Determinants of Target Capital Structure and Adjustment Speed: Evidence from India

Shaw, Sutanuka; Rakshit, Debdas

doi:10.13189/ujaf.2021.090203

Cited by 3 publications

(6 citation statements)

References 8 publications

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“…Public companies in Indonesia tend to prefer large nominal fixed assets by selling old assets and buying new assets in order to benefit from tax deductions from annual depreciation costs. However, this study is not in line with the research of Dewi and Dana (2017), Syahara (2015), and Margaretha and Ramadhan (2010) who found that the Non Debt Tax Shield has no effect on capital structure. Syahara (2015) found that non-debit tax shiled statistically has no effect on capital structure.…”

Section: The Effect Of Non Debt Tax Shield On Debt To Asset Ratio (Dar)contrasting

confidence: 99%

The Effect of Return on Asset, Non Debt Tax Shield, Asset Growth, Company Size, and Current Ratio, Against Debt to Asset Ratio on Companies Consumer Goods Listed on Indonesia Stock Exchange for the Period (2011-2017)

Artati

2020

JAFM

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This research was conducted on Consumer Goods companies listed on the IDX (Indonesia Stock Exchange) for the period 2011 - 2017, aiming to examine the effect of Return on Assets (ROA), Non debt tax shield (NDTS), Asset Growth (GROWTH) Company Size (Size) , and Current Ratio (CR) simultaneously or partially to Debt to Asset Ratio (DAR). The sampling technique used was purposive sampling. The sample used in this study amounted to 26 companies, a total of 182 data. The data analysis technique in this research is multiple linear regression analysis, classic assumption test (normality, multicollinearity, heteroscedasticity, and autocorrelation), hypothesis testing, and the coefficient of determination. The software used for data processing is SPSS 22.0. The results of multiple linear regression analysis show the equation Ln_DAR = 2.119 - 0.041Ln_ROA + 0.091 Ln_NDTS + 0.0003 Ln_GROWTH - 0.030 Ln_SIZE - 0.565 Ln_CR + e with an F test of 103.468. The t-test value for the Return on Assets (ROA) variable is -2.529; the t-test value for the Non debt tax shield (NDTS) variable was 2,629; t test value for asset growth variable (GROWTH) is -0.014. t test value for variable firm size (Size) is -0.172; Current Ratio (CR) variable t test value of -21,437. The coefficient of determination (Adjusted R Square) is 0.739 or 73.9%, while the remaining 26.1% is influenced by other factors outside of this research model.

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Section: The Effect Of Non Debt Tax Shield On Debt To Asset Ratio (Dar)contrasting

confidence: 99%

The Effect of Return on Asset, Non Debt Tax Shield, Asset Growth, Company Size, and Current Ratio, Against Debt to Asset Ratio on Companies Consumer Goods Listed on Indonesia Stock Exchange for the Period (2011-2017)

Artati

2020

JAFM

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“…Under this theory, the difference between actual and target debt ratio plays a crucial role in a company's decision to issue debt or equity. Therefore, we estimate the target debt ratio using a partial adjustment model of debt ratio to confirm the existence of an optimal capital structure and to verify it theoretically [12,14,15,17,18,27].…”

Section: Estimation Of Target Debt Ratiomentioning

confidence: 99%

“…In the partial adjustment model, the LEV used for estimating the target debt ratio is measured with a dynamic panel model as in Equation ( 1), assuming that it is determined by the characteristics of the company in the previous year. The explanatory variables reflecting the characteristics of the company include tangibility (Tang), growth opportunities (MTB), company size (LogAsset), profitability (EBIT), and non-debt tax shields (Dep), which are typically used in verifying trade-off theory [6,14,15,17,18]. In addition, to reflect macroeconomic factors known to influence the capital structure, this study included the KOSPI return (MarketReturn) and 5-year government bond yield (5yearBond) [12,27,28].…”

Section: Estimation Of Target Debt Ratiomentioning

confidence: 99%

“…To examine theoretical support for verifying the two theories and market timing hypothesis, it is imperative to ensure a significant level of statistical power for the explanatory variable effects of the theory while controlling for the main variables suggested in existing research. Therefore, in Equation ( 4), we applied the following variables used in existing research [5,6,14,18,28,31] to control various company characteristics: tangibility (Tang), growth opportunities (MTB), company size (LogAsset), profitability (EBIT), and non-debt tax shield (Dep). First, Tang is measured as [tangible assets/total assets].…”

Section: Control Variablesmentioning

confidence: 99%

“…Moreover, theoretical debates have evolved from static perspectives focusing on the existence of an optimal capital structure to dynamic research tracing changes in capital raising [12][13][14][15]. Recent studies have shown a significant interest in dynamic capital-raising behaviors driving changes in capital structure rather than analyzing the static relationship between company characteristics and capital structure [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

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Capital Structure Dynamics: Evidence from the Korean Listing Market

2024

Sustainability

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This study analyzes how the trade-off theory, capital financing priority theory, and market timing hypothesis impact corporate capital structure for sustainable growth. Using a panel regression and system generalized method for moment analyses with balanced panel data for 1636 listed firms in the Korean stock market and KOSDAQ from 2011 to 2021, we discovered that the level of and change in capital structure are determined through a complex mechanism in which the target debt ratio adjustment speed, previous year’s debt ratio, target debt ratio divergence, funding shortage situation, and market timing hypothesis interact complementarily. This indicates that the capital structure decisions of Korean listed firms are characterized by a complex mechanism that is difficult to explain with a single theory. The findings of this study have practical implications for understanding the capital structure decisions of Korean firms and for designing efficient capital-raising strategies. Additionally, by revealing the complementary relationship between the two theories, this study provides directions for future research on corporate capital structure.

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