Looking ahead: Forecasting total energy carbon dioxide emissions
In recent years, the international community has been increasing its efforts to reduce the human footprint on air pollution and global warming. Total carbon dioxide (CO2) releases are a crucial component of global greenhouse gas emissions, and as such, they are closely monitored at the national and...
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ftdoajarticles:oai:doaj.org/article:c2462eddcc6a42708da866991aeac747 2023-06-11T04:06:43+02:00 Looking ahead: Forecasting total energy carbon dioxide emissions Bernardina Algieri Leonardo Iania Arturo Leccadito 2023-06-01T00:00:00Z https://doi.org/10.1016/j.cesys.2023.100112 https://doaj.org/article/c2462eddcc6a42708da866991aeac747 EN eng Elsevier http://www.sciencedirect.com/science/article/pii/S2666789423000065 https://doaj.org/toc/2666-7894 2666-7894 doi:10.1016/j.cesys.2023.100112 https://doaj.org/article/c2462eddcc6a42708da866991aeac747 Cleaner Environmental Systems, Vol 9, Iss , Pp 100112- (2023) C53 C55 E71 Q47 Q53 Environmental effects of industries and plants TD194-195 article 2023 ftdoajarticles https://doi.org/10.1016/j.cesys.2023.100112 2023-04-23T00:36:53Z In recent years, the international community has been increasing its efforts to reduce the human footprint on air pollution and global warming. Total carbon dioxide (CO2) releases are a crucial component of global greenhouse gas emissions, and as such, they are closely monitored at the national and supranational levels. This study presents different models to forecast energy CO2 emissions for the US in the period 1972–2021, using quarterly observations. In an in-sample and out-of-sample analysis, the study assesses the accuracy of thirteen forecasting models (and their combinations), considering an extensive set of potential predictors (more than 260) that include macroeconomic, nature-related factors and different survey data and compares them to traditional benchmarks. To reduce the high-dimensionality of the potential predictors, the study uses a new class of factor models in addition to the classical principal component analysis. The results show that economic variables, market sentiment and nature-related indicators, especially drought and Antarctic wind indicators, help forecast short/medium-term CO2 emissions. In addition, some combinations of models tend to improve out-of-sample predictions. Article in Journal/Newspaper Antarc* Antarctic Directory of Open Access Journals: DOAJ Articles Antarctic Cleaner Environmental Systems 9 100112 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
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English |
topic |
C53 C55 E71 Q47 Q53 Environmental effects of industries and plants TD194-195 |
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C53 C55 E71 Q47 Q53 Environmental effects of industries and plants TD194-195 Bernardina Algieri Leonardo Iania Arturo Leccadito Looking ahead: Forecasting total energy carbon dioxide emissions |
topic_facet |
C53 C55 E71 Q47 Q53 Environmental effects of industries and plants TD194-195 |
description |
In recent years, the international community has been increasing its efforts to reduce the human footprint on air pollution and global warming. Total carbon dioxide (CO2) releases are a crucial component of global greenhouse gas emissions, and as such, they are closely monitored at the national and supranational levels. This study presents different models to forecast energy CO2 emissions for the US in the period 1972–2021, using quarterly observations. In an in-sample and out-of-sample analysis, the study assesses the accuracy of thirteen forecasting models (and their combinations), considering an extensive set of potential predictors (more than 260) that include macroeconomic, nature-related factors and different survey data and compares them to traditional benchmarks. To reduce the high-dimensionality of the potential predictors, the study uses a new class of factor models in addition to the classical principal component analysis. The results show that economic variables, market sentiment and nature-related indicators, especially drought and Antarctic wind indicators, help forecast short/medium-term CO2 emissions. In addition, some combinations of models tend to improve out-of-sample predictions. |
format |
Article in Journal/Newspaper |
author |
Bernardina Algieri Leonardo Iania Arturo Leccadito |
author_facet |
Bernardina Algieri Leonardo Iania Arturo Leccadito |
author_sort |
Bernardina Algieri |
title |
Looking ahead: Forecasting total energy carbon dioxide emissions |
title_short |
Looking ahead: Forecasting total energy carbon dioxide emissions |
title_full |
Looking ahead: Forecasting total energy carbon dioxide emissions |
title_fullStr |
Looking ahead: Forecasting total energy carbon dioxide emissions |
title_full_unstemmed |
Looking ahead: Forecasting total energy carbon dioxide emissions |
title_sort |
looking ahead: forecasting total energy carbon dioxide emissions |
publisher |
Elsevier |
publishDate |
2023 |
url |
https://doi.org/10.1016/j.cesys.2023.100112 https://doaj.org/article/c2462eddcc6a42708da866991aeac747 |
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Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_source |
Cleaner Environmental Systems, Vol 9, Iss , Pp 100112- (2023) |
op_relation |
http://www.sciencedirect.com/science/article/pii/S2666789423000065 https://doaj.org/toc/2666-7894 2666-7894 doi:10.1016/j.cesys.2023.100112 https://doaj.org/article/c2462eddcc6a42708da866991aeac747 |
op_doi |
https://doi.org/10.1016/j.cesys.2023.100112 |
container_title |
Cleaner Environmental Systems |
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9 |
container_start_page |
100112 |
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1768378802989170688 |