Abstract

The main purpose of this study is to investigate some financial indicators that affect the debt ratio in Thailand?s capital market. Two competing theories that explicate the capital structure are old-fashioned pecking order and static trade-off model. From existing literature reviews, we select seven traditional factors: profitability, asset structure, size, liquidity, non-debt tax shields, dividend policy and growth as explanatory variables. While long-term debt and total debt are used as proxies for dependent variables. This study uses secondary data collected from annual financial statements of companies in SET 100 index exclude financial business sector. All firms rank highest market capitalization and top trading liquidity in Thailand Stock Exchange for a period of 10 years during 2009-2018. After examine the data, only 760 samples are qualified under criteria. Two panel multiple regression models are implemented for statistic testing at the significant level 0.05.The results for model 1 (Long term debt) show positive and statistical significant effect of asset structure, size, liquidity and growth. While other three factors comprising profitability, non-debt tax shield and dividend policy indicate negative statistical relationships. The results for model 2 (Total debt) show positive and statistical significant effect of asset structure and growth. Whereas, two factors including profitability and liquidity display negative statistical correlation. The results of the two models are consistent with the Pecking Order theory for profitability and growth. High growth firms have higher need for funds then expect to borrow more. While asset structure is consistent with trade-off theory which hold that there should be a positive relationship between fixed assets and debt since fixed assets can serve as collateral. The explanatory variables which have the highest impact on capital structure choices for long term debt and total debt are non-debt tax shield and profitability respectively. Other independent variables such as product uniqueness, risk and macroeconomic indicators are subject to future research.

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