Forecasting total energy’s CO2 emissions

Leonardo Iania, Bernardina Algieri and Arturo Leccadito
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Arturo Leccadito: University of Calabria

No 2022003, LIDAM Discussion Papers LFIN from Université catholique de Louvain, Louvain Finance (LFIN)

Abstract: In recent years, the international community has been increasing its efforts to reduce the human footprint on air pollution and global warming. Total CO2 emissions are a key component of global emission, and as such, they are closely monitored by national and supranational entities. This study evaluates the performance of a broad set of forecasting models and their combinations to predict energy’s carbon dioxide releases using an in-sample and out-of-sample analysis. The focus is on the US for the period 1973-2021 using quarterly observations. The results show that economic variables, energy and interannual climate variability indicators help forecast short-/medium- term CO2 emissions. In addition, a combination of models sharpens quantile predictions.

Keywords: CO2 Emissions; Forecasting Models; Quantile Forecast; Economic, Energy and Nature- related drivers; Climate Change; Drought Severity; Interannual Variability (search for similar items in EconPapers)
JEL-codes: C01 C13 C31 C51 C52 C53 C55 C82 Q43 Q47 Q53 Q59 (search for similar items in EconPapers)
Pages: 58
Date: 2022-05-24
New Economics Papers: this item is included in nep-ene, nep-env and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:ajf:louvlf:2022003

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