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Bankruptcy risk and productive efficiency in manufacturing firms


  • Becchetti, Leonardo
  • Sierra, Jaime


The paper investigates the determinants of bankruptcy in three representative unbalanced samples of Italian firms for the periods 1989-1991, 1992-94 and 1995-97. Two important results are that: i) the degree of relative firm inefficiency measured as the distance from the efficient frontier has significant explanatory power in predicting bankruptcy ii) qualitative regressors such as customers' concentration and strength and proximity of competitors have significant predictive power and suggest that banks should not restrict their monitoring activity to balance sheet variables. These findings remain significant after controlling for balance sheet liquidity and profitability variables usually considered in these estimates
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  • 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.
  • Handle: RePEc:eee:jbfina:v:27:y:2003:i:11:p:2099-2120

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    Cited by:

    1. Marco Bisogno, 2012. "The Accessibility Of The Italian Bankruptcy Procedures: An Empirical Analysis," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 2(2), pages 1-24, December.
    2. Ruey-Ching Hwang & Jhao-Siang Siao & Huimin Chung & C. Chu, 2011. "Assessing bankruptcy prediction models via information content of technical inefficiency," Journal of Productivity Analysis, Springer, vol. 36(3), pages 263-273, December.
    3. Laura Nuñez, 2004. "The problem of variable selection for financial distress: applying GRASP methaeuristics," Working Papers Economia wp04-30, Instituto de Empresa, Area of Economic Environment.
    4. Wu, Yueh-Cheng & Wei Kiong Ting, Irene & Lu, Wen-Min & Nourani, Mohammad & Kweh, Qian Long, 2016. "The impact of earnings management on the performance of ASEAN banks," Economic Modelling, Elsevier, vol. 53(C), pages 156-165.
    5. Sofie Balcaen & Sophie Manigart & Hubert Ooghe, 2011. "From distress to exit: determinants of the time to exit," Journal of Evolutionary Economics, Springer, vol. 21(3), pages 407-446, August.
    6. Ferreira Filipe, Sara & Grammatikos, Theoharry & Michala, Dimitra, 2014. "Forecasting Distress in European SME Portfolios," MPRA Paper 53572, University Library of Munich, Germany.
    7. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    8. Koetter, M. & Bos, J.W.B. & Heid, F. & Kolari, J.W. & Kool, C.J.M. & Porath, D., 2007. "Accounting for distress in bank mergers," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3200-3217, October.
    9. Guimarães Barbosa, Evaldo, 2016. "The relationships between, on the hand, size, growth and age of the firm and, on the other hand, small business survival – a constructive critique and a proposal of a new framework," MPRA Paper 72111, University Library of Munich, Germany.
    10. Sun, Wenbin & Cui, Kexiu, 2014. "Linking corporate social responsibility to firm default risk," European Management Journal, Elsevier, vol. 32(2), pages 275-287.
    11. repec:eee:spacre:v:15:y:2012:i:1:p:7-58 is not listed on IDEAS
    12. Piruna Polsiri & Kingkarn Sookhanaphibarn, 2009. "Corporate Distress Prediction Models Using Governance and Financial Variables: Evidence from Thai Listed Firms during the East Asian Economic Crisis," Journal of Economics and Management, College of Business, Feng Chia University, Taiwan, vol. 5(2), pages 273-304, July.
    13. Guimarães Barbosa, Evaldo, 2016. "Determinants of Small Business Survival: The Case of Very Small Enterprises of the Traditional Manufacturing Sectors in Brazil," MPRA Paper 72304, University Library of Munich, Germany.
    14. Mogilat , Anastasia & Ipatova, Irina, 2016. "Technical efficiency as a factor of Russian industrial companies’ risks of financial distress," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 42, pages 05-29.
    15. Chen, Tsung-Kang & Liao, Hsien-Hsing & Chen, Wei-Lun, 2014. "Production efficiency uncertainty and corporate credit risk: Structural form credit model perspectives," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 266-280.
    16. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    17. Steen Thomsen & Frederik Vinten, 2014. "Delistings and the costs of governance: a study of European stock exchanges 1996–2004," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 18(3), pages 793-833, August.
    18. Leonardo Becchetti & Melody Garcia & Giovanni Trovato, 2009. "Credit rationing and credit view: empirical evidence from loan data," CEIS Research Paper 144, Tor Vergata University, CEIS, revised 30 Sep 2009.
    19. Alessandro Zeli, 2014. "The financial distress indicators trend in Italy: an analysis of medium-size enterprises," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 4(2), pages 199-221, December.
    20. Filipe, Sara Ferreira & Grammatikos, Theoharry & Michala, Dimitra, 2016. "Forecasting distress in European SME portfolios," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 112-135.
    21. Gupta, Jairaj & Wilson, Nicholas & Gregoriou, Andros & Healy, Jerome, 2014. "The effect of internationalisation on modelling credit risk for SMEs: Evidence from UK market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 397-413.
    22. Psillaki, Maria & Tsolas, Ioannis E. & Margaritis, Dimitris, 2010. "Evaluation of credit risk based on firm performance," European Journal of Operational Research, Elsevier, vol. 201(3), pages 873-881, March.
    23. Ipatova, Irina & Peresetsky, Аnatoly, 2013. "Technical efficiency of Russian plastic and rubber production firms," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 32(4), pages 71-92.
    24. So Sohn & Yoon Kim, 2013. "Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking," Small Business Economics, Springer, vol. 41(4), pages 931-943, December.

    More about this item

    JEL classification:

    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory


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