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Erschienen in: Social Indicators Research 1/2017

28.07.2016

Overeducation, Skills and Wage Penalty: Evidence for Spain Using PIAAC Data

verfasst von: Sandra Nieto, Raul Ramos

Erschienen in: Social Indicators Research | Ausgabe 1/2017

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Abstract

The literature on educational mismatches finds that overeducated workers suffer a wage penalty compared with properly educated workers with the same level of education. Recent literature also suggests that individuals’ skill heterogeneity could explain wage differences between overeducated and properly matched workers. The hypothesis is that overeducated workers earn less due to their lower competences and skills in relative terms. However, that hypothesis has been rarely tested due to data limitations on individuals’ skills. The aim of this paper is to test the individuals’ skill heterogeneity theory in Spain using microdata from PIAAC, because it is one of the developed countries supporting the highest overeducation rates and where its adult population holds the lowest level of skills among a set of developed countries. Our hypothesis is that the wage penalty of overeducation in Spain is explained by the lower skill level of overeducated workers. The obtained evidence confirms this hypothesis but only to a certain extent as skills only explain partially the wage penalty of overeducation.

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Fußnoten
1
Along with Italy (OECD 2013a).
 
2
See OECD (2013b) for more details about IRT and the Jackknife method.
 
3
The results for these control variables are not be discussed in the main text as we focus our comments in the variables of interest. Full details on the estimation results is available from the authors on request.
 
4
Although OECD (2013a) measures educational mismatch using the same self-assessment method than us, the percentages of mismatch are different. The reason of those differences is that they cluster education into 4 levels while we take advantage of the maximum level of disaggregation of the data.
 
5
Similar incidence of educational mismatch in Spain has been found by Murillo et al. (2012).
 
6
The Pearson Chi square test rejects the null hypothesis of non-correlation between variables.Pearson chi2(4) = 4.1182 p value= 0.390.
 
7
The probit equation of the probability of being employed includes as explanatory variables gender, experience, experience squared, years of attained education, immigrant status, number of children, whether individual is living with spouse or not, and regional dummies.
 
8
The variables we use as exclusion restrictions are both number of children at home and whether individual is living with partner or not. Those variables affect the probability of being employed, but do not determine wages.
 
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Metadaten
Titel
Overeducation, Skills and Wage Penalty: Evidence for Spain Using PIAAC Data
verfasst von
Sandra Nieto
Raul Ramos
Publikationsdatum
28.07.2016
Verlag
Springer Netherlands
Erschienen in
Social Indicators Research / Ausgabe 1/2017
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-016-1423-1

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