Association for Public Policy Analysis & Management

Research on the child care decision-making process identifies considerable challenges to accessing high-quality child care and early education programs (Forry, Tout, Rothenberg, Sandstrom, & Vesely, 2013). Parents report difficulties obtaining quality care that is affordable, available during work hours, and proximate to their homes and jobs. These challenges are greatest for low-income parents seeking center-based care, especially for infants and toddlers and during times outside traditional daytime, weekday hours. The current study considers these findings in light of data available on the child care market in four diverse regions of Illinois and New York. These regions are sites taking part in the Illinois-New York Child Care Research Partnership Study, a multi-component project designed to improve understanding of the availability, stability, and quality of child care for low-income working families. In each site, we compare the demand for subsidized child care for children under age six to the supply of child care available.

The paper addresses two research questions: 1) How are child care programs with different characteristics distributed across each of the four regions?  2) How does the supply of child care with different characteristics match the heterogeneous needs of subsidy-eligible families?

To identify child care supply, we use proprietary NACCRAware data maintained by the Illinois Network of Child Care Resource and Referral Agencies and by the Child Care Councils of Nassau and Westchester Counties in New York. Data include providers’ geocoded location, rates, schedules, capacity by age, whether the provider accepts subsidies, and diverse quality indicators. To estimate demand, we use census tract-level data from the American Community Survey 2010-2014 five-year file. Demand for subsidized care for non-school age children is estimated by calculating the number of children under age 6 in households with employed adults living below 200% of the federal poverty level. Demand-side estimates also take into account overall population density and household English language proficiency.

To address Question 1, we use ArcGIS software to illustrate the geospatial distribution of providers with different characteristics. By way of example, one density map shows the number of child care slots for infants differentiated by care type and subsidy program participation. To address Question 2, we restrict the supply data to subsidy-serving providers and calculate demand-supply ratios for each census tract to proxy the availability of subsidized child care options. To illustrate these ratios geospatially, we construct maps that identify the share of met need among potential subsidy beneficiaries (i.e., the number of subsidy-eligible children in each census tract divided by the number of slots in licensed subsidy-participating centers and family child care homes in that tract). These maps illustrate the presence of child care deserts and a high use of legally exempt care in low-income communities.

Through this work, we gain important knowledge about where and for whom child care options are most constrained. This knowledge can be used to support efforts to increase the availability and quality of care in underserved areas and for underserved populations, priority aims of the recently reauthorized Child Care and Development Block Grant.