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  1. Ehigiamusoe KU, Lean HH
    Environ Sci Pollut Res Int, 2019 Aug;26(22):22611-22624.
    PMID: 31165972 DOI: 10.1007/s11356-019-05309-5
    This paper examines the effects of energy consumption, economic growth, and financial development on carbon emissions in a panel of 122 countries. We employ both first-generation and second-generation cointegration and estimation procedures in order to address diverse economic and econometric issues such as heterogeneity, endogeneity, and cross-sectional dependence. We find a cointegration relationship between the variables. Energy consumption, economic growth, and financial development have detrimental effects on carbon emissions in the full sample. When the sample is split into different income groups, we reveal that economic growth and financial development mitigate carbon emissions in high-income group but have the opposite effects in low-income and middle-income groups. The implication of the findings is that energy consumption increases carbon emissions. While high levels of income and financial development decrease carbon emissions, low levels of income and financial development intensify it. Based on the findings, the paper makes some policy recommendations.
  2. Ehigiamusoe KU, Lean HH, Somasundram S
    Environ Sci Pollut Res Int, 2022 Jan;29(5):7465-7488.
    PMID: 34476686 DOI: 10.1007/s11356-021-16114-4
    This paper investigates the non-linear impacts of the agricultural, industrial, financial, and service sectors on environmental pollution in Malaysia during the 1980-2018 period. It employs the extended STIRPAT model and two indicators of environmental pollution (carbon dioxide emissions and ecological footprints). It uses the autoregressive distributed lag (ARDL) technique to estimate the parameters. Evidence from the study indicate that the agricultural, industrial, and service sectors have inverted U-shaped non-linear impacts on carbon dioxide emissions and ecological footprints, while the financial sector has a U-shaped non-linear relationship with carbon dioxide emissions and ecological footprint. These empirical outcomes are robust to diagnostic tests, structural breaks, and alternative estimation technique and proxies. The economic implication of this paper is that, at the early stage of sectoral growth, the pollution intensity of sectoral output increases, but after a certain turning point, a further increase in sectoral output will reduce environmental pollution. Precisely, environmental pollution will reduce if the agricultural, industrial, and service sectors exceed threshold levels of 11%, 44%, and 49% of GDP, respectively, while environmental pollution will be aggravated if financial sector exceeds a threshold level of 94%. Therefore, efforts to mitigate environmental pollution in Malaysia should integrate sectoral growth to attain sustainable development.
  3. Ehigiamusoe KU, Lean HH, Mustapha M, Ramakrishnan S
    Heliyon, 2023 Oct;9(10):e20699.
    PMID: 37876485 DOI: 10.1016/j.heliyon.2023.e20699
    This paper examines the causal relationship between industrialization, globalization, information communication technology (ICT) and environmental degradation in Malaysia during 1970-2019. It uses two indicators of environmental degradation (carbon emissions and ecological footprint), three dimensions of globalization (political, social, and economic) and three indicators of ICT (users of internet, mobile cellular, and fixed telephone subscriptions). It utilizes Granger causality technique in frequency domain which differentiates between permanent and temporary causality, Vector Error Correction approach as well as Variance Decompositions. The bound test shows that the variables have cointegration relationship. It reveals joint long-run and short-run causality from industrialization, globalization, and ICT to carbon emissions, albeit the causality to ecological footprint is tenuous. It indicates that industrialization, globalization, and ICT significantly predict carbon emissions at high frequency than at low frequency. A substantial percentage of the forecast error variance in environmental degradation are explained by industrialization, globalization, and ICT. The robustness of the empirical outcomes is confirmed by the alternative proxies of the variables. Our study implies that industrialization, globalization, and ICT are determinants of environmental degradation. Therefore, policies to mitigate environmental problem should prioritize these variables to attain green economy.
  4. Ehigiamusoe KU, Dogan E, Ramakrishnan S, Binsaeed RH
    J Environ Manage, 2024 Dec;371:123229.
    PMID: 39522189 DOI: 10.1016/j.jenvman.2024.123229
    The objective of this study is to unravel the linear impacts of economic growth, technological innovation, natural resource rents and trade openness on carbon emissions in Malaysia during 1980-2021. It also unveils the moderating role of technological innovation on the impacts of economic growth, natural resource rents and trade openness on carbon emissions. It further analyses the nonlinear relationship between technological innovation and carbon emissions. It estimates the parameters with the Autoregressive Distributed Lag model technique. The results of the linear model reveal that economic growth, natural resource rents and trade openness contributes to carbon emissions while technological innovation mitigates carbon emissions. The disaggregated analysis of natural resource rents indicates that oil rents, natural gas rents and coal rents intensify carbon emissions while mineral rents and forest rents do not contribute to carbon emissions. The disaggregated analysis of trade openness shows that exports worsen carbon emissions while imports have tenuous effect. The disaggregated analysis of technological innovation indicates that innovation by non-residents mitigate carbon emissions while innovation by residents do not alleviate carbon emissions. Moreover, evidence from the interaction model reveals that technological innovation can favourably mitigate the adverse impacts of economic growth and trade openness on carbon emissions albeit it cannot alleviate the impact of natural resource rents on carbon emissions. Besides, the nonlinear model indicates a U-shaped relationship between technological innovation and carbon emissions. Unlike previous studies that typically focused on the direct impacts of these variables, this study unravels the impacts of the disaggregated components as well as provides insights into the moderating and nonlinear effects of technological innovation on carbon emissions. The implication of this study is that efforts to achieve a carbon-neutral economy should consider the direct and indirect impacts of economic growth, technological innovation, natural resource rents and trade openness. It is recommended for Malaysia to encourage technological innovation in her quest to abate the adverse environmental impacts of economic activities.
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