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Climate Policy Uncertainty and Financial Stress: Evidence for China

Rangan Gupta, Qiang Ji () and Christian Pierdzioch
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Qiang Ji: Institutes of Science and Development, Chinese Academy of Sciences, Beijing, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing, China

No 202428, Working Papers from University of Pretoria, Department of Economics

Abstract: Focusing on China, we study the predictive value of Chinese climate policy uncertainty (CCPU) for subsequent stress in China’s financial markets in a sample of daily data running from October 2006 to December 2022. We control for the impact of international spillover effects of financial stress originating in the European Union (EU), the United Kingdom (UK), and the United States (US), and also for a large number of other important macroeconomic, financial, behavioral variables. Given the large number of predictors, we use random forests, an ensemble machine-learning technique, to trace out the impact of CCPU on financial stress by means of an out-of-sample forecasting experiment. We find that CCPU has predictive value for subsequent financial stress, and that its predictive power is stronger than that of measures of global climate risk. Its predictive value is strongest at a short (daily) forecast horizon and tends to decrease when the length of the forecast horizon increases. Moreover, we document the predictive value of CCPU across a spectrum of conditional quantiles of financial stress.

Keywords: Financial stress; Climate risks; China; Random forests; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C32 C53 G15 Q54 (search for similar items in EconPapers)
Pages: 38 pages
Date: 2024-06
New Economics Papers: this item is included in nep-big, nep-cna, nep-ene, nep-env and nep-eur
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