Digital competences mismatch in the Austrian labour force: A model of unemployment responses

Funding amount: 197.000,00 EUR (OeNB Jubiläumsfond)

Project start: 01.11.2020

Project leader: Univ-Prof. Dr. Richard Sturn

Scientific staff:
Carolina Lennon, Ph.D in Economics, M.sc B.A.
Marlies Schütz, Dr. Bakk.rer.soc.oec. M.A. (Econ.)
Laura Zilian, BSc MSc.
Stella Zilian, B.A.(Econ.) M.A. (Econ.)

The digital revolution has spurred concerns about artificial intelligence and robots taking over jobs. Although there is no consensus on whether the current revolution will render all types of labour redundant, there is an increasing amount of empirical and theoretical research pointing out to significant shifts in employment and structural change in the labour force as tasks are automated and skills become obsolete due to new technologies. Little research, however, has been devoted to understanding the short-run consequences for individual workers as economies adjust towards the new steady state. To fill this gap, we propose to investigate the current dynamics in the labour market by developing an Agent Based Model that explicitly accounts for the supply and demand (mis)match of digital competences. This will help to inform policymakers about the impact of the digital revolution on the employability across different groups of the Austrian labour force.

Economic research consistently points to a shift of employment based on the task content of jobs. However, little effort has been devoted to model and estimate the consequences for individual workers in the short run. We expand the existing literature by modelling the dynamics of unemployment based on the demand and supply of digital competences. We will develop two indicators to describe digital competences in the labour market. Further, we will simulate scenarios to investigate whether an unequal distribution of digital competences affects employability. Then, we will use micro data on the transition from and into unemployment to validate the main results of the ABM and construct a set of stylized facts on the distribution and trends of digital competences in the Austrian labour market. This project represents a genuine effort of bringing together economics and media and information sciences to inform policy makers about the consequence of the digital revolution in the short run.

To investigate the dynamics of unemployment triggered by the current digital revolution, we will develop an agent-based model (ABM) in order to explicitly account for the supply and demand (mis)match of digital competences. The model will be calibrated and validated using information on digital competences in the Austrian labour force. We will construct two indices to account for occupational requirements of digital competences at the lowest hierarchical level of ISCO-08. To this end, we will use, among others, search text algorithms and network and revealed comparative advantage analysis. We will use information from the labour market database to account for the demand of digital competences based on vacancies registered with the Austrian Public Employment Services (PES) and we will use the EU-LFS to account for the supply of digital competencies.  Finally, we will employ micro data on the transition from and into unemployment in Austria to validate the main results of the ABM.