Journals / Uygulamalı Ekonomi ve Sosyal Bilimler Dergisi / 2021 / Cilt: 3 - Sayı: 2

AN INTERACTION BETWEEN BANKING SYSTEM LIQUIDITY AND MACROECONOMIC VARIABLES: A VECTOR ERROR CORRECTION APPROACH

BANKACILIK SİSTEMİ LİKİDİTESİ VE MAKROEKONOMİK DEĞİŞKENLER ARASINDAKİ ETKİLEŞİM: VEKTÖR HATA DÜZELTME YAKLAŞIMI

Pages
1–18
Publication Date
2021-09-25
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

As a result of this research, conducted with a data set covering the 2001-2019 period, it was found that there is a long-term relationship among banking sector liquidity, per capita income, interest rate and net foreign trade variables in Turkish Economy.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, it is aimed to examine the interaction between liquidity and various macroeconomic variables.
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Key Findings & Data:As a result of this research, conducted with a data set covering the 2001-2019 period, it was found that there is a long-term relationship among banking sector liquidity, per capita income, interest rate and net foreign trade variables in Turkish Economy.
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Conclusion & Impact:Short-term causality analysis results show that interest rate is the Granger cause of liquidity and liquidity is the Granger cause of per capita income.
🔬Design:Research Article
📍Scope:2001-2019 Verileri
⚙️Variables:Likidite · Finansal Kriz · Bankacılık Sektörü

Abstract

In this study, it is aimed to examine the interaction between liquidity and various macroeconomic variables. As a result of this research, conducted with a data set covering the 2001-2019 period, it was found that there is a long-term relationship among banking sector liquidity, per capita income, interest rate and net foreign trade variables in Turkish Economy. According to the findings of the VECM analysis, the error correction mechanism works and there is a one-way causality from per capita income, interest rate and net foreign trade to liquidity in the long run. Short-term causality analysis results show that interest rate is the Granger cause of liquidity and liquidity is the Granger cause of per capita income.

Özet

Bu araştırmada, likiditeyle çeşitli makro iktisadi değişkenler arasındaki etkileşimin incelenmesi amaçlanmaktadır. 2001-2019 dönemini kapsayan bir veri setiyle yapılan araştırmanın sonucunda Türkiye Ekonomisinde bankacılık sektörü likiditesi, kişi başı milli gelir, faiz ve net dış ticaret değişkenleri arasında uzun dönemli ilişki olduğuna dair bulgular elde edilmiştir. VECM analizi bulgularına göre hata düzeltme mekanizması çalışmaktadır ve uzun dönemde kişi başı milli gelir, faiz ve net dış ticaret değişkenlerinden likidite yönünde tek yönlü nedensellik ilişkisi mevcuttur. Kısa dönemli nedensellik analizi sonuçları ise faizin likiditenin Granger sebebi ve likiditenin de kişi başı milli gelirin Granger sebebi olduğunu göstermektedir.

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Cite This Article

KARABIYIK, C. (2021). AN INTERACTION BETWEEN BANKING SYSTEM LIQUIDITY AND MACROECONOMIC VARIABLES: A VECTOR ERROR CORRECTION APPROACH. Uygulamalı Ekonomi ve Sosyal Bilimler Dergisi, Cilt: 3 - Sayı: 2, 1–18. https://ajindex.com/articles/820942

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References (15)

  1. Akkaya, M., & Azimli, T. (2018). Türk bankacılık sektöründe likidite riski yönetimi. Finans Politik & Ekonomik Yorumlar, 55(638), 35–48.
  2. Al-Harbi, A. (2017). Determinants of banks liquidity: Evidence from OIC countries. Journal of Economic and Administrative Sciences. Vol. 33 No. 2, pp. 164-177.
  3. Ayaydın, H., & Karaaslan, İ. (2014). Likidite riski yönetimi: Türk Bankacilik Sektörü üzerine bir araştirma. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 5(11), 237–256.
  4. BBVA (2020). Country Risk Quarterly Report. Fourth Quarter 2019 (December 13). Banco Bilbao Vizcaya Argentaria. https://www.bbvaresearch.com/en/publicaciones/country-risk-annual-report-2020/
  5. BDDK (2019). 2019 Faaliyet Raporu. https://www.bddk.org.tr/ContentBddk/dokuman/hakkinda_0003_11.pd
  6. BDDK (2020). Türk Bankacılık Sektörü temel göstergeleri (Haziran). https://www.bddk.org.tr/ContentBddk/dokuman/veri_000014_61.pdf
  7. BIS. (2008). Principles for sound liquidity risk management and supervision. Bank for International Settlements. https://www.bis.org/publ/bcbs138.pdf
  8. BIS. (2009). International Framework for Liquidity Risk Measurement, Standards and Monitoring, December. Bank for International Settlements. Blackman, C. N. (1981). The Management of Foreign Exchange Reserves in Small Developing Countries. Social and Economic Studies, 156-171.
  9. Calvo, G. A., & Mendoza, E. G. (2000). Contagion, globalization, and the volatility of capital flows. İçinde Capital flows and the emerging economies: Theory, evidence, and controversies (ss. 15–41).
  10. University of Chicago Press.
  11. Çelik, S., & Akarım, Y. D. (2012). Likidite riski yönetimi: panel veri analizi ile İMKB bankacılık sektörü üzerine ampirik bir uygulama. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, 13(1), 1–17.
  12. Deep, A., & Schaefer, G. K. (2004). Are banks liquidity transformers? Deep, Akash and Schaefer, Guido K., Are Banks Liquidity Transformers? (May 2004). KSG Working Paper No. RWP04-022. Diamond, D. W., & Rajan, R. G. (2001). Liquidity risk, liquidity creation, and financial fragility: A theory of banking. Journal of political Economy, 109(2), 287–327.
  13. El Hamma, I., & Ejbari, A. (2013). Determinants of banking liquidity in South Mediterranean countries: The case of Morocco. In Financial Integration (ss. 159–171).
  14. Springer. El-Chaarani, H. (2019). Determinants of bank liquidity in the Middle East region. International Review of Management and Marketing, 9(2), 64-75.
  15. Engert, W., Selody, J., & Wilkins, C. (2008). Financ