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A forward-looking model for time-varying capital requirements and the New Basel Capital Accord

Author

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  • Costanza Torricelli

    ()

  • Chiara Pederzoli

    ()

Abstract

This paper proposes a forward-looking model for time-varying capital requirements which finds application within the New Basel Capital Accord (NBCA) framework. The model aims at reconciling two somewhat contrasting objectives of the NBCA proposal: introducing risk-sensitive capital requirements and avoiding at the same time procyclical effects. The model rests on the relationship existing between default rates and the business cycle phases and proposes a modelisation of the default probabilities which is based on a business cycle forecast over the credit horizon. The model is applied to US data over the forecasting period 1971-2002: despite a failure in predicting the early nineties recession, the objective of raising the capital requirements in anticipation of a recessions is in general satisfied. The results obtained are interesting as they suggest that there is room for dampening procyclicality of capital requirements even within a risk-sensitive framework.

Suggested Citation

  • Costanza Torricelli & Chiara Pederzoli, 2004. "A forward-looking model for time-varying capital requirements and the New Basel Capital Accord," Department of Economics 0453, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
  • Handle: RePEc:mod:depeco:0453
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    Keywords

    capital requirement; default probability; business cycle; procyclicality;

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • 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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