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Modelling SME credit risk: Thai empirical evidence

  • Kanitsorn Terdpaopong
  • , Dessalegn Mihret

    Research output: Contribution to journal › Article › peer-review

    10 Citations (Scopus)

    Abstract

    This paper develops and tests a model to predict small and medium enterprise (SME) financial distress based on empirical evidence from Thailand. A sample comprising 198 financial statements of non-financially distressed and 68 statements of financially distressed SMEs were used. A parametric t-test was conducted to establish differences between financial characteristics of the two groups of SMEs. Results show statistically significant differences (t values significant at .001) between the two groups of SMEs in the financial ratios used for the study. Discriminant analysis was then conducted to develop a model for predicting the likelihood of an SME experiencing financial distress. The model hits an accuracy level of 97%, which compares favourably with the probability of accurate classification by chance (i.e., 65% after adjusting for the unequal sample sizes of the two groups of SMEs). A test of the model with a new sample shows the validity of the model beyond the original sample, confirming that Thai SME financial distress is amenable to prediction to a statistically significant extent. The model is expected to serve SME managers and creditors in assessing financial health of SMEs before making important decisions. The results are also expected to inform policymakers in formulating economic policies concerning SMEs.
    Original languageEnglish
    Pages (from-to)63-79
    JournalSmall Enterprise Research
    Volume18
    Issue number1
    DOIs
    Publication statusPublished - 2011

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure

    Keywords

    • Finance

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