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Identifying VARs through Heterogeneity: An Application to Bank Runs

Author

Listed:
  • De Graeve, Ferre

    (Research Department, Central Bank of Sweden)

  • Karas, Alexei

    (Roosevelt Academy)

Abstract

We propose to incorporate cross-sectional heterogeneity into structural VARs. Heterogeneity provides an additional dimension along which one can identify structural shocks and perform hypothesis tests. We provide an application to bank runs, based on microeconomic deposit market data. We impose identification restrictions both in the cross-section (across insured and non-insured banks) and across variables (as in macro SVARs). We thus (i) identify bank runs, (ii) quantify the contribution of competing theories, and, (iii) evaluate policies such as deposit insurance. The application suggests substantial promise for the approach and has strong policy implications.

Suggested Citation

  • De Graeve, Ferre & Karas, Alexei, 2010. "Identifying VARs through Heterogeneity: An Application to Bank Runs," Working Paper Series 244, Sveriges Riksbank (Central Bank of Sweden).
    • Handle: RePEc:hhs:rbnkwp:0244
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    References listed on IDEAS

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    1. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Thomas J. Sargent & Mark W. Watson, 2007. "ABCs (and Ds) of Understanding VARs," American Economic Review, American Economic Association, vol. 97(3), pages 1021-1026, June.
    2. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    3. María Soledad Martínez-Peria & Sergio Schmukler, 2002. "Do Depositors Punish Banks for Bad Behavior? Market Discipline, Deposit Insurance, and Banking Crises," Central Banking, Analysis, and Economic Policies Book Series, in: Leonardo Hernández & Klaus Schmidt-Hebbel & Norman Loayza (Series Editor) & Klaus Schmidt-Hebbel (Se (ed.),Banking, Financial Integration, and International Crises, edition 1, volume 3, chapter 5, pages 143-174, Central Bank of Chile.
    4. Juan F. Rubio-Ramirez & Daniel F. Waggoner & Tao Zha, 2005. "Markov-switching structural vector autoregressions: theory and application," FRB Atlanta Working Paper 2005-27, Federal Reserve Bank of Atlanta.
    5. Demirguc-Kunt, Asli & Huizinga, Harry, 2004. "Market discipline and deposit insurance," Journal of Monetary Economics, Elsevier, vol. 51(2), pages 375-399, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Christian Matthes & Felipe Schwartzman, 2019. "The Demand Origins of Business Cycles," 2019 Meeting Papers 1122, Society for Economic Dynamics.
    2. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel vector autoregressive models: a survey," Working Paper Series 1507, European Central Bank.
    3. Peersman, G. & Wagner, W.B., 2014. "Shocks to Bank Lending, Risk-Taking, Securitization, and Their Role for U.S. Business Cycle Fluctuations," Discussion Paper 2014-019, Tilburg University, Center for Economic Research.
    4. Brown, Martin & Trautmann, Stefan T. & Vlahu, Razvan, 2012. "Contagious Bank Runs: Experimental Evidence," Working Papers on Finance 1207, University of St. Gallen, School of Finance.
    5. Papadamou, Stephanos & Sidiropoulos, Moïse & Spyromitros, Eleftherios, 2015. "Central bank transparency and the interest rate channel: Evidence from emerging economies," Economic Modelling, Elsevier, vol. 48(C), pages 167-174.
    6. Laura Liu & Christian Matthes & Katerina Petrova, 2022. "Monetary Policy Across Space and Time," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 37-64, Emerald Group Publishing Limited.
    7. Christian Matthes & Felipe Schwartzman, 2019. "What Do Sectoral Dynamics Tell Us About the Origins of Business Cycles?," Working Paper 19-9, Federal Reserve Bank of Richmond.
    8. Martin Brown & Stefan T. Trautmann & Razvan Vlahu, 2017. "Understanding Bank-Run Contagion," Management Science, INFORMS, vol. 63(7), pages 2272-2282, July.
    9. Solntsev, O. & Mamonov, M. & Pestova, A. & Magomedova, Z., 2011. "Experience in Developing Early Warning System for Financial Crises and the Forecast of Russian Banking Sector Dynamic in 2012," Journal of the New Economic Association, New Economic Association, issue 12, pages 41-76.

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    More about this item

    Keywords

    Identification; SVAR; panel-VAR; Heterogeneity; Bank run;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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