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Business Failure Prediction Using Decision Trees, Adrian Gepp, Kuldeep Kumar, Sukanto Bhattacharya
Business Failure Prediction Using Decision Trees, Adrian Gepp, Kuldeep Kumar, Sukanto Bhattacharya
Kuldeep Kumar
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly financial investment and lending. The potential value of such models is emphasised by the extremely costly failure of high-profile companies in the recent past. Consequently, a significant interest has been generated in business failure prediction within academia as well as in the finance industry. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses have traditionally been the most popular approaches, but there are also a range of promising non-parametric techniques that can alternatively be applied. In …
Business Failure Prediction Using Decision Trees, Adrian Gepp, Kumar Kuldeep, Sukanto Bhattacharya
Business Failure Prediction Using Decision Trees, Adrian Gepp, Kumar Kuldeep, Sukanto Bhattacharya
Adrian Gepp
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly financial investment and lending. The potential value of such models is emphasised by the extremely costly failure of high-profile companies in the recent past. Consequently, a significant interest has been generated in business failure prediction within academia as well as in the finance industry. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses have traditionally been the most popular approaches, but there are also a range of promising non-parametric techniques that can alternatively be applied. In …
Managing Medical Bills On The Brink Of Bankruptcy, Melissa B. Jacoby, Mirya Holman
Managing Medical Bills On The Brink Of Bankruptcy, Melissa B. Jacoby, Mirya Holman
Melissa B. Jacoby
This paper presents original empirical evidence on financial interactions between medical providers and their patients who go bankrupt. We use a nationally representative sample of people who filed for bankruptcy in 2007 to compare two popular but hotly contested methods of measuring medical burden. By applying both methods to the same filers, we find that nearly four out of five respondents had some financial obligation for medical care not covered by insurance in the two years prior to filing as measured by the survey method. The court record method paints a different picture, with only half of the cases containing …