Employing earnings shortfall as afinancialdistress indicator, we formulate a dynamic nonlinear model, implementing Wooldridge's conditional maximum likelihood estimator and accounting for potentially endogenous covariates. Likewise, we not only achieve a significant improvement in consistency and classification accuracy over static approaches, but we also manage to understand better the evolution of the financialdistress process. In our sample of Greek listed firms the higher the positive performance and the lower the leverage at the initial period the greater the chance that a company enters financialdistress further down the road, possibly due to manager–owner overconfidence and debt-imposed discipline by company's creditors.
- Financial distress
- Dynamic nonlinear
- Distress evolution
Konstantaras, K., & Siriopoulos, C. (2011). Estimating financial distress with a dynamic model: Evidence from family owned enterprises in a small open economy. Journal of Multinational Financial Management, 21(4), 239-255. https://doi.org/10.1016/j.mulfin.2011.04.001