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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.
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University. (Statistik)ORCID iD: 0000-0002-3416-5896
Jönköping University.
2018 (English)In: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 10, no 5, article id 1315Article in journal (Refereed) 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.

Place, publisher, year, edition, pages
MDPI, 2018. Vol. 10, no 5, article id 1315
National Category
Mathematics Environmental Sciences
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-73012DOI: 10.3390/su10051315ISI: 000435587100011OAI: oai:DiVA.org:lnu-73012DiVA, id: diva2:1198748
Available from: 2018-04-18 Created: 2018-04-18 Last updated: 2018-07-13Bibliographically approved

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Shukur, Ghazi

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