Open AccessPredicting Financial Distress among SMEs in Malaysia
Author(s) -
Muhammad M. Ma’aji,
Nur Adiana Hiau Abdullah,
Karren Lee-Hwei Khaw
Publication year - 2018
Publication title -
european scientific journal
Language(s) - English
Resource type - Journals
eISSN - 1857-7881
pISSN - 1857-7431
DOI - 10.19044/esj.2018.v14n7p91
Subject(s) - corporate governance , financial distress , sample (material) , shareholder , business , estimation , warning system , distress , financial ratio , finance , linear discriminant analysis , actuarial science , econometrics , economics , financial system , engineering , psychology , computer science , artificial intelligence , management , chemistry , chromatography , psychotherapist , aerospace engineering
Predicting financial distress among Small and Medium Enterprises (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 which were used to analyze the influence of major corporate governance characteristics, like ownership and board structures, on the likelihood of financial distress. Multiple Discriminant Analysis (MDA) model as one of the extensively documented approaches was used. 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 between 2000 to 2012. The prediction models perform relatively well especially in MDA model that incorporate governance, financial and non-financial variables, with an overall accuracy rate of 90.7 percent in the estimated sample. The accuracy rate in the holdout sample was 91.2 percent for the MDA model. This evidence shows that the models serve as efficient earlywarning signals and can thus be beneficial for monitoring and evaluation. Controlling shareholder, number of directors, and gender of managing director are found to be significant predictors of financially distressed SMEs.