Technology and Labor Displacement: Evidence from Linking Patents with Worker-Level Data

Leonid Kogan, Dimitris Papanikolaou, Lawrence Schmidt and Bryan Seegmiller

No 31846, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We develop measures of labor-saving and labor-augmenting technology exposure using textual analysis of patents and job tasks. Using US administrative data, we show that both measures negatively predict earnings growth of individual incumbent workers. While labor-saving technologies predict earnings declines and higher likelihood of job loss for all workers, labor-augmenting technologies primarily predict losses for older or highly-paid workers. However, we find positive effects of labor-augmenting technologies on occupation-level employment and wage bills. A model featuring labor-saving and labor-augmenting technologies with vintage-specific human capital quantitatively matches these patterns. We extend our analysis to predict the effect of AI on earnings.

JEL-codes: E0 E01 J01 J23 J24 O3 O4 (search for similar items in EconPapers)
Date: 2023-11
New Economics Papers: this item is included in nep-lma and nep-tid
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