BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Cory McCartan (NYU Center for Data Science) DTSTART:20240513T213000Z DTEND:20240513T223000Z DTSTAMP:20260506T225745Z UID:MathandDemoc/23 DESCRIPTION:Title: Estimating Racial Disparities When Race is Not Observed\nby Cory McCartan (NYU Center for Data Science) as part of NYU CDS Math and Democr acy Seminar\n\n\nAbstract\nDiscovering and quantifying racial disparities is critical to ensuring equitable distribution of public goods and servic es\, and building fair decision-making algorithms and processes.  But in many important contexts\, data about race is not available at the individu al level.  Methods exist to predict individuals' race from attributes lik e their name and location\, but these tools create their own set of  stat istical challenges\, which if not addressed can significantly understate or overstate the size of racial disparities.  This talk will discuss the se challenges and introduce new methodology to address them\, allowing fo r accurate inference of racial disparities in datasets without racial info rmation.  The authors have worked with the U.S. Treasury Department to ap ply the new method to millions of individual tax returns to estimate dispa rities in who claims the home mortgage interest deduction\, the most expe nsive individual deduction in the federal tax code.\n\nCory McCartan is a Faculty Fellow at CDS and will join the Penn State Department of Statistic s in July.  He works on methodological and applied problems in the socia l sciences\, including gerrymandering\, electoral reform\, privacy of publ ic data\, and racial disparities.\n LOCATION:https://researchseminars.org/talk/MathandDemoc/23/ END:VEVENT END:VCALENDAR