From Online Job Postings to Economic Insights: A Machine Learning Approach to Structuring Naturally Occurring Data

Tatjana Dahlhaus, Reinhard Ellwanger, Gabriela Galassi and Pierre-Yves Yanni

AEA Papers and Proceedings, 2025, vol. 115, 73-78

Abstract: This paper develops a matched vacancy-company dataset by combining daily Canadian online job postings with smartphone-derived visits to points of interest. To address inconsistencies in company names, we enhance natural language processing algorithms for data structuring. The dataset offers granular, real-time labor market insights that complement official statistics. Analyzing technological change during the COVID-19 pandemic, we find that tech firms' expansion significantly drove digital job growth. This suggests the uptick in digital employment arose not only from increased digital adoption but also from new digital production.

JEL-codes: C45 D22 J23 J63 M15 M51 O33 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1257/pandp.20251104

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