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The Structure of Good Corporate Governance and Financial Indicators as Predictor of Financial Distress in Mining Sector Company in Indonesia

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  • Sumani Sumani

Abstract

The purpose of the paper are- (1) to examine financial indicators, including- current ratio, return on assets, debt to assets ratio, and total asset turn over as a predictor of financial distress in mining sector companies in Indonesia; (2) to examine the structure of Good Corporate Governance including- independent commissioner, audit committee, board of directors, independent audit committee ratios with non-independent, and institutional ownership ratio with managerial ownership as predictor of financial distress in mining sector company in Indonesia. Type of research is quantitative explanatory research. Sampling technique is used purposive sampling method, as many as 20 companies in the mining sector in Indonesia. Analytical techniques in this study uses logistic regression. The results of the research show that- current ratio, debt to asset ratio, total asset turnover, and institutional ownership ratio with managerial ownership are not predictors of financial distress in mining sector in Indonesia. However, return on Assets, independent commissioners, audit committees, boards of directors and independent audit committee ratios with non-independent are predictors of financial distress in mining companies in Indonesia.

Suggested Citation

  • Sumani Sumani, 2019. "The Structure of Good Corporate Governance and Financial Indicators as Predictor of Financial Distress in Mining Sector Company in Indonesia," Research in Business and Management, Macrothink Institute, vol. 6(1), pages 1-12, February.
  • Handle: RePEc:mth:rbmjnl:v:6:y:2019:i:1:p:1-12
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    References listed on IDEAS

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    1. 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.
    2. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    3. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    4. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    5. 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.
    6. Cornett, Marcia Millon & McNutt, Jamie John & Tehranian, Hassan, 2009. "Corporate governance and earnings management at large U.S. bank holding companies," Journal of Corporate Finance, Elsevier, vol. 15(4), pages 412-430, September.
    7. Platt, Harlan D. & Platt, Marjorie B., 2006. "Understanding Differences Between Financial Distress and Bankruptcy," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 2(2), pages 1-17.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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