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Investigating asymmetries in the bank lending channel. An analysis using Austrian banks’ balance sheet data

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Abstract

In the present paper we use a balanced bank panel data set to obtain an inference on two dimensions of the asymmetric response of bank lending to interest rate changes. The cross-sectional dimension is captured by group-specific parameters whereby each bank’s group membership is estimated along with the model parameters. Moreover, the asymmetric response over time is modelled with switching parameters that depend on a latent state variable. The presence of two latent indicators calls for Bayesian simulation methods. The results show that three bank groups, characterized by the groups' average asset total, differ in their lending reaction to interest rate changes. Some sensitivity analysis comparing the results for different group specifications and the models' out-of-sample forecasting performance confirms our model specification.

Suggested Citation

  • Sylvia Fruehwirth-Schnatter & Sylvia Kaufmann, 2003. "Investigating asymmetries in the bank lending channel. An analysis using Austrian banks’ balance sheet data," Working Papers 85, Oesterreichische Nationalbank (Austrian Central Bank).
  • Handle: RePEc:onb:oenbwp:85
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    References listed on IDEAS

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    1. Azariadis, Costas & Smith, Bruce, 1998. "Financial Intermediation and Regime Switching in Business Cycles," American Economic Review, American Economic Association, vol. 88(3), pages 516-536, June.
    2. Kashyap, Anil K. & Stein, Jeremy C., 1995. "The impact of monetary policy on bank balance sheets," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 42(1), pages 151-195, June.
    3. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August.
    4. Francesco Giavazzi, 1999. "The Transmission Mechanism of Monetary Policy in Europe: Evidence from Banks’ Balance Sheets," Working papers 99-20, Massachusetts Institute of Technology (MIT), Department of Economics.
    5. Asea, Patrick K. & Blomberg, Brock, 1998. "Lending cycles," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 89-128.
    6. Jeremy C. Stein & Anil K. Kashyap, 2000. "What Do a Million Observations on Banks Say about the Transmission of Monetary Policy?," American Economic Review, American Economic Association, vol. 90(3), pages 407-428, June.
    7. G.J. De Bondt, 1999. "Banks and monetary transmission in Europe: empirical evidence," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 52(209), pages 149-168.
    8. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    9. Anil K. Kashyap & Jeremy C. Stein, 1997. "What Do a Million Banks Have to Say About the Transmission of Monetary Policy?," NBER Working Papers 6056, National Bureau of Economic Research, Inc.
    10. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
    11. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
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    Cited by:

    1. Maria Teresa VALDERRAMA & Sylvia KAUFMANN, "undated". "Modeling Credit Aggregates," EcoMod2004 330600146, EcoMod.
    2. Werner Hölzl & Sögner Leopold, 2004. "Entry and Exit Dynamics in Austrian Manufacturing," Working Papers geewp36, Vienna University of Economics and Business Research Group: Growth and Employment in Europe: Sustainability and Competitiveness.

    More about this item

    Keywords

    Bank lending; clustering; forecasting; Markov switching; Markov chain Monte Carlo; panel data.;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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