GREEN FINANCE AND RENEWABLE ENERGY IN SUSTAINABLE TOURISM: A REGIONAL PANEL DATA APPROACH

Yıl 2025, Cilt: 10 Sayı: 2, 468 - 496, 12.12.2025

Erdem Baydeniz

https://doi.org/10.54452/jrb.1742509

Öz

The aim of this study is to empirically examine the relationships between renewable energy and sustainable tourism development in Türkiye. Using a balanced panel data set covering the period 2010-2022 and obtained from 12 NUTS-1 regions, the analysis was conducted on a total of 156 observations. To enhance methodological robustness in panel data modeling, Pesaran (2021) cross-sectional dependence test and Pesaran-Yamagata (2008) slope homogeneity test were first applied, followed by second-generation tests (CIPS unit root and Westerlund cointegration tests) based on their results. Given the detection of cross-sectional dependence and slope heterogeneity, System GMM (Generalized Method of Moments) method was employed for dynamic panel data modeling, with per capita GDP and carbon emissions included as control variables. The analyses conducted using R software reveal that a 1% increase in renewable energy capacity leads to a 0.15% increase in tourism revenue (elasticity coefficient: 0.15, p<0.01), while a 1% increase in visitor numbers results in a 0.42% increase in tourism revenue (elasticity coefficient: 0.42, p<0.01). Dumitrescu-Hurlin panel Granger causality tests confirm the existence of strong bidirectional causality relationships between the variables. Regional heterogeneity analyses demonstrate that the renewable energy effect is approximately three times stronger in developed tourism regions compared to less developed regions. Robustness checks (PMG, MG estimators) and sub-period analyses support the consistency of the main findings. The findings show that renewable energy investments increase the competitiveness of the tourism sector and contribute to environmental sustainability by reducing carbon emissions. The results provide concrete policy recommendations emphasizing the necessity of regionally differentiated policy design in line with Türkiye's 2053 Net Zero Emission target and sustainable development goals.

Anahtar Kelimeler

Sustainable tourism , green financing , renewable energy , panel data analysis , System GMM

SÜRDÜRÜLEBİLİR TURİZMDE YEŞİL FİNANSMAN VE YENİLENEBİLİR ENERJİ: BÖLGESEL PANEL VERİ YAKLAŞIMI

Öz

Bu çalışmanın amacı, Türkiye'de yenilenebilir enerji ve sürdürülebilir turizm gelişimi arasındaki ilişkileri ampirik olarak incelemektir. 2010-2022 dönemini kapsayan ve 12 NUTS-1 bölgesinden elde edilen dengeli panel veri seti kullanılarak, toplam 156 gözlem üzerinden analiz gerçekleştirilmiştir. Panel veri modellemesinde metodolojik sağlamlığı artırmak amacıyla, öncelikle Pesaran (2021) kesit bağımlılığı testi ve Pesaran-Yamagata (2008) eğim homojenliği testi uygulanmış, ardından bu testlerin sonuçlarına göre ikinci nesil testler (CIPS birim kök ve Westerlund eşbütünleşme testleri) kullanılmıştır. Kesit bağımlılığı ve eğim heterojenliğinin tespit edilmesi nedeniyle, dinamik panel veri modellemesinde System GMM (Generalized Method of Moments) yöntemi tercih edilmiş, kişi başı GSYİH ve karbon emisyonları kontrol değişkenleri olarak modele dahil edilmiştir. R yazılımı kullanılarak gerçekleştirilen analizler, yenilenebilir enerji kapasitesindeki %1'lik artışın turizm gelirinde %0.15'lik artışa yol açtığını (elastikiyet katsayısı: 0.15, p<0.01), ziyaretçi sayısındaki %1'lik artışın ise turizm gelirinde %0.42'lik artışa neden olduğunu (elastikiyet katsayısı: 0.42, p<0.01) ortaya koymaktadır. Dumitrescu-Hurlin panel Granger nedensellik testleri, değişkenler arasında güçlü çift yönlü nedensellik ilişkilerinin varlığını doğrulamaktadır. Bölgesel heterojenlik analizleri, yenilenebilir enerji etkisinin gelişmiş turizm bölgelerinde az gelişmiş bölgelere kıyasla yaklaşık üç kat daha güçlü olduğunu göstermektedir. Sağlamlık testleri (PMG, MG estimatörleri) ve alt dönem analizleri, ana bulguların tutarlılığını desteklemektedir. Bulgular, yenilenebilir enerji yatırımlarının turizm sektörünün rekabet gücünü artırdığını ve karbon emisyonlarını azaltarak çevresel sürdürülebilirliğe katkı sağladığını göstermektedir. Araştırma sonuçları, Türkiye'nin 2053 Net Sıfır Emisyon hedefi ve sürdürülebilir kalkınma amaçları doğrultusunda, bölgesel farklılaştırılmış politika tasarımının gerekliliğini vurgulayan somut öneriler sunmaktadır.

Anahtar Kelimeler

Sürdürülebilir turizm , yeşil finansman , yenilenebilir enerji , panel veri analizi , System GMM

Kaynakça

• Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297. https://doi. org/10.2307/2297968
• Arellano, M., & Bover, O. (1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics, 68(1), 29–51. https://doi.org/10.1016/0304-4076(94)01642-D
• Balsalobre-Lorente, D., Driha, O. M., Bekun, F. V., Sinha, A., & Adedoyin, F. F. (2020). Consequences of COVID-19 on the social isolation of the Chinese economy: accounting for the role of reduction in carbon emissions. Air Quality, Atmosphere & Health, 13(12), 1439-1451.
• Bramwell, B., & Lane, B. (2019). Critical research on the governance of tourism and sustainability. Journal of Sustainable Tourism, 27(4), 411–421. https://doi.org/10.1080/09669.582.2019.1583200
• Butler, R. W. (1999). Sustainable tourism: A state-of-the-art review. Tourism Geographies, 1(1), 7–25. https://doi. org/10.1080/146.166.89908721291
• Dogan, E., Seker, F., & Bulbul, S. (2017). Investigating the impacts of energy consumption, real GDP, tourism and trade on CO2 emissions by accounting for cross-sectional dependence: a panel study of OECD countries. Current Issues in Tourism, 20(16), 1701-1719.
• Dumitrescu, E. I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. https://doi.org/10.1016/j.econmod.2012.02.014
• Eberhardt, M., & Teal, F. (2010). Productivity analysis in global manufacturing production (Economics Series Working Papers No. 515). University of Oxford, Department of Economics. https://www.economics. ox.ac.uk/materials/working_papers/paper515.pdf
• Enerji Piyasası Düzenleme Kurumu. (2023). Elektrik piyasası gelişim raporu 2023. https://www.epdk.gov.tr/ Detay/Icerik/3-0-83/elektrik-piyasasi-raporlari
• Eyuboglu, K., & Uzar, U. (2020). The impact of tourism on CO2 emission in Turkey. Current Issues in Tourism, 23(13), 1631–1645. https://doi.org/10.1080/13683.500.2019.1669076
• González, A., Teräsvirta, T., Van Dijk, D., & Yang, Y. (2017). Panel smooth transition regression models.
• Hall, C. M. (2013). Framing behavioural approaches to understanding and governing sustainable tourism consumption: Beyond neoliberalism, “nudging” and green growth? Journal of Sustainable Tourism, 21(7), 1091–1109. https://doi.org/10.1080/09669.582.2013.815764
• Hartman, S. (2023). Destination governance in times of change: a complex adaptive systems perspective to improve tourism destination development. Journal of Tourism Futures, 9(2), 267-278. https://doi. org/10.1108/JTF-11-2020-0213
• Im, K. S., Pesaran, M. H., & Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115(1), 53–74. https://doi.org/10.1016/S0304-4076(03)00092-7
• International Energy Agency. (2021). Turkey 2021 energy policy review. https://www.iea.org/reports/turkey-2021
• Işık, C., Doğan, E., & Ongan, S. (2017). Analyzing the tourism–energy–growth nexus for the top 10 most-visited countries. Economies, 5(4), 40. https://doi.org/10.3390/economies5040040
• Katırcıoğlu, S. T. (2014). Testing the tourism-induced EKC hypothesis: The case of Singapore. Economic Modelling, 41, 383–391. https://doi.org/10.1016/j.econmod.2014.05.028 Kültür ve Turizm Bakanlığı. (2023). Turizm istatistikleri. https://yigm.ktb.gov.tr/TR-9851/turizm-istatistikleri.html
• Levin, A., Lin, C. F., & Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108(1), 1–24. https://doi.org/10.1016/S0304-4076(01)00098-7
• Li, Y., Nassani, A. A., Al-Aiban, K. M., Rahman, S. U., Naseem, I., & Zaman, K. (2024). Beyond the numbers: Unveiling the environmental impacts of international tourism and the role of renewable energy transition. Current Issues in Tourism, 27(22), 3908-3923. https://doi.org/10.1080/13683.500.2024.2313 057
• McCarthy, J. J. (2001). Climate change 2001: impacts, adaptation, and vulnerability: contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change (Vol. 2). Cambridge university press.
• Paramati, S. R., Alam, M. S., & Chen, C. F. (2017). The effects of tourism on economic growth and CO2 emissions: A comparison between developed and developing economies. Journal of Travel Research, 56(6), 712– 724. https://doi.org/10.1177/004.728.7516667848
• Pata, U. K. (2021). Renewable and non-renewable energy consumption, economic complexity, CO2 emissions, and ecological footprint in the USA: Testing the EKC hypothesis with a structural break. Environmental Science and Pollution Research, 28(1), 846–861. https://doi.org/10.1007/s11356.020.10446-3
• Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61(S1), 653–670. https://doi.org/10.1111/1468-0084.061.01332
• Pesaran, M. H. (2021). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 60(1), 13–50. https://doi.org/10.1007/s00181.020.01875-7
• Raihan, A. (2023). A review of the global climate change impacts, adaptation strategies, and mitigation options in the socio-economic and environmental sectors. Journal of Environmental Science and Economics, 2(3), 36-58. https://doi.org/10.56556/jescae.v2i3.587
• Sharif, A., Mishra, S., Sinha, A., Jiao, Z., Shahbaz, M., & Afshan, S. (2020). The renewable energy consumption- environmental degradation nexus in Top-10 polluted countries: Fresh insights from quantile-on-quantile regression approach. Renewable Energy, 150, 670–690. https://doi.org/10.1016/j.renene.2019.12.149
• Sonuç, N. (2020). Sustainable tourism (Sustainable development of tourism, sustainable tourism management). In Encyclopedia of sustainable management (pp. 1-8). Cham: Springer International Publishing. https:// doi.org/10.1007/978-3-030-02006-4_454-1
• Statista Research Department. (2024). Travel and tourism statistics in Turkey. Statista. https://www.statista.com/ topics/9676/travel-and-tourism-in-turkey/
• Tosun, C. (2021). Sustainable Tourism Development in Emerging Economies.
• Turkish Statistical Institute. (2023). Tourism statistics 2023. TÜİK. https://data.tuik.gov.tr/Kategori/ GetKategori?p=Egitim,-Kultur,-Spor-ve-Turizm-105
• United Nations Framework Convention on Climate Change. (2023). National inventory submissions 2023. https://unfccc.int/documents
• United Nations World Tourism Organization. (2023). International tourism highlights – 2023 edition. https:// www.unwto.org/statistics
• World Travel & Tourism Council. (2023). Economic impact 2023 – Turkey. WTTC. https://wttc.org/research/ economic-impact
• Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross‐section dependence. Journal of applied econometrics, 22(2), 265-312. https://doi.org/10.1002/jae.951
• Westerlund, J. (2008). Panel cointegration tests of the Fisher effect. Journal of applied econometrics, 23(2), 193- 233. https://doi.org/10.1002/jae.967