Macaristan Ekonomisinde Enerji Verimliliğini Etkileyen Faktörlerin FOURIER ADL Eşbütünleşme Yaklaşımıyla Belirlenmesi
Year 2022,
Volume: 30 Issue: 53, 487 - 507, 29.07.2022
Mustafa Naimoğlu
,
Ahmet Melik Sahabi
,
Sefa Özbek
Abstract
Bu çalışmada ileri piyasa yükselen ekonomileri arasında enerji verimliliğini en fazla artıran Macaristan ekonomisi için enerji verimliliğini etkileyen faktörler araştırılmıştır. Ampirik yöntem olarak son yıllarda literatüre kazandırılan Fourier ADL yaklaşımı kullanılmıştır. 1990-2020 örneklem döneminde Macaristan ekonomisine ait yıllık kişi başı GSYH, sanayileşme ve fosil yakıt kullanımı ile enerji verimliliği değişkenleri kullanılmıştır. Ampirik bulgular, kişi başı GSYH ve sanayileşmenin enerji verimliliğini artırdığını; fosil yakıt kullanımının ise enerji verimliliğini azalttığını göstermiştir.
References
- Antonietti, R. & F. Fontini (2019), “Does energy price affect energy efficiency? Cross-country panel evidence”, Energy Policy, 129, 896-906.
- Banerjee, P. et al. (2017), “Fourier ADL cointegration test to approximate smooth breaks with new evidence from Crude Oil Market”, Economic Modelling, 67, 114-124.
- Bayar, Y. & M.D. Gavriletea (2019), “Energy efficiency, renewable energy, economic growth: evidence from emerging market economies”, Quality & Quantity, 53(4), 2221-2234.
- Dumitrescu, E.-I. & C. Hurlin (2012), “Testing for Granger non-causality in heterogeneous panels”, Economic Modelling, 29(4), 1450-1460.
- Ediger, V.Ş. (2009), “Türkiye’nin Sürdürülebilir Enerji Gelişimi”, TÜBA Günce, 39, 18-25.
- Enders, W. & J. Lee (2012), “The flexible Fourier form and Dickey-Fuller type unit root tests”, Economics Letters, 117(1), 196-199.
- Farajzadeh, Z. & M.A. Nematollahi (2018), “Energy intensity and its components in Iran: Determinants and trends”, Energy Economics, 73, 161-177.
- Filipovic, S. et al. (2015), “Determinants of energy intensity in the European Union: A panel data analysis”, Energy, 92, 547-555.
- Fitriyanto, F. & D.D. Iskandar (2019), “An analysis on determinants of energy intensity in ASEAN countries”, Jurnal Ekonomi dan Studi Pembangunan, 11(1), 90-103.
- Işığıçok, E. (1994), Zaman serilerinde nedensellik çözümlemesi: Türkiye'de para arzı ve enflasyon üzerine amprik bir araştırma, Bursa: Uludağ Üniversitesi Basımevi.
- İslatince, H. & C. Haydaroğlu (2009), “Türk İmalat Sanayiinde Enerji Verimliliği ve Yoğunluluğunun Analizi”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (24), 155-164.
- Kao, C. (1999), “Spurious regression and residual-based tests for cointegration in panel data”, Journal of Econometrics, 90(1), 1-44.
- Karabat, S. & B. Aydın (2018), “İyi Tarım Uygulamalarının Mandarin Üretiminde Enerji Kullanım Etkinliği ve Ekonomik Analiz Üzerine Etkisi: İzmir İli Örneği”, Toprak Su Dergisi, 7(1), 1-10.
- Malik, A. (2019), “Dynamics and Determinants of Energy Intensity: Evidence from Pakistan”, Journal of Academic Research in Economics, 11(2), 249-275.
- Mark, N.C. & D. Sul (2003), “Cointegration vector estimation by panel DOLS and long‐run money demand”, Oxford Bulletin of Economics and Statistics, 65(5), 655-680.
- Mehmood, B. et al. (2014), “What causes what? Aviation demand and economic growth in Romania: Cointegration estimation and causality analysis”, Romanian Economic Business Review, 9(1), 21-34.
- Murshed, M. (2020), “An empirical analysis of the non-linear impacts of ICT-trade openness on renewable energy transition, energy efficiency, clean cooking fuel access and environmental sustainability in South Asia”, Environmental Science and Pollution Research, 27(29), 36254-36281.
- Nazlıoğlu, Ş. (2010), “Makro iktisat politikalarının tarım sektörü üzerindeki etkileri: Gelişmiş ve gelişmekte olan ülkeler için bir karşılaştırma”, Doktora Tezi, Kayseri: Erciyes Üniversitesi Sosyal Bilimler Enstitüsü.
- Özkara, Y. (2015), “Türk İmalat Sanayinin Bölgesel Düzeyde Etkinlik, Verimlilik ve Enerji Verimliliğinin Analizi (2003-2012)”, Doktora Tezi, Ankara: Gazi Üniversitesi Fen Bilimleri Enstitüsü.
- Park, J.Y. (1992), “Canonical Cointegrating Regressions”, Econometrica, 60(1), 119-143.
- Patterson, M.G. (1996), “What is energy efficiency?: Concepts, indicators and methodological issues”, Energy Policy, 24(5), 377-390.
- Phillips, P.C.B. & B.E. Hansen (1990), “Statistical-Inference in Instrumental Variables Regression with I(1) Processes”, Review of Economic Studies, 57(1), 99-125.
- Sadorsky, P. (2013), “Do urbanization and industrialization affect energy intensity in developing countries?”, Energy Economics, 37, 52-59.
- Sener, S. & A.T. Karakas (2019), “The effect of economic growth on energy efficiency: evidence from high, upper-middle and lower-middle income countries”, Procedia Computer Science, 158, 523-532.
- Solarin, S.A. (2020), “Towards sustainable development in developing countries: aggregate and disaggregate analysis of energy intensity and the role of fossil fuel subsidies”, Sustainable Production Consumption, 24, 254-265.
- Stock, J.H. & M.W. Watson (1993), “A simple estimator of cointegrating vectors in higher order integrated systems”, Econometrica: Journal of the Econometric Society, 783-820.
- Takim, A. (2010), “Türkiye’de GSYH ile ihracat arasındaki ilişki: granger nedensellik testi”, Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 14(2), 315-330.
- Tuominen, P. et al. (2013), “Economic effects of energy efficiency improvements in the Finnish building stock”, Energy Policy, 52, 181-189.
- Westerlund, J. (2005), “New simple tests for panel cointegration”, Econometric Reviews, 24(3), 297-316.
- Westerlund, J. (2007), “Testing for error correction in panel data”, Oxford Bulletin of Economics Statistics, 69(6), 709-748.
- Westerlund, J. (2008), “Panel cointegration tests of the Fisher effect”, Journal of Applied Econometrics, 23(2), 193-233.
- World Bank (2021), World Development Indicators Online Database, <https://databank.worldbank.org/source/world-developmentindicators>, 06.02.2021.
Determination of Factors Affecting Energy Efficiency in Hungary’s Economy by FOURIER ADL Cointegration Approach
Year 2022,
Volume: 30 Issue: 53, 487 - 507, 29.07.2022
Mustafa Naimoğlu
,
Ahmet Melik Sahabi
,
Sefa Özbek
Abstract
In this study, the factors affecting energy efficiency were investigated for the Hungarian economy, which increased energy efficiency the most among the developed market emerging economies. The Fourier ADL approach, introduced to the literature recently, has been used as an empirical method. In the sample period of 1990-2020, the annual GDP per capita of the Hungarian economy, industrialisation and fossil fuel use, and energy efficiency variables were used. Empirical findings show that GDP per capita and industrialisation increase energy efficiency; It has been shown that the use of fossil fuels reduces energy efficiency.
References
- Antonietti, R. & F. Fontini (2019), “Does energy price affect energy efficiency? Cross-country panel evidence”, Energy Policy, 129, 896-906.
- Banerjee, P. et al. (2017), “Fourier ADL cointegration test to approximate smooth breaks with new evidence from Crude Oil Market”, Economic Modelling, 67, 114-124.
- Bayar, Y. & M.D. Gavriletea (2019), “Energy efficiency, renewable energy, economic growth: evidence from emerging market economies”, Quality & Quantity, 53(4), 2221-2234.
- Dumitrescu, E.-I. & C. Hurlin (2012), “Testing for Granger non-causality in heterogeneous panels”, Economic Modelling, 29(4), 1450-1460.
- Ediger, V.Ş. (2009), “Türkiye’nin Sürdürülebilir Enerji Gelişimi”, TÜBA Günce, 39, 18-25.
- Enders, W. & J. Lee (2012), “The flexible Fourier form and Dickey-Fuller type unit root tests”, Economics Letters, 117(1), 196-199.
- Farajzadeh, Z. & M.A. Nematollahi (2018), “Energy intensity and its components in Iran: Determinants and trends”, Energy Economics, 73, 161-177.
- Filipovic, S. et al. (2015), “Determinants of energy intensity in the European Union: A panel data analysis”, Energy, 92, 547-555.
- Fitriyanto, F. & D.D. Iskandar (2019), “An analysis on determinants of energy intensity in ASEAN countries”, Jurnal Ekonomi dan Studi Pembangunan, 11(1), 90-103.
- Işığıçok, E. (1994), Zaman serilerinde nedensellik çözümlemesi: Türkiye'de para arzı ve enflasyon üzerine amprik bir araştırma, Bursa: Uludağ Üniversitesi Basımevi.
- İslatince, H. & C. Haydaroğlu (2009), “Türk İmalat Sanayiinde Enerji Verimliliği ve Yoğunluluğunun Analizi”, Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (24), 155-164.
- Kao, C. (1999), “Spurious regression and residual-based tests for cointegration in panel data”, Journal of Econometrics, 90(1), 1-44.
- Karabat, S. & B. Aydın (2018), “İyi Tarım Uygulamalarının Mandarin Üretiminde Enerji Kullanım Etkinliği ve Ekonomik Analiz Üzerine Etkisi: İzmir İli Örneği”, Toprak Su Dergisi, 7(1), 1-10.
- Malik, A. (2019), “Dynamics and Determinants of Energy Intensity: Evidence from Pakistan”, Journal of Academic Research in Economics, 11(2), 249-275.
- Mark, N.C. & D. Sul (2003), “Cointegration vector estimation by panel DOLS and long‐run money demand”, Oxford Bulletin of Economics and Statistics, 65(5), 655-680.
- Mehmood, B. et al. (2014), “What causes what? Aviation demand and economic growth in Romania: Cointegration estimation and causality analysis”, Romanian Economic Business Review, 9(1), 21-34.
- Murshed, M. (2020), “An empirical analysis of the non-linear impacts of ICT-trade openness on renewable energy transition, energy efficiency, clean cooking fuel access and environmental sustainability in South Asia”, Environmental Science and Pollution Research, 27(29), 36254-36281.
- Nazlıoğlu, Ş. (2010), “Makro iktisat politikalarının tarım sektörü üzerindeki etkileri: Gelişmiş ve gelişmekte olan ülkeler için bir karşılaştırma”, Doktora Tezi, Kayseri: Erciyes Üniversitesi Sosyal Bilimler Enstitüsü.
- Özkara, Y. (2015), “Türk İmalat Sanayinin Bölgesel Düzeyde Etkinlik, Verimlilik ve Enerji Verimliliğinin Analizi (2003-2012)”, Doktora Tezi, Ankara: Gazi Üniversitesi Fen Bilimleri Enstitüsü.
- Park, J.Y. (1992), “Canonical Cointegrating Regressions”, Econometrica, 60(1), 119-143.
- Patterson, M.G. (1996), “What is energy efficiency?: Concepts, indicators and methodological issues”, Energy Policy, 24(5), 377-390.
- Phillips, P.C.B. & B.E. Hansen (1990), “Statistical-Inference in Instrumental Variables Regression with I(1) Processes”, Review of Economic Studies, 57(1), 99-125.
- Sadorsky, P. (2013), “Do urbanization and industrialization affect energy intensity in developing countries?”, Energy Economics, 37, 52-59.
- Sener, S. & A.T. Karakas (2019), “The effect of economic growth on energy efficiency: evidence from high, upper-middle and lower-middle income countries”, Procedia Computer Science, 158, 523-532.
- Solarin, S.A. (2020), “Towards sustainable development in developing countries: aggregate and disaggregate analysis of energy intensity and the role of fossil fuel subsidies”, Sustainable Production Consumption, 24, 254-265.
- Stock, J.H. & M.W. Watson (1993), “A simple estimator of cointegrating vectors in higher order integrated systems”, Econometrica: Journal of the Econometric Society, 783-820.
- Takim, A. (2010), “Türkiye’de GSYH ile ihracat arasındaki ilişki: granger nedensellik testi”, Atatürk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 14(2), 315-330.
- Tuominen, P. et al. (2013), “Economic effects of energy efficiency improvements in the Finnish building stock”, Energy Policy, 52, 181-189.
- Westerlund, J. (2005), “New simple tests for panel cointegration”, Econometric Reviews, 24(3), 297-316.
- Westerlund, J. (2007), “Testing for error correction in panel data”, Oxford Bulletin of Economics Statistics, 69(6), 709-748.
- Westerlund, J. (2008), “Panel cointegration tests of the Fisher effect”, Journal of Applied Econometrics, 23(2), 193-233.
- World Bank (2021), World Development Indicators Online Database, <https://databank.worldbank.org/source/world-developmentindicators>, 06.02.2021.