Using an Ensemble of Machine Learning Algorithms to Predict Economic Recession

The COVID-19 pandemic and the current wars in some countries have put incredible pressure on the global economy. Challenges for the U.S. include not only economic factors, major disruptions, and reorganizations of supply chains, but also those of national security and global geopolitics. This unprecedented situation makes predicting economic crises for the coming years crucial yet challenging. In this paper, we propose a method based on various machine learning models to predict the probability of a recession for the U.S. economy in the next year. We collect the U.S.’s monthly macroeconomic indicators and recession data from January 1983 to December 2023 to predict the probability of an economic recession in 2024. The performance of the individual economic indicator for the coming year was predicted separately, and then all of the predicted indicators were used to forecast a possible economic recession. Our results showed that the U.S. will face a high probability of being in a recession period in the last quarter of 2024.

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Publication Details

Journal
Journal of risk and financial management
Published
2024-09-01
DOI
https://doi.org/10.3390/jrfm17090387
Citations
4
Primary Topic
Monetary Policy and Economic Impact
Type
article
Field-Weighted Citation Impact
3.31

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article

Using an Ensemble of Machine Learning Algorithms to Predict Economic Recession

Nguyet Nguyen, Leakey Omolo
4 citations
Journal of risk and financial management
Monetary Policy and Economic Impact
3.31
article

Using an Ensemble of Machine Learning Algorithms to Predict Economic Recession

Nguyet Nguyen, Leakey Omolo
article en
4 citations

Abstract

The COVID-19 pandemic and the current wars in some countries have put incredible pressure on the global economy. Challenges for the U.S. include not only economic factors, major disruptions, and reorganizations of supply chains, but also those of national security and global geopolitics. This unprecedented situation makes predicting economic crises for the coming years crucial yet challenging. In this paper, we propose a method based on various machine learning models to predict the probability of a recession for the U.S. economy in the next year. We collect the U.S.’s monthly macroeconomic indicators and recession data from January 1983 to December 2023 to predict the probability of an economic recession in 2024. The performance of the individual economic indicator for the coming year was predicted separately, and then all of the predicted indicators were used to forecast a possible economic recession. Our results showed that the U.S. will face a high probability of being in a recession period in the last quarter of 2024.

Journal of risk and financial managementVol. 17(9)
Youngstown State University (US)
Youngstown State University
Openalex Percentile: Top 7%
Monetary Policy and Economic Impact
3.31
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