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The Age-Productivity Gradient: Evidence from a Sample of F1 Drivers

Fabrizio Castellucci () and Giovanni Pica
Additional contact information
Fabrizio Castellucci: INSEAD

Authors registered in the RePEc Author Service: Mario Padula

CSEF Working Papers from Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy

Abstract: Aging is a global phenomenon. If older individuals are less productive, an aging working population can lower aggregate productivity, economic growth and fiscal sustainability. Therefore, understanding the age-productivity gradient is key in a aging society. However, estimating the effect of aging on productivity is a daunting task. First, it requires clean measures of productivity. Wages are not such measures to the extent that they reward other workers attributes than their productivity. Second, unobserved heterogeneity at workers, firms and workers/firms level challenges the identification of the age-productivity gradient in cross-sectional data. Longitudinal data attenuate some identification issues, but give rise to the problem of partialling out the effect of aging from the pure effect of time. Third, the study of the age-productivity link requires investigating the role of experience and of seniority. We tackle these issues by focussing on a sample of Gran Prix Formula One drivers and show that the age-productivity link has an inverted U-shape profile, with a peak at around the age of 30-32.

Keywords: Aging; individual effects; firm effects; match effects; Formula One (search for similar items in EconPapers)
JEL-codes: C23 J24 L83 (search for similar items in EconPapers)
Date: 2009-05-01
New Economics Papers: this item is included in nep-age
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Citations: View citations in EconPapers (1)

Published in Labour Economics, 2011, Volume 18, Issue 4, pp. 464-473

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http://www.csef.it/WP/wp226.pdf (application/pdf)

Related works:
Journal Article: The age-productivity gradient: Evidence from a sample of F1 drivers (2011) Downloads
Working Paper: The age-productivity gradient: evidence from a sample of F1 drivers (2009) Downloads
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