Jurnal Ekonomi Malaysia
49 (1) 2015 37 – 48
Pusat Pengajian Ekonomi
Fakulti Ekonomi dan Pengurusan
Universiti Kebangsaan Malaysia
43600 Bangi Selangor
MALAYSIA
Pusat Pengajian Ekonomi
Fakulti Ekonomi dan Pengurusan
Universiti Kebangsaan Malaysia
43600 Bangi Selangor
MALAYSIA
Abstract
Human capital theory postulates that human capital investment has positive impact on wages. Training as one of the human capital components is important for providing the workforce with the necessary skills, enhancing workers skills and productivity and hence raising their wages. The objective of this paper is to investigate the degree to which workrelated training affect the location, scale and shape of the conditional wage distribution using quantile regression (QR) approach. Using data from the Workers’ Competitiveness Survey conducted in the year 2007/2008, we utilize both ordinary least squares (OLS) and QR regression techniques to estimate associations between work-related training and wages for selected services subsectors in Malaysia. The results show that the association between number of training attended and wages are dissimilar across the five quantiles. The training affects not only the location but the scale and the shape of the conditional wages distribution. We also observe positive and significant training effects as well as symmetrical-sloping profiles across quantiles of the conditional wages distribution.
Keywords
Similar Articles
- Analysis of Glass Ceiling and Sticky Floor Effects for Gender Wage Gap in Malaysian Labour Market
- The Incidence and the Effect of Overskilling on Individuals’ Wages in Malaysia: A Quantile Regression Approach
- Do Cost of Training, Education Level and R&D Investment Matter towards Influencing Labour Productivity?
Bibliography
@article{liew2015impact,
title={The Impact of Training on the Conditional Wage Distribution in Selected Service Subsectors in Malaysia},
author={Siang, Liew and Noor, Zulridah},
journal={Jurnal Ekonomi Malaysia},
volume={49},
number={1},
pages={37—48},
}
Receive updates when new articles are published.