An Empirical Analysis of Private SMEs' Insolvency in Thailand Using Machine Learning

Chalerm Jaitang (), Zhaohua Li () and Christopher Gan
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Chalerm Jaitang: Faculty of Economics, Prince of Songkla University, Thailand and Department of Financial and Business Systems, Lincoln University, New Zealand, Postal: Faculty of Economics, Prince of Songkla University, Songkhla 90110 Thailand, and Department of Financial and Business Systems, Lincoln University, New Zealand
Zhaohua Li: Department of Financial and Business Systems, Lincoln University, New Zealand
Christopher Gan: Department of Financial and Business Systems, Lincoln University, New Zealand

Asian Journal of Applied Economics/ Applied Economics Journal, 2024, vol. 31, issue 2, 1-30

Abstract: We investigate the insolvency of private Thai SMEs in the manufacturing, trading, and service sectors from 2017 to 2021. We model insolvency as a function of industry-relative financial ratios, firm characteristics, and local economic conditions using Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression. The analysis shows the significant influence of financial ratios on the probability of insolvency for all sectors, particularly inventory turnover, accounts payable turnover, assets to equity, and debt to assets ratio. The service sector shows a unique positive effect of working capital to total assets on insolvency risk, implying that firms with high current assets or very low current liabilities are more prone to insolvency. Medium-sized firms, those registered as juristic ordinary partnerships, owned by foreigners, and located in less competitive areas are less likely to face insolvency.

Keywords: SMEs; insolvency; financial ratios; LASSO; Thailand (search for similar items in EconPapers)
JEL-codes: C23 C53 G33 M21 (search for similar items in EconPapers)
Date: 2024
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