Target Group Monitoring in European Regions: Empirical Findings and Conceptual Approaches

Christa Larsen, Waldemar Mathejczyk, Jenny Kipper, Alfons Schmid (Eds.)

Target Group Monitoring is a regional approach to generate data to cover adequately the information needs of labour market actors. Approaches from different European regions are presented in this book, applied onto migrants as a target group of labour market politics. Furthermore, the central elements of these approaches are discussed with respect to their suitability for other target groups, such as older or young employees, low-skilled and skilled workers. Finally, methods and techniques are considered to provide a wide scope of information in combining target group and branch/industry approaches. This book was developed by several members of the European Network of Regional Labour Market Monitoring.

Monitoring of Regional Labour Markets in European States: Concepts–Experiences–Perspectives

Christa Larsen, Waldemar Mathejczyk, Alfons Schmid (Eds.)

Regional factors are important for the economy and employment in highly competitive, international markets. As a precondition for the functioning of regional labour markets, adequate information has to be generated and transformed into new knowledge – for all actors involved. Regional Labour Market Monitoring can be seen as an approach to meet these requirements. A variety of projects in this area have been set up in several European countries. Their common purpose is to develop and implement sets of indicators to measure the current regional labour market and to provide information over its development into the future. Both the regional labour force and business enjoy the benefits from this activity. This anthology gives an idea of the diversity of European approaches to monitoring of regional labour markets. It renders different concepts and instruments representing the region in which they are used.

Big Data and the Complexity of Labour Market Policies:
New Approaches in Regional and Local Labour Market Monitoring for Reducing Skills Mismatches

Christa Larsen, Sigrid Rand, Alfons Schmid, Mario Mezzanzanica, Silvia Dusi (Eds.)

The experience of regional and local labour market observatories shows that information on some aspects of the labour market – such as the demand for skilled labour in certain sectors or spatial units – is difficult to obtain. In the recent years, ICT-related innovations have created new forms and types of data that can be used for enhancing the efficiency in several areas of economic activity. So far, the vast amount of unstructured data contained in the World Wide Web – Big Data – has been largely unexploited. However, as the available technology provides increasingly cost-effective solutions, it has become possible to provide services that have formerly been too expensive. Therefore, applying Big Data in labour market monitoring can provide innovative insights into the functioning of labour markets. Also the process data of Public Employment Services or Statistical Offices constitute a promising source of large amounts of data. The results of the analyses based on the different sources of data can be used to improve the efficiency of the labour market at large and the provision of services by governments and private enterprises.

However, the attempts to use Big Data in the context of labour market monitoring have been relatively rare so far, even though a growing interest can be observed among researchers and practitioners alike. Against this background, the issues of collecting, elaborating, analysing and disseminating the information available on the Web urgently needed to be addressed – as did the associated ethical and legal issues concerned with data ownership and protection. This year’s Anthology of the EN RLMM covers these issues from the viewpoint of labour market researchers and practitioners in labour market observatories from different European regions and localities. The contributions provide first insights into new models and tools of labour market monitoring based on the usage of Big Data.