Using an Ensemble of Machine Learning Algorithms to Predict Economic Recession

Q4 Business, Management and Accounting Journal of Risk and Financial Management Pub Date : 2024-09-01 DOI:10.3390/jrfm17090387
Leakey Omolo, Nguyet Nguyen
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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.
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使用机器学习算法组合预测经济衰退
COVID-19 大流行病和当前一些国家的战争给全球经济带来了巨大压力。美国面临的挑战不仅包括经济因素、重大干扰和供应链重组,还包括国家安全和全球地缘政治。这种前所未有的形势使得预测未来几年的经济危机变得至关重要而又充满挑战。在本文中,我们提出了一种基于各种机器学习模型的方法,用于预测明年美国经济衰退的概率。我们收集了美国从 1983 年 1 月到 2023 年 12 月的月度宏观经济指标和经济衰退数据,以预测 2024 年经济衰退的概率。我们分别预测了各个经济指标在未来一年的表现,然后利用所有预测指标来预测可能出现的经济衰退。结果表明,美国在 2024 年最后一个季度陷入经济衰退的概率很高。
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来源期刊
CiteScore
4.50
自引率
0.00%
发文量
512
审稿时长
11 weeks
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