Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/284202 
Year of Publication: 
2022
Series/Report no.: 
IFS Working Papers No. 22/32
Publisher: 
Institute for Fiscal Studies (IFS), London
Abstract: 
We set up a framework to conduct experiments for estimating spillover effects when units are grouped into mutually exclusive clusters. We improve upon existing methods by allowing for heteroskedasticity, intra-cluster correlation and cluster size heterogeneity, which are typically ignored when designing experiments. We show that ignoring these factors can severely overestimate power and underestimate minimum detectable effects. We derive formulas for optimal group-level assignment probabilities and the power function used to calculate power, sample size, and minimum detectable effects. We apply our methods to the design of a large-scale randomized communication campaign in a municipality of Argentina to estimate total and neighborhood spillover effects on property tax compliance. Besides the increase in tax compliance of individuals directly targeted with our mailing, we find evidence of spillover effects on untreated individuals in street blocks where a high proportion of taxpayers were notified.
Subjects: 
two-stage designs
partial population experiments
spillovers
randomization
property tax
tax compliance
JEL: 
H71
H26
H21
O23
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.