Using online job postings to predict key labour market indicators

Abstract

We explore data collected as an administrative by-product of an online job advertisement portal with dominant market coverage in Slovakia. Specifically, we process information on the aggregate quarterly registered number of online job vacancies. We assess the potential of this information in predicting official vacancy, employment and unemployment statistics. We compare the characteristics of the online job posting data with those reported in comparable studies conducted for the Netherlands and Italy. Several differences are identified; most notably, our data are more persistent and stationary around a linear time trend. Additionally, we assess the predictive potential of the online job posting data by comparing in-and out-of-sample estimates of three regression models that predict job vacancy statistics and employment and unemployment levels one to four quarters ahead. Irrespective of the predictive horizon and labour market indicator, the online job posting data always provide a statistically significant predictor. These results are further solidified in an out-of-sample study that shows that forecast errors are lowest for predictions generated by models incorporating online job posting data. In general, the usefulness of the data seems best for longer forecast horizons.

Methodological issues related to the use of online labour market data

“…As a consequence, using online job vacancies as a data source for calculating common labour market indicators (such as number of vacancies, labour market tightness, degree of skill mismatch) has become a relatively common practice for scholars and practitioners (Japec and Lyberg 2020;Štefánik, Lyócsa, and Bilka [2022]; Turrell et al 2019). Interesting micro-level applications of online labour market data, beyond skills analysis, include those focusing on the value of the migration experience in employers' demands (Kureková and Žilinčíková, 2018); the role of occupational mismatch in explaining the productivity puzzle (Turrell et al 2021); the relationship between firm credit crunch and employee job search behaviour (Gortmaker, Jeffers, and Lee 2021); discrimination against women in the labour market (Kuhn and Shen 2013); or links between the introduction of unemployment benefits, job searches and job postings during the Great Recession in the US (Marinescu 2017).…”