Sectoral analysis of capital structure adjustment: evidence from emerging market

A. Hegde, A. K. Panda, Venkateshwarlu Masuna
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Abstract

PurposeThis paper aims to investigate the non-homogeneity in the speed of adjustment (SoA) of the capital structure of manufacturing companies. It also attempts to study the key determinants that accelerate the speed of adjustment towards the target leverage level.Design/methodology/approachUsing the dynamic panel fraction (DPF) estimator on the partial adjustment model, the study captures the heterogeneous SoA of 2,866 firms across eight prominent sectors of the Indian manufacturing industry from 2009 to 2020. To ensure robustness, the empirical inferences of DPF are cross-verified with the estimates of panel-corrected standard errors (PCSE).FindingsThe authors find a combination of the capital structure's slow, moderate and rapid adjustment speed along with the relevance of trade-off theory. Interestingly, the lowest and fastest SoA is recorded by the dwindling textile sector and expanding food and agro sector, respectively. Profitability, firm size, asset tangibility and non-debt tax shields are the key firm-specific parameters that impact the SoA towards the target.Originality/valueAvailing the rarely employed estimator ‘DPF’ and the objective of documenting diverse and non-uniform adjustment speeds across the Indian manufacturing sectors marks a novel addition to capital structure literature.
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资本结构调整的行业分析:来自新兴市场的证据
目的研究制造业企业资本结构调整速度的非同质性。它还试图研究加快向目标杠杆水平调整速度的关键决定因素。采用部分调整模型上的动态面板分数(DPF)估计器,本研究捕获了2009年至2020年印度制造业八个主要部门2,866家公司的异构SoA。为了确保稳健性,DPF的经验推断与面板校正标准误差(PCSE)的估计值进行了交叉验证。研究发现资本结构的慢、中、快速调整速度与权衡理论的相关性相结合。有趣的是,最低和最快的SoA分别记录在萎缩的纺织部门和扩大的食品和农业部门。盈利能力、公司规模、资产有形性和非债务税盾是影响SoA实现目标的关键公司特定参数。原创性/价值利用很少使用的估算器“DPF”和记录印度制造业不同和不统一的调整速度的目标,标志着资本结构文献的新补充。
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来源期刊
CiteScore
6.50
自引率
3.20%
发文量
30
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