Panel:
Low-Income Households and Effective Marginal Tax Rates: From Simulation to Family Voices
(Poverty and Income Policy)
*Names in bold indicate Presenter
Effective marginal tax rates quantify the portion of additional earnings eroded by reductions in benefit programs and taxes; as such, benefit reductions act as a tax on additional earnings. For example, if a family earns an additional $1,000 from extra work hours over the course of a year, the added earnings are taxed (-$200) and SNAP benefits are reduced (-$200). Altogether, the bite taken out of new earnings by taxes and reduced benefits yields a marginal tax rate of 40 percent. Extra earnings of $1,000 amounts to a resource increase of only $600.
For observers who wish to incentivize work, high marginal tax rates are problematic because they potentially disincentive work. For observers who wish to ensure families sufficient resources to thrive, high marginal tax rates are problematic because they take away resources even as families work more to increase resources. No matter where one stands on the policy spectrum, high marginal tax rates are a problem.
But marginal tax rates are a necessary result of providing means-tested benefits. And high marginal tax rates are (usually) the unintended consequences of well-intentioned programs created and administered in silos. For example, the Earned Income Tax Credit administered by the Treasury Department and SNAP (Supplementary Nutrition Assistance Program) administered by the Department of Agriculture combine to create high marginal tax rates, although each alone has a moderate marginal tax rate. Potential policy solutions are challenging to implement. This panel takes a deep dive to better understand the nature of the problem, and ends with a tool to explore solutions.
The first paper uses Current Population Survey data and microsimulation methodology to describe marginal tax rates faced by families with and without children, and families receiving child care subsidies. This approach is also known as the “distributional method,” and is appropriate for describing (e.g., frequencies and medians) marginal tax rates faced by U.S. households.
The second paper employs focus group methodology to understand what families with children perceive about their own marginal tax rates, and to what extent that perception affects their employment decisions. In other words, what do people think would happen to their overall resources if they were to increase their work hours from 30 to 40 hours? And does that affect how they feel about increasing work hours? To the extent that marginal tax rates affect employment decisions, it’s the perceptions that matter (not the actual rates).
The third paper also uses qualitative methodology (semi-structured interviews) to understand people’s perceptions about their own marginal tax rates, and decisions related to those perceptions. But unlike the second paper, these views are collected in response to a real and contemporaneous policy event: the Seattle Minimum Wage Ordinance.
The fourth paper demonstrates a valuable tool – the Family Resource Simulator – for policy makers to understand how various programs interact to yield varying levels of marginal tax rates. Using a hypothetical family approach, the tool will shed light on how policies such as minimum wage policies would affect different kinds of families.
