Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/195263 
Erscheinungsjahr: 
2017
Quellenangabe: 
[Journal:] SERIEs - Journal of the Spanish Economic Association [ISSN:] 1869-4195 [Volume:] 8 [Issue:] 4 [Publisher:] Springer [Place:] Heidelberg [Year:] 2017 [Pages:] 373-399
Verlag: 
Springer, Heidelberg
Zusammenfassung: 
We carry out a classical development accounting exercise using data from the 'Programme for the International Assessment of Adult Competencies' (PIAAC). PIAAC data, available for 30 upper-middle and high-income countries and nationally representative for the working-age population, allow us to construct a multidimensional measure for the stock of human capital in each country, taking into account years of schooling, job experience, cognitive skills, on-the-job-training, and health. Individual level PIAAC data for the US are then used to estimate the weight of each dimension in the human capital composite by running Mincerian wage regressions. We find that differences in physical capital together with our broad measure of human capital account for 42% of the variance in output per worker, compared to only 27% when proxying human capital by average years of schooling only. Differences in cognitive skills play the largest role while experience and health are of lesser importance.
Schlagwörter: 
Development accounting
Multi-dimensional human capital measure
PIAAC
Mincerian wage equation
JEL: 
O11
O4
I25
J11
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