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The Work-from-Home Technology Boon and its Consequences


  • Morris A. Davis
  • Andra C. Ghent
  • Jesse M. Gregory


We study the impact of widespread adoption of work-from-home (WFH) technology using an equilibrium model where people choose where to live, how to allocate their time between working at home and at the office, and how much space to use in production. A key parameter is the elasticity of substitution between working at home and in the office that we estimate using cross-sectional time-use data. The model indicates that the pandemic induced a large change to the relative productivity of working at home which will permanently affect incomes, income inequality, and city structure.

Suggested Citation

  • Morris A. Davis & Andra C. Ghent & Jesse M. Gregory, 2021. "The Work-from-Home Technology Boon and its Consequences," NBER Working Papers 28461, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:28461
    Note: AP EFG LS

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    References listed on IDEAS

    1. Iris Arbogast & Charles S. Gascon & Andrew Spewak, 2019. "Working from Home: More Americans Are Telecommuting," The Regional Economist, Federal Reserve Bank of St. Louis, vol. 27(3).
    2. Barrero, Jose Maria & Bloom, Nick & Davis, Steven J., 2020. "Why Working From Home Will Stick," SocArXiv wfdbe, Center for Open Science.
    3. Leah Brooks & Byron Lutz, 2019. "Vestiges of Transit: Urban Persistence at a Microscale," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 385-399, July.
    4. Glaeser, Edward L. & Kahn, Matthew E. & Rappaport, Jordan, 2008. "Why do the poor live in cities The role of public transportation," Journal of Urban Economics, Elsevier, vol. 63(1), pages 1-24, January.
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    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Long-term consequences


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    Cited by:

    1. Liu, Sitian & Su, Yichen, 2021. "The impact of the COVID-19 pandemic on the demand for density: Evidence from the U.S. housing market," Economics Letters, Elsevier, vol. 207(C).
    2. Daiji Kawaguchi & Sagiri Kitao & Manabu Nose, 2021. "The impact of COVID-19 on Japanese firms: Mobility and resilience via remote work," CAMA Working Papers 2021-71, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. William D. Larson & Christos Makridis & Chad Redmer, 2021. "Borrower Expectations and Mortgage Performance: Evidence from the COVID-19 Pandemic," FHFA Staff Working Papers 21-02, Federal Housing Finance Agency.

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    More about this item

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R33 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Nonagricultural and Nonresidential Real Estate Markets

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