``Waiting for life to arrive: a history of the regression-discontinuity design in psychology, statistics and economics

DOI10.1016/j.jeconom.2007.05.002zbMath1418.62436OpenAlexW2063022356WikidataQ56706026 ScholiaQ56706026MaRDI QIDQ291076

Thomas D. Cook

Publication date: 6 June 2016

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

Full work available at URL: https://doi.org/10.1016/j.jeconom.2007.05.002

zbMATH Keywords

statisticspsychologyeconomicshistory of regression discontinuity

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric estimation (62G05) Research exposition (monographs, survey articles) pertaining to statistics (62-02) Applications of statistics to psychology (62P15)

Related Items (13)

Model uncertainty and model averaging in regression discontinuity designs ⋮ Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach ⋮ Regression discontinuity: review with extensions ⋮ Quantile treatment effects in the regression discontinuity design ⋮ Extending the regression-discontinuity approach to multiple assignment variables ⋮ Causal inference by quantile regression kink designs ⋮ Robust uniform inference for quantile treatment effects in regression discontinuity designs ⋮ A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs ⋮ Nonparametric identification and estimation of dynamic treatment effects for survival data in a regression discontinuity design ⋮ Do School Districts Affect NYC House Prices? Identifying Border Differences Using a Bayesian Nonparametric Approach to Geographic Regression Discontinuity Designs ⋮ Understanding Estimators of Treatment Effects in Regression Discontinuity Designs ⋮ Instrumental variables: an econometrician's perspective ⋮ Evaluating the causal effect of university grants on student dropout: evidence from a regression discontinuity design using principal stratification

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• Estimating the superiority of a drug to a placebo when all and only those patients at risk are treated with the drug.
• Estimating a multiplicative treatment effect under biased allocation
• Identification and Estimation of Local Average Treatment Effects

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