This paper examines the linkages among Information and Communication Technologies (ICT) penetration, electricity consumption, economic growth, urbanization, and environmental pollution for 25 OECD countries over the 1990–2017 period. We first conduct several panel data analyses and then write and apply a new Machine Learning (ML) algorithm. Empirical findings show that ICT usage enhances economic growth, and it is also a crucial driver of electricity consumption, which, in turn, translates into polluting emissions. The ML results highlight internet usage emerges as a substantial CO2 emissions-enabler, thus corroborating our panel data findings. Potential policy measures are discussed.

Magazzino, C., Mele, M., Morelli, G., Schneider, N. (2021). The nexus between information technology and environmental pollution: Application of a new machine learning algorithm to OECD countries. UTILITIES POLICY, 72 [10.1016/j.jup.2021.101256].

The nexus between information technology and environmental pollution: Application of a new machine learning algorithm to OECD countries

Magazzino, Cosimo
;
Mele, Marco;Morelli, Giovanna;
2021-01-01

Abstract

This paper examines the linkages among Information and Communication Technologies (ICT) penetration, electricity consumption, economic growth, urbanization, and environmental pollution for 25 OECD countries over the 1990–2017 period. We first conduct several panel data analyses and then write and apply a new Machine Learning (ML) algorithm. Empirical findings show that ICT usage enhances economic growth, and it is also a crucial driver of electricity consumption, which, in turn, translates into polluting emissions. The ML results highlight internet usage emerges as a substantial CO2 emissions-enabler, thus corroborating our panel data findings. Potential policy measures are discussed.
Magazzino, C., Mele, M., Morelli, G., Schneider, N. (2021). The nexus between information technology and environmental pollution: Application of a new machine learning algorithm to OECD countries. UTILITIES POLICY, 72 [10.1016/j.jup.2021.101256].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/390612
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