Data and Code for: Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks

Principal Investigator(s):  View help for Principal Investigator(s) Annika Camehl, Erasmus University Rotterdam; Malte Rieth, Martin-Luther-Universität Halle-Wittenberg and DIW Berlin

Version:  View help for Version V1

Name File Type Size Last Modified
  R 07/14/2022 07:39:AM
  data 12/20/2022 04:58:AM
  functions 12/20/2022 05:06:AM
  stata 12/20/2022 05:01:AM
README.pdf application/pdf 227.9 KB 11/14/2022 02:26:AM
appendix.m text/x-matlab 19.5 KB 12/19/2022 11:59:PM
main.m text/x-matlab 3.8 KB 11/14/2022 02:58:AM

Project Citation: 

Camehl, Annika, and Rieth, Malte. Data and Code for: Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks. 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/E175241V1

Project Description

Summary:  View help for Summary This is data and code accompanying the article Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks. We study the dynamic interaction between Covid-19, economic mobility, and containment policy. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through traditional and narrative sign restrictions. We find that incidence shocks and containment shocks have large and persistent effects on mobility, morbidity, and mortality that last for 1-2 months. These shocks are the main drivers of the pandemic, explaining between 20-60% of the average and historical variability in mobility, cases, and deaths worldwide. The policy tradeoff associated to non-pharmaceutical interventions is 1pp less economic mobility per day for 8% fewer deaths after three months.


Scope of Project

Subject Terms:  View help for Subject Terms Epidemics; non-pharmaceutical interventions; structural vector autoregressions; coronavirus; Bayesian analysis; panel data
JEL Classification:  View help for JEL Classification
      C32 Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
      E32 Business Fluctuations; Cycles
      I18 Health: Government Policy; Regulation; Public Health
Geographic Coverage:  View help for Geographic Coverage 44 countries: Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, Colombia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hong Kong, Hungary, India, Indonesia, Ireland, Israel, Italy, Japan, Lithuania, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Russia, Saudi Arabia, Slovenia, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey, United Arab Emirates, United Kingdom and United States.
Time Period(s):  View help for Time Period(s) 12/31/2019 – 8/17/2020
Universe:  View help for Universe Covid-19 cumulative death, Covid-19 cumulative cases, containment policy index, economic mobility index, stock prices small firms for all 44 countries
Data Type(s):  View help for Data Type(s) aggregate data

Methodology

Response Rate:  View help for Response Rate not applicable
Sampling:  View help for Sampling The 44 countries in the sample account for 81% of worldwide infections and deaths due to Covid-19 and for 72% of global GDP.
Data Source:  View help for Data Source Data are downloaded via Macrobond. 
  • Containment policy index; source: University of Oxford
  • Covid-19 cumulative deaths; source: World Health Organization
  • Covid-19 cumulative cases; source: World Health Organization
  • Total tests; source: Our World in Data
  • Economic mobility index; source: Google
  • MEI; source: Mobility and Engagement Index of Atkinson et al. (2020)
  • Real GDP; source: World Bank
  • Population; source: World Bank
  • Unemployment rate; source: World Bank
  • Stock prices small firms; source: MSCI
  • Stock prices large firms; source: MSCI
  • Weekly Economic Index; source: Leading Indicators, Federal Reserve Bank of New York
  • Event data; source: http://superspreadingdatabase.com
Collection Mode(s):  View help for Collection Mode(s) other
Scales:  View help for Scales not applicable
Weights:  View help for Weights not applicable
Unit(s) of Observation:  View help for Unit(s) of Observation daily data for 44 countries
Geographic Unit:  View help for Geographic Unit country

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Published Versions

V1 [2023-09-12]

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