Energy efficiency evaluation of oil producing economies in Africa: DEA, malmquist and multiple regression approaches

Tachega, Mark Awe; Yao, Xilong; Liu, Yang; Ahmed, Dulal; Li, Hui; Mintah, Clement

doi:10.1016/j.cesys.2021.100025

Cited by 32 publications

(15 citation statements)

References 70 publications

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“…In particular, the model that does not take into account the pollution issues in the evaluation of energy efficiency underestimates the energy efficiency scores. Our results are in line with previous findings that found countries with a high level of CO 2 emissions are less eco-energy efficient than those who have low environmental impact production behavior (Tachega et al, 2021;Bampatsou et al, 2013;Wang et al, 2013). Other findings outside the energy area also confirmed that efficiency models that ignore undesirable outputs tend to overestimate the inefficiency scores (Almanza et al, 2018;Liu et al, 2020).…”

Section: Energy and Eco-energy Efficiency Scoressupporting

confidence: 92%

“…Although the work of Ohene-Asare et al (2020) and that of Tachega et al (2021) had the merit of evaluating the energy efficiency of some African countries by taking into account the environmental dimension, they overlooked exploring the role of the level of income in the examination of the environmental-energy efficiency of African countries. Yet, there is a theoretical argument in favour of the consideration of the countries' income levels.…”

Section: Environmental Energy Efficiency In Africamentioning

confidence: 99%

“…According to this theory, countries are polluting at the early stages of their economic development while their preferences for environmental quality increase when reaching a threshold of income per capita. Many studies found empirical evidence of the environmental Kuznets curve hypothesis in developed countries (Blampied, 2020;Rodil-Marzábal & Campos-Romero, 2021) as well as in developing countries (Amowine et al, 2019;Tachega et al, 2021).…”

Section: Environmental Energy Efficiency In Africamentioning

confidence: 99%

See 2 more Smart Citations

Africa Countries’ Energy Efficiency: Evidence from a Directional Distance Function Approach

Alinsato¹,

Bassongui²,

Alakonon³

2021

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Section: Energy and Eco-energy Efficiency Scoressupporting

confidence: 92%

Section: Environmental Energy Efficiency In Africamentioning

confidence: 99%

Section: Environmental Energy Efficiency In Africamentioning

confidence: 99%

See 1 more Smart Citation

Africa Countries’ Energy Efficiency: Evidence from a Directional Distance Function Approach

Alinsato¹,

Bassongui²,

Alakonon³

2021

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“…Some other literatures analyzed energy efficiency at the industrial sector or enterprise level, such as Qi [23] and Khodadadipour et al [24]; a few scholars measured energy efficiency at the urban level [25,26]. Other scholars used DEA to discuss the differences of energy efficiency at the national level by regional comparison [27,28].…”

Section: Measurement Of Energy Efficiencymentioning

confidence: 99%

The Influence of Energy Price Distortion on Region Energy Efficiency in China’s Energy-Intensive Industries from the Perspectives of Urban Heterogeneity

Wang

Liang

et al. 2021

Sustainability

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As typical representatives of China’s industrial sectors, energy intensive industries are the focus of energy conservation. This study constructs a trans-log production function and stochastic frontier analysis model to analyze the impact of energy price distortion on total factor energy efficiency in energy intensive industries on the city level. The results reveal that the phenomenon of energy price distortion existed in all cities from 2003 to 2019, with an average degree of −0.175; and the total factor energy efficiency in China’s energy intensive sectors showed an upward trend, with an average efficiency of 0.729. Further deep analysis of affecting mechanisms concluded that the price distortion showed a significant restraining effect on improving energy efficiency, while the improvement of urban agglomeration systems had an opposite effect. In addition, energy consumption structure, foreign trade, and infrastructure construction are positively correlated with energy efficiency. Therefore, promoting the market-oriented reform of China’s energy market is of great significance to improve city energy efficiency and build a resource-conserving society.

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“…Despite the efficiency measurement, many energy-based studies attempted to assess productivity growth over time (see e.g. Managi et al 2004 ; Barros and Managi 2009 ; Barros and Antunes 2014 ; Ike and Lee 2014 ; Sueyoshi and Goto 2015 ; Sheng et al 2015 ; Wang et al 2019 ; Tavana et al 2020 ; Tachega et al 2021 ). Of late, the structural complexity of the oil and gas industry has received some attention, and hence a few papers used network DEA models to combat this type of complexity (see e.g.…”

Section: Introductionmentioning

confidence: 99%

Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

2022

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This paper aims to contribute to the contemporary and imperative research on the performance and productivity growth of the oil industry. Among cutting edge methods, frontier analysis is a successful approach that has been widely used to assess the efficiency and productivity of entities with multiple resources and multiple outputs. This study first develops a unique framework based upon data envelopment analysis (DEA) to measure efficiency and productivity in the way that it tackles the uncertainty in data and undesirable outputs and, in turn, provides useful information to decision-makers. An adaptive robust optimisation is utilised to combat uncertain data whose distributions are unknown and consider the nexus between the level of conservatism and decision-makers’ risk preference. The key advantage of the proposed robust DEA approach is that the results remain relatively unchanged when uncertain conditions exist in the problem. An empirical study on the oil refinery is presented in situations of data uncertainty along with considering CO 2 emissions as the undesirable output to conduct environmental efficiency and productivity analysis of the 25 countries over the period 2000–2018. The empirical results obtained from the proposed approach give some imperative implications. First, results show that the price of robustness does not affect identically for varying technologies when assessing productivity in a global oil market, and the USA oil industry is observed as the highest productivity growth in all cases confirming its efforts for the rapid rise in oil extraction and production at low costs. There may be practical lessons for other nations to learn from the USA oil industry to improve productivity. Findings also support a considerable regress during the 2008 Global Financial Crisis in the oil industry compared to the rest of the periods in question, and due to monetary and fiscal stimulus, there is a sharp productivity growth from 2009 to 2011. The other implication that can be drawn is that the GDP growth rate and technology innovation can more effectively improve the productivity of the oil industry across the globe. Supplementary Information The online version contains supplementary material available at 10.1007/s00291-022-00683-y.

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Energy efficiency evaluation of oil producing economies in Africa: DEA, malmquist and multiple regression approaches

Cited by 32 publications

References 70 publications

Africa Countries’ Energy Efficiency: Evidence from a Directional Distance Function Approach

Africa Countries’ Energy Efficiency: Evidence from a Directional Distance Function Approach

The Influence of Energy Price Distortion on Region Energy Efficiency in China’s Energy-Intensive Industries from the Perspectives of Urban Heterogeneity

Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry

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