Michala, Dimitra Grammatikos, Theoharry Ferreira Filipe, Sara
Year of Publication:
EIF Working Paper 2013/17
We develop distress prediction models for non-financial small and medium sized enterprises (SMEs) using a dataset from eight European countries over the period 2000-2009. We examine idiosyncratic and systematic covariates and find that macro conditions and bankruptcy codes add predictive power to our models. Moreover, industry effects usually demonstrate significance but provide only small improvements. The paper contributes to the literature in several ways. First, using a sample with many micro companies, it offers unique insights into European small businesses. Second, it explores distress in a multi-country setting, allowing for regional and country comparisons. Third, the models can capture changes in overall distress rates and co-movements during economic cycles. The researchers invite for feedback and comments.
credit risk distress forecasting SMEs discrete time hazard model multi-period logit model duration analysis