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Randomized Evaluation of Institutions: Theory with Applications to Voting and Deliberation Experiments
 

Summary: Randomized Evaluation of Institutions: Theory with Applications
to Voting and Deliberation Experiments
Yves Atchadey
and Leonard Wantchekonz
June 20, 2009
Abstract
We study causal inference in randomized experiments where the treatment is a decision
making process or an institution such as voting, deliberation or decentralized governance. We
provide a statistical framework for the estimation of the intrinsic e¤ect of the institution. The
proposed framework builds on a standard set-up for estimating causal e¤ects in randomized
experiments with noncompliance (Hirano-Imbens-Rubin-Zhou [2000]). We use the model to re-
analyze the e¤ect of deliberation on voting for programmatic platforms in Benin (Wantchekon
[2008]), and provide practical suggestions for estimating intrinsic causal e¤ects of institutions.
1 Introduction
Randomized experiments are a widely accepted approach to infer causal relations in statis-
tics and social sciences. The idea dates back at least to Neyman (1923) and Fisher (1935) and has
been extended by D. Rubin and coauthors (Rubin (1974), Rubin (1978), Rosenbaum and Rubin
(1983)) to observational studies and other more general experimental designs. In this approach,
causality is de...ned in terms of potential outcomes. The causal e¤ect of a treatment, say Treatment
1 (compared to another treatment, Treatment 0) on the variable Y and on the statistical unit i

  

Source: Atchadé, Yves F. - Department of Statistics, University of Michigan

 

Collections: Mathematics