Wages, Skills, and Skill-Biased Technical Change: The Canonical Model Revisited

A-Tier
Journal: Journal of Human Resources
Year: 2023
Volume: 58
Issue: 6

Authors (4)

Score contribution per author:

1.005 = (α=2.01 / 4 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

While influential, the canonical supply–demand model of the wage returns to skill has faced challenges, including theoretically wrong-signed elasticities of substitution, counterintuitive paths for skill-biased technical change (SBTC), and an inability to account for observed deviations in college premia for younger versus older workers. We show that using improved estimates of skill prices and supplies that account for variation in skills across cohorts helps to explain the college premium differences between younger versus older workers and produces better out-of-sample predictions, positive elasticities of substitution between high- and low-skill workers, and a more modest role for SBTC. We further show that accounting for recession-induced jumps and trend adjustments in SBTC and linking SBTC to direct measures of information technology investment expenditures yield an improved fit, no puzzling slowdown in SBTC during the early 1990s, and a higher elasticity of substitution between high- and low-skill workers than previous ad hoc assumptions.

Technical Details

RePEc Handle
repec:uwp:jhriss:v:58:y:2023:i:6:p:1783-1819
Journal Field
Labor
Author Count
4
Added to Database
2026-01-24