A machine learning approach for predicting the relationship between energy resources and economic development

Dušan Cogoljević, Meysam Alizamir, Ivan Piljan, Tatjana Piljan, Katarina Prljić and Stefan Zimonjić

Physica A: Statistical Mechanics and its Applications, 2018, vol. 495, issue C, 211-214

Abstract: The linkage between energy resources and economic development is a topic of great interest. Research in this area is also motivated by contemporary concerns about global climate change, carbon emissions fluctuating crude oil prices, and the security of energy supply. The purpose of this research is to develop and apply the machine learning approach to predict gross domestic product (GDP) based on the mix of energy resources. Our results indicate that GDP predictive accuracy can be improved slightly by applying a machine learning approach.

Keywords: Economic development; Energy usage; Prediction (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:495:y:2018:i:c:p:211-214

DOI: 10.1016/j.physa.2017.12.082

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