Exploring Household Earnings, Income, and Responses to Policy Using Tax Data
Saturday, Jan. 7, 2023 2:30 PM - 4:30 PM (CST)
- Chair: John Voorheis, U.S. Census Bureau
The Measurement of Income Growth, Mobility, and Volatility in the U.S. By Race and Gender: Introducing MOVS
AbstractFederal statistical agencies and policymakers have identified the need for integrated systems of household and personal income statistics, including measures of income growth, mobility, and volatility. This interest marks a recognition that aggregated measures of income, such as GDP or average income growth, tell an incomplete story that may conceal large gaps in wellbeing between different types of individuals and families. Until recently, income data that is rich enough to calculate detailed income statistics across demographic characteristics, such as race and ethnicity, has not been available. The MOVS (Mobility, Opportunity, and Volatility Statistics) project proposes to fill this gap using linked demographic and tax records on the population of U.S. workers. We define households and calculate household income, applying equivalence scales to create a personal income concept, and then trace the progress of incomes by demographic groups via a suite of statistics on income mobility, income volatility, and related topics, such as the concentration of affluence or poverty. We calculate and report key statistics within characteristics that include race, ethnicity, and gender. The ultimate goal of MOVS is a public-use data tool that researchers may use to explore income mobility patterns in rich detail.
The Anti-Poverty, Targeting, and Labor Supply Effects ofThe Anti-Poverty, Targeting, and Labor Supply Effects of Replacing a Child Tax Credit with a Child Allowance
AbstractWe estimate the anti-poverty, targeting, and labor supply effects of replacing the Child Tax Credit (CTC) with a child allowance by linking survey data with administrative tax and program data which form part of the Comprehensive Income Dataset (CID). We focus on the provisions of the 2021 Build Back Better Act, which would have increased maximum benefit amounts to $3,000 or $3,600 per child (up from $2,000 per child) and made the full credit available to all low and middle-income families regardless of earnings or income. Initially ignoring any behavioral responses, we estimate that the replacement of the CTC would reduce child poverty by 34% and deep child poverty by 39%. The change to a child allowance would have a larger anti-poverty effect on children than any existing government program, though at a higher cost per child raised above the poverty line than any other means-tested program. Relatedly, the child allowance would allocate a smaller share of total dollars to families with the lowest levels of income, education, or health than any existing means-tested program with the exception of housing assistance. We then simulate anti-poverty effects accounting for labor supply responses. By replacing the CTC (which contained substantial work incentives akin to the EITC) with a child allowance, the policy change would reduce the return to working at all by at least $2,000 per child for most workers with children. Relying on elasticity estimates consistent with mainstream simulation models and the academic literature, we estimate that this change in policy would lead 1.5 million workers (constituting 2.6% of all working parents) to exit the labor force. The decline in employment and the consequent earnings loss would mean that child poverty would only fall by at most 22% and deep child poverty would not fall at all with the policy change.
Washington Center for Equitable Growth
- J1 - Demographic Economics
- H2 - Taxation, Subsidies, and Revenue