Academic journal article E+M Ekonomie a Management

The Stability of Bankruptcy Predictors in the Construction and Manufacturing Industries at Various Times before Bankruptcy

Academic journal article E+M Ekonomie a Management

The Stability of Bankruptcy Predictors in the Construction and Manufacturing Industries at Various Times before Bankruptcy

Article excerpt

Introduction

According to Wu (2010), the internal causes of Arm bankruptcy may be seen in insufficient management skills, marketing and an inability to compete. They are reflected in company performance. For this reason, accounting data, or rather financial ratios, are a frequent source of information for assessing the stability and viability of an enterprise.

The literature (Chen & Hsiao, 2008) categorizes companies undergoing business crises as follows:

* Companies lacking the capital to manage the business and starting to have problems paying their short-term debts (current liabilities)--see Deakin (1972) and Gilson (1989). Financially, this condition is detectable in the values of current liquidity, quick liquidity, accounts receivable, cash flow, total asset turnover, and other factors.

* Companies with a negative value of retained earnings for two consecutive periods or negative growth for at least 1 year. The signs of financial problems appear in the following indicators (Altman, 1983): asset profitability, sales receipts, earnings before and after taxes, and operating profit margin.

* Companies whose shares on a public stock market show an overall drop, are excluded from trading, or withdrawn from the market.

Timely recognition of signs pointing to potential bankruptcy provides a chance to avert it. This is why the economic research has long been on a quest for indicators that could signal the threat of bankruptcy at the earliest possible time. In devising a model, it is rather difficult to collect sufficient data on bankrupt companies, as bankruptcy is relatively rare in business. The first models (Altman (1968), Ohlson (1980), Zmijewski (1984) and others) were designed on the basis of financial ratios calculated using company data one year prior to bankruptcy (the period t+1). One of the methods of increasing the accuracy of a model is to use indicators covering several years before bankruptcy (e.g. Perry et al., 1984). Deakin (1972) found that the ranking of predictor significance changes with receding time. Deakin's conclusion was confirmed by the work of Grice and Dugan (2001). Shumway (2001) criticizes the earlier bankruptcy models (of Altman, Zmijewski and Ohlson) as static since the time factor is ignored. These issue were also considered by Henerby (1996) who, aided by Cox's model (see Cox, 1972), analyzed the appropriateness of cash-flow-based indicators for predicting bankruptcy, and concluded that these indicators are statistically most significant 3 years before the event and can therefore serve as early indicators. Lin, Liang, and Chen (2011) summarize this problem in the following way: "Early studies tend to treat financial ratios measuring profitability, liquidity and solvency as significant indicators for the detection of financial difficulties. However, reliance on these financial ratios can be problematic. The order of their importance, for example, remains unclear as different studies suggest different ratios as the major indicators of potential financial problems."

Another question debated by the academic community is whether the models are transferrable, i.e. whether they can be applied in any environment other than that in which they were created. From a different point of view, authors such as Platt and Platt (1990), Grice and Dugan (2001), Delina, Packova (2013), Niemann et al. (2008) and Wu, Gaunt and Gray (2010) have pointed out this problem and indicated that the predication accuracy of bankruptcy models (their ability to differentiate correctly between a company threatened by bankruptcy and a prospering company) falls markedly when they are applied to a different branch, period or economic environment than the original environment. Thomas Ng, Wong and Zhang (2011) also concur with this view and point out the need of creating models for branches such as construction, as the existing models are inappropriate for this branch. …

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