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Published in: Social Indicators Research 1/2019

06-12-2018

The Effects of Unemployment on Non-monetary Job Quality in Europe: The Moderating Role of Economic Situation and Labor Market Policies

Author: Jonas Voßemer

Published in: Social Indicators Research | Issue 1/2019

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Abstract

Previous research has illustrated that unemployment not only has short-term, but also medium-term negative effects on workers’ careers. While most studies have focused on employment chances and earnings losses, this article examines the effects of unemployment on four different facets of non-monetary job quality in Europe. Specifically, I take a comparative perspective investigating to what extent the effects of unemployment on subsequent occupational status, autonomy, authority, and job security are moderated by countries’ economic situation and institutions, including active and passive labor market policies in addition to employment protection legislation. The analyses draw on micro data from round 1–7 (2002–2014) of the European Social Survey including harmonized information about 125,000 workers nested in 34 countries for up to 7 rounds. Using two-stage multi-level models, the first-stage micro-level analyses reveal that unemployment has negative effects on all four facets of non-monetary job quality in the majority of the 164 country-rounds examined. Specifically, job security is negatively affected by experiences of unemployment within the last 5 years. However, at odds with the theoretical predictions, the second-stage macro-level analyses do not provide consistent empirical evidence for the moderating role of economic situation and labor market policies.

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Appendix
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Footnotes
1
While autonomy and job security figure prominently in different definitions of job quality (Findlay et al. 2013), occupational status (Brand 2006) and job authority (Brand 2006; Dieckhoff 2011) have been investigated in previous studies. Therefore, the latter measures allow discussing the results of this study in relation to previous findings.
 
2
By average effects I mean that no subgroup differences between workers within countries are examined. For example, I do not estimate separate effects for women and men within each country. I also use regression methods that only model differences in conditional expectations/means, leaving changes in other aspects of the conditional distribution unexamined. Although this is standard in the social sciences, it should be noted that means do not necessarily represent distributions very well (e.g., Maggino 2017) (see also Footnote 7).
 
3
The theoretical argumentation focuses on what Gangl (2006: 990) calls the “behavioral implications” of macro-level variables. However, economic conditions and labor market policies may also affect who becomes unemployed and re-employed. For example, in countries with poor economic conditions, the re-employed may be composed of individuals who are less negatively affected by job loss.
 
4
In this study, we focus on variation in the economic situation across countries and over time. Of course, differences in economic situations within countries across regions or industries may also result in different effects of past unemployment on subsequent job quality (see also Footnote 10).
 
5
I use the following integrated data files: ESS 1: Edition 6.4, ESS 2: Edition 3.4, ESS 3: Edition 3.5, ESS 4: Edition 4.3, ESS 5: Edition 3.2, ESS 6: Edition 2.2, ESS 7: Edition 2.0. For the imputation models I also use the following data from the interviewer questionnaires: ESS 1: Edition 5.1, ESS 2: Edition 3.2, ESS 3: Edition 2.0, ESS 4: Edition 2.0, ESS 5: Edition 3.0, ESS 6: Edition 2.1, ESS 7: Edition 2.0. The data are provided by the Norwegian Social Science Data Services, Norway—Data Archive and distributor of ESS data for ESS ERIC.
 
6
Self-employed individuals have been excluded, because the theories that predict negative effects of past unemployment on job quality do not usually apply. Individuals reporting an occupation in the armed forces have been excluded, too, because they are not differentiated in ISCO-88.
 
7
As explained in Footnote 2, I do not examine subgroup differences between workers within countries. This has two reasons. First, the sample sizes for subgroups within countries are often too low to reliably estimate the effects of unemployment within these. Second, focusing on average effects makes sense as a first step, because research on the effects of unemployment on non-monetary job quality is still very scarce and the theoretical derivations presented do not suggest that the labor market policies I consider are targeted at specific subgroups.
 
8
Unfortunately, the data used do not include repeated measures of earnings. The data do, however, include a question on whether respondents’ have taken courses or attended lectures or conferences. Although this may represent another dimension of job quality (“continued training”), the question does not allow identifying whether the training is employer-funded. It may also include participation in ALMP making it not suitable for the current analysis.
 
9
I translated the four-digit ISCO-88 (COM) and ISCO-08 codes that are provided in the ESS into SIOPS using the conversion tools of Ganzeboom and Treiman. In round 6 and 7 the ESS changed its occupational coding from ISCO-88 (COM) to ISCO-08. The ISCO-08 codes have been translated into ISCO-88 before conversion into SIOPS. For occupational codes that are unique to ISCO-88 (COM), SIOPS is assigned using two- or three-digit level information.
 
10
While the labor market policies are designed and implemented at the national level, it would have been interesting to examine variation in the economic situation at the regional or industry level, too (see also Footnote 4). However harmonized information at these levels are not available for most of the examined countries.
 
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Metadata
Title
The Effects of Unemployment on Non-monetary Job Quality in Europe: The Moderating Role of Economic Situation and Labor Market Policies
Author
Jonas Voßemer
Publication date
06-12-2018
Publisher
Springer Netherlands
Published in
Social Indicators Research / Issue 1/2019
Print ISSN: 0303-8300
Electronic ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-018-2044-7

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