Changing Income Risk across the US Skill Distribution: Evidence from a Generalized Kalman Filter

J. Carter Braxton; Kyle Herkenhoff; Jonathan Rothbaum; Lawrence Schmidt

doi:10.1257/aer.20231656

Changing Income Risk across the US Skill Distribution: Evidence from a Generalized Kalman Filter

J. Carter Braxton¹; Kyle Herkenhoff²; Jonathan Rothbaum³; Lawrence Schmidt⁴

¹ University of Wisconsin (email: ) · ² University of Minnesota, FRB Minneapolis, IZA, and NBER (email: ) · ³ US Census Bureau (email: ) · ⁴ MIT (email: )

American Economic Review 2025

For whom has earnings risk changed, and why? We answer these questions by combining the Kalman filter and EM algorithm to estimate persistent and temporary earnings for every individual at every point in time. We apply our method to administrative earnings linked with survey data. We show that since the 1980s, persistent earnings risk rose by 12.5 percent for both employed and unemployed workers and the scarring effects of unemployment doubled. At the same time, temporary earnings risk declined. Using education and occupation codes, we show that rising persistent earnings risk is concentrated among high-skill workers and related to technology adoption. (JEL J22, J24, J31, J64)

DOI: 10.1257/aer.20231656
Volume: 115 (12)
Pages: 4438-4475
Language: en
Export: BibTeX
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