Job Polarization and Jobless Recoveries

By Nir Jaimovich, Henry E. Siu. Review of Economics and Statistics, 2020

333 citations recorded by the source corpus.

Abstract Job polarization refers to the shrinking share of employment in middle-skill, routine occupations experienced over the past 35 years. Jobless recoveries refers to the slow rebound in aggregate employment following recent recessions despite recoveries in aggregate output. We show how these two phenomena are related. First, essentially all employment loss in routine occupations occurs in economic downturns. Second, jobless recoveries in the aggregate can be accounted for by jobless recoveries in the routine occupations that are disappearing.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/209ac6a1cf6abba275d99f29377d780e4edfffe4

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In Economics and Econometrics

Citations in the corpus

Political machinery: did robots swing the 2016 US presidential election? (2018, methodology): “Identifying the workers that have lost out to automation is empirically challenging, yet it is evident from a series of studies that automation has led to the displacement of workers particularly in routine or middle-skill occupations which has led to a polarization of the US labour market (Autor et”
Heterogeneous Labor Market Impacts of the COVID-19 Pandemic (2020, background): “In line with the Jaimovich and Siu (2020) evidence, the figure shows that the job losses during the Great Recession were disproportionately concentrated among middle-wage occupations and industries, both at the point of the employment trough, in December 2009, and also in the recovery period, in…”
Artificial Intelligence as Augmenting Automation: Implications for Employment (2020, background): “Furthermore, studies suggest that those on the lower-skilled end of routine manual work are unlikely to migrate upwards to the “cognitive” categories of work (Jaimovich and Siu, 2020).”
Upskilling: Do Employers Demand Greater Skill When Workers Are Plentiful? (2015, background): “For example, prior research has demonstrated that changes over the business cycle are subtle and complicated because both cyclical and structural factors can interact (Jaimovich and Siu 2018; Charles, Hurst, and Notowidigdo 2016).”