Social distancing and lockdown measures taken to contain the spread of COVID-19 may have distributional economic costs beyond the contraction of GDP. Here we evaluate the capacity of individuals to work under a lockdown based on a Lockdown Working Ability index which considers their teleworking capacity and whether their occupation is essential or closed. Our analysis reveals substantial and uneven potential wage losses across the distribution all around Europe and we consistently find that both poverty and wage inequality rise in all European countries. Under four different scenarios (2 months of lockdown and 2 months of lockdown plus 6 months of partial functioning of closed occupations at 80%, 70% and 60% of full capacity) we estimate for 29 European countries an average increase in the headcount poverty index that goes from 4.9 to 9.4 percentage points and a mean loss rate for poor workers between 10% and 16.2%. The average increase in the Gini coefficient ranges between 3.5% to 7.3% depending on the scenario considered. Decomposing overall wage inequality in Europe, we find that lockdown and social distance measures produce a double process of divergence: both inequality within and between countries increase.

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This paper presents new evidence on the evolution of job polarisation in Spain between 1994 and 2014. After showing the U-shaped relationship between employment share growth and job's percentile in the wage distribution, I use the task approach to investigate the main determinants behind job polarisation. Using the European Working Condition Survey I analyse in detail the task content of the jobs which display the most significant employment changes. I show that changes in employment shares are negatively related to the initial level of routine. I then explore the impact of computerisation on routine task inputs and I find that the routine measure is negatively related to computerisation. Finally, by using information on past jobs, I provide evidence on the displacement of middle-paid workers. Results suggest that they did not predominantly relocate their labour supply to bottom-paid occupations: while non-graduate middle workers move towards bottom occupations, graduate middle employees shift towards top occupations. This fact suggests that supply-side changes are important factors in explaining the expansion at the lower and upper tail of the employment distribution.

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Purpose. The purpose of this paper is to present the stylized facts of over-education among European graduates over time (1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013), paying special attention to the measurement issues. Design/methodology/approach. The authors use two different sources, the Programme for the International Assessment of Adult Competencies 2012, and the European Union Labour Force Survey 1998-2013, with two different aims. We employ the first one to make a detailed analysis of the different forms of measuring over-education and its implications in terms of the result obtained. The analysis of the second one responds to study the evolution and characteristics of over-education in Europe. Findings. In first place, the paper provides evidence of the high level of sensitivity of the level of measured over-education to the type of methodology used. Such difference is even higher when we focus on skills versus educational mismatch. The work also shows how with all their shortcomings, the measures of over-education used in the analysis point to the existence of convergence in over-education levels among the European countries of the sample (only interrupted by the crisis), in a context of reduction of over-education rates in many countries. Practical implications. Researchers should be particularly careful when estimating overeducation, because of the strong implications in terms of the so different results obtained when choosing between competing methods. Originality/value. The analysis abound in the implications of the use of different methodologies of estimating over-education in terms of both size and ranking among European countries. The production of long-run and updated estimates of over-education for a large sample of countries using a homogenous database and different estimation methods.