language English
Article 2024 · 38 atıf

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

Caglar, Abdullah Emre, Dastan, Muhammet, Avci, Salih Bortecine

Özet

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.

Anahtar Kelimeler
Artificial intelligence Carbon reduction Energy efficiency Fossil fuels Renewable energy Sustainable development goals RENEWABLE ENERGY INNOVATION POLICY
WoS Kategorileri
Energy & Fuels Engineering, Chemical
Sürdürülebilir Kalkınma Amaçları
Künye
Dergi
APPLIED ENERGY
Yıl
2024
Cilt
365
ISSN
0306-2619
eISSN
1872-9118
DOI
10.1016/j.apenergy.2024.123216
WoS UID
WOS:001287364800001
Yayını aç (DOI)