IDEAS home Printed from https://ideas.repec.org/a/agr/journl/v9(562)y2011i9(562)p103-128.html
   My bibliography  Save this article

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 / Editura Economica, vol. 0(9(562)), pages 103-128, September.
    • Handle: RePEc:agr:journl:v:9(562):y:2011:i:9(562):p:103-128
    as

    Download full text from publisher

    File URL: http://store.ectap.ro/articole/640.pdf
    Download Restriction: no
    File URL: http://www.ectap.ro/articol.php?id=640&rid=78
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:agr:journl:v:9(562):y:2011:i:9(562):p:103-128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mircea Dinu (email available below). General contact details of provider: https://edirc.repec.org/data/agerrea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.