Data and code for: Measuring Work from Home in the Cross Section

Principal Investigator(s):  View help for Principal Investigator(s) Augustus Kmetz, Federal Reserve Bank of San Francisco; John Mondragon, Federal Reserve Bank of San Francisco; Johannes Wieland, University of California, San Diego

Version:  View help for Version V1

Name File Type Size Last Modified
  acs2020errorcalculation 05/04/2023 12:58:PM
  aggregateACS 05/04/2023 12:58:PM
  bickerrorcalculation 05/04/2023 12:58:PM
  bloomerrorcalculation 05/04/2023 12:58:PM
  crosswalks 05/04/2023 12:58:PM
  dingel_neiman_teleworkability 05/04/2023 12:58:PM
  downloaddata 05/04/2023 12:58:PM
  externaldata 05/04/2023 12:58:PM
  papersandproceedings 05/04/2023 12:58:PM
  processACS 05/04/2023 12:58:PM

Project Citation: 

Kmetz, Augustus, Mondragon, John, and Wieland, Johannes. Data and code for: Measuring Work from Home in the Cross Section. Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-05-18. https://doi.org/10.3886/E190361V1

Project Description

Summary:  View help for Summary
The shift to work from home (WFH) has been a large and persistent consequence of the pan- demic. To quantify the effect of WFH on the macroeconomy, researchers have exploited the fact that local labor markets are differentially exposed to this shock, in either empirical or quantitative spatial settings. These analyses require a measure of WFH at disaggregated levels. In this paper, we compare several important measures used in the literature: Barrero, Bloom, and Davis (2021); Bick, Blandin, and Mertens (2022); Dingel and Neiman (2020); and the American Community Survey (ACS). While these measures differ in how comprehensively they measure WFH (e.g., they may or may not include hybrid work), we show that they are highly correlated in the cross section. Therefore, these measures will yield similar causal effects once appropriately scaled by the average level of WFH. We argue that when choosing a particular measure, researchers should carefully consider the trade-off between how comprehensively WFH is measured and measurement error in the survey at the particular level of geographic aggregation.

Scope of Project

Subject Terms:  View help for Subject Terms Work from home; local labor market; cross sectional analysis
JEL Classification:  View help for JEL Classification
      J22 Time Allocation and Labor Supply
      R10 General Regional Economics (includes Regional Data)
Geographic Coverage:  View help for Geographic Coverage National, State, CBSA
Time Period(s):  View help for Time Period(s) 1/1/2015 – 12/31/2022 (2015 through 2022)


Related Publications

Download this project

Published Versions

V1 [2023-05-18]

Export Metadata

Dublin Core

DDI 2.5

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.