Covid-19: Health or economy?

Topics

• Is there a trade off between economic and health outcomes?

Microsimulation model

• Which policies are effective in reducing the spread of Covid-19?
• What are the costs of these policies in terms of foregone output (value added) and employment?
• Who are the most effected by these policies?
• What could the government do to reduce the social and economic cost of Covid-19?

Covid-19 measures

• Stay-at-home rules (partial/general)
• Closing down businesses (restaurants, tourism, etc)
• Restricting certain (mass) activities (conferences, concerts, etc)
• Travel restrictions (local, national and international)
• Closing schools/on-line education
• Others
  • Testing and filiation
    
  • Masks, social distancing
  • Teleworking

Economic effects of Covid-19 measures

Short run

• Decline in output and employment
  • Closing down businesses
  • Reducing (consumption) expenditures
    • Uncertainty and restrictions
    • Increasing unemployment
      • Income support
  • Decline in investment
  • Decline in foreign demand (declining exports)

Economic effects of Covid-19 measures

Long term

• Depreciation of human capital
  • Health problems
  • Problems in education/access to on-line education
  • Increasing youth unemployment
• Declining investment
• Changes in consumer behavior
• Changes in the direction of technological change

Health vs economics

Economic effect: Level x Duration (-) Health effect: Level x Duration (+)

• Economic effects
  • Decline in value added and employment
  • Policy stringency index
  • Google mobility index
    • Workplace mobility, retail and recreation mobility, etc
• Health effects
  • Covid-19 deaths
  • Additional deaths
  • Case numbers

Summary

The microsimulation model

• Agents
  • About 500,000 individual representing whole population (about 80 million)
    • The number of unique individual in the model increases to 3-4 million during simulation
  • Household, age, gender, school, sector, occupation, formal/informal, working hours, region
  • 2017 Labor Survey Data
• Locations
  • Household: Household members
  • School: Students and the education sector employees in a given region (“region” is defined at NUTS 2-digit level).
  • Workplace: People employed in a given sector and region
  • Essential activities: All people living in a given region and those work in the “essential” sectors
  • Leisure activities: All people living in a given region and those work in the “leisure” sectors
  • Travel: All people

Modules

• Disease progression module
• Infection module
• Measures/policies module
• Production and employment module

Modul 2. Infection

• Individuals
  • pre-school, school, unemployed women, unemployed men, employed women, employed men
• Locations
  • home, school, workplace, essential activities, leisure activities, travel
• Each individual spends 16 hours per day in those locations
• The number of infected people in a given location in a day depends on
  • Time spent by susceptible people times
  • Time spent by infected people over
  • Time spent by all people (including recovered)
• In the case of essential and leisure activities, transmission probability depends the degree of contacts with customers [O*Net, “Deal With External Customers” data]
• For teleworking, Dingel and Neiman’s (2020) “work-at-home” data is used.

Module 3. Measures/policies

• Closing schools
• Stay-home rules for 65+ years old
• Stay-home rules for 20- years old
• Travel restrictions (regional and national)
• Nation-wide lockdown
• Closing businesses
• Quarantine and isolation rules
• Social distancing

These measures/restrictions change the time use of individuals.

We take into account quarantine and isolation rules and social distancing measures as well.

Module 4. Production and employment

• Economic effect of policies
  • Businesses closures -> decline in production and employment
    • Decline in demand for inputs (backward links)
    • Decline in households’ demand (income effect)
      • Income support by the government
    • Decline in investment and exports
• Use IO table to calculate these effects
  • For different categories of people (young/old, men/women, formal/informal, etc.)
  • For government finances (tax revenue - expenditures)

Parameter values

• Publications
• Calibration
  • Daily data on cases, deaths, and ICU numbers

Counterfactuals?

Policy responses and outcomes, March 18-May 31, 2020

Results

• There is no trade off between economy and health (in the case of Covid-19)
• Microsimulation is a useful tool
  • Which measures are effective?
  • What are the costs of measures?
  • Who are the most effected?
  • What could the government do?

Many thanks…