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									Assessing the Impact of Welfare
  Reform on Single Mothers

  Hanming Fang       Michael P. Keane
         Department of Economics
             Yale University

 • 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

      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
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
       DD Effect                                    -30%            -11%

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 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,
  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.
      limited duration of reforms;
      collinearity between the strong macroeconomy and the timing of
      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
  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
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-
     Work participation rate actually declined in the
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
      Child care subsidy: should have no effect on women whose
       children are older than 12;
      Child Support Enforcement: should have no effect on the
      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
   Much in the prior literature has relied on specifications that
       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

   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

   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

   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%).

  Work requirements are very effective at getting
  people off welfare, but not so effective at inducing
  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
  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
  Such expectations are not available; and any available
  measurement would be noisy.
  Keane and Wolpin (2003) assumed perfect foresight.

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