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Activity Number:
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415
- Massive Administrative Data to Advance the Public Good
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 5, 2020 : 1:00 PM to 2:50 PM
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Sponsor:
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Social Statistics Section
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Abstract #313075
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Title:
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Massive Administrative Data to Advance the Public Good: Nudging Data-Based Exit Policy - Nearcasting Lessons from the Crucible of Pandemic Crisis
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Author(s):
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Asaph Young Chun* and Bruce Meyer*
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Companies:
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Statistics Research Institute - Statistics Korea and University of Chicago, Harris School of Public Policy
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Keywords:
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administrative data;
COVID-19;
pandemic;
Korea
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Abstract:
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Incorporation of administrative records has long been regarded as a way of advancing the quality of surveys as the rising cost of surveys is subject to harnessing. The extent and pace of using massive administrative data in survey statistics varies from continent to continent and from country to country. This paper illustrates the use of administrative epidemic data to nearcast and flatten the COVID-19 pandemic curve. It is among the panel of papers that provides best practices of using massive administrative data for advancing survey methodology or inform policymaking (Chun, Larsen, Reiter, Durrant, a forthcoming Wiley book).
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Authors who are presenting talks have a * after their name.
