SIPP sample members report FSP participation. If the 

problem is driven by a different sample, the SIPP weights (which are not controlled to FSP 

targets) do not correct for the oversample of adult FSP participants. Users looking to correct for 

these differences could consider revising the SIPP weights to better control for FSP

characteristics.

B. CHANGES IN FSP VOLATILITY

In examining patterns of entry and exit, we discovered that the FSP sample in the 1996 panel 

was significantly more volatile than those of earlier panels. Replacement and exit rates were 

uniformly higher by about two percentage points in the 1996 panel (Figures A.5 and A.6).27

 

27 Replacement rates are defined as the number of new entrants in a given month divided by 

the previous month’s caseload; exit rates are defined as the number of exiters in a given month 

divided by the previous month’s caseload. See full report for details of how these rates are 

computed in SIPP and FSPQC.
79

It is unclear what caused the increase in volatility. However, the fact that the 1996 SIPPbased estimates of replacement and exit rates were more in line with FSPQC-based estimates of 

those rates leads us to suspect that the change constituted an improvement in the data. Indeed, it 

may be the case that changes to the 1996 panel estimates, such as the use of computer-assisted 

interviewing, could capture more program exits and entries each month. This is just speculation, 

however; the real cause of the increase in volatility is unknown.

C. CHANGES IN NEW ENTRANT HOUSEHOLDS WITH EARNINGS

There is some evidence that the sample of FSP participants in the 1996 SIPP panel differed 

systematically in terms of earnings. In pre-1996 panels, the proportion of new entrant

households that had earnings generally was between 19 and 21 percent, while in the 1996 panel, 

the proportion was between 24 and 28 percent. This may indicate a difference in sample, but it 

may also reflect a real phenomenon. In the pre-1996 panels, the proportion of new entrant 

households with earnings was trending upward over time (Figure A.7). This trend could have 

peaked in early 1996 and leveled off. However, given the other evidence of differences in the 

SIPP sample, we must also consider the possibility that the 1996 sample included more new 

entrant households with earnings.
80

FIGURE A.4

PROPORTION OF FSP PARTICIPANTS THAT IS ADULT AGE 18 OR OLDER

ORIGINAL VS. REVISED SIPP ESTIMATES

40.0

45.0

50.0

55.0

60.0

Jan92

Apr92

Jul92

Oct92

Jan93

Apr93

Jul93

Oct93

Jan94

Apr94

Jul94

Oct94

Jan95

Apr95

Jul95

Oct95

Jan96

Apr96

Jul96

Oct96

Jan97

Apr97

Jul97

Oct97

Jan98

Apr98

Jul98

Oct98

Jan99

Apr99

Jul99

Oct99

Percent

FSPQC

Original SIPP 

1996 Panel

Revised SIPP
81

TABLE A.4

PROPORTION OF ADULTS (18 OR OLDER)

Percent of FSP that is Adult

SIPP, Unadjusted SIPP, Adjusted

 SIPP 

Unweighted 

 SIPP 

Weighted 

 SIPP 

Unweighted 

 SIPP 

Weighted FSPQC 

1992 47.0 48.4 46.2 47.6 48.4

1993 46.6 47.5 45.9 46.8 48.3

1994 47.1 47.2 46.4 46.5 48.6

1995 47.1 46.4 46.4 45.6 48.4

1996 51.7 52.7 49.6 50.5 48.8

1997 52.4 53.5 50.1 51.2 48.0

1998 53.3 53.3 51.0 51.0 47.4

1999 54.9 53.9 52.6 51.8 48.6

Average

 1992-1995 46.9 47.4 46.2 46.6 48.4

 1996-1999 53.0 53.4 50.8 51.1 48.2
FIGURE A.5

 REPLACEMENT RATES

1990 THROUGH 1999

0.0

2.0

4.0

6.0

8.0

10.0

12.0

199119921993199419951996199719981999

Year

Replacement Rate

1996 SIPP Panel

SIPP

FSPQC

8

2
FIGURE A.6

 EXIT RATES

1990 THROUGH 1999

0.0

2.0

4.0

6.0

8.0

10.0

12.0

199119921993199419951996199719981999

Year

Exit Rate

1996 SIPP Panel

SIPP

FSPQC

8

3
8

4

FIGURE A.7

NEW ENTRANT FSP HOUSEHOLDS WITH EARNINGS

SIPP, 1990 THROUGH 1999

15.0

20.0

25.0

30.0

35.0

199119921993199419951996199719981999

Year

Percent

1996 SIPP Panel
85

D. CONCLUSIONS

FSP-based estimates derived from the 1996 SIPP panel were inconsistent with estimates of 

earlier panels. The 1996 SIPP panel estimates may have had an error in the way in which child 

FSP coverage was assigned. Children of FSP participants were flagged as being covered by food 

stamps at a much lower rate than in earlier panels. In addition, the sample of FSP participants 

appeared to be systematically different even after correcting for problems with coverage flags. 

The sample had disproportionate shares of adult and child participants, and participants entered 

and exited the FSP at higher rates relative to earlier panels. Furthermore, it may be the case that 

the sample included more FSP households with earnings. 

The differences in the 1996 panel suggest that users should exercise caution when estimating 

FSP characteristics, particularly when comparing changes in FSP characteristics between the pre1996 and 1996 panels. Additionally, if age is an important analysis variable, users should 

consider imputing child participation based on the parents’ participation. Users looking at a 

limited number of characteristics in addition to age may consider adjusting the SIPP weights to 

account for the sampling differences.
APPENDIX B

RESULTS FROM REGRESSIONS TO ADJUST SIPP REPLACEMENT 

AND EXIT RATES FOR INCREASED VOLITILITY IN 1996 PANEL
TABLE B.1

RESULTS FROM REGRESSIONS TO ADJUST SIPP REPLACEMENT 

AND EXIT RATES FOR INCREASED VOLITILITY IN 1996 PANEL

Total FSP Single Mothers Working Poor Elderly Noncitizens ABAWDs

Replacement 

Rate Exit Rate

Replacement 

Rate Exit Rate

Replacement 

Rate Exit Rate

Replacement 

Rate Exit Rate

Replacement 

Rate Exit Rate

Replacement 

Rate Exit Rate

Intercept 4.312 * 2.480 * 2.705 * 0.366 6.883 * * 4.460 * 2.812 * 2.839 * 3.224 * * *

( 0.948 ) ( 0.640 ) ( 0.748 ) ( 0.526 ) ( 1.807 ) ( 3.098 ) ( 1.245 ) ( 0.913 ) ( 1.425 ) ( 1.320 ) ( 3.911 ) ( 4.322 )

Time Trend -0.013 -0.002 0.008 0.015 -0.024 -0.029 -0.028 * 0.001 0.033 0.004 -0.038 0.018

( 0.009 ) ( 0.007 ) ( 0.010 ) ( 0.012 ) ( 0.017 ) ( 0.019 ) ( 0.014 ) ( 0.011 ) ( 0.023 ) ( 0.023 ) ( 0.044 ) ( 0.047 )

Season Flags

Summer 0.623 * 0.080 0.004 -0.099 0.574 0.287 0.392 0.007 0.051 0.565 -0.987 1.079

( 0.263 ) ( 0.209 ) ( 0.295 ) ( 0.276 ) ( 0.523 ) ( 0.501 ) ( 0.360 ) ( 0.335 ) ( 0.684 ) ( 0.683 ) ( 1.334 ) ( 1.471 )

Fall 0.624 * -0.119 0.395 0.107 0.633 0.405 0.478 0.158 -0.205 -0.128 -2.147 3.212 *

( 0.268 ) ( 0.201 ) ( 0.281 ) ( 0.269 ) ( 0.511 ) ( 0.501 ) ( 0.356 ) ( 0.330 ) ( 0.665 ) ( 0.725 ) ( 1.347 ) ( 1.455 )

Winter 0.257 -0.287 0.185 0.201 0.877 * 0.110 0.254 -0.024 0.804 -0.830 1.162 1.341

( 0.260 ) ( 0.193 ) ( 0.279 ) ( 0.267 ) ( 0.508 ) ( 0.509 ) ( 0.359 ) ( 0.326 ) ( 0.660 ) ( 0.658 ) ( 1.292 ) ( 1.456 )

Lagged Rate 0.048 0.452 * -0.050 0.578 * 0.099 0.163 -0.155 -0.072 -0.226 0.268 -0.464 * -0.119

( 0.179 ) ( 0.159 ) ( 0.221 ) ( 0.159 ) ( 0.207 ) ( 0.240 ) ( 0.243 ) ( 0.244 ) ( 0.221 ) ( 0.207 ) ( 0.224 ) ( 0.276 )

1996 Panel Flag 1.759 * 1.177 * 0.542 0.226 2.211 * 1.410 * 1.941 * 0.853 * 0.483 1.150 2.384 3.647

( 0.447 ) ( 0.353 ) ( 0.393 ) ( 0.375 ) ( 0.806 ) ( 0.836 ) ( 0.699 ) ( 0.512 ) ( 0.933 ) ( 0.914 ) ( 1.850 ) ( 2.383 )

R Square 0.493 0.493 0.217 0.217 0.258 0.258 0.198 0.198 0.172 0.172 0.143 0.143

10.435 19.785 10.796

8

7
88

TABLE B.2

AVERAGE MONTHLY GROWTH, REPLACEMENT, AND EXIT RATES, 

1990 THROUGH 1999ESTIMATES USING UNADJUSTED SIPP DATA

Period

Average Monthly 

Growth Rate

Average Monthly 

Replacement Rate

Average Monthly 

Exit Rate

Caseload Growth I: 1990-1993

 August 1990 – July 1991 0.96 5.6 3.8

 August 1991 – July 1992 0.70 5.2 3.9

 August 1992 – July 1993 1.24 5.0 3.9

 Overall 0.97 5.3 3.9

Caseload Decline I: 1993-1996

 August 1993 – July 1994 -0.23 4.4 4.1

 August 1994 – July 1995 0.10 4.1 4.2

 August 1995 – July 1996 -0.46 5.2 5.0

 Overall -0.20 4.6 4.5

Caseload Decline II: 1996-1999

 August 1996 – July 1997 -1.40 5.5 6.6

 August 1997 – July 1998 -0.91 5.6 6.2

 August 1998 – October 1999 -0.45 5.7 6.1

 Overall -0.88 5.6 6.3

Overall 1990-1999 -0.06 5.2 4.9

SOURCE: SIPP data for years shown.