Abstract
Rapid population growth and economic expansion affect environmental sustainability by raising emissions from increased urbanization, industrialization, and energy consumption in South Asia. Therefore, the current research aims to scrutinize the dynamic impacts of urbanization, industrialization, and energy consumption on carbon dioxide (CO2) emissions in five South Asian countries (Bangladesh, Pakistan, India, Nepal, and Sri Lanka) under the umbrella of the famous stochastic regression for impact for technology, population, and asset on environmental condition (STIRPAT) model. This research employed the second-generation unit root and cointegration tests by applying the data from 1972 to 2021 to investigate the existence of slope heterogeneity (SH) and cross-sectional dependence (CSD) problem. After checking CSD, SH, unit root, and cointegration tests, the research utilized cross-sectional autoregressive distributive lag (CS-ARDL) as a baseline model and augmented mean group (AMG), mean group (MG), and common correlated effects mean group (CCEMG) as a robustness check. The evidence shows that the economic boom, urbanization, and industrialization increase CO2 emissions. CO2 emissions in South Asian nations have been reduced due to population growth, natural resources rent, and electrification. All estimators point to urbanization’s negative effects, being far more severe than any other environmental impact. Conversely, natural resource rent prevents environmental degradation more effectively than electricity. Therefore, it is recommended that South Asian economies adopt consistent, sustainable economic policies to reap the benefits of industrialization, urbanization, and increased electricity use. The findings are generally consistent with the policy implications.
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