Social, human and job characteristics as the determinants of wages and gender discrimination in Syria: direct and indirect effects

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe issue of gender wage differentials has long been of interest not only to economists, but also to governments and policy makers. In the last few decades, the labour market outcomes for females seem to be improving; however, the gender pay gap persists globally and females still earn significantly less than males. However, labour market discrimination has not received the research attention it deserves in developing countries in general, and in Syria in particular. A wide variety of factors could influence the gender pay gap, such as human capital, job characteristics and social factors. In the Syrian context, social and cultural factors play an important role in determining the position of females in the labour market. However, most previous studies have ignored the effects of social factors on other variables. Therefore, this research investigates the indirect effect of social factors on wages through human capital and job characteristics. This thesis has two main aims: to examine the main determinants of earnings for men and women in Syria, and to investigate the existence and extent of discrimination in the observed gender wage differentials there. To achieve this, two methods were used. Firstly, the Mincerian wage equations were used to analyse gender wage determinants, then discrimination was estimated using Oaxaca’s decomposition. Secondly, General Linear Modelling (GLM) Univariate ANOVA was tested to reveal the main and interaction effects of the factors specified in the theoretical model. The data used in this research came from the Syrian Labour Force Survey (LFS) 2010 conducted by the Government through the Central Bureau of Statistics. The results indicated that human capital variables were vital in explaining individuals’ earnings. Also, job characteristics and social variables explained wages to different degrees. Rates of return to education were, on average, around 5%, with women’s returns being better for higher educational levels. All three groups of variables explained only 17.19% of the earning gap between men and women, leaving 82.81% that could be considered as labour market discrimination. The GLM models revealed that social factors have significant indirect effects on wages as, when adding these indirect effects to the model, the explained variance in wages increased from 35% to 55%. This research makes significant contributions to the field of gender wage differentials and discrimination in Syria. The results of this study could help the Syrian government to develop tailored policies for the Syrian labour market to narrow the gender pay gap as decreasing gender inequality would enhance productivity and foster economic growth