The Transition into Work – specialities for the hidden labour force in comparison to other economically inactive persons

Publication type

Research Paper

Series Number



Working Paper


Publication date

March 22, 2004


Building on earlier work by Holst and Spiess (2002), in this paper we define a sub-group of the Hidden Labour Force (HLF), the so-called Attached. We present a multivariate approach on transitions into work for five non working groups including the unemployed, the Attached, people in education, people doing housework and others. Further, we provide separate analyses for eleven EU countries, and offer a comparative analysis. The study is based on ECHP data from 1994 to 1998. We are looking at possible determinants that motivate individuals to take up work and compare the results for the non-employed groups. It is expected that individuals in the Attached group will have significantly higher transition probabilities into work than others outside the labour force although we control for other socio-demographic, economic factors and some macro indicators. We also expect that country specific conditions drive the chances of men and women differently. To investigate this we consider gender specific aspects of particular countries in our study including analyses of the EU-sample entire, and within this sample separate clustered and individual analyses. Throughout we provide estimations for separate sub-samples of females and males to show the different influence of the variables on men and women respectively. The regressions for all 11 EU countries together showed clearly that there were different labour market transition probabilities between females and males, more specifically that females overall had a lower transition probability into work in all non working groups compared to males. In grouping countries in the sample into either a more or less conservative country cluster we found significant differences in the group of females. Those in the more conservative cluster had the lowest transition probabilities of all non employed groups. Gender specific differences arose when we took the need to work into account.


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