Uncertainty measures and business cycles : evidence from the US

Chen, Haining and Vitenu-Sackey, Prince Asare and Bathuure, Isaac Akpemah (2024) Uncertainty measures and business cycles : evidence from the US. Sage Open, 14 (2). pp. 1-20. ISSN 2158-2440 (https://doi.org/10.1177/21582440241240620)

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Abstract

Most of the macro-literature on uncertainty has focused on macro-uncertainty caused by real activity as a source of economic fluctuations. Economic uncertainty reduces total demand in the economy via a conventional channel that is associated with real option theory. Given the findings of the existing literature, financial uncertainty other than macroeconomic uncertainty matters more for business cycle fluctuations. This study seeks to answer the following questions: Is uncertainty the primary cause of the business cycle’s fluctuations? Alternatively, does it matter what kind of uncertainty exists? The research utilized the generalized linear model (GLM) and the Bayesian generalized linear model (BGLM) to analyze a dataset covering the time from July 1960 to April 2015 in the United States. Elevated levels of macroeconomic uncertainty, akin to real uncertainty, and economic policy uncertainty, as measured by news sources, demonstrate a counter-cyclical pattern in relation to business cycles. Low levels of uncertainty have a positive impact on business cycles, leading to an increase in industrial production. Conversely, high levels of uncertainty have a negative effect on business cycles, causing a decline in industrial output. We are of the opinion that high levels of macroeconomic uncertainty have a ripple effect on the entire economy, which may stifle investments, reduce consumption, and create unemployment, which is likely to influence labor participation.