Tho Pham (University of York) - Augmented Matching Function: Does Search Effort Really Matter?

BOFIT seminars

BOFIT Seminar - Tho Pham (University of York) - Augmented Matching Function: Does Search Effort Really Matter?

Co-authors: Oleksandr Talavera (University of Birmingham) and Bingsong Wang (University of Sheffield)

Abstract
We study how the intensity and distribution of search effort shape matching efficiency in an online labour market. Using unique vacancy–application microdata from a Ukrainian job portal, we find that higher search effort per unemployed worker is strongly associated with more hires, but its marginal productivity declines with labour market tightness. In contrast, search effort is more effective in slack markets, consistent with positive thick‑market externalities on the worker side. To rationalise this, we propose an augmented matching function in which the elasticity of matches with respect to search effort decreases in tightness, generating counter‑cyclical optimal search intensity.

We then examine how applications are distributed across vacancies and job seekers. Concentration measures such as the Herfindahl–Hirschman Index yield ambiguous effects, reflecting directed search toward high‑quality vacancies or highly active applicants. By contrast, inequality measures, i.e., the coefficient of variation and the Gini index, show clear evidence of congestion: when applications are unevenly distributed, some vacancies and job seekers are flooded while others are starved, reducing hires. These negative effects are amplified in tight markets, where duplication of applications is more wasteful. Our results highlight that both the level and the dispersion of search effort are central to understanding matching efficiency, especially when labour markets tighten.

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