Duty calls: prediction of failure in reorganization processes

Abstract

Purpose – Using data from business reorganization processes under Act 1116 of 2006 in Colombia during the period 2008 to 2018, a model for predicting the success of these processes is proposed. The paper aims to validate the model in two different periods. The first one, in 2019, characterized by stability, and the second one, in 2020, characterized by the uncertainty generated by the COVID-19 pandemic. Design/methodology/approach – A set of five financial variables comprising indebtedness, profitability and solvency proxies, firm age, macroeconomic conditions, and industry and regional dummies are used as independent variables in a logit model to predict the failure of reorganization processes. In addition, an out-ofsample analysis is carried out for the 2019 and 2020 periods. Findings – The results show a high predictive power of the estimated model. Even the results of the out-ofsample analysis are satisfactory during the unstable pandemic period. However, industry and regional effects add no predictive power for 2020, probably due to subsidies for economic activity and the relaxation of insolvency legislation in Colombia during that year. Originality/value – In a context of global reform in insolvency laws, the consistent predictive ability shown by the model, even during periods of uncertainty, can guide regulatory changes to ensure the survival of companies entering into reorganization processes, and reduce the observed high failure rate.