Journals / Ekonomi Politika ve Finans Araştırmaları Dergisi / 2025 / Cilt: 10 Sayı: 4

Sectoral Convergence Analysis of Primary Energy Consumption in Turkey

Türkiye’de Birincil Enerji Tüketiminde Sektör Yakınsama Analizi

Ezgi Doğan(YÜKSEK İHTİSAS ÜNİVERSİTESİ)0000-0002-7751-7687
Celal Taşdoğan(ANKARA HACI BAYRAM VELİ ÜNİVERSİTESİ)0000-0002-8626-8862
Pages
1622–1654
Publication Date
2025-12-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

A positive and significant relationship was observed between the value added and natural gas consumption of the sectors.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study analyzes the energy consumption of sectors using the Phillips-Sul Club Convergence model and examines the relationship between sector value added, energy consumption, and deviations in energy prices via Quantile Moments Regression.
📊
Key Findings & Data:First, the consumption of natural gas and petroleum products in the main sectors and sub-sectors in Turkey for the period 1992-2021 is examined using the club convergence method.
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Conclusion & Impact:A positive and significant relationship was observed between the value added and natural gas consumption of the sectors.
🔬Design:Modeling & Simulation
📍Scope:2021 Verileri
⚙️Variables:Enerji Ekonomisi · Enerji Tüketimi · Kulüp Yakınsama Analizi

Abstract

This study analyzes the energy consumption of sectors using the Phillips-Sul Club Convergence model and examines the relationship between sector value added, energy consumption, and deviations in energy prices via Quantile Moments Regression. First, the consumption of natural gas and petroleum products in the main sectors and sub-sectors in Turkey for the period 1992-2021 is examined using the club convergence method. In the second stage of the study, the factor cost and value-added data of the sectors are considered, and the effect of energy consumption and deviations in energy prices on value added is analyzed. In the first stage of the analysis, one club was identified in natural gas consumption among the sectors, while three clubs were identified in petroleum consumption. In the second stage of the analysis, according to the regression results applied to the converging sectors, it was determined that petroleum consumption positively affects the value added of the sectors in all quantiles. A positive and significant relationship was observed between the value added and natural gas consumption of the sectors.

Özet

Bu çalışma, sektörlerin enerji tüketimini Phillips-Sul Kulüp Yakınsama modeli ile analiz etmeyi ve sektörlerin katma değeri, enerji tüketimi ve enerji fiyatlarındaki sapmalar arasındaki ilişkiyi Momentler Kantil Regresyonu yöntemi ile ele almayı amaçlamaktadır. Çalışmada ilk olarak, 1992-2021 dönemi için Türkiye’deki temel sektörler ve bunların alt sektörlerinin doğalgaz ve petrol ürünleri tüketimi kulüp yakınsama yöntemiyle incelenmiştir. Çalışmanın ikinci aşamasında ise sektörlerin faktör maliyetiyle katma değer verileri ele alınmış, enerji tüketimi ile enerji fiyatlarındaki sapmaların katma değere etkisi analiz edilmiştir. Analizin ilk aşamasında kulüp yakınsama yöntemi ile doğalgaz ve petrol ürünleri tüketiminde yakınsayan sektörler tespit edilmiştir. Doğalgaz tüketiminde sektörler arasında bir adet alt kulüp oluşurken, petrol tüketiminde ise üç adet alt kulüp tespit edilmiştir. Analizin ikinci aşamasında, yakınsayan sektörler için uygulanan Momentler Kantil Regresyonu sonuçlarına göre, petrol tüketiminin tüm kantillerde sektörlerin katma değerini pozitif etkilediği tespit edilmiştir. Sektörlerin doğalgaz tüketimi incelendiğinde ise sektörlerin katma değeri ile pozitif ve anlamlı bir ilişki söz konusudur.

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Cite This Article

Doğan, E., Taşdoğan, C. (2025). Sectoral Convergence Analysis of Primary Energy Consumption in Turkey. Ekonomi Politika ve Finans Araştırmaları Dergisi, Cilt: 10 Sayı: 4, 1622–1654. https://doi.org/10.30784/epfad.1816147

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References (60)

  1. Anwar, A., Siddique, M., Dogan, E. and Sharif, A. (2021). The moderating role of renewable and non-renewable energy in environment-income nexus for ASEAN countries: Evidence from Method of Moments Quantile Regression. Renewable Energy, 164, 956-967. https://doi.org/10.1016/j.renene.2020.09.128
  2. Apergis, N. and Christou, C. (2016). Energy productivity convergence: New evidence from club converging. Applied Economics Letters, 23(2), 142-145. https://doi.org/10.1080/13504851.2015.1058899
  3. Apergis, N. and Payne, J.E. (2017). Per capita carbon dioxide emissions across US states by sector and fossil fuel source: Evidence from club convergence tests. Energy Economics, 63, 365-372. https://doi.org/10.1016/j.eneco.2016.11.027
  4. Apergis, N., Christou, C. and Hassapis, C. (2013). Convergence in public expenditures across EU countries: Evidence from club convergence. Economics & Finance Research, 1(1), 45–59. https://doi.org/10.1080/21649480.2013.862735
  5. Apergis, N., Ewing, B.T. and Payne, J.E. (2017a). Introduction: Symposium on energy sector convergence. Energy Economics, 62, 335-337. https://doi.org/10.1016/j.eneco.2016.09.015
  6. Apergis, N., Fontini, F. and Inchauspe, J. (2017b). Integration of regional electricity markets in Australia: A price convergence assessment. Energy Economics, 62, 411-418. https://doi.org/10.1016/j.eneco.2016.06.022
  7. Ayazoğlu, B. (2022). Seçilmiş OECD ülkelerinde kişi başi CO2 emisyonu ve toplam enerji tüketimleri yakınsama kulüpleri analizi (Master's thesis). Pamukkale University, Türkiye.
  8. Baktemur, F.İ. and Özmen, M. (2016). AB-27 ülkeleri için gelir yakınsamasının mekânsal ekonometrik analiz ile tahmini. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 20(1), 1-10. Baležentis, T., Butkus, M. and Štreimikienė, D. (2023). Energy productivity and GHG emission in the european agriculture: The club convergence approach. Journal of Environmental Management, 342, 118238. https://doi.org/10.1016/j.jenvman.2023.118238
  9. Bangjun, W., Linyu, C., Feng, J. and Yue, W. (2023). Research on club convergence effect and its influencing factors of per capita energy consumption: Evidence from the data of 243 prefecture-level cities in China. Energy, 263, 125657. https://doi.org/10.1016/j.energy.2022.125657
  10. Barro, R.J. and Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2), 223-251. Retrieved from https://www.jstor.org/journal/jpoliecon
  11. Başar, S., Tosun, B. and Bartik, A. (2020). Türkiye’de büyüme ve sektörel bazda elektrik tüketimi arasındaki ilişki. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 34(3), 1089-1109. https://doi.org/10.16951/atauniiibd.724638
  12. Baumol, W.J. (1986). Productivity growth, convergence, and welfare: What the long-run data show. American Economic Review, 76(5), 1072-85. Retrieved from https://www.jstor.org/
  13. Bowden, N. and Payne, J.E. (2009). The causal relationship between US energy consumption and real output: A disaggregated analysis. Journal of Policy Modeling, 31(2), 180-188. https://doi.org/10.1016/j.jpolmod.2008.09.001
  14. Bulut, M. (2020). Sektörel enerji tüketimi ve ekonomik büyüme ilişkisi (Master's thesis). Nevşehir Hacı Bektaş Veli University, Türkiye.
  15. Burnett, J.W. (2016). Club convergence and clustering of US energy-related CO2 emissions. Resource and Energy Economics, 46, 62-84. https://doi.org/10.1016/j.reseneeco.2016.09.001
  16. Canay, I.A. (2011). A simple approach to quantile regression for panel data. The Econometrics Journal, 14(3), 368-386. https://doi.org/10.1111/j.1368-423X.2011.00349.x
  17. Chandio, A.A., Rauf, A., Jiang, Y., Ozturk, I. and Ahmad, F. (2019). Cointegration and causality analysis of dynamic linkage between industrial energy consumption and economic growth in Pakistan. Sustainability, 11(17), 4546. https://doi.org/10.3390/su11174546
  18. Doğan, B. (2019). Enerji tüketimi ve büyüme ilişkisinin Türkiye’de sektörel uygulaması. B. Yuvalı ve T. Eğri (Eds.), 8.Türkiye Lisansüstü Çalışmaları Kongresi Bildiriler Kitabı-II içinde (ss. 191-207). 8. Türkiye Lisansüstü Çalışmaları Kongresi’nde sunulan bildiri, Malatya. Malatya: İLEM.
  19. Doyar, B.V. (2015). Enerji tüketimi–ekonomik büyüme ilişkisi: Türkiye ekonomisi örneği (Master's thesis). Nevşehir Hacı Bektaş Veli Üniversitesi, Türkiye.
  20. Du, L., Jiang, H., Adebayo, T.S., Awosusi, A.A. and Razzaq, A. (2022). Asymmetric effects of high-tech industry and renewable energy on consumption-based carbon emissions in MINT countries. Renewable Energy, 196, 1269-1280. https://doi.org/10.1016/j.renene.2022.07.028
  21. EİGM. (2022). EIGM reports. Retrieved from https://www.enerji.gov.tr/eigm-raporlari
  22. Erol, U. and Yu, E.S. (1987). On the causal relationship between energy and income for industrialized countries. The Journal of Energy and Development, 113-122. Retrieved from https://www.jstor.org/
  23. Galor, O. (1996). Convergence? Inferences from theoretical models. The Economic Journal, 106(437), 1056-1069. https://doi.org/10.2307/2235378
  24. Gökmen, B. (2019). Sanayi sektörü çıktı hacmi ve enerji tüketimi ilişkisi: Türkiye üzerine ampirik bir analiz (Master's thesis). Necmettin Erbakan University, Türkiye.
  25. Gross, C. (2012). Explaining the (non-) causality between energy and economic growth in the U.S.—A multivariate sectoral analysis. Energy Economics, 34(2), 489-499. https://doi.org/10.1016/j.eneco.2011.12.002
  26. He, W. and Chen, H. (2022). Will China's provincial per capita energy consumption converge to a common level over 1990–2017? Evidence from a club convergence approach. Energy, 249, 123624. https://doi.org/10.1016/j.energy.2022.123624
  27. Herrerias, M.J., Aller, C. and Ordonez, J. (2017). Residential energy consumption: A convergence analysis across Chinese regions. Energy Economics, 62, 371-381. https://doi.org/10.1016/j.eneco.2016.06.006
  28. Ivanovski, K., Churchill, S.A. and Smyth, R. (2018). A club convergence analysis of per capita energy consumption across Australian regions and sectors. Energy Economics, 76, 519-531. https://doi.org/10.1016/j.eneco.2018.10.035
  29. Karimu, A., Brännlund, R., Lundgren, T. and Söderholm, P. (2017). Energy intensity and convergence in Swedish industry: A combined econometric and decomposition analysis. Energy Economics, 62, 347-356. https://doi.org/10.1016/j.eneco.2016.07.017
  30. Khaddage-Soboh, N., Safi, A., Rasheed, M.F. and Hasnaoui, A. (2023). Examining the role of natural resource rent, environmental regulations, and environmental taxes in sustainable development: evidence from G-7 economies. Resources Policy, 86, 104071. https://doi.org/10.1016/j.resourpol.2023.104071
  31. Khan, Z., Hossain, M. R., Badeeb, R.A. and Zhang, C. (2023). Aggregate and disaggregate impact of natural resources on economic performance: Role of green growth and human capital. Resources Policy, 80, 103103. https://doi.org/10.1016/j.resourpol.2022.103103
  32. Kim, Y.S. (2015). Electricity consumption and economic development: Are countries converging to a common trend? Energy Economics, 49, 192-202. https://doi.org/10.1016/j.eneco.2015.02.001
  33. Koç, Ü. (2020). Sektörel enerji tüketimi ve ekonomik büyüme. Third Sector Social Economic Review, 55(1), 508-521. https://doi.org/10.15659/3.sektor-sosyal-ekonomi.20.03.1289
  34. Koenker, R. (2004). Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91(1), 74-89. https://doi.org/10.1016/j.jmva.2004.05.006
  35. Koenker, R. and Bassett Jr, G. (1978). Regression quantiles. Econometrica: Journal of the Econometric Society, 33-50. https://doi.org/10.2307/1913643
  36. Kraft, J. and Kraft, A. (1978). On the relationship between energy and GNP. The Journal of Energy and Development, 3(2), 401-403. Retrieved from https://www.jstor.org/
  37. Lamarche, C. (2010). Robust penalized quantile regression estimation for panel data. Journal of Econometrics, 157(2), 396-408. https://doi.org/10.1016/j.jeconom.2010.03.042
  38. Liu, C., Hong, T., Li, H. and Wang, L. (2018). From club convergence of per capita industrial pollutant emissions to industrial transfer effects: An empirical study across 285 cities in China. Energy Policy, 121, 300-313. https://doi.org/10.1016/j.enpol.2018.06.039
  39. Liu, F., Li, A. and Khan, Y. (2024). PM2.5 Neutrality goals: The role of government strengthen and digitalization in BRICS Countries. Air Quality, Atmosphere & Health, 17(11), 2615-2629. https://doi.org/10.1007/s11869-024-01592-5
  40. Machado, J.A. and Silva, J.S. (2019). Quantiles via moments. Journal of Econometrics, 213(1), 145-173. https://doi.org/10.1016/j.jeconom.2019.04.009
  41. Miao, Y., Razzaq, A., Adebayo, T.S. and Awosusi, A.A. (2022). Do renewable energy consumption and financial globalisation contribute to ecological sustainability in newly industrialized countries? Renewable Energy, 187, 688-697. https://doi.org/10.1016/j.renene.2022.01.073
  42. Morales-Lage, R., Bengochea-Morancho, A., Camarero, M. and Martínez-Zarzoso, I. (2019). Club convergence of sectoral CO2 emissions in the European Union. Energy Policy, 135, 111019. https://doi.org/10.1016/j.enpol.2019.111019
  43. Panopoulou, E. and Pantelidis, T. (2009). Club convergence in carbon dioxide emissions. Environmental and Resource Economics, 44(1), 47-70. https://doi.org/10.1007/s10640-008-9260-6
  44. Parker, S. and Liddle, B. (2017). Economy-wide and manufacturing energy productivity transition paths and club convergence for OECD and non-OECD countries. Energy Economics, 62, 338-346. https://doi.org/10.1016/j.eneco.2016.07.018
  45. Phillips, P.C. and Sul, D. (2007). Transition modeling and econometric convergence tests. Econometrica, 75(6), 1771-1855. https://doi.org/10.1111/j.1468-0262.2007.00811.x
  46. Pinar, M. (2024). Convergence in renewable energy innovation and factors influencing convergence club formation. Renewable Energy, 220, 119607. https://doi.org/10.1016/j.renene.2023.119607
  47. Rahman, M.H., Ruma, A., Hossain, M.N., Nahrin, R. and Majumder, S.C. (2021). Examine the empirical relationship between energy consumption and industrialization in Bangladesh: Granger causality analysis. International Journal of Energy Economics and Policy, 11(3), 121-129. https://doi.org/10.32479/ijeep.10843
  48. Rahman, M.M. and Kashem, M.A. (2017). Carbon emissions, energy consumption and industrial growth in Bangladesh: Empirical evidence from ARDL cointegration and Granger causality analysis. Energy Policy, 110, 600-608. https://doi.org/10.1016/j.enpol.2017.09.006
  49. Rios Avila, F., Siles, L. and Canavire-Bacarreza, G.J. (2024). Estimating quantile regressions with multiple fixed effects through method of moments (IZA DP No. 17262). Retrieved from https://www.jstor.org/stable/pdf/resrep69218.pdf?acceptTC=true&coverpage=false&addFooter=false
  50. Saba, C.S. and Ngepah, N. (2022). Convergence in renewable energy sources and the dynamics of their determinants: An insight from a club clustering algorithm. Energy Reports, 8, 3483-3506. https://doi.org/10.1016/j.egyr.2022.01.190
  51. Şahin, B.Y. (2022). Orta gelir grubu ülkelerde gelir yakınsaması: Phillips Sul kulüp yakınsama analizi. Asya Studies, 6(19), 179-188. https://doi.org/10.31455/asya.1023118
  52. Sala-i-Martin, X.X. (1996). Regional cohesion: Evidence and theories of regional growth and convergence. European Economic Review, 40(6), 1325-1352. https://doi.org/10.1016/0014-2921(95)00029-1
  53. Uçar, M. and Çoban, S. (2023). Ulaştırma sektöründeki enerji tüketimi, ekonomik büyüme ve çevresel kalite ilişkisi. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 13(1), 485-506. https://doi.org/10.30783/nevsosbilen.1228732
  54. Ulucak, R. and Apergis, N. (2018). Does convergence really matter for the environment? An application based on club convergence and on the ecological footprint concept for the EU countries. Environmental Science & Policy, 80, 21-27. https://doi.org/10.1016/j.envsci.2017.11.002
  55. Usta, C. and Berber, M. (2017). Türkiye’de enerji tüketimi ekonomik büyüme ilişkisinin sektörel analizi. Ekonomik ve Sosyal Araştırmalar Dergisi, 13(1), 173-187. Erişim adresi: https://dergipark.org.tr/tr/pub/esad
  56. Yağış, O. (2023). Doğalgaz tüketimi ve ekonomik büyüme ilişkisi: Batı Avrupa ülkeleri için Bootstrap panel nedensellik testi. Journal of Economic & Social Research, 10(20), 2148-1407. Erişim adresi: https://openurl.ebsco.com/
  57. Zachariadis, T. (2007). Exploring the relationship between energy use and economic growth with bivariate models: New evidence from G-7 countries. Energy Economics, 29(6), 1233-1253. https://doi.org/10.1016/j.eneco.2007.05.001
  58. Zhang, C. and Xu, J. (2012). Retesting the causality between energy consumption and GDP in China: Evidence from sectoral and regional analyses using dynamic panel data. Energy Economics, 34(6), 1782-1789. https://doi.org/10.1016/j.eneco.2012.07.012
  59. Zhu, J. and Lin, B. (2020). Convergence analysis of city-level energy intensity in China. Energy Policy, 139, 111357. https://doi.org/10.1016/j.enpol.2020.111357
  60. Baktemur, F.İ. and Özmen, M. (2016). AB-27 ülkeleri için gelir yakınsamasının mekânsal ekonometrik analiz ile tahmini. Çukurova Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 20(1), 1-10.