Journal of Financial and Quantitative Analysis · 2023 · 40 citations · 48 references
ManagementBusiness AnalyticsHuman Resource ManagementLabor Market AnalysisMachine LearningRecruitmentEmployee TrainingLabor Market TrendsWorkforce ManagementConstraintsFlexibilityJob Ad Content AnalysisJob Advertisement Text MiningJob Advertisements AnalysisJob Posting Text MiningMachine Learning In HiringSkill Profiles
Abstract Big data on job postings reveal multiple facets of the impact of COVID-19 on corporate hiring. Firms disproportionately cut new hiring for high-skill positions, with financially constrained firms reducing skilled hiring the most. Applying machine learning methods to job-ad texts, we find that firms have skewed their hiring toward operationally-core functions. New positions display greater flexibility regarding schedules and tasks. While job posting levels show signs of recovery starting in late-2020, changes to job descriptions and skill profiles persist through early-2022. Financial constraints amplify these changes, with constrained firms’ new hires witnessing greater adjustments to job roles and employment arrangements.
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