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MODELLING CARBON DIOXIDE EMISSION IN INDIA USING AUTOREGRESSIVE DISTRIBUTED LAG MODELS
Keywords:
autoregressive distributed lag model, renewable energy, non-renewable energy, carbon dioxide emissionDOI:
https://doi.org/10.17654/0972361723031Abstract
Autoregressive distributed lag (ARDL) model is one of the powerful tools to model time series data, which allows simultaneous estimation of both long run and short run parameters. The current article focuses on modelling the impact of renewable energy production, non-renewable energy production, gross domestic product and urban population growth on carbon dioxide emission in India during 1971 to 2014. The long run relationship between covariates and regressors is established using ARDL bound test. The estimated long run parameters suggest that both renewable and non-renewable energy production make a significant impact on the carbon dioxide emission. The asymmetric relationship between the considered factors and carbon dioxide emission is analyzed using non-linear autoregressive distributed lag (NARDL) model. The asymmetric analysis indicates that carbon dioxide emission from non-renewable energy production is comparatively higher than renewable energy production, thus suggesting increasing renewable energy production in India to meet the energy demand.
Received: December 14, 2022
Accepted: February 22, 2023
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