The Incidence of and Returns to ‘Overeducation’: PIAAC Evidence on the G7

Johnes, Geraint

doi:10.1007/s11024-018-9357-1

Cited by 5 publications

(4 citation statements)

References 29 publications

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“…Subjective measures are based on self-reports provided by the workers themselves about some personal and job-related characteristics and on the rate of skill utilisation. Examples on the application of these measures are found in Dolton and Silles (2008), Dolton and Vignoles (2000), Erdsiek (2016), Foley and Brinkley (2015), Holmes and Mayhew (2015), Iammarino and Marinelli (2015), Johnes (2016), Rumberger (1987) and Sicherman (1991).…”

Section: Returns To Overeducationmentioning

confidence: 99%

“…Lastly, there is growing interest in the literature on the presence of unobserved heterogeneity in studies of overeducation. Quantile regression has been employed with the aim of investigating how the returns to required and surplus education vary across the distribution (Budría and Moro-Egido, 2014;Johnes, 2016 andMcGuinness andBennett, 2007). The evidence on this is mixed.…”

Section: Returns To Overeducationmentioning

confidence: 99%

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Human capital and returns to education

Johnes¹,

Johnes²,

López-Torres³

2017

Handbook of Contemporary Education Economics

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Section: Returns To Overeducationmentioning

confidence: 99%

Section: Returns To Overeducationmentioning

confidence: 99%

Human capital and returns to education

Johnes¹,

Johnes²,

López-Torres³

2017

Handbook of Contemporary Education Economics

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“…In contrast, Budría (2011), andHernández andSerrano (2012) showed the opposite evidence, indicating that the wage inequality is caused by educational mismatch, and not by unobservable characteristics such as innate ability or motivation. Furthermore, Johnes (2019) found a mixture of results of earnings penalty over the wage distribution across countries. Billger and Lamarche (2015) applied a panel data quantile regression analysis to examine native-immigrant earnings differentials and verified heterogeneity across immigrant earnings distributions.…”

Section: Introductionmentioning

confidence: 99%

Over-education and immigrant earnings: a penalized quantile panel regression analysis

Maani

Wen

2021

Applied Economics

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Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world's largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.

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“…The report by Holmes and Mayhew (2015) generated some degree of alarm owing to the finding that around 60% of graduates in the UK are in non-graduate jobs. My own recent work (Johnes, 2016), based on PIAAC data, suggests that just over 50% of UK workers self-report as being overeducated in relation to the requirements of their job. Yet -and here is the rub -of those, no fewer than 97% are employed in jobs that require skills in reading and writing articles or reports, or in preparing graphs and tables, or in using algebra or more advanced maths or statistics.…”

mentioning

confidence: 99%