Abstract

Predicting financial distress among SMEs can have a significant impact on the economy as it serves as an effective early warning signal.The study develops distress prediction models combining financial, non-financial and governance variables particularly ownership and board structures, on the likelihood of financial distress by using the logit model.The final sample for the estimation model consists of 172 companies with 50 percent non-failed cases and 50 percent failed cases for the period of 2000 to 2012.The prediction models perform relatively well especially model 3 that incorporates governance, financial and non financial variables, with an overall accuracy rate of 93.6 percent and 91.2 percent in the estimated and holdout samples.This evidence shows that the models serve as effective early warning signals which are beneficial for monitoring and evaluation purposes.Controlling shareholder, number of directors and gender of managing director are found to be significant predictors of financially distressed SMEs.

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