scholarly journals A study about the determinant factors of the capital structure of Brazilian companies: a quantile regression analysis

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Osvaldo Martins Quintella Junior ◽  
Claudio Ulysses Ferreira Coelho
Keyword(s):  
Regression Analysis ◽  
Capital Structure ◽  
Quantile Regression ◽  
Relevant Variables ◽  
Quantile Regression Analysis ◽  
Data Inference ◽  
Quantile Regression Method ◽  
The Relationship ◽  
The Capital Structure

Purpose: The present paper aims to analyses the determinants of capital structure of ninety-four organizations from the five hundred largest Brazilian companies according to 2018 Exame magazine yearbook. Methodology: For this research we used information from financial statements of the five hundred largest Brazilian companies.  Data inference was made through descriptive statistical analysis and quantile regression analysis. The data was obtained through the companies’ websites and through economática software. The descriptive and econometric analysis were performed using Stata 12 software. Results: The results indicate that the variables such as size and structure of the assets are significant in some quantiles to determine how companies adopt a particular capital structure. In addition, the results indicate the relationship between firm size and total debt level is positive for 25th quantile of the sample. Another point to note is that the asset structure variable has a positive relationship with the long-term debt variable for the 75th and 95th quantiles. Contributions of the study: This research is an important contribution for finance literature considering that the quantile regression method was used. The scarcity of research using this method is notorious. Moreover, the results obtained in other works on the subject are not yet convergent about the relevant variables to determine the capital structure.

scholarly journals Determinants of Capital Structure: A Quantile Regression Analysis

2015 ◽  
Vol 10 (1) ◽  
pp. 16-34 ◽  
Author(s):  
Kumar Tiwari Aviral ◽  
Krishnankutty Raveesh
Keyword(s):  
Regression Analysis ◽  
Panel Data ◽  
Capital Structure ◽  
Quantile Regression ◽  
Negative Sign ◽  
Positive Sign ◽  
Quantile Regression Analysis ◽  
The Capital Structure

Abstract In this study, we attempted to analyze the determinants of capital structure for Indian firms using a panel framework and to investigate whether the capital structure models derived from Western settings provide convincing explanations for capital structure decisions of the Indian firms. The investigation is performed using balanced panel data procedures for a sample 298 firms (from the BSE 500 firms based on the availability of data) during 2001-2010. We found that for lowest quantile LnSales and TANGIT are significant with positive sign and NDTS and PROFIT are significant with negative sign. However, in case of 0.25th quantile LnSales and LnTA are significant with positive sign and PROFIT is significant with negative sign. For median quantile PROFIT is found to be significant with negative sign and TANGIT is significant with positive sign. For 0.75th quantile, in model one, LnSales and PROFIT are significant with negative sign and TANGIT and GROWTHTA are significant with positive sign whereas, in model two, results of 0.75th quantile are similar to the median quantile of model two. For the highest quantile, in case of model one, results are similar to the case of 0.75th quantile with exception that now GROWTHTA in model one (and GROWTHSA in model two).

scholarly journals Statistical Analysis of Causality between Capital Structure and Firm Profitability: Evidence from Bosnia and Herzegovina

2015 ◽  
Vol 1 (1-2) ◽  
pp. 1-11
Author(s):  
Emina Resić ◽  
Jasmina Mangafić ◽  
Tunjo Perić
Keyword(s):  
Capital Structure ◽  
Bosnia And Herzegovina ◽  
Canonical Correlation ◽  
Debt Structure ◽  
Short Term ◽  
The Relationship ◽  
Structure Choice ◽  
Capital Structure Choice ◽  
The Capital Structure

Abstract This research is designed to examine the relationship between the capital structure and profitability of non-financial firms in Bosnia and Herzegovina during the ten years period, from 2003-2012. The goal is to prove the existence of the relationship between the firm’s capital structure choice and its profitability. The analysis is extended by including the debt structure and differentiating between the types of debt such as the long-term and the short-term ones. Canonical correlation and multiple regression analysis are used. The results of the multivariate canonical correlation analysis provide support to a hypothesis that the capital structure and profitability have statistically significant relationships. Furthermore, the findings provide support that firms develop different patterns of profitability depending on the capital structure choice. We found that an increasing proportion of short-term debt and long-term debt in the overall liability of the firm reduces its profitability.

scholarly journals Hubungan Struktur Modal Dan Profitabilitas: Analisis Perusahaan Infrastruktur pada Indonesian Stock Exchange Tahun 2012-2016

2019 ◽  
Vol 7 (2) ◽  
Author(s):  
Eddy Winarso, Francis M. Hutabarat
Keyword(s):  
Regression Analysis ◽  
Capital Structure ◽  
Significant Relationship ◽  
Stock Exchange ◽  
Statistical Software ◽  
Return On Equity ◽  
Correlation And Regression Analysis ◽  
Auto Correlation ◽  
The Relationship ◽  
The Capital Structure

The purpose of this research is to analyze the relationship between capital structure and profitability of infrastructure companies listed in SMINFRA18 on the Indonesia Stock Exchange from 2012-2016. The advantage of an appropriate capital structure can help companies to grow primarily in the profits of their companies. This research is descriptive-correlation and quantitative approach. The data used in this study is the Capital Structure and Profitability Data of Infrastructure Companies in the Indonesia Stock Exchange which are members of the SMINFRA Index. There are 18 companies listed in the index which are the best companies in the infrastructure industry. The ratio used to describe the capital structure is Debt to Equity and the profitability ratio used is Return on Equity. This study uses statistical software to analyze: Auto-correlation, Multicollinearity, Normality, Heterocedascity, Correlation, and Regression analysis. Thus, the results of the study show that there is a significant relationship between capital structure and profitability in the SMINFRA18 Infrastructure Company listed on the Indonesia Stock Exchange.Keywords: Capital Structure, Profitability, Infrastructure, return on equity

scholarly journals Struktur Modal: Ditinjau dari Karakteristik Perusahaan yang Terdaftar di Jakarta Islamic Index 70 (JII70)

2019 ◽  
Vol 7 (2) ◽  
pp. 263
Author(s):  
Bayu Tri Cahya ◽  
Siti Nafiah ◽  
Suparwi Suparwi ◽  
Danang Kurniawan
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Capital Structure ◽  
Multiple Linear Regression ◽  
Research Design ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Retained Earnings ◽  
The Capital Structure

<p>Capital structure is a combination of long-term debt and the company's own capital in the form of retained earnings and the issuance of shares. This study aims to determine the effect of size, asset structure, and profitability on the capital structure of companies registered in the Jakarta Islamic Index 70. Jakarta Islamic Index 70 (JII70) is a sharia stocks index that was just launched in 2018. This research design is quantitative. The population in this study is companies listed on the Jakarta Islamic Index 70 during the 2018 period. The sample in this study was 51 company stocks. The techniques in this study are classic assumptions and multiple linear regression analysis. The results of this study indicate that the Asset Structure affects the capital structure. While profitability and size do not affect capital structure.</p>

scholarly journals The Determinants of Debt Load for Companies in Emerging Markets

2021 ◽  
Vol 15 (3) ◽  
pp. 39-59
Author(s):  
Mark Klestov ◽  
Irena Jindřichovská
Keyword(s):  
Regression Analysis ◽  
Emerging Markets ◽  
Capital Structure ◽  
Explanatory Power ◽  
Load Level ◽  
Corporate Capital ◽  
Corporate Capital Structure ◽  
Relevant Variables ◽  
A Company

Corporate capital structure is one of the key elements of long-term development, which determines the company value.Consequently, defining the factors that influence the debt load level of a company and, hence, its capital structure is also of great importance. In this paper we have collected a sample of data of 753 Russian companies and 292 Brazilian companies for 2020 to evaluate the influence of various factors on their debt-load level. The data was downloaded from Bloomberg database and the basis of the analysis focuses on evaluation of conventional academic theories on capital structure, and a regression analysis based on variables extracted from a set of original hypotheses. Among our results, our analysis illustrates that individual sets of determinants differ significantly in explanatory power, and operate unequally when contrasting Russian companies and Brazilian ones. Additionally, it was established that when companies define their debt load, they do not limit themselves to a single theory of capital structure. We conclude, inter alia, that it is impossible to identify with confidence which of the examined theories companies are most likely to follow in their actions, because observed interrelations between relevant variables and debt load have indications of various academic theories.

scholarly journals Bayesian quantile regression analysis for continuous data with a discrete component at zero

2017 ◽  
Vol 18 (1) ◽  
pp. 73-93 ◽  
Author(s):  
Bruno Santos ◽  
Heleno Bolfarine
Keyword(s):  
Regression Analysis ◽  
Quantile Regression ◽  
Durable Goods ◽  
Continuous Distribution ◽  
Real Data ◽  
Discrete Component ◽  
Bayesian Quantile Regression ◽  
Conditional Quantiles ◽  
Quantile Regression Analysis ◽  
Quantile Regression Method

In this work, we propose a Bayesian quantile regression method to response variables with mixed discrete-continuous distribution with a point mass at zero, where these observations are believed to be left censored or true zeros. We combine the information provided by the quantile regression analysis to present a more complete description of the probability of being censored given that the observed value is equal to zero, while also studying the conditional quantiles of the continuous part. We build up a Markov Chain Monte Carlo method from related models in the literature to obtain samples from the posterior distribution. We demonstrate the suitability of the model to analyse this censoring probability with a simulated example and two applications with real data. The first is a well-known dataset from the econometrics literature about women labour in Britain, and the second considers the statistical analysis of expenditures with durable goods, considering information from Brazil.

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