Letting Job Postings Talk: Recent Trends in Digitalization

Gabriela Galassi, Alejandra Bellatin and Vivian Chu

A chapter in Big Data Applications in Labor Economics, Part B, 2024, vol. 52B, pp 1-33 from Emerald Group Publishing Limited

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.

Keywords: Job postings; labor demand; digitalization; text analytics; COVID-19 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eme:rleczz:s0147-91212024000052b022

DOI: 10.1108/S0147-91212024000052B022

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