Assessing the nonlinear impact of economic growth and renewable energy consumption on CO₂ emissions in India: recent evidence from smooth transition autoregression model

Abstract

Purpose

The purpose of this study is to investigate the nonlinear effects of renewable energy (RE) consumption and economic growth on per capita CO₂ emissions during the time span from 1980 to 2020.

Design/methodology/approach

The study uses the logistic smooth transition autoregression (STAR) model to decipher the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in the Indian economy.

Findings

The estimated results confirm a nonlinear relationship between India’s economic growth, RE consumption and CO₂ emissions. The authors found that economic growth positively impacts CO₂ emissions until it reaches a specific threshold of 1.81 (per capita growth). Beyond this point, further economic growth leads to a reduction in CO₂ emissions. Similarly, RE consumption positively affects CO₂ emissions until economic growth reaches the same threshold level, after which an increase in RE consumption negatively impacts CO₂ emissions.

Research limitations/implications

The study suggests that India should optimize the balance between economic growth and RE consumption to mitigate CO₂ emissions. Policymakers should prioritize the adoption of RE during the early stages of economic growth. As economic growth reaches the specific threshold of 1.81 per capita, the economy should shift to more sustainable and energy-efficient practices to limit the effect of further CO₂ emissions on further economic growth.

Originality/value

To the best of the authors’ knowledge, this study represents the first-ever endeavor to reexamine the nonlinear relationship between RE consumption, economic growth and CO₂ emissions in India, using the STAR model.

Citation

Ganie, A.U.H. and Ahmad, M. (2024), "Assessing the nonlinear impact of economic growth and renewable energy consumption on CO₂ emissions in India: recent evidence from smooth transition autoregression model", International Journal of Energy Sector Management, Vol. 18 No. 6, pp. 1852-1869. https://doi.org/10.1108/IJESM-10-2023-0023