Short-term Forecasting of the COVID-19 Pandemic using Google Trends Data: Evidence from 158 Countries

Applied Econometrics, Forthcoming

26 Pages Posted: 20 Aug 2020

See all articles by Dean Fantazzini

Dean Fantazzini

Moscow School of Economics, Moscow State University; National Research University Higher School of Economics

Date Written: August 10, 2020

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.

Note: Funding: The author gratefully acknowledges financial support from the grant of the Russian Science Foundation n. 20-68-47030.

Conflict of Interest: No conflict of interest to declare.

Keywords: COVID-19, Google Trends, VAR, ARIMA, ARIMA-X, ETS, LASSO, SIR model

JEL Classification: C22, C32, C51, C53, G17, I18, I19

Suggested Citation

Fantazzini, Dean, Short-term Forecasting of the COVID-19 Pandemic using Google Trends Data: Evidence from 158 Countries (August 10, 2020). Applied Econometrics, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3671005 or http://dx.doi.org/10.2139/ssrn.3671005

Dean Fantazzini (Contact Author)

Moscow School of Economics, Moscow State University ( email )

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HOME PAGE: https://sites.google.com/site/deanfantazzini/

National Research University Higher School of Economics ( email )

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HOME PAGE: http://www.hse.ru/org/persons/11532644

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