Population changes and labour market in Syria
Project Leader(s): Ayham Rezk
Staff: Professor Tony Champion, Professor Mike Coombes and Dr Jane Pollard
My research project will examine how the demographic patterns of Syrian population affect the local labour market in term of jobs availability. Ultimately, the changes in population structure, particularly high rates of population growth, in the previous decades, will be studied as these changes played an essential role in the current complications in the Syrian economy. I seek to study why the population growth rate varies among Syrian regions and provinces and how has shaped different patterns and levels of economic growth, with big variations in the local labour markets, as well as how the Syrian’s provinces (Mohafzat) responded to different development opportunities that shaped current economic levels of the labour market.
Essentially, the proposed analysis will be determined in what way the deteriorating economic situation and shortages in the labour market in term of job availability has led much population in working age (15-64) to move directly from main economic sectors “agriculture” to services sectors, as well as how this contributed to the concentration of population in certain areas that do not contain key resources, which in turns caused unbalanced urban growth. Therefore, my efforts through this research will be devoted to empirically evaluate these variations and determine how the population aspects, including migration flows, are important and need to be identified to examine their impact on spatial variations of the labour market in term of labour supply and demand.
The contribution of this work can be measured in two directions. First, providing a practical understanding of the complex way specific population factors particularly migration influence the local labour market, within specific period 1994-2004. Second, developing an empirical method for micro-data collection and analysis (aggregated numeric and statistical data) from comprehensive sources, while adopting more sophisticated statistical