Space-Time Variations in Job Types: A Tale of “Three Europes”

Abstract

This article, which draws on three waves (2005, 2010, 2015) of the European Working Conditions Survey, examines the nature and prevalence of different job types in a representative sample of employees in 30 European countries (N = 59,839) and investigates their change over time. Using self-organizing map, sampled employees were first grouped into seven job types, based on similar job features in the following dimensions: physical environment, work intensity, working time quality, social environment, skill and discretion, and earnings and prospects. Subsequently, the resulting job types were validated by linear regression models on outcomes that are indicative of job quality, such as well-being and job satisfaction. Finally, space-time variations in the distribution of job types were explored using a two-stage formulation model that contrasted universalistic and institutional explanations of change. Results indicate that three clusters of countries could be distinguished, which only partially fit into existing regime classifications: i) the Northern cluster (Scandinavian countries); ii) the Central and Western cluster (Belgium, the Netherlands, Luxembourg, France, Germany, Austria, Slovenia, Estonia, but also the UK, Ireland and Malta); and iii) the Southern and Eastern cluster (Mediterranean countries including Cyprus and Turkey, the former socialist EU member states, Latvia, and Lithuania). These clusters present specific patterns of change in the distribution of job types that are more closely related to the change in the national economic situation and the employment structure than to institutional variation.

Keywords:

• Job types
• job quality
• self-organizing map
• well-being
• job satisfaction
• European countries

Acknowledgement

The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730998, InGRID-2—Integrating Research Infrastructure for European expertise on Inclusive Growth from data to policy.

Compliance with ethical standards

We ensure objectivity and transparency in research, and we also ensure that accepted principles of ethical and professional conduct have been followed

We included information regarding sources of funding, as follows: “The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730998, InGRID-2—Integrating Research Infrastructure for European expertise on Inclusive Growth from data to policy”

We declare that:

• there are no potential conflicts of interest (financial or non-financial) to report;

• the research has not involved human participants;

• the research has not involved animals.

Notes

1 When measuring job quality using dimensionality reduction techniques, different approaches have been employed. For instance, Leschke and Watt (2008) assigned normative weights: each indicator of job attributes was given a weight which was related to its relative importance in the description of job quality. However, Eurofound (2012) constructed an overall job quality index with equal weights assigned to the different indices covering the different job quality dimensions.

Additional information

Funding

This work was funded by Horizon 2020 Framework Programme.