Evidence map›Paper›PMID 42034815›Full record

ArticleEuropean journal of population = Revue europeenne de demographie2026

Trends in Working Life Expectancy and Untapped Employment Potential in an Ageing Population: The Case of Germany.

Harun Sulak, Christian Dudel, Elke Loichinger, Sebastian Klüsener

Abstract read
In one paragraph

Article in European journal of population = Revue europeenne de demographie, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Harun SulakFederal Institute for Population Research (BiB), Wiesbaden, Germany. Harun.Sulak@bib.bund.de.
Christian DudelFederal Institute for Population Research (BiB), Wiesbaden, Germany.
Elke LoichingerFederal Statistical Office of Germany (Destatis), Wiesbaden, Germany.
Sebastian KlüsenerFederal Institute for Population Research (BiB), Wiesbaden, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The population of Germany is ageing rapidly. As a result, the country's working age population is expected to shrink substantially over the next 15 years. To cope with this challenge, a number of policy reforms have been introduced to activate untapped employment potential and increase the length of working life. However, little is known to what extent employment potentials have already been realised, and what differences exist between socio-economic groups. This paper addresses these questions using large-scale data from the German Microcensus to calculate working life expectancy (WLE) and unrealised working life expectancy. WLE not only accounts for labour market status (i.e., employed, unemployed, and inactive), but also considers actual working hours and preferences on working hours that allow capturing under- and overemployment. Our results show that WLE for most groups exhibits a U-shaped development, with WLE in 2022 resembling the levels recorded in 1991. At the same time, socio-economic inequalities in WLE were and still are substantial, and the group with the highest WLE works more than twice as long over their lifetime compared with the group with the lowest WLE. Moreover, trends in unrealised employment potential mirror trends in WLE - when WLE goes down, unrealised potential goes up. During recent years, only individuals with a low level of education have continued to display considerable unrealised potential, whereas for highly educated individuals, virtually no unrealised potential remains. On the contrary, we obtained evidence of overemployment for this group.

Indexed as

GermanyLifetime in unemploymentOveremploymentSocio-economic differencesUnderemploymentWorking life expectancy

Identifiers

PMID42034815
PMCPMC13133311

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.