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Predicting Bankruptcy in Pakistan

Author

Listed:
  • Abdul RASHID

    (International Islamic University (IIU), Islamabad)

  • Qaiser ABBAS

    (International Islamic University (IIU), Islamabad)

Abstract

This paper aims to identify the financial ratios that are most significant in bankruptcy prediction for the non-financial sector of Pakistan based on a sample of companies which became bankrupt over the time period 1996-2006. Twenty four financial ratios covering four important financial attributes, namely profitability, liquidity, leverage, and turnover ratios, were examined for a five-year period prior bankruptcy. The discriminant analysis produced a parsimonious model of three variables viz. sales to total assets, EBIT to current liabilities, and cash flow ratio. Our estimates provide evidence that the firms having Z-value below zero fall into the “bankrupt” whereas the firms with Z-value above zero fall into the “non-bankrupt” category. The model achieved 76.9% prediction accuracy when it is applied to forecast bankruptcies on the underlying sample.

Suggested Citation

  • Abdul RASHID & Qaiser ABBAS, 2011. "Predicting Bankruptcy in Pakistan," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(9(562)), pages 103-128, September.
    • Handle: RePEc:agr:journl:v:9(562):y:2011:i:9(562):p:103-128
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    Citations

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    Cited by:

    1. Šlefendorfas Gediminas, 2016. "Bankruptcy Prediction Model for Private Limited Companies of Lithuania," Ekonomika (Economics), Sciendo, vol. 95(1), pages 134-152, January.
    2. Shilpa H. Shetty & Theresa Nithila Vincent, 2021. "The Role of Board Independence and Ownership Structure in Improving the Efficacy of Corporate Financial Distress Prediction Model: Evidence from India," JRFM, MDPI, vol. 14(7), pages 1-13, July.
    3. Ijaz, Muhammad Shahzad & Hunjra, Ahmed Imran & Hameed, Zahid & Maqbool, Adnan & Azam, Rauf i, 2013. "Assessing the Financial Failure Using Z-Score and Current Ratio: A Case of Sugar Sector Listed Companies of Karachi Stock Exchange," MPRA Paper 60787, University Library of Munich, Germany.
    4. Atta Ullah & Chen Pinglu & Saif Ullah & Ningyu Qian & Mubasher Zaman, 2023. "Impact of intellectual capital efficiency on financial stability in banks: Insights from an emerging economy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1858-1871, April.
    5. Khushbu Agrawal, 2015. "Default Prediction Using Piotroski’s F-score," Global Business Review, International Management Institute, vol. 16(5_suppl), pages 175-186, October.
    6. Rubina Shaheen & Attiya Yasmin Javid, 2014. "Effect of Credit Rating on Firm Performance and Stock Return; Evidence form KSE Listed Firms," PIDE-Working Papers 2014:104, Pakistan Institute of Development Economics.
    7. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    8. Xiaodong Teng & Bao-Guang Chang & Kun-Shan Wu, 2021. "The Role of Financial Flexibility on Enterprise Sustainable Development during the COVID-19 Crisis—A Consideration of Tangible Assets," Sustainability, MDPI, vol. 13(3), pages 1-16, January.

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