Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster

Pradyot Jena, Ritanjali Majhi, Rajesh Kalli, Shunsuke Managi and Babita Majhi

Economic Analysis and Policy, 2021, vol. 69, issue C, 324-339

Abstract: The ongoing COVID-19 pandemic has caused global health impacts, and governments have restricted movements to a certain extent. Such restrictions have led to disruptions in economic activities. In this paper, the GDP figures for the April–June quarter of 2020 for eight countries, namely, the United States, Mexico, Germany, Italy, Spain, France, India, and Japan, are forecasted. Considering that artificial neural network models have higher forecasting accuracy than statistical methods, a multilayer artificial neural network model is developed in this paper. This model splits the dataset into two parts: the first with 80% of the observations and the second with 20%. The model then uses the first part to optimize the forecasting accuracy and then applies the optimized parameters to the second part of the dataset to assess the model performance. A forecasting error of less than 2% is achieved by the model during the testing procedure. The forecasted GDP figures show that the April–June quarter of the current year experienced sharp declines in GDP for all countries. Moreover, the annualized GDP growth is expected to reach double-digit negative growth rates. Such alarming prospects require urgent rescue actions by governments.

Keywords: Forecasting; GDP; Multilayer neural network; Mean absolute percentage error (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecanpo:v:69:y:2021:i:c:p:324-339

DOI: 10.1016/j.eap.2020.12.013

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