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Measuring Systemic Risk on Indonesia’s Banking System

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  • Mansur, Alfan

Abstract

Inter-connectedness is one important aspect of measuring the degree of systemic risk arising in the banking system. In this paper, this aspect together with the degree of commonality and volatility are measured using Principal Component Analysis (PCA), dynamic Granger causality tests and a Markov regime switching model. These measures can be used as leading indicators to detect pressures in the financial system, in particular, the banking system. There is evidence that the inter-connectedness level together with a degree of commonality and volatility among banks escalate substantially during the financial distress. It implies that less systemically important banks could become more important in the financial system during abnormal times. Therefore, the list of systemically important banks regulated in the Law on Prevention and Mitigation of Financial System Crisis (UU PPKSK) should be updated more frequently during the period of financial distress.

Suggested Citation

  • Mansur, Alfan, 2018. "Measuring Systemic Risk on Indonesia’s Banking System," MPRA Paper 93300, University Library of Munich, Germany, revised 12 Apr 2018.
  • Handle: RePEc:pra:mprapa:93300
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    File URL: https://mpra.ub.uni-muenchen.de/93300/1/MPRA_paper_93300.pdf
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    References listed on IDEAS

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    Cited by:

    1. Mansur, Alfan & Nizar, Muhammad Afdi, 2019. "Mengukur Perkembangan Sektor Keuangan di Indonesia dan Faktor – Faktor yang Mempengaruhi [Assessing the Measurement and Determinants of Financial Sector Development in Indonesia]," MPRA Paper 96265, University Library of Munich, Germany, revised 30 Sep 2019.

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    More about this item

    Keywords

    Inter-connectedness; systemic risk; Principal Component Analysis; Granger causality; regime switching.;
    All these keywords.

    JEL classification:

    • 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
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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