scholarly journals Determinants of capital structure of listed firms in Vietnam: A quantile regression approach

2017 ◽  
Vol 24 (02) ◽  
pp. 114-131
Author(s):  
Canh Nguyen Thi ◽  
Liem Nguyen Thanh ◽  
Son Tran Hung
Keyword(s):  
Panel Data ◽  
Capital Structure ◽  
Quantile Regression ◽  
Linear Relationship ◽  
Firm Characteristics ◽  
Conditional Quantile ◽  
Listed Firms ◽  
Panel Data Methods ◽  
Regression Approach ◽  
Different Levels

This study empirically examines the link between firm characteristics and leverage using the data of Vietnamese non-financial listed firms from 2006 to 2015. In addition to traditional panel data methods, we employ a conditional quantile regression that unveils the behavior of regressors throughout the leverage distribution. The results confirm the non-linear relationship between firm characteristics and leverage at different levels of debt.

scholarly journals CAPITAL STRUCTURE AND ITS DETERMINANTS IN NEW ZEALAND FIRMS

2013 ◽  
Vol 14 (5) ◽  
pp. 852-866 ◽  
Author(s):  
Nirosha Hewa Wellalage ◽  
Stuart Locke
Keyword(s):  
Corporate Governance ◽  
New Zealand ◽  
Capital Structure ◽  
Quantile Regression ◽  
Stock Exchange ◽  
Firm Characteristics ◽  
Conditional Quantile ◽  
Listed Firms ◽  
Firm Type ◽  
The Relationship

The current study aims to empirically explore the relationship between firm characteristics, corporate governance and capital structure in New Zealand's large listed companies. Eight years of data for 40 firms listed on the NZX50 Stock Exchange, are collected and observations are analysed using a conditional quantile regression. This study finds firm-specific characteristics rather than corporate governance variables play a significant role in determining firm leverage levels. The results indicate that finance policies need to vary across firm type and firm characteristics, and should match with the different borrowing requirements of listed firms.

scholarly journals Capital structure determinants in South Africa: A quantile regression approach

2017 ◽  
Vol 9 (1) ◽  
pp. 275-290 ◽  
Author(s):  
Tendai Gwatidzo ◽  
Miracle Ntuli ◽  
Mthokozisi Mlilo
Keyword(s):  
South Africa ◽  
Capital Structure ◽  
Quantile Regression ◽  
South African ◽  
Predictor Variables ◽  
Regression Approach ◽  
The Mean ◽  
Using Data ◽  
Different Levels

Using data on 239 listed South African firms and covering the period 1996-2010, we apply a quantile regression approach to investigate the effect of capital structure determinants on leverage. The paper’s main contribution is to assess the effect of the predictor variables across the distribution of leverage. That is, does the effect of a capital structure determinant vary at different levels of leverage? With the exception of asset tangibility and age, whose effect increased with leverage, our results suggest that the importance of leverage determinants does not vary with leverage. This is an important result, as it suggests that for the case of South Africa, studies that estimate the correlates of leverage at the mean are still valid and appropriate.

scholarly journals Quantile Regression for Panel Data: An Empirical Approach for Knowledge Spillovers Endogeneity

2017 ◽  
Vol 9 (7) ◽  
pp. 106 ◽  
Author(s):  
Luigi Aldieri ◽  
Concetto Paolo Vinci
Keyword(s):  
Theoretical Model ◽  
Panel Data ◽  
Quantile Regression ◽  
Knowledge Spillovers ◽  
Spillover Effect ◽  
Technology Spillovers ◽  
Significant Heterogeneity ◽  
The Core ◽  
Endogenous Regressors ◽  
Different Levels

The aim of this paper is to investigate the extent to which knowledge spillovers effects are sensitive to different levels of innovation. We develop a theoretical model in which the core of spillover effect is showed and then we implement the empirical model to test for the results. In particular, we run the quantile regression for panel data estimator (Baker, Powell, & Smith, 2016), to correct the bias stemming from the endogenous regressors in a panel data sample. The findings identify a significant heterogeneity of technology spillovers across quantiles: the highest value of spillovers is observed at the lowest quartile of innovation distribution. The results might be interpreted to provide some useful implications for industrial policy strategy.

scholarly journals Does corporate ownership affect capital structures and adjustment of capital structures — evidences from Chinese listed companies

2009 ◽  
Vol 6 (4) ◽  
pp. 532-541 ◽  
Author(s):  
Zhengwei Wang ◽  
Wei Lin ◽  
Michael Keefe
Keyword(s):  
Capital Structure ◽  
Transition Economy ◽  
Structural Difference ◽  
Firm Characteristics ◽  
Financial Friction ◽  
Listed Firms ◽  
Optimal Capital Structure ◽  
Study Results ◽  
Optimal Capital ◽  
The Difference

In Chinese transition economy, compared with state-owned firms, private firms face higher financial friction in financing activities, but have more incentive to adjust toward optimal capital structure to maximize the shareholders‟ benefit. Based on panel data of China’s listed firms from 1998 to 2007, we compare the capital structures of state-owned and privately-owned listed firms. The empirical results show that there is structural difference in static capital structure between state-owned and private listed firms while controlling for firm characteristics. We then investigate the difference in dynamics of the capital structure between these two groups of firms. Further study results tell us that the adjustment to an optimal capital structure to be faster for the private firm than for the state-owned firm.

A quantile regression approach to trail financial performance of manufacturing firms

2019 ◽  
Vol 20 (3) ◽  
pp. 290-310
Author(s):  
Swagatika Nanda ◽  
Ajaya Kumar Panda
Keyword(s):  
Quantile Regression ◽  
Financial Performance ◽  
Large Scale ◽  
Service Sector ◽  
Business Environment ◽  
Manufacturing Firms ◽  
Policy Implications ◽  
Content Type ◽  
Regression Approach ◽  
Different Levels

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

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