Forecasting recovery from COVID-19 using financial data: An application to Viet Nam - Jesse Lastunen; Matteo Richiardi (University of Essex, Centre for Microsimulation and Policy Analysis (CeMPA), 2021)
We develop a new methodology to nowcast the effects of the COVID-19 crisis and forecast its evolution in small, export-oriented countries. To this aim, we exploit variation in financial indexes at the industry level and relate them to the expected duration of the crisis for each industry, under the assumption that the main shocks to financial prices in recent months have come from COVID-19. Starting from the latest information available on the size of the shock at the industry level, often a few months old, we predict the ensuing recovery trajectories using the most recent financial data available, monitoring how subsequent waves of infections and information about new vaccines have impacted expectations about the future. We apply our method to Viet Nam, one of the most open economies in the world, and obtain predictions that are close to (though more optimistic than) later projections by the International Monetary Fund and other international forecasters. Our claim is that this better-than-expected performance was visible in stock market data early on but was largely missed by conventional methods. The Vietnamese application hence supports the validity of our method, showing that financial information can be used to accurately nowcast recovery paths following a large economic shock such as a global pandemic.
Keywords: 330; Finance; Economics; Covid-19; Health; Microsimulation