The dynamic relationships among CO2 emissions, renewable and non-renewable energy sources, and economic growth in India: Evidence from time-varying Bayesian VAR model

We apply a three-variable VAR model with probabilistic variability using a time-varying parametric approach to determine the dynamic interactions among GDP growth, energy use by renewable energy sources (RES, wind, solar, or hydro) and non-renewable energy sources (NRES, hydroelectric or coal) and C...

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Bibliographic Details
Main Authors: Islam, F. (Author), Kang, S.H (Author), Kumar Tiwari, A. (Author)
Format: Article
Language:English
Published: Elsevier B.V. 2019
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Online Access:View Fulltext in Publisher
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Summary:We apply a three-variable VAR model with probabilistic variability using a time-varying parametric approach to determine the dynamic interactions among GDP growth, energy use by renewable energy sources (RES, wind, solar, or hydro) and non-renewable energy sources (NRES, hydroelectric or coal) and CO2 emission. Further, we characterize and quantify the impact of the nexus on the CO2 emissions, energy sources (RES and NRES) vis-à-vis India's economic growth and fluctuations during 1965Q1-2015Q4. We contribute to the literature by finding that stochastic volatility for RES and NRES appear to be U-shaped besides using TVP-VAR model to the Indian context. This U-shaped pattern seems to be related to economic growth. We also observe the time-varying patterns of the impact transmission mechanisms among energy sources, CO2 emissions, and GDP. In addition, the impulse response of GDP from a positive shock to CO2 varies with the type of energy use in different time horizons. © 2019 Elsevier B.V.
ISBN:0954349X (ISSN)
DOI:10.1016/j.strueco.2019.05.006