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Global Economic Policy Uncertainty (GEPU) and Non-Performing Loans (NPL) in Iran's Banking System: Dynamic Correlation using the DCC-GARCH Approach

Author

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  • Botshekan , Mohammad Hashem

    (Finance and Banking Department, Management and Accounting Faculty, Allameh Tabataba'i University)

  • Takaloo , Amir

    (Management and Accounting Faculty, Allameh Tabataba'i University)

  • H. soureh , Reza

    (Finance and Banking Department, Management and Accounting Faculty, Allameh Tabataba'i University)

  • Abdollahi Poor , Mohammad Sadegh

    (Finance and Banking Department, Management and Accounting Faculty, Allameh Tabataba'i University)

Abstract

The aim of this article is to investigate the dynamic correlation between the Global Economic Policy Uncertainty index (GEPU) and Non-Performing Loans (NPL) in Iran. The relationship between economic uncertainty and banking performance indices is significant because of the systemic importance of banks in every economy. We evaluated this relationship in this developing country, especially under economic sanctions. In this study, we used the Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) to assess the relationship between Global Economic Policy Uncertainty and Non-Performing Loans of Iranian banks using the statistics of these two indicators by R and Eviews programming and statistical software in the period from 2004 to 2021. Our results show that Iranian banks' Non-Performing Loans (NPL) are rather associated with Global Economic Policy Uncertainty (GEPU) during major global shocks such as the global financial crisis in 2008 or the Covid-19 pandemic. However, despite fluctuations in the correlation between Non-Performing Loans and Global Economic Policy Uncertainty over time, this study also illustrates that these correlations in some periods are generally somewhat low that some of the reasons could be the sanctions imposed on Iran's economy and banking system, imposed loans to banks by the government, forced interest rate, etc., which led to a limited connection among Iranian banks and global banking system. To prove this claim we estimate the model for some countries with an open economy, like Japan, Singapore, the US, Turkey, and Spain. The result shows that this correlation is much higher in comparison to Iran.

Suggested Citation

  • Botshekan , Mohammad Hashem & Takaloo , Amir & H. soureh , Reza & Abdollahi Poor , Mohammad Sadegh, 2021. "Global Economic Policy Uncertainty (GEPU) and Non-Performing Loans (NPL) in Iran's Banking System: Dynamic Correlation using the DCC-GARCH Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(2), pages 187-212, June.
  • Handle: RePEc:mbr:jmonec:v:16:y:2021:i:2:p:187-212
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    References listed on IDEAS

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    Cited by:

    1. Salim Hamza Ringim & Abdulkareem Alhassan & Hasan Güngör & Festus Victor Bekun, 2022. "Economic Policy Uncertainty and Energy Prices: Empirical Evidence from Multivariate DCC-GARCH Models," Energies, MDPI, vol. 15(10), pages 1-18, May.
    2. Pejman Peykani & Mostafa Sargolzaei & Mohammad Hashem Botshekan & Camelia Oprean-Stan & Amir Takaloo, 2023. "Optimization of Asset and Liability Management of Banks with Minimum Possible Changes," Mathematics, MDPI, vol. 11(12), pages 1-24, June.
    3. Pejman Peykani & Mostafa Sargolzaei & Amir Takaloo & Shahla Valizadeh, 2023. "The Effects of Monetary Policy on Macroeconomic Variables through Credit and Balance Sheet Channels: A Dynamic Stochastic General Equilibrium Approach," Sustainability, MDPI, vol. 15(5), pages 1-21, March.

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    More about this item

    Keywords

    Global Economic Policy Uncertainty (GEPU); Non-Performing Loans (NPL); DCC-GARCH; Banks.;
    All these keywords.

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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