The Capital Structure of Sri Lankan Companies: A Quantile Regression Analysis

2014 ◽  
Vol 15 (3) ◽  
pp. 211-230 ◽  
Author(s):  
Nirosha Hewa Wellalage ◽  
Stuart Locke
Keyword(s):  
Regression Analysis ◽  
Capital Structure ◽  
Quantile Regression ◽  
Sri Lankan ◽  
Quantile Regression Analysis ◽  
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 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 Association between leukocyte telomere length and sex by quantile regression analysis

2021 ◽  
Author(s):  
Fernanda Gutierrez-Rodrigues ◽  
Raquel M. Alves-Paiva ◽  
Natália F. Scatena ◽  
Edson Z. Martinez ◽  
Priscila S. Scheucher ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Quantile Regression ◽  
Telomere Length ◽  
Leukocyte Telomere Length ◽  
Quantile Regression Analysis

Determinants of liquidity in Malaysian SMEs: a quantile regression approach

2018 ◽  
Vol 67 (9) ◽  
pp. 1566-1584 ◽  
Author(s):  
Shaista Wasiuzzaman
Keyword(s):  
Regression Analysis ◽  
Quantile Regression ◽  
Emerging Market ◽  
Developed Countries ◽  
Data Availability ◽  
Firm Level ◽  
Liquidity Management ◽  
Ols Regression ◽  
Content Type ◽  
Quantile Regression Analysis

PurposeThe management of liquidity has always been seen as a critical but often ignored issue in finance. Despite the abundance of studies on liquidity management, these studies mainly focus on developed countries and on large firms. Liquidity is critical for the small firm but studies on liquidity management in small and medium enterprises (SMEs) are lacking. The purpose of this paper is to examine the firm-level determinants of liquidity of SMEs in Malaysia.Design/methodology/approachData are collected for a total of 986 small firms in Malaysia from 2011 to 2014, resulting in a total of 2,683 observations. Firm-specific variables and the effect of the economy are considered as the possible determinants of liquidity. Ordinary least squares (OLS) regression analysis with standard errors adjusted for firm-level clustering and quantile regression analysis are used for this purpose.FindingsAnalysis using OLS regression technique indicates that a firm’s profitability, its growth, asset tangibility, size, age and firm status are significant factors in influencing its liquidity decision. Leverage and economic condition are not found to have any significant influence on liquidity. However, quantile regression analysis provides a different picture especially for SMEs with liquidity at the quantile levels ofθ=0.10 and 0.90. Atθ=0.10, only profitability, tangibility and firm status are significant, while atθ=0.90, tangibility, size, firm status and, to some extent, age are significant in influencing liquidity levels.Originality/valueTo the author’s knowledge, this is the first study analyzing the liquidity decision of SMEs in an emerging market such as Malaysia. Most studies on liquidity management of SMEs are focused on developed countries due to data availability but these studies are also only a handful. Additionally, this study uses quantile regression analysis which highlights the need to analyze financial decisions at different levels rather than at the aggregate level as done in OLS regression analysis.

Absenteeism and performance in a quantitative module A quantile regression analysis

2016 ◽  
Vol 8 (3) ◽  
pp. 376-389 ◽  
Author(s):  
Pranab Kumar Pani ◽  
Pallavi Kishore
Keyword(s):  
Regression Analysis ◽  
Academic Performance ◽  
Learning Styles ◽  
Quantile Regression ◽  
United Arab Emirates ◽  
Classroom Environment ◽  
Negative Impact ◽  
Content Type ◽  
Quantile Regression Analysis ◽  
And Performance

Purpose – There is growing evidence that learning is faster, measurably better and more productive in a classroom setting when a student attends classes regularly. Each student brings in his/her experience, skills, and unique learning styles to a class – thus a classroom environment can potentially create positive externalities through which a student can gain substantially from various strengths of his/her peers. However, students do remain absent from their classes for a variety of reasons. One of the measurable effects of regular non-attendance in a university class, where students from various cultures and regions interact, is the academic performance. The purpose of this paper is to determine if there is any potential causal link between absenteeism (attendance) and academic performance. Design/methodology/approach – Data were culled from the records of three batches of students in a British university campus in the Middle East. Quantile regression methods were used to establish the causal relationship between absenteeism and academic performance. Findings – A quantile regression analysis reveals that absenteeism has negative impact on academic performance. This also suggests that low performers are worse affected by absenteeism as compared to the high performers. Research limitations/implications – Inclusion of some other factors, such as study habits, additional hours spent on quantitative modules, student’s ethnicity background, particularly in the context of United Arab Emirates, could have emboldened the robustness of the study. Non-availability or paucity of this information, to some degree, has limited the conclusions of this study. Originality/value – Proponents of mandatory attendance argue that there is a positive correlation between attendance and performance. But, one very important issue which gets overlooked is who actually benefits more by attending classes – are the shirkers who have a poor attendance record or the ones who are more sincere, more regular, and active participants in a class? This study uses quantile regression analysis to address this issue.

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