The main objective of this research was to test the effect of oil prices, renewable and non-renewable energy consumption, and economic growth on Turkey’s carbon emissions by using three co-integration tests, namely, the newly-developed bootstrap autoregressive distributed lag (ARDL) testing technique as proposed by (McNown et al., 2018); the new approach involving the Bayer–Hanck (2013) combined co-integration test; and the H-J (2008) co-integration technique, which induces two dates of structural breaks. The autoregressive distributed lag model (ARDL), dynamic ordinary least squares (DOLS), canonical cointegrating regression (CCR), and fully modified ordinary least square (FMOLS) approaches were utilized to test the long-run interaction between the examined variables. The Granger causality (GC) analysis was utilized to investigate the direction of causality among the variables. The long-run coefficients of ARDL, DOLS, CCR, and FMOLS showed that the oil prices had a negative influence on CO₂ emissions in Turkey in the long run. Furthermore, the findings demonstrate that non-renewable energy, which includes oil, natural gas, and coal, increased CO₂ emissions. In contrast, renewable energy can decrease the environmental pollution. These empirical findings can be attributed to the fact that Turkey is heavily dependent on imported oil; more than 50% of the energy requirement has been supplied by imports. Hence, oil price fluctuations have severe effects on the economic performance in Turkey, which in turn affects energy consumption and the level of carbon emissions. The study suggests that the rate of imported oil in Turkey must be decreased by finding more renewable energy sources for the energy supply formula to avoid any undesirable effects of oil price fluctuations on the CO₂ emissions, and also to achieve sustainable development.

In the literature, the linkage between income, energy, and carbon emissions has been widely examined and most of the empirical studies have not investigated the impact of the real estate market on their empirical models. Our study endeavors to present a novel topic by investigating the influence of the real estate market on Turkey’s environmental quality, using an advanced method of the Bootstrap Autoregressive Distributed Lag (BARDL). We estimate that consumption of renewable energy contributes significantly to CO₂ emissions, while real income increases the environmental degradation in both the short and long run. Furthermore, our study demonstrates that the real estate market contributes negatively to the deduction of carbon emissions in Turkey. A one percent increase in the real estate market will cause a rise in Turkey’s carbon level by 0.010% and 0.009% in the short and long term, respectively. Our research suggests that Turkey should design new strategies for sustainable real estate markets to improve the environmental quality by supporting green investment projects.