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


  • Madalina Ecaterina Popescu
  • Victor Dragotă


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, University of Economics, Prague, vol. 2018(6), pages 637-653.
  • Handle: RePEc:prg:jnlpep:v:2018:y:2018:i:6:id:664:p:637-653

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    References listed on IDEAS

    1. Mãdãlina Ecaterina POPESCU, 2015. "Proposal for a Decision Support System to Predict Financial Distress," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 16(1), pages 112-118, March.
    2. Stephen A. Ross, 1977. "The Determination of Financial Structure: The Incentive-Signalling Approach," Bell Journal of Economics, The RAND Corporation, vol. 8(1), pages 23-40, Spring.
    3. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    4. Liviu Tudor & Mădălina Ecaterina Popescu & Marin Andreica, 2015. "A Decision Support System to Predict Financial Distress. The Case Of Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 170-179, December.
    5. Elisabeta Jaba & Ioan-Bogdan Robu & Costel Istrate & Christiana Brigitte Balan & Mihai Roman, 2016. "Statistical Assessment of the Value Relevance of Financial Information Reported by Romanian Listed Companies," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 27-42, June.
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    More about this item


    financial distress; predictors; prediction models; post-communist countries; CHAID decision trees; neural networks;

    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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