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New approaches for the financial distress classification in agribusiness

Author

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  • Jan Vavřina

    (Department of Business Economics, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic)

  • David Hampel

    (Department of Statistics and Operation Analysis, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic)

  • Jitka Janová

    (Department of Statistics and Operation Analysis, Mendel University in Brno, Zemědělská 1, 613 00 Brno, Czech Republic)

Abstract

After the recent financial crisis the need for unchallenged tools evaluating the financial health of enterprises has even arisen. Apart from well-known techniques such as Z-score and logit models, a new approaches were suggested, namely the data envelopment analysis (DEA) reformulation for bankruptcy prediction and production function-based economic performance evaluation (PFEP). Being recently suggested, these techniques have not yet been validated for common use in financial sector, although as for DEA approach some introductory studies are available for manufacturing and IT industry. In this contribution we focus on the thorough validation calculations that evaluate these techniques for the specific agribusiness industry. To keep the data as homogeneous as possible we limit the choice of agribusiness companies onto the area of the countries of Visegrad Group. The extensive data set covering several hundreds of enterprises were collected employing the database Amadeus of Bureau van Dijk. We present the validation results for each of the four mentioned methods, outline the strengths and weaknesses of each approach and discuss the valid suggestions for the effective detection of financial problems in the specific branch of agribusiness.

Suggested Citation

  • Jan Vavřina & David Hampel & Jitka Janová, 2013. "New approaches for the financial distress classification in agribusiness," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 61(4), pages 1177-1182.
  • Handle: RePEc:mup:actaun:actaun_2013061041177
    DOI: 10.11118/actaun201361041177
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    References listed on IDEAS

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    1. Premachandra, I.M. & Bhabra, Gurmeet Singh & Sueyoshi, Toshiyuki, 2009. "DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique," European Journal of Operational Research, Elsevier, vol. 193(2), pages 412-424, March.
    2. Yang, Z. R. & Platt, Marjorie B. & Platt, Harlan D., 1999. "Probabilistic Neural Networks in Bankruptcy Prediction," Journal of Business Research, Elsevier, vol. 44(2), pages 67-74, February.
    3. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    4. 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.
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    Cited by:

    1. Kavčáková, Michaela & Kočišová, Kristína, 2020. "Using Data Envelopment Analysis in Credit Risk Evaluation of ICT Companies," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 10(3), December.
    2. Mário S. Céu & Raquel M. Gaspar, 2023. "Financial Distress in European Vineyards and Olive Groves," Working Papers REM 2023/0266, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    3. Kristína Kočišová & Iveta Palečková, 2017. "The Super-efficiency Model and its Use for Ranking and Identification of Outliers," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(4), pages 1371-1382.
    4. Václav KLEPAC & David HAMPEL, 2017. "Predicting financial distress of agriculture companies in EU," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(8), pages 347-355.

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