Entry Date:
September 22, 2014

Labor Market Decision Support System (LMDSS)

Principal Investigator David Autor

Co-investigator James M Lyneis

The Saudi Arabia labor market is characterized by an emergence of high youth participation, high levels of expatriate workers (mostly in the private sector), leading to a depressing of levels of average general wages, lower productivity, and potentially high unemployment levels for years to come.

With a national population increasing by close to half a million people per year and unemployment running above 40 per cent for those aged 20 to 24, with higher concentration of unemployment amongst females the Ministry of Labor is facing tough challenges to create sufficient job opportunities in a country where 29.4 per cent of the population is under 15 years of age.

The project aims to understand the labor market dynamics of Saudi Arabia and its impact on economic growth, and then developing a framework for the modeling, simulation, and analysis of the labor market in Saudi Arabia, including the ability to display spatial information.

The project uses the modeling framework to provide a capability to assess the interdependencies between current labor market policies and programs to assist decision makers in Saudi Arabia in the areas of policy analysis, investment planning, and education and training by simulating the impact of new labor policies, before implementing them in the real world.

The purpose of the LMDSS project is to develop a decision support system that addresses labor market dynamics in Saudi Arabia. This will be done by creating an integrated and powerful modeling environment that can analyze the present situation regarding the labor market dynamics for the Kingdom of Saudi Arabia and predict future trends.

The proposed modeling system combines different types and levels of analysis including statistical analysis, econometrics, system dynamics, agent based modeling and scenario analysis. By combining options of different scenarios to generate different schemas