Effects of Firm Size, Financial Leverage and R&D Expenditures on Firm Earnings: An Analysis Using Quantile Regression Approach

Abstract

As documented in the literature, the effects of firm size, financial leverage, and R&D expenditures on firm earnings are inclusive. Our hypothesis is that the inconsistent empirical results of such effects may be driven by the regression models implemented in data analysis. Using the quantile regression (QR) approach developed by Koenker and Basset (1978), this study analyses S&P 500 firms from 1996 to 2005. We find that the effects of firm size, financial leverage and R&D expenditures on firm earnings differ considerably across earnings quantiles. Comparing the results from the QR approach with those from the ordinary least squares (OLS) and least absolute deviation (LAD) methods, this study further explains the puzzling relationship between firm size, financial leverage, R&D expenditures and firm earnings.

Effect of Financial Leverage on Firm Value: Evidence From Selected Firms Quoted on the Nigerian Stock Exchange

“…This work will thus adopt both the Random Effect Panel Data Estimation Technique (REM) and the Pooled Ordinary Least Squares (POLS) estimation techniques to determine the values of the parameters of the firm value model which has the Tobin's Q (a proxy of firm value) as the dependent variable and the primary explanatory variable being Leverage. Total Asset, ROA, AGE, were include within the model as mediating variable, in line with existing literature such as Li & Hwang (2011) the variables are imputed into the model after their logarithmic transformations are obtained this is so as to remove the effect of outliers.…”

The effect of ex ante and ex post conservatism on the cost of equity capital: A quantile regression approach for MENA countries

“…The quantile regression approach has been widely used in economic literature, financial research, corporate governance and other fields outside management sciences. For example Arias et al (2001), Buchinsky (1994 and and Eide and Mark (1998) in education economics, Chernozhukov and Umantsev (2001) and Engle and Manganelli (2004) in Value at Risk, Barnes and Highes (2002) in cross-section of stock market return, Basset and Chen (2001) in mutual fund investment styles, Meligkotsidou and Vrontos (2009) in hedge fund strategies, Li and Miu (2010) in bankruptcy prediction, Barreto and Hughes (2004) in economic growth studies, Li and Hwang (2011) in accounting earnings, Ramdani and Witteloostuijn (2010) in corporate governance, Buchinsky (1994), Garcia et al (2001), Machado and Mata (2001) and Nielsen and Rosholm (2001) in wage analysis. The present study represents the first study that applies the quantile regression in accounting conservatism and the quality of financial reporting literature.…”

Heterogeneous Effect of Financial Leverage on Corporate Performance: A Quantile Regression Analysis of Taiwanese Companies

“…So as to appraise if the estimate parameters of using QR model might be biased as a result of a missing-variables issue, we now afford results obtained by covering several variables in our quantile regression model. Following Murphy et al (1996) and Li and Hwang (2011), we count four liquidity ratios: current ratio (current assets divided by current liabilities), accounts receivable turnover ratio (net sales divided by average accounts receivable), inventory turnover ratio (cost of goods sold divided by average inventory) and total asset turnover ratio (net sales divided by total assets). We cover these liquidity-ratio variables to treat as control variables in our model.…”