Araştırma Makalesi
BibTex RIS Kaynak Göster

ABD İKLİM POLİTİKASI BELİRSİZLİĞİNİ ANLAMAK: KARBON PİYASALARI, MERKEZİYETSİZ FİNANS (DeFi) VE YENİLENEBİLİR ENERJİ İNOVASYONLARINDAN YENİLİKÇİ KANITLAR

Yıl 2025, Cilt: 27 Sayı: 2, 811 - 843

Cengizhan Karaca

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

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
  • Ren, X., Zhang, X., Yan, C., & Gozgor, G. (2022). Climate policy uncertainty and firm-level total factor productivity: Evidence from China. Energy Economics, 113, 106209. https://doi.org/10.1016/j.eneco.2022.106209
  • 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
  • Sautner, Z., Van Lent, L., Vilkov, G., & Zhang, R. (2023). Firm-level climate change exposure. The Journal of Finance, 78 (3), 1449–1498. https://doi.org/10.1111/jofi.13219
  • Su, C. W., Wei, S., Wang, Y., & Tao, R. (2024). How does climate policy uncertainty affect the carbon market? Technological Forecasting and Social Change, 200, 123155. https://doi.org/10.1016/j.techfore.2023.123155
  • Syed, Q. R., Goh, S. K., & Apergis, N. (2024). Modeling the impact of climate policy uncertainty on energy production. Applied Economics Letters, 0 (0), 1–5. https://doi.org/10.1080/13504851.2024.2415322
  • Tedeschi, M., Foglia, M., Bouri, E., & Dai, P.-F. (2024). How does climate policy uncertainty affect financial markets? Evidence from Europe. Economics Letters, 234, 111443. https://doi.org/10.1016/j.econlet.2023.111443
  • Tian, L., Li, X., Lee, C.-W., & Spulbăr, C. (2024). Investigating the asymmetric impact of artificial intelligence on renewable energy under climate policy uncertainty. Energy Economics, 137, 107809. https://doi.org/10.1016/j.eneco.2024.107809
  • Tommaso, C. D., Foglia, M., & Pacelli, V. (2024). The impact of climate policy uncertainty on the Italian financial market. Finance Research Letters, 69, 106094. https://doi.org/10.1016/j.frl.2024.106094
  • Treepongkaruna, S., Chan, K. F., & Malik, I. (2023). Climate policy uncertainty and the cross-section of stock returns. Finance Research Letters, 55, 103837. https://doi.org/10.1016/j.frl.2023.103837
  • Vo, H., Nguyen, T., & Phan, H. V. (2024). Building a sustainable future: The role of corporate social responsibility in climate policy uncertainty management. Finance Research Letters, 60, 104831. https://doi.org/10.1016/j.frl.2023.104831
  • Wu, R., & Liu, B.-Y. (2023). Do climate policy uncertainty and investor sentiment drive the dynamic spillovers among green finance markets? Journal of Environmental Management, 347, 119008. https://doi.org/10.1016/j.jenvman.2023.119008
  • Wu, X., Yin, X., & Mei, X. (2022). Forecasting the volatility of European Union allowance futures with climate policy uncertainty using the EGARCH-MIDAS model. Sustainability, 14(7), 4306. https://doi.org/10.3390/su14074306
  • Xu, X., Huang, S., Lucey, B. M., & An, H. (2023). The impacts of climate policy uncertainty on stock markets: Comparison between China and the US. International Review of Financial Analysis, 88, 102671. https://doi.org/10.1016/j.irfa.2023.102671
  • Xu, Y., Li, M., Yan, W., & Bai, J. (2022). Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty. Resources Policy, 79, 103141. https://doi.org/10.1016/j.resourpol.2022.103141
  • Yilanci, V., Bozoklu, S., & Gorus, M. S. (2020). Are BRICS countries pollution havens? Evidence from a bootstrap ARDL bounds testing approach with a Fourier function. Sustainable Cities and Society, 55, 102035. https://doi.org/10.1016/j.scs.2020.102035
  • Yilanci, V., & Eris, Z. A. (2013). Purchasing power parity in African countries: Further evidence from Fourier unit root tests based on linear and nonlinear models. South African Journal of Economics, 81(1), 20–34. https://doi.org/10.1111/j.1813-6982.2012.01326.x
  • Yousfi, M., Brahim, M., Farhani, S., & Bouzgarrou, H. (2023). Revisiting the relationship between business conditions, climate policy uncertainty, and environmental pollution: Evidence from the USA. Environmental Science and Pollution Research, 30 (41), 94334–94346. https://doi.org/10.1007/s11356-023-28869-z
  • Zhang, Z., Cheng, S., Wang, C., Song, S., & Feng, Y. (2023). Climate policy uncertainty and corporate investment efficiency: Evidence from China. Journal of Environmental Planning and Management, 0 (0), 1–21. https://doi.org/10.1080/09640568.2023.2276062
  • Zhao, H., & Luo, N. (2024). Climate uncertainty and green index volatility: Empirical insights from Chinese financial markets. Finance Research Letters, 60, 104857. https://doi.org/10.1016/j.frl.2023.104857
  • Zhou, D., Siddik, A. B., Guo, L., & Li, H. (2023). Dynamic relationship among climate policy uncertainty, oil price and renewable energy consumption—Findings from TVP-SV-VAR approach. Renewable Energy, 204, 722–732. https://doi.org/10.1016/j.renene.2023.01.018
  • Zhou, S., & Kutan, A. M. (2014). Smooth structural breaks and the stationarity of the yen real exchange rates. Applied Economics, 46 (10), 1150–1159. https://doi.org/10.1080/00036846.2013.868587

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

Yıl 2025, Cilt: 27 Sayı: 2, 811 - 843

Cengizhan Karaca

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

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

  • 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
  • Ren, X., Zhang, X., Yan, C., & Gozgor, G. (2022). Climate policy uncertainty and firm-level total factor productivity: Evidence from China. Energy Economics, 113, 106209. https://doi.org/10.1016/j.eneco.2022.106209
  • 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
  • Sautner, Z., Van Lent, L., Vilkov, G., & Zhang, R. (2023). Firm-level climate change exposure. The Journal of Finance, 78 (3), 1449–1498. https://doi.org/10.1111/jofi.13219
  • Su, C. W., Wei, S., Wang, Y., & Tao, R. (2024). How does climate policy uncertainty affect the carbon market? Technological Forecasting and Social Change, 200, 123155. https://doi.org/10.1016/j.techfore.2023.123155
  • Syed, Q. R., Goh, S. K., & Apergis, N. (2024). Modeling the impact of climate policy uncertainty on energy production. Applied Economics Letters, 0 (0), 1–5. https://doi.org/10.1080/13504851.2024.2415322
  • Tedeschi, M., Foglia, M., Bouri, E., & Dai, P.-F. (2024). How does climate policy uncertainty affect financial markets? Evidence from Europe. Economics Letters, 234, 111443. https://doi.org/10.1016/j.econlet.2023.111443
  • Tian, L., Li, X., Lee, C.-W., & Spulbăr, C. (2024). Investigating the asymmetric impact of artificial intelligence on renewable energy under climate policy uncertainty. Energy Economics, 137, 107809. https://doi.org/10.1016/j.eneco.2024.107809
  • Tommaso, C. D., Foglia, M., & Pacelli, V. (2024). The impact of climate policy uncertainty on the Italian financial market. Finance Research Letters, 69, 106094. https://doi.org/10.1016/j.frl.2024.106094
  • Treepongkaruna, S., Chan, K. F., & Malik, I. (2023). Climate policy uncertainty and the cross-section of stock returns. Finance Research Letters, 55, 103837. https://doi.org/10.1016/j.frl.2023.103837
  • Vo, H., Nguyen, T., & Phan, H. V. (2024). Building a sustainable future: The role of corporate social responsibility in climate policy uncertainty management. Finance Research Letters, 60, 104831. https://doi.org/10.1016/j.frl.2023.104831
  • Wu, R., & Liu, B.-Y. (2023). Do climate policy uncertainty and investor sentiment drive the dynamic spillovers among green finance markets? Journal of Environmental Management, 347, 119008. https://doi.org/10.1016/j.jenvman.2023.119008
  • Wu, X., Yin, X., & Mei, X. (2022). Forecasting the volatility of European Union allowance futures with climate policy uncertainty using the EGARCH-MIDAS model. Sustainability, 14(7), 4306. https://doi.org/10.3390/su14074306
  • Xu, X., Huang, S., Lucey, B. M., & An, H. (2023). The impacts of climate policy uncertainty on stock markets: Comparison between China and the US. International Review of Financial Analysis, 88, 102671. https://doi.org/10.1016/j.irfa.2023.102671
  • Xu, Y., Li, M., Yan, W., & Bai, J. (2022). Predictability of the renewable energy market returns: The informational gains from the climate policy uncertainty. Resources Policy, 79, 103141. https://doi.org/10.1016/j.resourpol.2022.103141
  • Yilanci, V., Bozoklu, S., & Gorus, M. S. (2020). Are BRICS countries pollution havens? Evidence from a bootstrap ARDL bounds testing approach with a Fourier function. Sustainable Cities and Society, 55, 102035. https://doi.org/10.1016/j.scs.2020.102035
  • Yilanci, V., & Eris, Z. A. (2013). Purchasing power parity in African countries: Further evidence from Fourier unit root tests based on linear and nonlinear models. South African Journal of Economics, 81(1), 20–34. https://doi.org/10.1111/j.1813-6982.2012.01326.x
  • Yousfi, M., Brahim, M., Farhani, S., & Bouzgarrou, H. (2023). Revisiting the relationship between business conditions, climate policy uncertainty, and environmental pollution: Evidence from the USA. Environmental Science and Pollution Research, 30 (41), 94334–94346. https://doi.org/10.1007/s11356-023-28869-z
  • Zhang, Z., Cheng, S., Wang, C., Song, S., & Feng, Y. (2023). Climate policy uncertainty and corporate investment efficiency: Evidence from China. Journal of Environmental Planning and Management, 0 (0), 1–21. https://doi.org/10.1080/09640568.2023.2276062
  • Zhao, H., & Luo, N. (2024). Climate uncertainty and green index volatility: Empirical insights from Chinese financial markets. Finance Research Letters, 60, 104857. https://doi.org/10.1016/j.frl.2023.104857
  • Zhou, D., Siddik, A. B., Guo, L., & Li, H. (2023). Dynamic relationship among climate policy uncertainty, oil price and renewable energy consumption—Findings from TVP-SV-VAR approach. Renewable Energy, 204, 722–732. https://doi.org/10.1016/j.renene.2023.01.018
  • Zhou, S., & Kutan, A. M. (2014). Smooth structural breaks and the stationarity of the yen real exchange rates. Applied Economics, 46 (10), 1150–1159. https://doi.org/10.1080/00036846.2013.868587
Toplam 59 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Makro İktisat (Diğer)
Bölüm Makaleler
Yazarlar

Cengizhan Karaca 0000-0002-8121-7142

Erken Görünüm Tarihi 2 Haziran 2025
Yayımlanma Tarihi
Gönderilme Tarihi 10 Aralık 2024
Kabul Tarihi 15 Mart 2025
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
 Kapak Resmi İndir