A semiparametric stochastic spline model as a managerial tool for potential insolvency

This study introduces a flexible nonlinear semiparametric spline model, new to solvency studies, as a tool for managerial discretion and regulatory oversight. The model has a linear component and a nonlinear component that uses stochastic splines. The study focuses on the functional relationship between regressors and the probability of financial distress as an object for managerial action. Leverage plots are provided to analyze the potential effect of decisions to modify firm levels of financial variables. If the true relationship between regressors and the response is not linear, then managerial efforts to rectify deteriorating financial conditions can be misinformed by reliance on a linear solvency model. The leverage plots adjust to the firm's position within the industry and its specific levels of various financial variables. A five-regressor semiparametric spline model is shown to yield insights into the behavior of the risk of financial distress probabilities that linear parametric models suppress. The model also classifies and validates well in comparison with recent insolvency studies and as well as parametric logit and probit models on the same data.

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