Evaluation of the financial condition of companies after the announcement of arrangement bankruptcy: application of the classical and Bayesian logistic regression Cover Image

Evaluation of the financial condition of companies after the announcement of arrangement bankruptcy: application of the classical and Bayesian logistic regression
Evaluation of the financial condition of companies after the announcement of arrangement bankruptcy: application of the classical and Bayesian logistic regression

Author(s): Barbara Pawełek, Jadwiga Kostrzewska, Maciej Kostrzewski, Krzysztof Gałuszka
Subject(s): Economy, Socio-Economic Research
Published by: Główny Urząd Statystyczny
Keywords: company; arrangement bankruptcy; financial condition; Maximum Likelihood Method; Bayesian approach; logistic regression

Summary/Abstract: The aim of this paper is to present the results of an assessment of the financial condition of companies from the construction industry after the announcement of arrangement bankruptcy, in comparison to the condition of healthy companies. The logistic regression model estimated by means of the maximum likelihood method and the Bayesian approach were used. The first achievement of our study is the assessment of the financial condition of companies from the construction industry after the announcement of bankruptcy. The second achievement is the application of an approach combining the classical and Bayesian logistic regression models to assess the financial condition of companies in the years following the declaration of bankruptcy, and the presentation of the benefits of such a combination. The analysis described in the paper, carried out in most part by means of the ML logistic regression model, was supplemented with information yielded by the application of the Bayesian approach. In particular, the analysis of the shape of the posterior distribution of the repeat bankruptcy probability makes it possible, in some cases, to observe that the financial condition of a company is not clear, despite clear assessments made on the basis of the point estimations.

  • Issue Year: 67/2020
  • Issue No: 1
  • Page Range: 5-32
  • Page Count: 28
  • Language: English
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