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NAVIGATING US CLIMATE POLICY UNCERTAINTY: NOVEL EVIDENCE FROM CARBON MARKETS, CRYPTOCURRENCY (DeFi), AND RENEWABLE ENERGY INNOVATIONS

Yıl 2025, Cilt: 27 Sayı: 2 , 811 - 843 , 15.06.2025

Cengizhan Karaca

https://doi.org/10.16953/deusosbil.1599272
https://izlik.org/JA58HF33BE

Öz

The aim of this study is to reveal the dynamics between climate policy uncertainty (CPU) and S&P Global Carbon Credit Index (CARBON), S&P Cryptocurrency DeFi Index (DeFi), and WilderHill New Energy Global Innovation Index (NEX) using data from December 2017 to March 2024 in the US. Fourier Bootstrap ARDL, Fourier Bootstrap quantile causality, and KRLS methods are used in the study. The findings reveal that there is a negative relationship between the CARBON and the CPU index in the long term. Although the DeFi does not have a statistically significant effect in the long term, it reveals that it has a negative effect on the CPU index in the short term. In contrast, the NEX has a positive relationship with the CPU index in both the short and long term. Moreover, there is a U-shaped non-linear relationship between the NEX and the CPU index, which weakens in moderate climate uncertainties and strengthens again in high uncertainty. Considering the causality results, there exists a causality from CARBON to CPU in the 2nd, 3rd, and 4th quantiles, and from CPU to CARBON in the 2nd and 3rd quantiles. Additionally, there is a causality from DeFi to CPU in the 8th quantile and from CPU to DeFi in the 1st quantile. Finally, there is a causal relationship from NEX to CPU in the 2nd, 3rd, 4th, and 5th quantiles and from CPU to NEX in the 9th quantile.

Anahtar Kelimeler

Climate Policy Uncertainty Decentralized Finance (DeFi) Renewable Energy Carbon Credit

Etik Beyan

The author(s) confirm compliance with the requirements for ethical approval and declare their understanding of the relevant rules and content.

Destekleyen Kurum

None

Teşekkür

The author(s) sincerely thank the editorial board and reviewers for their valuable time, insightful feedback, and constructive suggestions, which have significantly contributed to enhancing the quality of this manuscript.

Kaynakça

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  • Athari, S. A., & Kirikkaleli, D. (2024). How do climate policy uncertainty and renewable energy and clean technology stock prices co-move? Evidence from Canada. Empirical Economics. https://doi.org/10.1007/s00181-024-02643-7
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  • Christopoulos, D. K., & León-Ledesma, M. A. (2010). Smooth breaks and non-linear mean reversion: Post-Bretton Woods real exchange rates. Journal of International Money and Finance, 29 (6), 1076–1093. https://doi.org/10.1016/j.jimonfin.2010.02.003
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  • Du, Y., & Guo, Q. (2023). Green credit policy and green innovation in green industries: Does climate policy uncertainty matter? Finance Research Letters, 58, 104512. https://doi.org/10.1016/j.frl.2023.104512
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ABD İKLİM POLİTİKASI BELİRSİZLİĞİNİ ANLAMAK: KARBON PİYASALARI, MERKEZİYETSİZ FİNANS (DeFi) VE YENİLENEBİLİR ENERJİ İNOVASYONLARINDAN YENİLİKÇİ KANITLAR

Yıl 2025, Cilt: 27 Sayı: 2 , 811 - 843 , 15.06.2025

Cengizhan Karaca

https://doi.org/10.16953/deusosbil.1599272
https://izlik.org/JA58HF33BE

Öz

Bu çalışmanın amacı, ABD’de Aralık 2017 ile Mart 2024 arasındaki verileri kullanarak iklim politikası belirsizliği (CPU) ile S&P Küresel Karbon Kredi Endeksi (CARBON), S&P Kripto Para DeFi Endeksi (DeFi) ve WilderHill Yeni Enerji Küresel İnovasyon Endeksi (NEX) arasındaki dinamikleri ortaya koymaktır. Çalışmada Fourier Bootstrap ARDL, Fourier Bootstrap kantil nedensellik ve KRLS yöntemleri kullanılmıştır. Bulgular, CARBON ile CPU endeksi arasında uzun vadede negatif bir ilişki olduğunu ortaya koymaktadır. DeFi’nin uzun vadede istatistiksel olarak anlamlı bir etkisi olmasa da, kısa vadede CPU endeksi üzerinde negatif bir etkisi olduğunu ortaya koymaktadır. Buna karşılık, NEX’in hem kısa hem de uzun vadede CPU endeksi ile pozitif bir ilişkisi vardır. Ayrıca, NEX ile CPU endeksi arasında ılımlı iklim belirsizliklerinde zayıflayan ve yüksek belirsizlikte tekrar güçlenen U şeklinde doğrusal olmayan bir ilişki vardır. Nedensellik sonuçlarını göz önünde bulundurarak, 2., 3. ve 4. kantillerde CARBON’dan CPU’ya ve 2. ve 3. kantillerde CPU’dan CARBON’a bir nedensellik vardır. Ek olarak, 8. kantilde DeFi’den CPU’ya ve 1. kantilde CPU’dan DeFi’ye bir nedensellik bulunmaktadır. Son olarak, 2., 3., 4. ve 5. kantillerde NEX’ten CPU’ya ve 9. kantilde CPU’dan NEX’e doğru bir nedensellik ilişkisi bulunmaktadır.

Anahtar Kelimeler

İklim Politika Belirsizliği Merkeziyetsiz Finans (DeFi) Yenilenebilir Enerji Karbon Kredileri

Kaynakça

  • Akyol, G., Bi̇li̇rer, M., & Zeren, F. (2023). Türkiye’de ihracat, döviz kuru, işsizlik ve ekonomik büyüme ilişkisi: Fourier kantil nedensellik ve fourier adl eşbütünleşme testlerinden yeni kanıtlar. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 8 (2), 298–309. https://doi.org/10.29106/fesa.1256614
  • Ameen, M. H., & Afşar, A. (2022). Investigating the effects of climate policy uncertainty on the US petroleum markets. International Journal of Energy Studies, 7 (1), 1–20. https://dergipark.org.tr/en/download/article- file/2177093
  • Amin, M. R., Akindayomi, A., Sarker, M. S. R., & Bhuyan, R. (2023). Climate policy uncertainty and corporate tax avoidance. Finance Research Letters, 58, 104581. https://doi.org/10.1016/j.frl.2023.104581
  • Athari, S. A., & Kirikkaleli, D. (2024). How do climate policy uncertainty and renewable energy and clean technology stock prices co-move? Evidence from Canada. Empirical Economics. https://doi.org/10.1007/s00181-024-02643-7
  • Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27 (3), 381–409. https://doi.org/10.1111/j.1467-9892.2006.00478.x
  • Bouri, E., Iqbal, N., & Klein, T. (2022). Climate policy uncertainty and the price dynamics of green and brown energy stocks. Finance Research Letters, 47, 102740. https://doi.org/10.1016/j.frl.2022.102740
  • Cavlak, O. D. (2022). A nonlinear autoregressive distributed lag (NARDL) approach for U.S. climate policy uncertainty index, Renewable Energy Consumption, and Oil Prices. Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 24 (2), 757–776. https://doi.org/10.26745/ahbvuibfd.1055390
  • Cheng, K., Hsueh, H.-P., Ranjbar, O., Wang, M.-C., & Chang, T. (2021). Urbanization, coal consumption and CO2 emissions nexus in China using bootstrap Fourier Granger causality test in quantiles. Letters in Spatial and Resource Sciences, 14 (1), 31–49. https://doi.org/10.1007/s12076-020-00263-0
  • Choi, Y., & Lee, S. (2020). The impact of urban physical environments on cooling rates in summer: Focusing on interaction effects with a kernel-based regularized least squares (KRLS) model. Renewable Energy, 149, 523–534. https://doi.org/10.1016/j.renene.2019.12.021
  • Christopoulos, D. K., & León-Ledesma, M. A. (2010). Smooth breaks and non-linear mean reversion: Post-Bretton Woods real exchange rates. Journal of International Money and Finance, 29 (6), 1076–1093. https://doi.org/10.1016/j.jimonfin.2010.02.003
  • Dong, X., Jiang, Z., & Yoon, S.-M. (2024). Impact of global financial and energy markets, uncertainty, and climate change attention on Bitcoin carbon footprint. Finance Research Letters, 70, 106254. https://doi.org/10.1016/j.frl.2024.106254
  • Du, Y., & Guo, Q. (2023). Green credit policy and green innovation in green industries: Does climate policy uncertainty matter? Finance Research Letters, 58, 104512. https://doi.org/10.1016/j.frl.2023.104512
  • Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks*. Oxford Bulletin of Economics and Statistics, 74 (4), 574–599. https://doi.org/10.1111/j.1468-0084.2011.00662.x
  • Faccini, R., Matin, R., & Skiadopoulos, G. (2023). Dissecting climate risks: Are they reflected in stock prices? Journal of Banking & Finance, 155, 106948. https://doi.org/10.1016/j.jbankfin.2023.106948
  • Fareed, Z., Salem, S., Adebayo, T. S., Pata, U. K., & Shahzad, F. (2021). Role of export diversification and renewable energy on the load capacity factor in Indonesia: A Fourier quantile causality approach. Frontiers in Environmental Science, 9. Retrieved from https://www.frontiersin.org/articles/10.3389/fenvs.2021.770152
  • Fendoğlu, E., & Gökçe, E. C. (2021). Türkiye’de eğitim ve sağlık harcamaları ile ekonomik büyüme arasındaki ilişki: Fourier yaklaşımı. Ekonomi İşletme ve Maliye Araştırmaları Dergisi, 3 (2), 203–216. https://doi.org/10.38009/ekimad.970527
  • Gavriilidis, K. (2021). Measuring climate policy uncertainty [SSRN Scholarly Paper]. Rochester, NY: Social Science Research Network. http://dx.doi.org/10.2139/ssrn.3847388
  • Ghani, U., Zhu, B., Qin, Q., & Ghani, M. (2024). Forecasting US stock market volatility: Evidence from ESG and CPU indices. Finance Research Letters, 59, 104811. https://doi.org/10.1016/j.frl.2023.104811
  • Guesmi, K., Makrychoriti, P., & Spyrou, S. (2023). The relationship between climate risk, climate policy uncertainty, and CO2 emissions: Empirical evidence from the US. Journal of Economic Behavior & Organization, 212, 610–628. https://doi.org/10.1016/j.jebo.2023.06.015
  • Gürsoy, S., Jóźwik, B., Dogan, M., Zeren, F., & Gulcan, N. (2024). Impact of climate policy uncertainty, clean energy index, and carbon emission allowance prices on bitcoin returns. Sustainability, 16 (9), 3822. https://doi.org/10.3390/su16093822
  • Hainmueller, J., & Hazlett, C. (2014). Kernel regularized least squares: Reducing misspecification bias with a flexible and interpretable machine learning approach. Political Analysis, 22 (2), 143–168. https://doi.org/10.1093/pan/mpt019
  • Hatemi-J, A., & Uddin, G. S. (2012). Is the causal nexus of energy utilization and economic growth asymmetric in the US? Economic Systems, 36 (3), 461–469. https://doi.org/10.1016/j.ecosys.2011.10.005
  • Hoang, K. (2022). How does corporate R&D investment respond to climate policy uncertainty? Evidence from heavy emitter firms in the United States. Corporate Social Responsibility and Environmental Management, 29 (4), 936–949. https://doi.org/10.1002/csr.2246
  • Hoque, M. E., & Azlan Shah Zaidi, M. (2020). Impacts of global-economic-policy uncertainty on emerging stock market: Evidence from linear and non-linear models. Prague Economic Papers, 29 (1), 53–66. https://doi.org/10.18267/j.pep.725
  • Huang, W. (2023). Climate policy uncertainty and green innovation. Economics Letters, 233, 111423. https://doi.org/10.1016/j.econlet.2023.111423
  • Husain, S., Sohag, K., & Wu, Y. (2022). The response of green energy and technology investment to climate policy uncertainty: An application of twin transitions strategy. Technology in Society, 71, 102132. https://doi.org/10.1016/j.techsoc.2022.102132
  • Işık, C., Ongan, S., Ozdemir, D., Jabeen, G., Sharif, A., Alvarado, R., & Rehman, A. (2024). Renewable energy, climate policy uncertainty, industrial production, domestic exports/re-exports, and CO2 emissions in the USA: A SVAR approach. Gondwana Research, 127, 156–164. https://doi.org/10.1016/j.gr.2023.08.019
  • Kartal, M. T., Pata, U. K., Kılıç Depren, S., & Depren, Ö. (2023). Effects of possible changes in natural gas, nuclear, and coal energy consumption on CO2 emissions: Evidence from France under Russia’s gas supply cuts by dynamic ARDL simulations approach. Applied Energy, 339, 120983. https://doi.org/10.1016/j.apenergy.2023.120983
  • Li, M., Han, X., & Li, Y. (2024). The impact of climate policy uncertainty on stock price synchronicity: Evidence from China. Finance Research Letters, 69, 106166. https://doi.org/10.1016/j.frl.2024.106166
  • Liang, C., Umar, M., Ma, F., & Huynh, T. L. D. (2022). Climate policy uncertainty and world renewable energy index volatility forecasting. Technological Forecasting and Social Change, 182, 121810. https://doi.org/10.1016/j.techfore.2022.121810
  • Ludlow, J., & Enders, W. (2000). Estimating non-linear ARMA models using Fourier coefficients. International Journal of Forecasting, 16 (3), 333–347. https://doi.org/10.1016/S0169-2070(00)00048-0
  • Lv, W., & Li, B. (2023). Climate policy uncertainty and stock market volatility: Evidence from different sectors. Finance Research Letters, 51, 103506. https://doi.org/10.1016/j.frl.2022.103506
  • Mao, K., & Huang, J. (2022). How does climate policy uncertainty affect green innovation? Evidence from China. International Journal of Environmental Research and Public Health, 19 (23), 15745. https://doi.org/10.3390/ijerph192315745
  • McNown, R., Sam, C. Y., & Goh, S. K. (2018). Bootstrapping the autoregressive distributed lag test for cointegration. Applied Economics, 50 (13), 1509–1521. https://doi.org/10.1080/00036846.2017.1366643
  • Nazlioglu, S., Gormus, N. A., & Soytas, U. (2016). Oil prices and real estate investment trusts (REITs): Gradual-shift causality and volatility transmission analysis. Energy Economics, 60, 168–175. https://doi.org/10.1016/j.eneco.2016.09.009
  • Ozkan, O., Sunday Adebayo, T., & Usman, O. (2024). Dynamic connectedness of clean energy markets, green markets, and sustainable markets: The role of climate policy uncertainty. Energy, 303, 131957. https://doi.org/10.1016/j.energy.2024.131957
  • Pástor, Ľ., Stambaugh, R. F., & Taylor, L. A. (2021). Sustainable investing in equilibrium. Journal of Financial Economics, 142 (2), 550–571. https://doi.org/10.1016/j.jfineco.2020.12.011
  • Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16 (3), 289–326. https://doi.org/10.1002/jae.616
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  • Sarker, P. K., Bouri, E., & Marco, C. K. L. (2023). Asymmetric effects of climate policy uncertainty, geopolitical risk, and crude oil prices on clean energy prices. Environmental Science and Pollution Research, 30 (6), 15797–15807. https://doi.org/10.1007/s11356-022-23020-w
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Toplam 59 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makro İktisat (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Cengizhan Karaca 0000-0002-8121-7142

Gönderilme Tarihi 10 Aralık 2024
Kabul Tarihi 15 Mart 2025
Erken Görünüm Tarihi 2 Haziran 2025
Yayımlanma Tarihi 15 Haziran 2025
DOI https://doi.org/10.16953/deusosbil.1599272
IZ https://izlik.org/JA58HF33BE
Yayımlandığı Sayı Yıl 2025 Cilt: 27 Sayı: 2

Kaynak Göster

APA Karaca, C. (2025). NAVIGATING US CLIMATE POLICY UNCERTAINTY: NOVEL EVIDENCE FROM CARBON MARKETS, CRYPTOCURRENCY (DeFi), AND RENEWABLE ENERGY INNOVATIONS. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 27(2), 811-843. https://doi.org/10.16953/deusosbil.1599272

Cited By

TÜRKİYE’YE ÖZGÜ EKONOMİK BELİRSİZLİĞİN BORSA İSTANBUL ÜZERİNDEKİ ETKİSİ: FOURİER BOOTSTRAP YAKLAŞIMLARINDAN YENİ KANITLAR
Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi
https://doi.org/10.24889/ifede.1726711
ECONOMIC POLICY UNCERTAINTY AND CORPORATE INVESTMENT DECISIONS: EVIDENCE FROM TURKISH MANUFACTURING FIRMS
Journal of Research in Business
https://doi.org/10.54452/jrb.1671499

Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi Aile Yılı Özel Sayısı Çağrısı
Sayı Editörü
Prof. Dr. NEBİYE KONUK KANDEMİR

Sevgili Araştırmacılar ve Değerli Yazarlar,
Aile, toplumun temel yapı taşıdır ve bireylerin gelişimi ile sosyal yaşamın şekillenmesinde kritik bir rol oynamaktadır. Aile yapıları ve dinamikleri, tarihsel, kültürel ve toplumsal faktörlerle şekillenirken, bu faktörlerin aile içerisinde yaşanan sorunları, ilişkileri ve güç dengelerini nasıl etkilediği büyük bir önem taşımaktadır. 2025 yılı "Aile Yılı" olarak ilan edilmesi, aile olgusunun daha geniş bir perspektiften ele alınmasını ve bu konudaki farkındalığın artırılmasını hedeflemektedir.
Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, "Cilt: 28 Sayı: Özel Sayı" olarak 2026 yılında yayımlanacak olan Aile Yılı Özel Sayısı'na yönelik makale çağrısında bulunmaktadır. Bu özel sayı, aile yapılarını, rollerini ve dinamiklerini inceleyen çalışmalara ev sahipliği yapmayı hedeflemektedir.
Aile ile ilgili çalışmalara olan ihtiyaç, yalnızca bireysel düzeyde değil, toplumsal düzeyde de açıktır. Son yıllarda, aile içi ilişkilerin sağlıklı bir şekilde sürdürülmesi, toplumsal cinsiyet eşitliği, kadın hakları, çocuk sağlığı ve eğitim gibi konular ön plana çıkmış, bu konularda yapılacak bilimsel araştırmaların önemi artmıştır. Aile Yılı Özel Sayısı'nın hazırlanması, bu kritik meselelerin sistematik bir biçimde incelenmesine ve topluma duyurulmasına olanak sağlayacaktır.
Bu özel sayı, aile dinamiklerini, ilişkilerini ve sorunlarını derinlemesine inceleyen, özgün ve yenilikçi çalışmaları bir araya getirerek, alanında önemli bir kaynak oluşturmayı hedeflemektedir. Ayrıca, uzmanların görüşleri ve çeşitli disiplinlerden gelen katkılar sayesinde, aile kavramına dair güncel bakış açıları sunulacak, toplumsal fayda sağlanacaktır.
Aşağıda, özel sayıda kabul edilebilecek (ama bunlarla sınırlı olmayan) güncellenmiş konular listesi yer almaktadır:

• Aile Yapıları ve Değişimi
• Geleneksel ve Modern Aile Rolleri
• Aile İçi İletişim ve İlişkiler
• Ailedeki Psiko-Sosyal Dinamikler
• Aile İlişkilerinde Kültürel Farklılıklar
• Evlilik ve Boşanma Dinamikleri
• Aile ve Çocuk Gelişimi
• Ebeveynlik Stilleri ve Çocuk Üzerindeki Etkileri
• Aile Ekonomisi ve Sosyal Politika
• Aileyi Etkileyen Toplumsal Değişimler
• Aile ve Eğitim İlişkisi
• Ailede Şiddet ve Koruma Mekanizmaları
• Aile İçi Sağlık ve Refah
• Kadınların Aile İçindeki Rolü ve Değişen Dinamikleri
• Kadın Hakları ve Aile İlişkileri
• Kadının Aile Üyeleriyle İlişkileri ve Güç Dinamikleri
• Ailede Cinsiyet Eşitliği
İki bağımsız anonim hakem tarafından değerlendirmeden geçecek makaleler, kabul edilmesi halinde, Aralık 2026'da yayımlanacak özel sayımızda yer alacaktır. Gelecek sayıların dolmuş olması ve süreçte makale yoğunluğunun bulunması nedeniyle dergimiz, özel sayı dışında makale kabulüne kapalıdır. Özel sayı dışında dergimize gönderilen makaleler iade edilecektir.
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