Emma SifreSenior Data Analyst
Emma works to support and expand ITEP’s microsimulation model and other off-model analyses. Her work aims to disaggregate the effects of tax policy changes by race, income, citizenship status, and geography. Before joining the team, Emma researched domestic social policy at the Congressional Research Service. She received an Interdisciplinary B.A. in Economic Inequality from the University of Connecticut and her MSc in Public Policy from University College London.emma at itep.org
Recent Publications and Posts view more
National and State-by-State Estimates of Two Approaches to Expanding the Child Tax Credit
The Romney Child Tax Credit plan would leave a quarter of children worse off compared to current law and help half as many low-income children as the 2021 expansion of the credit.
Why Treasury’s Pending Race-Based Analysis of Stimulus Payments is Important
One important data inadequacy is the lack of demographic information in tax data. While the IRS data offers rich data on taxpayer income, it does not collect information on important demographic characteristics like race and ethnicity. This presents a challenge for researchers interested in the racialized impacts of the U.S. tax system and has prompted many researchers and organizations to advocate for public-use tax data that is disaggregated by race and ethnicity.