Internal and external determinants of corporate failure

Abstract

Starting from a series of financial ratios analysis, I build up two indices which take into account both the firm’s debt level and its sustainability. The construction of a Composite Indebtedness index, based on an original use of Robust Principal Component Analysis for skewed data, allows to classify firms according to their indebtedness degree and nature. This is a first tool to evaluate firms’ financial health. Secondly, a model aimed at investigating if and to what extent the proposed indices are able to correctly predict firms’ financial bankruptcy probabilities is proposed. The econometric results are compared with those of the popular Altman Z-score for different lengths of the reference period. The empirical evidence would suggest a good performance of the proposed Composite Indebtedness index which, therefore, could also be used as an early warning signal of bankruptcy.This chapter investigates the role of local context, with regard to the effect of local financial development and banking concentration, on a new firm’s probability of bankruptcy. The empirical setting is based on the Logit Multilevel Model that better allows the treatment of data referring to different levels of aggregation (firm and local variables) applied to new firms located in Italian provinces. I find that a higher level of financial development in a province decreases the likelihood of a new firm’s bankruptcy. This result is robust considering a 2SLS regression in which I use instruments for the local financial development and for the concentration of bank branches. In addition, the estimations suggest that the effect of local financial development and bank concentration is shaped by size. Local financial development is particularly significant for small start-ups, which traditionally suffer from great difficulty in accessing credit, whereas local banking concentration reduces the probability of bankruptcy for large, new firms.The purpose of this research is to study the role of spatial agglomeration economies as drivers of firm’s exit in France over the period 2009-2013 with a focus on two regional variables: local financial development and local specialisation. I apply spatial econometric techniques (Spatial Dynamic Panel data and Spatial GMM) to consider the spatial dependence in firm’s exit. I show that the firm’s exit is characterized by positive spatial autocorrelation, so that locations with high exit rates tend to be surrounded by similar ones. In addition, the results suggest that a higher local financial development reduces the exit rate of a department whereas local specialisation seems not to exert any effect.