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Pooling cross-sectional and time series data for estimating causality between technological innovation, affluence and carbon dynamics: A comparative evidence from developed and developing countries

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  • Shobande, Olatunji A.
  • Ogbeifun, Lawrence

Abstract

The trends in affluence and carbon emissions remain a concern in view of the pressing need to establish conditions for sustainable development. Scientific evidence reveals that if far-reaching reforms of technological innovation are not undertaken, the environment will deteriorate beyond repair, which will be detrimental to the development agenda. Our study explored whether technological innovation has failed to anticipate the rise in affluence factors that dictate the level of economic activities and associated carbon emissions. We analysed the relationships between technological innovation and affluence and carbon emissions. The empirical strategy followed the standard panel fixed effects, Arellano–Bover/Blundell–Bond dynamic panel analysis, and the Hausman–Taylor methodology. The results of our dynamic econometric tests did not reject the Stochastic Impact by Regression on Population, Affluence, and Technology framework for the successful reduction of carbon emissions through technological innovation. Our findings further suggest that improved technological innovation can not only predict and identify carbon emissions but may also be used to monitor and mitigate their impacts. We recommend strategies for promoting technological innovation to accelerate reductions in carbon emissions without compromising sustainability.

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  • Shobande, Olatunji A. & Ogbeifun, Lawrence, 2023. "Pooling cross-sectional and time series data for estimating causality between technological innovation, affluence and carbon dynamics: A comparative evidence from developed and developing countries," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:tefoso:v:187:y:2023:i:c:s0040162522007132
    DOI: 10.1016/j.techfore.2022.122192
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