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What Do Post-Communist Countries Have in Common When Predicting Financial Distress?

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  • Madalina Ecaterina Popescu
  • Victor Dragotă

Abstract

Business failure prediction is an important issue in corporate finance. Different prediction models are proposed by financial theory and are often used in practice. Their application is effortless, selecting only few key inputs with the greatest informative power from the large list of possible indicators. Our paper identifies the financial distress predictors for 5 post-communist countries (Bulgaria, Croatia, the Czech Republic, Hungary and Romania) based on information collected from the Amadeus database for the period 2011-2013 using CHAID decision trees and neural networks. We propose a short list of indicators, which can offer a synthetic perspective on corporate distress risk, adapted for these countries. The best prediction models are substantially different from country to country: in the Czech Republic, Hungary and Romania the flow-approach indicators perform better, while in Bulgaria and Croatia - the stock-approach indicators. The results suggest that the extrapolation of such models from one country to another should be made cautiously. One interesting finding is the presence of the ratios per employee as predictors of financial distress.

Suggested Citation

  • Madalina Ecaterina Popescu & Victor Dragotă, 2018. "What Do Post-Communist Countries Have in Common When Predicting Financial Distress?," Prague Economic Papers, Prague University of Economics and Business, vol. 2018(6), pages 637-653.
    • Handle: RePEc:prg:jnlpep:v:2018:y:2018:i:6:id:664:p:637-653
    DOI: 10.18267/j.pep.664
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    Cited by:

    1. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.
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    3. Fernando Zambrano Farias & María del Carmen Valls Martínez & Pedro Antonio Martín-Cervantes, 2021. "Explanatory Factors of Business Failure: Literature Review and Global Trends," Sustainability, MDPI, vol. 13(18), pages 1-26, September.
    4. Katarina Valaskova & Pavol Durana & Peter Adamko & Jaroslav Jaros, 2020. "Financial Compass for Slovak Enterprises: Modeling Economic Stability of Agricultural Entities," JRFM, MDPI, vol. 13(5), pages 1-16, May.

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    More about this item

    Keywords

    financial distress; predictors; prediction models; post-communist countries; CHAID decision trees; neural networks;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

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