Climate Policy Uncertainty and the Forecastability of Inflation

Afees Salisu, Ahamuefula Ogbonna, Rangan Gupta () and Yunhan Zhang ()
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Ahamuefula Ogbonna: Centre for Econometrics & Applied Research, Ibadan, Nigeria
Rangan Gupta: Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa
Yunhan Zhang: Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China

No 202525, Working Papers from University of Pretoria, Department of Economics

Abstract: We investigate the predictive content of climate policy uncertainty (CPU) for forecasting the inflation rate of the United States (US) over the monthly period of 1987:05 to 2024:11. We evaluate the performance of our proposed CPU-based predictive model, estimated via the Feasible Quasi Generalized Least Squares (FQGLS) approach, against a historical average benchmark model, with the FQGLS technique adopted to account for heteroscedasticity and autocorrelation in the data. We find statistical evidence in favor of a CPU-based model relative to the benchmark, as well as in case of an extended model involving physical risks of climate change and financial and macroeconomic factors, extracted from a large data set, when CPU is included. The predictive superiority of climate policy-related uncertainties relative to the historical mean continues to be robust under alternative local and global metrics of CPU, as well as in a mixed-frequency set-up, given the availability of high-frequency (weekly) CPU data. Moreover, the importance of local- and global-CPUs is also found to hold in forecasting the inflation rates of 11 other advanced and emerging countries in a statistically significant manner compared to the historical average model. Though across all the 12 economies, own- and global-CPUs perform equally well in forecasting the respective inflation rates. The general importance of uncertainties surrounding policy decisions to tackle climate change in shaping the future path of inflation, understandably, carries implications for the monetary authority.

Keywords: Climate Policy Uncertainty; Inflation; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 E31 E37 Q54 (search for similar items in EconPapers)
Pages: 21 pages
Date: 2025-08
New Economics Papers: this item is included in nep-for and nep-mon
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