This study delves into the intricacies of India's export of petroleum products within the dynamic landscape of the Gulf Cooperation Council (GCC) countries by utilizing extensive export data. Besides this, some critical macroeconomic variables affecting India’s export of petroleum products, namely OPEC oil prices and India's economic size, which is epitomized by gross domestic product, are analyzed. The empirical analysis time frame is from 2000 to 2023. To examine linkages between the variables with their coefficient signs, this study uses autoregressive distributed lag bound testing to obtain short and long-run estimates with an error correction model and ordinary least squares. Moreover, non-frequentist Bayesian linear regression is used for validity estimations. The findings reveal that both frequentist and non-frequentist approaches justify that the OPEC oil prices and India's GDP significantly affect India’s export of petroleum products to GCC countries. Lastly, diagnostic tests are applied to check stability and robustness in both frequentist and non-frequentist Bayesian regression.

Achieving sustainable economic growth by addressing structural and environmental issues has become a top priority for decision-makers worldwide. This study investigates the impacts of renewable energy use, export diversification, and agricultural growth on sustainable economic development among G-20 economies. The analysis employs panel data from 1990 to 2021 with second-generation panel econometric methods, such as the PMG-ARDL test and dynamic panel estimation techniques, to elucidate both short- and long-term relationships. To examine the stationarity of the data series and identify cross-sectional dependence, this study applies some panel unit root tests, including the Cross-Sectionally Augmented Im and Pesaran test, the cross-sectional dependence (CSD) test, the Cross-Sectional Augmented Dickey–Fuller (CADF) test, and the Im, Pesaran, and Shin (IPS) test. The Westerlund co-integration test is employed to explore long-term relationships among the variables. To assess the prolonged impact of these factors, this study adopts the Pooled Mean Group–Autoregressive Distributed Lag (PMG-ARDL) approach. Findings reveal a statistically significant and persistent relationship between the variables, indicating that agricultural growth, renewable energy utilisation, and export diversification negatively affect economic growth. All insights highlight critical implications for G-20 policymakers; countries can develop a more resilient and sustainable economic pathway by addressing obstacles in agriculture, clean energy, and trade diversification.