Energy innovation and ecological footprint: Evidence from OECD countries during 1990–2018

Maria Shabir, Pasquale Pazienza and Caterina De Lucia

Technological Forecasting and Social Change, 2023, vol. 196, issue C

Abstract: Recent developments in energy engineering and state-of-the art technologies to increase eco-friendly energy production are receiving increasing attention in scientific debate as engines of growth. Although the energy-growth-environment nexus has been extensively studied, the ecological implications of innovative technologies in energy production are yet to be adequately addressed to provide adhoc social changes and policy perspectives. To bridge these gaps, the present study investigates the relationship between energy innovation (EIN), renewable energy production (REP), non-renewable energy production (NREP), energy intensity (EI), research and development (R&D) expenditures, GDP, and ecological footprint (EF) in 21 OECD economies during the period 1990–2018. This study applies advanced, rigorous, and robust econometric methodologies. The empirical outcomes reveal that REP, EIN, and EI, mitigate EF, while NREP, GDP, and R&D somehow accelerate the ecological deficit. This study advances the empirically proven validity of the Environmental Kuznets Curve hypothesis for OECD countries and provides valuable policy insights in terms of intensification of governmental budget spending on R&D, and boosting technological energy innovations and non-polluting energy projects. Of particular importance to trace a green energy growth is the development of comprehensive economic and energy policies with a specific focus on ecological wellbeing.

Keywords: Energy innovation; Energy intensity; Ecological footprint; Economic growth; OECD (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:196:y:2023:i:c:s0040162523005218

DOI: 10.1016/j.techfore.2023.122836

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