Gelişmekte Olan Ülkelerde Enerji Verimliliği ve Geri Tepme Etkisinin Analizi

Abstract

Bu çalışmada, 1989’dan 2018’e kadar olan dönem için iki stokastik sınır analizi yaklaşımı kullanılarak Afrika, Avrasya ve Ortadoğu bölgelerinde bulunan seçili 17 gelişmekte olan ülkenin göreceli toplam enerji verimliliğini araştırılmaktadır. Söz konusu sınır testlerinden ilkinde enerji talep fonksiyonu benimsenirken ikincisinde ise girdi mesafesi yaklaşımı kullanılmaktadır. İki aşamalı dinamik panel veri yaklaşımı kullanılarak paneldeki her ülke için hem enerji verimliliği performansı hem de geri tepme etkisi (Rebound Effect) karşılaştırmalı olarak tahmin edilmektedir. Analizden elde edilen bulgular, incelenen ülke grubundaki ortalama verimlilik skorunun yaklaşık %84 olduğunu göstermektedir. Ayrıca, hesaplanan ortalama geri tepme etkisinin, kısa vadede verimlilik iyileştirmelerinden elde edilen enerji tasarruflarının %50’sinden fazlasını bertaraf edebileceği yönündedir. Bu sonuçlar aslında gelişmekte olan ekonomilerde enerji talebini azaltmak için enerji verimliliğine ilişkin dikkate değer potansiyeli vurgulamaktadır.

Keywords

• Stokastik sınır analizi
• Enerji verimliliği
• Enerji talebi
• Geri tepme etkisi
• Gelişmekte olan ülkeler

An Analysis of the Energy Efficiency and Rebound Effect in Developing Countries

Abstract

This study investigates the relative total energy efficiency of 17 selected developing countries, located in Africa, Eurasia and Middle East regions, using two stochastic frontier analysis methods between the period of 1989 and 2018. Initially, the energy demand function is adopted, while the input distance approach is used in the second boundary test. Using a two-stage dynamic panel data procedure, both the energy efficiency performance and rebound effect are estimated comparatively, for each country in the panel. Findings from the analysis show that the average efficiency score in the group of countries examined is approximately 84%. Additionally, the calculated average rebound effect could eliminate more than 50% of the energy savings from the efficiency improvements in the short term. These results actually highlight the significant potential for energy efficiency to lower energy demand in emerging economies.

Keywords

• Stochastic frontier analysis
• Energy efficiency
• Energy demand
• Rebound effect
• Developing countries

References

1. Adetutu, M., Glass, A., Weyman-Jones, T. (2016), “Economy-Wide Estimates of Rebound Effects: Evidence from Panel Data”, The Energy Journal, 37(3): 251-269.
2. Aigner, D., Lovell, C. A. K., Schmidt, P. (1977), “Formulation and Estimation of Stochastic Frontier Production Function Models”, Journal of Econometrics, 6(1): 21-37.
3. Arellano, M., Bond, S. (1991), “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations”, The Review of Economic Studies, 58(2): 277-297.
4. Bhattacharyya, S. C. (2011), Energy Economics: Concepts, Issues, Markets and Governance, Springer London, London.
5. BP (British Petroleum). (2022), “Statistical Review of World Energy 2022”, https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html (30.07.2023).
6. Broadstock, D. C., Li, J., Zhang, D. (2016), “Efficiency Snakes and Energy Ladders: A (Meta-) Frontier Demand Analysis of Electricity Consumption Efficiency in Chinese Households”, Energy Policy, 91: 383-396.
7. Cansino, J. M., Ordóñez, M., Prieto, M. (2022), “Decomposition and Measurement of The Rebound Effect: The Case of Energy Efficiency Improvements in Spain”. Applied Energy, 306: 117961.
8. Cantore, N., te Velde, D.W. (2011), “Promoting Energy Efficiency in Developing Countries - New Evidence Based on Firm Analysis”, (Ed.), Cantore, N Synthesis: Energy Efficiency in Developing Countries for the Manufacturing Sector içinde, WP 15/2011. Vienna: United Nations Industrial Development Organization.

9. Dufournaud, C. M., Quinn, J. T., Harrington, J. J. (1994), “An Applied General Equilibrium (Age) Analysis of a Policy Designed to Reduce the Household Consumption of Wood in the Sudan”, Resource and Energy Economics, 16(1): 67-90.
10. Dünya Bankası (World Bank). (2021), “World Development Indicators”, https://databank.worldbank.org/source/world-development-indicators (17.07.2023).
11. Evans, J., Filippini, M., Hunt, L. C. (2013), “The Contribution of Energy Efficiency Towards Meeting CO2 Targets”, (Ed.), R. Fouquet, Handbook on Energy and Climate Change içinde, Edward Elgar Publishing, Oxford, Bölüm 8: 175-223.
12. Filippini, M., Greene, W. (2016), “Persistent and Transient Productive Inefficiency: A Maximum Simulated Likelihood Approach”, Journal of Productivity Analysis, 45(2): 187-196.
13. Filippini, M., Hunt, L. C. (2011), “Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach”, Energy Journal, 32(2): 59-80.
14. Filippini, M., Hunt, L. C. (2012), “US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach”, Energy Economics, 34(5): 1484-1491.
15. Filippini, M., Hunt, L. C. (2015), “Measurement of Energy Efficiency Based on Economic Foundations”, Energy Economics 52, Supplement 1: 5-16.
16. Filippini, M., Hunt, L., Zoric, J. (2014), “Impact of Energy Policy Instruments on the Estimated Level of Underlying Energy Efficiency in The EU Residential Sector”, Energy Policy, 69: 73-81.
17. Fouquet, R. (2008), Heat, Power and Light: Revolutions in Energy Services, Edward Elgar Publishing, Cheltenham, UK and Northampton, MA, USA.
18. Greening, L. A., Greene, D. L., Difiglio, C. (2000), “Energy Efficiency and Consumption - The Rebound Effect - A Survey”, Energy Policy, 28(6): 389-401.
19. IEA (International Energy Agency-Uluslararası Enerji Ajansı). (2015), “Capturing the Multiple Benefits of Energy Efficiency, Technical Report, OECD/IEA”, Paris, http://www.iea.org/publications/freepublications/publication/capturing-the-multiplebenefits-of-energy-e_ciency.html (17.07.2023).
20. IEA (International Energy Agency-Uluslararası Enerji Ajansı). (2016a), “CO2 Emissions from Fuel Combustion Highlights”, Technical Report, OECD/IEA, Paris.
21. IEA (International Energy Agency-Uluslararası Enerji Ajansı). (2016b), “Energy Efficiency Indicators Highlights 2016”, Technical Report, OECD/IEA, Paris, http://www.iea.org/publications/freepublications/publication/energy-e_ciencyindicators-highlights-2016.html (17.07.2023).
22. IEA (International Energy Agency-Uluslararası Enerji Ajansı). (2021a), “Key World Energy Statistics 2021”, Paris, https://www.iea.org/reports/key-world-energy-statistics-2021 (17.07.2023).
23. IEA (International Energy Agency-Uluslararası Enerji Ajansı). (2021b), “World Energy Balances (Edition 2021)”, IEA World Energy Statistics and Balances (database), https://doi.org/10.1787/45be1845-en (17.07.2023).
24. IEA (International Energy Agency-Uluslararası Enerji Ajansı). (2022), “CO2 Emissions in 2022”, IEA, Paris, https://www.iea.org/reports/co2-emissions-in-2022 (17.07.2023).
25. IMF (International Monetary Fund- Uluslararası Para Fonu). (2021), “Country Composition of WEO Groups”, https://www.imf.org/en/Publications/WEO/weo-database/2023/April/groups-and-aggregates (17.07.2023).
26. IMF (International Monetary Fund- Uluslararası Para Fonu). (2023), World Economic Outlook 2023 Edition, Washington, USA.
27. Irfan, M., Mahapatra, B., Ojha, R. K. (2023). “Energy Efficiency and Carbon Emissions in Developed and Developing Economies: Investigating the Moderating Role of Financial Development”, Journal of Quantitative Economics, 21:437-455.
28. Jafari, M., Stern, D. I., Bruns, S. B. (2022). “How Large is the Economy-Wide Rebound Effect in Middle Income Countries? Evidence from Iran”, Ecological Economics, 193, 107325.
29. Jimenez, R., Mercado, J. (2014), “Energy Intensity: A Decomposition and Counterfactual Exercise for Latin American Countries”, Energy Economics, 42: 161-171.
30. Jin, T., Kim, J. (2019), “A New Approach for Assessing the Macroeconomic Growth Energy Rebound Effect”, Applied Energy, 239: 192-200.
31. Kral Abdullah Petrol Çalışmaları ve Araştırma Merkezi (King Abdullah Petroleum Studies and Research Centre). (2019), “A Global Degree Days Database for Energy-Related Applications”. https://datasource.kapsarc.org/pages/home/ (17.07.2023).
32. Li, L., Yonglei, H. (2012), “The Energy Efficiency Rebound Effect in China from Three Industries Perspective”, Energy Procedia, 14: 1105-1110.
33. Lin, B.. Du, K. (2013), “Technology Gap and China’s Regional Energy Efficiency: A Parametric Meta Frontier Approach”, Energy Economics, 40: 529-536.
34. Lundgren, T., Marklund, P.-O., Zhang, S. (2016), “Industrial Energy Demand and Energy Efficiency: Evidence from Sweeden”, Resource and Energy Economics, 43: 130-152.
35. Mahapatra, B., Irfan, M. (2021), “Asymmetric Impacts of Energy Efficiency on Carbon Emissions: A Comparative Analysis between Developed and Developing Economies”, Energy, 227: 120485.
36. Marin, G., Palma, A. (2017), “Technology Invention and Adoption in Residential Energy Consumption: A Stochastic Frontier Approach”, Energy Economics, 66: 85-98.
37. Mirza, F. M., Sinha, A., Khan, J. R., Kalugina, O. A., Zafar, M. W. (2022). “Impact of Energy Efficiency on CO2 Emissions: Empirical Evidence from Developing Countries”, Gondwana Research, 106: 64-77.
38. Otsuka, A., Goto, M. (2015), “Estimation and Determinants of Energy Efficiency in Japanese Regional Economies”, Regional Science Policy & Practice, 7(2): 89-101.
39. Population Reference Bureau (2017), “Human Population: Population Growth’, Population Reference Bureau”, http://www.prb.org/Publications/Lesson-Plans/HumanPopulation/PopulationGrowth.aspx (17.07.2023).
40. Saunders, H. D. (1992), “The Khazzoom-Brookes Postulate and Neoclassical Growth”, The Energy Journal, 13(4): 131-148.
41. Saunders, H. D. (2000), “A View from the Macro Side: Rebound, Backfire, and Khazzoom-Brookes”, Energy Policy, 28(6): 439-449.
42. Semboja, H. H. H. (1994), “The Effects of an Increase in Energy Efficiency on the Kenya Economy”, Energy Policy, 22(3): 217-225.
43. Sorrell, S., Dimitropoulos, J. (2007), “UKERC Review of Evidence for The Rebound Effect: Technical Report 2: Econometric Studies”, Technical Report, UKERC, London.
44. Topallı, N., Buluş, A. (2016), “The Rebound Effect: Empirical Evidence from Turkey”, Anadolu Üniversitesi Sosyal Bilimler Dergisi, 16(1): 29-38.
45. Uluslararası Çalışma Örgütü (International Labour Organisation). (2021), “Ilostat-Ilo Database of Labour Statistics”. https://www.ilo.org/global/statistics-and-databases/lang--en/index.htm. (17.07.2023).
46. UNIDO (United Nations for Industrial Development Organisation-Birleşmiş Milletler Sınai Kalkınma Örgütü). (2010), “Energy for a Sustainable Future, Technical Report”, http://www.un.org/millenniumgoals/pdf/AGECCsummaryreport[1].pdf (28.07.2023).
47. UNFCCC (2012), “Decisions Adopted by the Conference of The Parties”, Technical Report, United Nations Framework Convention on Climate Change.
48. UNFCCC (2017), “Climate Get the Big Picture”, United Nations Framework Convention on Climate Change, http://bigpicture.unfccc.int/ (05.06.2023)
49. Voigt, S., Cian, E. D., Schymura, M., Verdolini, E. (2014), “Energy Intensity Developments in 40 Major Economies: Structural Change or Technology Improvement?”, Energy Economics, 41: 47-62.
50. Wei, T., Liu, Y. (2017), “Estimation of Global Rebound Effect Caused by Energy Efficiency Improvement”, Energy Economics, 66: 27-34.
51. Wenlong, Z., Tien, N. H., Sibghatullah, A., Asih, D., Soelton, M., Ramli, Y. (2023). “Impact of Energy Efficiency, Technology Innovation, Institutional Quality, and Trade Openness on Greenhouse Gas Emissions in Ten Asian Economies”, Environmental Science and Pollution Research, 30(15): 43024-43039.
52. Zhang, X.-P., Cheng, X.-M., Yuan, J.-H., Gao, X.-J. (2011), “Total-Factor Energy Efficiency in Developing Countries”, Energy Policy, 39(2): 644-650
53. Zhou, P., Ang, B., Zhou, D. (2012), “Measuring Economy-Wide Energy Efficiency Performance: A Parametric Frontier Approach”, Applied Energy, 90(1): 196-200.