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Hunting the Living Dead A “Peso Problem” in Corporate Liabilities Data

Author

Listed:
  • Matteo Manera

    (University of Milan-Bicocca and Fondazione Eni Enrico Mattei)

  • Umberto Cherubini

    (University of Bologna)

Abstract

Recent literature has pointed out that information asymmetries may be the reason for the poor performance of structural credit risk models to fit corporate bond data. It is well known in fact that these models lead to a strong understatement of the credit spread terms structure, particularly on the short maturity end. Possible explanations stem from strategic debt service behavior and, as discovered more recently, the problem of accounting transparency. This raises the possibility that some of these flaws could be reconducted to a sort of “peso problem”, i.e. that the market may ask for a premium in order to allow for a small probability that accounting data may actually be biased (Baglioni and Cherubini, 2005). In this paper we propose a modified version of the Duan (1994,2000) MLE approach to structural models estimation in order to allow for this “peso problem” effect. The model is estimated for the Parmalat case, one of the most famous cases of accounting opacity, using both equity and CDS data.

Suggested Citation

  • Matteo Manera & Umberto Cherubini, 2005. "Hunting the Living Dead A “Peso Problem” in Corporate Liabilities Data," Working Papers 2005.76, Fondazione Eni Enrico Mattei.
    • Handle: RePEc:fem:femwpa:2005.76
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    More about this item

    Keywords

    Credit risk; Corporate debt; Peso problem; Maximum likelihood; Transformed data;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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