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Assessing Potential Financial Problems for Firms in Brazil

Author

Listed:
  • Edward I Altman

    (New York University)

  • Tara K N Baidya

    (Catholic University of Rio de Janeiro)

  • Luis Manoel Ribeiro Dias

    (Catholic University of Rio de Janeiro)

Abstract

This paper examines the recent business failure experience in Brazil and develops, tests and analyzes a quantitative model for classifying and predicting serious financial problems of companies. It utilizes a bankruptcy classification model developed by Altman (1968) in order to classify Brazilian firms during the period 1973 to 1976. A sample of 23 serious–problem firms is compared with a slightly larger control sample of healthy firms. A four–variable model successfully classified 88 percent of the firms one year prior to serious problems and as much as 78 percent three years prior. The importance of models that highlight financial problems early enough to suggest remedial changes is apparent in Brazil. For example an equilibrium situation between the domestic private sector, multinationals and public–owned firms is more likely to continue if weaker domestic firms can be helped and preserved. The application of such models by financial institutions and for financial market analysis is comparable to that in the United States and other developed countries. Finally, the paper explores the application of such models in developing countries.© 1979 JIBS. Journal of International Business Studies (1979) 10, 9–24

Suggested Citation

  • Edward I Altman & Tara K N Baidya & Luis Manoel Ribeiro Dias, 1979. "Assessing Potential Financial Problems for Firms in Brazil," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 10(2), pages 9-24, June.
  • Handle: RePEc:pal:jintbs:v:10:y:1979:i:2:p:9-24
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    Citations

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    Cited by:

    1. Tomasz Korol, 2018. "The Implementation of Fuzzy Logic in Forecasting Financial Ratios," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(2), June.
    2. Caro, Norma Patricia & Díaz, Margarita & Porporato, Marcela, 2013. "Predicción de quiebras empresariales en economías emergentes: uso de un modelo logístico mixto || Bankruptcy Prediction in Emerging Economies: Use of a Mixed Logistic Model," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 16(1), pages 200-215, December.
    3. Zherlitsyn, Dmytro & Levytskyi, Stanislav & Mykhailyk, Denys & Ogloblina, Victoriia, 2019. "Assessment of Financial Potential as a Determinant of Enterprise Development," MPRA Paper 97069, University Library of Munich, Germany.
    4. Tomasz Korol, 2020. "Assessment of Trajectories of Non-bankrupt and Bankrupt Enterprises," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1113-1135.
    5. 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.
    6. Lobna Abid & Afif Masmoudi & Sonia Zouari-Ghorbel, 2018. "The Consumer Loan’s Payment Default Predictive Model: an Application of the Logistic Regression and the Discriminant Analysis in a Tunisian Commercial Bank," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 948-962, September.
    7. Marcelo J. Braga & Valéria G. Fully Bressan & Enrico A. Colosimo & Aureliano A. Bressan, 2006. "Investigating the solvency of brazilian credit unions using a proportional hazard model," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 77(1), pages 83-106, March.
    8. repec:zbw:bofrdp:2008_015 is not listed on IDEAS
    9. Katia Rocha & Francisco A. Alcaraz Garcia, 2005. "Do Ranking das Distribuidoras ao risco de Crédito no Pool- A remuneração dos Investimentos em Geração Elétrica no Brasil," Discussion Papers 1086, Instituto de Pesquisa Econômica Aplicada - IPEA.
    10. Barboza, Flavio & Altman, Edward, 2024. "Predicting financial distress in Latin American companies: A comparative analysis of logistic regression and random forest models," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
    11. Becchetti, Leonardo & Castelli, Annalisa & Hasan, Iftekhar, 2008. "Investment-cash flow sensitivities, credit rationing and financing constraints," Bank of Finland Research Discussion Papers 15/2008, Bank of Finland.
    12. Tang, Ryan W. & Buckley, Peter J., 2022. "Outward foreign direct investment by emerging market multinationals: The directionality of institutional distance," Journal of Business Research, Elsevier, vol. 149(C), pages 314-326.
    13. Alexandra Horobet & Stefania Cristina Curea & Alexandra Smedoiu Popoviciu & Cosmin-Alin Botoroga & Lucian Belascu & Dan Gabriel Dumitrescu, 2021. "Solvency Risk and Corporate Performance: A Case Study on European Retailers," JRFM, MDPI, vol. 14(11), pages 1-34, November.
    14. Korol, Tomasz, 2013. "Early warning models against bankruptcy risk for Central European and Latin American enterprises," Economic Modelling, Elsevier, vol. 31(C), pages 22-30.
    15. Caro, Norma Patricia & Arias, Ver—nica & Ortiz, Pablo, 2017. "Predicci—n de fracaso en empresas latinoamericanas utilizando el mŽtodo del vecino más cercano para predecir efectos aleatorios en modelos mixtos || Prediction of Failure in Latin-American Companies U," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 5-24, Diciembre.
    16. Becchetti, Leonardo & Castelli, Annalisa & Hasan, Iftekhar, 2008. "Investment-cash flow sensitivities, credit rationing and financing constraints," Research Discussion Papers 15/2008, Bank of Finland.
    17. Erdely, Arturo, 2017. "Value at Risk and the Diversification Dogma || Valor en riesgo y el dogma de la diversificación," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 24(1), pages 209-219, Diciembre.
    18. K.K. Jain & P.K. Gupta & Sanjiv Mittal, 2011. "Logistic Predictive Model for SMEs Financing in India," Vision, , vol. 15(4), pages 331-346, December.
    19. repec:ath:journl:tome:34:v:2:y:2014:i:34:p:99-109 is not listed on IDEAS
    20. André Luiz de Souza Guimarães & Valcemiro Nossa, 2010. "Working capital, profitability, liquidity and solvency of healthcare insurance companies," Brazilian Business Review, Fucape Business School, vol. 7(2), pages 37-59, May.
    21. Leonardo Becchetti & Annalisa Castelli & Iftekhar Hasan, 2010. "Investment–cash flow sensitivities, credit rationing and financing constraints in small and medium-sized firms," Small Business Economics, Springer, vol. 35(4), pages 467-497, November.
    22. Rocha, Katia & Alcaraz Garcia, Francisco A., 2006. "Credit risk in the pool--implications for private capital investments in Brazilian power generation," Energy Policy, Elsevier, vol. 34(18), pages 3827-3835, December.
    23. Ashraf, Sumaira & Félix, Elisabete G.S. & Serrasqueiro, Zélia, 2020. "Development and testing of an augmented distress prediction model: A comparative study on a developed and an emerging market," Journal of Multinational Financial Management, Elsevier, vol. 57.

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