Project

Resilience of communities in Mexico during COVID-19

MIT Human Dynamics

In this project we seek to combine data sources to understand the effect of the shock of COVID-19 as well as the recovery dynamics.  We combine data from: 

  • Transactions of credit and debit cards at the aggregate level by Municipality, gender, salary, week and category of transaction.
  • COVID-19 trends in Mexico at the municipal level.
  • Employment trends in Mexico aggregated at the municipal, gender, salary level, and employer size, each month.
  • Mobility data at the municipal daily level

Some questions we want to answer are: what determined which municipalities had higher shocks in terms of expenditure and employment during COVID-19. What determined the rate of recovery? What are some expected long term changes in the expenditure/ employment sectors?

So far we have observed that the reduction in mobility and expenditure was mainly driven by people's capacity to stay at home. This resulted in higher reductions in expenditure from people with higher income. The worst employment shocks are observed in services such as food and tourism. Moreover, in places where more people reduced their expenditure in such services, employ… View full description

In this project we seek to combine data sources to understand the effect of the shock of COVID-19 as well as the recovery dynamics.  We combine data from: 

  • Transactions of credit and debit cards at the aggregate level by Municipality, gender, salary, week and category of transaction.
  • COVID-19 trends in Mexico at the municipal level.
  • Employment trends in Mexico aggregated at the municipal, gender, salary level, and employer size, each month.
  • Mobility data at the municipal daily level

Some questions we want to answer are: what determined which municipalities had higher shocks in terms of expenditure and employment during COVID-19. What determined the rate of recovery? What are some expected long term changes in the expenditure/ employment sectors?

So far we have observed that the reduction in mobility and expenditure was mainly driven by people's capacity to stay at home. This resulted in higher reductions in expenditure from people with higher income. The worst employment shocks are observed in services such as food and tourism. Moreover, in places where more people reduced their expenditure in such services, employment in those same sectors was hit harder.  Finally, the employment shocks were harder for people with lower salaries, and working in mid-sized  (250-1000 employees) companies.