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Stress Test of Banks in India: A VAR Approach


  • Sreejata Banerjee

    (Madras School of Economics)

  • Divya Murali

    (Research Associate at Athenainfonomics)


Banking crisis have serious repercussion causing loss of household savings and decline in confidence and soundness in the banking sector. The present study is an attempt to analyze this aspect in light of the challenges of financial sector reforms faced by banks in India . Stress test of banks operating in India is undertaken to identify factors that adversely influence banks’ non-performing assets (NPA) which is the key indicator of banks’ soundness. We examine the response of bank’s NPA to unexpected shocks from external and domestic macroeconomic factors namely interest rate, exchange rate, GDP. NPAs are regressed in Vector Auto Regressive model on a set of macroeconomic variables with quarterly data from 1997 to 2012 to examine whether there is divergence in the response across the four types ownership: public, old private, new private, and foreign. Granger Causality, IRF and FEVD are used to verify the VAR results. Interest rate significantly impairs asset quality for all banks in two-way causality. Exchange rate, net foreign institutional investor flow and deposits Granger cause public banks’ NPA. GDP gap Granger cause NPA in old private and foreign banks. IRF show banks are vulnerable to inflation shock requiring 8 quarters to stabilize. The stress test clearly demonstrates that all banks need to re-capitalize and improve asset quality.

Suggested Citation

  • Sreejata Banerjee & Divya Murali, 2015. "Stress Test of Banks in India: A VAR Approach," Working Papers 2015-102, Madras School of Economics,Chennai,India.
  • Handle: RePEc:mad:wpaper:2015-102

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    References listed on IDEAS

    1. Glenn Hoggarth & Steffen Sorensen & Lea Zicchino, 2005. "Stress tests of UK banks using a VAR approach," Bank of England working papers 282, Bank of England.
    2. Basabi Bhattacharya & Tanima Niyogi Sinha Roy, 2008. "Macroeconomic Determinants of Asset Quality of Indian Public Sector Banks: A Recursive VAR Approach," The IUP Journal of Bank Management, IUP Publications, vol. 0(1), pages 20-40, February.
    3. Antonella Foglia, 2009. "Stress Testing Credit Risk: A Survey of Authorities' Aproaches," International Journal of Central Banking, International Journal of Central Banking, vol. 5(3), pages 9-45, September.
    4. Michael Boss & Gerald Krenn & Claus Puhr & Martin Summer, 2006. "Systemic Risk Monitor: A Model for Systemic Risk Analysis and Stress Testing of Banking Systems," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 11, pages 83-95.
    5. Jiménez, Gabriel & Mencía, Javier, 2009. "Modelling the distribution of credit losses with observable and latent factors," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 235-253, March.
    6. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    7. Jan Willem van den End & Marco Hoeberichts & Mostafa Tabbae, 2006. "Modelling Scenario Analysis and Macro Stress-testing," DNB Working Papers 119, Netherlands Central Bank, Research Department.
    8. Reinout De Bock & Alexander Demyanets, 2012. "Bank Asset Quality in Emerging Markets; Determinants and Spillovers," IMF Working Papers 12/71, International Monetary Fund.
    9. Marco Sorge, 2004. "Stress-testing financial systems: an overview of current methodologies," BIS Working Papers 165, Bank for International Settlements.
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    More about this item


    Macro Stress test; Non-performing Assets; Impulse response function; Vector Auto Regression; Granger Causality;

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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