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The purpose of this paper is to empirically investigate the factors deriving effective tax rate (ETR) for Indian manufacturing firms in different sectors. The study also tries to analyze the sensitiveness of ETR because of shocks on its key determinants.

The study is using Arellano–Bond dynamic panel regression model to identify the key drivers of ETR, and impulse response functions of panel vector auto-regression model to analyze the response of ETR because of one standard deviation (SD) shock to its key determinants.

This study concludes that ETR is significantly explained by firm size, profitability, growth rate and non-debt tax shield in most of the sectors, and debt ratio, asset tangibility and age of the firms are impacting ETR differently across sectors. In case of entire manufacturing sector, firm size, profitability, growth and non-debt tax shield are driving ETR positively and asset tangibility is driving ETR negatively. Interest coverage ratio (ICR) and firm age are not significant drivers of ETR. ETR is positively related with firm size, but responses negatively when there is an immediate shock to firm size. Similarly, ETR is negatively related with asset tangibility, but responds positively following an immediate shock to it. Overall, ETR is more sensitive and responses significantly because of shocks in firm size, profitability, growth, asset tangibility and non-debt tax shield whereas, the response is very marginal following shocks to debt ratio, ICR and age of the firm.

Firm managers may find the study useful to understand the receptiveness of ETRs at each sector level. The empirical findings are not only validating the theoretical developments but also providing a root cause analysis to the firm managers to understand the cause and consequence of ETRs for firms at different sectors.

Empirically investigating the factors driving ETR and analyzing its sensitiveness because of one SD shock on its key determinants for Indian manufacturing firms from different sectors is the originality of this study. Developing a strong theoretical background and empirically validating it through advanced methodology makes the study unique.

The purpose of this paper is to examine the short-term and long-term interdependence among the stock markets of Africa and Middle East region. It also attempts to analyze the pattern of volatility spillover among the regional stock markets.

The study has used Granger causality test, variance decomposition test of vector auto-regression (VAR) model, vector error correction model (VECM), multivariate generalized conditional heteroskedasticity (MGARCH-BEKK) models and Johansen and Juselius multivariate cointegration techniques.

The study finds that the interlinkages of the stock markets are not uniform across all the countries of the region. The stock market of Israel, South Africa and Jordan are found to be highly connected stock market of the region followed by Egypt and Botswana. The study also finds significant spillover of lagged standardized volatility across the stock markets of the region. But the magnitude of the response of volatility spillover and its persistence is very minimum. However, the stock markets are found to be co-integrated and expected to share long-run equilibrium relationships among each other.

The study has the scope to be extended to capture the time-varying integration of market returns with transmission of monetary policy and exchange rate changes within the region. The results obtained from this study may assist the firm managers and international investors to understand the key drivers of market connectedness.

Empirically investigating the pattern of stock market connectedness in Africa and Middle East region with advanced methodology over a long study period is the originality of this study.

The purpose of this paper is to empirically analyze the determinants of capital structure and their long-run equilibrium relationships with firm-specific and macroeconomic indicators for Indian manufacturing firms.

The study is conducted using the panel semi-parametric and non-parametric regression models to identify the key determinants of capital structure. Panel cointegration models are also employed for analyzing the long-run equilibrium association of capital structure with its determinants.

The study finds that each manufacturing sector has unique determinants of capital structure. The debt level is significantly affected by asset tangibility, growth opportunity, effective tax rate, non-debt tax shield, cash flow, profitability, firm size, foreign investment, government borrowing, economic growth, and interest rate. All these firm-specific and macroeconomic variables have strong long-run equilibrium relationship with capital structure as a whole.

The study analyzes the determinants of capital structure for eight manufacturing sectors of India, which helps firm managers and policy-makers to identify appropriate factors that maximize firm value. The sector-specific features of firms may lead to a new path with regard to corporate governance and ownership structure to enhance stakeholder's satisfaction.

The use of semi-parametric and non-parametric panel regression models to analyze the determinants of capital structure, and the use of panel cointegration approach to explore the long-run equilibrium relationship between the determinants and its factors are the unique contributions of the present research.

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.

The purpose of this study is to examine the evidences of leverage effects on the conditional volatility of exchange rates because of asymmetric innovations and its spillover effects among the exchange rates of selected emerging and growth-leading economies.

The empirical analysis uses the sign bias test and asymmetric generalized autoregressive conditional heteroskedasticity (GARCH) models to capture the leverage effects on conditional volatility of exchange rates and also uses multivariate GARCH (MGARCH) model to address volatility spillovers among the studied exchange rates.

The study finds substantial impact of asymmetric innovations (news) on the conditional volatility of exchange rates, where Russian Ruble is showing significant leverage effect followed by Indian Rupee. The exchange rates depict significant mean spillover effects, where Rupee, Peso and Ruble are strongly connected; Real, Rupiah and Lira are moderately connected; and Yuan is the least connected exchange rate within the sample. The study also finds the assimilation of information in foreign exchanges and increased spillover effects in the post 2008 periods.

The results probably have the implications for international investment and asset management. Portfolio managers could use this research to optimize their international portfolio. Policymakers such as central banks may find the study useful to monitor and design interventions strategies in foreign exchange markets keeping an eye on the nature of movements among these exchange rates.

This is one of the few empirical research studies that aim to explore the leverage effects on exchange rates and their volatility spillovers among seven emerging and growth-leading economies using advanced econometric methodologies.

The purpose of this paper is to track the financial performance of manufacturing firms at different levels of their conditional quantiles. It also analyzes the relevance of revenue and cost channels along with key firm-specific parameters that influence firm’s profitability.

The study analyses a sample of 1,000 manufacturing firms over a study period spanning from 2000 to 2016. It uses both quantile regression and panel ordinary linear square (OLS) models to analyze the financial performance of the firms.

The study finds large scale of heterogeneity among the firms under different quantiles of profitability. Export earnings, firm size, asset turnover and volatility of exchange rate are the decisive determinants of financial performance across all quantiles. Financing assets by current debt is negatively impacting return on assets and return on capital employed of firms from lower quantile whereas profitability is positively impacted if they are financed by long term debt. Debt financing of assets does not make any sense for firms with high quantile of profitability. The study also finds that quantile regression approach is a better method than panel OLS models in the presence of highly heterogeneous and non-normal distributions.

This study is limited to the financial performance of manufacturing firms and does not consider service sector which is also equally competitive. However, a sector wise analysis of firm’s profitability could be more meaningful than comparing all the firms in one basket of manufacturing domain.

The research findings have both practical as well as policy implications. Practically, the study helps the firm managers to identify critical success factors that significantly influence firm’s financial performance at different levels of profitability. It also helps the policy makers to align policy focus to stabilize firms at lower level of profitability and also to manage conducive business environment for all firms at different levels of their profitability.

The study provides a deep theoretical underpinning of literatures on firm’s financial performance and empirically investigates it using advanced methodology. The robust estimates of the study ensure to analyze financial performance under revenue and cost channels at diverse level of their profitability.

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.

The purpose of this paper is to examine the impact of changes in the exchange rate on long-term investment decisions of Indian manufacturing firms at the sector level.

The study is undertaken on a sample of 1,222 firms from six key manufacturing sectors of Indian economy during the period 2000-2016. The non-linear relationship between real exchange rate and long-term investment is studied using the two-step generalized model of moments estimator.

The study finds a concave (i.e. inverted U-shaped) relationship between the long-term investment and real exchange rate, particularly in case of chemical, construction, machinery and textile sector, in particular, and Indian manufacturing industry as a whole. It implies that investments in these sectors increase with depreciation of real exchange rate up to a point of inflection and subsequent to which it starts decreasing if exchange rate continues to depreciate further. But consumer goods and metal product sectors ensure a convex pattern, which demonstrates that investment is decreasing at the initial stage of depreciation of the exchange rate. The study moves one-step forward in validating this nexus between investment and exchange rate with respect to the price-cost margin and the extent of financial flexibility of firms. It is found that high price cost margin and financial flexibility moderates the adverse impact of exchange rate depreciation and immunizes the long-term investments in the scenario of a weak domestic currency and induce long-term investments.

The study measures the impact of exchange rate changes, but the impact of exchange rate volatility on investment has not been studied, which is absolutely different with different implications.

The study provides a clear guideline to firm managers for using the exchange rate movements in a favorable manner. The findings can be used to ensure sustainable long-term investments with respect to the core competence of firms in terms of price cost margin and financial flexibility at sector level of Indian manufacturing firms.

The study analyzes the non-linear relationship between exchange rate changes and long-term investment behavior of manufacturing firms from six key sectors of India. Further, the study moves one step forward to analyze this nexus under different scenarios of financial flexibility and price cost margin using dynamic panel models.

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 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.