scholarly journals A bootstrap test for instrument validity in heterogeneous treatment effect models

2013 ◽  
Author(s):  
Toru Kitagawa
Keyword(s):  
Treatment Effect ◽  
Bootstrap Test ◽  
Instrument Validity ◽  
Treatment Effect Models ◽  
Heterogeneous Treatment Effect

Treatment Effects and Informative Missingness with an Application to Bank Recapitalization Programs

2014 ◽  
Vol 104 (5) ◽  
pp. 212-217 ◽  
Author(s):  
Angela Vossmeyer
Keyword(s):  
Treatment Effect ◽  
Treatment Effects ◽  
Sample Selection ◽  
Financial System ◽  
Bayesian Framework ◽  
Lender Of Last Resort ◽  
Treatment Effect Models ◽  
Bank Recapitalization

This article develops a Bayesian framework for estimating multivariate treatment effect models in the presence of sample selection. The methodology is applied to a banking study that evaluates the effectiveness of lender of last resort (LOLR) policies and their ability to resuscitate the financial system. This paper employs a novel bank-level dataset from the Reconstruction Finance Corporation, and jointly models a bank's decision to apply for a loan, the LOLR's decision to approve the loan, and the bank's performance a few years after the disbursements. This framework offers practical estimation tools to unveil new answers to important regulatory questions.

scholarly journals Please Call Again: Correcting Non-Response Bias in Treatment Effect Models

2012 ◽  
Author(s):  
Luc Behaghel ◽  
Bruno Crepon ◽  
Marc Gurgand ◽  
Thomas Le Barbanchon
Keyword(s):  
Response Bias ◽  
Treatment Effect ◽  
Treatment Effect Models

scholarly journals Please Call Again: Correcting Nonresponse Bias in Treatment Effect Models

2015 ◽  
Vol 97 (5) ◽  
pp. 1070-1080 ◽  
Author(s):  
Luc Behaghel ◽  
Bruno Crépon ◽  
Marc Gurgand ◽  
Thomas Le Barbanchon
Keyword(s):  
Treatment Effect ◽  
Nonresponse Bias ◽  
Treatment Effect Models

Local Average and Quantile Treatment Effects Under Endogeneity: A Review

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Martin Huber ◽  
Kaspar Wüthrich
Keyword(s):  
Instrumental Variable ◽  
Treatment Effects ◽  
Randomized Experiments ◽  
Quantile Treatment Effects ◽  
Indirect Treatment ◽  
Treatment Effect Models ◽  
Multiple Treatments ◽  
The Relationship ◽  
Local Average ◽  
Heterogeneous Treatment Effect

Abstract This paper provides a review of methodological advancements in the evaluation of heterogeneous treatment effect models based on instrumental variable (IV) methods. We focus on models that achieve identification by assuming monotonicity of the treatment in the IV and analyze local average and quantile treatment effects for the subpopulation of compliers. We start with a comprehensive discussion of the binary treatment and binary IV case as for instance relevant in randomized experiments with imperfect compliance. We then review extensions to identification and estimation with covariates, multi-valued and multiple treatments and instruments, outcome attrition and measurement error, and the identification of direct and indirect treatment effects, among others. We also discuss testable implications and possible relaxations of the IV assumptions, approaches to extrapolate from local to global treatment effects, and the relationship to other IV approaches.

scholarly journals Estimating heterogeneous treatment effect by balancing heterogeneity and fitness

2018 ◽  
Vol 19 (S19) ◽  
Author(s):  
Weijia Zhang ◽  
Thuc Duy Le ◽  
Lin Liu ◽  
Jiuyong Li
Keyword(s):  
Treatment Effect ◽  
Heterogeneous Treatment Effect

Estimating Heterogeneous Treatment Effect on Multivariate Responses Using Random Forests

2021 ◽  
Author(s):  
Boyi Guo ◽  
Hannah D. Holscher ◽  
Loretta S. Auvil ◽  
Michael E. Welge ◽  
Colleen B. Bushell ◽  
...  
Keyword(s):  
Random Forests ◽  
Treatment Effect ◽  
Heterogeneous Treatment Effect ◽  
Multivariate Responses
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