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INTERNATIONAL RESERVE CURRENCIES AND THE FUTURE OF THE CHINESE YUAN

Year 2023, , 812 - 846, 29.12.2023
https://doi.org/10.36543/kauiibfd.2023.033

Abstract

The purpose of this study is to explore has the possibility of the Chinese Yuan to becoming a dominant currency among countries with reserve currencies. The study examines GDP (world share), the share of total reserves in a country’s GDP, and the Consumer Price Index (CPI). Only countries that possess reserve currencies were analyzed. In this study, an Artificial Neural Network (ANN) prediction model was employed. According to the study results, it is estimated that Chinese Yuan meets the specified criteria and has the potential to become a strong currency in the future. Additionally, the study predicts that the United States will maintain its status as a strong reserve currency in the future but could lose its strength based on the specified criteria. Germany and the United Kingdom are expected to perform weakly according to the specified criteria.

Ethical Statement

Araştırma makalesinin hazırlanmasında bütün etik kurallara uyulmuştur.

Supporting Institution

yok

References

  • Alp, A., Kılıç, S., & Gönülalçak, H. (2020). An empirical study on the future of reserve currencies. Journal of Social Sciences, 5(1).
  • Aydın, Ö. (2019). Inflation forecasting with artificial neural networks. Master's thesis, Beykent University, Institute of Science and Technology, Istanbul.
  • Bonpasse, M. (2008). The single global currency common cents for the world. September 9, 2023 http://www.singleglobalcurrency.org/documents/ecopyno15forfreeunlimiteddistribnpdf accessed from the address.
  • Chin, M., & Frankel, J. (2005). Will the euro eventually surpass the dollar as a leading international reserve currency. NBER Bureau Economic Research Working Papers, 11 (2), 11-12.
  • Chinn, M., & Frankel, J. (2005). Will the euro eventually surpass the dollars leading international reserve currency?. NBER Working Paper Series, 2(4), 18.
  • Cohen, B. (2019). Monetary rivalry and geopolitical ambition. USA: The University of Chicago Publications.
  • Elmas, Ç. (2003). Artifical neural networks (theory, architecture, training, application). İstanbul: Seçkin Publishing, 42.
  • Erilli, A., Eğrioğlu, E., Yolcu, U., Aladağ, H., & Uslu, R. (2010). Prediction of ınflation in Turkey using a hybrid aproach of forward and backward feed artifical neural networks. Doğuş University Journal, 11 (1), 29.
  • Fischer, S. (1993). The role of macroeconomic factors in growth. NBER Working Paper Series, 1, 4.
  • Haykin, S. (1999). Neural networks: a comprehensive foundation. second edition, New Jersey: Prentice Hall.
  • Helleiner, E. (2008). Political determinants of international currencies: what future for the us dollar?. Review of International Political Economy, 15 (3), 14-15.
  • IMF. (2022). United Kingdom data. September 9, 2023 https://www.imf.org/en/Search accessed from the address.
  • IMF. (2022). Global economic reports. September 9, 2023 https://www.imf.org/en/search accessed from the address.
  • Junoh, M. (2004). Predicting GDP in Malaysia using knowledge-based economy indicators: a comprassion between nural network and econometric aproach. Sunway Academic Journal, 1, 39-50.
  • Krugman, P. R. (1984). The international role of the dollar: theory and prospect. Bilson, J., Martson (ed). Exchange rate theory and practice (pp. 261-278). USA: University of Chicago Press.
  • Li, Y. W. (2018). China’s financial opening coalition politics and policy changes. New York: Routledge Publishing.
  • Moore, B. J. (2004). A global currency economy. Journal of Post Keynesian Economics, 26 (4), 635.
  • Naugthon, B. (2007). The Chinese economy transitions and growth. Cambridge: The MIT Press Publishing.
  • Öztemel, E. (2006). Artifical neural Networks. Istanbul: Papatya Publishing, 29-30.
  • Özyılmaz, A. (2016). The effectiveness of coordination between monetary and fiscal policies on macroeconomic variables. Balkan and Near Eastern Journal of Social Sciences,2, 28.
  • Prasad, E. S. (2016). Gaining currency: the rise of Renminbi. US of America, Oxford University Press, 158.
  • Prasad, E. S. (2017). Gaining currency: the rise of Renminbi. US of America, Oxford University Press, 114-127.
  • Richardson, D. (2016). Guide to China-Hong Kong stock coonect. September 9, 2023 https://www.dorsey.com//media/files/asiapacific/dorsey_guide_hk_stock_connect_china_ equity_market.pdf?la=en accessed from the adress.
  • Rozhentsova, E. (2012). Alternative international currencies. Economic Annals, 57 (5), 32-33.
  • Seyidoğlu, H. (2003). International economics: theory, policy, and practice. Istanbul: Güzem Can Publishing.
  • Subramanian, A. (2011). Renminbi rules: the conditional imminence of the reserve currency transition. Peterson Institute for International Economics Working Paper, 1, 4-6.
  • Tatlıyer, M. (2019). What will replace the dollar in a multipolar world. SETA, 1(2), 12.
  • TCMB. (2019). 100 questions on central banking. September 9, 2023 https://www.tcmb.gov.tr accessed from the adress.
  • Tektaş, A., & Karataş, A. (2004). Application of artifical neural networks to finance: stock price prediction. Atatürk Univesity Journal of Economics and Administrative Sciences, 18 (4), 14.
  • Tkacz, G. (2011). Neural network forecasting of Canadian GDP growth. International Journal of Forecasting, 17 (1), 38-42.
  • World Bank. (2022). Data. September 9, 2023 https://databank.worldbank.org/ accessed from the adress.
  • Wu, J., Yingli, P., & Zhu, Q. (2014). The conditions and potential of rmb as an international reserve: the empirical evidences from the history of eight major international reserve currencies. China Finance Review International, 4 (2).
  • Yurtoğlu, B. (2005). Founding family effects on business group growth: longitudinal evidence from Turkey. Long range Planing, 51 (6), 26.
  • Yüksek, A. G. (2007). Comparison of multiple regression analysis and artifical neural networks in air pollution prediction. Doctoral dissertation, Graduate Scholl of Social Sciences, Cumhuriyet University, Sivas, 11.
  • Zhang, S., & Chen, C. (2009). Township and village enterprises in China’s sustainable development in China. Area Studies-China, Regional Sustainable Development Review,3, 18-19.

INTERNATIONAL RESERVE CURRENCIES AND THE FUTURE OF THE CHINESE YUAN

Year 2023, , 812 - 846, 29.12.2023
https://doi.org/10.36543/kauiibfd.2023.033

Abstract

Bu çalışmanın amacı, rezerv paraya sahip ülkeler içinde Çin Yuan’ının gelecekte güçlü bir para birimi olma potansiyelini araştırmaktır. Çalışma için kullanılan GSYH (dünya payı), toplam rezervlerin ülke GSYH içindeki payları ve TÜFE değişkeni rezerv para kriterleri içerisinden seçilmiştir. Araştırma kapsamında analiz edilen ülkeler resmi olarak rezerv paraya sahiptirler. Çalışmada, Yapay Sinir Ağları (YSA) tahmin modeli kullanılmıştır. Çalışma sonuçlarına göre, Çin Yuan’ının belirlenen kriterleri karşıladığı ve gelecekte güçlü bir para olma potansiyeli taşıdığı tahmin edilmiştir. Ayrıca çalışmada, ABD’nin gelecekte güçlü bir rezerv para olarak varlığını sürdüreceği, ancak bu gücünü belirlenen kriterlere göre kaybedebileceği öngörülmektedir. Almanya ve İngiltere’nin belirlenen kriterlerde zayıf kalacağı tahmin edilmiştir.

References

  • Alp, A., Kılıç, S., & Gönülalçak, H. (2020). An empirical study on the future of reserve currencies. Journal of Social Sciences, 5(1).
  • Aydın, Ö. (2019). Inflation forecasting with artificial neural networks. Master's thesis, Beykent University, Institute of Science and Technology, Istanbul.
  • Bonpasse, M. (2008). The single global currency common cents for the world. September 9, 2023 http://www.singleglobalcurrency.org/documents/ecopyno15forfreeunlimiteddistribnpdf accessed from the address.
  • Chin, M., & Frankel, J. (2005). Will the euro eventually surpass the dollar as a leading international reserve currency. NBER Bureau Economic Research Working Papers, 11 (2), 11-12.
  • Chinn, M., & Frankel, J. (2005). Will the euro eventually surpass the dollars leading international reserve currency?. NBER Working Paper Series, 2(4), 18.
  • Cohen, B. (2019). Monetary rivalry and geopolitical ambition. USA: The University of Chicago Publications.
  • Elmas, Ç. (2003). Artifical neural networks (theory, architecture, training, application). İstanbul: Seçkin Publishing, 42.
  • Erilli, A., Eğrioğlu, E., Yolcu, U., Aladağ, H., & Uslu, R. (2010). Prediction of ınflation in Turkey using a hybrid aproach of forward and backward feed artifical neural networks. Doğuş University Journal, 11 (1), 29.
  • Fischer, S. (1993). The role of macroeconomic factors in growth. NBER Working Paper Series, 1, 4.
  • Haykin, S. (1999). Neural networks: a comprehensive foundation. second edition, New Jersey: Prentice Hall.
  • Helleiner, E. (2008). Political determinants of international currencies: what future for the us dollar?. Review of International Political Economy, 15 (3), 14-15.
  • IMF. (2022). United Kingdom data. September 9, 2023 https://www.imf.org/en/Search accessed from the address.
  • IMF. (2022). Global economic reports. September 9, 2023 https://www.imf.org/en/search accessed from the address.
  • Junoh, M. (2004). Predicting GDP in Malaysia using knowledge-based economy indicators: a comprassion between nural network and econometric aproach. Sunway Academic Journal, 1, 39-50.
  • Krugman, P. R. (1984). The international role of the dollar: theory and prospect. Bilson, J., Martson (ed). Exchange rate theory and practice (pp. 261-278). USA: University of Chicago Press.
  • Li, Y. W. (2018). China’s financial opening coalition politics and policy changes. New York: Routledge Publishing.
  • Moore, B. J. (2004). A global currency economy. Journal of Post Keynesian Economics, 26 (4), 635.
  • Naugthon, B. (2007). The Chinese economy transitions and growth. Cambridge: The MIT Press Publishing.
  • Öztemel, E. (2006). Artifical neural Networks. Istanbul: Papatya Publishing, 29-30.
  • Özyılmaz, A. (2016). The effectiveness of coordination between monetary and fiscal policies on macroeconomic variables. Balkan and Near Eastern Journal of Social Sciences,2, 28.
  • Prasad, E. S. (2016). Gaining currency: the rise of Renminbi. US of America, Oxford University Press, 158.
  • Prasad, E. S. (2017). Gaining currency: the rise of Renminbi. US of America, Oxford University Press, 114-127.
  • Richardson, D. (2016). Guide to China-Hong Kong stock coonect. September 9, 2023 https://www.dorsey.com//media/files/asiapacific/dorsey_guide_hk_stock_connect_china_ equity_market.pdf?la=en accessed from the adress.
  • Rozhentsova, E. (2012). Alternative international currencies. Economic Annals, 57 (5), 32-33.
  • Seyidoğlu, H. (2003). International economics: theory, policy, and practice. Istanbul: Güzem Can Publishing.
  • Subramanian, A. (2011). Renminbi rules: the conditional imminence of the reserve currency transition. Peterson Institute for International Economics Working Paper, 1, 4-6.
  • Tatlıyer, M. (2019). What will replace the dollar in a multipolar world. SETA, 1(2), 12.
  • TCMB. (2019). 100 questions on central banking. September 9, 2023 https://www.tcmb.gov.tr accessed from the adress.
  • Tektaş, A., & Karataş, A. (2004). Application of artifical neural networks to finance: stock price prediction. Atatürk Univesity Journal of Economics and Administrative Sciences, 18 (4), 14.
  • Tkacz, G. (2011). Neural network forecasting of Canadian GDP growth. International Journal of Forecasting, 17 (1), 38-42.
  • World Bank. (2022). Data. September 9, 2023 https://databank.worldbank.org/ accessed from the adress.
  • Wu, J., Yingli, P., & Zhu, Q. (2014). The conditions and potential of rmb as an international reserve: the empirical evidences from the history of eight major international reserve currencies. China Finance Review International, 4 (2).
  • Yurtoğlu, B. (2005). Founding family effects on business group growth: longitudinal evidence from Turkey. Long range Planing, 51 (6), 26.
  • Yüksek, A. G. (2007). Comparison of multiple regression analysis and artifical neural networks in air pollution prediction. Doctoral dissertation, Graduate Scholl of Social Sciences, Cumhuriyet University, Sivas, 11.
  • Zhang, S., & Chen, C. (2009). Township and village enterprises in China’s sustainable development in China. Area Studies-China, Regional Sustainable Development Review,3, 18-19.
There are 35 citations in total.

Details

Primary Language English
Subjects Monetary Policy
Journal Section Articles
Authors

Ayvaz Bartik 0000-0003-2856-5137

Kerem Karabulut 0000-0002-3159-3289

Publication Date December 29, 2023
Submission Date October 11, 2023
Acceptance Date December 11, 2023
Published in Issue Year 2023

Cite

APA Bartik, A., & Karabulut, K. (2023). INTERNATIONAL RESERVE CURRENCIES AND THE FUTURE OF THE CHINESE YUAN. Kafkas Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 14(28), 812-846. https://doi.org/10.36543/kauiibfd.2023.033

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