A global economic policy uncertainty index from principal component analysis

• Published in: Finance research letters Vol. 40; p. 101686
• Main Authors: Dai, Peng-Fei, Xiong, Xiong, Zhou, Wei-Xing
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.05.2021
• Subjects: Correlation; Economic policy uncertainty; Econophysics; Principal component analysis; Volatility; Econophysics; Correlation; Economic policy uncertainty; E66; Volatility; D80; Principal component analysis; G18
• ISSN: 1544-6123; 1544-6131
• DOI: 10.1016/j.frl.2020.101686

•We propose a global EPU index from principal component analysis.•The PCA-GEPU index is a good proxy for the EPU on a global scale.•The PCA-GEPU index is positively related with the volatility and correlation of the global financial market.•The stocks are more volatile and correlated when the GEPU is higher.•The PCA-GEPU index performs slightly better than the GDP-GEPU. This paper constructs a global economic policy uncertainty index through the principal component analysis of the economic policy uncertainty indices for twenty primary economies around the world. We find that the PCA-based global economic policy uncertainty index is a good proxy for the economic policy uncertainty on the global scale, which is quite consistent with the GDP-weighted global economic policy uncertainty index. The PCA-based economic policy uncertainty index is found to be positively related with the volatility and correlation of the global financial market, which indicates that the stock markets are more volatile and correlated when the global economic policy uncertainty is higher. The PCA-based global economic policy uncertainty index (T=24) performs slightly better because the relationships between the PCA-based uncertainty and market volatility and between the PCA-based uncertainty and market correlation are more significant.