Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/227166 
Erscheinungsjahr: 
2020
Schriftenreihe/Nr.: 
IZA Discussion Papers No. 13639
Verlag: 
Institute of Labor Economics (IZA), Bonn
Zusammenfassung: 
We propose a new model-selection algorithm for Regression Discontinuity Design, Regression Kink Design, and related IV estimators. Candidate models are assessed within a 'placebo zone' of the running variable, where the true effects are known to be zero. The approach yields an optimal combination of bandwidth, polynomial, and any other choice parameters. It can also inform choices between classes of models (e.g. RDD versus cohort-IV) and any other choices, such as covariates, kernel, or other weights. We use the approach to evaluate changes in Minimum Supervised Driving Hours in the Australian state of New South Wales. We also re-evaluate evidence on the effects of Head Start and Minimum Legal Drinking Age. We conclude with practical advice for researchers, including implications of treatment effect heterogeneity.
Schlagwörter: 
regression discontinuity
regression kink
graduated driver licensing
JEL: 
C13
C52
I18
Dokumentart: 
Working Paper

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