Determinants of capital structure: an empirical study of manufacturing firms in India

2017 ◽  
Vol 59 (6) ◽  
pp. 1029-1045 ◽  
Author(s):  
Rajni Sofat ◽  
Sukhdev Singh
Keyword(s):  
Capital Structure ◽  
Multiple Regression Model ◽  
Manufacturing Firms ◽  
Debt Ratio ◽  
Business Risk ◽  
Service Capacity ◽  
Pecking Order ◽  
Return On Assets ◽  
Risk And Return ◽  
Content Type

Purpose The purpose of this paper is to explore the most significant determinants of capital structure of manufacturing firms in India and to investigate whether the capital structure models derived from foreign research provide convincing explanations for capital structure decisions of Indian firms by using multiple regression model. Design/methodology/approach Different conditional theories of capital structure like trade off theory, pecking order theory and agency theory are reviewed to formulate testable propositions concerning determinants of capital structure of manufacturing firms. Multiple regression model and correlation matrix have been used as statistical tools to investigate the most significant determinants of capital structure of manufacturing firms in India with the help of SPSS Software for a sample of top 100 manufacturing firms listed in BSE. Findings The results suggest that variables like asset composition, business risk and return on assets are positively related to debt ratio whereas firm size and debt service capacity are negatively related to debt ratio. The asset composition, business risk and return on assets appear to be significant determinants of capital structure, while firm size and debt service capacity are insignificant determinants. Research limitations/implications The findings of this study are consistent with predictions of trade off, pecking order and agency theory of finance which helps in understanding financing behaviour of firms in India. Practical implications This study has laid some ground work to explore the determinants of capital structure of Indian firms upon which a more detailed evaluation could be based. Furthermore, empirical findings should help corporate managers to make optimal capital structure decisions. Originality/value To the authors’ knowledge, this study is the first that explores the most significant determinants of capital structure of manufacturing firms in India by using the most recent data. Moreover, this study also confirms that same factors affect the capital structure decisions of firms in developing countries as identified for firms in developed economies.

Capital structure decisions: What Spanish CFOs think

2018 ◽  
Vol 31 (2) ◽  
pp. 306-325 ◽  
Author(s):  
Pablo de Andrés ◽  
Gabriel de la Fuente ◽  
Pablo San Martin
Keyword(s):  
Capital Structure ◽  
Design Methodology ◽  
Debt Ratio ◽  
Pecking Order ◽  
Academic World ◽  
Financial Flexibility ◽  
Content Type ◽  
Internal Funds ◽  
Internal Financing ◽  
Research Show

PurposeThe way business practice adjusts to the models proposed by financial theory has been under moderate yet constant scrutiny from the academic world. The purpose of this paper is to contribute to this line of research by showing CFOs’ perceptions of Spanish companies with regard to their capital structure decisions.Design/MethodologyThe empirical approach is examined using information gathered through a survey answered by 140 CFOs of Spanish companies during 2011. Results are obtained from mean difference tests and ordered probit estimations.FindingsThe results of the paper show that managers attach importance to establishing and monitoring a target debt ratio and the capacity to maintain additional debt in order to provide financial flexibility. In addition, CFOs prefer internal financing to external, using debt when internal funds do not allow investments to be funded.Originality/ValueOn the whole, the results of this research show that trade-off and pecking order theories are not alternative views of the same problem, but represent complementary approaches of how companies define their capital structures.

scholarly journals Determinants of capital structure: evidence from Jordanian service companies

2020 ◽  
Vol 17 (2) ◽  
pp. 364-376
Author(s):  
Omar K. Gharaibeh ◽  
Saqer AL-Tahat
Keyword(s):  
Capital Structure ◽  
Secondary Data ◽  
Agency Cost ◽  
Debt Ratio ◽  
Business Risk ◽  
Pecking Order ◽  
Tax Shield ◽  
Service Companies ◽  
Tax Shields ◽  
The Capital Structure

This paper examines capital structure determinants for service companies in Jordan between 2014 and 2018. Secondary data from 45 companies were analyzed using the panel regression approach. The results show that the independent variables, suggested as capital structure determinants, have an effect on the debt ratio made by the service companies. Size and non-debt tax shield have a positive significant effect on the debt ratio, while profitability and business risk have a negative significant impact on the debt ratio. In general, the findings support the notion that the trade-off, bankruptcy cost, agency cost and pecking order theories are crucial in explaining the capital structure of Jordanian service companies except for non-debt tax shields and tangibility factors. Jordanian service companies do not use fixed assets as collateral or companies with higher collateral value tend to borrow less debt. Although the coefficient of institutional investors is statistically insignificant, it is still negative and economically significant. This paper concludes that size, profitability, business risk, non-debt tax shields and institutional ownership factors are fundamental in terms of shaping the capital structure in Jordanian service companies.

Determinants Of Capital Structure For Multinational And Domestic Companies In India: Panel Data Regression Model

2019 ◽  
Vol 118 (7) ◽  
pp. 147-154
Author(s):  
K. Maheswari ◽  
Dr. J. Gayathri ◽  
Dr. M. Babu ◽  
Dr.G. Indhumathi
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Regression Model ◽  
Business Risk ◽  
Return On Assets ◽  
Panel Data Regression ◽  
Data Regression ◽  
Return On Capital ◽  
Domestic Companies ◽  
The Capital Structure

The capital structure refers to the components of capital needed to establish and expand its business activities. The study was made with an objective to examine the determinants of capital structure of multinational and domestic companies listed in S&P BSE automobile sector. The study concluded that there is significant impact on capital structure determinants such as size, business risk, non debt shield tax, return on assets, tangibility, profit, return on capital employed and liquidity on the capital structure of multinational and domestic companies of Indian Automobile Sector.  

Financial Leverage and its Determinants: Evidence from Indian Cement Industry

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Anupam De ◽  
Arindam Banerjee
Keyword(s):  
Growth Rate ◽  
Capital Structure ◽  
Firm Growth ◽  
Stock Exchange ◽  
Debt Service ◽  
Cement Industry ◽  
Business Risk ◽  
Service Capacity ◽  
Independent Variables ◽  
The Capital Structure

In this study an attempt has been made to examine the determinants of capital structure in companies belonging to the Cement Industry of India. The companies listed in the Bombay Stock Exchange (BSE) and National Stock Exchange (NSE) has been used for the study. The study has been conducted for the period from 1999-2000 to 2010-2011. To study the influence of various independent variables on the capital structure, Multiple Regression Analysis has been carried out taking the ratio of average total debt to average total assets as dependent variable and seven variables, which might have some impact on the capital structure, as independent variables. These seven variables are namely business risk, size of the firm, growth rate, debt service capacity, degree of operating leverage, dividend payout, and earning rate. It is observed from the study that size of the firm, debt service capacity, business risk and growth rate are statistically significant to have an influence in taking capital structure related decisions and considered as determinants of capital structure of the listed companies belonging to the Indian Cement

Mean reversion in corporate leverage: evidence from India

2019 ◽  
Vol 45 (9) ◽  
pp. 1183-1198
Author(s):  
Gaurav S. Chauhan ◽  
Pradip Banerjee
Keyword(s):  
Capital Structure ◽  
Emerging Market ◽  
Simulated Data ◽  
Mean Reversion ◽  
Developed Countries ◽  
Data Sets ◽  
Debt Ratio ◽  
Testing Strategy ◽  
Content Type ◽  
Financing Behavior

Purpose Recent papers on target capital structure show that debt ratio seems to vary widely in space and time, implying that the functional specifications of target debt ratios are of little empirical use. Further, target behavior cannot be adjudged correctly using debt ratios, as they could revert due to mechanical reasons. The purpose of this paper is to develop an alternative testing strategy to test the target capital structure. Design/methodology/approach The authors make use of a major “shock” to the debt ratios as an event and think of a subsequent reversion as a movement toward a mean or target debt ratio. By doing this, the authors no longer need to identify target debt ratios as a function of firm-specific variables or any other rigid functional form. Findings Similar to the broad empirical evidence in developed economies, there is no perceptible and systematic mean reversion by Indian firms. However, unlike developed countries, proportionate usage of debt to finance firms’ marginal financing deficits is extensive; equity is used rather sparingly. Research limitations/implications The trade-off theory could be convincingly refuted at least for the emerging market of India. The paper here stimulated further research on finding reasons for specific financing behavior of emerging market firms. Practical implications The results show that the firms’ financing choices are not only depending on their own firm’s specific variables but also on the financial markets in which they operate. Originality/value This study attempts to assess mean reversion in debt ratios in a unique but reassuring manner. The results are confirmed by extensive calibration of the testing strategy using simulated data sets.

scholarly journals Factors Explaining Debt Firm Policy: A Comparison between Five Intercontinental Countries

2017 ◽  
Vol 7 (1) ◽  
pp. 285
Author(s):  
Ben Said Hatem
Keyword(s):  
South Africa ◽  
Capital Structure ◽  
Firm Growth ◽  
Debt Ratio ◽  
Firm Age ◽  
Growth Opportunities ◽  
Short Term ◽  
Return On Assets ◽  
Debt Policy

We test the factors explaining the debt policy of firms across five continents. To this end, we examine samples from South Africa, Australia, Brazil, India and Spain over a period of 8 years from 2003 to 2010. The results manipulate differences in debt policy for all countries (except for the variable Return on Assets, ROA). As for the effect of activity sectors on firm debt policy, higher performance led to lower firm debt ratios. Furthermore, we concluded some differences in other variables. Higher tangibility ratios for firms from South Africa, India and Spain led to higher capital structure ratios. Larger firms from Brazil led to lower short term debt ratio. We could not find evidence on the effect of firm growth opportunities in Brazil and India. Furthermore, we concluded to a positive and a statistically significant effect of liquidity ratio for Australia and India, and a positive and a statistically significant effect of firm age for firms from Spain.

scholarly journals New evidences on determinants of capital structure from the Indian manufacturing industry

2016 ◽  
Vol 13 (3) ◽  
pp. 82-88 ◽  
Author(s):  
Pradeepta Sethi ◽  
Ranjit Tiwari
Keyword(s):  
Capital Structure ◽  
Manufacturing Industry ◽  
Order Theory ◽  
Manufacturing Firms ◽  
Indian Government ◽  
Pecking Order ◽  
Pecking Order Theory ◽  
Optimal Capital Structure ◽  
Financing Decisions ◽  
Size Growth

In the backdrop of Make in India push by Indian government the purpose of this study is to examine the determinants of capital structure towards a better understanding of financing decisions to be undertaken by the Indian manufacturing firms. The data for the analysis is drawn from COSPI manufacturing index of Centre for Monitoring Indian Economy (CMIE). Our sample is an unbalanced panel of 1077 firms over the period 2000-01 to 2012-13. We apply system-GMM to study different factors that affect the leverage decision of firms in India. The findings of the study reveals that the choice of optimal capital structure can be influenced by factors such as profitability, size, growth, tangibility, non-debt tax shields, uniqueness and signal. We also find the existence of both pecking order theory and static trade-off theory in the case of Indian manufacturing firms. The results thus obtained are robust across the different proxies of leverage

Do Capital Structure Models Square with the Dynamics of Payout?

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Shiqi Chen ◽  
Bart M. Lambrecht
Keyword(s):  
Capital Structure ◽  
Annual Review ◽  
Publication Date ◽  
Debt Ratio ◽  
Net Income ◽  
Income Shocks ◽  
Pecking Order ◽  
Negative Relation ◽  
Asset Volatility ◽  
Target Leverage

We explore whether theoretically the target leverage and pecking-order models can be reconciled with payout smoothing. Investment absorbs a significant part of income and asset volatility if the firm follows both a payout target and a net debt ratio (NDR) target. A positive (negative) NDR amplifies (dampens) shocks in assets. Slow adjustment toward the NDR target facilitates payout smoothing. Under strict pecking-order financing, income shocks are absorbed primarily by changes in net debt. More payout smoothing implies a stronger negative relation between debt and net income. Shocks to assets in place need not affect current payout. Expected final online publication date for the Annual Review of Financial Economics, Volume 13 is November 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Do DJIA Firms Reflect Stationary Debt Ratios?

Economies ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 76
Author(s):  
Feng-Li Lin
Keyword(s):  
Capital Structure ◽  
Stationary Processes ◽  
Debt Ratio ◽  
Pecking Order ◽  
Trade Off ◽  
Listed Firms ◽  
Growth Opportunity ◽  
Dow Jones Industrial Average ◽  
The Mean ◽  
The Stability

To form optimum firm capital structure strategies to face unanticipated economic events, firm managers should understand the stability of a firm’s capital structure. The aim of this research was to study whether the debt ratio is stationary in listed firms on the Dow Jones Industrial Average (DJIA). Two vital capital structure concepts regarding pecking order and trade-off theory are fairly contradictory. Using opposing theoretical contexts, the Sequential Panel Selection Method apparently categorizes which and how many series are stationary processes in the panel. This method was used to test the mean reverting properties of the 25 companies listed on Dow Jones Industrial Average between 2001 and 2017 in this study, which is expected to fill the current gap in the literature. The overall results show that stationary debt ratios exist in 10 of the 25 studied firms, supporting the trade-off theory. Moreover, the 10 firms utilizing trade-off theory are affected by firm size, profitability, growth opportunity, and dividend payout ratio. These results provide vital information for firms to certify strategies to optimize capital structure.

Receptiveness of effective tax rate to firm characteristics: an empirical analysis on Indian listed firms

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ajaya Kumar Panda ◽  
Swagatika Nanda
Keyword(s):  
Regression Model ◽  
Firm Size ◽  
Manufacturing Firms ◽  
Debt Ratio ◽  
Effective Tax Rate ◽  
Content Type ◽  
Tax Rate ◽  
Tax Shield ◽  
Dynamic Panel Regression ◽  
Debt Tax Shield

Purpose 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. Design/methodology/approach 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. Findings 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. Research limitations/implications 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. Originality/value 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.

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