Micro-Market Priority Targeting Algorithm
RCTReview
Public employment agencies frequently distribute recruitment assistance uniformly across sectors, diluting resources in healthy markets while under-serving severely depressed local labor markets.
Picture this
Imagine an emergency medical team routing ambulances specifically to neighborhoods experiencing the highest density of critical calls, rather than patrolling every street evenly regardless of need.
What the evidence says
Prioritizing small and medium-sized firms (5 to 250 employees) in low-tightness micro-markets concentrated treatment among high-need sectors, achieving a 24% increase in permanent vacancies (p < 0.01) while keeping the proportion of treated firms in any single micro-market below 2% median.
- Who was studied
- N = 7,438 firms across 129 local employment agencies representing 85 French commute zones.
- How
- Algorithmic ranking of local sectors using baseline survey data (BMO survey on 400,000 firms) weighted by agency-level jobseeker stocks, local labor tightness ($\theta \approx 0.42$), and job-finding probabilities.
What to do
Construct a priority targeting index that ranks sectors by local labor market tightness and job-finding rates to direct employer outreach toward the most depressed micro-markets.
From the source
"We created a priority ranking of professions per agency based on local-level tightness and job finding probabilities weighted by the stock of jobseekers registered in the agency. Using a profession-sector correspondence table, we then merged these 'priority professions' to sectors."
Are_Active_Labor_Market_Policies_Directed_at_Firms_Effective_Evidence.pdf