Dean Fantazzini: «Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries»

Scientific journal of applied econometrics: «Applied Econometrics» published an article by Dean Fantazzini, (Professor of the Department of econometrics and mathematical methods of Economics, Moscow state University): “Short-term forecasting of the COVID-19 pandemic using Google Trends data: Evidence from 158 countries».

Abstract:

The ability of Google Trends data to forecast the number of new daily cases and deaths of COVID-19 is examined using a dataset of 158 countries. The analysis includes the computations of lag correlations between confirmed cases and Google data, Granger causality tests, and an out-of-sample forecasting exercise with 18 competing models with a forecast horizon of 14 days ahead. This evidence shows that Google-augmented models outperform the competing models for most of the countries. This is significant because Google data can complement epidemiological models during difficult times like the ongoing COVID-19 pandemic, when official statistics maybe not fully reliable and/or published with a delay. Moreover, real-time tracking with online-data is one of the instruments that can be used to keep the situation under control when national lockdowns are lifted and economies gradually reopen.

This paper is dedicated to the memory of Dean Fantazzini’s mother Maria Pirazzini, who passed away at Imola hospital in Italy on 16/07/2020.