The COVID-19 Shock: A Bayesian Approach

The coronavirus crisis that started in December 2019 was declared a pandemic by March 2020 and had devastating global consequences. spread of the virus led to implementation different preventive measures prior availability effective vaccines. While many governments implemented lockdowns counter pandemic, others did not let halt economic activity. In this paper, we use Bayesian Vector Autoregressive framework study effects on prices, unemployment rates, interest rates nine countries took distinctive approaches tackling where introduce as shocks unemployment. Based impulse response functions, find most rate rose, fell or turned negative, prices initially following lockdown measures. However, massive fiscal monetary stimulus packages counteract reversed some variables, suggesting models with explicit recognition such should be developed.