A Note on Selecting a Response Measure for Financial Distress

Abstract

Since 1966, researchers have examined financial distress prediction models to determine the usefulness of accounting information to lenders. These researchers primarily used legal bankruptcy as the response variable for economic financial distress, or included legal bankruptcy with other events in dichotomous prediction models. However, theoretical models of financial distress normally define financial distress as an economic event, the inability to pay debts when due (insolvency). This study uses a loan default/accommodation response variable as a proxy for the inability to pay debts when due. The purpose of this note is to empirically test whether or not using the inability of a firm to pay debts when due, loan default/accommodation, as a response measure produces different results than using legal bankruptcy as the response measure. The study's empirical results show that legal bankruptcy and loan default/accommodation financial distress prediction models produce different statistical results, thus suggesting that the responses measure different constructs. A loan default/accommodation model also fits the data better than a bankrupt model. Our results suggest that a loan default/accommodation response may be a more appropriate measure to determine which accounting information is most useful to lenders in evaluating a firm's credit risk. Copyright Blackwell Publishers Ltd 1997.

An Effective Financial Statements Fraud Detection Model for the Sustainable Development of Financial Markets: Evidence from Taiwan

“…In the early days, the prediction of financial distress or bankruptcy often used financial ratios as the tool [1,[16][17][18]. Later, cash flow was also incorporated [19][20][21]. In recent years, corporate governance has been included as part of the equation for the prediction of financial crises or accounting fraud [3][4][5][6]10,11,[13][14][15]22,23].…”

EBITDA vs. Cash Flows in Bankruptcy Prediction on the Polish Capital Market

“…Due to these issues, the research on the usefulness of cash flows in financial distress prediction produced somewhat mixed results. Many researchers indeed found that various cash flow-based ratios are statistically significant predictors of the forthcoming bankruptcy (Ohlson, 1980;Gentry et al, 1985;Casey and Bartczak, 1985;Ward and Foster, 1997;Bhandari and Iyer, 2013;Unegbu and Adefila, 2013;Khan and Guruli, 2015). However, Gupta et al (2012), in their study of British small and medium-sized enterprises, found that the presence of operating cash flow information does not improve the prediction accuracy of the distress prediction models.…”

“…With such a use of EBITDA, the interest rate is often revised periodically, based on a grid of predetermined levels of the borrower's EBITDA-based ratios (Beatty et al, 2012;Beatty et al, 2015). EBITDA is also used in business valuation (Verninmen et al, 2005;Gray and Vogel, 2012;Hughen and Strauss, 2016), particularly of small private enterprises which do not report cash flow statement (Greenwald et al, 2001). The popularity of EBITDA is confirmed by a research, according to which EBITDA-based multiple is one of the two most frequently used valuation indicators by European stock analysts (Fernandez, 2002;Bancel and Mittoo, 2014;Lie and Lie, 2002).…”

Good Corporate Governance and Predicting Financial Distress Using Logistic and Probit Regression Model

“…Investor trust will have a positive impact on the availability of working capital, while creditor confidence will impact on the decrease of cost of debt (Ashbaugh et.al, 2004;Byun, 2007;Bhojraj & Sengupta, 2003). Furthermore, Elloumi & Gueyie (2001); Supatmi (2007); Huang & Zhao, (2008); Fich & Slezak (2008); Ward & Foster (1997), Yin & Tsui (2004) and Sengupta & Faccio (2011) proved that the probability of financial difficulties of implementing GCG, is lower than companies that do not implement GCG.…”