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The Value of Governance Variables in Predicting Financial Distress Among Small and Medium-Sized Enterprises in Malaysia

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  • Nur Adiana Hiau Abdullah

    (School of Economics, Finance and Banking, College of Business (COB), Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia)

  • Muhammad M. Ma'aji

    (School of Economics, Finance and Banking, College of Business (COB), Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia)

  • Karren Lee-Hwei Khaw

    (School of Economics, Finance and Banking, College of Business (COB), Universiti Utara Malaysia, 06010 UUM Sintok, Kedah, Malaysia)

Abstract

Predicting financial distress among SMEs can have a significant impact on the economy as it serves as an effective early warning signal. The study develops distress prediction models combining financial, non-financial and governance particularly ownership and board structures, on the likelihood of financial distress by using the logit model. The final sample for the estimation model consists of 172 companies with 50% non-failed cases and 50% failed cases for the period from 2000 to 2012. The prediction models perform relatively well especially Model 3 that incorporates governance, financial and nonfinancial variables, with an overall accuracy rate of 93.6% and 91.2% in the estimated sample and holdout sample respectively. This evidence shows that the models serve as effective early warning signals which are beneficial for monitoring and evaluation purposes. Controlling shareholder, number of directors and gender of managing director are found to be significant predictors of financially distressed SMEs.

Suggested Citation

  • Nur Adiana Hiau Abdullah & Muhammad M. Ma'aji & Karren Lee-Hwei Khaw, 2016. "The Value of Governance Variables in Predicting Financial Distress Among Small and Medium-Sized Enterprises in Malaysia," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 12(Suppl. 1), pages 1-77–91.
    • Handle: RePEc:usm:journl:aamjaf012s1_77-91
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    References listed on IDEAS

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    1. Blum, M, 1974. "Failing Company Discriminant-Analysis," Journal of Accounting Research, Wiley Blackwell, vol. 12(1), pages 1-25.
    2. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    3. 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.
    4. Edward I. Altman & Gabriele Sabato, 2013. "MODELING CREDIT RISK FOR SMEs: EVIDENCE FROM THE US MARKET," World Scientific Book Chapters, in: Oliviero Roggi & Edward I Altman (ed.), Managing and Measuring Risk Emerging Global Standards and Regulations After the Financial Crisis, chapter 9, pages 251-279, World Scientific Publishing Co. Pte. Ltd..
    5. 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.
    6. B. Luppi & M. Marzo & E. Scorcu, 2007. "A credit risk model for Italian SMEs," Working Papers 600, Dipartimento Scienze Economiche, Universita' di Bologna.
    7. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    8. Mohammad Saleh JAHUR & S. M. Nasrul QUADIR, 2012. "Financial Distress in Small and Medium Enterprises (SMES) of Bangladesh: Determinants and Remedial Measures," Economia. Seria Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 15(1), pages 46-61, June.
    9. Harold Siow Song Teng & Gurpreet Singh Bhatia & Sajid Anwar, 2011. "A success versus failure prediction model for small businesses in Singapore," American Journal of Business, Emerald Group Publishing Limited, vol. 26(1), pages 50-64, April.
    10. 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.
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    Cited by:

    1. Mangena, Musa & Priego, Alba Maria & Manzaneque, Montserrat, 2020. "Bank power, block ownership, boards and financial distress likelihood: An investigation of Spanish listed firms," Journal of Corporate Finance, Elsevier, vol. 64(C).
    2. Juraini Zainol Abidin & Nur Adiana Hiau Abdullah & Karren Lee-Hwei Khaw, 2020. "Predicting SMEs Failure: Logistic Regression vs Artificial Neural Network Models," Capital Markets Review, Malaysian Finance Association, vol. 28(2), pages 29-41.
    3. Rasa Kanapickiene & Renatas Spicas, 2019. "Credit Risk Assessment Model for Small and Micro-Enterprises: The Case of Lithuania," Risks, MDPI, vol. 7(2), pages 1-23, June.
    4. Farida Titik Kristanti, 2019. "Integrating Capital Structure, Financial and Non-Financial Performance: Distress Prediction of SMEs," GATR Journals afr175, Global Academy of Training and Research (GATR) Enterprise.
    5. Chih‐Chun Chen & Chun‐Da Chen & Donald Lien, 2020. "Financial distress prediction model: The effects of corporate governance indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1238-1252, December.

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