Data and Code for: Changing Tracks: Human Capital Investment after Loss of Ability
Principal Investigator(s): View help for Principal Investigator(s) Pernille Plato, University of Copenhagen; Anders Humlum, University of Chicago. Booth School of Business; Jakob Roland Munch, University of Copenhagen
Version: View help for Version V1
Name | File Type | Size | Last Modified |
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ChangingTracksReplication | 01/29/2025 07:24:AM |
Project Citation:
Plato, Pernille, Humlum, Anders , and Munch, Jakob Roland. Data and Code for: Changing Tracks: Human Capital Investment after Loss of Ability. Nashville, TN: American Economic Association [publisher], 2025. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2025-03-26. https://doi.org/10.3886/E213281V1
Project Description
Summary:
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We provide the first evidence on how workers invest in human capital after losing
ability. Using quasi-random work accidents in Danish administrative data, we find
that workers enroll in bachelor’s programs after physical injuries, pursuing degrees
that build on their past training and experience. Exploiting institutional differences
in the stackability of degrees, we find that higher education moves injured
workers from disability benefits to full-time employment, earning 25% more than
before injury. Reskilling subsidies for injured workers pay for themselves four times
over, and current rates of reskilling are substantially below the social optimum,
especially for middle-aged workers.
Funding Sources:
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Rockwool Foundation Research Unit
Scope of Project
Subject Terms:
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reskilling;
occupational transition;
disabilities;
career shocks
JEL Classification:
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I26 Returns to Education
J24 Human Capital; Skills; Occupational Choice; Labor Productivity
J62 Job, Occupational, and Intergenerational Mobility; Promotion
I26 Returns to Education
J24 Human Capital; Skills; Occupational Choice; Labor Productivity
J62 Job, Occupational, and Intergenerational Mobility; Promotion
Geographic Coverage:
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Denmark
Time Period(s):
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1995 – 2017
Universe:
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Universe of the Danish Population
Data Type(s):
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aggregate data;
program source code
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