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Office of the Press Secretary

For Immediate Release August 3, 1999
                     The Effects of Welfare Policy 
            and the Economic Expansion on Welfare Caseloads: 
                                An Update

August 3, 1999

A Report by the Council of Economic Advisers

This study could not have been completed without the generous assistance of the Department of Health and Human Services in providing data and program information.

                 The Effects of Welfare Policy and the
           Economic Expansion on Welfare Caseloads: An Update

                             Executive Summary

This study investigates the causes behind recent changes in welfare caseloads, updating a 1997 CEA report of caseload change.

The large sustained declines in caseloads provide one piece of evidence about the effectiveness of welfare reform efforts. However, there are multiple indicators of the impact of welfare reform, including changes in work and earnings among welfare leavers, in marriage rates and out-of-wedlock pregnancies, and in poverty rates. The Clinton Administration is collecting and tracking information on all of these measures in order to fully assess the impact of welfare reform.

                 The Effects of Welfare Policy and the
           Economic Expansion on Welfare Caseloads: An Update

                Objective of Study & Summary of Findings

From the start of the Clinton Administration to March 1999, the number of people receiving welfare declined by 6.8 million. In 31 states the caseload is less than half of what it was when President Clinton took office. Not since 1967 has such a small share of the population received welfare. Not only have the declines been large, they have also been widespread and continuous (Table 1). Between 1993 and 1998 (the last year of data analyzed in this study), all 50 states and the District of Columbia experienced double-digit percent reductions in welfare participation, and in most states the declines were unprecedented. Although a substantial share of the reduction occurred between 1994 and 1996, in many states the largest declines have occurred more recently. In fact, in 22 states the percentage decline during 1998 (from January to December) was greater than it was in 1997.

This study updates and extends a 1997 Council of Economic Advisers (CEA) report examining the relative importance of a variety of economic and policy changes on caseload declines.[1] The earlier study examined changes in welfare participation between 1993 and 1996; the current study updates that report by including data through 1998. It also analyzes the effects of additional factors, such as changes in the minimum wage as well as the welfare reforms enacted in 1996.

This report uses data from 1976 to 1998 and finds that from 1996-98 policy factors were extremely important, which is not surprising given the scope of the 1996 reform. The 33 percent decline in the recipiency rate between 1996 and 1998 was due in large part to the changes in state welfare programs implemented under the Temporary Assistance for Needy Family (TANF) block grant. Specifically, roughly one-third of the caseload decline between 1996 and 1998 was due to program reforms implemented under TANF, 8-10 percent was due to the improved labor market, about 10 percent was due to the higher minimum wage, and 1-5 percent was due to lower cash welfare benefits.

During 1993-96, roughly 26-36 percent of the caseload decline was due to the improved labor market. The relatively large effect of labor market conditions on the caseload over this period reflects the fact that the decline in unemployment between 1996-98 was much smaller than the decline experienced between 1993-96. Another 12-15 percent of the decline in welfare participation was due to welfare waivers, which were issued to states to allow them to experiment with alternative program designs. The caseload fell 6-22 percent because of lower inflation-adjusted welfare benefits. The real value of the minimum wage fell between 1993 and 1996 (the increase in the minimum wage in 1996 occurred in October, so it was not effective most of the year), which by itself would have caused the caseload to increase by about 10 percent. The remaining change was due to other factors.

Table 1. Changes in the Number of Recipients in Each State

Number of recipients Percentage Change From

State 1993 1998 '93 to '96 '96 to '98 '93 to '98

Alabama         138,465     54,635        -26        -46        -61
Alaska           37,078     29,582         -1        -19        -20
Arizona         199,153    102,511        -16        -39        -49
Arkansas         71,989     32,633        -21        -43        -55
California    2,511,293  1,998,618          3        -23        -20
Colorado        122,890     50,746        -22        -47        -59
Connecticut     162,481    117,777         -2        -26        -28
Delaware         27,736     15,820        -16        -32        -43
DC               69,549     54,856          0        -21        -21
Florida         691,053    261,581        -22        -52        -62
Georgia         398,077    185,052        -15        -45        -54
Hawaii           57,336     46,724         16        -30        -19
Idaho            21,877      3,867          1        -83        -82
Illinois        694,050    476,576         -7        -26        -31
Indiana         215,367    111,176        -35        -21        -48
Iowa            102,438     65,665        -16        -24        -36
Kansas           88,363     34,536        -26        -47        -61
Kentucky        220,766    119,360        -22        -31        -46
Louisiana       259,762    124,800        -12        -46        -52
Maine            66,914     39,423        -18        -28        -41
Maryland        219,998    116,456        -11        -40        -47
Massachusetts   321,219    167,043        -28        -27        -48
Michigan        689,139    332,240        -26        -35        -52
Minnesota       192,173    143,685        -12        -15        -25
Mississippi     168,924     52,523        -26        -58        -69
Missouri        262,382    147,105        -14        -35        -44
Montana          34,875     19,540        -13        -35        -44
Nebraska         47,840     36,665        -20         -4        -23
Nevada           36,009     25,472         -2        -28        -29
New Hampshire    29,797     15,409        -22        -34        -48
New Jersey      345,370    196,947        -19        -30        -43
New Mexico       97,246     74,170          2        -25        -24
New York      1,215,526    886,746         -5        -23        -27
North Carolina  335,620    169,144        -20        -37        -50
North Dakota     18,215      8,541        -28        -35        -53
Ohio            712,277    340,179        -24        -37        -52
Oklahoma        135,762     61,191        -27        -38        -55
Oregon          117,852     46,001        -31        -43        -61
Pennsylvania    610,531    360,009        -14        -32        -41
Rhode Island     62,187     54,150         -8         -6        -13
South Carolina  146,280     60,110        -22        -48        -59
South Dakota     19,913      9,653        -21        -39        -52
Tennessee       310,486    149,089        -20        -40        -52
Texas           784,816    370,857        -16        -44        -53
Utah             52,144     28,258        -25        -28        -46
Vermont          28,301     19,643        -12        -21        -31
Virginia        194,765     99,053        -20        -36        -49
Washington      289,965    202,573         -6        -25        -30
West Virginia   118,113     38,638        -25        -56        -67
Wisconsin       235,247     40,167        -33        -75        -83
Wyoming          17,859      2,471        -32        -80        -86
Total        14,007,468  8,199,666        -13        -33        -41

Data are the average monthly caseloads for the calendar year.

Welfare Participation and the Labor Market

Caseloads normally fluctuate with the business cycle, rising in periods of high unemployment and declining when unemployment falls. Chart 1 illustrates this relationship between labor market opportunities and welfare participation over the past three decades. When unemployment increased in the early 1970s, so did welfare participation. The increase in welfare participation in the late 1980s and early 1990s, as well as the decline that began in 1994, also correspond with changes in employment opportunities during these periods. However, the trend in welfare participation does not always match that in unemployment, most notably when other important changes are taking place, including changes in family structure and welfare policies.

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Economic conditions vary across states as well as over time. Chart 2 displays a scatterplot of the unemployment rate versus the welfare participation rate for each state and the District of Columbia in 1994 when participation was near its peak. This relationship is quite strong, with a simple correlation of 0.65. While this correlation suggests a strong role for economic factors, it is likely to overstate their true role. Characteristics of states that influence their unemployment rates may also influence welfare participation. These characteristics include the age distribution, educational level, metropolitan/rural population shares, and racial and ethnic composition. While these factors may change over time, such change occurs more slowly than changes in policy or economic conditions.

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One way to eliminate the effects of these "fixed" factors is to examine changes over time within states, which is the approach employed in this study. Chart 3 displays the simple relationship between the change in the unemployment rate and the change in the welfare participation rate in each state between 1994 and 1998. It demonstrates that once unchanging state characteristics are removed, the relationship between the unemployment rate and caseloads is not nearly as strong as the simple cross-sectional one, with a correlation of 0.17.

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The changes over time for the nation as a whole also suggest that factors other than the economy have a substantial effect on welfare participation (Chart 1). For example, increases in welfare participation during the recession of the early 1980s were truncated by eligibility restrictions that were part of President Reagan's welfare reform efforts in 1982. As a result, over the entire 1980s the simple correlation between unemployment and welfare participation was much lower (0.23) than it was in the 1970s (0.41) or the 1990s (0.78).

Federal and State Policies

A number of key policy changes have been implemented in recent years and might be expected to have had an impact on welfare participation and caseloads.

Welfare Waivers

Since 1962 the Secretary of Health and Human Services has had the authority to waive federal program requirements in the Aid to Families with Dependent Children (AFDC) program if a state proposed experimental or pilot programs that furthered the goals of AFDC. Although there were a few waivers granted in the early 1980s, it was not until the early to mid-1990s that major, state-wide waivers became widespread. Between 1993 and 1996, the Clinton Administration issued welfare waivers to 43 states, more than any previous Administration. Table 2 lists the date that each state implemented a major state waiver.

These waivers varied substantially across states, and in many cases they differed greatly from the rules under AFDC. Some waivers increased the amount of earnings recipients were allowed to keep and still be eligible for welfare. Other waivers expanded work requirements to a larger number of recipients, established limits on the length of time recipients could remain on aid, permitted states to sanction participants who failed to meet work requirements, or allowed states to eliminate benefit increases to families who conceived and gave birth to children while on welfare (the so-called "family cap"). Given the widespread use of waivers and the degree to which these policies differed from traditional AFDC policy, there is substantial reason to believe that waivers contributed to changes in welfare caseloads.

Like the 1997 CEA study, this report focuses on six "major" types of waivers that received approval to be implemented state-wide[2]: termination time limits, work requirement time limits, family caps, JOBS exemptions, JOBS sanctions, and the earnings disregard. Each of these policies was discussed in detail in the appendix to the 1997 CEA Technical Report.[3]

                Table 2.  Dates of Major Welfare Waivers and
                            TANF Implementation
                                 Date of First           TANF
                                 Major Waiver       Implementation
                                 Implementation          Date
            Alabama                                    11/15/96
            Alaska                                       7/1/97
            Arizona                 11/1/95             10/1/96
            Arkansas                 7/1/94              7/1/97
            California              12/1/92              1/1/98
            Colorado                                     7/1/97
            Connecticut              1/1/96             10/1/96
            Delaware                10/1/95             3/10/97
            DC                                           3/1/97
            Florida                                     10/1/96
            Georgia                  1/1/94              1/1/97
            Hawaii                   2/1/97              7/1/97
            Idaho                                        7/1/97
            Illinois               11/23/93              7/1/97
            Indiana                  5/1/95             10/1/96
            Iowa                    10/1/93              1/1/97
            Kansas                                      10/1/96
            Kentucky                                   10/18/96
            Louisiana                                    1/1/97
            Maine                                       11/1/96
            Maryland                 3/1/96             12/9/96
            Massachusetts           11/1/95             9/30/96
            Michigan                10/1/92             9/30/96
            Minnesota                                    7/1/97
            Mississippi             10/1/95              7/1/97
            Missouri                 6/1/95             12/1/96
            Montana                  2/1/96              2/1/97
            Nebraska                10/1/95             12/1/96
            Nevada                                      12/3/96
            New Hampshire                               10/1/96
            New Jersey              10/1/92              7/1/97
            New Mexico                                   7/1/97
            New York                                    11/1/97
            North Carolina           7/1/96              1/1/97
            North Dakota                                 7/1/97
            Ohio                     7/1/96             10/1/96
            Oklahoma                                    10/1/96
            Oregon                   2/1/93             10/1/96
            Pennsylvania                                 3/3/97
            Rhode Island                                 5/1/97
            South Carolina                             10/12/96
            South Dakota             6/1/94             12/1/96
            Tennessee                9/1/96             10/1/96
            Texas                    6/1/96             11/5/96
            Utah                     1/1/93             10/1/96
            Vermont                  7/1/94             9/20/96
            Virginia                 7/1/95              2/1/97
            Washington               1/1/96             1/10/97
            West Virginia                               1/11/97
            Wisconsin                1/1/96              9/1/97
            Wyoming                                      1/1/97

Some of the waivers that were approved for state-wide implementation were initially implemented state-wide, some were implemented in selected areas of the state, while still others began in small regions of the state but were eventually phased in state-wide. Information on the pace of implementation is not available for all states. Therefore, the date that is used to signal implementation is the date that the waiver began to be implemented.[4]

The statistical analysis in this report, as in the earlier CEA report, compares states that did and did not have welfare waivers, determining whether those states that implemented waivers experienced larger caseload declines than those that did not. It improves on the earlier report by using the actual date the waivers were implemented in the states rather than the dates they were approved by HHS. In making these comparisons, the current analysis also adjusts for other differences across these states that may account for the differential decline, including economic conditions, cash benefit levels, and the minimum wage.


Enacted in August of 1996, the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) is designed to emphasize self-sufficiency and employment in place of welfare dependency and gives states greater flexibility to design and implement programs to achieve these goals. Benefits are time-limited; adults usually cannot receive Federal aid for more than 5 years during their lifetime, and some States have chosen to set shorter time limits. Most recipients must also participate in a work activity within two years to continue receiving aid.

PRWORA abolished the AFDC program and established the Temporary Assistance for Needy Families (TANF) block grant to help states fund their welfare programs. Under the TANF block grant, Federal assistance consists of an annual fixed transfer to each state equal to the amount of federal transfers the state received in fiscal year 1994, 1995, or the average of 1992-4, whichever was higher. In addition, most of the authority to design welfare programs was passed along to the States, who are required to have half of all recipients working by 2002 (40 percent by 2000). As a result, there are now substantial differences in how welfare programs operate across the nation. Some states increase benefits to welfare families who have additional children, while others do not. Some states stop payment of benefits to the entire family at the first instance of their failure to meet work activity requirements, while other states never sanction more than the adult. Most states allow welfare recipients to keep a substantial portion of their labor market earnings without reducing their welfare payments, while others do not. We investigate both the overall effect of TANF-funded programs on caseloads, as well as the impact of specific policy choices made by the states as part of their waiver or TANF-funded plan.

The effects of the new state programs implemented under the TANF block grant are estimated by examining changes in each state's caseload before and after it implemented TANF, again, after adjusting for other factors such as the unemployment rate and the minimum wage. States were required to submit their TANF plans to the Department of Health and Human Services for approval no later than July 1, 1997. Some states moved quickly after PRWORA was passed to enact TANF-funded programs, building on their welfare reform waivers, while other states operated for a period of time under the older AFDC program rules.[5] The date that each state implemented its TANF program is listed in Table 2.

Minimum Wage

A higher minimum wage can make work more attractive, giving welfare recipients a greater incentive to enter the workforce and leave public assistance. On the negative side, if a higher minimum wage reduces employment of low-skilled workers, some people may lose their jobs and enter welfare. At the same time, an increase in the minimum wage may lead employers to substitute away from teenagers (a relatively large share of whom work for the minimum wage) and towards older welfare workers (who are perhaps not as likely to work at the minimum wage, but more likely than teenagers to be working just above the minimum). The latest empirical evidence is mixed, but most studies find either modest or no disemployment effects associated with past increases in the minimum wage.

The minimum wage also varies among states, with 15 states having minimums above the federal floor at some point during the period analyzed in the study (1976-1998). Therefore, the study compares the relationship between welfare participation and minimum wages over time and across states.

AFDC/TANF Benefit Levels

States have long set their own level of maximum monthly benefit payments, with variation by family size and composition. All else equal, higher benefit levels are expected to increase the number of participants. Over the period of this study, the inflation-adjusted level of welfare benefits fell in almost all states. In some cases the state explicitly lowered (or raised) benefits, but in most states benefit levels were fixed and eroded over time with inflation.

Data and Methodology

Using annual calendar year data from 1976 to 1998 on all states and the District of Columbia, the analysis is based on 1,173 observations. A set of models are estimated which correlate movements in welfare participation with movements in state unemployment rates, state AFDC/TANF benefit levels, state/federal minimum wage levels, the implementation of state waivers, and the implementation of state TANF-funded welfare programs.[6]

The estimated models also control for the characteristics of states that are largely unchanged over the entire (1976-98) time period, and for changes in each year that are common to all states. In technical jargon this is known as controlling for state and year fixed effects; this technique is used in most existing studies of annual caseload changes. The estimates are based on a technique known as weighted least squares, which uses the data across states and over time, and weights the data in each state by its overall population. A Technical Report is available which provides more details on the data and the estimation procedures for interested readers. As always in such studies, we estimate a variety of slightly different models to test the robustness of our results to the exact set of variables included.

The results of this methodology are to estimate the effect of changes in the economy or in policies over time within a state on the caseload in that state. Hence, the results are the direct result of asking "If variable X changes over time within a state, what will be the effect on caseloads in that state?" This is clearly the question in which we are most interested. It allows us to measure the effects of (say) waiver implementation or unemployment changes on caseload changes over time.

This approach is very similar to the approach used in the 1997 study. One difference is that the earlier study emphasized models that incorporated a "lead" effect of waiver policies. That is, waivers were allowed to affect caseloads one year prior to the date they were approved. While the current study also reports models that incorporate leads, the preferred models do not contain leads, since the leads may capture more than the causal effects of these policies. (For example, perhaps states with recently declining caseloads had slack resources and manpower to design and submit a waiver.) This difference explains why waivers were found to account for 31 percent of the change between 1993 and 1996 in the 1997 study, but only 12-15 percent of the change in the current study.


These results report the estimated effects on caseloads of each of the variables discussed above over the 1976-98 period, holding constant the effects of changes in all other variables. Based on these estimated relationships, chart 4 shows the contribution of various factors in the recent 1996-98 period.

The 1996 welfare reform legislation has been a key contributor to caseload declines since it was enacted. The average state experienced an 18 percent decline in welfare participation following the implementation of their TANF-funded state welfare plan, holding all other policy and economic variables constant. These new state programs funded by the TANF block grant account for roughly one-third of the 33 percent decline in the recipiency rate that has occurred since 1996 (Chart 4).

As reported in the earlier CEA study, welfare waivers that were implemented prior to PRWORA explain a substantial share of the caseload decline from 1993 to 1996. States that implemented major waivers experienced an 8-9 percent greater decline in welfare participation than states that did not, holding all other policy and economic variables constant. This accounts for 12-15 percent of the overall decline between 1993-96.

The strong labor market has made work opportunities relatively more attractive, drawing people off welfare and into jobs. The unemployment rate has not declined as much in the post-TANF period (1996-98) as it did in the 1993-96 waiver period. As a result, the share of the decline in the caseload that is attributable to improvements in the labor market was much higher in the 1993-96 period (26 to 36 percent) than in the 1996-98 period (8 to 10 percent). This study reaffirms the importance of maintaining a healthy macroeconomy with low unemployment rates in order to help families move off and remain off of welfare. Any future 1-percentage-point increase in unemployment is likely to produce a 5 to 7 percent increase in welfare caseloads.

The study also finds that increases in the minimum wage have made work more attractive and, as a result, caused welfare participation to decline. The estimates suggest that a $0.50 increase in the minimum wage has been associated with a decline in welfare participation of 4 to 6 percent. Hence, the recent minimum wage increases have helped reduce welfare rolls (Chart 4).

As many other studies have confirmed, higher welfare benefit levels result in higher caseloads. As noted above, this need not reflect any behavioral differences in higher-benefit states, but may only be due to the fact that higher benefits typically imply that a larger share of the population is eligible to receive public assistance.

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The specific program design adopted by a state can affect its caseload declines. The study examines the effects of a number of specific policies, including time limits, earnings disregards, work sanctions, family caps, and work exemptions on the size of the caseload. We estimate the effects of these policies regardless of whether they were implemented as part of a state's waiver plan or a TANF-funded plan. Our results on the effects of specific policies should be interpreted with caution, since only a limited number of states have implemented many of these policies for only a relatively short period of time. The primary results with regard to these policies are:


The large sustained declines in caseloads provide one piece of evidence about the effectiveness of welfare reform efforts. This study suggests that caseload declines have occurred in part because of a strong economy with low unemployment rates. However, policy changes by state and Federal governments have been even more important in explaining the post-1996 decline than the strong labor market. The new state programs implemented following the enactment of PRWORA, most of them focused on increasing work effort among welfare participants, have been the most important identifiable factor explaining the decline from 1996-1998. Increases in the minimum wage, at the Federal level and among some states, have also reduced caseloads.

However, there are multiple indicators of the impact of welfare reform, including changes in work and earnings among welfare leavers, in marriage rates and out-of-wedlock pregnancies, and in poverty rates. The Clinton Administration is collecting and tracking information on all of these measures in order to fully assess the impact of welfare reform.

[1] Council of Economic Advisers (1997). "Explaining the Decline in Welfare Receipt, 1993-1996: Technical Report," Executive Office of the President of the United States.

[2] In a few instances waivers were examined which were not approved to be implemented state-wide but affected a large share of the state's caseload.

[3] It was determined that the waiver in West Virginia, which was considered a "major" waiver in the 1997 CEA study, did not in fact meet this requirement (Martini and Wiseman, 1997), which is reflected in Table A1.

[4] Somewhat larger effects are estimated when the date of approval, which was utilized in the 1997 CEA study, is used instead of the date of implementation, as described in appendix A of the technical report.

[5] In most cases, the waiver concept becomes meaningless once TANF was implemented because states were given broad control over their welfare policies. In particular, states could operate the broad categories of policies under TANF, whether or not they were continuing a waiver. However, if a state continued a time limit waiver, then participants' time clocks in that state would have been running prior to TANF implementation. As a result, these participants would reach their time limits more quickly than if their clock would have been reset on the date of TANF implementation.

[6] Most of the data used in the analysis come from well-known sources, with a few exceptions. The information on implementation dates as well as program waivers and TANF were obtained from the Department of Health and Human Services and the Urban Institute (Gallagher et al., 1998).

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