Arbeitspapier

Matching through search channels

Firms and workers predominately match via job postings, networks of personal contacts or the public employment agency, all of which help to ameliorate labor market frictions. In this paper we investigate the extent to which these search channels have differential effects on labor market outcomes. Using novel linked survey-administrative data we document that (i) low-wage firms and low-wage workers are more likely to match via networks or the public agency, while high-wage firms and high-wage workers succeed more often via job postings; (ii) job postings help firms the most in poaching and attracting high-wage workers and help workers the most in climbing the job ladder. To evaluate the implications of these findings for employment, wages and labor market sorting, we structurally estimate an equilibrium job ladder model featuring two-sided heterogeneity, multiple search channels and endogenous recruitment effort. The estimation reveals that networks are the most cost-effective channel, allowing firms to hire quickly, yet attracting workers of lower average ability. Job postings are the most costly channel, facilitate hiring workers of higher ability, and matter most for worker-firm sorting. Although the public employment agency provides the lowest hiring probability, its removal has sizeable consequences, with aggregate employment declining by at least 1.4 percent and rising bottom wage inequality.

Language
Englisch

Bibliographic citation
Series: IAB-Discussion Paper ; No. 10/2023

Classification
Wirtschaft
Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
Labor Demand
Wage Level and Structure; Wage Differentials
Labor Turnover; Vacancies; Layoffs
Unemployment: Models, Duration, Incidence, and Job Search
Subject
Search Channels
On-the-job search
Recruitment effort
Sorting
Wage dispersion

Event
Geistige Schöpfung
(who)
Carrillo-Tudela, Carlos
Kaas, Leo
Lochner, Benjamin
Event
Veröffentlichung
(who)
Institut für Arbeitsmarkt- und Berufsforschung (IAB)
(where)
Nürnberg
(when)
2023

DOI
doi:10.48720/IAB.DP.2310
Handle
Last update
20.09.2024, 8:23 AM CEST

Data provider

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Object type

  • Arbeitspapier

Associated

  • Carrillo-Tudela, Carlos
  • Kaas, Leo
  • Lochner, Benjamin
  • Institut für Arbeitsmarkt- und Berufsforschung (IAB)

Time of origin

  • 2023

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