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Employer Reallocation During the COVID-19 Pandemic: Validation and Application of a Do-It-Yourself CPS

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  • Bick, Alexander
  • Blandin, Adam

Abstract

Economists have recently begun using independent online surveys to collect national labor market data. Questions remain over the quality of such data. This paper provides an approach to address these concerns. Our case study is the Real-Time Population Survey (RPS), a novel online survey of the US built around the Current Population Survey (CPS). The RPS replicates core components of the CPS, ensuring comparable measures that allow us to weight and rigorously validate our results using a high-quality benchmark. At the same time, special questions in the RPS yield novel information regarding employer reallocation during the COVID-19 pandemic. We document that 26% of pre-pandemic workers were working for a new employer one year into the COVID-19 outbreak in the US, at least double the rate of any previous episode in the past quarter century. Our discussion contains practical suggestions for the design of novel labor market surveys and highlights other promising applications of our methodology.

Suggested Citation

  • Bick, Alexander & Blandin, Adam, 2022. "Employer Reallocation During the COVID-19 Pandemic: Validation and Application of a Do-It-Yourself CPS," CEPR Discussion Papers 17288, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:17288
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    Cited by:

    1. is not listed on IDEAS
    2. Alexander Bick & Adam Blandin & David Deming, 2023. "The Rapid Adoption of Generative AI," On the Economy 98843, Federal Reserve Bank of St. Louis.
    3. Bick, Alexander & Blandin, Adam & Mertens, Karel & Rubinton, Hannah, 2024. "Work from Home and Interstate Migration," CEPR Discussion Papers 19101, C.E.P.R. Discussion Papers.
    4. Alexander Bick & Adam Blandin & Aidan Caplan & Tristan Caplan, 2025. "Measuring Trends in Work from Home: Evidence from Six U.S. Datasets," Review, Federal Reserve Bank of St. Louis, vol. 107(15), pages 1-23, October.
    5. Alexander Bick & Adam Blandin & Aidan Caplan & Tristan Caplan, 2025. "Heterogeneity in Work from Home: Evidence from Six U.S. Datasets," Review, Federal Reserve Bank of St. Louis, vol. 107(14), pages 1-23, October.
    6. Mohimont, Jolan & de Sola Perea, Maite & Zachary, Marie-Denise, 2024. "Softening the blow: Job retention schemes in the pandemic," Journal of Public Economics, Elsevier, vol. 238(C).

    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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