Sample Economics Paper on Bankruptcy Prediction


Models to predict companies’ bankruptcy levels have been formulated but the z-score model is used for advanced system failure warnings. Challenges concerned with companies running bankrupt have been rampant hence causing failure to many business enterprises. Through the z-score model, companies should be able to capitalize on their weak points and take enough precautions to avoid the incident. The Z-score model uses statistical tools to determine the independent variables and the objective function score described from the multivalent discriminant analysis.

The Z-score Machine Learning Technique

The results from the Z-score model are used to link up current and future financial situation. The model has revealed that numerous features could reveal bankrupt institutions without any dogma. It provided complete results for a period predicted to be five years before bankrupt onset. The z-score is more convenient compared to financial analysis. Feature selection in the problem of bankruptcy prediction will be discussed in detail (Alkhatib and Ahmad 89).

Some of the features mostly used by the science-based model to predict company bankruptcy is accounting and market variables. The model uses the entire information on the company accounted profit to be able to predict on what terms the accounted finance will be depleted within the coming years (Altman et al. 123). The marketed variables are also another feature to be considered when evaluating and predicting the profitable company progress. The model also analyzes this variable and checks on the future implication if they limit or magnify the marketed variables. The feature on the market based information was used to acknowledge current pricing, which would be used in return to predict the future company loss (Bauer and Vineet 438). The model opens up the potholes in a company enabling it to come up with a plan.

Firm-characteristics is another feature which can be used to predict bankruptcy within an organization. Firm characteristics implies on the number of business’ segments a company poses and the total financial impacts they represent to the company yearly (Grice and Robert 58).  Analysis revealed that abundance in business segments the more reliable the company is regarding financial capability (Li 38). From this, the idea of why the most prominent firm has a lower percentage of bankruptcy was confirmed. Another feature which can be of great use is the company’s interest in the well-being of his employees. The success of any organization depends mostly on the employees since they do most of the workforce as well as management. For these reasons company shows ensures that their employees’ welfare is well catered for regarding salaries, vacations, and good working conditions (Siddiqui 78). This in return has boosted companies finance since employees work intensively thereafter.


In summary, the scientific models have revealed various features which can trigger bankruptcy if they are not taken into consideration. They have also enabled companies to focus on both current and future plans thus strengthening and improving its existing span. On the other hand, the employee’s well -being has been well catered for thus improving their working condition and in turn positively impacting company finance. These features are not only crucial to existing companies but can also be used by investors to establish new companies. Application of the various bankruptcy prediction models offers the much needed outline and correction model that may be employed in identifying and allowing financial corporations to improve their financial credibility and ranking among the consumers through improved ethical practice.


Work Cited

Alkhatib, Khalid, and Ahmad Eqab Al Bzour. “Predicting corporate bankruptcy of Jordanian listed companies: Using Altman and Kida models.” International Journal of Business and Management 6.3 (2011): 208.

Altman, Edward I., et al. “Distressed firm and bankruptcy prediction in an international context: A review and empirical analysis of Altman’s Z-score model.” Available at SSRN 2536340 (2014).

Bauer, Julian, and Vineet Agarwal. “Are hazard models superior to traditional bankruptcy prediction approaches? A comprehensive test.” Journal of Banking & Finance 40 (2014): 432-442.

Grice, John Stephen, and Robert W. Ingram. “Tests of the generalizability of Altman’s bankruptcy prediction model.” Journal of Business Research 54.1 (2001): 53-61.

Li, June. “Prediction of corporate bankruptcy from 2008 through 2011.” Journal of Accounting and Finance 12.1 (2012): 31-41.

Siddiqui, Sanobar Anjum. “Business bankruptcy prediction models: A significant study of the Altman’s Z-score model.” Available at SSRN 2128475 (2012).