Association for Public Policy Analysis & Management

Research Questions: The Family Resource Simulator (FRS), an online tool developed and maintained by the National Center for Children in Poverty, allows researchers to analyze the individual and combined impacts of a comprehensive range of safety net polices and potential policy changes on low-income families, using a “hypothetical family approach” that is explained further below. The FRS tool is updated state by state, and is currently being expanded to include basic expenses and policies as of 2019 in Pennsylvania, among other states. This project's initial findings are expected to be published by August 2019, and will address the following questions: (1) How might currently available social safety net programs – such as tax credits, child care subsidies, TANF, and Medicaid – affect incentives to earning higher income among Pennsylvanians, as reflected through marginal tax rates? (2) Will increasing the minimum wage in Pennsylvania potentially lead to low-income families encountering marginal tax rates exceeding 100%, commonly called “benefit cliffs,” that could leave families financially worse than they would be without this policy change? (3) If raising the minimum wage may lead to benefit cliffs, can we estimate how many families would experience these benefit cliffs, based on survey data?

Methodology: The FRS tool uses a “hypothetical family approach” as the basis for its simulation modeling. Based on user-defined family characteristics (e.g., family composition, age of family members, single vs. unmarried parents, employer vs. marketplace health insurance, and which safety net programs the family utilizes when eligible), the tool models a family's monetary resources – such as earnings, cash assistance, and child support – and compares those resources to the hypothetical family’s basic needs, inclusive of any reductions to these expenses due to safety net programs, over a range of incomes. Unlike microsimulation models (or "distributional approaches") whose analyses rely on estimates of program participation based on surveys and/or administrative data, this model does not incorporate observations of how real families engage with public policies, but rather assesses how user-defined families can utilize these policies in an optimal manner. This approach can reveal program inefficiencies such as "benefit cliffs," described above. Survey or administrative data can then be used to estimate how many families actually experience these policy inefficiencies.

Topic Importance: While there are certainly advantages to using microsimulation models for public policy analysis, especially at the national level, the hypothetical family approach can be more suitable for certain types of research questions. For example, although microsimulation analyses can help prioritize program improvements to more widely used programs, which is especially conducive to cost-benefit analyses, hypothetical family approaches may be more appropriate to assessing the impacts of less widely-used programs or program rules that are nonetheless very important to specific subpopulations. Hypothetical family approaches may also be more useful for analyses at the state or local level, such as analyzing minimum wage policies in Pennsylvania, as the sample sizes of the data sets that include the necessary data for microsimulation analysis (such as the CPS) may not be suitable for smaller geographies.