Using online vacancy and job applicants’ data to study skills dynamics

Bennett, Fidel,, Verónica Escudero, Hannah Liepmann and Podjanin, Ana,

ILO Working Papers from International Labour Organization

Abstract: This paper finds that big data on vacancies and applications to an online job board can be a promising data source for studying skills dynamics, especially in countries where alternative sources are scarce. To show this, we develop a skills taxonomy, assess the characteristics of such online data, and employ natural language processing and machine-learning techniques. The empirical implementation uses data from the Uruguayan job board BuscoJobs, but can be replicated with similar data from other countries.

Keywords: skills development; job seeker; trend (search for similar items in EconPapers)
Pages: 1 online resource (50 p.) pages
Date: 2022
New Economics Papers: this item is included in nep-big and nep-pay
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Published in ILO working paper series

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https://doi.org/10.54394/EWWE6877 (application/pdf)

Related works:
Chapter: Using Online Vacancy and Job Applicants' Data to Study Skills Dynamics (2024)
Working Paper: Using Online Vacancy and Job Applicants' Data to Study Skills Dynamics (2022)
Working Paper: Using Online Vacancy and Job Applicants' Data to Study Skills Dynamics (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:ilo:ilowps:995202692602676

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