BRIC ÜLKELERİNDE BİTCOİN İLE EKONOMİK POLİTİKA BELİRSİZLİK ENDEKSİ, ENFLASYON VE GENİŞ PARA ARZI (M3) ARASINDAKİ İLİŞKİSİ

Year 2023, Issue: 59, 1 - 17, 22.11.2023

Meltem Kılıç , Aydın Gürbüz , Nur Esra Bekereci

https://doi.org/10.30794/pausbed.1291278

Abstract

Bu çalışmada, Bitcoin fiyatları ile ekonomik politika belirsizlik endeksi (EPU), geniş para arzı (M3) ve enflasyon arasındaki ilişki ARDL sınır testi ve Toda-Yamamoto nedensellik testleri kullanarak araştırılmak istenmiştir. Bu bağlamda söz konusu değişkenler arasındaki kısa ve uzun dönem ilişkisi BRIC (Brezilya, Rusya, Hindistan ve Çin) ülkeleri açısından Ağustos 2010-Aralık 2021 arası aylık veriler kullanılarak gerçekleştirilmiştir. Ampirik analizler sonucunda Çin’nin EPU endeksinin uzun ve kısa dönemde Bitcoin’i negatif etkilediğine ulaşılmıştır. Hindistan için EPU endeksinin uzun dönemde Bitcoin fiyatı üzerindeki etkisi negatif iken; kısa dönemli etkiye rastlanılamadığı görülmüştür. Rusya ve Brezilya içinse EPU endeksi Bitcoin üzerinde etkili bulunamamıştır. BRIC ülkelerinde enflasyonun Bitcoin üzerindeki etkisi uzun dönemde pozitiftir. M3’ün Bitcoin üzerindeki etkisi Hindistan için kısa dönemde pozitif, Brezilya için uzun dönemde negatif yönlü çıkmıştır. Son olarak nedensellik sonuçlarına göre Hindistan ve Brezilya’da enflasyondan Bitcoin’e doğru tek yönlü nedensellik mevcuttur. Çin içinse enflasyondan Bitcoin’e; Bitcoin’den de ekonomik politika belirsizliğine doğru nedensellik ilişkisi söz konusudur. Elde edilen bulgular Bitcoin yatırımcılarının ve politika yapıcıların M3, enflasyon ve EPU’nun etkilerini göz önünde bulundurarak girişimde bulunmalarına ve Bitcoin’le ilgili düzenlemeler geliştirmelerine katkıda bulunacaktır.

Keywords

Bitcoin, EPU, Para Arzı, Enflasyon

THE RELATIONSHIP BETWEEN BITCOIN AND ECONOMIC POLICY UNCERTAINTY INDEX, INFLATION AND BROAD MONEY SUPPLY (M3) IN BRIC COUNTRIES

Abstract

In this study, it is aimed to investigate the relationship between Bitcoin prices and economic policy uncertainty (EPU), money supply (M3), and inflation using the ARDL bounds test and Toda-Yamamoto causality tests. In this context, the short- and long-term relationship between the mentioned variables was carried out for the BRIC (Brazil, Russia, India, and China) countries by using monthly data between August 2010 and December 2021. As a result of empirical analysis, it has been found that China's EPU index negatively affects Bitcoin in the long and short term. For India, the effect of the EPU index on the Bitcoin price in the long run is negative; No short-term effects were found. In Russia and Brazil, the EPU index was not found to be effective on Bitcoin. In the BRIC countries, the effect of inflation on Bitcoin is positive in the long run. The effect of M3 on Bitcoin has been positive for India in the short run and negative for Brazil in the long run. Finally, according to the causality results, there is unidirectional causality from inflation to Bitcoin in India and Brazil. For China, from inflation to Bitcoin; There is a causal relationship from Bitcoin to economic policy uncertainty. The findings will contribute to Bitcoin investors and policy makers to take initiatives and develop regulations regarding Bitcoin by considering the effects of M3, inflation and EPU.

Keywords

Bitcoin, EPU, Money Supply, Inflation

References

• Altıntaş, H., ve Ayrıçay Y. (2010). Türkiye’de Finansal Gelişme ve Ekonomik Büyüme İlişkisinin Sınır Testi Yaklaşımıyla Analizi:1987-2007. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 10(2), 71- 98.
• Akar, C, (2008). Hisse Senedi Fiyatlarıyla Yabancı İşlem Hacmi Arasındaki Nedensellik: Toda-Yamamato Yaklaşımı. Muhasebe ve Finans Dergisi, 37, 185-191.
• Baker, S. R., Bloom, N., ve Davis, S.J. (2016). Measuring Economic Policy Uncertainty. The Quarterly. Journal of Economics, 131(4) 1593–1636, https://doi.org/10.1093/qje/qjw024.
• Balua, B.M., Griffith, T.G. ve Whitby, R.J. (2021). Inflation and Bitcoin: A Descriptive Time-series Analysis. Economics Letters, 203, 1-5. https://doi.org/10.1016/j.econlet.2021.109848.
• Bouri, E. Gupta, R. Lau, C.K.M., Roubaud, D. ve Wang, S. (2018). Bitcoin and Global Financial Stress: A Copula-based Approach to Dependence and Causality in the Quantiles. The Quarterly Review of Economics and Finance, 69, 297-307. https://doi.org/10.1016/j.qref.2018.04.003.
• Bouri, E., Gupta, R. Tiwari, A.K., Roubaud, D. (2017). Does Bitcoin Hedge Global Uncertainty? Evidence From wavelet-based quantile-in-quantile regressions. Finance Research Letters. 23, 87-95.
• Brown, R. L., Durbin, j., ve Evans, j.M. (1975). Techniques For Testing the Constancy of Regression Relationships Over Time. Journal of the Royal Statistical Society, 37(2), 149-192.
• Carbó, J. M. ve Gorjón, S. (2022). Application of Machine Learning Models and Interpretability Techniques to Identify the Determinants of the Price of Bitcoin. Banco de Espana, Documentos de Trabajo, No:2215, 1-35.
• Demir, E., Gozgor, G., Lau, C.K.M., ve Vigne, S.A. (2018). Does Economic Policy Uncertainty Predict the Bitcoin Returns? An Empirical Investigation. Finance Research Letters, 26, 145-149. https://doi.org/10.1016/j.frl.2018.01.005.
• Engle, R. F., ve Granger, C.W.J. (1987). Cointegration and Error-correction: Representation, Estimation and Testing. Econometrica, 66, 251-276.
• Fang, L., Bouri, E., Gupta, R., ve Roubaud, D. (2019). Does Global Economic Uncertainty Matter for the Volatility and Hedging Effectiveness of Bitcoin? International Review of Financial Analysis, 62, 29-36. https://doi.org/10.1016/j.irfa.2018.12.010.
• Fasanya, I. O., Oliyide, J. O., Adekoya, O. B., ve Agbatogun, T. (2021). How Does Economic Policy Undertainty Connect With the Dynamic Spillovers Between Precious Etals and Bitcoin Markets? Resources Policy, 72, 1-17. https://doi.org/10.1016/j.resourpol.2021.102077.
• Hernandez, J. A., Hassan, M. Z., ve Mclver, R.P. (2021). Bitcoin, Gold, and the VIX: Short and Long-term Effects of Economic Policy Uncertainty. Applied Economics Letters, https://doi.org/10.1080/13504851.2021.2018125.
• İçözü, T. (2022). Bitcoin 13 yaşında: Geçmişten Günümüze Bitcoin’in Dönüm Noktaları https://webrazzi.com/2022/01/04/bitcoin-gecmisten-gunumuze/
• Johansen, S. (1988). Statistical Anaylsis of Cointegrating Vectors. Journal of Economic Dynamics and Control, 12, 231-254.
• Kanat, E. (2021). Küresel Ekonomik Politika Belirsizliği ve Kripto Paralar: Bootstrap Panel Nedensellik Analizi. Journal of Research in Business, 6(2), 319-331. https://dergipark.org.tr/en/download/article-file/1721090.
• Karagöl, E., Erbaykal, E., ve Ertuğrul, M.H. (2007). Türkiye’de Ekonomik Büyüme ile Elektrik Tüketimi İlişkisi: ARDL Sınır Testi Yaklaşımı. Doğuş Üniversitesi Dergisi, 8(1), 72-80.
• Koutmos, D. (2020). Market Risk and Bitcoin Returns. Annals of Operations Research, 294, 453-477. https://doi.org/10.1007/s10479-019-03255-6.
• Lucey, B. M., Vigne, S. A., Yarovaya, L. ve Wang, Y. (2022). The Cryptocurrency Uncertainty Index. Finance Research Letters, 45, 102147.
• Mamedov, N. ve Koç, S. (2023). Bitcoin ile Borsa Endeksleri İlişkisi: Yükselen Piyasa Ekonomileri için Panel Veri Analizi Uygulaması. Uluslararası Yönetim İktisat ve İşletme Dergisi, 19(1), 34-60. http://dx.doi.org/10.17130/ijmeb.1176842.
• Matkovskyy, R., Jalan, A., ve Dowling, M. (2020). Effects of Economic Policy Uncertainty Shocks on the Interdependence Between Bitcoin and Traditional Financial Markets. The Quarterly Review of Economics and Finance, 77, 150-155. https://doi.org/10.1016/j.qref.2020.02.004.
• Mokni, K. (2021). When, Where and How Economic Policy Uncertainty Predicts Bitcoin Returns and Volatility? A Quantiles-Based Analysis. The Quarterly Review of Economics and Finance, 80, 65-73.
• Nasreen, S., Tiwari, A. K., Jiang, Z., ve Yoon, S.M. (2022). Dependence Structure Between Bitcoin and Economic Policy Uncertainty: Evidence From Time-Frequency Quantile-Dependence Methods. International Journal Finance Stud, 10(49).
• Narayan, P. K., ve Narayan, S. (2005). Estimating Income and Price Elasticities of Imports For Fiji in a Cointegration Framework. Economic Modelling, 22(3), 423-438.
• Narayan, P. K., Narayan, S. Rahman, R. E. ve Setiawan, I. (2019). Bitcoin Price Growth and Indonesia’s Monetary System. Emerging Market Review, 38, 364-376. https://doi.org/10.1016/j.ememar.2018.11.005.
• Özkul, F. ve Ece, B. A. Ş. (2020). Dijital Çağın Teknolojisi Blokzincir ve Kripto Paralar: Ulusal Mevzuat ve Uluslararası Standartlar Çerçevesinde Mali Yönden Değerlendirme. Muhasebe ve Denetime Bakış, 20(60), 57-74.
• Pesaran, M. H., Shin, Y., ve Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289-326.
• Phillips, P. C., ve Peraon, P. (1988). Testing For a Unit Root in Time Series Regression. Biometrika, 75(2), 335-346.
• Piru, V. (2016). Decrypting Bitcoin Prices and Adoption Rates Using Google Search, CMC Senior Theses. Paper 1418. http://scholarship.claremont.edu/cmc_theses/1418.
• Sarker, P. K., ve Wang, L. (2022). Co-movement and Granger Causality Between Bitcoin and M2, Inflation and Economic Policy Encertainty: Evidence From the U.K. and Japan. Heliyon, 8, https://doi.org/10.1016/j.heliyon.2022.e11178.
• Shaikh, I. (2020). Policy Uncertainty and Bitcoin Returns. Borsa Istanbul Review, 20(3), 257-268.
• Song, Y., Sun, J., Zheng, S. ve Zou, W. (2022). Whether Cryptocurrency is a Tool of Investment?. in 2022 7th international conference on financial innovation and economic development (ICFIED 2022), 1393-1399. Atlantis Press.
• Sevüktekin, M. (1995). Model Karlılığının Belirlenmesi İçin Alternatif Bir Test: CUSUM ve CUSUMQ Testi. D.E.Ü. İ.İ.B.F. Dergisi, 10(2), 313-321.
• Sevüktekin, M., Ve Nargeleçekenler M. (2007). Ekonometrik Zaman Serileri Analizi Eviews Uygulamalı. 2. Basım, Nobel Yayın Dağıtım, Ankara.
• Tursoy, T. (2019). The Interaction Between Stock Prices and Interest Rates in Turkey: Empirical Evidence From ARDL Bounds Test Cointegration. Financial Innovation 5(7), 1-12, https://doi.org/10.1186/s40854-019-0124-6.
• Umar, M., Su, C-W, Rizvi, S.K.A., ve Shao, X-F. (2021). Bitcoin: A Safe Haven Asset and a Winner Amid Political and Economic Uncertainties in the US?. Technological Forecasting & Social Change, 167, 1-13, https://doi.org/10.1016/j.techfore.2021.120680.
• Yen, K. C., ve Cheng, H. P. (2021). Economic Policy Uncertainty and Cryptocurrency Volatility. Finance Research Letters, 38, 1-7, https://doi.org/10.1016/j.frl.2020.101428.
• Yin, L., Nie, J., ve Han, L. (2021). Understanding Cryptocurrency Volatility: The Role of Oil Market Shocks. International Review of Economics & Finance, 72, 233-253.
• Wang, G. J., Xie, C., Wen, D., ve Zhao, L. (2019). When Bitcoin Meets Economic Policy Uncertainty (EPU): Measuring Risk Spillover Effect From EPU to Bitcoin. Finance Research Letters, 31, 489-497. https://doi.org/10.1016/j.frl.2018.12.028.
• Wang, L., Sarker, P. K., ve Bouri, E. (2022). Short and Long Term Interactions Between Bitcoin and Economic Variables: Evidence From the US. Computational Economics.
• Wu, C. C., Ho, S. L., ve Wu, C. C. (2022). The Determinants of Bitcoin Returns and Volatility: Perspectives on Global and National Economic Policy Uncertainty. Finance Research Letters, 45, 1-7. https://doi.org/10.1016/j.frl.2021.102175.