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This paper investigates the nexus between CO2 emissions (CO2E), GDP, energy use (ENU), and population growth (PG) in India from 1980–2018 by comparing the "vector error correction" model (VECM) and "auto regressive distributed lag" (ARDL). We applied the unit root test, Johansen multi-variate cointegration, and performed a Variance decomposition analysis using the Cholesky approach. The VECM and ARDL-bound testing approaches to cointegration suggest a long-term equilibrium nexus between GDP, energy use, population growth and CO2E. The empirical outcomes show the existence of a long-term equilibrium nexus between the variables. The Granger causality results show that short-term bi-directional causality exists between GDP and ENU, while a uni-directional causality between CO2E and GDP, CO2E and ENU, CO2E and PG, and PG and ENU. Evidence from variance decomposition indicates that 58.4% of the future fluctuations in CO2E are due to changes in ENU, 2.8% of the future fluctuations are due to changes in GDP, and 0.43% of the future fluctuations are due to changes in PG. Finally, the ARDL test results indicate that a 1% increase in PG will lead to a 1.4% increase in CO2E. Our paper addresses some important policy implications. [ABSTRACT FROM AUTHOR]

The shift to renewable energy is essential for addressing climate change and reducing reliance on fossil fuels. This paper analyzes the relationship between patent applications for renewable energy technologies and clean energy production in 45 countries from 2000 to 2019. Using a System Generalized Method of Moments Panel Vector Autoregressive (GMM-PVAR) model, Impulse Response Functions (IRFs), and Granger causality tests, the findings show that a shock to renewable energy patents does not immediately affect clean energy production. However, a temporary decline occurs in the second period, followed by gradual increases that stabilize in the long run. This suggests a delayed but sustained impact of innovation on energy generation due to the time required for technology implementation and infrastructure adaptation. Bidirectional causality between patents and energy production reveals a feedback loop, where innovation drives energy development, and increased energy production fosters further advancements. Additionally, GDP per capita, foreign direct investment, political stability, and trade openness significantly affect clean energy production. Political stability positively influences long-term renewable energy generation, while GDP and trade openness show short-term fluctuations before stabilizing. These findings highlight the evolving nature of the renewable energy sector and the critical role of innovation and economic factors in driving growth. [Display omitted] • The effect of patents on renewable energy in 45 countries (2000–2019) was analyzed. • Patents have no immediate impact on renewable energy but show long-term effects. • There is a bidirectional causality between patents and renewable energy production. • Renewable energy improves political stability by reducing fossil fuel dependence. [ABSTRACT FROM AUTHOR]