Geographic Variation in Food Stamp and Other Assistance
Program Participation Rates:
Identifying Poverty Pockets in the South
Final Report submitted to the Southern Rural Development Center, Mississippi State
University, Mississippi State, MS in completion of a grant funded by the Economic
Research Service of the U.S. Department of Agriculture.
William H. Hoyt
Gatton Professor of Economics
Department of Economics
University Of Kentucky
Lexington, KY 40506-0034
(859)257-2518 office
(859)323-1920 fax
[email protected]
Frank A. Scott, Jr.
Gatton Professor of Economics and DGS
Department of Economics
University Of Kentucky
Lexington, KY 40506-0034
(859)257-7643 office
(859)323-1920 fax
[email protected]
December 2004
Project Summary:
A result of the 1996 welfare reforms was that TANF/AFDC rolls declined dramatically,
while SSI enrollment increased slightly. Since Food Stamp participation rates are considerably
lower among SSI recipients than among TANF recipients, Food Stamp enrollment was significantly affected by welfare reform even though it was not directly targeted by the legislation. Understanding changes in Food Stamp participation thus requires a simultaneous analysis of participation in TANF and SSI.
Along with welfare participation, Food Stamp participation declined in the late 1990’s.
While the reductions in Food Stamp participation are generally not of the same magnitude as
those in welfare participation, they are, nonetheless significant. Given relatively insignificant
changes in the Food Stamp program as a result of PWROA of 1996, particularly when compared
to those made with respect to welfare, the large reductions in Food Stamp participation seem
puzzling. As a result of the observed reductions in participation in both programs, evaluating the
link between AFDC/TANF participation and Food Stamp participation may be helpful in
explaining why Food Stamp participation declined so sharply during this period.
In this project we have directly examined the link not only between Food Stamp
participation and AFDC/TANF participation but also between Food Stamp participation and SSI
participation using county-level data on participation in these three programs. Our results from
estimation using both a sample of states throughout the U.S. and only southern states indicate
that a strong relationship exists between the level of Food Stamp participation and both welfare
and SSI participation, even when controlling for numerous demographic, economic, and program
characteristics that are likely to affect both eligibility and participation. If anything, the link
1
between TANF participation and Food Stamp participation in 2001 appears stronger than the link
between AFDC participation and Food Stamp participation in 1995.
Food Stamp participation responds in predictable ways to the different options states now
have as a result of welfare reform to treat income and resources, eligibility, and assets for the
purposes of determining Food Stamp eligibility and income. County administration as opposed
to state administration has a significant negative impact on participation, while exempting child
support from income and expanded categorical eligibility increase participation. State-required
training and employment appear to have a significant negative on Food Stamp participation,
particularly in the Southern states. While One-Stop Centers appear to have little impact on
participation, at least in the South, the longer the time span for certification the higher the Food
Stamp participation rate.
We have also directly examined the change in Food Stamp participation, both in absolute
terms (change in the number recipients per 1000 residents) and percentage terms, while
controlling for the levels and changes in both AFDC/TANF and SSI participation. Absolute
changes in Food Stamp participation between 1995 and 2001 are generally negatively related to
the levels of both AFDC and SSI participation in 1995. However, changes in Food Stamp
participation are positively related to changes in AFDC/TANF participation, suggesting that
counties with large reductions in welfare case loads have large reductions in Food Stamp
caseloads as well. This result, however, is not robust. When the change in Food Stamp
participation is measured as a percentage change, we find that larger (percentage) reductions in
welfare participation result in smaller (percentage) reductions in Food Stamp participation,
indicating that Food Stamp and welfare participation might be better described as substitutes
than complements.
2
Introduction and Problem Statement
The obvious, and frequently striking, demographic and geographical variation in welfare
recipiency has been a topic of research for both economists and sociologists.1 The usual starting
point for this research is the assumption that there are no inherent differences among eligible individuals in their likelihood to participate in welfare programs. Any differences in observed participation among demographic groups or across regions would thus be explained by differences
in eligibility rates. Invariably, differences in welfare recipiency are not fully explained by differences in eligibility alone. Instead, among different demographic groups and across regions
participation by eligible individuals and households can vary dramatically.
Maps 1 and 2 give participation rates for Food Stamps for Kentucky and Arkansas in
1999. As these maps suggest, there is a great deal of geographical variation in Food Stamp
participation among counties in these two states. Maps 3 and 4 give poverty rates for Kentucky
and Arkansas in 1999.2 Again, there is a great deal of variation among counties. Of particular
interest to us is to what extent and why there are differences in the variation across counties in
Food Stamp participation and the poverty rate. While there is clearly a strong correlation
between heavy or light Food Stamp participation and high or low poverty rates in a county, the
correlation is not perfect. Some counties with high participation in Food Stamps are not among
the ranks of the poorest counties and some of the poorest counties in these two states do not have
the highest participation in food stamps. If poverty does not fully explain the variation in Food
Stamp participation among counties, what other factors might explain it?
1
Hoyt and Scott (2002a) provide a summary of this research.
Maps were generated using the ERS Food Stamp Map Machine, located at
http://www.ers.usda.gov/Data/FoodStamps/.
2
3
Several different patterns among welfare participants have attracted the attention of
researchers, including intergenerational correlations, social network correlations, and physical
location correlations. The fundamental question is whether spatial concentrations of poverty
represent more than just collections of poor people who happen to live in the same place. If
there are identifiable transmission mechanisms, the answer is yes. As others have suggested,
possible mechanisms include positive and negative information flows, role modeling, attitude or
stigma effects, and institutional infrastructure that supports welfare participation.
We are thus interested in spatial concentrations of poverty and the existence of neighborhood effects. We propose to study the variation in participation rates across geographic locations
in Food Stamps, Supplemental Security Income (SSI), and Aid to Families with Dependent
Children (AFDC)/Temporary Assistance for Needy Families (TANF) using county-level data.
By using county-level data, we can analyze differences in program policy parameters at the state
level in combination with population eligibility characteristics at the county level to see how
these differences influence variation in participation rates. And the use of county-level data
enables us to explicitly consider the influence of geography on the transmission of welfare
participation.
While this study is national in scope, we focus on areas where welfare participation rates
are highest. We pay particular attention to the South, and specifically to four regions within the
South with high poverty rates: the Mississippi Delta Region, the Rio Grande Valley, the Black
Belt, and the Appalachian Region.3 Our primary emphasis is participation in the Food Stamp
program. But since Food Stamp participation is closely connected to TANF and SSI
participation, we simultaneously analyze participation in those two programs as well. We first
analyze welfare participation in 1995, prior to the 1996 passage of major reforms to the AFDC
3
See Table 1 for a list of the counties included in each of these high poverty areas.
4
program (creating TANF) and minor reforms to the SSI program. We then analyze welfare
participation in 2001, after the program changes have been in effect for awhile.
This approach enables us to assess the use over time of the nation’s major food assistance
program. We are able to compare rural vs. urban and metro vs. non-metro participation in Food
Stamps, as well as in TANF and SSI. We are able to analyze the effects of macro factors, such
as program interactions, eligibility criteria, and benefit levels, and of micro factors, such as
economic and demographic characteristics of the eligible populations, on Food Stamp
participation. By examining food stamp participation both before and after welfare reform we
are also able to analyze how welfare reform may have differentially affected food stamp
participation in different regions and settings.
Objectives
This research project has a number of specific objectives:
o To identify the determinants of program usage for Food Stamps, SSI, and AFDC/TANF.
Explanatory variables fall into three broad categories. First are characteristics of individuals
that by legislative design determine program eligibility. Second are variables describing
program structure, specifically measures of benefits levels and the allocation of funding
responsibilities. Third are characteristics of the population that serve as proxies for
environmental or cultural factors that are unrelated to eligibility but may, nonetheless,
influence welfare participation.
o To compare changes in the determinants of program usage for Food Stamps, SSI, and
AFDC/TANF before and after the welfare reforms of 1996. We specifically look at the
interaction between AFDC participation and Food Stamp participation in the pre-reform
period and compare it to the interaction between TANF participation and Food Stamp parti-
5
cipation in the post-reform period to determine whether the relationship has changed. We
also examine the interaction between SSI participation and Food Stamp participation pre- and
post-reform to determine the extent to which changes in the SSI program and the recipient
population have impacted the use of Food Stamps.
o To investigate county-by-county participation rates throughout the South in Food Stamps,
SSI, and TANF. We first look at raw participation rates in each of the three programs. Then
we control for differences in (estimated) eligible populations to calculate an adjusted
participation rate. It is this variation in participation due to non-eligibility factors that is most
relevant for identifying neighborhood or network effects, because this residual variation may
yield clues about other factors that serve as transmission mechanisms for welfare
dependence. We then compare the raw participation rates and the adjusted participation
rates.
In this report, for obvious reasons, we focus on participation in the food stamps program
but consider this participation in the context of a model in which participation in other programs
(AFDC/TANF and SSI) as well as the characteristics of these programs are considered. The
determinants of participation in AFDC/TANF and SSI are not reported here.
Research Methodology
Since our interest is in explaining and understanding geographical variation in Food
Stamp recipiency rates, particularly variation beyond that explained by variation in the eligible
population, we estimate a participation, or more precisely “recipiency”, equation for Food
Stamps. Since we believe the structure of and participation in other welfare programs, particularly, AFDC/TANF and SSI, may be important in understanding participation in Food Stamps,
characteristics of these programs are included in the Food Stamp participation equation. Of
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course, it follows that if the structure of and participation in AFDC/TANF and SSI influence
Food Stamp participation, then Food Stamp participation will likely have an influence on
participation in AFDC/TANF and SSI. For this reason we estimate a system of equations
explaining participation in all three programs.4
Before discussing more completely both the estimation procedure and explanatory
variables, we turn our attention to measures of program participation. As previously explained,
we examine participation in three major welfare programs: Food Stamps, AFDC/TANF, and SSI.
Our focus is on participation. For Food Stamps and SSI we measure this in terms of participants
per 1000 persons at the county level, and for AFDC/TANF we measure as cases per 1000
households at the county level. There are several advantages to the use of county-level data
instead of state-level data as is more typically done. First, use of state-level data masks both the
considerable variation in welfare program participation within states and what we consider some
of the reasons that welfare participation may vary within states. Second, to the extent that
regional characteristics influence Food Stamp and other program participation, the county, not
the state, is probably a better approximation of the relevant region. If, for example, “supply”
factors such as the extent of legal or medical services influence program participation, these
factors are probably only relevant within a county or contiguous counties and certainly not
throughout the state. If population density or concentration of ethnic groups lead to “networks”
that increase information about programs, again this is probably relevant at the county or lower
level, and not at the state level. Given both the limited geographical information and the limited
geographical representation found in individual or households surveys on program participation
(for example, SIPP, CPS, NLSY), a focus on participation aggregated to the county level ensures
4
This simultaneous system can be estimated either as a system or equation by equation using instrumental variables
for each equation. We use the latter approach.
7
both identification at the county level and measures of participation in counties where
populations are small and therefore representation in surveys might be very limited.
As mentioned before, we believe that one explanation of geographical variation in Food
Stamp participation may be differences in participation in other welfare programs, specifically
AFDC/TANF and SSI. Given the significant structural changes that occurred with the transition
from AFDC to TANF as well as the dramatic declines in participation, we wish examine
geographical variation in Food Stamp participation as well as in AFDC/TANF and SSI both
before welfare reform and after welfare reform. While SSI has not had the same major programmatic changes as AFDC/TANF, there has been a significant change in the composition of SSI
cases during this period due to earlier changes in the program. Beginning in the early 1990’s but
continuing throughout the decade, there have been significant increases in the percentage of
persons receiving SSI who are classified as disabled, specifically with mental disorders and
under eighteen years of age. Since the mix of SSI participants may influence participation in
Food Stamps, we might expect different Food Stamp participation pre- and post-welfare reform
for this reason as well. For these reasons, we examine geographic variation in Food Stamps,
AFDC/TANF, and SSI pre- and post-welfare reform.
While our focus in this project is on counties for states within the South, for completeness
we have obtained county-level data for the entire U.S. Data on AFDC, SSI, and Food Stamp
participation aggregated to the county-level were obtained for 1995 and 2001. 1995 data reflect
the last full year prior to welfare reform.5 2001 data represent the post-reform sample. We
chose 2001 rather than an earlier year to allow more complete adjustment to the changes in
welfare policy.
5
SSI participation rates are actually for January 1996.
8
Data on the number of Food Stamp cases at the county level are collected by the United
States Department of Agriculture. These are referred to as the FNS-101 data. Their use has been
rather limited. Wilde and Dicken (2003) and Goetz et al. (2002) are the only studies using these
data of which we are aware. The data are now readily available electronically from the Bureau
of Census (http://www.census.gov/hhes/www/saipe/techdoc/inputs/foodstmp.html), which uses
them as inputs in its simulation model for determining small area income and poverty estimates.
Data are available for July of the years 1989, 1993, 1995, 1997, 1999, 2000, and 2001.
Data
on aggregate SSI recipients within a county are available electronically from 1990 to 1996 on the
compact disc, USA Counties. Data on county-level SSI participation for 2000 and 2001 are also
available electronically at the Social Security Administration website:
http://www.ssa.gov/policy/docs/statcomps/ssi_sc/2001/index.html. Other years are available in
hard copy in “SSI recipients by state and county,” an annual publication of the Social Security
Administration. One advantage that this publication has over the data obtainable from USA
Counties is that, in addition to the total recipients in a county, it provides a breakdown of recipients by category (aged and blind or disabled) as well as age (under 18, 18-64, 65 or older).
Since participation in Food Stamps is likely influenced not only by the number of SSI
participants but also the composition of SSI participants with respect to category and age, we
have entered these data manually.
County-level data on AFDC/TANF are much more difficult to obtain. In contrast to
Food Stamps and SSI which are administered federally, AFDC/TANF is administrated by state
governments. Since federal assistance is given to state governments based on state caseloads, no
reporting of caseloads at the county level to federal agencies is required and none is federally
available. While caseloads for some counties are available in federal publications or data
9
collections such as USA Counties or The Metropolitan Area Data Book, there is no federal
source for data on AFDC/TANF for all counties. For earlier work (Hoyt and Scott, 2002b) we
obtained county-level AFDC participation for 45 states for the year 1995. This was done by
contacting and requesting the data from each of the states’ agencies for administering AFDC.
We have had to use the same labor-intensive approach to get TANF participation data for 2001.
We contacted each state and obtained TANF participation data for each county for the year 2001.
To insure consistency, we also obtained AFDC participation data for 1995.
In addition to the structure of and participation in AFDC/TANF and SSI, Food Stamp
participation is influenced by a number of other factors for which we also obtained data. With
welfare reform, several changes occurred with the Food Stamp program as well as the change
from AFDC to TANF. One of the changes was expanded flexibility by states in administering
Food Stamps in their state. While benefit levels are federally set, states have significant
flexibility in defining income and resources, asset limitations, and expanding the eligible
population by using TANF funds if they so desire. Table 2 lists some of the options available to
the states with a summary of what each state does. One distinction among states is whether the
program is administered by the state or county government. Another option states have, which
eight currently use, is to exclude child support as income, thereby increasing Food Stamp
income. Sixteen states currently have Employment & Training Pledges that place a three-month
limit on Able-Bodied Adults Without Dependents (ABAWD) to obtain qualifying education,
training or employment in order to continue receiving food stamps. Thirteen states offer
Transitional Benefits enabling TANF recipients, upon the loss of TANF, to continue to receive
Food Stamp income equal to or above the level they received on TANF for up to five months.
Thirty-nine states have Expanded Categorical Eligibility that essentially eliminates any asset
10
tests for households receiving TANF money. In addition, states have a great deal of flexibility in
the treatment of automobiles as an asset.6 While the alternative options are reported in Table 2,
the complexity of these options makes it difficult to operationalize their use in our empirical
analysis. In addition to differences among the states in the options they employ, attention has
been given to how states might vary in certifying or re-certifying that a household is eligible for
food stamps. Table 2 reports summary data on time for recertification for a variety of cases
calculated from the Economic Research Service (ERS) data on quality control as reported in
Bartlett, et. al. (2002). We create an average time for recertification for all categories of
recipients based on these data.
First and most obvious are variables that can be considered as determinants of or proxies
for determinants of eligibility. These include measures of poverty and income within the county
as well as measures of family size. Annual estimates of poverty rates and median income were
obtained from the Census Bureau (http://www.census.gov/hhes/www/saipe/sitemap.html). In addition to giving the poverty rate for the entire county, the Census estimates the poverty rate for
households with children under 18 and elderly households as well.
Analogously, AFDC/TANF and SSI participation depend on the eligible populations for
these programs. While poverty and income are obviously relevant for these means-tested programs, other factors are important in determining eligibility. As either disability or age is
necessary to qualify for SSI, we have obtained measures of both. Annual estimates of the elderly
population for each county are available from the Census Bureau. A measure of disability (selfreported) is available from the decennial Census. For AFDC/TANF, we include as proxies for
6
Information on state food stamp options are from Food and Nutrition Service, “Food Stamp
Program Options: State Options Report,” United States Department of Agriculture, September
2004.
11
the eligible population in a county the percentage of households with children under 18 and the
percentage of family households with a single parent. Again, both are obtained from the U.S.
Census Bureau.
In addition, following other studies of program participation, we include “demographic”
factors unrelated to eligibility for the program. Thus we include measures of the ethnic and racial
composition of the county’s population, the age distribution for the county, and the education
background of county residents. These factors should not affect eligibility but may affect informational “networks” about programs or affect participation for other reasons. Again, data on
these factors were obtained from the U.S. Census, many of which are provided as annual
estimates.
As factors explaining participation in all three programs we include measures of locational characteristics of the county (population density, urban/rural, MSA/non MSA), employment and economic conditions (earnings, employment rates), and region. Data on employment
and earnings were obtained electronically from the Department of Commerce Bureau of
Economic Activity via REIS (Regional Economic Information System). In addition to general
employment and earnings levels, we include measures of earnings in industries which we
characterize as “suppliers” of services related to participation in welfare programs. Specifically,
following our earlier study on AFDC and SSI participation (Hoyt and Scott, 2002b), we include
county-level earnings (percentage of total earnings) in the health, legal, and social service sectors
as well as government spending at the local, state, and federal level.
Among the three programs, Food Stamps is unique in having uniform benefits and eligibility requirements across all the states. While SSI is also federally administered, some states do
supplement benefits and have different criteria for eligibility for Medicaid for SSI recipients as
12
well as different benefit levels for Medicaid recipients. Benefits and to a lesser extent eligibility
for AFDC/TANF vary significantly across states. Data on benefit levels for AFDC/TANF for
the different states were obtained from the Statistical Abstract of the United States. Data on state
supplements and the Medicaid criteria for SSI were obtained from the Social Security
Administration. A comprehensive list of other differences among states in eligibility, work, and
time limits for AFDC and TANF was obtained from the Urban Institute.
Data Analysis
As our discussion of the data suggests, we estimate a system of participation equations
for the three programs in which participation depends on a number of different (sets of) factors.
Formally we can express the model as
F
Fijt = α1t ATjt + α2 SSIijt + α3t SPjt + α4t EFijt + α5t EATijt + α6t ESijt + α7t Cijt + α8t Sijt + α9t Dijt + α10t Lijt + π rjt
+ ε ijtF
ATijt = β1t Fi jt + + β2t SSIi jt + β3t ATPjt + β4t EFijt + β5t EATijt + β6t ESijt + βtCijt + β8t Sijt + β9t Dijt + β10t Lijt + πrjtAT + εijtAT
and
S
SSIijt =γ1t ATj + γ 2t Fi j + γ 3t SPji + γ 4t EFijt + γ 5t EATijt + γ 6t ESijt + γ 7t Eijt + γ 8t Sijt + γ 9t Dijt + γ10t Lijt + πrjt
+ εijtS
where the subscript i refers to county; j to state; t to year; and r to region (cluster of counties).
The terms Fijt, ATijt, and SSIijt refer to the participation rates in Food Stamps,
AFDC/TANF, and SSI in county i in state j in year t. The terms ATPj and SPj represent the set of
variables characterizing the program structure and benefits for AFDC/TANF and SSI in state j.
The terms EFijt, EATijt, and ESijt are characteristics of the county population that serve as measures
of the fraction of individuals (SSI) or households (AFDC/TANF, Food Stamps) in the county
eligible for the programs. These measures would include the poverty rate and characteristics of
family structure. The subscript AT refers to AFDC/TANF, F is for Food Stamps, and S is for
SSI. The term Cijt refers to economic and employment conditions in the county and the term Sijt
13
refers to supply factors discussed in the preceding section. Demographic characteristics of the
county population unrelated to eligibility, such as race and ethnic composition, are included in
Dijt and locational characteristics such as population density and whether the county is in an
MSA are included in Lijt. The term π rtk , k=F,AT,S represents a “spatial” element to participation
that might indicate, for example, spatial autocorrelation in participation among adjacent counties.
The term ε rtk , k=F,AT,S is a county-specific error term.
Note that the coefficients, α, β, and γ are not assumed to remain constant over time. Specifically, we do not believe that the relationships between participation in the programs and
program and eligibility characteristics (ATjt, SPjt, Ekjt, k=F,AT,S) are the same before and after
welfare reform.
The inclusion of other program participation rates in the equation explaining participation
of a program will result in inconsistent estimates using ordinary least squares if the error terms of
the three equations are correlated. For this reason we estimate these equations separately using
an instrumental variable technique. As discussed in more detail in our results sections, our
instruments are variables included in one equation but not the others and are composed of
eligibility and program characteristics of the three programs that vary among states and the
programs.
Estimation of the parameters of these participation equations enables us to address the issues in which we are most interested: 1) the reasons for geographical variation in Food Stamp
participation among counties; 2) what impact welfare reform has had on the determinants of
geographical variation; and 3) what impact welfare reform has had on Food Stamp participation.
Empirical Results
Participation by Location
14
Before turning to regression results it is informative to examine the raw data on program
participation before and after welfare reform. Figures 1a-j contain summary data on participation rates in the Food Stamp, AFDC/TANF, and SSI programs for 1995 and 2001 for the entire
U.S. (lower 48 states). Figure 1a illustrates Food Stamp participation. Between 1995 and 2001
Food Stamp participation declined everywhere, but the decline was sharpest in the West. Figure
1b, which also illustrates Food Stamp participation, reveals that the decline in Food Stamp
participation was greatest in high poverty areas within MSA’s. Figures 1c and 1d illustrate SSI
participation. There were only modest changes in SSI participation between 1996 and 2001.
The biggest decline in SSI utilization occurred in the South. Figures 1e and 1f illustrate
AFDC/TANF participation. The obvious conclusion is that between 1995 and 2001 participation
in AFDC/TANF declined sharply everywhere, in all regions of the country and in MSA and nonMSA areas.
Figure 1g contains the ratio of Food Stamp recipients to AFDC/TANF recipients in 1995
and 2001 by region of the country. Food Stamp usage declined the least relative to
AFDC/TANF usage in the Midwest and the South, and, as Figure 1h shows, in non-MSA
regions. Figure 1i contains the ratio of SSI recipients to AFDC/TANF recipients in 1995 and
2001 by region. There has been a significant decline in the utilization of AFDC/TANF relative
to SSI between 1995 and 2001, and it is most evident in the South. Figure 1j shows that SSI
participation relative to AFDC and TANF is higher in non-MSA regions, whether the county is
in a high poverty area or not.
Figures 2a-j contain the same information for the South. An additional breakdown is to
add the high poverty areas of the Mississippi Delta, Appalachia, the Black Belt, and the Rio
Grande Valley. Our definition of these areas is more restrictive than, for example, the definition
15
of Appalachia by the Appalachian Regional Commission or the definition of the Mississippi
Delta by the Mississippi Delta Authority. Our definition of Appalachia is restricted to what is
referred to as central Appalachia by the ARC. However, as with these other poverty areas we
require that all counties that are included have poverty rates in 2000 exceeding 18% and not be
within an MSA. In addition, included counties are coterminous with at least one other county in
the poverty region. A list of the counties in these poverty regions is found in Table 1.
It is especially important to understand program utilization and program interactions in
these specially designated regions. Pre and post welfare reform Food Stamp recipiency rates for
the southern states are illustrated in Figure 2a. There is considerable variation across states in
both the utilization rates and changes in utilization. Food Stamp participation declined sharply
between 1995 and 2001 in Georgia, Maryland, Mississippi, Texas, Virginia, and West Virginia.
There was relatively little decline in Arkansas, Florida, North Carolina, and South Carolina.
Figure 2b contains the same information according to MSA and Poverty status, and for
designated poverty areas. Food Stamp utilization was relatively high and declined more sharply
in the Delta and Rio Grande Valley regions, as compared to the Appalachia and Black Belt
regions.
Figure 2c contains AFDC and TANF recipiency rates for southern states in 1995 and
2001. Again there is considerable variation across states, but there is one common theme—
participation declined sharply everywhere between 1995 and 2001. Figure 2d illustrates
AFDC/TANF participation for MSA, Poverty, and specific poverty areas. The proportionate
changes from 1995 to 2001 were similar in the Appalachia, Black Belt, and Delta regions. In
each case the relative decline in recipients was more pronounced than in the Rio Grande Valley
region. Figure 2e shows SSI recipiency rates in 1996 and 2001. SSI participation was almost
16
unchanged or actually increased in the District of Columbia, Delaware, Florida, Kentucky,
Maryland, and West Virginia. Declines were only slight in the other states. As can be seen in
Figure 2f, SSI participation actually increased in Appalachia, and declined the most in the Delta
region.
The ratios of Food Stamp recipients to AFDC/TANF recipients in 1995 and 2001 for the
southern states are illustrated in Table 2g. In some states, such as Florida and South Carolina,
the decline in AFDC/TANF participation was much more pronounced that the decline in Food
Stamp participation. In other states, such as Tennessee and Texas, the relative declines were
closer in magnitude. Similarly, the decline in AFDC/TANF participation was higher relative to
the decline in Food Stamp participation in the Black Belt region than in the Rio Grande Valley
region, as is shown in Table 2h. Figure 2i illustrates the increase in SSI participation relative to
AFDC/TANF participation between 1995 and 2001. This measure combines the effects of small
declines or even increases in SSI participation and large declines in AFDC/TANF participation.
Large relative shifts occurred in Florida, Louisiana, Maryland, and Mississippi. Figure 2j shows
that large relative shifts occurred in Appalachia, the Black Belt, and the Delta, but not in the Rio
Grande Valley.
Estimation Results
While much can be gleaned from examining raw participation rates, further insights can
be obtained by using multiple regression analysis to investigate participation rates. As our
examination of participation rates indicates, throughout the U.S. there were significant decreases
in welfare participation from 1996 to 2001. At the same time, Food Stamp participation also
decreased significantly. Of course, these reductions in the U.S. overall are well known, as well
as reductions, though not uniformly, in every state. Our contribution to the analysis of welfare
17
reform is the ability to track how these changes varied among rural and urban regions and in
areas particularly prone to poverty. Given that we have geographical variation and
identification, we also have the opportunity to examine how differences among states in the
structures of their programs, particularly in Food Stamps, affect Food Stamp participation.
Previous studies have been unable to perform this type of analysis because of the availability of
data available at or only identified at the state level.
Food Stamp Participation
While the examination of mean participation rates is useful, it does not offer much insight
into how and why reductions in program participation, particularly for food stamps, occurred.
As discussed earlier, we believe that examining participation in Food Stamps in a framework that
simultaneously considers participation in both welfare programs (AFDC in 1995 and TANF in
2001) and SSI may offer some insights into these reductions in participation.
We begin our examination of Food Stamp participation with a cross-sectional analysis of
the level of Food Stamp participation in both 1995 and 2001. As discussed earlier, we are
interested in the influence of a number of different factors on Food Stamp participation. Some of
these factors can be expected to be positively related to Food Stamp participation (at the county
level) because they will determine the fraction of the county population that is eligible (poverty
measures, unemployment rates, and mean income, for example). Other factors not directly
related to eligibility might be correlated with participation conditional on eligibility. That is,
these factors might be related to characteristics of the eligible population that make participation
more or less likely (demographic characteristics such as age, race, non-native fraction of the
population, education). Locational characteristics (rural vs. urban, for example, or population
density) also may influence participation. We also include measures of “supply” factors, i.e.,
18
sectors of the economy that might influence participation such as legal, health, or social services.
Finally, characteristics of the programs that vary among states are also included. Variable
descriptions and summary statistics for 1995 and 2001 both for the U.S. and the South are found
in Table 3.
We estimate structural rather than reduced-form equations. In our analysis, in the
structural estimates we include as explanatory variables AFDC (1995) or TANF (2001)
participation and SSI participation. As we argued earlier, these participation rates are
endogenous and are themselves functions of other factors such as welfare and SSI program
characteristics that vary across states and characteristics of the county population. Estimating
structural rather than reduced-form equations requires instruments to independently identify the
endogenous variables, which are in our case participation in AFDC/TANF or SSI. For
AFDC/TANF we use as instruments characteristics of the programs, including maximum
benefits, work requirements, child care, and time limits, as well as measures of eligibility,
including the fraction of households headed by single parents for AFDC/TANF. For SSI we
have as instruments whether the state offers a supplement and if so how much, the link with
Medicaid eligibility in the state, and work disability rates for the county as reported in the
Census of Population.
These regression results for 1995 are contained in Table 4 and for 2001 in Table 5.
Columns (a) and (d) in Table 5 are directly comparable to the results reported for all states and
for southern states in Table 4. Columns (b) and (c) in Table 5 contain results using additional
Food Stamp program characteristic variables for all states, and columns (e) and (f) contain
similar results for southern states. In 1995 for all states and for just the southern states Food
Stamp participation rates were significantly related to AFDC and SSI participation rates. That
19
relationship was still true in 2001 for all states, but in the southern state sample there was a tight
connection with TANF participation but no significant connection between Food Stamp
participation and SSI participation.
In both years and in both samples the proportions of the population with incomes
between 0% and 50% and between 50% and 100% of the poverty level were positively and
significantly related to Food Stamp participation. In 1995 there was a significant connection
between Food Stamp participation and per capita income, but that relationship does not show up
in the 2001 regressions. The unemployment rates among both males and females did not seem to
affect Food Stamp participation in 1995, but are significant in the 2001 regressions, with the
exception of the female unemployment rate in southern states. The one consistent age
distribution effect on Food Stamp participation seems to be the fraction of the population under
age 5 years old, which is consistently positive and significant.
In the 1995 sample the African-American fraction of the population is a positive and
significant predictor of Food Stamp participation. The Hispanic fraction is positive and
significant in the southern state sample. Those results change in the 2001 sample. Percent
African-American is not significant in the southern state sample, and percent Hispanic is
negative and significant in the southern state sample. The location variables, MSA vs. non-MSA
and population density, do not show any consistent relationship with Food Stamp participation,
once all of the other control variables are included in the analysis. Within the southern state
sample, the poverty regions are characterized by higher Food Stamp participation rates, even
after controlling for poverty rates, unemployment rates, income levels, education levels, racial
and ethnic composition, and other factors.
20
The effects of specific Food Stamp program characteristics that were in place in 2001 can
be seen in the regressions reported in columns (b), (c), (e), and (f). In the all states sample, each
of the program variables has the expected effect on Food Stamp participation rates. Expanded
eligibility and exempted child support increase participation, and county administration and
employment and training requirements decrease participation. In the southern state sample,
increasing the number of months between recertification significantly increases Food Stamp
participation. One final item of interest is One-Stop Centers. We collected data on the number
of One-Stop Centers in each county in the southern states. When this variable is included in the
southern state sample, there is no significant effect on Food Stamp participation.
Changes in Food Stamp Participation
Tables 6 and 7 analyze the absolute and the percentage change in Food Stamp
participation rates between 1995 and 2001. Results are reported for both the all states sample
and the southern states sample. Three different specifications are run for each sample. The first
includes the AFDC participation rate and the SSI participation rate in 1995 as an explanatory
variable. The second includes the change in the AFDC/TANF participation rate and the change
in the SSI participation rate between 1995 and 2001. The third includes both the 1995 level and
the 1995-2001 change in both AFDC/TANF and SSI participation.
As can be seen in Table 6, in the all states regressions the decline in Food Stamp
participation was greater the higher the level of AFDC participation in 1995 (column (a)) and the
greater the decline in AFDC/TANF participation between 1995 and 2001 (column (b)). When
both variables are included in the regression as reported in column (c), neither the level of AFDC
participation in 1995 nor the change in AFDC/TANF are associated with greater declines in
Food Stamp participation between 1995 and 2001. In contrast, while the change in SSI
21
participation between 1995 and 2001 had no significant impact the change in Food Stamp
participation, greater participation in SSI in 1995 had resulted in a statistically-significant
reductions in Food Stamp participation between 1995 and 2001.
Food Stamp program characteristics affect participation in predictable ways.
Administration of Food Stamps at the county level is associated with significant declines in
participation. Exempting child support is associated with smaller declines in participation, while
imposing an employment and training requirement is associated with larger declines in
participation. The fraction of the county’s population with incomes below the poverty level does
not seem to be connected with changes in Food Stamp participation. The greater the change in
unemployment, both among males and females, the greater the change in Food Stamp
participation between 1995 and 2001. As inspection of columns (d) – (f) indicate, the
coefficients, in sign and significance, for these variables is quite similar for the sample of only
Southern States.
Counties with larger fractions of the population below age 5 or greater than age 64
experienced larger declines in Food Stamp participation between 1995 and 2001. Where the
African-American or Hispanic proportion of the county’s population was greater, the greater was
the decline in Food Stamp participation. The reverse is true for counties where the Native
American proportion of the population was greater. Controlling for other factors, counties with
larger fractions of the population living in rural areas experienced larger declines in Food Stamp
participation. In the all states sample there were significantly greater declines in Food Stamp
participation in the South and the Northeast. In the southern states sample, the designated high
poverty regions did not appear to experience greater or lesser changes in Food Stamp participation than other areas, after controlling for other factors. In the sample of Southern states, the
22
coefficients on our categorical variables indicating a county located in one of our four poverty
pockets indicates that only for counties in the Black Belt region is the change in Food Stamp
participation significantly different than that in counties with similar demographic and economic
characteristics, with the decrease in Food Stamp participation in the Black Belt counties
approximately 9 - 18 recipients per 1000 less than similar counties.
It may not be too surprising that counties with the highest AFDC rolls in 1995 exhibited
the greatest absolute decrease in Food Stamp participation, as these counties will also exhibit the
highest Food Stamp rolls as well. For this reason we also estimate the change in Food Stamps
participation between 1995 and 2001 in percentage terms, with changes in AFDC/TANF and SSI
participation measured in percentage terms as well. Results of this set of estimates are found in
Table 7. In addition, inference using the absolute change in AFDC/TANF is made difficult
because of the high correlation between the level of AFDC in 1995 and the absolute change in
AFDC/TANF participation between 1995 and 2001.7
Focusing on estimates using all the states (columns (a) – (c)) and the interaction of the
programs, we find results that are somewhat different than those examining the determinants of
the absolute change in Food Stamp participation found in Table 6. In column (a) of Table 7, we
see that the level of AFDC cases in 1995 has a positive, but insignificant coefficient contrasting
with the significant negative coefficient on this variable in the analogous estimate of absolute
changes in participation. The coefficient on SSI participation in 1995 continues to be negative
and significant. Perhaps more interesting is the coefficient on the percentage change in
AFDC/TANF participation in both the specifications reported in column (b) and column (c).
The negative coefficient on this variable indicates that, ceteris paribus, Food Stamp participation
7
The correlation coefficient between the two variables is -0.95. In contrast, the correlation coefficient between the
1995 level of AFDC and the percentage change in AFDC/TANF is only -0.06.
23
increased more (or decreased less) in counties where there were greater percentage decreases in
AFDC/TANF rolls. The results for the sample of Southern states are reported in columns (d) –
(f). Unlike the results with all states, the results for the South indicate that the higher the level of
AFDC participation in 1995, the greater the percentage decrease in Food Stamp participation.
The level of SSI participation in 1995 has a positive impact on Food Stamp participation when
no changes in participation are included (column (d)) but no significant impact when changes in
participation are included (column (f)). Similar to the results with all states, the greater the
percentage reduction in AFDC/TANF, the smaller the (percentage) reduction in Food Stamp
participation (columns (e) and (f)) though this effect is statistically insignificant when the level
of AFDC participation is included (column (f)).
With a few exceptions, the impacts of the other variables on the change in Food Stamp
participation are similar to those found in Table 6. The magnitudes of coefficients obviously
change as the magnitude of the dependent variable is significantly smaller. In general, the
impacts of the Food Stamp program variables seem to be insignificant and perhaps less stable
with respect to changes in our specifications.
Summary and Conclusions
Along with welfare participation, Food Stamp participation declined in the late 1990’s.
While the reductions in Food Stamp participation are generally not of the same magnitude as
those in welfare participation, they are, nonetheless significant. Given relatively insignificant
changes in the Food Stamp program as a result of PWROA of 1996, particularly when compared
to those made with respect to welfare, the large reductions in Food Stamp participation seem
puzzling. As a result of the observed reductions in participation in both programs, evaluating the
24
link between AFDC/TANF participation and Food Stamp participation may be helpful in
explaining why Food Stamp participation declined so sharply during this period.
In this project we have directly examined the link not only between Food Stamp
participation and AFDC/TANF participation but also between Food Stamp participation and SSI
participation using county-level data on participation in these three programs. Our results from
estimation using both a sample of states throughout the U.S. and only southern states indicate
that a strong relationship exists between the level of Food Stamp participation and both welfare
and SSI participation, even when controlling for numerous demographic, economic, and program
characteristics that are likely to affect both eligibility and participation. If anything, the link
between TANF participation and Food Stamp participation in 2001 appears stronger than the link
between AFDC participation and Food Stamp participation in 1995.
Food Stamp participation responds in predictable ways to the different options states now
have as a result of welfare reform to treat income and resources, eligibility, and assets for the
purposes of determining Food Stamp eligibility and income. County administration as opposed
to state administration has a significant negative impact on participation, while exempting child
support from income and expanded categorical eligibility increase participation. State-required
training and employment appear to have a significant negative on Food Stamp participation,
particularly in the Southern states. While One-Stop Centers appear to have little impact on
participation, at least in the South, the longer the time span for certification the higher the Food
Stamp participation rate.
We have also directly examined the change in Food Stamp participation, both in absolute
terms (change in the number recipients per 1000 residents) and percentage terms, while
controlling for the levels and changes in both AFDC/TANF and SSI participation. Absolute
25
changes in Food Stamp participation between 1995 and 2001 are generally negatively related to
the levels of both AFDC and SSI participation in 1995. However, changes in Food Stamp
participation are positively related to changes in AFDC/TANF participation, suggesting that
counties with large reductions in welfare case loads have large reductions in Food Stamp
caseloads as well. This result, however, is not robust. When the change in Food Stamp
participation is measured as a percentage change, we find that larger (percentage) reductions in
welfare participation result in smaller (percentage) reductions in Food Stamp participation,
indicating that Food Stamp and welfare participation might be better described as substitutes
than complements.
26
References
Bartlett, Susan, Nancy Burstein, and William Hamilton, “Food Stamp Program Access Study
Final Report” E-FAN-03-013-3 November 2004
Rebecca Blank, “Evaluating Welfare Reform in the United States,” Journal of Economic
Literature, December 2002, 1105-1166.
Janet Currie and Jeffrey Grogger, “Explaining Recent Declines in Food Stamp Program
Participation,” Brookings-Wharton Papers on Urban Affairs: 2001.
Food and Nutrition Service, “Food Stamp Program Options: State Options Report,” United
States Department of Agriculture, September 2004.
William Greene, Econometric Analysis (4th edition), Upper Saddle River, New Jersey: Prentice
Hall, 2000.
Stephan Goetz, Anil Rupasingha, and Julie Zimmerman. Food Stamp Program Participation
Dynamics in US Counties and States: Final Report. University Park, PA: The
Pennsylvania State University.
Thomas Hirschl and Mark Rank, “The Effect of Population Density on Welfare Participation,”
Social Forces, September 1991, 225-235.
William Hoyt and Frank Scott, “Geographic Variation in Welfare Participation Rates:
Identifying Poverty Pockets,” working paper, University Of Kentucky, April 2002a.
William Hoyt and Frank Scott, “Participation in AFDC/TANF and SSI: Analyzing Substitution
between Programs by Recipients and State Governments,” working paper, University Of
Kentucky, August 2002b.
Jonathan Jacobson, Nuria Rodriguez-Planas, Loren Puffer, Emily Pas, and Laura Taylor-Kale,
Mathematica Policy Research, Inc., The Consequences of Welfare Reform and Economic
Change for the Food Stamp Program—Illustrations from Microsimulation, Economic
Research Service, January 2001.
Robert Kornfeld, Abt Associates Inc., Explaining Recent Trends in Food Stamp Program
Caseloads, Economic Research Service, March 2002.
Park Wilde, “The Impact of Race and Ethnicity on County Level Food Stamp Program
Participation Measures in California,” Economic Research Service, December 2002.
Park Wilde and Chris Dicken, “Using County-Level Data to Study the Race and Ethnicity of
Food Stamp Program Participants in California,” working paper, Economic Research
Service for presentation at the American Agricultural Economics Association Meetings,
July 27-30, 2003.
27
Sheila Zedlewski and Sarah Brauner, “Declines in Food Stamp and Welfare Participation: Is
There a Connection? Urban Institute Working Paper 99-13, October 1999.
Jim Ziliak, Craig Gundersen, and David Figlio, “Food Stamp Caseloads over the Business
Cycle,” Southern Economic Journal, April 2003, 903-919.
Jim Ziliak, David Figlio, Elizabeth Davis, and Laura Connelly, “Accounting for the Decline in
AFDC Caseloads: Welfare Reform or the Economy,” Journal of Human Resources,
Summer 2000, 570-586.
28
Map 1: Food Stamp Participation in Kentucky, 1999
Map 2: Food Stamp Participation in Arkansas, 1999
Legend
Per Capita FSP Participation, 1999
Less than 4.8%
4.8% - 8.7%
8.7% - 14.3%
14.3% - 23.1%
29
Greater than 23.1%
Map 3: Poverty Rate in Kentucky, 1999
Map 4: Poverty Rate in Arkansas, 1999
Legend
Per Capita Poverty, 1999
Less than 10%
10% - 14.6%
14.6% - 20%
20% - 28.5%
Greater than 28.5%
30
Figure 1a: Food Stamp Recipients, 1995 and 2001, By Region
110
FS, '95
FS, '01
100
90
Recipients per 1000
80
70
60
50
40
30
20
10
0
U.S. (48 State Totals)
Northeast
Mideast
South
West
Region
Figure 1b: Food Stamp Recipients, 1995 and 2001, MSA and Poverty
280
FS, '95
FS, '01
260
240
220
Recipients per 1000
200
180
160
140
120
100
80
60
40
20
0
Non-MSA
Poverty
Poverty, Non-MSA
Region
31
Poverty, MSA
Figure 1c: AFDC/TANF Recipients, 1995 and 2001, By Region
70
65
Recipients, 95
Recipients, '01
60
55
Recipients per 1000
50
45
40
35
30
25
20
15
10
5
0
US Totals (48 States)
Northeast
Midwest
South
West
Region
Figure 1d: AFDC/TANF Recipients, 1995 and 2001, MSA and Poverty
150
140
130
Recipients, 95
Recipients, '01
120
110
Recipients per 1000
100
90
80
70
60
50
40
30
20
10
0
MSA
Non-MSA
High Poverty
Region
32
Poverty, Non-MSA
Poverty, MSA
Figure 1e: SSI Recipients, 1995 and 2001, By Region
30
SSI, '95
SSI, '01
25
Recipients per 1000
20
15
10
5
0
U.S. (48 State
Totals)
Northeast
Mideast
South
West
MSA
Non-MSA
Region
Figure 1f: SSI Recipients, 1995 and 2001, MSA and Poverty
70
65
60
55
Recipients per 1000
50
SSI, '95
SSI, '01
45
40
35
30
25
20
15
10
5
0
MSA
Non-MSA
Poverty
Region
33
Poverty, Non-MSA
Poverty, MSA
Figure 1g: Ratio of Food Stamp Recipients to AFDC/TANF Recipients, 1995 and 2001,
By Region
6.00
5.50
FS to AFDC, '95
FS ot TANF, '01
5.00
4.50
Recipients per 1000
4.00
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
US Totals (48 States)
Northeast
Midwest
South
West
Region
Figure 1h: Ratio of Food Stamp Recipients to AFDC/TANF Recipients, 1995 and 2001,
MSA and Poverty
8.0
7.5
FS to AFDC, '95
FS ot TANF, '01
7.0
6.5
6.0
Recipients per 1000
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
MSA
Non-MSA
High Poverty
Region
34
Poverty, Non-MSA
Poverty, MSA
Figure 1i: Ratio of SSI Recipients to AFDC/TANF Recipients, 1995 and 2001, By Region
1.80
SSI to AFDC, '95
SSI to TANF, '01
1.60
1.40
Recipients per 1000
1.20
1.00
0.80
0.60
0.40
0.20
0.00
US Totals (48 States)
Northeast
Midwest
South
West
Region
Figure 1j: Ratio of SSI Recipients to AFDC/TANF Recipients, 1995 and 2001, MSA and
Poverty
2.50
2.25
SSI to AFDC, '95
SSI to TANF, '01
2.00
Recipients per 1000
1.75
1.50
1.25
1.00
0.75
0.50
0.25
0.00
MSA
Non-MSA
High Poverty
Region
35
Poverty, Non-MSA
Poverty, MSA
Figure 2a: Food Stamp Recipiency, Southern States, 1995 and 2001
180
FS, '95
FS, '01
160
Recipients per 1,000
140
120
100
80
60
40
20
irg
in
ia
in
ia
W
es
tV
V
ir g
Te
xa
s
aw
ar
e
Fl
or
id
a
G
eo
rg
ia
K
en
tu
ck
y
Lo
ui
sia
na
M
ar
yl
an
d
M
iss
iss
N
ip
or
pi
th
Ca
ro
li n
a
O
kl
ah
So
om
ut
a
h
Ca
ro
lin
a
Te
nn
es
se
e
D
el
D
.C
.
as
an
s
A
rk
A
la
ba
m
a
0
State
Figure 2b: Food Stamp Recipiency in the South, MSA and Poverty, 1995 and 2001
340
320
FS, '95
FS, '01
300
280
260
Recipients per 1,000
240
220
200
180
160
140
120
100
80
60
40
20
0
MSA
Non-MSA
Poverty
Poverty, Non Poverty &
MSA
MSA
State
36
Appalachia
Black Belt
Delta
Rio Grande
Valley
Figure 2c: AFDC/TANF Recipiency, Southern States, 1995 and 2001
130
120
AFDC, '95
TANF, '01
110
100
Recipients per 1,000
90
80
70
60
50
40
30
20
10
irg
in
ia
in
ia
W
es
tV
V
ir g
Te
xa
s
aw
ar
e
Fl
or
id
a
G
eo
rg
ia
K
en
tu
ck
y
Lo
ui
sia
na
M
ar
yl
an
d
M
iss
iss
N
ip
or
pi
th
Ca
ro
li n
a
O
kl
ah
So
om
ut
a
h
Ca
ro
lin
a
Te
nn
es
se
e
D
el
D
.C
.
as
an
s
A
rk
A
la
ba
m
a
0
State
Figure 2d: AFDC/TANF Recipiency in the South, MSA and Poverty, 1995 and 2001
120
AFDC, '95
TANF, '01
110
100
90
Recipients per 1,000
80
70
60
50
40
30
20
10
0
MSA
Non-MSA
Poverty
Poverty, Non Poverty &
MSA
MSA
State
37
Appalachia
Black Belt
Delta
Rio Grande
Valley
as
D
.C
.
an
s
ba
m
a
State
38
W
es
tV
irg
V
ir g
in
ia
in
ia
Recipients per 1,000
50
Te
xa
s
aw
ar
e
Fl
or
id
a
G
eo
rg
ia
K
en
tu
ck
y
Lo
ui
sia
na
M
ar
yl
an
d
M
iss
iss
N
ip
or
pi
th
Ca
ro
li n
a
O
kl
ah
So
om
ut
a
h
Ca
ro
lin
a
Te
nn
es
se
e
D
el
A
rk
A
la
Figure 2e: SSI Recipiency, Southern States, 1996 and 2001
55
SSI, '96
SSI, '01
45
40
35
30
25
20
15
10
5
0
Figure 2f: SSI Recipiency in the South, MSA and Poverty, 1996 and 2001
100
SSI, '96
SSI, '01
90
80
60
50
40
30
20
10
0
MSA
Non-MSA
Poverty
Poverty, Non Poverty &
MSA
MSA
Appalachia
Black Belt
Delta
Rio Grande
Valley
State
Figure 2g: Ratio of Food Stamp Recipients to AFDC/TANF Recipients, Southern States,
1995 and 2001
10.0
9.5
9.0
8.5
8.0
7.5
7.0
6.5
6.0
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
State
39
irg
in
ia
in
ia
W
es
tV
V
ir g
Te
xa
s
aw
ar
e
Fl
or
id
a
G
eo
rg
ia
K
en
tu
ck
y
Lo
ui
sia
na
M
ar
yl
an
d
M
iss
iss
N
ip
or
pi
th
Ca
ro
li n
a
O
kl
ah
So
om
ut
a
h
Ca
ro
lin
a
Te
nn
es
se
e
D
.C
.
D
el
A
rk
an
s
as
FS to AFDC
FS to TANF
ba
m
a
A
la
Recipients per 1,000
70
Figure 2h: Ratio of Food Stamp Recipients to AFDC/TANF Recipients in the South, MSA
and Poverty, 1995 and 2001
12.0
11.5
11.0
10.5
10.0
9.5
9.0
8.5
8.0
7.5
7.0
6.5
6.0
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
FS to AFDC
FS to TANF
MSA
Non-MSA
Poverty
Poverty, Non Poverty &
MSA
MSA
State
40
Appalachia
Black Belt
Delta
Rio Grande
Valley
Figure 2i: Ratio of SSI Recipients to AFDC/TANF Recipients, Southern States, 1995 and
2001
3.6
3.4
3.2
SSI to AFDC
SSI to TANF
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
State
41
V
ir g
in
W
ia
es
tV
ir g
in
ia
Te
xa
s
aw
ar
e
Fl
or
id
a
G
eo
rg
ia
K
en
tu
ck
y
Lo
ui
sia
na
M
ar
yl
an
d
M
iss
iss
N
ip
or
pi
th
Ca
ro
li n
a
O
kl
ah
So
om
ut
a
h
Ca
ro
lin
a
Te
nn
es
se
e
D
.C
.
D
el
as
an
s
A
rk
A
la
ba
m
a
0.2
0.0
Figure 2j: Ratio of SSI Recipients to AFDC/TANF Recipients in the South, MSA and
Poverty, 1995 and 2001
4.0
3.8
3.6
3.4
3.2
3.0
2.8
2.6
2.4
2.2
2.0
1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
SSI to AFDC
SSI to TANF
MSA
Non-MSA
Poverty
Poverty, Non Poverty &
MSA
MSA
State
42
Appalachia
Black Belt
Delta
Rio Grande
Valley
Table 1: Counties of Southern Poverty Pockets
Appalachian Counties
Counties in Kentucky
Mississippi Delta Counties
Black Belt Counties
Counties in Arkansas
Counties in Alabama
Rio Grande Counties
Counties in Texas
Bath
Chicot
Barbour
Cameron
Bell
Desha
Bullock
Dimmit
Breathitt
Lee
Butler
Hidalgo
Carter
Phillips
Choctaw
Maverick
Clay
Counties in Lousiana
Clarke
Webb
Crittenden
East Carroll
Conecuh
Willacy
Cumberland
Madison
Crenshaw
Zapata
Elliott
Zavala
Tensas
Dallas
Estill
Counties in Mississippi
Escambia
Floyd
Bolivar
Greene
Franklin
Coahoma
Hale
Harlan
Holmes
Lowndes
Jackson
Humphreys
Macon
Johnson
Issaquena
Marengo
Knott
Leflore
Monroe
Knox
Quitman
Perry
Laurel
Sharkey
Pickens
Lawrence
Sunflower
Sumter
Lee
Tallahatchie
Washington
Leslie
Tunica
Wilcox
Letcher
Washington
McCreary
Yazoo
Marion
Martin
Menifee
Morgan
Owsley
Perry
Pike
Powell
Whitley
Wolfe
Counties in Tennessee
Claiborne
Hancock
Buchanan
Counties in Virginia
Dickenson
Lee
Counties in West Virginia
Fayette
Mingo
Lincoln
Wayne
Logan
Webster
Wyoming
43
Table 2: Food Stamp Eligibility, Income, and Asset Rules, 2001, By State
Eligibility and Income
Vehicle Exemption Rules
Certification
0
0
1
0
0
Alaska
0
1
0
0
0
1
0
0
0
0
1
0
Arizona
0
0
1
0
1
1
0
0
0
0
1
Arkansas
0
1
0
0
0
1
0
0
0
0
California
1
0
0
0
1
0
0
1
0
Colorado
1
1
1
1
1
0
0
1
Connecticut
0
1
0
0
0
1
0
Delaware
0
1
0
1
0
0
DC
0
0
0
0
0
Florida
0
1
0
0
Georgia
1
1
0
Hawaii
0
1
Idaho
0
Illinois
TANF, Without Earnings
0
TANF, With Earnings
1
Other, Non TANF
0
Non TANF with other benefits
0
Other, Non-TANF with earnings
0
ABAWD, with Children
0
ABAWD, No Childre
0
Elderly Without
Elderly, with Earnings
Child only
Exemption >4650
One Vehicle
All Vehicles
Food Stamp Rules
Child Care or Foster Rules
TANF_MOE Categorical Eligibility
TANF MOE Rules
Transitional Benefits
Employment & Training Pledges
Child Support Exclusions
Expanded Categorical Eligibility
County Administration
State
Alabama
10.9
12
11.8
8.7
11.6
11.6
9.9
9.3
9.3
7.7
0
3.7
5.4
8.2
3.8
3.8
3.4
5.1
3.9
3.8
4.3
1
0
11
12
19.8
11.3
11.8
11.9
12.1
11.4
11.2
11.5
1
0
0
12.1
24
12
11.1
12.5
11.4
11.5
12
12.1
12
0
1
0
0
4.5
9.6
11.8
6.8
4.4
4.6
6.8
3.9
7.1
8
0
0
0
0
1
11.4
13.1
21.2
10.3
11.4
11.2
8.4
10.9
12.2
10.7
1
0
0
1
0
0
1
0
0
0
1
0
0
9.7
13
14.5
8.1
10.2
9.1
10.6
8.4
10.2
10.6
0
1
0
0
0
0
0
1
4.5
7.2
10.5
4.3
4
4
6.5
4.1
4.4
5.2
0
0
0
0
0
1
0
0
0
4.1
6
11
4.2
3.5
3.3
5.7
4.7
4.6
5.4
0
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
0
1
0
0
0
5.8
10.3
11.2
6.2
5.6
5.7
6.8
4.9
6
5.2
0
0
1
1
0
1
0
0
0
0
1
0
10.8
17.7
18.1
8.1
11.4
10.7
12
9.8
9.6
7.7
Indiana
0
1
0
1
0
0
0
1
0
1
0
0
7.8
9.1
10.9
5.4
5.4
6.1
9.9
7.3
5.5
6.2
Iowa
0
0
0
0
0
1
0
0
0
0
1
0
Kansas
0
1
0
0
0
1
0
0
0
1
0
0
11.6
13
13.8
11.2
11.7
11.8
12.6
11.4
11.8
11.8
Kentucky
0
1
0
0
0
1
0
0
0
1
0
0
4.4
13.4
20.2
4.3
4.4
4.3
6.7
4.5
7.2
9.3
44
Table 2: Food Stamp Eligibility, Income, and Asset Rules, 2001, By State
Eligibility and Income
Vehicle Exemption Rules
Certification
TANF, Without Earnings
TANF, With Earnings
Other, Non TANF
Non TANF with other benefits
Other, Non-TANF with earnings
ABAWD, with Children
ABAWD, No Childre
Elderly Without
Elderly, with Earnings
Child only
Exemption >4650
One Vehicle
All Vehicles
Food Stamp Rules
Child Care or Foster Rules
TANF_MOE Categorical Eligibility
TANF MOE Rules
Transitional Benefits
Employment & Training Pledges
Child Support Exclusions
Expanded Categorical Eligibility
County Administration
State
Louisiana
0
1
1
0
0
1
0
0
0
1
0
0
6
9.4
17.3
4.2
4.3
3.8
5.7
4.2
8.9
9.3
Maine
0
1
1
0
0
1
0
0
0
0
1
0
4.6
8.3
11.1
4.6
3.6
3.6
6.4
3.9
3
5.6
Maryland
1
1
0
0
1
1
0
0
0
1
0
0
7.5
5.7
11.6
7.1
5
4.5
8.3
5.2
4
7.7
Massachusetts
0
1
1
1
1
0
0
1
0
1
0
0
8.2
8
13.9
8.2
6.8
3.4
9.4
4.1
9.3
11.4
Michigan
0
1
0
1
0
0
1
0
0
1
0
0
7.2
10.2
17.5
6.6
6.1
4.6
10.6
8.7
10.9
11.5
Minnesota
1
1
0
0
0
1
0
0
0
0
0
1
12
11.9
11.9
11.3
11.8
11.7
11.4
11.9
11.9
12
Mississippi
0
1
0
1
0
1
0
0
0
1
0
0
8.6
11.1
10.5
7.4
10.4
11.2
8.6
7.7
9.6
8.1
Missouri
0
1
1
0
0
0
0
1
0
1
0
0
3.8
9.6
14.9
3.9
3.1
3.2
5.6
3.3
4.6
4.4
Montana
1
0
0
0
0
0
0
1
0
1
0
0
11.8
11.9
11.7
11.6
11.7
11.7
9.7
11.3
11.9
11.8
Nebraska
0
1
0
1
1
0
0
1
0
0
0
1
5.4
11.7
12.9
4.9
4.2
4.9
9.3
4.7
4.4
4.9
Nevada
New
Hampshire
0
1
0
0
0
0
0
0
1
0
0
0
0
1
0
0
0
1
0
0
0
0
1
0
6.8
9.7
12.6
6
7.5
6.3
6.3
6
7.7
9
New Jersey
1
0
0
1
0
0
0
0
0
0
0
1
4.1
8
11.3
4.7
3.5
3.5
5.1
4
3.4
4.2
New Mexico
0
1
0
0
1
0
0
1
0
1
0
0
New York
North
Carolina
1
1
1
1
1
0
0
1
0
0
1
0
1
1
0
1
1
1
0
0
0
0
1
0
3.6
8.4
11.5
4
3.6
3.4
8
3.9
6.2
6.4
North Dakota
1
1
0
0
0
0
1
0
0
1
0
0
45
Table 2: Food Stamp Eligibility, Income, and Asset Rules, 2001, By State
Eligibility and Income
Vehicle Exemption Rules
Certification
TANF, Without Earnings
TANF, With Earnings
Other, Non TANF
Non TANF with other benefits
Other, Non-TANF with earnings
ABAWD, with Children
ABAWD, No Childre
Elderly Without
Elderly, with Earnings
Child only
Exemption >4650
One Vehicle
All Vehicles
Food Stamp Rules
Child Care or Foster Rules
TANF_MOE Categorical Eligibility
TANF MOE Rules
Transitional Benefits
Employment & Training Pledges
Child Support Exclusions
Expanded Categorical Eligibility
County Administration
State
Ohio
1
1
0
0
0
1
0
0
0
1
0
0
5.2
9.4
10.8
5.8
4.5
3.8
6.4
5.9
4.1
5.8
Oklahoma
0
1
0
0
0
1
0
0
0
0
1
0
4.5
9.8
15.6
4
3.4
3.3
4.8
3
12.2
14.9
Oregon
0
1
0
0
1
0
1
0
0
1
0
0
6
12
11.4
5.9
6.2
5.7
7.9
5.8
6.8
6.9
Pennsylvania
0
1
0
0
1
1
0
0
0
0
0
0
12
12
11.9
11.2
11.8
11.6
12
10.6
11.7
11.6
Rhode Island
South
Carolina
0
0
0
0
0
1
0
0
0
0
1
0
11.2
12
11.9
8
11.3
8.9
9.1
9.1
11.9
11.8
0
1
0
0
0
1
1
0
0
0
1
0
12
12
15.2
11.4
11.8
11.9
12
11.9
11.3
11.9
South Dakota
0
1
0
1
0
0
0
0
0
0
1
0
Tennessee
0
1
0
0
0
0
0
1
0
1
0
0
3.8
5.9
10.4
4
3.6
3.2
5.6
3.7
3.8
4.2
Texas
0
1
0
1
0
0
1
0
0
0
0
1
4.4
7.2
9.4
3.7
4
3.9
4.7
3.5
5.4
5.8
Utah
0
1
0
1
0
1
0
0
0
0
0
1
4.5
9.2
10.8
5.7
4
4.2
7.6
5
3.9
6.5
Vermont
0
1
0
0
0
1
0
0
0
0
1
0
Virginia
1
1
0
0
1
1
0
0
0
1
0
0
3.9
7.6
11.8
4.7
4.2
4.1
6.7
3.8
6
5.6
Washington
0
1
0
0
0
0
0
0
1
0
0
0
4.6
6.3
11.6
3.7
4.4
4.6
3.8
4.4
4.5
West Virginia
0
1
0
1
0
0
0
1
0
1
0
0
12.8
16.1
6.1
5.4
3.7
9.6
6.5
8.7
11.5
Wisconsin
1
1
0
0
1
0
1
0
0
1
0
0
11
11
3.2
3.4
3.4
3.4
3.7
3.6
3.4
Wyoming
0
0
0
0
0
1
0
0
0
0
0
1
46
NA
3.1
. 3.5
Table 3: Variable Descriptions and Means
1995
Southern
U.S
States
Variable
Food Stamp Participation (Recipients per
1000)
Welfare Cases (Cases per 1000 Households
with Children<18)
SSI Participation (Recipients per 1000)
Disability, Female (# per 1000 ages 20-64)
Disability, Male (# per 1000 ages 20-64)
Female-Only Headed Households with
children<18, Fraction
Male-Only Headed Households with
children<18, Fraction
Poverty, Fraction below 50%
Poverty, Fraction 50-100%
Poverty, Fraction, 100 - 150%
Unemployment rate, Female
Unemployment rate, Male
Income, Per Capita
Earnings (per job)
Age, Fraction under 5
Age, Fraction under 20
Age, Fraction over 64
African-American (Fraction)
Native American (Fraction)
Hispanic (Fraction)
Immigrants (Fraction)
Education, Fraction less than 9th
Education, Fraction>9 and <12
Education, High School Graduate
Mobility, Same county 5 years age
Mobility, Same State
Earnings, Local Government
Earnings, State Government
Earnings, Federal Government
Earnings, Fraction in Health Services
Earnings, Fraction in Legal Services
Earnings, Fracion in Social Services
MSA (1 if in MSA)
Rural, Fraction of Population
Population Density
47
U.S
2001
Southern
States
102.5
133.0
72.4
94.3
101.8
27.9
0.099
0.122
108.8
38.7
0.113
0.140
42.3
25.6
0.111
0.135
46.6
35.3
0.127
0.157
0.058
0.066
0.061
0.070
0.018
0.062
0.091
0.112
0.062
0.061
18,259
21,037
0.067
0.291
0.150
0.088
0.015
0.050
0.014
0.117
0.147
0.345
0.792
0.911
0.139
0.045
0.035
0.041
0.005
0.008
0.271
0.61
231
0.017
0.077
0.107
0.120
0.072
0.063
17,387
20,984
0.068
0.289
0.144
0.169
0.009
0.057
0.012
0.147
0.177
0.327
0.791
0.911
0.136
0.050
0.032
0.044
0.005
0.006
0.285
0.63
190
0.021
0.059
0.083
0.106
0.058
0.058
23,335
25,100
0.063
0.284
0.085
9.128
2.224
6.205
0.006
0.091
0.136
0.347
0.787
0.910
0.117
0.032
0.033
0.065
0.007
0.009
0.271
0.60
242
0.020
0.071
0.098
0.116
0.067
0.058
22,014
25,025
0.065
0.282
0.077
17.108
1.599
7.103
0.006
0.116
0.166
0.337
0.783
0.910
0.119
0.036
0.031
0.065
0.007
0.008
0.285
0.61
201
Table 4: Food Stamp Participation Rates, 1995, All States and Southern States Only
All States
Coefficient
Welfare Cases
SSI Participation
Southern States
t-statistic
0.2181
7.05
Coefficient
t-statistic
0.10974
4.41
0.8048
5.24
1.56981
6.88
Poverty, Fraction below 50%
376.9864
5.73
238.89740
3.62
Poverty, Fraction 50-100%
317.6500
4.64
211.26800
2.36
-125.0428
-2.54
-62.20500
-0.93
0.0004
1.23
-0.00069
-1.60
26.8417
0.43
-6.69427
-0.10
290.7277
6.02
246.14630
3.59
-0.0001
-0.76
0.00097
3.14
Poverty, Fraction, 100 - 150%
Unemployment rate, Female
Unemployment rate, Male
Income, Per Capita
Earnings (per job)
Age, Fraction under 5
416.3055
2.25
1038.84400
5.18
Age, Fraction under 20
-0.1763
0.00
-86.66524
-1.28
Age, Fraction over 64
62.2311
2.32
140.87560
3.88
African-American (Fraction)
30.7160
3.42
42.60369
5.57
Native American (Fraction)
-44.3565
-2.33
-47.12436
-0.96
66.8454
1.68
139.03090
8.21
-175.8176
-1.11
-186.30760
-1.84
Education, Fraction less than 9
51.6190
2.07
-63.15991
-1.64
Education, Fraction>9 and <12
Hispanic (Fraction)
Immigrants (Fraction)
th
101.3743
3.86
50.37777
1.52
Education, High School Graduate
53.1681
3.41
73.70399
3.16
Mobility, Same county 5 years age
-36.2135
-2.48
-49.15087
-2.52
Mobility, Same State
-13.8280
-0.66
45.29245
1.93
Earnings, Local Government
58.6939
3.62
96.15501
3.12
Earnings, State Government
-52.5512
-4.14
-22.85413
-1.07
36.6579
2.65
42.38513
1.86
Earnings, Fraction in Health Services
-27.9706
-1.49
31.60211
1.65
Earnings, Fraction in Legal Services
-39.4396
-0.26
-291.88340
-1.99
Earnings, Fracion in Social Services
21.1066
0.33
94.08487
0.85
MSA (1 if in MSA)
-3.1262
-1.56
3.58418
1.88
Rural, Fraction of Population
-3.3613
-0.57
0.38196
0.08
Population Density
-0.0092
-4.80
-0.00086
-0.49
South
5.2860
2.24
West
-5.9376
-2.05
9.3410
2.90
Appalachia
27.56440
3.25
Black Belt
2.08400
0.32
Delta
24.80486
3.02
Rio Grande
25.68943
2.45
Earnings, Federal Government
Northeast
Number of Observations
F-Statistics
Prob > F
Root Mean Square Error
2749
1182
344.62
306.55
0
0
31.206
23.824
48
Table 5: Food Stamp Participation Rates, 2001, All States and Southern States Only
All States
(a)
Southern States
(b)
(c)
Coefficient
tstatistic
Coefficient
t-statistic
Welfare Cases
0.1430
4.70
0.2397
7.84
SSI Participation
Food Stamps, County
Administration
Food Stamps, Expanded
Categorical Eligibility
Food Stamps, Exempted Child
Support
Food Stamps, Employment &
Training Requirement
Food Stamps, Transitional
Benefits
1.2078
8.01
0.5899
(d)
(e)
(f)
t-statistic
Coefficient
tstatistic
0.1842
4.78
0.5352
12.53
0.5770
11.13
1.0244
5.58
4.39
0.5842
4.27
-0.0259
-0.19
0.2306
1.40
-0.5412
-1.16
-8.5674
-8.10
-8.4274
-5.81
-4.9921
-2.44
-3.4870
-1.22
8.7588
5.70
9.6700
3.96
-2.4351
-0.87
-1.3963
-0.30
8.1850
4.75
6.4761
3.34
0.6763
0.19
14.7619
1.92
-6.8000
-6.59
-6.3466
-5.13
-15.6610
-8.45
-8.7082
-1.16
-1.0418
-0.50
-1.4756
-0.70
1.5124
0.53
9.2373
2.17
-0.5725
-2.57
3.0365
4.08
0.8423
0.87
Food Stamps, Certification Time
Food Stamps, # of One Stop
Centers
Coefficient
Coefficient
tstatistic
Coefficient
tstatistic
Poverty, Fraction below 50%
240.3840
5.56
255.4176
5.57
327.7827
6.53
341.2535
6.17
295.8751
5.48
247.2220
2.87
Poverty, Fraction 50-100%
371.7568
7.17
458.4489
8.89
456.8955
8.30
500.0217
8.46
440.2525
7.18
452.7174
3.35
26.6125
0.44
10.9209
0.28
22.9467
0.52
46.6629
1.11
109.0783
2.77
23.8129
0.34
105.9682
2.35
81.6308
1.89
80.4111
1.69
28.6494
0.64
30.8404
0.72
37.7686
0.63
92.9164
2.78
125.1549
3.76
133.7202
3.67
108.8045
2.56
133.9664
3.11
-7.1328
-0.13
Income, Per Capita
0.0003
1.69
0.0002
1.31
0.0003
1.83
0.0003
1.09
0.0001
0.34
0.0004
1.12
Earnings (per job)
-0.0003
-1.95
-0.0001
-0.42
0.0000
-0.27
-0.0002
-0.97
-0.0001
-0.82
-0.0002
-1.15
272.3993
1.71
279.8144
2.15
322.1964
2.23
641.3864
4.16
673.9418
4.45
632.1376
2.63
6.8833
0.19
-34.0711
-0.90
-43.0085
-1.00
-41.4552
-0.77
-11.4642
-0.22
148.6027
1.72
-47.5161
-1.82
-70.4452
-3.26
-60.8276
-2.52
-13.4825
-0.49
-3.3326
-0.13
134.5862
3.02
African-American (Fraction)
0.1123
1.75
0.2000
3.26
0.1869
2.93
0.0160
0.24
-0.0260
-0.39
-0.2257
-1.92
Native American (Fraction)
0.3821
2.61
0.1494
1.14
0.1487
1.04
0.0958
0.64
-0.2265
-1.63
-1.1928
-1.81
Hispanic
7.7113
0.73
-10.8334
-1.02
-17.1602
-1.49
-58.8381
-4.56
-23.9554
-1.71
-171.2933
-3.35
-219.4831
-3.21
-202.6452
-2.97
-166.9425
-2.40
52.3575
0.70
-74.5646
-0.99
334.8912
2.24
Education, Fraction less than 9th
-11.5471
-0.47
34.4607
1.67
59.1839
2.63
94.2794
3.17
-1.5473
-0.05
115.4393
1.67
Education, Fraction>9 and <12
-41.1611
-0.51
-59.9196
-0.73
-22.0108
-0.46
-30.9209
-1.08
-83.6549
-2.33
124.2686
1.94
Poverty, Fraction, 100 - 150%
Unemployment rate, Female
Unemployment rate, Male
Age, Fraction under 5
Age, Fraction under 20
Age, Fraction over 64
Immigrants (Fraction)
49
All States
(a)
Southern States
(b)
(c)
Coefficient
tstatistic
Coefficient
t-statistic
83.2250
4.18
55.2461
4.51
58.0385
5.09
76.4061
-62.5346
-2.36
Earnings, Local Government
18.0073
Earnings, State Government
(d)
(e)
(f)
t-statistic
Coefficient
tstatistic
62.6795
4.39
62.2677
3.30
47.0120
2.57
-43.6773
-1.41
6.71
83.4967
6.97
110.4671
7.53
91.0511
6.56
75.7317
3.42
-44.9487
-2.34
-43.9126
-2.21
-49.7992
-2.59
-8.0784
-0.35
-42.8098
-1.13
2.06
23.7406
2.91
22.8741
2.60
10.1175
0.91
11.7420
1.09
-17.7750
-0.97
-36.2729
-0.85
-30.4167
-1.31
-28.4144
-1.14
14.9417
0.87
-14.1923
-0.84
53.4245
1.75
36.7817
2.92
43.7012
3.47
46.1437
3.55
54.7843
4.23
52.2407
4.06
23.4433
1.36
23.4607
1.03
30.9249
1.99
30.9170
1.71
-5.1318
-0.28
-7.8920
-0.42
-53.8114
-1.83
-40.1319
-0.38
24.7962
0.29
-85.8659
-0.90
-148.8584
-1.39
-115.4360
-1.16
-117.1185
-0.75
4.8859
0.05
79.6731
1.01
90.5260
1.00
271.1799
2.75
177.5694
1.84
364.6797
1.93
1.6077
1.54
0.8531
0.82
1.4454
1.29
4.1852
2.77
2.9893
2.07
2.0798
1.02
Rural, Fraction of Population
-7.8237
-2.63
-4.8031
-1.89
-3.5301
-1.27
-2.3989
-0.67
1.2606
0.37
4.7087
0.92
Population Density
-0.0024
-3.78
-0.0037
-4.61
-0.0011
-1.36
-0.0016
-0.80
-0.0017
-0.82
0.0001
0.02
South
1.6755
0.54
3.8103
1.81
1.3230
0.54
West
-8.1540
-4.06
-2.7213
-1.13
-0.6352
-0.24
Northeast
-7.5882
-3.31
-8.5310
-3.58
-9.2435
-3.76
Appalachia
27.2102
5.10
21.4311
4.00
26.4525
2.54
Black Belt
44.5386
4.60
34.3497
3.71
52.2998
3.86
Delta
22.6953
2.85
26.0126
3.78
17.8028
2.40
Rio Grande
16.5654
1.65
9.9654
1.18
Education, High School
Graduate
Mobility, Same county 5 years
age
Mobility, Same State
Earnings, Federal Government
Earnings, Fraction in Health
Services
Earnings, Fraction in Legal
Services
Earnings, Fraction in Social
Services
MSA (1 if in MSA)
Number of Observations
F-Statistics
Prob > F
Root Mean Square Error
Coefficient
Coefficient
tstatistic
Coefficient
2712
2712
2405
1312
1312
899
336.89
293.79
252.37
276.89
199.54
102.8
0
0
0
0
0
0
27.944
26.836
30.547
22.714
25.724
33.837
50
tstatistic
Table 6: Change in Food Stamp Participation, 1995 to 2001, All States and Southern States
All States
(a)
Welfare Cases (1995)
(b)
Coefficient
tstatistic
-0.0689
-3.88
Change in Welfare Cases, 1995 to 2001
SSI Participation (1995)
Coefficient
0.1051
-0.2784
Southern States
(c)
tstatistic
(e)
Coefficient
tstatistic
Coefficient
tstatistic
-0.0406
-1.08
-0.1126
-4.01
-0.0074
-0.14
-0.6679
-4.89
3.01
-2.65
Change in SSI Cases, 1995 to 2001
(d)
-0.3225
-1.02
-1.1613
-1.33
Coefficient
0.2130
-0.3971
(f)
tstatistic
4.23
-1.73
Coefficient
tstatistic
0.1603
1.39
0.3758
2.67
-0.6230
-2.20
1.3936
1.11
0.5871
0.73
Food Stamps, County Administration
-5.7435
-5.90
-5.7243
-5.69
-6.6947
-6.19
1.2342
0.49
0.3713
0.13
-4.5833
-1.24
Food Stamps, Expanded Categorical Eligibility
-0.3725
-0.32
0.7980
0.67
-1.9805
-1.60
-1.1823
-0.39
1.2431
0.29
1.4919
0.40
5.9397
4.00
6.2464
3.63
3.8306
2.44
-4.8689
-1.26
-4.3867
-0.98
-3.7501
-0.78
-4.5254
-4.96
-4.6687
-4.87
-4.8768
-5.02
-30.2018
-11.30
-25.2432
-8.48
-25.4338
-8.95
1.6542
1.37
0.9541
0.47
6.3552
4.14
-15.8290
-5.16
-31.3097
-5.08
-24.7819
-3.93
Poverty, Fraction below 50%
52.1822
1.55
3.9838
0.12
76.8263
2.01
116.7610
2.40
30.4442
0.63
52.5643
0.90
Poverty, Fraction 50-100%
21.0537
0.59
-49.0050
-1.49
65.3406
1.61
12.3593
0.19
-78.2991
-1.28
1.9321
0.02
Poverty, Fraction, 100 - 150%
-7.8562
-0.33
5.5437
0.22
-44.3149
-1.28
33.7187
0.87
122.5807
1.62
74.1628
1.31
Unemployment rate, Female (95)
-154.6692
-2.59
-148.6820
-2.36
-84.2289
-1.31
-120.9283
-1.54
-254.4630
-2.29
-148.6576
-1.31
Unemployment rate, Female (01)
163.9946
3.28
146.7776
2.83
102.3701
1.87
157.6461
2.43
235.4164
2.91
162.1234
1.88
Unemployment rate, Male (95)
-260.1733
-4.75
-371.8563
-6.43
-256.3615
-4.27
-131.8792
-1.07
-152.2742
-1.07
-162.5736
-0.96
Unemployment rate, Male (01)
109.1617
2.21
175.7386
3.19
121.4654
2.07
27.7695
0.30
67.6589
0.64
49.7400
0.42
Age, Fraction under 5
-227.0019
-1.97
-433.0520
-3.06
-331.4434
-3.29
-443.8907
-2.94
-283.4601
-1.71
-355.1331
-2.05
Age, Fraction under 20
-42.7123
-1.22
5.5374
0.15
-62.7175
-1.95
48.1330
0.95
127.8949
1.78
75.1785
1.07
Age, Fraction over 64
-89.6823
-6.28
-92.6294
-5.71
-102.0662
-5.48
-45.7701
-1.87
-34.2807
-1.01
-64.3896
-1.55
African-American (Fraction)
-28.6581
-5.03
-29.5370
-4.50
-31.8244
-2.74
-25.8545
-3.26
-21.6869
-1.63
-17.0309
-1.83
Native American (Fraction)
69.0865
4.84
77.7394
5.33
54.4443
2.45
-74.9313
-0.94
51.6423
0.68
10.3552
0.14
-70.3467
-5.29
-55.0985
-3.86
-84.8372
-6.69
-78.0381
-5.33
-72.3041
-5.50
-99.6735
-5.83
26.2363
1.51
.73167
0.05
72.7811
4.05
10.1309
0.26
-62.4989
-1.61
16.8365
0.36
-30.5017
-2.06
-31.6984
-1.70
18.7007
0.70
-95.3592
-3.39
-217.3672
-4.31
-157.6075
-3.42
Food Stamps, Exempted Child Support
Food Stamps, Employment & Training Requirement
Food Stamps, Transitional Benefits
Hispanic (Fraction)
Education, Fraction less than 9th
Education, Fraction>9 and <12
51
All States
(a)
Southern States
(b)
Coefficient
Coefficient
Coefficient
tstatistic
-0.92
-31.7155
-2.97
-64.3870
-2.93
-30.5636
-1.23
-75.7146
-2.63
80.8145
7.55
83.3845
6.13
87.2466
5.79
80.2637
3.67
101.0238
4.71
-3.75
-72.1448
-4.70
-69.4622
-4.57
-22.0662
-0.94
30.6103
1.16
-8.7381
-0.26
-6.4112
-2.25
-8.3096
-2.14
-7.4408
-2.15
-12.0714
-2.78
-12.6134
-1.82
-12.6246
-2.28
Population Density
0.0020
2.12
0.0020
1.64
0.0004
0.40
0.0009
0.77
0.0053
2.77
0.0031
1.41
MSA (1 if in MSA)
-1.8036
-1.66
-0.5549
-0.47
-2.7923
-2.22
-4.2701
-2.22
-4.0412
-1.73
-3.4050
-1.52
South
-4.6306
-3.04
-5.7798
-3.61
-5.6955
-2.82
West
0.3722
0.23
0.3010
0.17
-1.8771
-1.05
-6.5745
-4.33
-5.8871
-3.51
-5.7178
-2.71
Appalachia
9.6990
1.66
-1.3529
-0.15
6.1083
0.69
Black Belt
10.4514
1.66
8.6869
1.24
18.0964
2.10
Delta
-5.3592
-0.63
-1.7701
-0.15
-3.8285
-0.37
-14.5963
-1.13
-9.8214
-0.72
-12.3749
-1.04
Northeast
-9.9782
74.2310
7.78
-50.2954
(f)
Coefficient
Rural, Fraction of Population
-1.34
(e)
tstatistic
Mobility, Same State
Coefficient
tstatistic
(d)
tstatistic
Mobility, Same county 5 years age
-13.7511
(c)
tstatistic
Education High School Graduate
Coefficient
tstatistic
Rio Grande
Number of Observations
2453
2435
2435
1081
1080
1080
F-Statistics
54.62
51.06
48.71
28.42
22.86
5.19
18.448
21.587
28.767
19.087
44.706
116.18
Root Mean Square Error
52
Table 7: Percentage Change in Food Stamp Participation, 1995 to 2001, All States and Southern States
All States
(a)
Welfare Cases (1995)
(b)
Coefficient
tstatistic
0.0002
1.17
Change in Welfare Cases, 1995 to 2001 (%)
SSI Participation (1995)
Coefficient
-0.0011
-0.0030
Southern States
(c)
tstatistic
-3.40
-2.54
Change in SSI Cases, 1995 to 2001 (%)
(d)
(e)
Coefficient
tstatistic
Coefficient
tstatistic
0.0006
2.23
-0.0005
-2.54
-0.0013
-3.23
-0.0068
-2.94
-0.0858
-1.23
-0.1461
-1.25
Coefficient
-0.0009
0.0052
(f)
tstatistic
-3.12
2.47
Coefficient
tstatistic
-0.0019
-2.18
-0.0005
-0.70
-0.0001
-0.02
0.0149
0.55
0.1856
1.27
Food Stamps, County Administration
0.0264
1.59
-0.0791
-6.69
-0.0931
-5.92
-0.0279
-1.82
-0.0480
-2.75
0.0717
1.14
Food Stamps, Expanded Categorical Eligibility
0.0259
0.94
0.0302
2.43
0.0044
0.26
-0.0170
-0.70
-0.0404
-1.80
0.0490
0.77
Food Stamps, Exempted Child Support
0.0080
0.34
-0.0095
-0.37
-0.0198
-0.66
-0.1028
-4.80
-0.0601
-2.85
-0.1138
-3.10
Food Stamps, Employment & Training Requirement
0.1178
2.48
-0.0154
-1.05
-0.0101
-0.60
-0.1832
-11.26
-0.1788
-9.84
-0.1619
-4.13
Food Stamps, Transitional Benefits
0.2788
0.78
0.1540
2.66
0.2001
2.84
-0.0856
-4.42
-0.0217
-0.68
-0.3107
-1.93
Poverty, Fraction below 50%
2.8794
3.06
-0.1416
-0.36
0.2873
0.65
0.6014
1.96
0.6288
2.13
2.3969
1.35
Poverty, Fraction 50-100%
0.8149
2.62
2.0202
2.46
3.1713
2.80
1.7114
3.23
0.8490
2.98
1.3023
1.98
Poverty, Fraction, 100 - 150%
1.5208
0.98
1.3352
4.18
0.9965
2.59
1.3208
5.38
1.3157
4.86
1.4515
1.80
Unemployment rate, Female (95)
-0.3967
-0.34
0.1113
0.11
0.7868
0.66
-0.4191
-0.74
-1.2520
-2.34
-3.1767
-2.58
Unemployment rate, Female (01)
-2.5789
-2.27
0.3328
0.59
-0.1474
-0.21
0.7954
1.66
1.3168
3.51
2.6185
3.24
Unemployment rate, Male (95)
0.6630
0.53
-2.1026
-3.97
-1.0457
-1.69
-0.2043
-0.27
-0.4651
-0.86
2.1599
1.15
Unemployment rate, Male (01)
-3.2963
-1.40
0.4206
0.50
-0.2375
-0.24
-0.1318
-0.26
-0.0629
-0.15
-1.3159
-1.01
Age, Fraction under 5
-0.4300
-0.46
-5.8677
-3.80
-4.5256
-2.73
-4.9656
-3.00
-4.5704
-3.82
-3.4857
-1.49
Age, Fraction under 20
-0.5924
-3.10
0.6819
1.57
0.1739
0.33
1.1936
2.62
1.0353
2.24
-0.7086
-0.38
Age, Fraction over 64
-0.0719
-1.59
-0.4247
-1.82
-0.4848
-1.74
-0.2249
-1.25
-0.3269
-1.04
-1.3451
-1.24
African-American (Fraction)
0.2465
2.55
-0.0015
-0.03
0.0648
0.94
0.0003
0.01
-0.0853
-2.12
-0.0418
-0.50
Native American (Fraction)
-0.4455
-5.20
0.4633
4.65
0.1204
0.91
-0.6144
-1.18
-0.1581
-0.39
0.2031
0.29
0.0099
0.04
-0.2928
-4.96
-0.6573
-3.99
-0.2122
-2.16
-0.0743
-1.43
-0.1514
-1.08
-0.2449
-0.71
-0.1562
-0.72
0.5162
2.12
-0.1247
-0.56
-0.3558
-2.23
-0.6977
-1.35
Hispanic (Fraction)
Education, Fraction less than 9th
53
Education, Fraction>9 and <12
0.1046
0.98
0.1564
0.54
0.3877
1.00
-0.5194
-2.21
-0.3858
-1.62
-1.7009
-3.36
Education, High School Graduate
0.8583
6.51
0.1825
1.69
0.0695
0.44
-0.0394
-0.28
0.1270
0.97
-0.0155
-0.03
Mobility, Same county 5 years age
1.0125
8.86
0.7152
7.72
0.7309
5.33
0.6988
7.16
0.6293
6.32
1.2596
2.49
54
All States
(a)
Southern States
(b)
Coefficient
tstatistic
Mobility, Same State
-0.8772
Rural, Fraction of Population
(c)
Coefficient
tstatistic
-3.71
-0.8270
-0.0052
-0.12
Population Density
0.0000
MSA (1 if in MSA)
(d)
Coefficient
tstatistic
-4.05
-0.7905
-0.0865
-2.87
-1.82
0.0000
-0.0126
-0.73
South
-0.0583
West
Northeast
(e)
Coefficient
tstatistic
-3.48
-0.0235
-0.0730
-2.04
-0.42
0.0000
0.0041
0.23
-2.29
-0.0915
-0.0574
-1.25
-0.1466
-4.18
(f)
Coefficient
tstatistic
Coefficient
tstatistic
-0.13
-0.1670
-0.84
-0.3075
-0.49
-0.0876
-2.64
-0.0653
-2.59
-0.1383
-2.66
-2.05
0.0000
1.28
0.0000
-1.12
-0.0001
-0.74
-0.0102
-0.56
-0.0155
-1.22
-0.0380
-2.88
-0.0323
-1.42
-2.96
-0.0558
-1.90
-0.0979
-2.22
-0.1076
-2.26
-0.1776
-3.96
-0.1723
-3.88
Appalachia
0.0430
1.46
-0.0269
-1.16
0.0737
1.04
Black Belt
-0.0335
-0.98
-0.0558
-1.74
0.0258
0.25
Delta
-0.0140
-0.41
-0.0145
-0.50
0.1108
0.90
Rio Grande
-0.0047
-0.09
0.0050
0.11
0.0402
0.42
Number of Observations
2453
2419
2419
1081
1076
1076
F-Statistics
32.17
33.54
22.16
39.01
40.8
17.67
0.33875
0.34895
0.42808
0.1396
0.13301
0.58257
Root Mean Square Error
55