Working Paper: NBER ID: w28699
Authors: Fiona Burlig; Anant Sudarshan; Garrison Schlauch
Abstract: Domestic mobility restrictions to control the spread of COVID-19 are widespread in developing countries, and have trapped millions of migrant workers in hotspot cities. We show that bans can increase cumulative infections relative to a counterfactual sans restrictions. A SEIR model shows bans’ impacts are nonlinear in duration. We empirically test this hypothesis using a natural experiment in India as well as data from China, Indonesia, the Philippines, South Africa, and Kenya. Although very short and long restrictions limit the spread of disease, moderately lengthy restrictions substantially increase infections. This underscores the importance of considering duration in mobility-restricting policy decisions in developing countries.
Keywords: COVID-19; travel bans; SEIR model; natural experiment
JEL Codes: I18; J60; O12
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Short and long travel restrictions (Z38) | COVID-19 spread (I14) |
| Longer travel restrictions (Z38) | Probability of infected migrants (J11) |
| Infected migrants (F22) | Cumulative COVID-19 cases post-lifting bans (Y10) |
| Prolonged travel bans (F22) | Community transmission in rural sinks (R20) |
| Domestic travel bans duration (Z38) | COVID-19 infections (I14) |
| Moderately lengthy travel restrictions (Z38) | Cumulative infections (I12) |