Methodological issues related to the use of online labour market data

Brian Fabo and Kurekova, Lucia Mytna,
Authors registered in the RePEc Author Service: Lucia Mytna Kurekova

ILO Working Papers from International Labour Organization

Abstract: This report provides a mapping of existing research that employs online labour market data, covering both online job vacancies (demand side) and online applicant data (CVs) (supply side). We discuss and assess a variety of tools and empirical methods that have been used to address specific disadvantages of this data, such as non-representativeness or fluctuations in data quantity and structure; these may be due to external shocks, such as the COVID-19 pandemic. We find that while this research field has expanded rapidly, including with respect to geographical coverage, many empirical studies do not engage with the methodological aspects and weaknesses of online labour market data and take them at face value. We highlight that there are legitimate research approaches, which are inductive in nature, focused on discovering patterns and trends in underlying data. These are by definition less concerned with generalizability of findings, as they have different objectives. For this body of research, online labour market data open new avenues for understanding developments in labour markets. We also argue that biases in online labour market data emerge due to multiple factors. With respect to the order of discrepancies between online labour market data and representative data sources, these are typically not paramount. Different techniques have been adopted to deal with the non-representativeness problem, such as statistical techniques; adapting the research questions and research focus to the quality of data; and use of mixed methods, including qualitative methods, to increase the robustness of results.

Keywords: labour market; job vacancy; curriculum vitae; research method; data collecting; information technology (search for similar items in EconPapers)
Pages: 1 online resource (40 p.) pages
Date: 2022
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Published in ILO working paper series

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Persistent link: https://EconPapers.repec.org/RePEc:ilo:ilowps:995191692102676

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