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description Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Public Library of Science (PLoS) Authors: Mihaela Simionescu; Wadim Strielkowski; Nicolas Schneider; Luboš Smutka;With the EU Green Deal initiatives, European members seek to launch the first climate neutral continent by 2050. This paper assesses the stochastic convergence of per capita energy consumption series for an illustrative sample of 15 EU countries with memberships prior to the 2004 enlargement, using data spanning the 1970–2018 period. Results from the confidence interval subsampling (asymmetric and equal-tailed) highlight that 11 out of the 15 EU series exhibit a long-run memory behaviour, while a diverging pattern was observed for the UK, Germany, Portugal, and Italy. Finally, per capita energy use series persist but fail to reveal one of the above dynamics for Ireland and Spain. Also, findings from the non-parametric Bayesian application (ANOVA/linear Dependent Dirichlet Process (DDP) mixture model) show how economic growth operates as a converging energy consumption-enabler over the long-run, from which the EU membership cannot be excluded. In particular, we highlight how the nature of energy-GDP hypotheses vary with the stochastic properties of energy use (converging behaviour with temporary shocks, converging pattern with permanent shocks, and diverging dynamic). Finally, our conclusions overcome the well-established development stage argument as we claim that countries with similar energy convergence patterns may need to adopt similar energy policies.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 3 citations 3 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Public Library of Science (PLoS) Authors: Mihaela Simionescu; Wadim Strielkowski; Nicolas Schneider; Luboš Smutka;With the EU Green Deal initiatives, European members seek to launch the first climate neutral continent by 2050. This paper assesses the stochastic convergence of per capita energy consumption series for an illustrative sample of 15 EU countries with memberships prior to the 2004 enlargement, using data spanning the 1970–2018 period. Results from the confidence interval subsampling (asymmetric and equal-tailed) highlight that 11 out of the 15 EU series exhibit a long-run memory behaviour, while a diverging pattern was observed for the UK, Germany, Portugal, and Italy. Finally, per capita energy use series persist but fail to reveal one of the above dynamics for Ireland and Spain. Also, findings from the non-parametric Bayesian application (ANOVA/linear Dependent Dirichlet Process (DDP) mixture model) show how economic growth operates as a converging energy consumption-enabler over the long-run, from which the EU membership cannot be excluded. In particular, we highlight how the nature of energy-GDP hypotheses vary with the stochastic properties of energy use (converging behaviour with temporary shocks, converging pattern with permanent shocks, and diverging dynamic). Finally, our conclusions overcome the well-established development stage argument as we claim that countries with similar energy convergence patterns may need to adopt similar energy policies.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 3 citations 3 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Informa UK Limited Authors: COSIMO MAGAZZINO; Donatella Porrini; Giulio Fusco; Nicolas Schneider;handle: 11590/377771 , 11587/447274 , 11586/518843
This study investigates the relationship between Information and Communication Technology (ICT) penetration, electricity consumption, economic growth, and environmental pollution within a multivari...
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu84 citations 84 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Informa UK Limited Authors: COSIMO MAGAZZINO; Donatella Porrini; Giulio Fusco; Nicolas Schneider;handle: 11590/377771 , 11587/447274 , 11586/518843
This study investigates the relationship between Information and Communication Technology (ICT) penetration, electricity consumption, economic growth, and environmental pollution within a multivari...
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu84 citations 84 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Emerald Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;handle: 11590/390613
PurposeThe purpose of this paper is to empirically test the economic convergence that operate between five selected Asian countries (namely Thailand, Singapore, Malaysia, the Philippines and Indonesia). In particular, it seeks to investigate how increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN.Design/methodology/approachA new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index.FindingsThe Generalized Method of Moments (GMM) results highlight that the endogenous growth theory seems to be supported for the selected Asian countries, indicating evidence of diverging forces resulting from unequal growth and polarization dynamics. Overcoming the technical issues raised by the econometric approach, the new ML algorithm brings contrasted but interesting results. Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members.Originality/valueUsing the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. As a matter of fact, the new LSTM algorithm has provided consistent evidence supporting the existence of converging forces. In fact, the results highlighted the effectiveness of the experiments and the algorithm we chose. The high predictability of the authors’ model and the absence of self-alignment in the values showed a convergence be-tween the economies.
Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 3visibility views 3 download downloads 3 Powered bymore_vert Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Emerald Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;handle: 11590/390613
PurposeThe purpose of this paper is to empirically test the economic convergence that operate between five selected Asian countries (namely Thailand, Singapore, Malaysia, the Philippines and Indonesia). In particular, it seeks to investigate how increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN.Design/methodology/approachA new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index.FindingsThe Generalized Method of Moments (GMM) results highlight that the endogenous growth theory seems to be supported for the selected Asian countries, indicating evidence of diverging forces resulting from unequal growth and polarization dynamics. Overcoming the technical issues raised by the econometric approach, the new ML algorithm brings contrasted but interesting results. Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members.Originality/valueUsing the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. As a matter of fact, the new LSTM algorithm has provided consistent evidence supporting the existence of converging forces. In fact, the results highlighted the effectiveness of the experiments and the algorithm we chose. The high predictability of the authors’ model and the absence of self-alignment in the values showed a convergence be-tween the economies.
Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 3visibility views 3 download downloads 3 Powered bymore_vert Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Now Publishers Authors: COSIMO MAGAZZINO; Nicolas Schneider;doi: 10.1561/101.00000121
handle: 11590/373141
The Causal Relationship between Primary Energy Consumption and Economic Growth in Israel: A Multivariate Approach
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 4visibility views 4 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Now Publishers Authors: COSIMO MAGAZZINO; Nicolas Schneider;doi: 10.1561/101.00000121
handle: 11590/373141
The Causal Relationship between Primary Energy Consumption and Economic Growth in Israel: A Multivariate Approach
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 4visibility views 4 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;handle: 11590/374950
Abstract China, India, and the USA are the world’s biggest energy consumers and CO2 emitters. Being the leading contributors to climate change, these economies are also at the core of environmental solutions. This paper investigates the causal relationship among solar and wind energy production, coal consumption, economic growth, and CO2 emissions for these three countries. To do so, we use an advanced methodology in Machine Learning to verify the predictive causal linkages among variables. The Causal Direction from Dependency (D2C) algorithm set CO2 emissions as the target variable. The obtained results were disaggregated and estimated in a supervised prediction model. The findings, confirmed by three different Machine Learning procedures, showed an interesting output. While a reduction in overall carbon emissions is predicted in China and the US (resulting from the intensive use of renewable sources of energy), India displays critical predictions of a rise in CO2 emissions. This indicates that curbing CO2 emissions cannot be achieved without conducting a comprehensive shift from fossil to renewable resources, although China and the U.S. present a more promising path to sustainability than India. Being an emerging renewable energy leader, India should further enhance the use of low-carbon sources in its power supply and limit its dependence on coal.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu291 citations 291 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!
visibility 11visibility views 11 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;handle: 11590/374950
Abstract China, India, and the USA are the world’s biggest energy consumers and CO2 emitters. Being the leading contributors to climate change, these economies are also at the core of environmental solutions. This paper investigates the causal relationship among solar and wind energy production, coal consumption, economic growth, and CO2 emissions for these three countries. To do so, we use an advanced methodology in Machine Learning to verify the predictive causal linkages among variables. The Causal Direction from Dependency (D2C) algorithm set CO2 emissions as the target variable. The obtained results were disaggregated and estimated in a supervised prediction model. The findings, confirmed by three different Machine Learning procedures, showed an interesting output. While a reduction in overall carbon emissions is predicted in China and the US (resulting from the intensive use of renewable sources of energy), India displays critical predictions of a rise in CO2 emissions. This indicates that curbing CO2 emissions cannot be achieved without conducting a comprehensive shift from fossil to renewable resources, although China and the U.S. present a more promising path to sustainability than India. Being an emerging renewable energy leader, India should further enhance the use of low-carbon sources in its power supply and limit its dependence on coal.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu291 citations 291 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!
visibility 11visibility views 11 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Giovanna Morelli; Nicolas Schneider;handle: 11575/119375 , 11590/390612
Abstract This paper examines the linkages among Information and Communication Technologies (ICT) penetration, electricity consumption, economic growth, urbanization, and environmental pollution for 25 OECD countries over the 1990–2017 period. We first conduct several panel data analyses and then write and apply a new Machine Learning (ML) algorithm. Empirical findings show that ICT usage enhances economic growth, and it is also a crucial driver of electricity consumption, which, in turn, translates into polluting emissions. The ML results highlight internet usage emerges as a substantial CO2 emissions-enabler, thus corroborating our panel data findings. Potential policy measures are discussed.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu93 citations 93 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Giovanna Morelli; Nicolas Schneider;handle: 11575/119375 , 11590/390612
Abstract This paper examines the linkages among Information and Communication Technologies (ICT) penetration, electricity consumption, economic growth, urbanization, and environmental pollution for 25 OECD countries over the 1990–2017 period. We first conduct several panel data analyses and then write and apply a new Machine Learning (ML) algorithm. Empirical findings show that ICT usage enhances economic growth, and it is also a crucial driver of electricity consumption, which, in turn, translates into polluting emissions. The ML results highlight internet usage emerges as a substantial CO2 emissions-enabler, thus corroborating our panel data findings. Potential policy measures are discussed.
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You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu93 citations 93 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021Publisher:Elsevier BV Authors: Nicolas Schneider; Nicolas Schneider; Mehdi Ben Jebli; Umer Shahzad;Abstract While the relationship between aggregate renewables and economic growth has been extensively studied, the literature lacks examinations assessing the responses of economic and environmental indicators to geothermal energies. This caveat turns critical when the second largest geothermal energy producer worldwide remains also overlooked. This paper seeks to fill these above-mentioned gaps and proposes the first assessment of the dynamic interactions between coal energy consumption, geothermal energy consumption, industry value added and carbon emissions in the Philippines. Having provided a state-of-the-art review of the subject, our econometric procedure applies the F-Bounds test, the Autoregressive Distributed Lags and the Pairwise Granger causality test. Results support the existence of a bidirectional link among geothermal energy and aggregate income, congruent with the feedback hypothesis. Also, industry value added is found to drive coal consumption, and vice versa. Finally, geothermal energy and coal reveal a counter-intuitive positive and negative impact on carbon pollution on the short- and long-run, respectively. These results relate to the structure of the electricity supply largely dominated by fossil fuels in the Philippines and emphasize the need to further deploy geothermal energies. To meet the booming power demand from manufacturers, it is thus crucial to set up the conditions for scale effects and efficiency gains in the geothermal industry.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu69 citations 69 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021Publisher:Elsevier BV Authors: Nicolas Schneider; Nicolas Schneider; Mehdi Ben Jebli; Umer Shahzad;Abstract While the relationship between aggregate renewables and economic growth has been extensively studied, the literature lacks examinations assessing the responses of economic and environmental indicators to geothermal energies. This caveat turns critical when the second largest geothermal energy producer worldwide remains also overlooked. This paper seeks to fill these above-mentioned gaps and proposes the first assessment of the dynamic interactions between coal energy consumption, geothermal energy consumption, industry value added and carbon emissions in the Philippines. Having provided a state-of-the-art review of the subject, our econometric procedure applies the F-Bounds test, the Autoregressive Distributed Lags and the Pairwise Granger causality test. Results support the existence of a bidirectional link among geothermal energy and aggregate income, congruent with the feedback hypothesis. Also, industry value added is found to drive coal consumption, and vice versa. Finally, geothermal energy and coal reveal a counter-intuitive positive and negative impact on carbon pollution on the short- and long-run, respectively. These results relate to the structure of the electricity supply largely dominated by fossil fuels in the Philippines and emphasize the need to further deploy geothermal energies. To meet the booming power demand from manufacturers, it is thus crucial to set up the conditions for scale effects and efficiency gains in the geothermal industry.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu69 citations 69 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;Municipal solid waste generation is becoming a prominent issue in the environmental arena. The aim of this paper is to investigate the relationship among municipal waste generation, greenhouse gas emissions, and GDP in Switzerland over the period 1990-2017. We apply both time series procedures (stationarity and causality tests) and a Machine Learning approach. Empirical findings underline a bidirectional causal relationship between municipal solid waste generation and GDP, indicating that the Environmental Kuznets Curve hypothesis holds for Switzerland. Moreover, we found that waste recovery (recycling and composting) is a key driver in mitigating greenhouse gas emissions. In fact, in the Tree Model, the probability that a change in the waste recovery variable could lead to a reduction in the greenhouse gas emissions registered a value of 87%.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu145 citations 145 popularity Top 1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 7visibility views 7 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;Municipal solid waste generation is becoming a prominent issue in the environmental arena. The aim of this paper is to investigate the relationship among municipal waste generation, greenhouse gas emissions, and GDP in Switzerland over the period 1990-2017. We apply both time series procedures (stationarity and causality tests) and a Machine Learning approach. Empirical findings underline a bidirectional causal relationship between municipal solid waste generation and GDP, indicating that the Environmental Kuznets Curve hypothesis holds for Switzerland. Moreover, we found that waste recovery (recycling and composting) is a key driver in mitigating greenhouse gas emissions. In fact, in the Tree Model, the probability that a change in the waste recovery variable could lead to a reduction in the greenhouse gas emissions registered a value of 87%.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu145 citations 145 popularity Top 1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 7visibility views 7 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Springer Science and Business Media LLC Authors: Mehdi Ben Jebli; Mara Madaleno; Nicolas Schneider; Umer Shahzad;Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far. Since China is going through structural economic changes and environmental reforms, we relied on this illustrative case and developed an augmented-EKC framework to investigate whether this hypothesis holds between export product diversification and environmental pollution, stratifying by carbon energy content: renewable (Model 1) and fossil energy (Model 2). Quarterly data are collected over the most available and recent period (i.e., 1990Q1-2018Q4) and computed by applying the Quadratic Match-Sum Method (QMS) on annual series. Besides, per capita income and foreign direct investments are included as additional factors to the baseline models specifications. The empirical analysis comprises the Clemente-Montanes-Reyes unit root test with structural break and additive outlier, the autoregressive distributed lag (ARDL) bounds test for cointegration, the Granger causality test, and dynamic (DOLS) and fully modified OLS (FMOLS) estimators, followed by robustness checks confirming the stability of the coefficients exhibited in the two autoregressive settings. For both models, empirical results failed to support the existence of an inverted-U-shaped relationship among export product diversification and carbon release from fuel combustion in China. Also, as income grows, low-carbon resources seem improving export diversification and vice versa. Related findings are thought to bring robust inferences able to complement the existing literature and open a fruitful research direction.
PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Springer Science and Business Media LLC Authors: Mehdi Ben Jebli; Mara Madaleno; Nicolas Schneider; Umer Shahzad;Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far. Since China is going through structural economic changes and environmental reforms, we relied on this illustrative case and developed an augmented-EKC framework to investigate whether this hypothesis holds between export product diversification and environmental pollution, stratifying by carbon energy content: renewable (Model 1) and fossil energy (Model 2). Quarterly data are collected over the most available and recent period (i.e., 1990Q1-2018Q4) and computed by applying the Quadratic Match-Sum Method (QMS) on annual series. Besides, per capita income and foreign direct investments are included as additional factors to the baseline models specifications. The empirical analysis comprises the Clemente-Montanes-Reyes unit root test with structural break and additive outlier, the autoregressive distributed lag (ARDL) bounds test for cointegration, the Granger causality test, and dynamic (DOLS) and fully modified OLS (FMOLS) estimators, followed by robustness checks confirming the stability of the coefficients exhibited in the two autoregressive settings. For both models, empirical results failed to support the existence of an inverted-U-shaped relationship among export product diversification and carbon release from fuel combustion in China. Also, as income grows, low-carbon resources seem improving export diversification and vice versa. Related findings are thought to bring robust inferences able to complement the existing literature and open a fruitful research direction.
PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;Being heavily dependent to oil products (mainly gasoline and diesel), the French transport sector is the main emitter of Particulate Matter (PMs) whose critical levels induce harmful health effects for urban inhabitants. We selected three major French cities (Paris, Lyon, and Marseille) to investigate the relationship between the Coronavirus Disease 19 (COVID-19) outbreak and air pollution. Using Artificial Neural Networks (ANNs) experiments, we have determined the concentration of PM2.5 and PM10 linked to COVID-19-related deaths. Our focus is on the potential effects of Particulate Matter (PM) in spreading the epidemic. The underlying hypothesis is that a pre-determined particulate concentration can foster COVID-19 and make the respiratory system more susceptible to this infection. The empirical strategy used an innovative Machine Learning (ML) methodology. In particular, through the so-called cutting technique in ANNs, we found new threshold levels of PM2.5 and PM10 connected to COVID-19: 17.4 µg/m3 (PM2.5) and 29.6 µg/m3 (PM10) for Paris; 15.6 µg/m3 (PM2.5) and 20.6 µg/m3 (PM10) for Lyon; 14.3 µg/m3 (PM2.5) and 22.04 µg/m3 (PM10) for Marseille. Interestingly, all the threshold values identified by the ANNs are higher than the limits imposed by the European Parliament. Finally, a Causal Direction from Dependency (D2C) algorithm is applied to check the consistency of our findings.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 171 citations 171 popularity Top 0.1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 3visibility views 3 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;Being heavily dependent to oil products (mainly gasoline and diesel), the French transport sector is the main emitter of Particulate Matter (PMs) whose critical levels induce harmful health effects for urban inhabitants. We selected three major French cities (Paris, Lyon, and Marseille) to investigate the relationship between the Coronavirus Disease 19 (COVID-19) outbreak and air pollution. Using Artificial Neural Networks (ANNs) experiments, we have determined the concentration of PM2.5 and PM10 linked to COVID-19-related deaths. Our focus is on the potential effects of Particulate Matter (PM) in spreading the epidemic. The underlying hypothesis is that a pre-determined particulate concentration can foster COVID-19 and make the respiratory system more susceptible to this infection. The empirical strategy used an innovative Machine Learning (ML) methodology. In particular, through the so-called cutting technique in ANNs, we found new threshold levels of PM2.5 and PM10 connected to COVID-19: 17.4 µg/m3 (PM2.5) and 29.6 µg/m3 (PM10) for Paris; 15.6 µg/m3 (PM2.5) and 20.6 µg/m3 (PM10) for Lyon; 14.3 µg/m3 (PM2.5) and 22.04 µg/m3 (PM10) for Marseille. Interestingly, all the threshold values identified by the ANNs are higher than the limits imposed by the European Parliament. Finally, a Causal Direction from Dependency (D2C) algorithm is applied to check the consistency of our findings.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 171 citations 171 popularity Top 0.1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 3visibility views 3 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Public Library of Science (PLoS) Authors: Mihaela Simionescu; Wadim Strielkowski; Nicolas Schneider; Luboš Smutka;With the EU Green Deal initiatives, European members seek to launch the first climate neutral continent by 2050. This paper assesses the stochastic convergence of per capita energy consumption series for an illustrative sample of 15 EU countries with memberships prior to the 2004 enlargement, using data spanning the 1970–2018 period. Results from the confidence interval subsampling (asymmetric and equal-tailed) highlight that 11 out of the 15 EU series exhibit a long-run memory behaviour, while a diverging pattern was observed for the UK, Germany, Portugal, and Italy. Finally, per capita energy use series persist but fail to reveal one of the above dynamics for Ireland and Spain. Also, findings from the non-parametric Bayesian application (ANOVA/linear Dependent Dirichlet Process (DDP) mixture model) show how economic growth operates as a converging energy consumption-enabler over the long-run, from which the EU membership cannot be excluded. In particular, we highlight how the nature of energy-GDP hypotheses vary with the stochastic properties of energy use (converging behaviour with temporary shocks, converging pattern with permanent shocks, and diverging dynamic). Finally, our conclusions overcome the well-established development stage argument as we claim that countries with similar energy convergence patterns may need to adopt similar energy policies.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 3 citations 3 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Public Library of Science (PLoS) Authors: Mihaela Simionescu; Wadim Strielkowski; Nicolas Schneider; Luboš Smutka;With the EU Green Deal initiatives, European members seek to launch the first climate neutral continent by 2050. This paper assesses the stochastic convergence of per capita energy consumption series for an illustrative sample of 15 EU countries with memberships prior to the 2004 enlargement, using data spanning the 1970–2018 period. Results from the confidence interval subsampling (asymmetric and equal-tailed) highlight that 11 out of the 15 EU series exhibit a long-run memory behaviour, while a diverging pattern was observed for the UK, Germany, Portugal, and Italy. Finally, per capita energy use series persist but fail to reveal one of the above dynamics for Ireland and Spain. Also, findings from the non-parametric Bayesian application (ANOVA/linear Dependent Dirichlet Process (DDP) mixture model) show how economic growth operates as a converging energy consumption-enabler over the long-run, from which the EU membership cannot be excluded. In particular, we highlight how the nature of energy-GDP hypotheses vary with the stochastic properties of energy use (converging behaviour with temporary shocks, converging pattern with permanent shocks, and diverging dynamic). Finally, our conclusions overcome the well-established development stage argument as we claim that countries with similar energy convergence patterns may need to adopt similar energy policies.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 3 citations 3 popularity Top 10% influence Average impulse Average Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1371/journal.pone.0271345&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Informa UK Limited Authors: COSIMO MAGAZZINO; Donatella Porrini; Giulio Fusco; Nicolas Schneider;handle: 11590/377771 , 11587/447274 , 11586/518843
This study investigates the relationship between Information and Communication Technology (ICT) penetration, electricity consumption, economic growth, and environmental pollution within a multivari...
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu84 citations 84 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Informa UK Limited Authors: COSIMO MAGAZZINO; Donatella Porrini; Giulio Fusco; Nicolas Schneider;handle: 11590/377771 , 11587/447274 , 11586/518843
This study investigates the relationship between Information and Communication Technology (ICT) penetration, electricity consumption, economic growth, and environmental pollution within a multivari...
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu84 citations 84 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2021Data sources: Archivio della Ricerca - Università degli Studi Roma TreEnergy Sources Part B Economics Planning and PolicyArticle . 2021 . Peer-reviewedData sources: CrossrefUniversità degli Studi di Bari Aldo Moro: CINECA IRISArticle . 2021Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1080/15567249.2020.1868622&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Emerald Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;handle: 11590/390613
PurposeThe purpose of this paper is to empirically test the economic convergence that operate between five selected Asian countries (namely Thailand, Singapore, Malaysia, the Philippines and Indonesia). In particular, it seeks to investigate how increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN.Design/methodology/approachA new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index.FindingsThe Generalized Method of Moments (GMM) results highlight that the endogenous growth theory seems to be supported for the selected Asian countries, indicating evidence of diverging forces resulting from unequal growth and polarization dynamics. Overcoming the technical issues raised by the econometric approach, the new ML algorithm brings contrasted but interesting results. Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members.Originality/valueUsing the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. As a matter of fact, the new LSTM algorithm has provided consistent evidence supporting the existence of converging forces. In fact, the results highlighted the effectiveness of the experiments and the algorithm we chose. The high predictability of the authors’ model and the absence of self-alignment in the values showed a convergence be-tween the economies.
Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 3visibility views 3 download downloads 3 Powered bymore_vert Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Emerald Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;handle: 11590/390613
PurposeThe purpose of this paper is to empirically test the economic convergence that operate between five selected Asian countries (namely Thailand, Singapore, Malaysia, the Philippines and Indonesia). In particular, it seeks to investigate how increased economic integration has impacted the inter-country income levels among the five founding members of ASEAN.Design/methodology/approachA new Machine Learning (ML) approach is applied along with a panel data analysis (GMM), and the application of KOF Globalization Index.FindingsThe Generalized Method of Moments (GMM) results highlight that the endogenous growth theory seems to be supported for the selected Asian countries, indicating evidence of diverging forces resulting from unequal growth and polarization dynamics. Overcoming the technical issues raised by the econometric approach, the new ML algorithm brings contrasted but interesting results. Using the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members.Originality/valueUsing the KOF Globalization Index, the authors confirm how the last phase of globalization set the conditions for an economic convergence among sample members. As a matter of fact, the new LSTM algorithm has provided consistent evidence supporting the existence of converging forces. In fact, the results highlighted the effectiveness of the experiments and the algorithm we chose. The high predictability of the authors’ model and the absence of self-alignment in the values showed a convergence be-tween the economies.
Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 6 citations 6 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 3visibility views 3 download downloads 3 Powered bymore_vert Archivio della Ricer... arrow_drop_down Journal of Economic StudiesArticle . 2021 . Peer-reviewedLicense: Emerald Insight Site PoliciesData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1108/jes-01-2021-0027&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Now Publishers Authors: COSIMO MAGAZZINO; Nicolas Schneider;doi: 10.1561/101.00000121
handle: 11590/373141
The Causal Relationship between Primary Energy Consumption and Economic Growth in Israel: A Multivariate Approach
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 4visibility views 4 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Now Publishers Authors: COSIMO MAGAZZINO; Nicolas Schneider;doi: 10.1561/101.00000121
handle: 11590/373141
The Causal Relationship between Primary Energy Consumption and Economic Growth in Israel: A Multivariate Approach
Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
visibility 4visibility views 4 Powered bymore_vert Archivio della Ricer... arrow_drop_down Archivio della Ricerca - Università degli Studi Roma TreArticle . 2020Data sources: Archivio della Ricerca - Università degli Studi Roma TreInternational Review of Environmental and Resource EconomicsArticle . 2020 . Peer-reviewedData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1561/101.00000121&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;handle: 11590/374950
Abstract China, India, and the USA are the world’s biggest energy consumers and CO2 emitters. Being the leading contributors to climate change, these economies are also at the core of environmental solutions. This paper investigates the causal relationship among solar and wind energy production, coal consumption, economic growth, and CO2 emissions for these three countries. To do so, we use an advanced methodology in Machine Learning to verify the predictive causal linkages among variables. The Causal Direction from Dependency (D2C) algorithm set CO2 emissions as the target variable. The obtained results were disaggregated and estimated in a supervised prediction model. The findings, confirmed by three different Machine Learning procedures, showed an interesting output. While a reduction in overall carbon emissions is predicted in China and the US (resulting from the intensive use of renewable sources of energy), India displays critical predictions of a rise in CO2 emissions. This indicates that curbing CO2 emissions cannot be achieved without conducting a comprehensive shift from fossil to renewable resources, although China and the U.S. present a more promising path to sustainability than India. Being an emerging renewable energy leader, India should further enhance the use of low-carbon sources in its power supply and limit its dependence on coal.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu291 citations 291 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!
visibility 11visibility views 11 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;handle: 11590/374950
Abstract China, India, and the USA are the world’s biggest energy consumers and CO2 emitters. Being the leading contributors to climate change, these economies are also at the core of environmental solutions. This paper investigates the causal relationship among solar and wind energy production, coal consumption, economic growth, and CO2 emissions for these three countries. To do so, we use an advanced methodology in Machine Learning to verify the predictive causal linkages among variables. The Causal Direction from Dependency (D2C) algorithm set CO2 emissions as the target variable. The obtained results were disaggregated and estimated in a supervised prediction model. The findings, confirmed by three different Machine Learning procedures, showed an interesting output. While a reduction in overall carbon emissions is predicted in China and the US (resulting from the intensive use of renewable sources of energy), India displays critical predictions of a rise in CO2 emissions. This indicates that curbing CO2 emissions cannot be achieved without conducting a comprehensive shift from fossil to renewable resources, although China and the U.S. present a more promising path to sustainability than India. Being an emerging renewable energy leader, India should further enhance the use of low-carbon sources in its power supply and limit its dependence on coal.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu291 citations 291 popularity Top 0.1% influence Top 1% impulse Top 0.1% Powered by BIP!
visibility 11visibility views 11 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.renene.2020.11.050&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Giovanna Morelli; Nicolas Schneider;handle: 11575/119375 , 11590/390612
Abstract This paper examines the linkages among Information and Communication Technologies (ICT) penetration, electricity consumption, economic growth, urbanization, and environmental pollution for 25 OECD countries over the 1990–2017 period. We first conduct several panel data analyses and then write and apply a new Machine Learning (ML) algorithm. Empirical findings show that ICT usage enhances economic growth, and it is also a crucial driver of electricity consumption, which, in turn, translates into polluting emissions. The ML results highlight internet usage emerges as a substantial CO2 emissions-enabler, thus corroborating our panel data findings. Potential policy measures are discussed.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu93 citations 93 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Giovanna Morelli; Nicolas Schneider;handle: 11575/119375 , 11590/390612
Abstract This paper examines the linkages among Information and Communication Technologies (ICT) penetration, electricity consumption, economic growth, urbanization, and environmental pollution for 25 OECD countries over the 1990–2017 period. We first conduct several panel data analyses and then write and apply a new Machine Learning (ML) algorithm. Empirical findings show that ICT usage enhances economic growth, and it is also a crucial driver of electricity consumption, which, in turn, translates into polluting emissions. The ML results highlight internet usage emerges as a substantial CO2 emissions-enabler, thus corroborating our panel data findings. Potential policy measures are discussed.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu93 citations 93 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
visibility 5visibility views 5 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jup.2021.101256&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021Publisher:Elsevier BV Authors: Nicolas Schneider; Nicolas Schneider; Mehdi Ben Jebli; Umer Shahzad;Abstract While the relationship between aggregate renewables and economic growth has been extensively studied, the literature lacks examinations assessing the responses of economic and environmental indicators to geothermal energies. This caveat turns critical when the second largest geothermal energy producer worldwide remains also overlooked. This paper seeks to fill these above-mentioned gaps and proposes the first assessment of the dynamic interactions between coal energy consumption, geothermal energy consumption, industry value added and carbon emissions in the Philippines. Having provided a state-of-the-art review of the subject, our econometric procedure applies the F-Bounds test, the Autoregressive Distributed Lags and the Pairwise Granger causality test. Results support the existence of a bidirectional link among geothermal energy and aggregate income, congruent with the feedback hypothesis. Also, industry value added is found to drive coal consumption, and vice versa. Finally, geothermal energy and coal reveal a counter-intuitive positive and negative impact on carbon pollution on the short- and long-run, respectively. These results relate to the structure of the electricity supply largely dominated by fossil fuels in the Philippines and emphasize the need to further deploy geothermal energies. To meet the booming power demand from manufacturers, it is thus crucial to set up the conditions for scale effects and efficiency gains in the geothermal industry.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu69 citations 69 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021Publisher:Elsevier BV Authors: Nicolas Schneider; Nicolas Schneider; Mehdi Ben Jebli; Umer Shahzad;Abstract While the relationship between aggregate renewables and economic growth has been extensively studied, the literature lacks examinations assessing the responses of economic and environmental indicators to geothermal energies. This caveat turns critical when the second largest geothermal energy producer worldwide remains also overlooked. This paper seeks to fill these above-mentioned gaps and proposes the first assessment of the dynamic interactions between coal energy consumption, geothermal energy consumption, industry value added and carbon emissions in the Philippines. Having provided a state-of-the-art review of the subject, our econometric procedure applies the F-Bounds test, the Autoregressive Distributed Lags and the Pairwise Granger causality test. Results support the existence of a bidirectional link among geothermal energy and aggregate income, congruent with the feedback hypothesis. Also, industry value added is found to drive coal consumption, and vice versa. Finally, geothermal energy and coal reveal a counter-intuitive positive and negative impact on carbon pollution on the short- and long-run, respectively. These results relate to the structure of the electricity supply largely dominated by fossil fuels in the Philippines and emphasize the need to further deploy geothermal energies. To meet the booming power demand from manufacturers, it is thus crucial to set up the conditions for scale effects and efficiency gains in the geothermal industry.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu69 citations 69 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!
more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.resourpol.2021.102342&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;Municipal solid waste generation is becoming a prominent issue in the environmental arena. The aim of this paper is to investigate the relationship among municipal waste generation, greenhouse gas emissions, and GDP in Switzerland over the period 1990-2017. We apply both time series procedures (stationarity and causality tests) and a Machine Learning approach. Empirical findings underline a bidirectional causal relationship between municipal solid waste generation and GDP, indicating that the Environmental Kuznets Curve hypothesis holds for Switzerland. Moreover, we found that waste recovery (recycling and composting) is a key driver in mitigating greenhouse gas emissions. In fact, in the Tree Model, the probability that a change in the waste recovery variable could lead to a reduction in the greenhouse gas emissions registered a value of 87%.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu145 citations 145 popularity Top 1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 7visibility views 7 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2020 ItalyPublisher:Elsevier BV Authors: Cosimo Magazzino; Marco Mele; Nicolas Schneider;Municipal solid waste generation is becoming a prominent issue in the environmental arena. The aim of this paper is to investigate the relationship among municipal waste generation, greenhouse gas emissions, and GDP in Switzerland over the period 1990-2017. We apply both time series procedures (stationarity and causality tests) and a Machine Learning approach. Empirical findings underline a bidirectional causal relationship between municipal solid waste generation and GDP, indicating that the Environmental Kuznets Curve hypothesis holds for Switzerland. Moreover, we found that waste recovery (recycling and composting) is a key driver in mitigating greenhouse gas emissions. In fact, in the Tree Model, the probability that a change in the waste recovery variable could lead to a reduction in the greenhouse gas emissions registered a value of 87%.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu145 citations 145 popularity Top 1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 7visibility views 7 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.wasman.2020.05.033&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Springer Science and Business Media LLC Authors: Mehdi Ben Jebli; Mara Madaleno; Nicolas Schneider; Umer Shahzad;Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far. Since China is going through structural economic changes and environmental reforms, we relied on this illustrative case and developed an augmented-EKC framework to investigate whether this hypothesis holds between export product diversification and environmental pollution, stratifying by carbon energy content: renewable (Model 1) and fossil energy (Model 2). Quarterly data are collected over the most available and recent period (i.e., 1990Q1-2018Q4) and computed by applying the Quadratic Match-Sum Method (QMS) on annual series. Besides, per capita income and foreign direct investments are included as additional factors to the baseline models specifications. The empirical analysis comprises the Clemente-Montanes-Reyes unit root test with structural break and additive outlier, the autoregressive distributed lag (ARDL) bounds test for cointegration, the Granger causality test, and dynamic (DOLS) and fully modified OLS (FMOLS) estimators, followed by robustness checks confirming the stability of the coefficients exhibited in the two autoregressive settings. For both models, empirical results failed to support the existence of an inverted-U-shaped relationship among export product diversification and carbon release from fuel combustion in China. Also, as income grows, low-carbon resources seem improving export diversification and vice versa. Related findings are thought to bring robust inferences able to complement the existing literature and open a fruitful research direction.
PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type 2022 United KingdomPublisher:Springer Science and Business Media LLC Authors: Mehdi Ben Jebli; Mara Madaleno; Nicolas Schneider; Umer Shahzad;Over the past three decades, researchers have extensively examined the environmental Kuznets curve (EKC) hypothesis. Despite their early focus on the ecological impacts of anthropogenic development, associated conclusions differ and often conflict. In this study, we conducted a state-of-the-art review of this topic and shed light on the methodological challenges that the literature attempted to overcome so far. Since China is going through structural economic changes and environmental reforms, we relied on this illustrative case and developed an augmented-EKC framework to investigate whether this hypothesis holds between export product diversification and environmental pollution, stratifying by carbon energy content: renewable (Model 1) and fossil energy (Model 2). Quarterly data are collected over the most available and recent period (i.e., 1990Q1-2018Q4) and computed by applying the Quadratic Match-Sum Method (QMS) on annual series. Besides, per capita income and foreign direct investments are included as additional factors to the baseline models specifications. The empirical analysis comprises the Clemente-Montanes-Reyes unit root test with structural break and additive outlier, the autoregressive distributed lag (ARDL) bounds test for cointegration, the Granger causality test, and dynamic (DOLS) and fully modified OLS (FMOLS) estimators, followed by robustness checks confirming the stability of the coefficients exhibited in the two autoregressive settings. For both models, empirical results failed to support the existence of an inverted-U-shaped relationship among export product diversification and carbon release from fuel combustion in China. Also, as income grows, low-carbon resources seem improving export diversification and vice versa. Related findings are thought to bring robust inferences able to complement the existing literature and open a fruitful research direction.
PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 26 citations 26 popularity Top 10% influence Average impulse Top 10% Powered by BIP!
more_vert PubMed Central arrow_drop_down Environmental Monitoring and AssessmentArticle . 2022 . Peer-reviewedLicense: Springer Nature TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s10661-022-10037-4&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;Being heavily dependent to oil products (mainly gasoline and diesel), the French transport sector is the main emitter of Particulate Matter (PMs) whose critical levels induce harmful health effects for urban inhabitants. We selected three major French cities (Paris, Lyon, and Marseille) to investigate the relationship between the Coronavirus Disease 19 (COVID-19) outbreak and air pollution. Using Artificial Neural Networks (ANNs) experiments, we have determined the concentration of PM2.5 and PM10 linked to COVID-19-related deaths. Our focus is on the potential effects of Particulate Matter (PM) in spreading the epidemic. The underlying hypothesis is that a pre-determined particulate concentration can foster COVID-19 and make the respiratory system more susceptible to this infection. The empirical strategy used an innovative Machine Learning (ML) methodology. In particular, through the so-called cutting technique in ANNs, we found new threshold levels of PM2.5 and PM10 connected to COVID-19: 17.4 µg/m3 (PM2.5) and 29.6 µg/m3 (PM10) for Paris; 15.6 µg/m3 (PM2.5) and 20.6 µg/m3 (PM10) for Lyon; 14.3 µg/m3 (PM2.5) and 22.04 µg/m3 (PM10) for Marseille. Interestingly, all the threshold values identified by the ANNs are higher than the limits imposed by the European Parliament. Finally, a Causal Direction from Dependency (D2C) algorithm is applied to check the consistency of our findings.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 171 citations 171 popularity Top 0.1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 3visibility views 3 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Other literature type , Journal 2020 ItalyPublisher:Elsevier BV Authors: COSIMO MAGAZZINO; Marco Mele; Nicolas Schneider;Being heavily dependent to oil products (mainly gasoline and diesel), the French transport sector is the main emitter of Particulate Matter (PMs) whose critical levels induce harmful health effects for urban inhabitants. We selected three major French cities (Paris, Lyon, and Marseille) to investigate the relationship between the Coronavirus Disease 19 (COVID-19) outbreak and air pollution. Using Artificial Neural Networks (ANNs) experiments, we have determined the concentration of PM2.5 and PM10 linked to COVID-19-related deaths. Our focus is on the potential effects of Particulate Matter (PM) in spreading the epidemic. The underlying hypothesis is that a pre-determined particulate concentration can foster COVID-19 and make the respiratory system more susceptible to this infection. The empirical strategy used an innovative Machine Learning (ML) methodology. In particular, through the so-called cutting technique in ANNs, we found new threshold levels of PM2.5 and PM10 connected to COVID-19: 17.4 µg/m3 (PM2.5) and 29.6 µg/m3 (PM10) for Paris; 15.6 µg/m3 (PM2.5) and 20.6 µg/m3 (PM10) for Lyon; 14.3 µg/m3 (PM2.5) and 22.04 µg/m3 (PM10) for Marseille. Interestingly, all the threshold values identified by the ANNs are higher than the limits imposed by the European Parliament. Finally, a Causal Direction from Dependency (D2C) algorithm is applied to check the consistency of our findings.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 171 citations 171 popularity Top 0.1% influence Top 10% impulse Top 0.1% Powered by BIP!
visibility 3visibility views 3 Powered bymore_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.apenergy.2020.115835&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu