Data and Code for: Work from Home Before and After the COVID-19 Outbreak

Principal Investigator(s): View help for Principal Investigator(s) Karel Mertens, Federal Reserve Bank of Dallas; Adam Blandin, Vanderbilt University; Alexander Bick, Federal Reserve Bank of St. Louis

Version: View help for Version V1

Name	File Type	Size	Last Modified
Replication_files_for_AEJ_Macro			09/07/2023 07:38:AM

Project Citation:

Mertens, Karel, Blandin, Adam, and Bick, Alexander. Data and Code for: Work from Home Before and After the COVID-19 Outbreak. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-09-12. https://doi.org/10.3886/E181641V1

Project Description

Summary: Based on novel survey data, we document a persistent rise in work from home (WFH) over the course of the COVID-19 pandemic. Using theory and direct survey evidence, we argue that three quarters of this increase reflects adoption of new work arrangements that will likely be permanent for many workers. A quantitative model matched to survey data predicts that twice as many workers will WFH full-time post-pandemic compared to pre-pandemic, and that one in every five instead of seven workdays will be WFH. These model predictions are consistent with survey evidence on workers' own expectations about WFH in the future.

Funding Sources: Federal Reserve Bank of Dallas; Center for the Advanced Study in Economic Efficiency at ASU; Office of the Vice President for Research and Innovation at VCU

Scope of Project

Subject Terms: working from home; telecommuting; telework; remote work; Covid

JEL Classification:
      I18 Health: Government Policy; Regulation; Public Health
      J10 Demographic Economics: General
      J20 Demand and Supply of Labor: General
      J22 Time Allocation and Labor Supply
      R40 Transportation Economics: General

Geographic Coverage: US

Time Period(s): 2/1/2020 – 6/30/2021

Collection Date(s): 4/1/2020 – 6/30/2021

Universe: population of US adults aged 18 to 64

Data Type(s): aggregate data; survey data

Collection Notes:

For more details on the data collection, see Bick and Blandin (2022) (DOI: https://doi.org/10.1016/j.red.2022.11.002) and https://www.openicpsr.org/openicpsr/project/158081/version/V4/view.

Methodology

Sampling:

The RPS derives its sample from an online panel provided by Qualtrics.

The sample was targeted to be nationally representative for the U.S. for the age group 18-64 along several broad demographic characteristics: gender, age, race and ethnicity, education, marital status, number of children in the household, Census region, and household income in 2019.

The targets were based on the following categories: Age: 18-24, 25-34, 35-44, 45-54, 55-64; Race and ethnicity: non-Hispanic White, non-Hispanic Black, Hispanic, other; Education: high school or less, some college or associate degree, bachelor’s degree or more; Marital status: married or not; Number of children in the household: 0, 1, 2, 3 or more; Census region: Midwest, Northeast, South and West; Annual household income in 2019: <$50k, $50k-100k, >$100k.

Collection Mode(s): web-based survey

Weights: Sample weights were constructed using an iterative proportional fitting (raking) algorithm based on Deming and Stephan (1940) to match the distribution of initial targets, finer categories for some variables and interactions with sex. We provide two different sets of weights, which conditional on additional variables, for details and references see the readme file.

Unit(s) of Observation: Individuals and Couples

Geographic Unit: US States

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Published Versions

V1 [2023-09-12]

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