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The Use of Online Job Sites for Measuring Skills and Labour Market Trends: A Review

Author

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  • Oleksii Romanko

  • Mary O'Mahony

Abstract

We explore the use of online job postings as an innovative complementary source of labour demand statistics. The paper concentrates on new developments in the area, including the usage and validation of online data sources, trends, biases and caveats of the data generation and data extraction process. We provide detailed explanations of the data cleansing and data preparation process which proves to be useful for anyone working with raw online data sources. We explore the general data pipeline underpinning continuous data mining and data utilization, that could be beneficial for any organization building its own online data analysis process. We provide detailed discussions of the design of the skills extraction process using word2vec model. We discuss the application of the model and explore some of the skills analysis methods and visualizations, such as job titles, salaries, frequent skills histograms, skills correlation scatterplots, graph analysis of skills co-occurrence, UK regional skills analysis. We applied regression analysis, outlining various effects of person competencies on the salary. We conclude that online job postings provide rich and extensive insights into the labour market and can complement the official statistics.

Suggested Citation

  • Oleksii Romanko & Mary O'Mahony, 2022. "The Use of Online Job Sites for Measuring Skills and Labour Market Trends: A Review," Economic Statistics Centre of Excellence (ESCoE) Technical Reports ESCOE-TR-19, Economic Statistics Centre of Excellence (ESCoE).
    • Handle: RePEc:nsr:escoet:escoe-tr-19
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    References listed on IDEAS

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    1. Acemoglu, Daron & Scott, Andrew, 1994. "Asymmetries in the Cyclical Behaviour of UK Labour Markets," Economic Journal, Royal Economic Society, vol. 104(427), pages 1303-1323, November.
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    Cited by:

    1. Dossche, Wouter & Vansteenkiste, Sarah & Baesens, Bart & Lemahieu, Wilfried, 2026. "Anticipating delays in recruitment: Explainable machine learning for the prediction of hard-to-fill online job vacancies," European Journal of Operational Research, Elsevier, vol. 328(2), pages 680-693.
    2. Marc Pinski & Thomas Hofmann & Alexander Benlian, 2024. "AI Literacy for the top management: An upper echelons perspective on corporate AI orientation and implementation ability," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-23, December.

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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
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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