The impact of US productivity growth on unemployment in the time–frequency domain: is AI causing a change in the relationship?

Patrick Crowley and David Hudgins

Empirical Economics, 2024, vol. 66, issue 5, No 10, 2169-2190

Abstract: Abstract US data are used to explore the relationship between the unemployment rate and productivity at different cycle lengths by employing time–frequency methodology. Previous studies suggest that the unemployment rate is positively related to productivity increases in the short-run (high frequency ranges), and negatively related at the longer-intervals (low frequency ranges)—and although we largely reproduce these results, with more recent data, we also provide some important additional insights. The extended results show the relationship between unemployment and productivity in the time–frequency domain using growth in corporate profitability as a conditioning variable, to observe the long-term stability of the productivity-unemployment relationship. We find that when conditioned on the growth in corporate profits, the response of unemployment to the growth in productivity has become much stronger and faster in recent years, with the result that labor market adjustments are no longer keeping pace with the technological change. Not only this, but the usual explanation that short-term losses in employment consequent on growth in productivity is outweighed by long-term gains appears to be weakening and our results suggest that this may already be reversing, perhaps in response to the AI revolution currently underway.

Keywords: Time–frequency domain; Continuous wavelet transform; Unemployment; Productivity growth; Business cycle (search for similar items in EconPapers)
JEL-codes: C49 C88 E24 E32 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s00181-023-02510-x

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