Replicating the Levitt and Porter estimates of drunk driving
Bibliographic Data
| ID | 21653359 |
|---|---|
| Authors | Richard A Dunn (0000-0003-0415-6662, Department of Agricultural and Resource Economics University of Connecticut Storrs Connecticut USA, corresponding author), Nathan Tefft (0000-0002-2758-8700, Bates College), Nathan W Tefft (Department of Economics Bates College Lewiston Maine USA) |
| Year | 2020 |
| Volume | 35 |
| Issue | 6 |
| Pages | 786-796 |
| Publication date | 2020-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Applied Econometrics (JOURNAL) |
| Journal identifiers | ISSN: 1099-1255 • E-ISSN: 0883-7252 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/jae.2782 |
| OpenAlex | W3033731491 |
| Language | EN |
| Citations received | 1 |
| References cited | 9 |
Estimates of the prevalence and risk of drinking‐and‐driving are a high‐priority need for researchers and policymakers. Levitt and Porter ( Journal of Political Economy , 2001, 109 (6), 1198–1237) demonstrate how these can be recovered using publicly available information in the Fatality Analysis Reporting System (FARS). Although robust to systematic misreporting and sample selection and far cheaper to implement than surveys, their methodological innovations are largely ignored. We believe this arises partly from difficulty in replicating their results. This article identifies the underlying causes of replication failure and offers practical guidance for future implementation that takes advantage of the current structure of the FARS data
Business · Computer security · Drunk driving · Econometrics · Economics · Environmental health · Operations research · Poison control · Political science · Politics · Public economics · Statistics · Computer Science · Energy, Environment, and Transportation Policies · Engineering · Human Factors and Ergonomics · Law · Mathematics · Medicine · Substance Abuse Treatment and Outcomes · Traffic and Road Safety · Artificial Intelligence
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |