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"Harnessing the Power: Academic and Government Collaborations to Use Administrative Data for Research and Policy Insights"

Professor Day Manoli, University of Texas at Austin
  • "Harnessing the Power: Academic and Government Collaborations to Use Administrative Data for Research and Policy Insights"
  • 2018-05-23T12:00:00-07:00
  • 2018-05-23T13:00:00-07:00
  • Professor Day Manoli, University of Texas at Austin
When
May 23, 2018 from 12:00 PM to 01:00 PM (America/Los_Angeles / UTC-700)
Where
1130 K Street, Room LL3
Contact Name
Contact Phone
916-445-5161
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In partnership with UCI Economic Self-Sufficiency Policy Research Institute

State and federal government agencies collect data to administer and evaluate a variety of government programs. As computing resources have become more sophisticated, academic researchers have developed novel strategies to analyze these large administrative datasets. Professor Manoli will discuss multiple examples from his research that involve collaborating with government agencies to conduct research using administrative data and gain insights that are relevant for government agencies and academic researchers. The research examples are based on collaborations with the IRS and US Treasury and examine outreach to increase tax filing and EITC participation, impacts of tax refunds on college enrollment and impacts of job search assistance on employment, tax filing and tax liability. Professor Manoli will also discuss practices to create sustainable collaborations between academic researchers and government agencies.

Day Manoli is an assistant professor in the Department of Economics at the University of Texas at Manoli PhotoAustin. Professor Manoli’s research focuses on empirical analyses to document and improve the impacts of government policies. His research interests include social security and retirement policy, income tax policy and education policy. In current and previous research projects, Professor Manoli has worked closely with private companies and government agencies to analyze data, test economic models and implement large-scale field experiments. He received his PhD in Economics from UC Berkeley.

 

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