| Abstract |
The environment's quality is the cornerstone for every country's long-term growth. Pakistan, like other countries, is embracing modern, efficient technologies to build a sustainable environment following the SDGs. In this situation, policymakers and experts have emphasized more on environmental factors. To do this, the study explores the impact of green innovation (GI), public-private partnerships in energy (PPP), energy use (EU), economic development (ED), and power prices (PP) on CO2 emissions in Pakistan from 1980 to 2019. The research uses a novel econometric technique for estimating environmental factors, notably the dynamic autoregressive distributed lag simulations (ARDLS) model and spectral frequency domain causality (SFDC), to examine positive and negative shocks for the prediction of the short-, medium-, and long-run impact of selected determinants, respectively. Additionally, robustness checks were performed using the fully modified OLS (FMOLS), dynamic OLS (DOLS), and canonical cointegrating regression (CCR) estimations. The short and long-term empirical findings indicate that GI lowers emissions; nevertheless, PPP, EU, and ED have a significant impact on emissions in the short run, while the EU increases emissions in the long run. PP, on the other hand, reduces emissions both short and long-term. The FMOLS, DOLS, and CCR estimations indicate significant discoveries. Additionally, the SFDC finding supports the long, medium, and short-term causation theories. This research advocates green innovation for a greener manufacturing process and PPP investment in renewable energy. In addition, the Pakistani government considers these variables while designing a comprehensive protracted environmental plan to meet SDGs 7 and 13. |