Predicting the efficacy of future training programs using past experiences at other locations

DOI10.1016/J.JECONOM.2004.04.009zbMath1334.62219OpenAlexW2131428863WikidataQ108880125 ScholiaQ108880125MaRDI QIDQ262733

Guido W. Imbens, Julie H. Mortimer, V. Joseph Hotz

Publication date: 30 March 2016

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2004.04.009

zbMATH Keywords

predictionheterogeneityefficacytraining programs

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Statistical methods; economic indices and measures (91B82)

Related Items (6)

Semiparametric estimation of long-term treatment effects ⋮ Difference-in-differences with variation in treatment timing ⋮ A simple approximation for evaluating external validity bias ⋮ Evidence of randomisation bias in a large-scale social experiment: the case of ERA ⋮ Learning Optimal Distributionally Robust Individualized Treatment Rules ⋮ Program evaluation as a decision problem

Cites Work

• Rejoinder: ``Does matching overcome LaLonde's critique of nonexperimental estimators?
• Bayesian inference for causal effects: The role of randomization
• Observational studies
• The central role of the propensity score in observational studies for causal effects
• Identification and Estimation of Local Average Treatment Effects
• On the Role of the Propensity Score in Efficient Semiparametric Estimation of Average Treatment Effects
• Characterizing Selection Bias Using Experimental Data
• Estimating the Labor Market Impact of Voluntary Military Service Using Social Security Data on Military Applicants
• Large Sample Properties of Matching Estimators for Average Treatment Effects
• Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score

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