Search results

This 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.

Using 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).

The 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.

Availing 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.

This paper aims to conduct bibliometric analysis on the studies dealing with capital structure’s speed of adjustment (SoA) and identify the prominent themes while suggesting future research directions in the area. The existing reviews broadly focus on the capital structure, which provides the scope for conducting a review on this sub-aspect of capital structure.

This study uses a three-stage process to conduct this review: identification of academic journals, selection and analysis of target papers. This study uses a combination of bibliometric tools and a system thinking approach to assess the current status of publications and emerging themes within the literature.

This study has found a progressive evolution of SoA in capital structure research from 1984 to 2021. Studies largely focus on implementing the dynamic models to analyse the impact of adjustment costs, dynamic economic conditions, corporate governance practices and other variables on the firms’ adjustment speed and financial decisions. The network analysis of citations, keywords and clusters gives further knowledge on the intellectual structure of the data.

This study is highly dependent on the papers available within the SCOPUS database. Studies not included herein are not part of this analysis, which may or may not bear an effect on the study’s findings.

To the best of the authors’ knowledge, the application of systems engineering concept of “system thinking approach” to identify literature gap and suggest directions for forthcoming research is the first of its kind, thus adding a novel and multidisciplinary aspect to this study.

This paper aims to empirically investigate the evidence of the transmission of monetary policy impulses to firm profitability via manufacturing firms’ short-term and long-term corporate financing decisions.

This study decomposes the receptiveness of firm profitability to monetary policy shock under circumstances of financial flexibility. Additionally, the study extends its scope to undertake a sector-wise analysis of manufacturing firms from 2008 to 2020. Generalized methods of moments (GMM) and quantile regression models are employed.

The profitability of firms in the chemical, food and machinery sector are positively impacted by short-term financing, whereas the metal sector is positively impacted. But during the tight monetary policy, short-term financing does not appear to be a significant parameter while explaining the firms’ profitability. Secondly, the profitability of firms in the consumer goods and metal sector is positively impacted by long-term financing. Therefore, debt financing of assets could be more appropriate to maximize profitability in these sectors.

Analyzing the transmission of monetary policy impulses to firm profitability by clustering firms with financial flexibility across six key manufacturing sectors makes the study unique.

This paper aims to study the leverage adjustment behavior of firms distinguished based on financial flexibility. Financial flexibility is one of the key strengths of the companies to borrow funds for long-term capital investment. The lack of extensive studies in this domain motivates the authors to delve into the significance of financial flexibility in making corporate capital structure decisions.

The data comprise a combination of firm-specific and macroeconomic variables for firms in eight manufacturing sectors from 2009 to 2020. The authors employ an advance estimator, dynamic panel fraction, on the partial adjustment model to investigate the diverse impact on capital structure's speed of adjustment (SoA) between the financially flexible and financially inflexible firms. Furthermore, the authors utilize the generalized method of moments and panel-corrected standard errors to establish the robustness.

The empirical analysis reveals that the SoA of financially flexible firms lies between 19.75% and 35.38% and the SoA of financially inflexible firms lies between 11.66% and 25.81%. Due to their conserved debt capabilities, financially flexible firms can rely on leverage to stay near the target whenever they move away from it. Furthermore, financially inflexible firms exhibit a low adjustment speed due to their incompetence to borrow funds to benefit from new growth opportunities. The existence of a target ratio among the studied firms is identified from the positive coefficient of lagged dependent variable, and the relevance of trade-off theory is proved by the quick adjustment speeds in most sectors.

The sectoral distinction in the backdrop of the financial flexibility component adds to the research novelty and managerial implications.