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Parsimonious Models of Financial Insolvency in Small Companies

Author

Listed:
  • Julio Pindado
  • Luis F. Rodrigues

Abstract

This study is an extension of current research on insolvency diagnosis. We intend to demonstrate that in small firms, the relevant information for the preventive diagnosis of insolvency can be synthesised in a model built upon a more reduced number of economic and financial ratios than the ones generally used in this kind of study. Our approach produces parsimonious models that can extract information from publicly available accounting-financial data. We demonstrate that using an extensive exploratory stage that will monitor the effects of correlation between financial variables, we will be able to build relatively stable models with a small set of variables.

Suggested Citation

  • Julio Pindado & Luis F. Rodrigues, 2004. "Parsimonious Models of Financial Insolvency in Small Companies," Small Business Economics, Springer, vol. 22(1), pages 51-66, February.
    • Handle: RePEc:kap:sbusec:v:22:y:2004:i:1:p:51-66
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    Citations

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    Cited by:

    1. Pindado, Julio & Rodrigues, Luis & de la Torre, Chabela, 2008. "How do insolvency codes affect a firm's investment?," International Review of Law and Economics, Elsevier, vol. 28(4), pages 227-238, December.
    2. Julio Pindado & Luis Rodrigues, 2005. "Determinants of Financial Distress Costs," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 19(4), pages 343-359, December.
    3. Pindado, Julio & Rodrigues, Luis & de la Torre, Chabela, 2008. "Estimating financial distress likelihood," Journal of Business Research, Elsevier, vol. 61(9), pages 995-1003, September.
    4. Mselmi, Nada & Lahiani, Amine & Hamza, Taher, 2017. "Financial distress prediction: The case of French small and medium-sized firms," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 67-80.
    5. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    6. Jones, Stewart & Wang, Tim, 2019. "Predicting private company failure: A multi-class analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 161-188.
    7. Atanas Delev, 2016. "Issues and Challenges for Bankruptcy Risk Assessment in Bulgarian Companies," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 3, pages 118-136.
    8. Sami BEN JABEUR & Youssef FAHMI & Abdellatif TAGHZOUTI & Hicham SADOK, 2014. "La défaillance des entreprises: une revue de littérature," Working Papers 2014-315, Department of Research, Ipag Business School.
    9. Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
    10. Francesco Ciampi & Valentina Cillo & Fabio Fiano, 2020. "Combining Kohonen maps and prior payment behavior for small enterprise default prediction," Small Business Economics, Springer, vol. 54(4), pages 1007-1039, April.
    11. Domingo Soriano & Gary Castrogiovanni, 2012. "The impact of education, experience and inner circle advisors on SME performance: insights from a study of public development centers," Small Business Economics, Springer, vol. 38(3), pages 333-349, April.

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