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Extracting O*NET Features from the NLx Corpus to Build Public Use Aggregate Labor Market Data

Author

Listed:
  • Meisenbacher, Stephen
  • Nestorov, Svetlozar
  • Norlander, Peter

Abstract

Data from online job postings are difficult to access and are not built in a standard or transparent manner. Data included in the standard taxonomy and occupational information database (O*NET) are updated infrequently and based on small survey samples. We adopt O*NET as a framework for building natural language processing tools that extract structured information from job postings. We publish the Job Ad Analysis Toolkit (JAAT), a collection of open-source tools built for this purpose, and demonstrate its reliability and accuracy in out-of-sample and LLM-as-judge testing. We extract more than 10 billion data points from more than 155 million online job ads provided by the National Labor Exchange (NLx) Research Hub, including O*NET tasks, occupation codes, tools, and technologies, as well as wages, skills, industry, and more features. We describe the construction of a dataset of occupation, state, and industry level features aggregated by monthly active jobs from 2015 – 2025. We illustrate the potential for research and future uses in education and workforce development.

Suggested Citation

  • Meisenbacher, Stephen & Nestorov, Svetlozar & Norlander, Peter, 2025. "Extracting O*NET Features from the NLx Corpus to Build Public Use Aggregate Labor Market Data," MPRA Paper 126336, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:126336
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    Keywords

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    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J63 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Turnover; Vacancies; Layoffs

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