Forecasting recovery from COVID-19 using financial data: An application to Vietnam

Abstract

We develop a new methodology to nowcast the effects of the COVID-19 crisis on GDP and forecast its evolution in small, export-oriented countries. To this aim, we exploit variation in financial indexes at the industry level in the early stages of the crisis and relate them to the expected duration of the crisis for each industry, under the assumption that the main shocks to financial prices in 2020 came from COVID-19. Starting from the latest official information available at different stages of the crisis on industry-level trend deviations of GDP, often a few months old, we predict the ensuing recovery trajectories using the most recent financial data available at the time of the prediction. The financial data reflect, among other things, how subsequent waves of infections and information about new vaccines have impacted expectations about the future. We apply our method to Vietnam, one of the most open economies in the world, and obtain predictions that are more optimistic than projections by the International Monetary Fund and other international forecasters, and closer to the realised figures. Our claim is that this better-than-expected performance was visible in stock market data early on but was largely missed by conventional forecasting methods.