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Analysis Of Financial Distress Determinants And The Role Of Corporate Governance For Risk Mitigation On Listed Indonesian Manufacturing Companies: Covid-19 Pandemic

Author

Listed:
  • Jessica Putri RARASSATI

    (Swiss German University, South Tangerang, Indonesia)

  • Yosman BUSTAMAN

    (Swiss German University, South Tangerang, Indonesia)

Abstract

The purpose of this research is to examine the impact of COVID-19 on financial distress; additionally, this paper also analyzes the link of financial ratio and corporate governance on financial distress. This study uses panel data regression analysis method to estimate the relationship between variables. Financial ratios used in this study are Return on Equity (ROE), Debt to Asset Ratio (DAR) and firm size, meanwhile several corporate governance measurements that are applied in this research consist of institutional ownership, commissionaires independent and board size. The measurement will also be aggregated into its sub-sector which consists of Consumer Goods Industry (CGI), miscellaneous industry and basic and chemical industry. It is found that, COVID-19 pandemic statistically impacted financial distress of manufacturing companies in Indonesia as it is proven by T-Test and also regression analysis method. The result reveals that Debt to Asset (DAR) which is the measurement of leverage owned by company, positively affected financial distress of manufacturing companies in Indonesia. The greater the leverage, the greater the risk of financial distress. Despite the discrepancy with previous studies results, the result shows that the numbers of commissionaires independent on manufacturing companies in Indonesia pose significant positive effect on financial distress. Action taken by Chief of Manufacturing companies in Indonesia during this COVID-19 crisis impact the survival of company. Manufacturing companies need to mitigate risk by maintaining higher profitability (ROE) and asset as measured by firm size, lowering debt value. On corporate governance site, companies need to consider limiting the number of independent commissionaires leading the company and gaining more intuitional investor.

Suggested Citation

  • Jessica Putri RARASSATI & Yosman BUSTAMAN, 2021. "Analysis Of Financial Distress Determinants And The Role Of Corporate Governance For Risk Mitigation On Listed Indonesian Manufacturing Companies: Covid-19 Pandemic," Business Excellence and Management, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 11(5), pages 182-195, October.
  • Handle: RePEc:rom:bemann:v:11:y:2021:i:5:p:182-195
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    References listed on IDEAS

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    1. Bipin Ajinkya & Sanjeev Bhojraj & Partha Sengupta, 2005. "The Association between Outside Directors, Institutional Investors and the Properties of Management Earnings Forecasts," Journal of Accounting Research, Wiley Blackwell, vol. 43(3), pages 343-376, June.
    2. 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.
    3. Sebastian Steinker & Mario Pesch & Kai Hoberg, 2016. "Inventory management under financial distress: an empirical analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 54(17), pages 5182-5207, September.
    4. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    5. Liang, Deron & Lu, Chia-Chi & Tsai, Chih-Fong & Shih, Guan-An, 2016. "Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study," European Journal of Operational Research, Elsevier, vol. 252(2), pages 561-572.
    6. Siti Nuryanah & Sardar M. N. Islam, 2015. "Corporate Governance and Financial Management," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-43561-3, December.
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