Causal Relationship Between GDP and Carbon Emissions: Panel Data Analysis for Türkiye and OECD Countries

In this study, by using data from 14 OECD countries between 1990-2023 years, I analyze the impact of per capita gross domestic product (GDP), per capita energy consumption (EC), and the share of the industrial sector in the economy (IND) on carbon dioxide (CO₂) emissions. The analysis contains the cross-sectional dependence between the series that was determined with the aid of the CD test improved by Pesaran (2004). Then, the second-generation unit root tests, IPS (2003) and CADF (2007), were applied, and it was concluded that all variables were stationary in their first differences [I(1)]. In this particular context, the ARDL methodology was employed to compare the Pooled Mean Group (PMG), Mean Group (MG), and Dynamic Fixed Effects (DFE) forecasters, and the Hausman test results indicated that the PMG estimator was the most suitable model for forecaster. The results show that, eventually, GDP has a statistically important negative impact on CO₂ emissions, even though both EC and IND variables exert statistically important positive impact on CO₂ emissions over the same period of time. The short-run coefficients at the country level signify heterogeneity in how variations in energy consumption and the industrial sector’s share influence carbon emissions. For this reason, it is clear that policymakers should prioritise supporting tools to increase energy efficiency, focusing on low-carbon renewable energy technologies in industry, and supporting green investments in this regard.