Urn-Ball Search Coordination Frictions
Standard Cobb-Douglas matching functions assume constant marginal returns to search intensity and omit double-coordination failures. They fail to explain why increased application volume across job seekers can reduce nonparticipant matching rates while simultaneously expanding regional job vacancies.
Picture this
Imagine hundreds of job applicants mailing resumes to local businesses without knowing where anyone else applied. Some popular companies receive dozens of applications and can only hire one person while rejecting the rest, whereas other companies receive zero applications and leave their job openings completely empty.
What the evidence says
Increasing application intensity per worker initially reduces search friction but eventually yields diminishing marginal returns due to severe application clustering, capturing how nonparticipant matching rates drop from 18.2% to 16.0% under full activation ($\tau = 1.0$).
- Who
- Structural discrete-time DMP model with 89,466 benefit spells and monthly vacancy stocks across 14 Danish counties.
- How
- Structural estimation of an endogenous urn-ball matching function incorporating dual coordination frictions (applicant unawareness of competitors and firm unawareness of applicant alternative offers) via indirect inference.
What to do
Incorporate dual coordination frictions into search-and-matching models when evaluating market-wide impacts of policy-induced search intensity changes.
From the source
"There are two coordination frictions affecting job finding: (i) workers do not know where other workers apply, and (ii) firms do not know which candidates are considered by other firms."
Estimating Equilibrium Effects of Job Search Assistance