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This paper explores the forecasting power of some of the most informative indicators of economic uncertainty on carbon emission price volatility. We use one- and two-component GARCH-MIDAS models based on mixed frequency data and Model Confidence Set (MCS) testing with ‘rolling scheme’ forecast method to examine the forecasting performance of economic uncertainty indicators. We employ an economic policy uncertainty (EPU) indicator with China, US and global economic policy uncertainty constituents together with traditional uncertainty indicators, such as macroeconomic and financial market volatility. Our empirical findings show that generally economic policy uncertainty indicators contain more information of carbon emission price volatility than other indicators. Specifically, one-component GARCH-MIDAS model with the EPU indicator with China constituent and two-component model with EPU indicator have superior performance in forecasting carbon emission price volatility of the Guangdong pilot in China. Our study adds insights into factors that affect carbon emission price movements.

applied economics

Does economic policy uncertainty outperform macroeconomic factor and financial market uncertainty in forecasting carbon emission price volatility? Evidence from China