IDEAS home Printed from https://ideas.repec.org/a/ahs/journl/v6y2021i1p254-274.html
   My bibliography  Save this article

Türkiye’de Sektör ve Kaynak Bazlı Enerji Kullanımları Yakınsıyor mu? Panel TAR ve Çoklu Kırılmalı Birim Kök Bulguları

Author

Listed:
  • Kumru Türköz
  • Utku Utkulu

Abstract

Fosil yakıtların neden olduğu çevresel baskının ortadan kaldırılması için yeşil büyüme, sürdürülebilir büyüme ve yenilenebilir kaynakların enerji kullanımındaki payının artırılması gibi alternatif çözümler ortaya atılmaktadır. Buradan hareketle bu çalışmada; sektörel dönüşümlerin yaşandığı 1970-2017 dönemi Türkiye ekonomisinde sektörel bazda enerji kaynakları arasında bir olası yakınsama ilişkisinin olup olmadığı, var ise bu ilişkinin fosil mi yoksa yenilenebilir kaynaklar yoluyla mı gerçekleştiği ampirik olarak test edilmektedir. Panel TAR (Threshold Autoregressive Model-Eşik Otoregresif Model) veri analiz bulguları; ilgili sektörler arasında doğrusal model altında bir yakınsama ilişkisi olmadığına, ancak farklı formlara sahip iki rejim altında kısmi bir yakınsama ilişkisi olduğuna işaret etmektedir. Buna ek olarak gerçekleştirilen çoklu yapısal kırılmalı Lumsdaine-Papell birim kök analiz bulguları ise bu kısmi yakınsamanın ilgili sektörlerde kullanılan fosil yakıtlar aracılığıyla gerçekleştiğini göstermektedir. Sektörler içerisinde sınırlı kullanım alanı bulunması nedeniyle yenilenebilir kaynakların hiçbir sektörde yakınsama göstermiyor oluşu, yenilenebilir (temiz) enerjiye yönelmeyi amaçlayan Türkiye’nin uyguladığı politikaların ve teşviklerin uygulamada yetersiz kaldığının bir göstergesi olarak değerlendirilmektedir.

Suggested Citation

  • Kumru Türköz & Utku Utkulu, 2021. "Türkiye’de Sektör ve Kaynak Bazlı Enerji Kullanımları Yakınsıyor mu? Panel TAR ve Çoklu Kırılmalı Birim Kök Bulguları," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 6(1), pages 254-274.
    • Handle: RePEc:ahs:journl:v:6:y:2021:i:1:p:254-274
    DOI: 10.30784/epfad.863388
    as

    Download full text from publisher

    File URL: https://dergipark.org.tr/tr/download/article-file/1517149
    Download Restriction: no
    File URL: https://libkey.io/10.30784/epfad.863388?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Martchamadol, Jutamanee & Kumar, S., 2013. "An aggregated energy security performance indicator," Applied Energy, Elsevier, vol. 103(C), pages 653-670.
    2. Lee, Chien-Chiang & Chang, Chun-Ping, 2007. "The impact of energy consumption on economic growth: Evidence from linear and nonlinear models in Taiwan," Energy, Elsevier, vol. 32(12), pages 2282-2294.
    3. Lee, Chul-Yong & Huh, Sung-Yoon, 2017. "Forecasting new and renewable energy supply through a bottom-up approach: The case of South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 207-217.
    4. Dan Ben-David & Robin L. Lumsdaine & David H. Papell, 2003. "Unit roots, postwar slowdowns and long-run growth: Evidence from two structural breaks," Empirical Economics, Springer, vol. 28(2), pages 303-319, April.
    5. Meng, Ming & Payne, James E. & Lee, Junsoo, 2013. "Convergence in per capita energy use among OECD countries," Energy Economics, Elsevier, vol. 36(C), pages 536-545.
    6. Aslan, Alper & Kum, Hakan, 2011. "The stationary of energy consumption for Turkish disaggregate data by employing linear and nonlinear unit root tests," Energy, Elsevier, vol. 36(7), pages 4256-4258.
    7. Markandya, Anil & Pedroso-Galinato, Suzette & Streimikiene, Dalia, 2006. "Energy intensity in transition economies: Is there convergence towards the EU average?," Energy Economics, Elsevier, vol. 28(1), pages 121-145, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Smyth, Russell & Narayan, Paresh Kumar, 2015. "Applied econometrics and implications for energy economics research," Energy Economics, Elsevier, vol. 50(C), pages 351-358.
    2. Romero-Ávila, Diego & Omay, Tolga, 2022. "Convergence of per capita energy consumption around the world: New evidence from nonlinear panel unit root tests," Energy Economics, Elsevier, vol. 111(C).
    3. Akram, Vaseem & Rath, Badri Narayan & Sahoo, Pradipta Kumar, 2020. "Stochastic conditional convergence in per capita energy consumption in India," Economic Analysis and Policy, Elsevier, vol. 65(C), pages 224-240.
    4. Mishra, Vinod & Smyth, Russell, 2014. "Convergence in energy consumption per capita among ASEAN countries," Energy Policy, Elsevier, vol. 73(C), pages 180-185.
    5. Wang, Na & Fu, Xiaodong & Wang, Shaobin & Yang, Hao & Li, Zhen, 2022. "Convergence characteristics and distribution patterns of residential electricity consumption in China: An urban-rural gap perspective," Energy, Elsevier, vol. 254(PB).
    6. Mishra, Vinod & Smyth, Russell, 2017. "Conditional convergence in Australia's energy consumption at the sector level," Energy Economics, Elsevier, vol. 62(C), pages 396-403.
    7. Schneider, Nicolas & Strielkowski, Wadim, 2023. "Modelling the unit root properties of electricity data—A general note on time-domain applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    8. Luqman, Muhammad & Ahmad, Najid & Bakhsh, Khuda, 2019. "Nuclear energy, renewable energy and economic growth in Pakistan: Evidence from non-linear autoregressive distributed lag model," Renewable Energy, Elsevier, vol. 139(C), pages 1299-1309.
    9. Salman, Muhammad & Zha, Donglan & Wang, Guimei, 2022. "Assessment of energy poverty convergence: A global analysis," Energy, Elsevier, vol. 255(C).
    10. Wu, Jianxin & Wu, Yanrui & Se Cheong, Tsun & Yu, Yanni, 2018. "Distribution dynamics of energy intensity in Chinese cities," Applied Energy, Elsevier, vol. 211(C), pages 875-889.
    11. Lean, Hooi Hooi & Smyth, Russell, 2014. "Will initiatives to promote hydroelectricity consumption be effective? Evidence from univariate and panel LM unit root tests with structural breaks," Energy Policy, Elsevier, vol. 68(C), pages 102-115.
    12. Lean, Hooi Hooi & Smyth, Russell, 2014. "Are shocks to disaggregated energy consumption in Malaysia permanent or temporary? Evidence from LM unit root tests with structural breaks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 319-328.
    13. Borozan, Djula, 2017. "Testing for convergence in electricity consumption across Croatian regions at the consumer's sectoral level," Energy Policy, Elsevier, vol. 102(C), pages 145-153.
    14. Le, Thai-Ha & Chang, Youngho & Park, Donghyun, 2017. "Energy demand convergence in APEC: An empirical analysis," Energy Economics, Elsevier, vol. 65(C), pages 32-41.
    15. Liu, Tie-Ying & Lee, Chien-Chiang, 2020. "Convergence of the world’s energy use," Resource and Energy Economics, Elsevier, vol. 62(C).
    16. Cai, Yifei & Menegaki, Angeliki N., 2019. "Fourier quantile unit root test for the integrational properties of clean energy consumption in emerging economies," Energy Economics, Elsevier, vol. 78(C), pages 324-334.
    17. Ivanovski, Kris & Awaworyi Churchill, Sefa & Smyth, Russell, 2018. "A club convergence analysis of per capita energy consumption across Australian regions and sectors," Energy Economics, Elsevier, vol. 76(C), pages 519-531.
    18. Erdogan, Sinan & Akalin, Guray & Oypan, Oguz, 2020. "Are shocks to disaggregated energy consumption transitory or permanent in Turkey? New evidence from fourier panel KPSS test," Energy, Elsevier, vol. 197(C).
    19. Mohammadi, Hassan & Ram, Rati, 2017. "Convergence in energy consumption per capita across the US states, 1970–2013: An exploration through selected parametric and non-parametric methods," Energy Economics, Elsevier, vol. 62(C), pages 404-410.
    20. Hao, Yu & Peng, Hui, 2017. "On the convergence in China's provincial per capita energy consumption: New evidence from a spatial econometric analysis," Energy Economics, Elsevier, vol. 68(C), pages 31-43.

    More about this item

    Keywords

    Enerji Kullanımı; Sektör-Kaynak Analizi; Yakınsama Analizi; Panel TAR Veri Analizi; Lumsdaine-Papell Çoklu Kırılmalı Birim Kök Testi;
    All these keywords.

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ahs:journl:v:6:y:2021:i:1:p:254-274. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ersan Ersoy (email available below). General contact details of provider: https://epfjournal.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.