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Diagnosis of the Domino Effect in Bankruptcy Situations Through Positioning Maps and Their Evolution 10 Years Later

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Listed:
  • Josep Patau
  • Antonio Somoza
  • Salvador Torra

Abstract

This work aims to describe how the insolvency of a firm affects other business creditors. Through a sample of small and medium entities in Catalonia for the biennium 2004–2005, the situation of creditors before and after the legal event (insolvency proceedings) has been studied. The results confirm the existence of a substantial change in the composition of the financial structure of these firms (substitution of long-term debt by short-term debt; decrease in solvency and profitability, increase in financial charge, among others) and, therefore, the contagion of liquidity problems. The study covers 2 years before and after the insolvency and is dynamic in the sense that it highlights how the creditors change their source of finance and the ending situation. The main contributions of the object are the effect of insolvency on other companies closely related and also the technique used—multidimensional scaling.

Suggested Citation

  • Josep Patau & Antonio Somoza & Salvador Torra, 2020. "Diagnosis of the Domino Effect in Bankruptcy Situations Through Positioning Maps and Their Evolution 10 Years Later," SAGE Open, , vol. 10(4), pages 21582440209, December.
  • Handle: RePEc:sae:sagope:v:10:y:2020:i:4:p:2158244020965250
    DOI: 10.1177/2158244020965250
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    1. Beata Gavurova & Miroslava Packova & Maria Misankova & Lubos Smrcka, 2017. "Predictive potential and risks of selected bankruptcy prediction models in the Slovak business environment," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 18(6), pages 1156-1173, November.
    2. Becchetti, Leonardo & Sierra, Jaime, 2003. "Bankruptcy risk and productive efficiency in manufacturing firms," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2099-2120, November.
    3. J. Carroll & Jih-Jie Chang, 1970. "Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition," Psychometrika, Springer;The Psychometric Society, vol. 35(3), pages 283-319, September.
    4. 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.
    5. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    6. Libby, R, 1979. "Bankers And Auditors Perceptions Of The Message Communicated By The Audit Report," Journal of Accounting Research, Wiley Blackwell, vol. 17(1), pages 99-122.
    7. Joseph Kruskal, 1976. "More factors than subjects, tests and treatments: An indeterminacy theorem for canonical decomposition and individual differences scaling," Psychometrika, Springer;The Psychometric Society, vol. 41(3), pages 281-293, September.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    9. Green, Paul E & Maheshwari, Arun, 1969. "Common Stock Perception and Preference: An Application of Multidimensional Scaling," The Journal of Business, University of Chicago Press, vol. 42(4), pages 439-457, October.
    10. Johan Eklund & Nadine Levratto & Giovanni B. Ramello, 2020. "Entrepreneurship and failure: two sides of the same coin?," Small Business Economics, Springer, vol. 54(2), pages 373-382, February.
    11. Evi Neophytou & Cecilio Mar Molinero, 2004. "Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 677-710, June.
    12. Gabriel Jiménez & Jesús Saurina, 2006. "Credit Cycles, Credit Risk, and Prudential Regulation," International Journal of Central Banking, International Journal of Central Banking, vol. 2(2), May.
    13. Marti Sagarra & Cecilio Mar-Molinero & Miguel García-Cestona, 2015. "Spanish savings banks in the credit crunch: could distress have been predicted before the crisis? A multivariate statistical analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 21(3), pages 195-214, February.
    14. Marco Lamieri & Ilaria Sangalli, 2019. "The propagation of liquidity imbalances in manufacturing supply chains: evidence from a spatial auto-regressive approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1377-1401, October.
    15. Blum, M, 1974. "Failing Company Discriminant-Analysis," Journal of Accounting Research, Wiley Blackwell, vol. 12(1), pages 1-25.
    16. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    17. 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.
    18. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    19. Tor Jacobson & Erik Schedvin, 2015. "Trade Credit and the Propagation of Corporate Failure: An Empirical Analysis," Econometrica, Econometric Society, vol. 83(4), pages 1315-1371, July.
    20. Altman, Edward I., 1977. "Predicting performance in the savings and loan association industry," Journal of Monetary Economics, Elsevier, vol. 3(4), pages 443-466, October.
    21. Jacobson, Tor & von Schedvin, Erik, 2012. "Trade Credit and the Propagation of Corporate Failure: An Empirical Analysis," Working Paper Series 263, Sveriges Riksbank (Central Bank of Sweden).
    22. Evi Neophytou & Cecilio Mar Molinero, 2004. "Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5-6), pages 677-710.
    23. Pratt, J, 1982. "Post-Cognitive Structure - Its Determinants And Relationship To Perceived Information Use And Predictive Accuracy," Journal of Accounting Research, Wiley Blackwell, vol. 20(1), pages 189-209.
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