Stratified Partial Likelihood for Externality Identification

Picture this

Imagine tracking runners in two different high schools across two different semesters. To figure out if a mandatory training program in School A hurt the non-trained runners on the same track, comparing trained versus untrained runners in School A is insufficient. Untrained runners in School A must be compared to runners in School B across both semesters, controlling for overall weather changes across semesters without assuming how fast runners normally tire out.

What the evidence says

Participation in the activation program reduced non-participants' unemployment exit hazard rate by approximately 5% ($\gamma = -0.048$, p < 0.10 in full covariate model; $\gamma = -0.079$, p < 0.05 in South Jutland sub-sample).

Who was studied

N = 89,466 unemployed benefit spells (40,403 experiment period, 49,063 pre-experiment period) across 14 Danish counties.

How

Stratified partial likelihood proportional hazard estimation comparing non-participants in trial counties (Storstrøm and South Jutland) to comparison counties, stratifying duration dependence by calendar cohort.

What to do

Apply stratified partial likelihood proportional hazard models using non-experiment comparison regions to isolate non-treated spillover effects without imposing parametric hazard assumptions.

From the source

"The key advantage of stratified partial likelihood estimation is that it does not require any functional form restriction on the duration dependence pattern... The effect of the presence of the activation program on the nonparticipants in the program is a reduction in the exit rate of about five percent."

816b5187-9076-4043-aba7-184043b2e524-Estimating Equilibrium Effects of Job Search Assistance.pdf

Tags

• duration analysis
• partial likelihood
• spillover effects