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Development Accounting Using PIAAC Data

Authors: Ana Hidalgo-Cabrillana; Zoë Kuehn; Cristina Lopez-Mayan;

Development Accounting Using PIAAC Data

Abstract

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

Financial support from the Spanish Ministry of Science and Innovation through Grant ECO2013-44920-P

Country
Spain
Keywords

O11, ddc:330, J11, I25, Multi-dimensional human capital measure, O4, Economía, Development accounting, PIAAC, Mincerian wage equation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Average
Top 10%
Green
gold
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