Ambiguity and capital structure adjustments

Ban, Mingyuan; Chen, Chang-Chih

doi:10.1016/j.iref.2019.05.009

Cited by 6 publications

(4 citation statements)

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“…For example, since preferences for ambiguity in the smooth model (Klibanoff et al, 2005) are outcome dependent, formed as preferences over expected utilities, they deliver conclusions different than ours (Lee, 2014). Preferences for ambiguity in the max-min model (Gilboa and Schmeidler, 1989) are also outcome dependent, which provides the different conclusions about optimal capital structure in Ban and Chen (2019). Inherently, outcome dependent preferences for ambiguity implies risk dependence.…”

Section: Introductionmentioning

confidence: 98%

Ambiguity and the Tradeoff Theory of Capital Structure

2022

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We examine the impact of ambiguity, or Knightian uncertainty, on the capital structure decision, using a static tradeoff theory model in which agents are both ambiguity and risk averse. The model confirms the well-known result that greater risk—the uncertainty over outcomes—leads firms to decrease leverage. Conversely, the model indicates that greater ambiguity—the uncertainty over the probabilities associated with the outcomes—leads firms to increase leverage. Using a theoretically based measure of ambiguity, our empirical analysis presents evidence consistent with these notions, showing that ambiguity has an important and distinct impact on capital structure. This paper was accepted by Gustavo Manso, finance.

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Section: Introductionmentioning

confidence: 98%

Ambiguity and the Tradeoff Theory of Capital Structure

2022

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“…Managers believe in the worst-case about the expected risk-adjusted EBIT behavior, implying a distortion of restructuring likelihood. This essential feature justifies that companies display a weaker willingness to readjust leverage by choosing a slower pace and smaller size of adjustment [11]. On the other hand, Liu et al (2019) [12] showed that executive compensation motivates CEOs to pursue more aggressive capital structure policy.…”

Section: -Introductionmentioning

confidence: 96%

Explanatory Factors of the Capital Structure

Silva¹,

Gomes

Lopes

2020

Emerg Sci J

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This paper presents an empirical study of the capital structure of Portuguese companies where the main objective is to find key explanatory factors for indebtedness decisions. The relations between indebtedness and its determinants are tested in the light of the Trade-Off Theory and the Pecking-Order Theory. The motivation of this work was to contribute to the scientific research on the influential determinants of the capital structure and to deepen the knowledge of the Portuguese market. The quantitative methodology is used, through an econometric model for panel data using accounting information of 55 Portuguese companies between 2014 and 2016. Statistical tests such as the F test, the Lagrange Multiplier Breusch-Pagan test and the Hausman test were used to identify the most appropriate method of estimation, which resulted in a panel data model with random effects for individuals. The findings of this study suggest that indebtedness have a positive relation with tangibility and the size of the company, which supports the Trade-Off Theory. However, the positive relationship with the non-debt tax benefits suggests the importance of taxes, contrary to Trade-Off Theory. The negative relationship with cash flows, coupled with the positive relationships between size and growth opportunities, suggest the use of funding only when internal funds become insufficient, supporting the Pecking-Order Theory. The general results support that both theories partially explain the financing decisions of Portuguese companies. Doi: 10.28991/esj-2020-01249 Full Text: PDF

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“…DeAngelo (2022) argued that managers worry about reliable access to funding and that, due to limited knowledge, managers cannot detect the material difference in capital structure decisions. Ban and Chen (2019) argued that due to market incompleteness, managers hold the worst-case belief and, as a result, do not readjust leverage.…”

Section: Introductionmentioning

confidence: 99%

CEO social network, capital structure complexity and firm performance

Mundi

2023

RBF

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PurposeThe paper aims to examine the effect of CEOs' social networks on capital structure complexity (CSC) and firm performance.Design/methodology/approachOrdinary Least Squares regression (OLS) and Generalized method of moments (GMM) regression results estimate the effect of CEOs' (Chief executive officer) social networks on capital structure complexity and firm performance. The number of sources of capital (NSC) and concentration ratio estimate the capital structure complexity for the sample firms.FindingsThe results show that CEOs' social networks significantly influence CSC. We suggest that the CEOs' social networks encourage them to make more complex capital structure decisions. This behavior deteriorates firm performance.Research limitations/implicationsThere is a lack of systematic conceptual reason for measuring CEO social network. Future research should use other measures of the social network to estimate the relation of the CEO's social network with CSC and firm performance.Practical implicationsThe findings support the managerial power approach and social network theory that the observable characteristics of CEOs influence CSC. The results are robust for an alternative explanation.Originality/valueBy investigating the impact of the influence of CEOs' social networks on CSC and performance, the authors extend research on strategic leadership and capital structure and firm performance.

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Ambiguity and capital structure adjustments

Cited by 6 publications

References 64 publications

Ambiguity and the Tradeoff Theory of Capital Structure

Ambiguity and the Tradeoff Theory of Capital Structure

Explanatory Factors of the Capital Structure

CEO social network, capital structure complexity and firm performance

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