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Representation and Hesitancy in Population Health Research: Evidence from a COVID-19 Antibody Study

Author

Listed:
  • Deniz Dutz
  • Michael Greenstone
  • Ali Hortaçsu
  • Santiago Lacouture
  • Magne Mogstad
  • Azeem M. Shaikh
  • Alexander Torgovitsky
  • Winnie van Dijk

Abstract

We examine why minority and poor households are often underrepresented in studies that require active participation. Using data from a serological study with randomized participation incentives, we find large participation gaps by race and income when incentives are low, but not when incentives are high. We develop a framework for using randomized incentives to disentangle the roles of hesitancy and non-contact in driving the participation gaps, and find that hesitancy is the predominant factor. Hesitancy rates strongly correlate with hospitalization rates and COVID-19 risk, suggesting that individuals facing higher health risks may be underrepresented in studies with low incentives.

Suggested Citation

  • Deniz Dutz & Michael Greenstone & Ali Hortaçsu & Santiago Lacouture & Magne Mogstad & Azeem M. Shaikh & Alexander Torgovitsky & Winnie van Dijk, 2023. "Representation and Hesitancy in Population Health Research: Evidence from a COVID-19 Antibody Study," NBER Working Papers 30880, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:30880
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    References listed on IDEAS

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    1. Karl M. Aspelund & Michael C. Droste & James H. Stock & Christopher D. Walker, 2020. "Identification and Estimation of Undetected COVID-19 Cases Using Testing Data from Iceland," NBER Working Papers 27528, National Bureau of Economic Research, Inc.
    2. Moffitt, Robert, 1983. "An Economic Model of Welfare Stigma," American Economic Review, American Economic Association, vol. 73(5), pages 1023-1035, December.
    3. Ioannidis, John P.A. & Cripps, Sally & Tanner, Martin A., 2022. "Forecasting for COVID-19 has failed," International Journal of Forecasting, Elsevier, vol. 38(2), pages 423-438.
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    More about this item

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • I1 - Health, Education, and Welfare - - Health
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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