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The determinants and consequences of child care subsidies for single mothers in the USA


This paper provides an analysis of child care subsidies under welfare reform in the USA. We used data from the 1999 National Survey of America's Families to analyze the determinants of receipt of a child care subsidy and the effects of subsidy receipt on employment, school attendance, unemployment, and welfare participation. Ordinary least-squares estimates that treat subsidy receipt as exogenous show an effect of subsidy receipt on employment of about 13 percentage points. Two-stage least-squares estimates that treat subsidy receipt as endogenous and use county dummies as identifying instruments show an effect of 33 percentage points on employment, 20 percentage points on unemployment, and no effects on schooling and welfare receipt.

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  1. 1.

    See Duncan and Giles (1996) and Blau and Currie (2004) for a more thorough discussion of the rationale for public child care subsidies.

  2. 2.

    See Crosby et al. (2001) for a discussion of these demonstrations and a comparison of their treatment effects.

  3. 3.

    An earlier round of the NSAF was conducted in 1997, with a different sample. A previous draft of this paper used data from the 1997 NSAF. In most cases, the results from the two waves are similar.

  4. 4.

    Alabama, California, Colorado, Florida, Massachusetts, Michigan, Minnesota, Mississippi, New Jersey, New York, Texas, Washington, and Wisconsin.

  5. 5.

    There is considerable variation in the subsidy receipt and other outcome variables across states. Subsidy receipt ranges from 0.041 in Texas to 0.203 in Washington. Employment ranges from 0.623 in New York to 0.790 in Wisconsin. Welfare receipt ranges from 0.057 in Colorado to 0.278 in Michigan.

  6. 6.

    Two thirds of the states in our sample report that there is a waiting list for a child care subsidy (Schulman et al. 2001). In the other states, the absence of a waiting list does not necessarily indicate the absence of rationing. These states may simply turn away clients for whom funds are not available, without putting them on a waiting list. For example, in 1999, Louisiana had a waiting period of 3–6 months because of administrative backlog and staffing shortages, although there was no official waiting list (Collins et al. 2000). Given the evidence cited above, that only 12–15% of eligible families are served by a CCDF subsidy, it is hard to imagine how states can avoid rationing unless a large majority of eligible families are unaware of their eligibility, or the hassle cost of obtaining a subsidy is very high. The states that do not maintain waiting lists (Colorado, Michigan, New Jersey, Washington, and Wisconsin) served 20.3% of eligible families in 1998–1999, while the states that did maintain waiting lists served 12.1% (Administration for Children and Families 1999). Most of this difference was due to more stringent eligibility criteria for a subsidy in the former group of states. When the most generous eligibility criterion allowed by federal law (85% of state median income) was used, the percentage served was 11.7 for the former group and 9.0 for the latter group.

  7. 7.

    We found that adding state fixed effects to Eq. (2) always improved the fit compared to a model that included a set of state-level covariates. The state-level covariates included state policy variables such as the CCDF reimbursement rate, income eligibility level, child care subsidy expenditure per capita, and other state-level variables such as the unemployment rate, median income, and the child poverty rate. Also, when we included these variables in the subsidy receipt equation (Eq. 1), they had effects on subsidy receipt that were jointly and individually insignificantly different from zero. In contrast, state dummies had effects in Eq. (1) that were jointly significantly different from zero. We attributed the lack of effects of the policy variables together with strong effects of state dummies to the fact that all states ration subsidies and rationing was the main determinant of subsidy receipt. Rationing mechanisms appeared to differ across states in ways that were not captured by program rules and policies.

  8. 8.

    Lemke et al. (2000) analyzed the work behavior of child care voucher recipients in Massachusetts using variation in local child care policy and other local variables to explain employment outcomes.

  9. 9.

    These variables include population size; the age, race, ethnic, education, and sex structure of the population; median income; percent in poverty; land area, population density; employment and employment growth; local government employment; payroll; and the number of establishments.

  10. 10.

    Children who were enrolled in Head Start were classified here as subsidy recipients if the mother reported receiving a child care subsidy. We could not determine from the data whether these cases received an employment-related child care subsidy in addition to Head Start. We estimated models in which Head Start cases who had no plausible reason for receiving a work-related child care subsidy (employment, school enrollment, and job search) were reclassified as not receiving a subsidy. This had negligible effects on the child care subsidy coefficient estimate. Also, we estimated the models reclassifying all mothers as not receiving a subsidy if their child is in Head Start. Again, this did not change the results.

  11. 11.

    There were 110 counties included in the 12-state sample used here, and there was considerable variation in the child care subsidy receipt rate across counties within each of the 12 states. The coefficient of variation of the county-level receipt rate ranged from 0.20 to 1.58 and averaged 0.79 across the 13 states. The (unweighted) average number of sample members per county was 12.7, which was relatively small and accounted for the increase in the standard errors in the 2SLS estimates. A Hausman test for the equality of the OLS and 2SLS estimates failed to reject equality.


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Thanks to Philip Levine, conference participants, seminar participants at the University of Chicago and Manpower Demonstration Research Corporation (MDRC), and three referees for helpful comments, and to the Joint Center for Poverty Research for support. None of the above bear any responsibility for the contents. Comments are welcome at or

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Correspondence to Erdal Tekin.

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Responsible editor: Deborah Cobb-Clark



Table 5 Descriptive statistics
Table 6 Results from OLS estimates of the outcome equations
Table 7 Results from 2SLS estimates of the outcome equations

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Blau, D., Tekin, E. The determinants and consequences of child care subsidies for single mothers in the USA. J Popul Econ 20, 719–741 (2007).

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  • Child care
  • Employment
  • Single mother
  • Welfare reform


  • J13
  • I38