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Bootstrap Algorithms for Risk Models with Auxiliary Variable and Complex Samples

Author

Listed:
  • Giancarlo Manzi

    (University of Milan)

  • Fulvia Mecatti

    (University of Milan–Bicocca)

Abstract

Resampling methods are often invoked in risk modelling when the stability of estimators of model parameters has to be assessed. The accuracy of variance estimates is crucial since the operational risk management affects strategies, decisions and policies. However, auxiliary variables and the complexity of the sampling design are seldom taken into proper account in variance estimation. In this paper bootstrap algorithms for finite population sampling are proposed in presence of an auxiliary variable and of complex samples. Results from a simulation study exploring the empirical performance of some bootstrap algorithms are presented.

Suggested Citation

  • Giancarlo Manzi & Fulvia Mecatti, 2009. "Bootstrap Algorithms for Risk Models with Auxiliary Variable and Complex Samples," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 21-27, March.
    • Handle: RePEc:spr:metcap:v:11:y:2009:i:1:d:10.1007_s11009-008-9072-8
    DOI: 10.1007/s11009-008-9072-8
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    References listed on IDEAS

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    1. de Fontnouvelle, Patrick & Dejesus-Rueff, Virginia & Jordan, John S. & Rosengren, Eric S., 2006. "Capital and Risk: New Evidence on Implications of Large Operational Losses," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(7), pages 1819-1846, October.
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    More about this item

    Keywords

    Probability-proportional-to-size sampling; Ratio model; Ratio estimator; Regression estimator; Resampling methods;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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