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Modelli di scoring per il rischio paese
[Scoring models for country risk]

Author

Listed:
  • Doretti, Marco

Abstract

Country risk and sovereign risk are two of the most important topics in risk management. The first part of this work introduces these concepts and shows the differences between them. The following chapters fit linear and ordinal regression models to a data-set with more than 100 countries, where the response variable is an appropriate measure of their creditworthiness. The main purposes are to identify the most relevant explanatory variables and to make predictions for those countries whose response variable is not available. For the second aim it is important to verify that records with missing values are not systematically different from the complete ones: a Little test for the MCAR hypothesis is implemented. About model selection, ad hoc algorithms are used and the theory of reduction, proposed by David Hendry, is also briefly described.

Suggested Citation

  • Doretti, Marco, 2012. "Modelli di scoring per il rischio paese [Scoring models for country risk]," MPRA Paper 38898, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:38898
    as

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    References listed on IDEAS

    as
    1. Calzolari, Giorgio & Neri, Laura, 2002. "Imputation of continuous variables missing at random using the method of simulated scores," MPRA Paper 22986, University Library of Munich, Germany, revised 2002.
    2. Hendry, David F., 1995. "Dynamic Econometrics," OUP Catalogue, Oxford University Press, number 9780198283164.
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    More about this item

    Keywords

    country risk; sovereign risk; rating; MCAR; regression; scoring;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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