Overview
Ithai Lurie is an economist at the U.S. Department of the Treasury, Office of Tax Analysis. He is a co-author of Friedman et al. (2016, 2018) on the long-run and geographic drivers of young adult disability insurance receipt; Lurie and McCubbin (2016) on using tax data to study the uninsured; Lurie and Pearce (2019) on individual-level health insurance coverage from IRS Form 1095 data; and Goldin, Lurie, and McCubbin (2021), the first randomized experimental study showing that health insurance reduces mortality.
Key Contributions / Features
- Goldin, Lurie, and McCubbin (2021): Co-author of the first randomized experimental evidence that health insurance reduces all-cause mortality, using an IRS informational letter RCT targeting 4.5 million ACA mandate-penalty households. Provided Treasury data infrastructure and expertise in linking Form 1095 monthly coverage records with SSA mortality data. See Medicaid and Mortality.
- IRS Form 1095 administrative data: Led work at Treasury OTA to construct and analyze the administrative health insurance coverage database created by the ACA individual mandate reporting requirements. Forms 1095-A (exchange), 1095-B (insurer), and 1095-C (employer) provide complete individual-level monthly coverage records — the most comprehensive available source for health insurance research.
- Lurie and McCubbin (2016): Early paper establishing that tax-filing data could characterize the uninsured population — who they are, their income composition, and their relationship to ACA subsidy eligibility. A methodological precursor to the mortality study.
- Lurie and Pearce (2019): Treasury working paper documenting the properties and research uses of Form 1095 coverage data.
- Friedman et al. (2016, 2018): Co-author of both papers documenting the intergenerational income gradient in DI receipt, the geographic concentration of DI variation among poor children, and the "good places paradox." Provided access and expertise for the IRS administrative data linkage (contract TIRNO-16-E-00013 with the Statistics of Income Division of IRS) that underlies both studies.
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