Do high-wage jobs attract more applicants? Directed search evidence from the online labor market

Summary

This research paper, "Do high-wage jobs attract more applicants? Directed search evidence from the online labor market," by Stefano Banfi and Benjamín Villena-Roldán, published in 2019, explores the phenomenon of directed search in online labor markets. The core hypothesis is that job seekers will direct their applications towards higher-wage opportunities, thereby increasing labor market efficiency. The authors leverage a unique dataset from an online job board that provides not only information on explicitly posted wages but also allows econometricians to observe the intended wages even when employers choose not to make them visible to applicants. This distinctive data feature is crucial for addressing potential selection bias in previous studies that may have overlooked jobs with implicit or "hidden" wages. The methodology involves analyzing a large dataset from an online job board. This microdata enables the researchers to observe job seekers' application behavior and discern how they respond to wage information, both explicit and implicit. The study acknowledges that explicit-wage ads often target unskilled workers, meaning that analyses focusing solely on these ads might suffer from selection bias. By including data where wages are not explicitly declared but are known to the researchers, Banfi and Villena-Roldán offer a more comprehensive understanding of directed search. They also examine how job ad requirements align with applicants' traits, as predicted by directed search models that incorporate worker heterogeneity. The findings strongly support the existence of directed search in online labor markets: high-wage job advertisements indeed attract a greater number of applicants. Furthermore, the research reveals a significant, albeit milder, directed search for "hidden" or implicit wages. This suggests that the language, requirements, and other textual elements within job advertisements tacitly convey information about the expected wage, guiding job seekers' application decisions. The alignment between job ad requirements and applicant characteristics is also confirmed, which is consistent with theoretical models of directed search that account for heterogeneity among workers. The paper highlights that estimates from previous literature that ignore hidden-wage ads might be subject to selection bias, particularly because explicit-wage ads frequently target less-skilled individuals. The authors suggest that job ads with hidden wages act as "noisy signals" of high expected wages, designed to attract skilled applicants and potentially deter less-skilled ones.