lnu.sePublikationer
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
On the Estimation of the CO2 Emission, Economic Growth and Energy Consumption Nexus Using Dynamic OLS in the Presence of Multicollinearity
Jönköping University.
Florida International University, USA.
Linnéuniversitetet, Ekonomihögskolan (FEH), Institutionen för nationalekonomi och statistik (NS). Jönköping University. (Statistik)ORCID-id: 0000-0002-3416-5896
Jönköping University.
2018 (Engelska)Ingår i: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 10, nr 5, artikel-id 1315Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

This paper introduces shrinkage estimators (Ridge DOLS) for the dynamic ordinary least squares (DOLS) cointegration estimator, which extends the model for use in the presence of multicollinearity between the explanatory variables in the cointegration vector. Both analytically and by using simulation techniques, we conclude that our new Ridge DOLS approach exhibits lower mean square errors (MSE) than the traditional DOLS method. Therefore, based on the MSE performance criteria, our Monte Carlo simulations demonstrate that our new method outperforms the DOLS under empirically relevant magnitudes of multicollinearity. Moreover, we show the advantages of this new method by more accurately estimating the environmental Kuznets curve (EKC), where the income and squared income are related to carbon dioxide emissions. Furthermore, we also illustrate the practical use of the method when augmenting the EKC curve with energy consumption. In summary, regardless of whether we use analytical, simulation-based, or empirical approaches, we can consistently conclude that it is possible to estimate these types of relationships in a considerably more accurate manner using our newly suggested method.

Ort, förlag, år, upplaga, sidor
MDPI, 2018. Vol. 10, nr 5, artikel-id 1315
Nationell ämneskategori
Matematik Miljövetenskap
Forskningsämne
Statistik
Identifikatorer
URN: urn:nbn:se:lnu:diva-73012DOI: 10.3390/su10051315ISI: 000435587100011Scopus ID: 2-s2.0-85046076098OAI: oai:DiVA.org:lnu-73012DiVA, id: diva2:1198748
Tillgänglig från: 2018-04-18 Skapad: 2018-04-18 Senast uppdaterad: 2019-08-29Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Personposter BETA

Shukur, Ghazi

Sök vidare i DiVA

Av författaren/redaktören
Shukur, Ghazi
Av organisationen
Institutionen för nationalekonomi och statistik (NS)
I samma tidskrift
Sustainability
MatematikMiljövetenskap

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetricpoäng

doi
urn-nbn
Totalt: 30 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf