Welfare Contrasts in Policy Choice

Picture this

Think of evaluating a new school lunch menu against the old default menu. Welfare contrast 1 checks if adapting choices during the school year fed kids better than flipping a coin every day. Contrast 2 measures how much health improves if every single student gets their exact personalized ideal meal instead of the old default. Contrast 3 measures how much health improves if every student gets the single best overall group meal instead of the old default.

What the evidence says

Contrast $\Delta_1 = 0.002$ (95% CS: [0.000, 0.004]), showing negligible in-sample adaptive gain due to muted 6-week treatment effects. Contrast $\Delta_2 = 0.017$ (95% CS: [0.001, 0.034]), demonstrating a 35% gain in employment for the optimal targeted policy over control. Contrast $\Delta_3 = 0.006$ (95% CS: [-0.015, 0.027]), showing half the gain for an un-targeted policy.

Who was studied

N = 3,770 Syrian refugees and Jordanian jobseekers in urban Jordan.

How

Bayesian hierarchical posterior expectations evaluating three formal welfare contrasts ($\Delta_1$: adaptive vs equal random assignment; $\Delta_2$: optimal targeted policy vs control; $\Delta_3$: optimal non-targeted policy vs control) on 6-week wage employment.

What to do

Calculate formal welfare contrasts ($\Delta_1, \Delta_2, \Delta_3$) comparing observed adaptive allocations, optimal targeted policies, and non-targeted policies against baseline controls to isolate targeting gains from adaptive design gains.

From the source

"We estimate that the optimal targeted policy has a treatment effect on six-week employment that is one percentage point larger than the optimal non-targeted policy..."

An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan

Tags

• welfare contrasts
• policy targeting
• experimental evaluation