The Federal Ministry of Labour and Social Affairs has commissioned Economix to carry out a long-term forecast of the German labour market. The aim is to identify sectoral, occupational and regional imbalances and to draw policy conclusions in a combination of strategic scenarios and quantitative forecasts.

Arbeitsmarkt 2030 – Wirtschaft und Arbeitsmarkt im digitalen Zeitalter (Projection 2016; W. Bertelsmann Verlag)

By Kurt Vogler-Ludwig, Nicola Düll, Ben Kriechel

(Projection 2016; W. Bertelsmann Verlag)

By Kurt Vogler-Ludwig, Nicola Düll, Ben Kriechel

(Fachexpertisen zur Prognose 2016; W. Bertelsmann Verlag)

By Nicola Düll

By Kurt Vogler-Ludwig

All results have been published by W. Bertelsmann Verlag.

The press release on the publication of the first forecast is available in German and in English.

Description

The German Ministry of Labour and Social Affairs has asked Economix to provide an analysis of future labour demand and supply by developing a new skills forecasting model for Germany. The project should provide "regular, transparent and detailed evaluations about future developments on the German labour market”. A forecasting model has been developed by an international consortium that consists of the Institute for Employment Research at Warwick University, Cambridge Econometrics and ROA at Maastricht University, which will help to identify future labour market imbalances and will propose policies to ensure that there is a sufficiently qualified labour force.

A model that forecasts the future solely based on extrapolation of past trends would fail given the recent financial and economic crisis. It is more realistic to assume that there are several structural breaks in historic time series through the recent crisis, globalization of economies and labour markets, and social changes. We have therefore combined mathematical forecasting models with qualitative future scenarios. This enables us to have a preview of the fundamental changes that the both the economy and society faces, which we can include in the empirical forecasting model.