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Ardl bound testing approach for a green low-carbon circular economy in Turkey

dc.contributor.authorKadiroğlu, İrfan
dc.contributor.authorTuran, Özlem
dc.contributor.authorGürbüz, İsmail Bülent
dc.contributor.buuauthorKadiroğlu, İrfan
dc.contributor.buuauthorTURAN, ÖZLEM
dc.contributor.buuauthorGÜRBÜZ, İSMAİL BÜLENT
dc.contributor.departmentKeles Meslek Yüksekokulu
dc.contributor.departmentBankacılık ve Sigortacılık Bölümü
dc.contributor.departmentZiraat Fakültesi
dc.contributor.departmentTarım Ekonomisi Bölümü
dc.contributor.orcid0000-0001-5340-3725
dc.contributor.researcheridAAG-8454-2021
dc.contributor.researcheridAAG-7236-2021
dc.contributor.researcheridA-8721-2018
dc.date.accessioned2025-10-17T11:30:17Z
dc.date.issued2025-03-19
dc.description.abstractThis study analyzes Turkey's development toward a green economy between 1990 and 2022 within the framework of certain green economic indicators. The data consist of secondary data from the official databases of the World Bank and the Turkish Statistical Institute (TURKSTAT). In the study, the total amount of carbon emissions was chosen as an indicator of green growth, while gross domestic product per capita (GDP) represents economic growth, domestic loans granted by banks to the private sector (as a percentage of GDP) and foreign direct investment represent financial development, and electricity generation represents pollution. To determine whether the variables are cointegrated and to determine the direction and strength of the relationship between the variables, the ARDL bounds test and the FMOLS and DOLS long-run estimators were used. Finally, Toda Yamamoto (TY)-Granger tests were performed to determine causality. The long-term relationship between the variables was confirmed by the results of the ARDL bounds test. The error correction coefficient (CointEq(-1)) was estimated to be statistically significant and negative (-0.757) when the short-term analysis was performed. This result shows that the short-term imbalances will be corrected in less than a year, and the system will approach the long-term equilibrium. In the long-term analysis of the model, all variables selected to explain the dependent variable were found to have a statistically significant impact on the dependent variable. The GDP per capita variable, the indicator of economic growth, has a negative effect on the dependent variable, while the other independent variables have a positive effect. The results of the causality analysis indicate that the dependent variable carbon emissions (CO2) has a unidirectional causality relationship with domestic credit provided to the private sector by banks (DC), which represents financial development, and with total electricity production (EP), which serves as an indicator of pollutants.
dc.identifier.doi10.3390/su17062714
dc.identifier.issue6
dc.identifier.scopus2-s2.0-105000842962
dc.identifier.urihttps://doi.org/10.3390/su17062714
dc.identifier.urihttps://hdl.handle.net/11452/55707
dc.identifier.volume17
dc.identifier.wos001453840400001
dc.indexed.wosWOS.SCI
dc.language.isoen
dc.publisherMDPI
dc.relation.journalSustainability
dc.subjectStatistical-inference
dc.subjectProductivity
dc.subjectGrowth
dc.subjectParadigm
dc.subjectEnvironment policies
dc.subjectEnergy economics
dc.subjectEconomic growth
dc.subjectClimate change
dc.subjectScience & technology
dc.subjectLife sciences & biomedicine
dc.subjectGreen & sustainable science & technology
dc.subjectEnvironmental sciences
dc.subjectEnvironmental studies
dc.subjectScience & technology - other topics
dc.subjectEnvironmental sciences & ecology
dc.titleArdl bound testing approach for a green low-carbon circular economy in Turkey
dc.typeArticle
dspace.entity.typePublication
local.contributor.departmentKeles Meslek Yüksekokulu/Bankacılık ve Sigortacılık Bölümü
local.contributor.departmentZiraat Fakültesi/Tarım Ekonomisi Bölümü
local.indexed.atWOS
local.indexed.atScopus
relation.isAuthorOfPublication63d04ac9-0cac-4a2b-a9da-da6c63b9ebf5
relation.isAuthorOfPublication887b7c70-d321-4ad6-8c91-76fc749df9d8
relation.isAuthorOfPublication.latestForDiscovery63d04ac9-0cac-4a2b-a9da-da6c63b9ebf5

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