Assessing the Impact of Welfare Reform on Single Mothers Hanming Fang Michael P. Keane Department of Economics Yale University Introduction • U.S. welfare system has been substantially reformed since 1993. • Many States obtained AFDC waivers in 1993-1996. • AFDC was replaced by TANF in 1996-1997. Under TANF: Block grants replaced federal matching funds; 5-year time limit on welfare from federal funds; Work requirement; Maintenance of Effort Requirement. • From 1993 to 2002, Welfare participation rate among single mothers dropped from 32% to 9%; Work participation increased from 68% to 79%. Goal of the Paper • To ascertain what features of welfare reform, Time limits; Work requirements; Child support enforcement, etc. have been most responsible for the decline in welfare participation and increase in work among single mothers. Challenges Data: States have great leeway in the design of their TANF programs, resulting in substantial program heterogeneity, making it very difficult to develop of set of variables that comprehensively characterize the nature of different State TANF programs. Contemporaneous economic and policy changes: strong macroeconomy of 1996-2000; Significant expansion of the Earned Income Tax Credit (EITC) after 1993; Dramatic increases in child care development fund (CCDF) expenditures since 1996; Medicaid expansion. Additional Purpose of this Study One could write down a structural dynamic model of single mother labor supply and welfare participation, estimate it using pre-reform data, and predict the effects of time limits, work requirement, EITC etc. In fact, Keane (1995), Keane and Wolpin (2003), Fang and Silverman (2003) etc. have attempted to make predictions of various policies using such structural approach. We still need to rely on such structural model to predict the effects of other policies that are yet to be implemented. But which of the various structural models should we use in future predictions? We need to compare the predictions of currently proposed models with evidence from the data. Prior Literature … • … often looked at one policy at a time, and took a Difference-in-difference (DD) approach. • Find a control group that is not affected by the policy, but otherwise similar to the treatment group. • E.g. Grogger (JHR 2000) uses single mothers whose children are over 13 as the control group, since a 5- year time limit would not affect them. • Problems: • Assumption that other aspects of the reform, like daycare expansion, affect the two groups similarly is implausible; • The two groups have very different baseline participation rates. Table 1: Welfare Participation Rates of Single Mothers, By Age of Youngest Child Age of Before After Changes in Changes Youngest Time Time Percentage in Percent Child Limits Limits Points 0-6 41.3 23.8 -17.5 -42% 13-17 16.0 11.0 -5.0 -31% DD Effect -12.5 -4.5 (percentage points) DD Effect -30% -11% (percentage) Note: Reproduced from Grogger (2000, JHR), Table 2. Data is the March CPS from 1979-1999. Our Approach We collect detailed data about all the time varying factors that we think are relevant in explaining welfare and work participation of single mothers. We combine these economic and policy data with individual data from March CPS 1981-2003. To allow for policies to have different effects on single mothers with different characteristics, we include interactions between demographic characteristics and economic and policy variables. Prior Literature (cont’d) Grogger and Michalopoulos (2003, JPE) used data from a randomized experiment in Florida (Family Transition Program, FTP). FTP is a fairly small experiment in which welfare recipients in one county were randomized into a treatment group that was subject to a 2-year time limit and a control group that was not. [Also a childcare subsidy was provided to both groups alone. Thus the DD approach still needs to assume no interaction b/w childcare subsidy and time limit.] They show that the 2-year time limit lowered welfare participation rates among single mothers with youngest children in 3-5 year old range by 7.4 percentage points (from a base rate of 40.3 percent). The main problem is that the way FTP was implemented was at odds with the national norm (examples). Prior Literature (cont’d) … Prior work attempting to look at many policies simultaneously includes Blank (1997), Council of Economic Advisors (1997, 1999). Dependent variable - State level caseloads or welfare participation rates. Puzzling results. E.g., Blank estimates that TL is insignificant (wrong sign); WR insignificant; biggest factor is the family cap (which seems implausible). And the models don’t fit caseloads very well. Problems: limited duration of reforms; collinearity between the strong macroeconomy and the timing of reforms; failure to exploit how demographic groups are differentially affected by policies. Some Institutional Background Explaining the Rise of Child Care Subsidy Section 409 of PRWORA stipulates that DHHS can reduce States’ Federal TANF block grant if the State failed to maintain its level of assistance for needy families at 75% of their historical peak levels (usually the level at 1994). This Maintenance of Effort (MOE) requirement was designed to prevent a feared “race to the bottom” where many States might start to cut assistance once Federal AFDC matching funds vanished. Clinton signed PRWORA only after MOE was added. MOE and Multiple Equilibria MOE has had some dramatic (and unexpected) consequences: Welfare caseloads for almost all States dropped dramatically after 1996, causing expenditure on TANF cash assistance to fall; Thus to satisfy MOE, States are forced to redirect money into other qualified programs – mainly to subsided daycare; Subsidized daycare faciliates more women to work and possibly leave welfare, freeing more money for daycare subsidy (under MOE). Possibility of a switch in multiple equilibria. Economic and Policy Variables AFDC/TANF benefit level Time Limits; Work Requirement and Exemptions; 20 States had an immediate work requirement; while most others allows for 24-month work requirement time limit; States may exempt women with young children from work requirement (up to 2 years old); States also allow for exemptions if they are disabled, if theire household member is disabled, if they had difficulty finding care for children under 6; Sanctions if WR is not satisfied also vary by States; Benefit Reduction Rate and Earnings Disregard; Diversion programs (receiving a few months benefits up front for agreeing not be in TANF for some period of time) Child Support Enforcement and Treatment of Child Support Income Child care subsidies; EITC: both Federal and State EITC The Federal EITC phase-in rate for families with one child increased from 10% in 1980-1984 to 18.5% in 1993, 26.3% in 1994 and 34% from 1995 onward Since 1991, the EITC phase-in rate and max credit differ for families with one vs. two or more children. Food Stamps; Medicaid and S-CHIP: Medicaid expansion since 1988 State Unemployment Rate Federal income tax Minimum wage (real) 20 percentile wage by state (real) Identifying the Effects of Macroeconomy We have an advantage over earlier studies because we have data from the 2001-2002 recession This allows us to better identify the separate effects of welfare reform and macroeconomy. We found that the macroeconomy, as measured by the local unemployment rate, has relatively small effects on welfare participation, but big effects on work participation. This is consistent with the simple observation that: Welfare participation continues to drop in 2001- 2002; Work participation rate actually declined in the recession. Identifying the Effects of Time Limits NY, MI and VT do not enforce time limits. Yet, these States have had caseload drops comparable to other States. Moreover, many States, such as CA, only reduce the benefit level (child portion kept) once TL is exhausted. Case studies suggest that many States provide liberal extensions and exemptions. Thus it seems implausible that TL were a key factor in reducing welfare participation. More on Identification We are careful about exploiting individual level variation whenever possible. WR: women with young kids could be exempted; EITC: EITC phase-in rates differ according to the number of children; Child care subsidy: should have no effect on women whose children are older than 12; Child Support Enforcement: should have no effect on the widowed; Medicaid: large variation across State and time in the oldest age of children covered by the Medicaid expansion. Our Specification Includes demographics, and policy variables and rich interactions between the two; A total of 245 terms. A lot of terms, but … Some Defense for Our Specification We are effectively trying to explain the welfare and work participation rates for women with different demographics in different States in different years; How many such participation rates are there? Specification (cont’d) For the sake of argument, consider a simple case: Suppose we observe women in Race (3 categories); educational attainment (4 categories); marital status (4 categories); 4 age categories; (4 categories) youngest child in 3 age intervals; (3 categories) Oldest child in 3 age intervals; (3 categories) Number of children is either 1, 2 or 3+; (3 categories) State of residence (51 categories) Urban/rural (2 categories); Year (23 years) Total: 12,161,664. Thus our specification is remarkably parsimonious. What will be the specification of the prior literature? Much in the prior literature has relied on specifications that include: State dummies; Year dummies; State specific quadratic time trends. This gives 51 + 23 + 100 = 174 parameters; Then it would include a measure of a single policy, such as a time-varying dummy variable for whether a State has yet imposed time limits. This adds 51 parameters. Note such model has no hope of explaining the evolution of welfare and work participation rates by demographics. Moreover, including State dummy makes OLS estimates more likely to be biased. Interpreting the Estimates The main problem of having so many interaction terms is that the regression coefficients are impossible to interpret by themselves. We instead try to give an intuition for what the estimates mean by presenting the predicted probability of welfare participation for a set of single mothers with different demographic characteristics when time limits and work requirements are imposed. Table 9. Counterfactual Simulations [TL]: No Time Limit: Suppose that no State implemented time limit, while all other economic and policy variables evolved as they actually did; [WR]: No work requirement; [EITC]: No EITC expansion (stayed the same as that in 1993); [UNEMP]: No unemployment rate change (stayed the same as that in 1993); [CCDF]: No CCDF expenditure; [MEDICAID]: No further Medicaid expansion since 1993. Findings According to our model, the key economic and policy variables that drove the overall 23 percentage-points decrease in the welfare participation rate from 1993-2002 were: Work requirements (57%); EITC (26%); Time limits (11%); Macroeconomy (7%); The key economic and policy variables that drove the overall 11.3 percentage-points increase in the work participation rate from 1993-2002 were: EITC (33%); macroeconomy (25%); Work requirement (17%); Time Limit (10%). Conclusion Work requirements are very effective at getting people off welfare, but not so effective at inducing employment. EITC is rather effective at both. Our model implies some important differences across demographic groups in the impact of various policies. For example, The macro economy and EITC largely explain the increase in work among relatively well educated single mothers; Work requirements were a much more important factor for high school drop outs. Confession: Problems with our Approach Assumed education, marriage and fertility decisions to be unaffected by the welfare reform itself; Though evidence of welfare policy on marriage and fertility decisions are rather mixed, these are definitely endogenous in principle; More damagingly, in a dynamic framework, women’s expectations about the future welfare policies, not just the current welfare system, should affect their decisions to work today. Such expectations are not available; and any available measurement would be noisy. Keane and Wolpin (2003) assumed perfect foresight.
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