Cargando…

An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan

Carbon dioxide (CO(2)) emissions have become a critical aspect of the economic and sustainable development indicators of every country. In Pakistan, where there is a substantial increase in the population, industrialization, and demand for electricity production from different resources, the fear of...

Descripción completa

Detalles Bibliográficos
Autores principales: Daniyal, Muhammad, Tawiah, Kassim, Qureshi, Moiz, Haseeb, Mohammad, Asosega, Killian Asampana, Kamal, Mustafa, Rehman, Masood ur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10212093/
https://www.ncbi.nlm.nih.gov/pubmed/37228064
http://dx.doi.org/10.1371/journal.pone.0285854
_version_ 1785047391527763968
author Daniyal, Muhammad
Tawiah, Kassim
Qureshi, Moiz
Haseeb, Mohammad
Asosega, Killian Asampana
Kamal, Mustafa
Rehman, Masood ur
author_facet Daniyal, Muhammad
Tawiah, Kassim
Qureshi, Moiz
Haseeb, Mohammad
Asosega, Killian Asampana
Kamal, Mustafa
Rehman, Masood ur
author_sort Daniyal, Muhammad
collection PubMed
description Carbon dioxide (CO(2)) emissions have become a critical aspect of the economic and sustainable development indicators of every country. In Pakistan, where there is a substantial increase in the population, industrialization, and demand for electricity production from different resources, the fear of an increase in CO(2) emissions cannot be ignored. This study explores the link that betwixt CO(2) emissions with different significant economic indicators in Pakistan from 1960 to 2018 using the autoregressive distributed lag (ARDL) modelling technique. We implemented the covariance proportion, coefficient of determination, the Durbin Watson D statistics, analysis of variance (ANOVA), variance inflating factor (VIF), the Breusch-Pagan test, the Theil’s inequality, the root mean quare error (RMSE), the mean absolute percentage error (MAPE), and the mean absolute error (MAE) for the diagnostics, efficiency, and validity of our model. Our results showed a significant association between increased CO(2) emissions and increased electricity production from oil, gas, and other sources. An increase in electricity production from coal resources was seen to have resulted in a decrease in CO(2) emissions. We observed that an increase in the gross domestic product (GDP) and population growth significantly contributed to the increased CO(2) emissions. The increment in CO(2) emissions resulting from industrial growth was not significant. The increment in CO(2) emissions in the contemporary year is significantly associated with the preceding year’s increase. The rate of increase was very alarming, a sign that no serious efforts have been channelled in this regard to reduce this phenomenon. We call for policy dialogue to devise energy-saving and CO(2) emission reduction strategies to minimize the impact of climate change on industrialization, population growth, and GDP growth without deterring economic and human growth. Electricity production from different sources with no or minimal CO(2) emissions should be adopted. We also recommend rigorous tree planting nationwide to help reduce the concentration of CO(2) in the atmosphere as well as environmental pollution.
format Online
Article
Text
id pubmed-10212093
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-102120932023-05-26 An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan Daniyal, Muhammad Tawiah, Kassim Qureshi, Moiz Haseeb, Mohammad Asosega, Killian Asampana Kamal, Mustafa Rehman, Masood ur PLoS One Research Article Carbon dioxide (CO(2)) emissions have become a critical aspect of the economic and sustainable development indicators of every country. In Pakistan, where there is a substantial increase in the population, industrialization, and demand for electricity production from different resources, the fear of an increase in CO(2) emissions cannot be ignored. This study explores the link that betwixt CO(2) emissions with different significant economic indicators in Pakistan from 1960 to 2018 using the autoregressive distributed lag (ARDL) modelling technique. We implemented the covariance proportion, coefficient of determination, the Durbin Watson D statistics, analysis of variance (ANOVA), variance inflating factor (VIF), the Breusch-Pagan test, the Theil’s inequality, the root mean quare error (RMSE), the mean absolute percentage error (MAPE), and the mean absolute error (MAE) for the diagnostics, efficiency, and validity of our model. Our results showed a significant association between increased CO(2) emissions and increased electricity production from oil, gas, and other sources. An increase in electricity production from coal resources was seen to have resulted in a decrease in CO(2) emissions. We observed that an increase in the gross domestic product (GDP) and population growth significantly contributed to the increased CO(2) emissions. The increment in CO(2) emissions resulting from industrial growth was not significant. The increment in CO(2) emissions in the contemporary year is significantly associated with the preceding year’s increase. The rate of increase was very alarming, a sign that no serious efforts have been channelled in this regard to reduce this phenomenon. We call for policy dialogue to devise energy-saving and CO(2) emission reduction strategies to minimize the impact of climate change on industrialization, population growth, and GDP growth without deterring economic and human growth. Electricity production from different sources with no or minimal CO(2) emissions should be adopted. We also recommend rigorous tree planting nationwide to help reduce the concentration of CO(2) in the atmosphere as well as environmental pollution. Public Library of Science 2023-05-25 /pmc/articles/PMC10212093/ /pubmed/37228064 http://dx.doi.org/10.1371/journal.pone.0285854 Text en © 2023 Daniyal et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Daniyal, Muhammad
Tawiah, Kassim
Qureshi, Moiz
Haseeb, Mohammad
Asosega, Killian Asampana
Kamal, Mustafa
Rehman, Masood ur
An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan
title An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan
title_full An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan
title_fullStr An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan
title_full_unstemmed An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan
title_short An autoregressive distributed lag approach for estimating the nexus between CO(2) emissions and economic determinants in Pakistan
title_sort autoregressive distributed lag approach for estimating the nexus between co(2) emissions and economic determinants in pakistan
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10212093/
https://www.ncbi.nlm.nih.gov/pubmed/37228064
http://dx.doi.org/10.1371/journal.pone.0285854
work_keys_str_mv AT daniyalmuhammad anautoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT tawiahkassim anautoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT qureshimoiz anautoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT haseebmohammad anautoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT asosegakillianasampana anautoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT kamalmustafa anautoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT rehmanmasoodur anautoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT daniyalmuhammad autoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT tawiahkassim autoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT qureshimoiz autoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT haseebmohammad autoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT asosegakillianasampana autoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT kamalmustafa autoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan
AT rehmanmasoodur autoregressivedistributedlagapproachforestimatingthenexusbetweenco2emissionsandeconomicdeterminantsinpakistan