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Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı

Yıl 2026, Cilt: 44 Sayı: 1, 1 - 25, 23.03.2026
https://doi.org/10.17065/huniibf.1664991
https://izlik.org/JA77CK43SL

Öz

Çalışma, küresel sürdürülebilir enerjiye geçiş bağlamında yeşil teknoloji endeksleri ile stratejik metaller, özellikle bakır ve nikel arasındaki dinamik ve asimetrik etkileşimleri incelemektedir. Amaç, farklı ekonomik koşullar altında finansal piyasalar ile emtia piyasaları arasındaki ilişkinin zaman içinde nasıl değiştiğini belirlemektir. Ocak 2015'ten Eylül 2024'e kadar aylık veriler kullanılarak, Asimetrik Zaman Değişkenli Parametre VAR (TVP-VAR) bağlantılılık yaklaşımı uygulanmıştır. Analiz, MSCI ACWI Sustainable Impact, NASDAQ Clean Edge Green Energy, S&P Kensho Cleantech endekslerini ve bakır ve nikel fiyatlarını içermektedir. Bulgular, ekonomik belirsizlik ve jeopolitik risklerin bağlantı yapısını güçlü bir şekilde etkilediğini göstermektedir. Yeşil enerji talebinin arttığı dönemlerde metal fiyatları ve yeşil endeksler birlikte hareket ederken kriz dönemlerinde bu ilişki zayıflamaktadır. NASDAQ Clean Edge Green Energy ve S&P Kensho Cleantech net aktarıcılar olarak bakır, nikel ve MSCI ACWI Sustainable Impact net alıcılar olarak hareket etmektedir. En güçlü aktarım NASDAQ'dan kaynaklanmaktadır. Bunu Kensho ve ACWI izlemektedir. Bu sonuç yeşil hisse senedi piyasalarının yayılma ağını domine ettiğini göstermektedir. Genel olarak sonuçlar stratejik metallerin portföy riskten korunma araçları olarak hizmet edebileceğini ve politika yapıcıların enerji geçişi sırasında arz güvenliği risklerini dikkate almaları gerektiğini göstermektedir.

Kaynakça

  • KAYNAKÇA Adekoya, O. B., Akinseye, A. B., Antonakakis, N., Chatziantoniou, I., Gabauer, D., & Oliyide, J. (2022). Crude oil and Islamic sectoral stocks: Asymmetric TVP-VAR connectedness and investment strategies. Resources Policy, 78(June), 102877. https://doi.org/10.1016/j.resourpol.2022.102877
  • Anscombe, F. J., & Glynn, W. J. (1983). Distribution of the kurtosis statistic b2 for normal samples. Biometrika, 70(1), 227–234. https://doi.org/10.1093/biomet/70.1.227
  • Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & de Gracia, F. P. (2020). Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness. Energy Economics, 91, 104762. https://doi.org/10.1016/j.eneco.2020.104762
  • Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on Time-Varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
  • Briere, M., & Ramelli, S. (2021). Green sentiment, stock returns, and corporate behavior. SSRN Electronic Journal, October. https://doi.org/10.2139/ssrn.3850923
  • Broadstock, D., Chatziantoniou, I., & Gabauer, D. (2020). Minimum connectedness portfolios and the market for green bonds: Advocating socially responsible investment (SRI) activity. SSRN Electronic Journal, 15(4), 429–439. https://doi.org/10.2139/ssrn.3793771
  • Chatziantoniou, I., & Gabauer, D. (2021). EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness. Quarterly Review of Economics and Finance, 79, 1–14. https://doi.org/10.1016/j.qref.2020.12.003
  • Chen, J., Wang, Y., & Ren, X. (2022). Asymmetric effects of non-ferrous metal price shocks on clean energy stocks: Evidence from a quantile-on-quantile method. Resources Policy, 78(May), 102796. https://doi.org/10.1016/j.resourpol.2022.102796
  • Chen, Z., Kleijn, R., & Lin, H. X. (2023). Metal requirements for building electrical grid systems of global wind power and utility-scale solar photovoltaic until 2050. Environmental Science and Technology, 57(2), 1080–1091. https://doi.org/10.1021/acs.est.2c06496
  • Chian, T. Y., Wei, W. L. J., Ze, E. L. M., Ren, L. Z., Ping, Y. E., Abu Bakar, N. Z., Faizal, M., & Sivakumar, S. (2019). A review on recent progress of batteries for electric vehicles. International Journal of Applied Engineering Research, 14(24), 4441–4461. http://www.ripublication.com
  • Christoffersen, P., Errunza, V., Jacobs, K., & Jin, X. (2014). Correlation dynamics and international diversification benefits. International Journal of Forecasting, 30(3), 807–824. https://doi.org/10.1016/j.ijforecast.2014.01.001 Coqueret, G., Tavin, B., & ZHOU, Y. (2024). Sustainable commodity factors. SSRN Electronic Journal, December. https://doi.org/10.2139/ssrn.4698258
  • D’AGOSTINO, R. B. (1970). Transformation to normality of the null distribution of g 1. Biometrika, 57(3), 679–681. https://doi.org/10.1093/biomet/57.3.679
  • Dias, R. M., Chambino, M., Teixeira, N., Alexandre, P., & Heliodoro, P. (2023). Balancing portfolios with metals: A safe haven for green energy investors?. Energies, 16(20), 1–21. https://doi.org/10.3390/en16207197
  • Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. Economic Journal, 119(534), 158–171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
  • Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006
  • Ding, Y., Mu, D., Wu, B., Wang, R., Zhao, Z., & Wu, F. (2017). Recent progresses on nickel-rich layered oxide positive electrode materials used in lithium-ion batteries for electric vehicles. Applied Energy, 195, 586–599. https://doi.org/10.1016/j.apenergy.2017.03.074
  • Ellabban, O., Abu-Rub, H., & Blaabjerg, F. (2014). Renewable energy resources: Current status, future prospects and their enabling technology. Renewable and Sustainable Energy Reviews, 39, 748–764. https://doi.org/10.1016/j.rser.2014.07.113
  • Elliott, B. Y. G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813–836.https://doi.org/10.2307/2171846
  • Fisher, T. J., & Gallagher, C. M. (2012). New weighted portmanteau statistics for time series goodness of fit testing. Journal of the American Statistical Association, 107(498), 777–787. https://doi.org/10.1080/01621459.2012.688465
  • Flammer, C. (2021). Corporate green bonds. Journal of Financial Economics, 142(2), 499–516. https://doi.org/10.1016/j.jfineco.2021.01.010
  • García-Olivares, A., Ballabrera-Poy, J., García-Ladona, E., & Turiel, A. (2012). A global renewable mix with proven technologies and common materials. Energy Policy, 41, 561–574. https://doi.org/10.1016/j.enpol.2011.11.018
  • Goutte, S., & Mhadhbi, M. (2024). Analyzing crisis dynamics: How metal-energy markets influence green electricity investments. Energy Economics, 134(May), 107614. https://doi.org/10.1016/j.eneco.2024.107614
  • Huber, S. T., & Steininger, K. (2022). Critical sustainability issues in the production of wind and solar electricity generation as well as storage facilities and possible solutions. Journal of Cleaner Production, 339(January), 130720. https://doi.org/10.1016/j.jclepro.2022.130720
  • Hussain, A., Arif, S. M., & Aslam, M. (2017). Emerging renewable and sustainable energy technologies: State of the art. Renewable and Sustainable Energy Reviews, 71(June 2015), 12–28. https://doi.org/10.1016/j.rser.2016.12.033
  • Hussain, J., Kui, Z., Khan, A., Akhtar, R., Ali, R., & Yin, Y. (2023). Proposing a sustainable investment index for measuring economic performance and sustainability: A step toward clean and affordable energy. Sustainable Energy Technologies and Assessments, 60(November), 103564. https://doi.org/10.1016/j.seta.2023.103564
  • Ikram, M., Ferasso, M., Sroufe, R., & Zhang, Q. (2021). Assessing green technology indicators for cleaner production and sustainable investments in a developing country context. Journal of Cleaner Production, 322(March), 129090. https://doi.org/10.1016/j.jclepro.2021.129090
  • Islam, M. M., Sohag, K., Hammoudeh, S., Mariev, O., & Samargandi, N. (2022). Minerals import demands and clean energy transitions: A disaggregated analysis. Energy Economics, 113(July), 106205. https://doi.org/10.1016/j.eneco.2022.106205
  • Jain, M., Sharma, G. D., & Srivastava, M. (2018). Can sustainable investment yield better financial returns: A comparative study of ESG indices and MSCI indices. Risks, 7(1), 15. https://doi.org/10.3390/risks7010015
  • Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5
  • Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4
  • Leader, A., Gaustad, G., & Babbitt, C. (2019). The effect of critical material prices on the competitiveness of clean energy technologies. Materials for Renewable and Sustainable Energy, 8(2), 1–17.https:/doi.org/10.1007/s40243-019-0146-z
  • Li, H., Li, Y., & Zhang, H. (2023). The spillover effects among the traditional energy markets, metal markets and sub-sector clean energy markets. Energy, 275(April), 127384. https://doi.org/10.1016/j.energy.2023.127384
  • Markowitz, H.M., 1959. Portfolio selection: Efficient diversification of investments. John Wiley. Meziani, A. S. (2020). It is still not easy being green for exchange-traded funds. Journal of Index Investing, 10(4), 6–23. https://doi.org/10.3905/jii.2020.1.084
  • Mohsin, M., Taghizadeh-Hesary, F., Iqbal, N., & Saydaliev, H. B. (2022). The role of technological progress and renewable energy deployment in green economic growth. Renewable Energy, 190, 777–787. https://doi.org/10.1016/j.renene.2022.03.076
  • Moreno-Leiva, S., Haas, J., Junne, T., Valencia, F., Godin, H., Kracht, W., Nowak, W., & Eltrop, L. (2020). Renewable energy in copper production: A review on systems design and methodological approaches. Journal of Cleaner Production, 246, 118978. https://doi.org/10.1016/j.jclepro.2019.118978
  • Negem, M., Nady, H., & El-Rabiei, M. M. (2019). Nanocrystalline nickel–cobalt electrocatalysts to generate hydrogen using alkaline solutions as storage fuel for the renewable energy. International Journal of Hydrogen Energy, 44(23), 11411–11420. https://doi.org/10.1016/j.ijhydene.2019.03.128
  • Nguyen, R. T., Eggert, R. G., Severson, M. H., & Anderson, C. G. (2021). Global electrification of vehicles and intertwined material supply chains of cobalt, copper and nickel. Resources, Conservation and Recycling, 167(September 2020), 105198. https://doi.org/10.1016/j.resconrec.2020.105198
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Time-Varying Relationships between Green Technology Indices and Metal Markets: Asymmetric TVP-VAR Connectedness Approach

Yıl 2026, Cilt: 44 Sayı: 1, 1 - 25, 23.03.2026
https://doi.org/10.17065/huniibf.1664991
https://izlik.org/JA77CK43SL

Öz

Abstract
The study examines the dynamic and asymmetric interactions between green technology indices and strategic metals, particularly copper and nickel, in the context of the global transition to sustainable energy.The aim is to determine how the relationship between financial markets and commodity markets changes over time under different economic conditions. Using monthly data from January 2015 to September 2024, the Asymmetric Time-Variable Parameter VAR (TVP-VAR) connectivity approach was applied. The analysis includes the MSCI ACWI Sustainable Impact, NASDAQ Clean Edge Green Energy, and S&P Kensho Cleantech indices, as well as copper and nickel prices. The findings show that economic uncertainty and geopolitical risks strongly affect the linkage structure. While metal prices and green indices move together during periods of increased green energy demand, this relationship weakens during times of crisis. NASDAQ Clean Edge Green Energy and S&P Kensho Cleantech act as net transmitters, while copper, nickel, and MSCI ACWI Sustainable Impact act as net receivers. The strongest transmission originates from NASDAQ, followed by Kensho and ACWI. This result indicates that green equity markets dominate the diffusion network.Overall, the findings suggest that strategic metals can serve as portfolio hedging instruments and that policymakers should consider supply security risks during the energy transition.

Kaynakça

  • KAYNAKÇA Adekoya, O. B., Akinseye, A. B., Antonakakis, N., Chatziantoniou, I., Gabauer, D., & Oliyide, J. (2022). Crude oil and Islamic sectoral stocks: Asymmetric TVP-VAR connectedness and investment strategies. Resources Policy, 78(June), 102877. https://doi.org/10.1016/j.resourpol.2022.102877
  • Anscombe, F. J., & Glynn, W. J. (1983). Distribution of the kurtosis statistic b2 for normal samples. Biometrika, 70(1), 227–234. https://doi.org/10.1093/biomet/70.1.227
  • Antonakakis, N., Cunado, J., Filis, G., Gabauer, D., & de Gracia, F. P. (2020). Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness. Energy Economics, 91, 104762. https://doi.org/10.1016/j.eneco.2020.104762
  • Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on Time-Varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
  • Briere, M., & Ramelli, S. (2021). Green sentiment, stock returns, and corporate behavior. SSRN Electronic Journal, October. https://doi.org/10.2139/ssrn.3850923
  • Broadstock, D., Chatziantoniou, I., & Gabauer, D. (2020). Minimum connectedness portfolios and the market for green bonds: Advocating socially responsible investment (SRI) activity. SSRN Electronic Journal, 15(4), 429–439. https://doi.org/10.2139/ssrn.3793771
  • Chatziantoniou, I., & Gabauer, D. (2021). EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness. Quarterly Review of Economics and Finance, 79, 1–14. https://doi.org/10.1016/j.qref.2020.12.003
  • Chen, J., Wang, Y., & Ren, X. (2022). Asymmetric effects of non-ferrous metal price shocks on clean energy stocks: Evidence from a quantile-on-quantile method. Resources Policy, 78(May), 102796. https://doi.org/10.1016/j.resourpol.2022.102796
  • Chen, Z., Kleijn, R., & Lin, H. X. (2023). Metal requirements for building electrical grid systems of global wind power and utility-scale solar photovoltaic until 2050. Environmental Science and Technology, 57(2), 1080–1091. https://doi.org/10.1021/acs.est.2c06496
  • Chian, T. Y., Wei, W. L. J., Ze, E. L. M., Ren, L. Z., Ping, Y. E., Abu Bakar, N. Z., Faizal, M., & Sivakumar, S. (2019). A review on recent progress of batteries for electric vehicles. International Journal of Applied Engineering Research, 14(24), 4441–4461. http://www.ripublication.com
  • Christoffersen, P., Errunza, V., Jacobs, K., & Jin, X. (2014). Correlation dynamics and international diversification benefits. International Journal of Forecasting, 30(3), 807–824. https://doi.org/10.1016/j.ijforecast.2014.01.001 Coqueret, G., Tavin, B., & ZHOU, Y. (2024). Sustainable commodity factors. SSRN Electronic Journal, December. https://doi.org/10.2139/ssrn.4698258
  • D’AGOSTINO, R. B. (1970). Transformation to normality of the null distribution of g 1. Biometrika, 57(3), 679–681. https://doi.org/10.1093/biomet/57.3.679
  • Dias, R. M., Chambino, M., Teixeira, N., Alexandre, P., & Heliodoro, P. (2023). Balancing portfolios with metals: A safe haven for green energy investors?. Energies, 16(20), 1–21. https://doi.org/10.3390/en16207197
  • Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. Economic Journal, 119(534), 158–171. https://doi.org/10.1111/j.1468-0297.2008.02208.x
  • Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57–66. https://doi.org/10.1016/j.ijforecast.2011.02.006
  • Ding, Y., Mu, D., Wu, B., Wang, R., Zhao, Z., & Wu, F. (2017). Recent progresses on nickel-rich layered oxide positive electrode materials used in lithium-ion batteries for electric vehicles. Applied Energy, 195, 586–599. https://doi.org/10.1016/j.apenergy.2017.03.074
  • Ellabban, O., Abu-Rub, H., & Blaabjerg, F. (2014). Renewable energy resources: Current status, future prospects and their enabling technology. Renewable and Sustainable Energy Reviews, 39, 748–764. https://doi.org/10.1016/j.rser.2014.07.113
  • Elliott, B. Y. G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient tests for an autoregressive unit root. Econometrica, 64(4), 813–836.https://doi.org/10.2307/2171846
  • Fisher, T. J., & Gallagher, C. M. (2012). New weighted portmanteau statistics for time series goodness of fit testing. Journal of the American Statistical Association, 107(498), 777–787. https://doi.org/10.1080/01621459.2012.688465
  • Flammer, C. (2021). Corporate green bonds. Journal of Financial Economics, 142(2), 499–516. https://doi.org/10.1016/j.jfineco.2021.01.010
  • García-Olivares, A., Ballabrera-Poy, J., García-Ladona, E., & Turiel, A. (2012). A global renewable mix with proven technologies and common materials. Energy Policy, 41, 561–574. https://doi.org/10.1016/j.enpol.2011.11.018
  • Goutte, S., & Mhadhbi, M. (2024). Analyzing crisis dynamics: How metal-energy markets influence green electricity investments. Energy Economics, 134(May), 107614. https://doi.org/10.1016/j.eneco.2024.107614
  • Huber, S. T., & Steininger, K. (2022). Critical sustainability issues in the production of wind and solar electricity generation as well as storage facilities and possible solutions. Journal of Cleaner Production, 339(January), 130720. https://doi.org/10.1016/j.jclepro.2022.130720
  • Hussain, A., Arif, S. M., & Aslam, M. (2017). Emerging renewable and sustainable energy technologies: State of the art. Renewable and Sustainable Energy Reviews, 71(June 2015), 12–28. https://doi.org/10.1016/j.rser.2016.12.033
  • Hussain, J., Kui, Z., Khan, A., Akhtar, R., Ali, R., & Yin, Y. (2023). Proposing a sustainable investment index for measuring economic performance and sustainability: A step toward clean and affordable energy. Sustainable Energy Technologies and Assessments, 60(November), 103564. https://doi.org/10.1016/j.seta.2023.103564
  • Ikram, M., Ferasso, M., Sroufe, R., & Zhang, Q. (2021). Assessing green technology indicators for cleaner production and sustainable investments in a developing country context. Journal of Cleaner Production, 322(March), 129090. https://doi.org/10.1016/j.jclepro.2021.129090
  • Islam, M. M., Sohag, K., Hammoudeh, S., Mariev, O., & Samargandi, N. (2022). Minerals import demands and clean energy transitions: A disaggregated analysis. Energy Economics, 113(July), 106205. https://doi.org/10.1016/j.eneco.2022.106205
  • Jain, M., Sharma, G. D., & Srivastava, M. (2018). Can sustainable investment yield better financial returns: A comparative study of ESG indices and MSCI indices. Risks, 7(1), 15. https://doi.org/10.3390/risks7010015
  • Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. https://doi.org/10.1016/0165-1765(80)90024-5
  • Koop, G., Pesaran, M. H., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119–147. https://doi.org/10.1016/0304-4076(95)01753-4
  • Leader, A., Gaustad, G., & Babbitt, C. (2019). The effect of critical material prices on the competitiveness of clean energy technologies. Materials for Renewable and Sustainable Energy, 8(2), 1–17.https:/doi.org/10.1007/s40243-019-0146-z
  • Li, H., Li, Y., & Zhang, H. (2023). The spillover effects among the traditional energy markets, metal markets and sub-sector clean energy markets. Energy, 275(April), 127384. https://doi.org/10.1016/j.energy.2023.127384
  • Markowitz, H.M., 1959. Portfolio selection: Efficient diversification of investments. John Wiley. Meziani, A. S. (2020). It is still not easy being green for exchange-traded funds. Journal of Index Investing, 10(4), 6–23. https://doi.org/10.3905/jii.2020.1.084
  • Mohsin, M., Taghizadeh-Hesary, F., Iqbal, N., & Saydaliev, H. B. (2022). The role of technological progress and renewable energy deployment in green economic growth. Renewable Energy, 190, 777–787. https://doi.org/10.1016/j.renene.2022.03.076
  • Moreno-Leiva, S., Haas, J., Junne, T., Valencia, F., Godin, H., Kracht, W., Nowak, W., & Eltrop, L. (2020). Renewable energy in copper production: A review on systems design and methodological approaches. Journal of Cleaner Production, 246, 118978. https://doi.org/10.1016/j.jclepro.2019.118978
  • Negem, M., Nady, H., & El-Rabiei, M. M. (2019). Nanocrystalline nickel–cobalt electrocatalysts to generate hydrogen using alkaline solutions as storage fuel for the renewable energy. International Journal of Hydrogen Energy, 44(23), 11411–11420. https://doi.org/10.1016/j.ijhydene.2019.03.128
  • Nguyen, R. T., Eggert, R. G., Severson, M. H., & Anderson, C. G. (2021). Global electrification of vehicles and intertwined material supply chains of cobalt, copper and nickel. Resources, Conservation and Recycling, 167(September 2020), 105198. https://doi.org/10.1016/j.resconrec.2020.105198
  • Niu, H., & Zhang, S. (2024). Asymmetric effects of commodity and stock market on Chinese green market: Evidence from wavelet-based quantile-on-quantile approach. Renewable Energy, 230(May), 120794.https:/doi.org/10.1016/j.renene.2024.120794
  • Norgren, A., Carpenter, A., & Heath, G. (2020). Design for recycling principles applicable to selected clean energy technologies: Crystalline-Silicon photovoltaic modules, electric vehicle batteries, and wind urbine blades. Journal of Sustainable Metallurgy, 6(4), 761–774. https://doi.org/10.1007/s40831-020-00313-3
  • Nwonye, N. G., Onuselogu, O. C. O., Anisiuba, C. A., Ezeaku, H. C., & Egbo, O. P. (2023). Dynamics of green metal price volatility in times of geopolitical tensions: Effects of oil price shocks and carbon emissions futures. Journal of Cleaner Production, 412(April), 137383. https://doi.org/10.1016/j.jclepro.2023.137383
  • Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17–29. https://doi.org/10.1016/S0165-1765(97)00214-0
  • Pigłowska, M., Kurc, B., Fuć, P., & Szymlet, N. (2024). Novel recycling technologies and safety aspects of lithium ion batteries for electric vehicles. Journal of Material Cycles and Waste Management, 26(5), 2656–2669. https://doi.org/10.1007/s10163-024-02028-z
  • Tirronen, T., Sukhomlinov, D., O’Brien, H., Taskinen, P., & Lundström, M. (2017). Distributions of lithium-ion and nickel-metal hydride battery elements in copper converting. Journal of Cleaner Production, 168, 399–409. https://doi.org/10.1016/j.jclepro.2017.09.051
  • Trancoso, T., & Gomes, S. (2024). Green shocks: The spillover effects of green equity indices on global market dynamics. Economies, 12(4), 1–16. https://doi.org/10.3390/economies12040083
  • Wang, L., Guan, L., Ding, Q., & Zhang, H. (2023). Asymmetric impact of COVID-19 news on the connectedness of the green energy, dirty energy, and non-ferrous metal markets. Energy Economics, 126(February), 106925. https://doi.org/10.1016/j.eneco.2023.106925
  • World Bank. (2020). Minerals for climate action: The mineral intensity of the clean energy transition. Washington, DC: World Bank. 5.04.2025 tarihinde https://documents.worldbank.org/en/publication/documents-reports/documentdetail/ 099052423172525564/p16627806f5aa400508f8c0bdcba0878a3e adresinden alınmıştır.
  • Yousfi, M., & Bouzgarrou, H. (2024). Geopolitical risk, economic policy uncertainty, and dynamic connectedness between clean energy, conventional energy, and food markets. Environmental Science and Pollution Research International, 31(3), 4925–4945. https://doi.org/10.1007/s11356-023-31379-7
  • Zeng, X., Li, M., Abd El-Hady, D., Alshitari, W., Al-Bogami, A. S., Lu, J., & Amine, K. (2019). Commercialization of Lithium Battery Technologies for Electric Vehicles. Advanced Energy Materials, 9(27), 1–25. https://doi.org/10.1002/aenm.201900161
  • Zhang, H., Shao, Y., Han, X., & Chang, H. L. (2022). A road towards ecological development in China: The nexus between green investment, natural resources, green technology innovation, and economic growth. Resources Policy, 77(December 2021), 102746. https://doi.org/10.1016/j.resourpol.2022.102746
Toplam 49 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Zaman Serileri Analizi
Bölüm Araştırma Makalesi
Yazarlar

Şerife Akıncı Tok 0000-0002-2505-1985

Gönderilme Tarihi 25 Mart 2025
Kabul Tarihi 6 Kasım 2025
Yayımlanma Tarihi 23 Mart 2026
DOI https://doi.org/10.17065/huniibf.1664991
IZ https://izlik.org/JA77CK43SL
Yayımlandığı Sayı Yıl 2026 Cilt: 44 Sayı: 1

Kaynak Göster

APA Akıncı Tok, Ş. (2026). Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 44(1), 1-25. https://doi.org/10.17065/huniibf.1664991
AMA 1.Akıncı Tok Ş. Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2026;44(1):1-25. doi:10.17065/huniibf.1664991
Chicago Akıncı Tok, Şerife. 2026. “Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı”. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 44 (1): 1-25. https://doi.org/10.17065/huniibf.1664991.
EndNote Akıncı Tok Ş (01 Mart 2026) Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 44 1 1–25.
IEEE [1]Ş. Akıncı Tok, “Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı”, Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, c. 44, sy 1, ss. 1–25, Mar. 2026, doi: 10.17065/huniibf.1664991.
ISNAD Akıncı Tok, Şerife. “Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı”. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 44/1 (01 Mart 2026): 1-25. https://doi.org/10.17065/huniibf.1664991.
JAMA 1.Akıncı Tok Ş. Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2026;44:1–25.
MLA Akıncı Tok, Şerife. “Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı”. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, c. 44, sy 1, Mart 2026, ss. 1-25, doi:10.17065/huniibf.1664991.
Vancouver 1.Şerife Akıncı Tok. Yeşil Teknoloji Endeksleri ve Metal Piyasaları Arasındaki Zamanla Değişen İlişkiler: Asimetrik TVP-VAR Bağlantılılık Yaklaşımı. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 01 Mart 2026;44(1):1-25. doi:10.17065/huniibf.1664991

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