Financial distress prediction in Indonesia companies: finding an alternative model

Anggraini Dewi and Mulya Hadri
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Anggraini Dewi: Faculty of Economics and Business, University of Mercu Buana
Mulya Hadri: Faculty of Economics and Business, University of Mercu Buana

Russian Journal of Agricultural and Socio-Economic Sciences, 2017, vol. 61, issue 1, 29-38

Abstract: This study aims to identify suitable financial distress prediction model for companies in Indonesia. The population and samples used in this study are listed companies with the data range from 2006 to 2015. Samples were selected in a purposive manner at some stage. The first stage of study was choosing a company with negative earnings for two consecutive periods in the study period with total assets of around IDR1 trillion to IDR5 trillion. For a comparison, the researcher chose companies with positive earnings by the same criteria. As independent variables other than using financial ratios, variable corporate governance with ownership structure and macro-economic variables were also used as representation of conditions faced by companies in Indonesia. Analysis method used in this study was Binary Logistic Regression Analysis. The research found financial distress prediction influences by: Working Capital to Total Assets; Current Ratio; Book value of equity to total liabilities; Total Debt to Total Assets; EBIT to Current Liabilities; and Institutional Ownership.

Keywords: PREDICTION MODEL; BINARY LOGISTIC REGRESSION; FINANCIAL DISTRESS (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:scn:031261:16967532

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