scholarly journals Partial Identification of Population Average and Quantile Treatment Effects in Observational Data under Sample Selection

2019 ◽  
Author(s):  
Dimitris Christelis ◽  
Julián Messina
Keyword(s):  
Observational Data ◽  
Treatment Effects ◽  
Sample Selection ◽  
Partial Identification ◽  
Quantile Treatment Effects ◽  
Population Average

scholarly journals Estimation of Population Average Treatment Effects in the FIRST Trial: Application of a Propensity Score-Based Stratification Approach

2017 ◽  
Vol 53 (4) ◽  
pp. 2567-2590 ◽  
Author(s):  
Jeanette W. Chung ◽  
Karl Y. Bilimoria ◽  
Jonah J. Stulberg ◽  
Christopher M. Quinn ◽  
Larry V. Hedges
Keyword(s):  
Propensity Score ◽  
Treatment Effects ◽  
Average Treatment ◽  
Population Average ◽  
Average Treatment Effects

The dangers of inferring treatment effects from observational data

2002 ◽  
Vol 23 (2) ◽  
pp. 106-110 ◽  
Author(s):  
David Dunn ◽  
Abdel Babiker ◽  
Malcolm Hooker ◽  
Janet Darbyshire
Keyword(s):  
Observational Data ◽  
Treatment Effects

Using Observational Data to Estimate Treatment Effects—Reply

JAMA ◽  
2007 ◽  
Vol 297 (19) ◽  
pp. 2075
Author(s):  
Ralph B. D’Agostino ◽  
Ralph B. D’Agostino
Keyword(s):  
Observational Data ◽  
Treatment Effects

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 Quantile Treatment Effects of College Quality on Earnings: Evidence from Administrative Data in Texas

2012 ◽  
Author(s):  
Rodney Andrews ◽  
Jing Li ◽  
Michael Lovenheim
Keyword(s):  
Administrative Data ◽  
Treatment Effects ◽  
College Quality ◽  
Quantile Treatment Effects

scholarly journals Treatment Interactions with Nonexperimental Data in Stata

2011 ◽  
Vol 11 (4) ◽  
pp. 545-555 ◽  
Author(s):  
Graham K. Brown ◽  
Thanos Mergoupis
Keyword(s):  
Experimental Data ◽  
Observational Data ◽  
Treatment Effect ◽  
Treatment Effects ◽  
Average Treatment Effect ◽  
Interaction Parameters ◽  
Average Treatment ◽  
Interaction Terms ◽  
Treatment Interaction ◽  
Predicted Values

Treatment effects may vary with the observed characteristics of the treated, often with important implications. In the context of experimental data, a growing literature deals with the problem of specifying treatment interaction terms that most effectively capture this variation. Some results of this literature are now implemented in Stata. With nonexperimental (observational) data, and in particular when selection into treatment depends on unmeasured factors, treatment effects can be estimated using Stata's treatreg command. Though not originally designed for this purpose, treatreg can be used to consistently estimate treatment interaction parameters. With interactions, however, adjustments are required to generate predicted values and estimate the average treatment effect. In this article, we introduce commands that perform this adjustment for multiplicative interactions, and we show the required adjustment for more complicated interactions.

scholarly journals Unconditional Quantile Treatment Effects Under Endogeneity

2013 ◽  
Vol 31 (3) ◽  
pp. 346-357 ◽  
Author(s):  
Markus Frölich ◽  
Blaise Melly
Keyword(s):  
Treatment Effects ◽  
Quantile Treatment Effects
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