Öz
Compared to 1990, Germany's GDP increased by 54% in 2019; renewable energy R&D expenditures increased by 99% and renewable energy use increased by 84811% (excluding hydro), while total energy consumption decreased by 14% and total energy losses 415%. In other words, Germany increased its use of renewable energy with its high income and managed to reduce its total energy consumption and total energy losses significantly. In the same period, France and Italy, which are partners between the G7 countries and the European Union countries, increased their total energy consumption by 7% and 0.71%. In comparison, Germany achieved a remarkable reduction of 14%. Therefore, the difference of this study from other studies is that the question of how Germany earned more income with less energy in the relevant period is investigated by econometric methods. In doing so, R&D expenditures made in renewable energy, non-renewable energy and nuclear energy were used for Germany from 1990 to 2019. For this purpose, the stability of the variables was investigated during the period examined by using Perron (1989) and Zivot and Andrews (1992) tests in which structural breaks were taken into account. Later, the long-term relationship was tested with the Gregory and Hansen (1996) cointegration test, and a cointegration relationship was found. Then, it was tested with estimators that structural changes such as the Developed Least Squares Method (FMOLS) and Canonical Cointegrated Regression (CCR) were included in the model as dummy variables for the long-term relationship. The findings show that the energy R&D expenditure for Germany that decreases the total energy use amount the most in the long term is the R&D expenditure for renewable energy. In contrast, the energy R&D expenditure that increases the most is the R&D expenditure for nuclear energy. Germany's increase in renewable energy R&D expenditures by 99% in 2019 compared to 1990 and decreased nuclear energy R&D expenditures by 45.46% supports the results obtained. Therefore, improvements in energy in Germany offer significant opportunities.
Anahtar Kelimeler
Energy consumption R&D expenditure Renewable Energy Non-Renewable Energy Nuclear Energy Germany
Kaynakça
- AFLAKİ, S., BASHER, S. A., & MASİNİ, A. (2014), Does economic growth matter? Technology-push, demand-pull and endogenous drivers of innovation in the renewable energy industry, HEC Paris Research Paper No. MOSI-2015-1070.
- ÁLVAREZ-HERRÁNZ, A., BALSALOBRE-LORENTE, D., SHAHBAZ, M., & CANTOS, J. M. (2017a), Energy innovation and renewable energy consumption in the correction of air pollution levels, Energy Policy 105:386–397.
- ÁLVAREZ-HERRÁNZ, A., BALSALOBRE, D., CANTOS, J. M., & SHAHBAZ, M. (2017b), Energy innovations-GHG emissions nexus: fresh empirical evidence from OECD countries, Energy Policy 101:90–100.
- BALSALOBRE, D., ÁLVAREZ, A., & CANTOS, J. M. (2015), Public budgets for energy RD&D and the effects on energy intensity and pollution levels, Environmental Science and Pollution Research, 22(7), 4881-4892.
- CHO, C.H., YANG, L. J., CHU, Y. P. & YANG, H. Y. (2013), Renewable energy and renewable R&D in EU countries: A cointegration analysis, Asian Journal of Natural & Applied Sciences, 2:1, 10-16.
- DAI, Q., & BIE, Z. (2006), FDI, Accumulation of Human Capital and Economic Growth, Econ. Res. J., 4, 15–27
- DINDA, S. (2011), Carbon emission and production technology: Evidence from the US, MPRA, 31935.
- FERNÁNDEZ, FY., LÓPEZ, FMA., BLANCO, OB. (2018), Innovation for sustainability: the impact of R&D spending on CO2 emissions, J Clean Prod 172:3459–3467.
- GREGORY, A. W., & HANSEN, B. E. (1996), Residual-Based Tests for Cointegration in Models With Regime Shifts, Journal of Econometrics, Vol. 70, pp. 99-126.
- GRILICHES, Z. (1998), Patent statistics as economic indicators: a survey. In R&D and productivity: the econometric evidence, University of Chicago Press, 287-343.
- IEA(INTERNATIONAL ENERGY AGENCY), (2015), Energy efficiency market report, Paris: International Energy Agency, issues, Energy policy, 24(5), 377-390.
- IRANDOUST, M. (2016), The renewable energy-growth nexus with carbon emissions and technological innovation: Evidence from the Nordic countries, Ecological Indicators, 69, 118-125.
- JIN, L., DUAN, K., SHI, C., & JU, X. (2017), The impact of technological progress in the energy sector on carbon emissions: an empirical analysis from China, Int J Environ Res Public Health 14:1–14.
- JUN, C., & SHIYUAN, X. (2008), The Impact of Technical Progress over China's Energy Efficiency: 1972-2006, Scientific Management Research, 1.
- KAHOULI, B. (2018), The causality link between energy electricity consumption, CO2 emissions, R&D stocks and economic growth in Mediterranean countries (MCs), Energy 145:388–399.
- LANTZ, V., & FENG, Q. (2006), Assessing income, population, and technology impacts on CO2 emissions in Canada: where’s the EKC?, Ecol Econ 57:229–238.
- LEE, K. H., & MIN, B. (2015), Green R&D for eco-innovation and its impact on carbon emissions and firm performance, Journal of Cleaner Production, 108, 534-542.
- LI, W., WANG, W., WANG, Y., & QİN, Y. (2017), Industrial structure, technological progress and CO2 emissions in China: analysis based on the STIRPAT framework, Nat Hazards 88:1545–1564.
- MEHMOOD, B., FELICEO, A., & SHAHİD, A. (2014), What Causes What? Aviation Demand and Economic Growth in Romania: Cointegration Estimation and Causality Analysis, Romanian Economic and Business Review, s.9, pp. 21-34.
- MENSAH, CN., LONG, X., BOAMAH, KB., BEDIAKO, IA., DAUDA, L., & SALMAN, M. (2018), The effect of innovation on CO2 emissions of OCED countries from 1990 to 2014, Environ Sci Pollut Res 25:29678–29698.
- NAZLIOĞLU, Ş. (2010), Makro İktisat Politikalarının Tarım Sektörü Üzerindeki Etkileri: Gelişmiş Ve Gelişmekte Olan Ülkeler İçin Bir Karşılaştırma, Erciyes Üniversitesi Sosyal Bilimler Enstitüsü, İktisat Anabilim Dalı, Yayınlanmamış Doktora Tezi, Kayseri.
- ÖZKAN, A. (2016), Güvenlik Paradigmasında Sınıraşan Bir Çevre Sorunsalı: “Nükleer Zarar”, Alternatif Politika, 8(1), 128-159.
- PARK, J.Y. (1992), Canonical Cointegrating Regressions, Econometrica: Journal of the Econometric Society, S.60(1), ss.119-143.
- PERRON, P. (1989), The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis, Econometrica, vol. 57, no. 6, pp.1361-1401.
- PHİLLİPS, P., & HANSEN, B. (1990), Statistical Inference in Instrumental Variables Regression with I(1) Processes, Review of Economic Studies, 57, 99-125.
- SAHU, S. K., & NARAYANAN, K. (2013), Carbon dioxide emissions from Indian manufacturing industries: Role of energy and technology intensity, Madras School of Economics, 82.
- SAİTO, S., (2010), Role of nuclear energy to a future society of shortage of energy resources and global warming, Journal of Nuclear Materials, 398(1-3), 1-9.
- SOHAG, K., BEGUM, R. A., ABDULLAH, S. M. S., & JAAFAR, M. (2015), Dynamics of energy use, technological innovation, economic growth and trade openness in Malaysia, Energy, 90, 1497-1507.
- TIRAŞOĞLU, M., & BURCU, Y. (2012), Yapısal Kırılma Durumunda Sağlık Harcamaları ve Ekonomik Büyüme İlişkisi: Türkiye Üzerine Bir Uygulama, Electronic Journal of Vocational Colleges, S. 2, s.111-117.
- ZHOU, Z., YE, X., & GE, X. (2017), The impacts of technical progress on sulfur dioxide Kuznets curve in China: a spatial panel data approach. Sustain, 9.
- ZIVOT, E., & ANDREWS, D. (1992), Further Evidence On The Great Crash, The OilPrice Shock, and The Unit Root Hypothesis, Journal of Business & Economic Statistics, vol. 10, no. 3, pp.251-270. ZOLTAN J. A., ANSELİN, L., & VARGA, A. (2002), Patents and innovation counts as measures of regional production of new knowledge, Research policy, 31(7), 1069-1085.
Öz
Almanya’nın 1990 yılına göre 2019 yılında GSYİH’sı %54, yenilenebilir enerji AR-GE harcamaları %99 ve yenilenebilir enerji kullanımı %84811(hidro hariç) artış gösterirken, toplam enerji tüketimi %14 ve toplam enerji kayıpları %415 oranında azalış göstermiştir. Yani Almanya yenilenebilir enerji kullanımını geliriyle beraber yüksek oranda artırmanın yanında toplam enerji tüketimini ve toplam enerji kayıplarını ciddi oranda azaltmayı başarmıştır. Ayrıca aynı dönemde G7 ülkeleri ve Avrupa Birliği ülkeleri arasında ortak olarak yer alan Fransa ve İtalya ülkeleri sırasıyla %7 ve %0.71 oranında toplam enerji tüketimini artırırken, Almanya ise %14 gibi dikkate değer bir oranda toplam enerji tüketimini azaltmayı başarmıştır. Dolayısıyla bu çalışmanın diğer çalışmalardan farkı Almanya’nın ilgili dönemde daha az enerjiyle nasıl daha fazla gelir elde ettiği sorusunun ekonometrik yöntemlerle araştırılmasıdır. Bunu yaparken Almanya için 1990-2019 döneminde yıllık verilerle yenilenebilir enerji, yenilenemez enerji ve nükleer enerji alanlarında yapılan AR-GE harcamaları kullanılmıştır. Bu amaçla yapısal kırılmaların dikkate alındığı Perron (1989) ve Zivot ve Andrews (1992) testleri kullanılarak incelenen dönem boyunca değişkenlerin durağanlığı araştırılmıştır. Sonra uzun dönem ilişkisi Gregory ve Hansen (1996) eşbütünleşme testi ile sınanmış ve eşbütünleşme ilişkisine rastlanmıştır. Daha sonra uzun dönemli ilişki için Geliştirilmiş En Küçük Kareler Yöntemi (FMOLS) ve Kanonik Eşbütünleşik Regresyon (CCR) gibi yapısal değişmelerin kukla değişken olarak modele dâhil edildiği tahmincilerle test edilmiştir. Bulgular, Almanya için uzun dönemde toplam enerji kullanım miktarını en fazla azaltan enerji AR-GE harcaması türünün yenilenebilir enerji için yapılan AR-GE harcamaları olduğunu, en fazla artıran enerji AR-GE harcamaları türünün ise nükleer enerji için yapılan AR-GE harcamaları olduğunu göstermiştir. Almanya’nın 1990 yılına göre 2019 yılında yenilenebilir enerji AR-GE harcamalarını %99 oranında arttırması ve nükleer enerji AR-GE harcamalarını ise %45.46 oranında azaltması elde edilen sonuçları desteklemektedir. Dolayısıyla Almanya için enerji alanında yapılan iyileştirmeler çok önemli fırsatlar sunmaktadır.
Anahtar Kelimeler
Enerji tüketimi AR-GE harcamaları Yenilenebilir Enerji Yenilenemez enerji Nükleer enerji Almanya.
Kaynakça
- AFLAKİ, S., BASHER, S. A., & MASİNİ, A. (2014), Does economic growth matter? Technology-push, demand-pull and endogenous drivers of innovation in the renewable energy industry, HEC Paris Research Paper No. MOSI-2015-1070.
- ÁLVAREZ-HERRÁNZ, A., BALSALOBRE-LORENTE, D., SHAHBAZ, M., & CANTOS, J. M. (2017a), Energy innovation and renewable energy consumption in the correction of air pollution levels, Energy Policy 105:386–397.
- ÁLVAREZ-HERRÁNZ, A., BALSALOBRE, D., CANTOS, J. M., & SHAHBAZ, M. (2017b), Energy innovations-GHG emissions nexus: fresh empirical evidence from OECD countries, Energy Policy 101:90–100.
- BALSALOBRE, D., ÁLVAREZ, A., & CANTOS, J. M. (2015), Public budgets for energy RD&D and the effects on energy intensity and pollution levels, Environmental Science and Pollution Research, 22(7), 4881-4892.
- CHO, C.H., YANG, L. J., CHU, Y. P. & YANG, H. Y. (2013), Renewable energy and renewable R&D in EU countries: A cointegration analysis, Asian Journal of Natural & Applied Sciences, 2:1, 10-16.
- DAI, Q., & BIE, Z. (2006), FDI, Accumulation of Human Capital and Economic Growth, Econ. Res. J., 4, 15–27
- DINDA, S. (2011), Carbon emission and production technology: Evidence from the US, MPRA, 31935.
- FERNÁNDEZ, FY., LÓPEZ, FMA., BLANCO, OB. (2018), Innovation for sustainability: the impact of R&D spending on CO2 emissions, J Clean Prod 172:3459–3467.
- GREGORY, A. W., & HANSEN, B. E. (1996), Residual-Based Tests for Cointegration in Models With Regime Shifts, Journal of Econometrics, Vol. 70, pp. 99-126.
- GRILICHES, Z. (1998), Patent statistics as economic indicators: a survey. In R&D and productivity: the econometric evidence, University of Chicago Press, 287-343.
- IEA(INTERNATIONAL ENERGY AGENCY), (2015), Energy efficiency market report, Paris: International Energy Agency, issues, Energy policy, 24(5), 377-390.
- IRANDOUST, M. (2016), The renewable energy-growth nexus with carbon emissions and technological innovation: Evidence from the Nordic countries, Ecological Indicators, 69, 118-125.
- JIN, L., DUAN, K., SHI, C., & JU, X. (2017), The impact of technological progress in the energy sector on carbon emissions: an empirical analysis from China, Int J Environ Res Public Health 14:1–14.
- JUN, C., & SHIYUAN, X. (2008), The Impact of Technical Progress over China's Energy Efficiency: 1972-2006, Scientific Management Research, 1.
- KAHOULI, B. (2018), The causality link between energy electricity consumption, CO2 emissions, R&D stocks and economic growth in Mediterranean countries (MCs), Energy 145:388–399.
- LANTZ, V., & FENG, Q. (2006), Assessing income, population, and technology impacts on CO2 emissions in Canada: where’s the EKC?, Ecol Econ 57:229–238.
- LEE, K. H., & MIN, B. (2015), Green R&D for eco-innovation and its impact on carbon emissions and firm performance, Journal of Cleaner Production, 108, 534-542.
- LI, W., WANG, W., WANG, Y., & QİN, Y. (2017), Industrial structure, technological progress and CO2 emissions in China: analysis based on the STIRPAT framework, Nat Hazards 88:1545–1564.
- MEHMOOD, B., FELICEO, A., & SHAHİD, A. (2014), What Causes What? Aviation Demand and Economic Growth in Romania: Cointegration Estimation and Causality Analysis, Romanian Economic and Business Review, s.9, pp. 21-34.
- MENSAH, CN., LONG, X., BOAMAH, KB., BEDIAKO, IA., DAUDA, L., & SALMAN, M. (2018), The effect of innovation on CO2 emissions of OCED countries from 1990 to 2014, Environ Sci Pollut Res 25:29678–29698.
- NAZLIOĞLU, Ş. (2010), Makro İktisat Politikalarının Tarım Sektörü Üzerindeki Etkileri: Gelişmiş Ve Gelişmekte Olan Ülkeler İçin Bir Karşılaştırma, Erciyes Üniversitesi Sosyal Bilimler Enstitüsü, İktisat Anabilim Dalı, Yayınlanmamış Doktora Tezi, Kayseri.
- ÖZKAN, A. (2016), Güvenlik Paradigmasında Sınıraşan Bir Çevre Sorunsalı: “Nükleer Zarar”, Alternatif Politika, 8(1), 128-159.
- PARK, J.Y. (1992), Canonical Cointegrating Regressions, Econometrica: Journal of the Econometric Society, S.60(1), ss.119-143.
- PERRON, P. (1989), The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis, Econometrica, vol. 57, no. 6, pp.1361-1401.
- PHİLLİPS, P., & HANSEN, B. (1990), Statistical Inference in Instrumental Variables Regression with I(1) Processes, Review of Economic Studies, 57, 99-125.
- SAHU, S. K., & NARAYANAN, K. (2013), Carbon dioxide emissions from Indian manufacturing industries: Role of energy and technology intensity, Madras School of Economics, 82.
- SAİTO, S., (2010), Role of nuclear energy to a future society of shortage of energy resources and global warming, Journal of Nuclear Materials, 398(1-3), 1-9.
- SOHAG, K., BEGUM, R. A., ABDULLAH, S. M. S., & JAAFAR, M. (2015), Dynamics of energy use, technological innovation, economic growth and trade openness in Malaysia, Energy, 90, 1497-1507.
- TIRAŞOĞLU, M., & BURCU, Y. (2012), Yapısal Kırılma Durumunda Sağlık Harcamaları ve Ekonomik Büyüme İlişkisi: Türkiye Üzerine Bir Uygulama, Electronic Journal of Vocational Colleges, S. 2, s.111-117.
- ZHOU, Z., YE, X., & GE, X. (2017), The impacts of technical progress on sulfur dioxide Kuznets curve in China: a spatial panel data approach. Sustain, 9.
- ZIVOT, E., & ANDREWS, D. (1992), Further Evidence On The Great Crash, The OilPrice Shock, and The Unit Root Hypothesis, Journal of Business & Economic Statistics, vol. 10, no. 3, pp.251-270. ZOLTAN J. A., ANSELİN, L., & VARGA, A. (2002), Patents and innovation counts as measures of regional production of new knowledge, Research policy, 31(7), 1069-1085.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Ekonomi |
| Bölüm | Araştırma Makaleleri |
| Yazarlar | |
| Yayımlanma Tarihi | 21 Ekim 2021 |
| Yayımlandığı Sayı | Yıl 2021Sayı: 22 |
- Makale Dosyaları
