The ability to predict corporate bankruptcy is critically important to investors, creditors, borrowing organizations and governments alike. Bankruptcy occurs when an organization is unable to afford its financial obligations or pay its creditors. While research has illustrated the role of financial ratios on predicting bankruptcy, social factors are largely not considered an effective element. In this paper, I investigate the social and human capital determinants of bankruptcy and explore them as new avenues for enhancing predictive power. Specifically, this study develops new models for predicting bankruptcy based on non-financial factors. The two social variables that I examine are (1) networking ability as a proxy of social capital and (2) the power of managers based on their education as a proxy of human capital. I also added to the Altman’s and Zmijewski’s models with two categorizes of financial variables, the first of which includes five that are financially based on the Altman model, and second three that are financially based on the Zmijewski model by industry and year fixed effect. The results demonstrated a significant and negative relationship between social and human capital and bankrupt companies, the most financial ratios of Altman and Zmijewski are also significant. The results are confirmed using Logistic regression, Cox Proportional Hazard Model and Neural Network.
|Commitee:||Elyasiani, Elyas, Chitturi, Pallavi, Guillotin, Bertrand|
|School Location:||United States -- Pennsylvania|
|Source:||DAI-A 81/12(E), Dissertation Abstracts International|
|Keywords:||Human and social capital, Predicting bankruptcy|
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