Data and Code for: Routine-Biased Technological Change and Endogenous Skill Investments
Principal Investigator(s): View help for Principal Investigator(s) Danyelle Branco, Sao Paulo School of Economics-FGV; Bladimir Carrillo, Sao Paulo School of Economics-FGV; Wilman Iglesias, University of Nebraska-Lincoln, Lincoln, NE
Version: View help for Version V1
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Project Description
Summary:
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We investigate how individuals alter their educational investments in response to routine-biased technology. We find that individuals growing up in robot-impacted areas are
more likely to complete a bachelor’s degree and experience a relative increase in earnings. Changes in the skill premium and opportunity cost appear to drive these effects.
To interpret these findings, we estimate a model of endogenous skill acquisition where
changes in the demand and supply of skills shape the path of earnings. Counterfactual
simulations suggest that the endogenous skill response cannot fully undo the adverse
earnings effects of automation unless there are sufficiently generous educational subsidies.
Scope of Project
Subject Terms:
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Automation;
industrial robots;
skill acquisition;
college attainment;
labor market
JEL Classification:
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I21 Analysis of Education
J23 Labor Demand
J24 Human Capital; Skills; Occupational Choice; Labor Productivity
I21 Analysis of Education
J23 Labor Demand
J24 Human Capital; Skills; Occupational Choice; Labor Productivity
Geographic Coverage:
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United States
Universe:
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The United States
Data Type(s):
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census/enumeration data;
survey data
Collection Notes:
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None
Methodology
Response Rate:
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Not applicable
Data Source:
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Main source: American Community Survey
Collection Mode(s):
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other
Scales:
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Not applicable
Weights:
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Not applicable
Unit(s) of Observation:
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Individuals
Geographic Unit:
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State
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