Optimal multi‐action treatment allocation: A two‐phase field experiment to boost immigrant naturalization

B-Tier
Journal: Journal of Applied Econometrics
Year: 2024
Volume: 39
Issue: 7
Pages: 1379-1395

Authors (4)

Achim Ahrens (ETH Zurich, Departement Geiste...) Alessandra Stampi‐Bombelli (not in RePEc) Selina Kurer (not in RePEc) Dominik Hangartner (not in RePEc)

Score contribution per author:

0.503 = (α=2.01 / 4 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

Research underscores the role of naturalization in enhancing immigrants' socio‐economic integration, yet application rates remain low. We estimate a policy rule for a letter‐based information campaign encouraging newly eligible immigrants in Zurich, Switzerland, to naturalize. The policy rule assigns one out of three treatment letters to each individual, based on their observed characteristics. We field the policy rule to one‐half of 1717 immigrants, while sending random treatment letters to the other half. Despite only moderate treatment effect heterogeneity, the policy tree yields a larger, albeit insignificant, increase in application rates compared with assigning the same letter to everyone.

Technical Details

RePEc Handle
repec:wly:japmet:v:39:y:2024:i:7:p:1379-1395
Journal Field
Econometrics
Author Count
4
Added to Database
2026-01-24