Working Paper: NBER ID: w28617
Authors: Jonas E. Arias; Jess Fernández-Villaverde; Juan Rubio-Ramirez; Minchul Shin
Abstract: We assess the causal impact of epidemic-induced lockdowns on health and macroeconomic outcomes and measure the trade-off between containing the spread of an epidemic and economic activity. To do so, we estimate an epidemiological model with time-varying parameters and use its output as information for estimating SVARs and LPs that quantify the causal effects of nonpharmaceutical policy interventions. We apply our approach to Belgian data for the COVID-19 epidemic during 2020. We find that additional government-mandated mobility curtailments would have reduced deaths at a very small cost in terms of GDP.
Keywords: Epidemic; Lockdown Policies; Health Outcomes; Macroeconomic Outcomes; Causal Analysis
JEL Codes: C1; C5; I1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Positive stringency shock (increase in the Oxford stringency index by one unit) (C54) | Fewer deaths in Belgium (approximately 1,000 fewer deaths after two months) (I14) |
| High level of government stringency (H19) | Saved lives (up to 250 lives in the first two weeks following a reproduction shock) (J17) |
| Stringent lockdown measures (H12) | Higher economic activity in the long run (O49) |