Persistence of disaggregate energy RD&D expenditures in top-five economies: Evidence from artificial neural network approach

Abdullah Emre Caglar, Muhammet Daştan and Salih Bortecine Avci

Applied Energy, 2024, vol. 365, issue C, No S0306261924005993

Abstract: The motivation of this paper is to investigate the resistance of countries' energy research and development (RD&D) expenditures to random shocks. The analysis includes the five countries (France, Germany, Japan, the United States, and the United Kingdom) that are the biggest investors in RD&D in fossil fuels, renewables, energy efficiency, and nuclear energy. Thus, economies will be able to take precautions against global shocks in producing sustainable energy policies. To achieve this aim, this paper uses the artificial neural network approach, which uses a distributed computing model that can store and generalize data after a learning period. Empirical results widely depend on countries and distinct energy technology policy fields. The key findings provide evidence that RD&D expenditures, except for renewables, do not tend to mean revert. The economies of Japan, Germany, and the United States should make more renewable investments to reduce the resistance of renewable energy sources to shocks and thus produce policies for both environmental sustainability and energy security. The economies of France and the United Kingdom can ensure energy security by continuing their sustainable energy policies.

Keywords: Artificial intelligence; Carbon reduction; Energy efficiency; Fossil fuels; Renewable energy; Sustainable development goals (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123216

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