On the adjustment speed of SMEs to their optimal capital structure

Aybar-Arias, Cristina; Casino-Martínez, Alejandro; López-Gracia, José

doi:10.1007/s11187-011-9327-6

Cited by 74 publications

(97 citation statements)

References 39 publications

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“…Recent studies validated the impact of deviation cost on adjustment speed (see for examples, Aybar Arias et al, 2011;Oztekin and Flannery, 2012;Haron, 2014b).…”

Section: Introductionmentioning

confidence: 97%

Do Indonesian firms practice target capital structure? A dynamic approach

Haron

2016

JABS

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Purpose This study aims to investigate the dynamic aspects in the capital structure decisions of firms in Indonesia, offering an extension to the existing literature on Indonesia via a dynamic model, including the existence of target capital structure, the influencing factors, the speed of adjustments and the supporting theories to explain the findings. Design/methodology/approach This study uses a dynamic partial adjustment model estimated based on a generalized method of moments. Findings Indonesian firms do practice target capital structure and are influenced by firm-specific factors like profitability, business risk, firm size, liquidity and share price performance due to time-varying factors. A rapid adjustment toward target leverage is detected, thus supporting the existence of the dynamic trade-off theory (TOT). The pecking order theory (POT) also has significant influence, particularly after the new reformation of financing policy, where retained earnings are also preferred as a source of financing apart from merely external financing through bank loans. There are also traces of market timing influences where firms also seem to time their equity issuance. Research limitations/implications Despite relatively utilizing recent data and bigger sample firms compared to the previous limited studies on Indonesia, the results of this study, however, need to be cautiously interpreted. First, the sample chosen focused on listed firms, hence may not be generalized to all Indonesian firms, listed and unlisted. Second, the study does not separate firms by sectors and their leverage positions, that is under-levered and over-levered, so as to note that financial decisions may also be affected by the sector in which the firms operate and their leverage positions. These are to be considered in future research. Practical implications There is strong evidence that the corporate financing behavior of Indonesian firms is governed by the POT and TOT. Both are dealing with the function of debt. The financial sector reformation does have a positive impact on the banking sector, but not the local corporate bond market. Therefore, regulators and policymakers should bear in mind that banking as well as private bond market in Indonesia must be tailored in such a way that both could act as intermediaries of debt financing, as bond market represents an important component of a diversified financial sector. Originality/value This study fills the gap by providing an extension to the existing literature and a deeper insight of the capital structure of Indonesian firms using a more robust dynamic model.

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“…Recent studies validated the impact of deviation cost on adjustment speed (see for examples, Aybar Arias et al, 2011;Oztekin and Flannery, 2012;Haron, 2014b).…”

Section: Introductionmentioning

confidence: 97%

Do Indonesian firms practice target capital structure? A dynamic approach

Haron

2016

JABS

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“…Also, they evidenced that the small firms may slowly revisit their capital structure from time to time to adjust, targeting the optimal capital. Aybar- Arias et al (2012) evidenced the same negative relationship in Spain, but it was weaker and also, the adjustment speed was slow. Despite what might be expected, Romano et al (2000) tested a sample of privately-owned companies in Australia; their findings highlighted an existence of a positive relationship between age and leverage.…”

Section: Agementioning

confidence: 71%

Investigating the Impact of Firm Characteristics on Capital Structure of Quoted and Unquoted SMEs

ELbekpashy¹,

Elgiziry²

2017

AFR

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This study aims to enhance the understanding of SMEs' capital structure in Egypt. The study tests the impact of asset structure (tangibility), size, profitability, liquidity, growth, age, and ownership structure as independent variables on the leverage ratio. Three alternative variables are used as a proxy for leverage: total, long term, and short term leverage. The study further investigates the significance of the relationship between the economic sector as a control variable and the three leverage ratios. Multiple regression analysis is used to develop the explanatory models for two samples of SMEs. The first sample comprises of 28 listed and traded SMEs in Egypt. The second sample includes panel data of 95 non-quoted SMEs. The overall model recommends that all the independent and control variables significantly explain the capital structure decisions of SMEs in Egypt. The results of the analysis of the two samples show a high degree of similarity. The managerial ownership is found to be negatively correlated with short term leverage, while the block holding ownership is positively correlated with the total and the short term leverage. Moreover, the sector shows a significant relationship with the capital structure. The results of the study demonstrate that the financing behavior of SMEs in Egypt is consistent with the pecking order theory. Finally, the study introduces useful recommendations for policy makers and SMEs' management in Egypt.

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“…MDR* is the target debt ratio for firm i at time t . The target adjustment coefficient, λ , can also be considered as the speed of adjustment: each period, the firm closes the gap between its actual debt ratio in the previous period and its target at the end of the current period by a proportion of λ (Aybar‐Arias et al., ). A λ >0 indicates adjustments toward the target, and a λ <1 suggests the presence of adjustment costs.…”

Section: Data and Empirical Methodologymentioning

confidence: 99%

“…In this way, the actual debt ratio can be obtained as a weighted average of MDR * it and MDR it −1 , where λ and (1− λ ) are the respective weights. It is important to underline that when λ = 0, which means that adjustment costs are extremely high, the debt ratio is “sticky” and MDR it = MDR it −1 (Aybar‐Arias et al., ).…”

Section: Data and Empirical Methodologymentioning

confidence: 99%

Rating and capital structure: How do the signs affect the speed of adjustment?

Samaniego‐Medina

Pietro

2019

Financ Manag Account

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Standard and Poor's ratings can be modified by the addition of a plus (+) or minus (−) sign to show the relative standing within each major rating category. In this paper, we analyze the influence of these signs on the speed of leverage adjustment for listed European companies in the 2004–2014 period. Our results indicate that (a) when a qualification is accompanied by a minus sign, it adjusts more slowly than qualifications either with a plus sign or without a sign; (b) when a rating has a plus sign, the adjustment is slower than when it has no sign; and (c) when a qualification is BBB‐, the speed of its leverage adjustment is close to zero. These results suggest that companies with signs in their ratings decrease their speed of adjustment to the target leverage ratio. In addition, such companies are especially concerned about a credit rating downgrade when it implies a possible loss of the degree of investment (BBB‐).

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On the adjustment speed of SMEs to their optimal capital structure

Cited by 74 publications

References 39 publications

Do Indonesian firms practice target capital structure? A dynamic approach

Do Indonesian firms practice target capital structure? A dynamic approach

Investigating the Impact of Firm Characteristics on Capital Structure of Quoted and Unquoted SMEs

Rating and capital structure: How do the signs affect the speed of adjustment?

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