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Before comparing and contrasting the status of welfare leavers across the leaver studies reviewed in this synthesis report, it is important to understand the environment in which families make their decisions to leave welfare. Indeed, the status of welfare leavers is likely affected by the welfare policies states have adopted, the economic opportunities prevailing in the states, and even the characteristics of the recipients themselves. Because there are so many factors contributing to the well-being of leavers, it is difficult to ascribe differences in outcomes across studies to any specific difference in context. In addition, in this descriptive synthesis report, all of these contextual differences cannot be taken into account simultaneously. However, these differences may be noted as they come to bear on comparisons across studies.
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Under TANF block grants, states have substantial flexibility in determining the length of time families can receive cash assistance (time limits), the penalties for not complying with program rules (sanctions), and the generosity of cash grants, as well as how benefits are reduced as a family moves from welfare to work. Differences in state policy choices may well affect the rate at which families leave TANF, the employment status and material well-being of these families, and their use of government aid after leaving the TANF program.
Table II.1 (appearing at the end of this chapter) shows the time limit and sanction policies that prevailed in 1997 in the states in which the ASPE-funded leaver studies were conducted. We focus on 1997 because this is when states began implementing their TANF programs, and most of the studies provide some data on families that exited welfare just prior to or during that year.
State |
Time Limit | Initial Sanction | Maximum Sanction |
|---|---|---|---|
| Arizona | 24 out of 60 months | Adult portion of benefit for one month or until compliance, whichever is longer | Adult portion of benefit for six months or until compliance, whichever is longer |
| District of Columbia | 60 months | Adult portion of benefit for one month or until compliance, whichever is longer | Adult portion of benefit for six months or until compliance, whichever is longer |
| Florida | 48 months and 24 out of 60 months or 36 out of 72 months1 | Entire benefit until in compliance for 10 working days | Entire benefit for three months or until in compliance for 10 working days, whichever is longer |
| Georgia | 48 months | 25% until compliance | Entire Benefit permanently |
| Illinois | 60 months | 50% until compliance | Entire Benefit for three months or until compliance, whichever is longer |
| Iowa | 60 months | Adult portion of benefit for three months | Entire benefit for six months |
| Massachusetts | 24 out of 60 months | Written warning | Entire benefit until in compliance for two weeks |
| Missouri | 60 months | Adult portion of benefit until compliance | Adult portion of benefit for six months or until compliance, whichever is longer |
| New York | 60 months | Adult portion of benefit until compliance | Adult portion of benefit for six months or until compliance, whichever is longer |
| South Carolina | 24 out of 60 months | Case is closed. Unit must reapply and comply for one month | Case is closed. Unit must reapply and comply for one month |
| Washington | 60 months | Adult portion of benefit until compliance | Adult portion of benefit for six months or until compliance, whichever is longer |
| Wisconsin | 60 months | Minimum wage times the number of hours of non-participation until compliance | Entire benefit and must reapply. |
| Cuyahoga Co. | 36 out of 60 months | Adult portion of benefit for one month | Entire benefit for six months. |
| Los Angeles Co. | No limit | Adult portion of benefit until compliance | Adult Portion of benefit for six months or until compliance, whichever is longer |
| San Mateo Co. | No limit | Adult portion of benefit until compliance | Adult Portion of benefit for six months or until compliance, whichever is longer |
| 1The 24 out of 60 month limit applies to non-exempt
recipients who have received less than 36 months of assistance during the
previous 60 months and are 1). over age 24 or 2). under age 24 with a high
school diploma/ GED. The 36 out of 72 month limit applies to non-exempt
recipients who 1). have received benefits for 36 of the previous 72 months
or 2). are under age 24, have not completed high school/ GED, are not enrolled
in a high school equivalency program, and have little or no work
experience. Sources: See Appendix B for a complete listing of the leavers studies referenced. Data reported from Urban Institute's Welfare Rules Database. All data are reported as of 7/97. |
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First, consider time limits. Families subject to shorter time limits may feel pressure to leave welfare sooner than families that are years away from exhausting their benefits. Also, leavers who have nearly exhausted their benefits may be more reluctant to return.
Out of the fifteen studies, seven are based in locations that as of 1997 allowed welfare recipients to receive benefits for the federally-imposed maximum of 60 months (5 years) and placed no intermittent time limits on receipt (see Table II.1). Florida and Georgia have a shorter lifetime limit of 48 months. And Arizona, Florida, Georgia, Massachusetts, South Carolina, and Cuyahoga county all have intermediate time limits, not only restricting the total number of months a family can receive benefits but also prohibiting a family from receiving their lifetime allotment over a single time period.7 For example, in Massachusetts, families can only receive benefits for 24 months in any 60 month period. Because of these intermediate time limits, both the Massachusetts and South Carolina leaver studies can assess the status of leavers that reached their initial time limits. Finally, California, the site of the Bay Area8 and Los Angeles county leaver studies, had no time limit in 1997; however, California imposed the standard 60 month lifetime limit retroactively in 1998 (Welfare Rules Database—WRD).
Next, consider states’ sanction policies. In general, states have imposed tiered sanctions, beginning with less severe sanctions at first and escalating penalties for
repeated instances of non-compliance. Note that leavers who were sanctioned off the rolls may be less "job-ready" then other leavers. Further, they may return to TANF at higher rates than non-sanctioned leavers upon coming back into compliance with program requirements.9
Table II.1also shows the initial and maximum sanction in each of the fourteen states covered by the leaver studies.10 Generally, for the first instance of non-compliance with program rules, a family’s TANF benefit is either reduced by a set percentage (usually 25 percent) or the adult portion of the benefit is eliminated (effectively turning a 3 person unit into a two person unit, for example). The District of Columbia, Illinois, Missouri, New York, Washington, and California restore benefits once a family complies with program rules while other states specify a minimum amount of time the family must make do with lower benefits even after it has come into compliance. For example, Iowa’s initial sanction removes the adult portion of a family’s benefit for three months regardless of whether the family quickly complies with program rules. Two states, however, have substantially stronger initial sanctions. In Florida, the family’s entire benefit is eliminated until the family is in compliance with program requirements for 10 working days. And in South Carolina, the case is closed, and the family must reapply for benefits and comply with program rules for one month.
Focusing on the maximum sanction, Table II.1 shows that ten of the ASPE leaver studies are based in states that impose full-family sanctions, removing the adult unit head and the children from the TANF rolls. Georgia and Wisconsin not only impose full-family sanctions, but their maximum sanctions are also permanent sanctions; families that reach this point can never return to cash assistance in these two states. In Iowa and Ohio (Cuyahoga County), the full family sanction lasts 6 months, while Arizona, Florida, Illinois, Massachusetts, and South Carolina impose shorter sanctions for families that begin to comply with program rules. DC, Missouri, New York, Washington, and California (site of the LA and Bay Area studies) do not use full family sanctions.
The generosity of a state's welfare program also affects its leavers' outcomes. For example, recipients in states with higher basic benefits and higher earnings disregards can remain on the rolls while working for longer than families in less generous states. As a result, leavers in more generous states may have higher incomes than leavers from less generous states in the months following their TANF exits simply because those with lower incomes do not leave the rolls. On the other hand, leavers may be more likely to return to welfare if the program offers generous assistance.
Table II.2 shows the 1997 maximum TANF benefit a family of three could receive in the 14 states covered by the ASPE leaver studies, as well as earned income disregards in each state. Massachusetts clearly has the most generous policies, with a high maximum benefit and large earnings disregards.11 California, New York, Washington, and Wisconsin all have high benefit levels (in excess of $500 per month for a family of three) with the standard earnings disregard (the first $120 of earnings and one third of the remainder are disregarded). Ohio (Cuyahoga County) and Florida have modest benefits but generous earnings disregards.12
| State | Maximum Benefit for a Family of 3 ($) | Earned Income Disregards | Working at $7 an Hour 20 Hours/Week | |
|---|---|---|---|---|
| TANF Benefit(1) ($) | Total Income(2) ($) | |||
| Arizona | 347 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 26 | 1,096 |
| District of Columbia | 379 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 58 | 1,133 |
| Florida | 303 | $200 and 50% of the remainder | 102 | 1,150 |
| Georgia | 280 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 103 | 1,135 |
| Illinois | 377 | 66.7% | 178 | 1,197 |
| Iowa | 426 | 20% and 50% | 185 | 1,176 |
| Massachusetts | 565 | $120 and 50% of the remainder | 324 | 1,335 |
| Missouri | 292 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 0 | 1,053 |
| New York | 577 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 256 | 1,283 |
| South Carolina | 200 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 200 | 1,189 |
| Washington | 546 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 225 | 1,190 |
| Wisconsin | 518 | $120 and 33.3% first 4 consecutive months, $120 next 8 months, $90 thereafter | 197 | 1,163 |
| Cuyahoga Co. | 341 | $250 and 50% of the remainder for first 12 months, then $90 thereafter | 165 | 1,169 |
| Los Angeles Co. | 565 | $120 and 33.3% | 244 | 1,274 |
| San Mateo Co. | 565 | $120 and 33.3% | 244 | 1,274 |
| 1 For benefit computation, information
on payment standards (not shown) is also required. 2 Total Income includes earnings of $602 ($7 an hour working 20 hours per week), TANF benefit, Food Stamp benefit, EITC and subtracts FICA tax. At this wage level there is no federal tax liability and we are assuming no state tax liability. |
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The last two columns of Table II.2 show how benefits and disregards interact as a single mother with two children on TANF begins to earn money through a part-time job. In Missouri, a family in which the mother works for 20 hours a week at $7.00 an hour would no longer be eligible for TANF. In Arizona, DC, Florida, and Georgia, monthly cash assistance benefits would be around $100 or less for such a family. The state that pays the highest TANF benefit to this prototypical family is Massachusetts at $324.
Because the family is earning $602 a month from the mother’s job, they would be eligible to receive $241 through the federal Earned Income Tax Credit 13(per month) and would owe $46 per month in FICA taxes. In addition, while this family’s TANF benefits phase out, it is still eligible for food stamps. This reduces some of the variation in total income between states as food stamp benefit levels are computed using the same federal formula in all states; thus, families in low TANF benefit states may receive greater food stamp benefits than otherwise similar families in high TANF benefit states. In 9 out of the 14 states, the monthly total income of this prototypical family making the transition from welfare to work falls between $1,100 and $1,200 (excluding state taxes and credits). This family’s total income would vary from a low of $1,053 in Missouri to a high of $1,335 in Massachusetts. Note that in Missouri, this family would have left TANF entirely, while in Massachusetts, it would still be receiving benefits. Thus, one might expect to see higher levels of hardship among leavers in Missouri than in Massachusetts.
While every aspect of states’ TANF policies (for example, work requirements and diversion policies have been ignored), are not reviewed here, some general observations about the policy context in which the ASPE leaver studies are based can be made. For example, California (LA and Bay Area studies), New York, and Washington generally pursued policies that would be expected to produce lower exit rates from welfare but higher incomes for those families that do leave. Conversely, states with lower benefits and more severe sanctions such as Arizona and Georgia may move families off the welfare rolls faster but their leavers may have lower total incomes. Finally, other studies are based in states that pursue a mix of policies that are likely to have offsetting effects on the outcomes of leavers—for example, Massachusetts and Cuyahoga County have strict time limits and full family sanctions but very generous earnings disregards.
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One would expect that when jobs are plentiful and wages are high, welfare leavers will generally fare better than during lean economic times. Table II.3 shows the 1997 unemployment rates and median incomes in the states in which the leaver studies we review were conducted. Note that these are state averages and some of the leaver studies only cover sub-state geographic areas. For example, the economic conditions in the state of Ohio may not necessarily reflect the conditions in one of its urban centers, Cuyahoga County.
| State | Unemployment Rate (%) | Median Income ($) |
|---|---|---|
| Arizona | 5.1 | 35,503 |
| District of Columbia | 8.9 | 32,382 |
| Florida | 4.3 | 32,455 |
| Georgia | 4.9 | 35,911 |
| Illinois | 5.2 | 40,094 |
| Iowa | 3.5 | 37,407 |
| Massachusetts | 5.4 | 40,624 |
| Missouri | 4.8 | 36,676 |
| New York | 6.3 | 34,783 |
| South Carolina | 5.1 | 30,616 |
| Washington | 6.4 | 37,458 |
| Wisconsin | 3.7 | 43,132 |
| Cuyahoga Co.1 | 4.8 | 36,798 |
| Los Angeles Co.1 | 7.8 | 38,976 |
| San Mateo Co.1 | 7.8 | 38,976 |
| United States | 5.6 | 36,244 |
| 1 Unemployment rate is given for the entire
state. Source: "Interpreting TANF Leaver Studies: Comparing ASPE Grantee States to the Nation as a Whole." Mathematica Policy Research, March 27, 2000. |
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Overall, Wisconsin had both the lowest unemployment rate (3.7 percent) and the highest median income ($43,132) in 1997. In contrast, the District of Columbia had both a relatively high unemployment rate (8.9 percent) and low median income ($32,382). Thus, if the welfare rolls are tied to macroeconomic conditions, one might expect that DC’s leavers may struggle more than Wisconsin’s leavers or be less likely to leave in the first place. For some states, the potential beneficial impacts of low unemployment are offset by low incomes while others have both high incomes and high unemployment. For example, Florida had a low unemployment rate at 4.3 percent, but its median income is also among the lowest at $32,455. And Washington experienced relatively high unemployment (6.4 percent) but its median income was above average ($37,458). Of course, the cost of living also differs from state to state. Thus, it is clear that economic conditions vary considerably across the sites conducting the leaver studies reviewed in this synthesis.
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While welfare caseloads declined throughout the US during the 1990s, the magnitude of the decline varied from state to state. The average leaver from states with large caseload declines may come from “deeper” in the caseload and have more barriers to overcome in moving to work than the average leaver from other states. As such, these leavers may have less success in the labor market, face greater hardships, and may be more likely to return to welfare. Note, however, that recent research suggests that leavers are not becoming more disadvantaged over time (Loprest 2001).
Figure II.1 shows caseload declines across the fourteen states hosting leaver studies. The vertical line represents the date of TANF implementation, and the shaded areas denote the cohorts examined in the leaver studies. Caseload declines between
Figure II.1:
AFDC/TANF Caseload Changes in Welfare Leaver Study Sites: 1994-2000
Note: Shaded areas denote the cohorts of TANF leavers that were followed in the studies. August 1996 and December 1999 range from 30 percent in the District of Columbia to 68 percent in Florida. Caseloads fell by more than 50 percent in Georgia, Illinois, Ohio, South Carolina, and Wisconsin. In addition to DC, caseloads declined by less than 40 percent in California, Iowa, and New York.
Differences in the personal characteristics of welfare recipients and welfare leavers also must be considered when comparing findings across leaver studies. Indeed, part of any difference in outcomes across sites may be due to differences among leavers themselves. Further, states likely structure their welfare policies with their welfare populations in mind—for example, a state with a high proportion of high school drop outs may emphasize work readiness programs—and this too may affect the status of leavers.
Table II.4 compares the characteristics of leavers across 12 studies which report such information. The table focuses on leavers’ ages, race/ethnicity, marital statuses, the number of children they have, and their educational attainment. Not all studies provide data on each of these characteristics, and they do not all report them in the same way. For example, Iowa and Massachusetts report the average age of leavers while other studies report a distribution of leavers’ ages. These differences make direct comparisons more challenging.
State/Study |
Age of Unit Head1 | Race/Ethnicity of Unit Head | ||||||
|---|---|---|---|---|---|---|---|---|
| <=20 | 21-30 | 31-40 | 40+ | White | Black | Other2 | Hispanic | |
Arizona |
7 | 51 | 38a | 4 | 42 | 10 | 14 | 35 |
District of Columbia |
4 | 44 | 36 | 16 | 1 | 97 | 1 | 2 |
Florida |
33c |
42 | 40 | 17 | ||||
Georgia # |
34b | 41b | 21b | 4b | 31 | 67 | 2 | |
Illinois # |
7 | 49 | 30 | 14 | 34 | 56 | 1 | 9 |
Iowa * |
30c |
81 | ||||||
Massachusetts # |
33c |
60 | 20 | 20 | 29 8 | |||
Missouri |
11 | 46 | 31 | 12 | 63 | 35 | 2 | 1 |
South Carolina * |
20d | 25d | 38 | 17 | 22 | 78 | ||
Washington * |
3 | 46 | 35 | 16 | 70 | 8 | 23 | 13 8 |
California Bay Area * |
14f | 33f | 35 | 18 | 28 | 12 | 16 | 44 |
Cuyahoga Co. |
6 | 52 | 31 | 12 | 23 | 70 | 2 | 6 |
State/Study |
Marital Status | Number of Children | Education | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Never Married | Married | D/W/S3 | 0-1 4 | 2 | 3+ | <HS | HS | HS+ | |
Arizona |
51 | 12 | 37 | 44 | 41 | 11.2 5 | |||
District of Columbia |
87 | 5 | 9 | 50 | 29 | 22 | |||
Florida |
2 6 | ||||||||
Georgia # |
61 | 12 | 23 5 | 33 | 33 | 35 | 22 | 59 | 19 |
Illinois # |
65 | 8 | 27 | 52 | 28 | 20 | 42 7 | 44 7 | 15 7 |
Iowa * |
48 | 15 | 26 | ||||||
Massachusetts # |
59 | 14 | 27 | 35 | 31 | 35 | 27 | 40 | 33 |
Missouri |
51 | 30 | 19 | 39 | 47 | 10 5 | |||
South Carolina * |
40 | 30 | 30 | 44 | 40 | 16 | |||
Washington * |
15 | 2 6 | 29 | 38 9 | 33 | ||||
Bay Area * |
10 | 49 | 30 | 21 | 48 | 26 | 26 | ||
Cuyahoga Co. |
45 | 32 | 24 | ||||||
1Age breakdowns differ from headings as follows: |
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A priori, it is difficult to anticipate whether younger leavers will, on average, fare better or worse than older leavers. While younger leavers probably have fewer children and likely have shorter spells of receipt prior to exit than older leavers, they also probably have younger children and less work experience. Six of the studies under review report the proportion of leavers age 20 and younger. The share of leavers who are very young ranges from a low of 3 in Washington to a high of 11 percent in Missouri. If we consider data regarding the under 30 group, we can include the South Carolina and San Mateo county studies. In four studies (Arizona, Cuyahoga county, Illinois, and Missouri ) well over half of all leavers are 30 or younger; in DC, the Bay Area, South Carolina, and Washington, less than half of leavers are under age 30.
It is also difficult to anticipate how race/ethnic differences between may affect leavers’ outcomes because race is only one of many differences among the study areas' TANF caseloads and local population bases. In the District of Columbia, virtually all leavers are black, which is not surprising given the demographic make-up of the city and its caseload. The proportion of leavers who are black ranges from a low of 8 percent in Washington to a high of 97 percent in DC. The share of leavers who are Hispanic ranges from 1 percent in Missouri to 44 percent in the Bay Area. The Bay Area also has a very high proportion (16 percent) of “others”. Although the majority of "others" in the Bay Area study are Vietnamese, the "other" races and ethnicities may include Asian and Pacific Islanders and Native Americans.
Differences in marital status, number of children, and education all have a stronger theoretical link than race or age to the outcomes of welfare leavers. For example, married or previously married leavers may well have access to more sources of support (for example, child support) than never married leavers. Table II.4 shows that among the 6 leaver studies reporting this information, the share of leavers who are never married ranges from 51 percent in Arizona to 87 percent in DC.
Leavers with more children may have a harder time balancing work and child rearing than other leavers. We see that the share of leavers with one child or less ranges from about one in three in Georgia and Massachusetts to about one half in DC, Illinois and Missouri.14 Conversely, Georgia and Massachusetts are the two study sites with highest proportions of leavers with three or more children, again, about one in three. Missouri has the lowest proportion of leavers with three or more children (19 percent).
Finally, leavers with higher levels of educational attainment should have an easier time finding, keeping, and advancing in jobs than less educated leavers. In four study sites, over 40 percent of leavers had failed to complete high school: Arizona, Illinois, South Carolina, and the California Bay Area. In Massachusetts and Wisconsin, leavers tend to have more education, with about one in three having some schooling beyond high school.
Overall, there are some potentially important differences across leavers in the various ASPE-funded studies; however, these differences may have offsetting effects on outcomes. For example, Massachusetts’ leavers are more educated on average than other leavers but they also tend to have more children, and Illinois’ leavers are less educated but tend to have fewer children.
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Welfare policies, economic conditions, and the characteristics of leavers themselves all likely affect leavers’ post-TANF experiences. However, after reviewing the range of differences across the 14 sites for these ASPE-funded leaver studies, it is difficult to derive any simple “rules of thumb” to aid in comparing findings across studies. The varied policies pursued by the states in which these leaver studies are conducted likely have offsetting effects on leavers’ outcomes. Further, while some states had unambiguously good economies (low unemployment and high incomes) many states had more mixed conditions. And leavers themselves often have a mixed set of characteristics, some of which should lead to higher levels of employment and well-being after exit while others should lead to lower levels. Thus, it is difficult to ascribe differences in average outcomes across leaver studies to observable differences between study locations. However, understanding these contextual differences may be particularly important when comparing specific outcomes for sub-groups of leavers.
7In Arizona, after a family has exhausted its
24 month allotment, the head is removed from the assistance unit, but the
children continue on as a child-only unit.
8The Bay Area Study comprises Santa Clara, Santa
Cruz, and San Mateo counties.
9For example, Arizona explicitly compares the
experience of sanctioned and non-sanctioned leavers and finds that sanctioned
leavers are more likely to return to welfare than non-sanctioned leavers
(40 v. 33 percent).
10The states conducting leaver studies reviewed
here tend to have less severe sanction policies than other states.
11Earnings disregards affect TANF benefit
computations. A certain portion of a family's earnings is disregarded for
the purposes of computing TANF benefits. States with higher earnings disregards
reduce TANF benefits more slowly as earned income rises.
12The standard of living in a state may affect
the generosity of its welfare benefits.
13This assumes that the family has no income
other than earnings and the mother continues to work at the same rate for
all 12 months of the year.
14A family with no children can receive welfare
if, for example, the woman is pregnant.
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