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Letting Job Postings Talk: Recent Trends in Digitalization

In: Big Data Applications in Labor Economics, Part B

Author

Listed:
  • Gabriela Galassi
  • Alejandra Bellatin
  • Vivian Chu

Abstract

We construct a novel dataset of Canadian online job postings, classified by occupation. The data, provided by Indeed, an online job board, represents vacancies advertised by employers across Canada. We have classified these job postings into standard occupations using text analytics. This dataset has been used to study changes in the demand for jobs linked to digitalization over the COVID-19 pandemic. To this end, we leverage time-series and cross-sectional variations in COVID-19 containment policies, examining their impact on jobs broadly related to digitalization. Our findings reveal that vacancies in digital production jobs increased more substantially than in traditional jobs during the reopening phases. However, no substantial differences were observed when considering different types of vacancies according to the use of digital technologies (i.e., occupations at low risk of automation or those that allow remote work). Overall, our results do not support the popular idea that the COVID-19 pandemic marked a significant turning point in digitalization trends, but rather document a modest shift in this direction.

Suggested Citation

  • Gabriela Galassi & Alejandra Bellatin & Vivian Chu, 2024. "Letting Job Postings Talk: Recent Trends in Digitalization," Research in Labor Economics, in: Big Data Applications in Labor Economics, Part B, volume 52, pages 1-33, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:rleczz:s0147-91212024000052b022
    DOI: 10.1108/S0147-91212024000052B022
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