Data and Code for: Sectoral Effects of Social Distancing

Principal Investigator(s):  View help for Principal Investigator(s) Jean-Noel Barrot, HEC Paris, CEPR; Basile Grassi, Bocconi University, CEPR; Julien Sauvagnat, Bocconi University, CEPR

Version:  View help for Version V1

Name File Type Size Last Modified
  Replication-AEAPP 04/27/2021 08:49:AM

Project Citation: 

Barrot, Jean-Noel, Grassi, Basile, and Sauvagnat, Julien. Data and Code for: Sectoral Effects of Social Distancing. Nashville, TN: American Economic Association [publisher], 2021. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-05-05. https://doi.org/10.3886/E138901V1

Project Description

Summary:  View help for Summary The outbreak of the Covid-19 virus has led many states to take drastic measures of social distancing. Using US executive order, occupation and survey data, we measure the fall in labor supply due to these measure. Starting from a model of production networks, we analyze the sectoral effects of these labor shocks for the United States. We find that non-linearities in the production network account for around half of the drop in GDP associated to the implementation of social distancing measures. The model also generates realistic dispersion in sectoral output change. We provide here the replication package to construct the fall in labor supply, the figures and tables of the paper, and, to solve our model of production network.

Scope of Project

JEL Classification:  View help for JEL Classification
      E10 General Aggregative Models: General
      E23 Macroeconomics: Production
      E27 Macroeconomics: Consumption, Saving, Production, Employment, and Investment: Forecasting and Simulation: Models and Applications
      E65 Studies of Particular Policy Episodes
      J22 Time Allocation and Labor Supply
Geographic Coverage:  View help for Geographic Coverage USA
Time Period(s):  View help for Time Period(s) 2020 – 2020 (Covid Outbreak 2020)


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V1 [2021-05-05]

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