The study answered the following questions: First, does energy evolves in different regimes by transitioning over a finite set of unobserved states? Second, does energy consumption follow an asymmetric behavior over "energy boom" and energy scarcity? and, Third, are there unobserved factors underpinning energy crisis? We employed Markov-switching dynamic regression to examine the asymmetric effect, NIPALS regression to examine energy determinants and neural network analysis for prediction. The neural network model suggests a 99% prediction of energy consumption by the predictor variables. It was evident that energy consumption evolves in two states by transitioning over a finite set of unobserved states. The 11.6% growth in energy consumption is expected to occur in 4.1 years while energy crisis is expected to last for 3.7 years. Technological advancement and the development of green energy through foreign direct investment are essential to improve energy sector portfolio.
Keywords: Energy efficiency; Ghana; Markov-switching; NIPALS; Neural network.
Copyright © 2018 Elsevier B.V. All rights reserved.