Manuscript Title:

DETERMINANTS AND CHANGES OF LABOUR FORCE PARTICIPATION IN MALAYSIA: A CASE STUDY ON LIVING STRATA PERSPECTIVE

Author:

LIM BAO MAN, NUZLINDA ABDUL RAHMAN, ZAINUDIN ARSAD

DOI Number:

DOI:10.17605/OSF.IO/TK9RA

Published : 2021-10-10

About the author(s)

1. LIM BAO MAN - School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia
2. NUZLINDA ABDUL RAHMAN - School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia
3. ZAINUDIN ARSAD - School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia

Full Text : PDF

Abstract

Labour Force Participation rate (LFPR) play an important role in economy of Malaysia. This study provides an overview of how the labour force factors will affect LFPR for each state in Malaysia on living strata from the year 2011 to 2016. There are a few of Static Panel data analysis, such as Random effect model (REM), Fixed effect model (FEM) and Pooled Ordinary Least Square (POLS) are employed in this study. The results show that FEM is used to estimate the effect of determinants and characteristics of LFPR on urban and rural. The factors such as married, outside labour force and primary, secondary, tertiary education level show a positive relationship with urban LFPR. While the age group 15-39 and 40-64 shown a negative relationship with urban LFPR. On the flip side, the nonmarried labour forces show significant and have negative relationship with the rural LFPR. Fixed effect Least Square Dummy Variables (FE-LSDV) is applied to investigate the time-effect and the states-effect. The results show FEM for urban and rural do not have time-effect but have only states – Fixed effect (Specific Effect of LSDV). In conclusion, it is important to understand the LFPR according to living strata for each state of Malaysia because it will shape the comparative advantage and situation of Malaysia labour market.


Keywords

Fixed Effect Model, Fixed Effect Least Square Dummy Variables, Labour force participation rate, Panel Data Analysis, Random Effect Model.