The Relationship Between Bitcoin and Carbon Emissions: Nonlinear Cointegration Analysis

Öz

In this study, the relationship between Bitcoin (BTC) and Carbon Emission (CO2) was examined using the data between the periods 2017M1-2022M1. Based on recent studies, it is observed that crypto money and energy markets have a speculative and fragile structure, and therefore the variables may have a non-linear form. Therefore, within the framework of this information, the linearity test of the variables is carried out primarily by Luukkonen et al..(1988), Harvey et al..(2008) linearity test, and KSS (2003) nonlinear unit root test. Afterwards, KSS (2006) Nonlinear Co-integration analysis is used in the study since it is determined that the variables have a nonlinear form. According to the KSS (2006) test findings, it is determined that there is a nonlinear cointegration relationship between BTC and CO2 in the long run. This shows that the relationship between BTC and CO2 converges non-linearly to the long-run equilibrium. According to the result of the Granger causality test performed to determine the direction of this relationship after detecting the nonlinear cointegration relationship between its variables, it is determined that there is one-way causality from Bitcoin to Carbon Emission. This finding can be interpreted as policies towards obtaining the energy used in BTC production from environmentally friendly sources should be adopted.

Anahtar Kelimeler

• Bitcoin
• Carbon Emissions
• Linearity Tests
• Nonlinear Cointegration Analysis
• Granger Causality Test

Bitcoin ile Karbon Emisyonu İlişkisi: Doğrusal Olmayan Eşbütünleşme Analizi

Öz

Bu çalışmada, 2017M1-2022M1 dönemleri arasındaki veriler kullanılarak Bitcoin (BTC) ile Karbon Emisyonu (CO2) arasındaki ilişki incelenmiştir. Son zamanlarda yapılan çalışmalara istinaden kripto para ve enerji piyasalarının spekülatif ve kırılgan yapıya sahip olduğu ve bundan dolayı değişkenlerin doğrusal olmayan bir forma sahip olabileceği konusuna dikkat çekildiği gözlenmektedir. Dolayısıyla bu bilgiler çerçevesinde çalışmada öncelikle Luukkonen vd. (1988), Harvey vd. (2008) doğrusallık testi ve Kapetanios vd. (2003) doğrusal olmayan birim kök testi ile değişkenlerin doğrusallık sınaması yapılmaktadır. Akabinde değişkenlerin doğrusal olmayan forma sahip olduğu tespit edildiği için çalışmada Kapetanios vd. (2006) Doğrusal Olmayan Eşbütünleşme analizi kullanılmaktadır. Kapetanios vd. (2006) testi bulgularına göre BTC ile CO2 arasında uzun dönemde doğrusal olmayan bir eşbütünleşme ilişkisi olduğu tespit edilmektedir. Bu durum BTC ile CO2 arasındaki ilişkinin uzun dönemde dengeye doğrusal olmayan bir şekilde yakınsadığı sonucunu göstermektedir. Değişkenler arasında doğrusal olmayan eşbütünleşme ilişkisini tespit ettikten sonra bu ilişkinin yönünü belirlemek amacıyla yapılan Granger nedensellik testi sonucuna göre ise Bitcoin’den Karbon Emisyonuna doğru tek yönlü nedensellik olduğu tespit edilmektedir. Bu bulgu, BTC üretiminde kullanılan enerjinin çevre dostu kaynaklardan elde edilmesine yönelik politikaların benimsenmesi gerektiği biçiminde yorumlanabilir.

Anahtar Kelimeler

• Bitcoin
• Karbon Emisyonu
• Granger Nedensellik Testi.
• Doğrusallık Testleri
• Doğrusal Olmayan Eşbütünleşme Analizi
• Granger Nedensellik Testi

Kaynakça

1. Baur, D.G. and Oll, J. (2022). Bitcoin investments and climate change: A financial and carbon intensity perspective. Finance Research Letters, 47, 102575. https://doi.org/10.1016/j.frl.2021.102575
2. Bouri, E., Shahzad, S.J.H. and Roubaud, D. (2019). Co-explosivity in the cryptocurrency market. Finance Research Letters, 29, 178-183. https://doi.org/10.1016/j.frl.2018.07.005
3. Brock, W.A., Dechert, D., Scheinkman, J.A. and LeBaron, B. (1987). A test for independence based on the correlation dimension. Eonometric Reviews, 15(3), 197-235, https://doi.org/10.1080/07474939608800353
4. Corbet, S., Lucey, B. and Yarovaya, L. (2021). Bitcoin-energy markets interrelationships - New evidence. Resources Policy, 70, 101916. https://doi.org/10.1016/j.resourpol.2020.101916
5. Cuestas J.C. and Garrant, D. (2011). Is real GDP per capita a stationary process? Smooth transitions, nonlinear trends and unit root testing. Empirical Economics, 41, 555–563. https://doi.org/10.1007/S00181-010-0389-0
6. Di Febo, E., Ortolano, A., Foglia, M., Leone, M. and Angelini, E. (2021). From Bitcoin to carbon allowances: An asymmetric extreme risk spillover. Journal of Environmental Management, 298, 113384. https://doi.org/10.1016/j.envman.2021.113384
7. Dogan, E., Majeed, M.T. and Luni, T. (2022). Are clean energy and carbon emission allowances caused by Bitcoin? A novel time-varying method. Journal of Cleaner Production, 347, 131089. https://doi.org/10.1016/j.jclepro.2022.131089
8. Engle, R.F. and Granger, C.W.J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251-276. https://doi.org/10.2307/1913236

9. Erdogan, S., Ahmed, M.Y. and Sarkodie, S.A. (2022). Analyzing asymmetric effects of cryptocurrency demand on environmental sustainability. Environmental Science and Pollution Research, 29(21), 31723-31733. https://doi.org/10.1007/s11356-021-17998-y
10. Harvey, D.I. and Leybourne, S.J. (2007). Testing for time series linearity. The Econometrics Journal, 10, 149-165. https://doi.org/10.1111/j.1368-423X.2007.00203.x
11. Harvey, D.I. Leybourne, S.J. and Xiao, B. (2008). A powerful test for linearity when the order of ıntegration is unknown. Studies in Nonlinear Dynamics & Econometrics, 12(3), 1-22. https://doi.org/10.2202/1558-3708.1582
12. Hepsağ, A. ve Akçalı, B.Y. (2015). Zayıf formda piyasa etkinliğinin asimetrik doğrusal olmayan birim kök testi ile analizi: G-7 ve E-7 ülkeleri örneği. BDDK Bankacılık ve Finansal Piyasalar Dergisi, 9(2), 73-90. Erişim adresi: https://dergipark.org.tr/en/pub/bddkdergisi/
13. Investing. (2022). Bitcoin [Veri seti]. Erişim adresi: https://www.investing.com/crypto/bitcoin
14. Jana, R.K., Ghosh, I., Das, D. and Dutta, A. (2021). Determinants of electronic waste generation in Bitcoin network: Evidence from the machine learning approach. Technological Forecasting and Social Change, 173, 121101. https://doi.org/10.1016/j.techfore.2021.121101
15. Jiang, S., Li, Y., Lu, Q., Hong, Y., Guan, D., Xiong, Y. and Wang, S. (2021). Policy assessments for the carbon emission flows and sustainability of Bitcoin blockchain operation in China. Nature Communications, 12(1), 1938 https://doi.org/10.1038/s41467-021-22256-3
16. Kapetanios G., Shin Y. and Snell A. (2003). Testing for a unit root in the nonlinear STAR framework. Journal of Econometrics, 112, 359-379. https://doi.org/10.1016/S0304-407(02)00202-6
17. Kapetanios, G., Shin, Y. and Snell, A. (2006). Testing for cointegration in nonlinear smooth transition error correction models. Econometric Theory, 22(2), 279-303. https://doi.org/10.1017/S0266466606060129
18. Khezri, M. Heshmati, A. and Khodaei, M. (2022). Environmental implications of economic complexity and its role in determining how renewable energies affect CO2 emissions. Applied Energy, 306, 117948. https://doi.org/10.1016/j.apenergy.2021.117948
19. Kompas, T., Pham, V.H. and Che, T.N. (2018). The effects of climate change on GDP by country and the global economic gains from complying with the Paris climate accord. Earth's Future, 6(8), 1153-1173. https://doi.org/10.1029/2018EF000922
20. Köhler, S. and Pizzol, M. (2019). Life cycle assessment of bitcoin mining. Environmental Science & Technology, 53(23), 13598-13606. https://doi.org/10.1021/acs.est.9b05687
21. Luukkonen, R., Saikkonen, P. and Terasvirta, T. (1988). Testing linearity against smooth transition autoregressive models. Biometrika, 75(3), 491–499. https://doi.org/10.1093/biomet/75.3.491
22. Miśkiewicz, R., Matan, K. and Karnowski, J. (2022). The role of crypto trading in the economy, renewable energy consumption and ecological degradation. Energies, 15(10), 3805. https://doi.org/10.3390/en15103805
23. Mohsin, M., Naseem, S., Zia‐ur‐Rehman, M., Baig, S.A. and Salamat, S. (2020). The crypto‐trade volume, GDP, energy use, and environmental degradation sustainability: An analysis of the top 20 crypto‐trader countries. International Journal of Finance & Economics, 25(1), 651-667. https://doi.org/10.1002/ijfe.2442
24. Mora, C., Rollins, R.L., Taladay, K., Kantar, M.B., Chock, M.K., Shimada, M. and Franklin, E.C. (2018). Bitcoin emissions alone could push global warming above 2 C. Nature Climate Change, 8(11), 931-933. https://doi.org/10.1038/s41558-018-0319-2
25. Narayanan, A., Bonneau, J., Felten, E., Miller, A. and Goldfeder, S. (2016). Bitcoin and cryptocurrency technologies: A comprehensive introduction. UK: Princeton University Press.
26. Omay, T. and Kan, E.Ö. (2010). Re-examining the threshold effects in the inflation–growth Nexus with cross-sectionally dependent non-linear panel: Evidence from six industrialized economies. Economic Modelling, 27, 996-1005. https://doi.org/10.1016/j.econmod.2010.04.011
27. Othman, A. and Bob, B.A. (2022). Bitcoin mining’s energy consumption and global carbon dioxide emissions: Wavelet coherence analysis (Arap Monetary Fund Economic Studies No. 100-2022). Retrieved from https://www.amf.org.ae/sites/default/files/publications/2022-06
28. Pham, L., Karim, S., Naeem, M.A. and Long, C. (2022). A tale of two tails among carbon prices, green and non-green cryptocurrencies. International Review of Financial Analysis, 82, 102139. https://doi.org/10.1016/j.irfa.2022.102139
29. Roeck, M. and Drennen, T. (2022). Life cycle assessment of behind-the-meter Bitcoin mining at US power plant. The International Journal of Life Cycle Assessment, 27(3), 355-365. https://doi.org/10.1007/s11367-022-02025-0
30. Rowlatt, J. (2020). How Bitcoin’s vast energy use could burst its bubble. Retrieved from https://www.bbc.com/news/science-environment-56215787
31. Schinckus C., Nguyen C.P. and Ling, F.C.H. (2020). Crypto-currencies trading and energy consumption. International Journal of Energy Economics and Policy, 10(3), 355. https://doi.org/10.32179/ijeep.9258
32. Trenberth, K.E. (2018). Climate change caused by human activities is happening and it already has major consequences. Journal of Energy and Natural Resources Law, 36(4), 463-481. https://doi.org/10.1080/02646811.2018.1450895
33. Truby, J. (2018). Decarbonizing Bitcoin: Law and policy choices for reducing the energy consumption of blockchain technologies and digital currencies. Energy Research and Social Science, 44, 399-410. https://doi.org/10.1016/j.erss.2018.06.009
34. Yang, L. and Xu, H. (2021). Climate value at risk and expected shortfall for Bitcoin market. Climate Risk Management, 32, 100310. https://doi.org/10.1016/j.crm.2021.100310
35. Yılancı, V. (2009). Fisher hipotezinin Türkiye için sınanması: Doğrusal olmayan eşbütünleşme analizi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 23(4), 205-213. Erişim adresi: https://dergipark.org.tr/en/pub/atauniiibd