ARDL Bound Testing Approach for a Green Low-Carbon Circular Economy in Turkey

Irfan Kadioglu, Ozlem Turan and Ismail Bulent Gurbuz ()
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Irfan Kadioglu: Department of Banking and Insurance, Keles Vocation School, Bursa Uludag University, 16740 Keles, Bursa, Turkey
Ozlem Turan: Department of Agricultural Economics, Faculty of Agriculture, Bursa Uludag University, Gorukle Campus, 16059 Nilufer, Bursa, Turkey
Ismail Bulent Gurbuz: Department of Agricultural Economics, Faculty of Agriculture, Bursa Uludag University, Gorukle Campus, 16059 Nilufer, Bursa, Turkey

Sustainability, 2025, vol. 17, issue 6, 1-17

Abstract: This 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 (CO 2 ) 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.

Keywords: paradigm; environment policies; energy economics; economic growth; climate change (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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