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Predicting Bankruptcy Based On The Full Population Of Croatian Companies

Author

Listed:
  • SiniÅ¡a Bogdan

    (University of Rijeka, Faculty of Turism and Hospitality Management)

  • Luka Å ikić

    (University of Zagreb, Institute of Social Sciences Ivo Pilar)

  • Suzana BareÅ¡a

    (University of Rijeka, Faculty of Turism and Hospitality Management)

Abstract

This paper analyses the bankruptcy prediction based on the population of companies representative of the total business sector in Croatia. The representativity of the sample is achieved through the propensity score matching of the full population of bankrupt and similar non-bankrupt companies. The robust estimation of bankruptcy prediction is carried out through the multiple discriminant analysis (MDA) and logistic regression (logit). The results indicate high classification accuracy of both models, but more favourable performance of logit estimation. Overall accuracy of the MDA model was 73.7%, while the overall accuracy of the logit model was 76.3%. The results serve as a bankruptcy estimation benchmark for the business sector in Croatia.

Suggested Citation

  • SiniÅ¡a Bogdan & Luka Å ikić & Suzana BareÅ¡a, 2021. "Predicting Bankruptcy Based On The Full Population Of Croatian Companies," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), vol. 72(5), pages 643-669.
  • Handle: RePEc:hde:epregl:v:72:y:2021:i:5:p:643-669
    DOI: 10.32910/ep.72.5.1
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    More about this item

    Keywords

    multiple discriminant analysis; MDA; logistic regression; logit; financial ratios;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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