 Forecasting distress in European SME portfoliosDimitra Michala (),
Theoharry Grammatikos and
Sara Ferreira Filipe
LSF Research Working Paper Series from Luxembourg School of Finance, University of Luxembourg Abstract: We develop distress prediction models for non-financial small and medium 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 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. Keywords: credit risk; distress; forecasting; SMEs; discrete time hazard model; multi-period; logit model; duration analysis (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:crf:wpaper:13-2 Access Statistics for this paper More papers in LSF Research Working Paper Series from Luxembourg School of Finance, University of Luxembourg Contact information at EDIRC. |
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