IHS

The IHS provides economic and social scientific research for the public benefit.

Today, there is high demand for analyzing the grand societal challenges drawing on evidence-based scientific methods and providing answers that are objective and independent.

As an independent post-university research center the Institute for Advanced Studies is well-established and recognized across Europe. The Institute develops research questions in dialogue with policy-makers as well as among the academic world, and delivers answers that are relevant to both sides. Its researchers focus on topics of high relevance that are aligned with societal challenges and that anticipate issues of high relevance in the near future.

Our contribution to the CONECTE project:

Like in many other countries the Lebanese labour market is hit by a matching problem. Hence, our contribution to the project is the development of a quantitative occupational forecasting model which is able to anticipate future trends of the supply and demand of labour. The outcome of this study will show the current mismatch in the Lebanese labour market, in particular in the field of higher education. It will also point to future trends in occupations needed and the supply of qualified graduates. This study will support Higher Education Institutions in their policy decisions and allow students and graduates to optimize their careers. It is to expect that the new findings will have a positive impact on the labour market as imbalances might decrease.

Our contribution to the CONECTE project is the development of a quantitative occupational forecasting model which is able to anticipate future trends of the supply and demand of labour. The methodology is based on research of the European Training Foundation (ETF), European Centre for the Development of Vocational Training (Cedefop) and the International Labour Office (ILO).

 

Our interim project report of July:

Kunst, R., Lassnigg, L. and Skriner, E. (2021). A quantitative occupational forecasting model for Lebanon. Study commissioned by Erasmus+ Capacity Building in Higher Education, July 2021.

 

Tasks we have carried out:

First, we decided on the methodology. The forecasting techniques in use focus on the extrapolation of past trends, or more complex time series methods, and on introducing behavioral content. The major determinants of the model are economic activity, labour demand, labour supply and labour market imbalances.

Second: In quantitative forecasting there are a number of prescribed procedures that must be followed. We collected data from IMF, ILOSTAT and CAS and prepared them for further processing. To make industrial activities comparable across sources we put some of the groupings of ISIC classifications together. We visualized the most relevant statistics because it plays a crucial role in model building and forecasting.

Third: We set up a basic quantitative occupational forecasting model. The data source for the model is the Labour Force and Household Living Conditions Survey 2018-2019 Lebanon, Beirut 2020. Due to simplicity reasons and availability the data set of the model has only one observed point in time and one forecast. The variables cover the major aggregates of the labour market.

In our base scenario, we assume that all determinants will remain unchanged in 2024 compared to 2019. In our growth scenario employment increases by 2.8 percent on a yearly average, however, leaving structures unchanged compared to 2019. The explanation for our growth assumption is that the severe economic downturn in 2019 and 2020 will be followed by a strong recovery.

The model results show that a lift in employment impacts occupations with medium and high skills. It would particularly lead to a higher demand for persons with a doctoral degree. However, such a rise in labour demand cannot be met by labour supply.