You drink, you drive, you die? : The dynamics of youth risk taking in response to a change in the legal drinking age / Stefan Boes (University of Lucerne), Steven Stillman (Free University of Bozen-Bolzano and IZA) ; IZA, Institute of Labor Economics
VerfasserBoes, Stefan In der Gemeinsamen Normdatei der DNB nachschlagen ; Stillman, Steven In der Gemeinsamen Normdatei der DNB nachschlagen
KörperschaftForschungsinstitut zur Zukunft der Arbeit In der Gemeinsamen Normdatei der DNB nachschlagen
ErschienenBonn, Germany : IZA Institute of Labor Economics, February 2017
Elektronische Ressource
Umfang1 Online-Ressource (21, 9, 4 Seiten) : Diagramme
SerieDiscussion paper ; no. 10543
URNurn:nbn:de:hbz:5:2-112854 Persistent Identifier (URN)
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This paper exploits the reduction in the legal drinking age in New Zealand from 20 to 18 to study the dynamics of youth risk taking. Using administrative data on the universe of road accidents over a fifteen year period spanning the law change, we undertake three complimentary analyses to examine the dynamics of alcohol-related and total vehicular accidents among youth. First, using an event history approach, we find no evidence that changing the drinking age from 20 to 18 led to more vehicular accidents or alcohol-related accidents among teens. This is true both in the short-run following the law change and when examining cumulative accidents for the affected cohorts. Next, using an age-based regression discontinuity design (RDD), we find that accidents do increase after ones 18th birthday, but this appears to be a short-run phenomenon. Finally, estimating flexible parametric regression models suggests that reducing the drinking age led to a decline in risky driving by youth who were already 15 at the time of the change but had no longerrun impacts. Overall, our results support the argument that the legal drinking age can be lowered without increasing detrimental outcomes for youth and call into question previous studies that have made policy recommendations by extrapolating from results identified using age-based RDDs.