Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/324853 
Year of Publication: 
2025
Series/Report no.: 
Working Paper No. WP 2025-14
Publisher: 
Federal Reserve Bank of Chicago, Chicago, IL
Abstract: 
Wage growth is a key indicator of labor market conditions, but common measures often conflate individual wage changes with shifts in workforce composition. This paper develops a composition-adjusted measure of wage growth using nonparametric decomposition and program evaluation methods. The adjusted measure tracks unadjusted growth in stable periods but diverges during disruptions: during the Covid-19 pandemic, wage growth falls from 12% to 6% after adjustment. The method accommodates rich covariates, is robust to data quality issues such as rounding, heaping and top-coding, and enables distributional and subgroup analysis using micro data, offering more accurate views of underlying wage dynamics.
Subjects: 
Wage Growth
Selection
Decomposition
Robust Measures
JEL: 
J31
C21
C18
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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