Evaluating the Energy Consumption Inequalities in the One Belt and One Road Region: Implications for the Environment
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data and Empirical Strategy
2.2. BRI’s Panel Correlation Analysis
2.3. Energy Inequalities Quantification
3. Empirical Results
3.1. Energy Inequality Analysis
3.2. Pareto analysis
3.3. Impact of Energy Inequalities and Financial Development on Environmental Degradation
4. Results and Discussion
5. Conclusions and Policy Implications
Author Contributions
Funding
Conflicts of Interest
References
- Hafeez, M.; Chunhui, Y.; Strohmaier, D.; Ahmed, M.; Jie, L. Does finance affect environmental degradation: Evidence from One Belt and One Road Initiative region? Environ. Sci. Pollut. Res. 2018, 25, 9579–9592. [Google Scholar] [CrossRef] [PubMed]
- Fung Business Intelligence Centre. The Belt and Road Initiative: 65 Countries and Beyond. 2016. Available online: https://www.fbicgroup.com/?q=reports&page=4 (accessed on 15 March 2019).
- Rauf, A.; Liu, X.; Amin, W.; Ozturk, I.; Rehman, O.U.; Hafeez, M. Testing EKC hypothesis with energy and sustainable development challenges: A fresh evidence from Belt and Road Initiative economies. Environ. Sci. Pollut. Res. 2018, 25, 1–15. [Google Scholar] [CrossRef]
- Belke, A.; Dobnik, F.; Dreger, C. Energy consumption and economic growth: New insights into the cointegration relationship. Energy Econ. 2011, 33, 782–789. [Google Scholar] [CrossRef] [Green Version]
- Hossain, S. An econometric analysis for CO2 emissions, energy consumption, economic growth, foreign trade and urbanization of Japan. Low Carbon Econ. 2012, 3, 92–105. [Google Scholar] [CrossRef]
- World Bank. World Development Indicator. 2017. Available online: http://data.worldbank.org/ (accessed on 20 March 2017).
- Yasmeen, R.; Li, Y.; Hafeez, M. Tracing the trade–pollution nexus in global value chains: Evidence from air pollution indicators. Environ. Sci. Pollut. Res. 2019, 26, 5221–5233. [Google Scholar] [CrossRef]
- Nassani, A.A.; Aldakhil, A.M.; Abro, M.M.Q.; Zaman, K. Environmental Kuznets curve among BRICS countries: Spot lightening finance, transport, energy and growth factors. J. Clean. Prod. 2017, 154, 474–487. [Google Scholar] [CrossRef]
- Yan, X.; Crookes, R.J.D. Energy demand and emissions from road transportation vehicles in China. Prog. Energy Combust. Sci. 2010, 36, 651–676. [Google Scholar] [CrossRef]
- Zhang, M.; Li, H.; Zhou, M.; Mu, H. Decomposition analysis of energy consumption in Chinese transportation sector. Appl. Energy 2011, 88, 2279–2285. [Google Scholar] [CrossRef]
- IPCC. IPCC Fifth Assessment Synthesis Report-Climate Change 2014 Synthesis Report; Synthesis Report; IPCC: Geneva, Switzerland, 2014; p. 167.
- Kahouli, B. The short and long run causality relationship among economic growth, energy consumption and financial development: Evidence from South Mediterranean Countries (SMCs). Energy Econ. 2017, 68, 19–30. [Google Scholar] [CrossRef]
- Khan, M.T.I.; Yaseen, M.R.; Ali, Q. Dynamic relationship between financial development, energy consumption, trade and greenhouse gas: Comparison of upper middle income countries form Asia, Europe, Africa and America. J. Clean. Prod. 2017, 161, 567–580. [Google Scholar] [CrossRef]
- Tamazian, A.; Chousa, J.P.; Vadlamannati, K.C. Does higher economic and financial development lead to enviromental degradation: Evidence from BRIC countries. Energy Policy 2009, 37, 246–253. [Google Scholar] [CrossRef]
- Nasreen, S.; Anwar, S.; Ozturk, I. Financial stability, energy consumption and environmental quality: Evidence from South Asian economies. Renew. Sustain. Energy Rev. 2017, 67, 1105–1122. [Google Scholar] [CrossRef]
- Komal, R.; Abbas, F. Linking financial development, economic growth and energy consumption in Pakistan. Renew. Sustain. Energy Rev. 2015, 44, 211–220. [Google Scholar] [CrossRef]
- Salahuddin, M.; Gow, J.; Ozturk, I. Is the long-run between economic growth, electricity consumption, carbon dioxide emissions and financial development in Gulf Cooperation Council Countries robust? Renew. Sustain. Energy Rev. 2015, 51, 317–326. [Google Scholar] [CrossRef]
- Claessens, S.; Feijen, E. Financial Sector Development and the Millennium Development Goals; Work Bank Working Paper: Washington, DC, USA, 2006; Volume 89, pp. 1–106. [Google Scholar]
- Csereklyei, Z.; Rubio Varas, M.d.M.; Stern, D.I. Energy and economic growth: The stylized facts. Energy J. 2016, 37, 223–255. [Google Scholar] [CrossRef]
- Jobert, T.; Karanfil, F. Sectoral energy consumption by source and economic growth in Turkey. Energy Policy 2007, 35, 5447–5456. [Google Scholar] [CrossRef]
- Lise, W.; Montfort, K.V. Energy consumption and GDP in Turkey: Is there a cointegration relationship? Energy Econ. 2007, 27, 1166–1178. [Google Scholar] [CrossRef]
- Odhiambo, N.M. Energy consumption and economic growth nexus in Tanzania: An ARDL bounds testing approach. Energy Policy 2009, 37, 617–622. [Google Scholar] [CrossRef]
- Rezitis, A.N.; Ahammad, S.M. The relationship between energy consumption and economic growth in south and Southeast Asian countries: A panel vector auto regression approach and causality analysis. Int. J. Energy Econ. Policy 2015, 5, 704–715. [Google Scholar]
- Coondoo, D.; Dinda, S. Causality between income and emission: A country group specific econometric analysis. Ecol. Econ. 2002, 40, 351–367. [Google Scholar] [CrossRef]
- Luzzati, T.; Orsini, M. Natural environment and economic growth: Looking for the energy-EKC. Energy 2009, 34, 291–300. [Google Scholar] [CrossRef]
- Say, N.P.; Yucel, M. Energy consumption and CO2 emissions in Turkey: Empirical analysis and future projection based on an economic growth. Energy Policy 2006, 34, 3870–3876. [Google Scholar] [CrossRef]
- Richmond, A.K.; Kaufmann, R.K. Is there a turning point in the relationship between income and energy use and/or carbon emissions? Ecol. Econ. 2006, 56, 176–189. [Google Scholar] [CrossRef]
- Lean, H.H.; Smyth, R. CO2 emissions, electricity consumption and output in ASEAN. Appl. Energy 2010, 87, 1858–1864. [Google Scholar] [CrossRef]
- Heidari, H.; Katircioğlu, S.T.; Saeidpour, L. Economic growth, CO2 emissions, and energy consumption in the five ASEAN countries. Int. J. Electr. Power Energy Syst. 2015, 64, 785–791. [Google Scholar] [CrossRef]
- Creane, S.; Goyal, R.; Mobarak, A.M.; Sab, R. Financial Development and Economic Growth in the Middle East and North Africa Finance and Development; A Quarterly Magazine of the IMF: 4 No. 1; International Monetary Fund: Washington, DC, USA, 2003. [Google Scholar]
- Shannon, C.E. A Mathematical Theory of Communication. Bell Syst. Tech. J. 1948, 27, 379–423. [Google Scholar] [CrossRef]
- Theil, H. Economics and Information Theory; North Holland: Amsterdam, The Netherlands, 1967. [Google Scholar]
- Theil, H. The Development of International Inequality 1960–1985. J. Econ. 1989, 42, 145–155. [Google Scholar] [CrossRef]
- Salois, M.J. Regional Changes in the Distribution of Foreign Aid: An Entropy Approach. Phys. A 2013, 392, 2893–2902. [Google Scholar] [CrossRef]
- Mishra, A.K.; Livanis, G.T.; Moss, C.B. Did the Federal Agriculture Improvement and Reform Act of 1996 Affect Farmland Values? Entropy 2011, 13, 668–682. [Google Scholar] [CrossRef] [Green Version]
- Salois, M.J.; Moss, C.B. An Information Approach to the Dynamics in Farm Income: Implications for 286 Farmland Markets. Entropy 2010, 13, 38–52. [Google Scholar] [CrossRef]
- Xu, H.Y.; Kuo, S.H.; Li, G.; Legara, E.F.T.; Zhao, D.; Monterola, C.P. Generalized Cross Entropy Method for Estimating Joint Distribution from Incomplete Information. Phys. A 2016, 453, 162–172. [Google Scholar] [CrossRef]
- Bourguignon, F. Decomposable Income Inequality Measures. Econometrica 1979, 47, 901–920. [Google Scholar] [CrossRef]
- Bourguignon, F.; Morrisson, C. Inequality among World Citizens. Am. Econ. Rev. 2002, 92, 727–744. [Google Scholar] [CrossRef]
- Maasoumi, E.; Racine, J. Entropy and Predictability of Stock Market Returns. J. Econ. 2002, 107, 291–312. [Google Scholar] [CrossRef]
- Salois, M.J.; Moss, C.B.; Erickson, K. FarmIncome, Population and Farmland Prices: A Relative Information Approach. Eur. J. Agric. Econ. 2012, 39, 289–307. [Google Scholar] [CrossRef]
- Theil, H. World Income Inequality and Its Components. Econ. Lett. 1979, 2, 99–102. [Google Scholar] [CrossRef]
- Shafiei, S.; Salim, R.A. Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: A comparative analysis. Energy Policy 2014, 66, 547–556. [Google Scholar] [CrossRef]
- Tang, C.F.; Tan, B.W. The impact of energy consumption, income and foreign direct investment on carbon dioxide emissions in Vietnam. Energy 2015, 79, 447–454. [Google Scholar] [CrossRef]
- Khwaja, M.A.; Umer, F.; Shaheen, N.; Sherazi, A.; Shaheen, F.H. Air Pollution Reduction and Control in South Asia; Sustainable Development Policy Institute: Islamabad, Pakistan, 2012. [Google Scholar]
- Iwata, H.; Okada, K.; Samreth, S. Empirical study on the environmental Kuznets curve for CO2 in France: The role of nuclear energy. Energy Policy 2010, 38, 4057–4063. [Google Scholar] [CrossRef]
- Iwata, H.; Okada, K.; Samreth, S. A note on the environmental Kuznets curve for CO2, a pooled mean group approach. Appl. Energy 2011, 88, 1986–1996. [Google Scholar] [CrossRef]
- Ben Jebli, M.; Ben Youssef, S. The role of renewable energy and agriculture in reducing CO2 emissions: Evidence for North Africa countries. Ecol. Indic. 2017, 74, 295–301. [Google Scholar] [CrossRef]
- Dong, K.; Sun, R.; Jiang, H.; Zeng, X. CO2 emissions, economic growth, and the environmental Kuznets curve in China: What roles can nuclear energy and renewable energy play? J. Clean. Prod. 2018, 196, 51–63. [Google Scholar] [CrossRef]
BRI Regions | Economies |
---|---|
East Asia | China, Mongolia |
Central Asia | Kazakhstan, Kyrgyz Republic, Tajikistan |
South Asia | Bangladesh, India, Nepal, Pakistan, Sri Lanka |
Southeast Asia | Cambodia, Indonesia, Malaysia, Myanmar, Philippines, Singapore, Thailand, Vietnam |
MENA | Bahrain, Egypt, Iran, Israel, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, United Arab Emirates, Yemen |
Europe | Albania, Armenia, Azerbaijan, Belarus, Bulgaria, Croatia, Czech Republic, Georgia, Hungary, Macedonia, Moldova, Poland, Romania, Russia, Turkey, Ukraine |
Variable | Notation | Quantification | Time Span | Data Source |
---|---|---|---|---|
Energy Consumption | EC | Energy use (kg of oil equivalent per capita) | 1990–2017 | WDI |
Population | POP | Population, total | 1990–2017 | WDI |
Environmental Degradation | ENV | CO2 emissions (metric tons per capita) | 1990–2017 | WDI |
Financial development | FInDEV | |||
FinDev indicator 1 | FD1 | Domestic credit provided by the financial sector (% of GDP) | 1990–2017 | WDI |
FinDev indicator 2 | FD2 | Domestic credit to private sector (% of GDP) | 1990–2017 | WDI |
FinDev indicator 3 | FD3 | Domestic credit to the private sector by banks (% of GDP) | 1990–2017 | WDI |
Variables | FD1 | FD2 | FD3 | ENV | AEI | TEI |
---|---|---|---|---|---|---|
FD1 | 1.000 | |||||
FD2 | 0.850 | 1.000 | ||||
FD3 | 0.845 | 0.994 | 1.000 | |||
ENV | 0.073 | 0.139 | 0.149 | 1.000 | ||
AEI | 0.017 | 0.068 | 0.077 | 0.928 | 1.000 | |
TEI | −0.011 | 0.108 | 0.117 | 0.444 | 0.487 | 1.000 |
Component | Eigenvalue | Difference | Proportion | Cumulative |
---|---|---|---|---|
Comp1 | 2.79411 | 2.59461 | 0.9314 | 0.9314 |
Comp2 | 0.1995 | 0.193107 | 0.0665 | 0.9979 |
Comp3 | 0.00639306 | . | 0.0021 | 1.0000 |
FInDEV indicators | Factor Loading | |||
FD1 | 0.5555 | |||
FD2 | 0.5886 | |||
FD3 | 0.5874 |
Region | BRI | East Asia | Central Asia | Europe | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Models | M1 | M2 | M3 | M1 | M2 | M3 | M1 | M2 | M3 | M1 | M2 | M3 |
2.39 * | 4.52 * | 4.02 * | 0.099 | −1.79 * | −1.77 * | 0.244 | 2.81 * | 2.61 * | 3.13 * | 3.98 * | 3.89 * | |
(0.00) | (0.00) | (0.00) | (0.761) | (0.00) | (0.00) | (0.288) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
1437.09 * | - | - | 2613.6 * | - | - | 5286.04 * | - | - | 1336.40 * | - | - | |
(0.00) | (0.00) | (0.00) | (0.00) | |||||||||
- | 167.78 * | - | - | 56.78 * | - | - | 710.62 * | - | - | −70.90 | - | |
(0.00) | (0.00) | (0.00) | (0.205) | |||||||||
- | - | 215.37 * | - | - | 57.06 * | - | - | - | 77.73 | |||
(0.00) | (0.00) | (0.00) | (0.162) | |||||||||
0.029 * | 0.039 * | 0.038 * | 0.099 * | 0.085 * | 0.086 * | −0.017 | 0.049 | 0.029 | 0.032 ** | 0.056 * | 0.050 * | |
(0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (−0.89) | (0.322) | 0.522 | (0.002) | (0.00) | (0.00) | |
R2 | 0.865 | 0.122 | 0.204 | 0.512 | 0.714 | 0.712 | 0.961 | 0.806 | 0.834 | 0.169 | 0.055 | 0.056 |
Economies | 46 | 46 | 46 | 2 | 2 | 2 | 3 | 3 | 3 | 16 | 16 | 16 |
Observation | 1288 | 1288 | 1288 | 56 | 56 | 56 | 84 | 84 | 84 | 448 | 448 | 448 |
Wald stats | 8258.71 | 178.61 | 329.95 | 41.5 | 116.5 | 114.97 | 2573.80 | 336.56 | 408.21 | 90.94 | 26.24 | 26.61 |
Wald Prob. | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) |
Region | MENA | South Asia | Southeast Asia | ||||||
---|---|---|---|---|---|---|---|---|---|
Models | M1 | M2 | M3 | M1 | M2 | M3 | M1 | M2 | M3 |
4.90 * | 7.91 * | 5.95 * | 0.06 | 0.26 *** | 0.26 *** | 0.184 | 0.136 | 0.14 | |
(0.00) | (0.00) | (0.00) | (0.279) | (0.005) | (0.005) | (0.326) | (0.461) | (0.448) | |
1365.64 * | - | - | −1557.36 * | - | 1445.86 * | - | - | ||
(0.00) | (0.00) | (0.00) | |||||||
BEI | - | 1080.01 * | - | - | −14.20 * | - | - | 122.63 * | - |
(0.00) | (0.00) | (0.00) | |||||||
TEI | - | - | 871.14 * | - | - | −14.46 * | - | - | 123.5 * |
(0.00) | (0.00) | (0.00) | |||||||
−0.003 | −0.111 | −0.006 | 0.006 *** | 0.016 * | 0.016 * | 0.044 * | 0.041 * | 0.042 * | |
(0.796) | (0.488) | (0.671) | (0.006) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | |
R2 | 0.895 | 0.840 | 0.878 | 0.732 | 0.333 | 0.339 | 0.822 | 0.8281 | 0.827 |
Economies | 12 | 12 | 12 | 5 | 5 | 5 | 8 | 8 | 8 |
Observation | 336 | 336 | 336 | 140 | 140 | 140 | 224 | 224 | 224 |
Wald stats | 2839 | 1752.45 | 2402.91 | 375.60 | 68.65 | 70.42 | 1025.92 | 1064.70 | 1061.40 |
Wald Prob. | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) | (0.00) |
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Hafeez, M.; Yuan, C.; Khelfaoui, I.; Sultan Musaad O, A.; Waqas Akbar, M.; Jie, L. Evaluating the Energy Consumption Inequalities in the One Belt and One Road Region: Implications for the Environment. Energies 2019, 12, 1358. https://doi.org/10.3390/en12071358
Hafeez M, Yuan C, Khelfaoui I, Sultan Musaad O A, Waqas Akbar M, Jie L. Evaluating the Energy Consumption Inequalities in the One Belt and One Road Region: Implications for the Environment. Energies. 2019; 12(7):1358. https://doi.org/10.3390/en12071358
Chicago/Turabian StyleHafeez, Muhammad, Chunhui Yuan, Issam Khelfaoui, Almalki Sultan Musaad O, Muhammad Waqas Akbar, and Liu Jie. 2019. "Evaluating the Energy Consumption Inequalities in the One Belt and One Road Region: Implications for the Environment" Energies 12, no. 7: 1358. https://doi.org/10.3390/en12071358
APA StyleHafeez, M., Yuan, C., Khelfaoui, I., Sultan Musaad O, A., Waqas Akbar, M., & Jie, L. (2019). Evaluating the Energy Consumption Inequalities in the One Belt and One Road Region: Implications for the Environment. Energies, 12(7), 1358. https://doi.org/10.3390/en12071358