Do Bankruptcy Models Really Have Predictive Ability? Evidence Using China Publicly Listed Companies

[Abstract] This study provides ex ante evidence of failure prediction power of various z-score models using China publicly listed companies. The data covers a range of 11 years (1998-2008) and 1,336 companies. The result shows that Wang and Campbell's (2010) revised model has the highest overall prediction accuracy, while Altman's (1968) z-score model has the lowest overall prediction accuracy. The result confirms the usefulness of z-score models in predicting company delistings. [Keywords] z-score model; China; failure prediction Introduction According to the official estimates, China's population has reached 1.32 billion at the end of 2007. Its economy grew by an average of 10% per year between 2000 and 2007. China's gross domestic product stood at US$3.4 trillion while Germany's GDP was USD $3.3 trillion for 2007. This made China the world's third largest economy by gross domestic product behind Japan and the United States. Despite the amazing growth of China, the Chinese economy is significantly affected by the 2008-9 global financial crises due to the export orientated nature of the economy, which depends heavily upon international trade. China is experiencing the hit of business failure. The pearl tri-angle, famous for its shoe production, now is quiet and confused. Thousands of shoe companies there have closed. Huaqiang, the biggest plastic producer in China, has declared bankruptcy in 2008, leaving 7000 people jobless. In 2007, China experienced its first increase since 2002, in the annual number of Bankruptcy cases (3207 cases). China has launched an economic stimulus plan to specifically deal with the financial crisis. It has primarily focused on increasing affordable housing, easing credit restrictions for home mortgages and SMEs (Small and Medium-Sized Enterprises), lowering taxes, such as those on real estate sales and commodities, and pumping more public investment into infrastructure development, such as the rail network, roads, and ports. From an academic point of view, what can we do to help people get through the crisis? In order to fulfill this obligation, this study tests the predictive ability of various bankruptcy prediction z-score models. This study tests whether z-score models have true ex ante predictive ability using 11 years of data from Chinese publicly listed companies from 1998-2008. The results should help investors make wise decisions about their investments and avoid unnecessary losses. Previous Studies The prediction of company failure has been well researched using developed country data (Beaver, 1966; Altman, 1968; Wilcox, 1973; Deakin, 1972; Ohlson, 1980; Taffler, 1983; Boritz, Kennedy & Sun, 2007). A variety of models have been developed in the academic literature using techniques, such as multiple discriminant analysis (MDA), logit, probit, recursive partitioning, hazard models, and neural networks. Summaries of the literature are provided in Zavgren (1983), Jones (1987), O'leary (1998), Boritz, Kennedy and Sun (2007) and Agarwal and Taffler (2007). Despite the variety of models available, both the business community and researchers often rely on the models developed by Altman (1968) and Ohlson (1980) (Boritz et al. 2007). A survey of the literature shows that the majority of international failure prediction studies employ MDA (Altman, 1984; Charitou et al., 2004). Beaver (1966) presented empirical evidence that certain financial ratios, most notably cash flow/total debt, gave statistically significant signals well before actual business failure. Altman (1968) extended Beaver's (1966) analysis by developing a discriminant function which combines ratios in a multivariate analysis. Altman found that his five ratios outperformed Beaver's (1966) cash flow to total debt ratio and created the final discriminant function: Z=1.2X1+1.4X2+3.3X3+0.6X4+0.999XS where Xl=working capital/total assets; X2=retained earnings/total assets; X3=earnings before interest and taxes/total assets; X4=market value of equity/book value of total liabilities and X5=sales/total assets. …