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CO(2) emissions in Latin America: a time series perspective based on fractional integration
This article deals with the analysis of [Formula: see text] emissions in Latin America by using a long memory process based on fractional integration. Using data of [Formula: see text] emission and [Formula: see text] emissions per capita, for 32 Latin American and Caribbean countries, the results s...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10622371/ https://www.ncbi.nlm.nih.gov/pubmed/37776424 http://dx.doi.org/10.1007/s11356-023-29987-4 |
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author | Asturias-Schaub, Luis Rodrigo Gil-Alana, Luis Alberiko |
author_facet | Asturias-Schaub, Luis Rodrigo Gil-Alana, Luis Alberiko |
author_sort | Asturias-Schaub, Luis Rodrigo |
collection | PubMed |
description | This article deals with the analysis of [Formula: see text] emissions in Latin America by using a long memory process based on fractional integration. Using data of [Formula: see text] emission and [Formula: see text] emissions per capita, for 32 Latin American and Caribbean countries, the results show significant differences according to the variable examined, the model used, and the country under examination. In particular, for the [Formula: see text] emissions, mean reversion is found in Belize and also under some circumstances in Antigua and Barbuda, Colombia, Dominica, Dominican Republic, Ecuador, Grenada, Honduras, Nicaragua, Panama, Peru, and Uruguay. Thus, shocks in these series have a transitory effect. With respect to the time trends, only for some Caribbean countries, namely, Antigua and Barbuda, Aruba, Bahamas, Cuba, and Jamaica, the trend is insignificant; on the other hand, large countries like Brazil, Mexico, and Argentina display the highest time trend coefficients; for the [Formula: see text] emissions per capita, there are eleven countries where mean reversion is detected, and there are ten that share a lack of significance for the trend. The most significant trends now take place in Trinidad and Tobago, British Virgin Islands, Barbados, and Guyana. Policy implications of the results obtained are reported at the end of the paper. |
format | Online Article Text |
id | pubmed-10622371 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-106223712023-11-04 CO(2) emissions in Latin America: a time series perspective based on fractional integration Asturias-Schaub, Luis Rodrigo Gil-Alana, Luis Alberiko Environ Sci Pollut Res Int Research Article This article deals with the analysis of [Formula: see text] emissions in Latin America by using a long memory process based on fractional integration. Using data of [Formula: see text] emission and [Formula: see text] emissions per capita, for 32 Latin American and Caribbean countries, the results show significant differences according to the variable examined, the model used, and the country under examination. In particular, for the [Formula: see text] emissions, mean reversion is found in Belize and also under some circumstances in Antigua and Barbuda, Colombia, Dominica, Dominican Republic, Ecuador, Grenada, Honduras, Nicaragua, Panama, Peru, and Uruguay. Thus, shocks in these series have a transitory effect. With respect to the time trends, only for some Caribbean countries, namely, Antigua and Barbuda, Aruba, Bahamas, Cuba, and Jamaica, the trend is insignificant; on the other hand, large countries like Brazil, Mexico, and Argentina display the highest time trend coefficients; for the [Formula: see text] emissions per capita, there are eleven countries where mean reversion is detected, and there are ten that share a lack of significance for the trend. The most significant trends now take place in Trinidad and Tobago, British Virgin Islands, Barbados, and Guyana. Policy implications of the results obtained are reported at the end of the paper. Springer Berlin Heidelberg 2023-09-30 2023 /pmc/articles/PMC10622371/ /pubmed/37776424 http://dx.doi.org/10.1007/s11356-023-29987-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Asturias-Schaub, Luis Rodrigo Gil-Alana, Luis Alberiko CO(2) emissions in Latin America: a time series perspective based on fractional integration |
title | CO(2) emissions in Latin America: a time series perspective based on fractional integration |
title_full | CO(2) emissions in Latin America: a time series perspective based on fractional integration |
title_fullStr | CO(2) emissions in Latin America: a time series perspective based on fractional integration |
title_full_unstemmed | CO(2) emissions in Latin America: a time series perspective based on fractional integration |
title_short | CO(2) emissions in Latin America: a time series perspective based on fractional integration |
title_sort | co(2) emissions in latin america: a time series perspective based on fractional integration |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10622371/ https://www.ncbi.nlm.nih.gov/pubmed/37776424 http://dx.doi.org/10.1007/s11356-023-29987-4 |
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