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Tax Arrears Versus Financial Ratios in Bankruptcy Prediction

Author

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  • Oliver Lukason

    (Faculty of Economics and Business Administration, University of Tartu, Liivi 4, 50409 Tartu, Estonia)

  • Art Andresson

    (Faculty of Economics and Business Administration, University of Tartu, Liivi 4, 50409 Tartu, Estonia)

Abstract

This paper aims to compare the usefulness of tax arrears and financial ratios in bankruptcy prediction. The analysis is based on the whole population of Estonian bankrupted and survived SMEs from 2013 to 2017. Logistic regression and multilayer perceptron are used as the prediction methods. The results indicate that closer to bankruptcy, tax arrears’ information yields a higher prediction accuracy than financial ratios. A combined model of tax arrears and financial ratios is more useful than the individual models. The results enable us to outline several theoretical and practical implications.

Suggested Citation

  • Oliver Lukason & Art Andresson, 2019. "Tax Arrears Versus Financial Ratios in Bankruptcy Prediction," JRFM, MDPI, vol. 12(4), pages 1-13, December.
    • Handle: RePEc:gam:jjrfmx:v:12:y:2019:i:4:p:187-:d:296570
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    References listed on IDEAS

    as
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    Cited by:

    1. Theodore Metaxas & Athanasios Romanopoulos, 2023. "A Literature Review on the Financial Determinants of Hotel Default," JRFM, MDPI, vol. 16(7), pages 1-19, July.
    2. Oliver Lukason & María-del-Mar Camacho-Miñano, 2021. "What Best Explains Reporting Delays? A SME Population Level Study of Different Factors," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    3. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.
    4. Youssef Zizi & Amine Jamali-Alaoui & Badreddine El Goumi & Mohamed Oudgou & Abdeslam El Moudden, 2021. "An Optimal Model of Financial Distress Prediction: A Comparative Study between Neural Networks and Logistic Regression," Risks, MDPI, vol. 9(11), pages 1-24, November.
    5. Keijo Kohv & Oliver Lukason, 2021. "What Best Predicts Corporate Bank Loan Defaults? An Analysis of Three Different Variable Domains," Risks, MDPI, vol. 9(2), pages 1-19, January.
    6. Oliver Lukason & Germo Valgenberg, 2021. "Failure Prediction in the Condition of Information Asymmetry: Tax Arrears as a Substitute When Financial Ratios Are Outdated," JRFM, MDPI, vol. 14(10), pages 1-13, October.
    7. Õie Renata Siimon & Oliver Lukason, 2021. "A Decision Support System for Corporate Tax Arrears Prediction," Sustainability, MDPI, vol. 13(15), pages 1-23, July.
    8. Dorohan-Pysarenko, Liudmyla & Rębilas, Rafał & Yehorova, Olena & Yasnolob, Ilona & Kononenko, Zhanna, 2021. "Methodological peculiarities of probability estimation of bankruptcy of agrarian enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 7(2), June.

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