Open AccessMeasuring Dynamic Energy Efficiency in Africa: A Slack‐Based DEA Approach
Author(s) -
Amowine Nelson,
Ma Zhiqiang,
Li Mingxing,
Zhou Zhixiang,
Yaw Naminse Eric,
Amowine James
Publication year - 2020
Publication title -
energy science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 29
ISSN - 2050-0505
DOI - 10.1002/ese3.782
Subject(s) - inefficiency , data envelopment analysis , efficient energy use , economics , greenhouse gas , energy consumption , productivity , econometrics , prosperity , environmental economics , stock (firearms) , dynamic efficiency , rebound effect (conservation) , natural resource economics , microeconomics , macroeconomics , engineering , economic growth , ecology , statistics , mathematics , electrical engineering , mechanical engineering , biology
In the quest for economic and social prosperity, countries all over the world are constantly engaged in energy consumption to propel development. The utilization of energy emits dangerous greenhouse gases which have adverse impact on human health and the entire ecosystem. Finding the trade‐off that exists between economic growth and environmental protection is essential nowadays. Previous energy efficiency studies in Africa have focused on static efficiency and ignoring dynamic implications of crossover factors in productivity. Those studies in Africa have also failed to capture energy efficiency trends and patterns over time. Therefore, the current study applies the dynamic slack‐based measure (DSBM) in a data envelopment analysis (DEA) framework to assess the dynamic energy efficiency of 25 sampled African economies from 2007 to 2014 by adopting energy stock as carryover factors. Further, the study investigates the inputs, output, and carryover factors inefficiency in the model to identify the potential areas where inefficiencies occurred. The empirical results suggest that these selected African countries are far from being energy efficient (0.519). Therefore, both adjustments and projections on the inputs, output, and carryover variables should be taken into account, to improve efficiency. Finally, useful suggestions for energy efficiency improvement are further discussed based on the empirical results.