Randomized Saturation Spillover Dynamics
RCTReview
Evaluating whether job search policies displace non-treated job-seekers or generate positive information spillovers through local social networks requires measuring indirect effects across varying treatment density levels.
Picture this
Varying the percentage of treated individuals across neighborhood clusters tests whether helping one worker harms neighboring job-seekers. It operates like testing different concentrations of water purification in distinct villages to see if clean water in one household improves or restricts neighbor access.
What the evidence says
Average indirect spillover effects on untreated neighbors were statistically zero across employment (-4.6 percentage points, p > 0.10) and earnings (-41.1 ETB, p > 0.10), proving that search interventions at this scale do not displace non-treated youth in integrated urban labor markets.
- Who was studied
- N = 3,052 youth clustered in 179 geographic units in Addis Ababa, Ethiopia.
- How
- Two-stage randomized saturation design varying cluster treatment density from 10% to 90% in transport clusters and 80% in workshop clusters.
What to do
Implement cluster-based randomized saturation designs to audit local labor market displacement before scaling youth employment policies.
From the source
"We find no difference between untreated individuals living in geographical clusters assigned to one of the two interventions and untreated individuals in pure control clusters."
Anonymity_or_Distance_Job_Search_and_Labour_Market_Exclusion_in.pdf