Data and Codes for Offshoring, Automation, Low-Skilled Immigration and Labor Market Polarization
Principal Investigator(s): View help for Principal Investigator(s) Federico S. Mandelman, Federal Reserve Bank of Atlanta; Andrei Zlate, Board of Governors of the Federal Reserve System
Version: View help for Version V1
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Project Description
Summary:
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We show that the observed polarization of employment toward the high- and low-skill occupations disappears when only native workers are considered. Instead, low-skilled immigration explains employment growth at the low tail of the skill distribution. Moreover, while employment rose, wages remained subdued in low-skill occupations. A data-disciplined structural model accounts for this evidence: Offshoring and automation negatively affect middle-skill occupations but enhance employment and wages for the high-skilled. Low-skill employment is sheltered from offshoring and automation, as it consists of manual, non-tradable services. However, low-skilled immigration depresses low-skill wages and encourages native workers to move up along the skill ladder through training.
Scope of Project
Subject Terms:
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[labor market polarization;
, Offshoring;
automation;
international labor migration;
labor market polarization;
, automation;
international labor migration;
]
JEL Classification:
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F16 Trade and Labor Market Interactions
F22 International Migration
F41 Open Economy Macroeconomics
F16 Trade and Labor Market Interactions
F22 International Migration
F41 Open Economy Macroeconomics
Geographic Coverage:
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USA
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