Türkiye'de Fosil Yakıtların ve Makroekonomik Göstergelerin Elektrik Sektörüne Etkisi: Dilim Regresyon Analizi

Yıl 2024, , 959 - 976, 25.12.2024

Şahnaz Koçoğlu

https://doi.org/10.26745/ahbvuibfd.1452173

Öz

İklim değişikliği, dünya genelinde tüm uluslar için bir güvenlik sorunu haline gelmiştir. İklim değişikliğinin nedeni karbondioksit birikimidir. Karbon emisyonunun başlıca nedeni, özellikle doğal gaz ve kömür olmak üzere fosil yakıtlara dayalı elektrik üreticileridir. Bu nedenle ülkeler, fosil yakıtlara dayalı enerji üretimini azaltmaya ve yenilenebilir enerji üretimine geçmeye çalışmaktadır. Tüm çabalara rağmen, doğal gaz ve kömür hala elektrik üretiminde önemli bir kaynaktır. Türkiye de farklı değildir ve doğal gaz ve kömüre dayalı elektrik üretimi önemli bir enerji kaynağıdır. İklim değişikliğinin yanı sıra, Rusya ve Ukrayna arasındaki savaş, doğal gaz bağımlılığının ciddi bir güvenlik sorunu olabileceğini göstermiştir. Bu çalışma, Borsa İstanbul'da işlem gören elektrik firmalarının üstünde doğal gaz ve kömür fiyatları ile birlikte temel makro ekonomik faktörlerin etkisini araştırmayı amaçlamaktadır. Farklı piyasa koşullarında faktörlerin etkisini belirlemek için dilim regresyon modeli kullanılmaktadır. BIST 100 endeksinin, döviz kurunun ve kömürün BIST Elektrik endeksi üstünde istatistiksel olarak bir etkisi gözlemlenmiştir.

Anahtar Kelimeler

Elektrik firmaları, doğalgaz, kömür, dilim regresyon

The Effect of Fossil Fuels and Macroeconomic Indicators on the Electricity Sector in Turkey: Quantile Regression Analysis

Öz

Climate change has turned to be a security problem for all nations in the world. The reason of climate change is the cumulation of carbon dioxide. The major reason of carbon emission is the electricity producers depending on fossil fuels especially natural gas and coal. Therefore, the countries are trying to phase out the fossil fuel-based energy production and switch to renewable energy production. Despite all the efforts natural gas and coal are still the major resources in electricity production. Turkey is no different and natural gas and coal-based electricity production is an important source of energy. Besides climate change, the war between Russia and Ukraine also showed that natural gas dependence can be a serious security issue. This study aims to explore the impact of natural gas and coal prices together with major macro-economic factors on the electricity firms enlisted in Borsa İstanbul. Quantile regression model is used to determine the impact of factors in different market conditions. Statistically significant impact of BIST 100, exchange rate and coal on BIST Electricity index is observed.

Anahtar Kelimeler

Electricity firms, natural gas, coal, quantile regression

Kaynakça

• Boyer, M. M., & Filion, D. (2007). Common and fundamental factors in stock returns of Canadian oil and gas companies. Energy economics, 29(3). 428-453.
• Broadstock, D. C., Cao, H., & Zhang, D. (2012). Oil shocks and their impact on energy related stocks in China. Energy Economics, 34(6). 1888-1895.
• C2ES (2023). Global Emissions. https://www.c2es.org/content/international-emissions/#:~:text=Globally%2C%20the%20primary%20sources%20of,72%20percent%20of%20all%20emissions.
• Degiannakis, S., Filis, G., & Floros, C. (2013). Oil and stock returns: Evidence from European industrial sector indices in a time-varying environment. Journal of International Financial Markets. Institutions and Money, 26, 175-191.
• Dickey, D, A,, & Fuller, W, A, (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American statistical association, 74(366a). 427-431.
• Faff, R. W., & Brailsford, T. J. (1999). Oil price risk and the Australian stock market. Journal of Energy Finance & Development, 4(1). 69-87.
• Filis, G., Degiannakis, S., & Floros, C. (2011). Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries. International review of financial analysis, 20(3). 152-164.
• Huang, S., & Liu, H. (2021). Impact of COVID-19 on stock price crash risk: Evidence from Chinese energy firms. Energy Economics, 101, 105431.
• Investing.com(2024). Dataset. https://www.investing.com/
• Koçoğlu, Ş., & Tanrıöven, C. (2019). Borsa İstanbul'da İşlem Gören Enerji Firmalarının Hisse Senedi Getirilerine Etki Eden Finansal Faktörler. İşletme Araştırmaları Dergisi, 11(1). 666-673.
• Koenker, R,, & Bassett Jr, G, (1978). Regression quantiles. Econometrica: journal of the Econometric Society, 46(1), 33-50.
• Ma, Y. R., Zhang, D., Ji, Q., & Pan, J. (2019). Spillovers between oil and stock returns in the US energy sector: does idiosyncratic information matter?. Energy Economics, 81, 536-544.
• Mensi, W., Hammoudeh, S., Reboredo, J. C., & Nguyen, D. K. (2014). Do global factors impact BRICS stock markets? A quantile regression approach. Emerging Markets Review, 19, 1-17.
• Narayan, P. K., & Sharma, S. S. (2011). New evidence on oil price and firm returns. Journal of Banking & Finance, 35(12). 3253-3262.
• Nusair, S. A. (2016). The effects of oil price shocks on the economies of the Gulf Co-operation Council countries: Nonlinear analysis. Energy Policy, 91, 256-267.
• Park, J., & Ratti, R. A. (2008). Oil price shocks and stock markets in the US and 13 European countries. Energy economics, 30(5). 2587-2608.
• Phillips, P, C,, & Perron, P, (1988). Testing for a unit root in time series regression. Biometrika, 75(2). 335-346
• Sadorsky, P. (1999). Oil price shocks and stock market activity. Energy economics, 21(5). 449-469.
• Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. The journal of finance, 19(3). 425-442.
• T.C. Enerji ve Tabii Kaynaklar Bakanlığı (2023). Elektrik. https://enerji.gov.tr/bilgi-merkezi-enerji-elektrik
• TCMB(2023). Son Dönem Enerji İthalatı Gelişmeleri ve Enerji Arzında Çeşitlendirme Politikaları. https://www.tcmb.gov.tr/
• Tiwari, A. K., Jena, S. K., Mitra, A., & Yoon, S. M. (2018). Impact of oil price risk on sectoral equity markets: Implications on portfolio management. Energy Economics, 72, 120-134.
• Yang, L., Zhu, Y., Wang, Y., & Wang, Y. (2016). Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets. Physica A: Statistical Mechanics and Its Applications, 462, 255-265.