TITLE:
Economic Recession Forecasts Using Machine Learning Models Based on the Evidence from the COVID-19 Pandemic
AUTHORS:
Yuhuan Huang, Erik S. Yan
KEYWORDS:
Economic Recession, COVID-19, Machine Learning Applications, US, Italy
JOURNAL NAME:
Modern Economy,
Vol.14 No.7,
July
17,
2023
ABSTRACT: This paper focuses on the use of machine
learning models to forecast economic recessions caused by incidents such as the
COVID-19 pandemic. Relevant economic variables are selected to fit into the
VAR, SVR, Random Forest, and LSTM models. The study examines the cases of the
US and Italy, analyzing how the models predict the Euro crisis, 2008 Financial
Crisis, and the economic recession induced by COVID-19. Evaluations and
comparisons among these models and cases are made to determine appropriate
models. Additionally, an analysis based on US 2020 mobility data is applied to
demonstrate the difference in economic activities between normal and crisis
times.