Modeling CO2 emissions in an emerging market: empirical finding from ARDL-based bounds and wavelet coherence approaches.

Abstract

This study aims to investigate the long-run and causal effects of energy consumption, economic growth, urbanization, and trade openness on CO2 emissions in Turkey using newly developed econometric techniques. To our best knowledge, there has been no study examining the relationship between CO2 emissions, energy consumption, trade openness, urbanization, and economic growth in Turkey. Therefore, this study proposes to fill this gap in the literature. In this study, we use time series data covering the years between 1960 and 2015. To capture long-run effects, we used ARDL, FMOLS, and DOLS estimators, while wavelet coherence technique is used to explore causal effects among the variables. Our results reveal that (i) there is a long-run equilibrium relationship between CO2 emissions and energy consumption, economic growth, urbanization, and trade openness; (ii) in the long-run, CO2 emission in Turkey is significantly triggered by energy consumption, economic growth, and urbanization; and (iii) the results of the wavelet coherence-based causality test provide supportive evidence to the long-run estimations of this study.