Sensitivity of crash models to alternative specifications
AbstractThis paper examines the sensitivity of policy conclusions that are derived from crash models using various specifications. Our analyses compare models specified as crash rate or population normalized models (i.e., fatalities per capita or per vehicle miles traveled) adjusted to account for serial correlation in the error term with negative binomial count models with the total number of fatalities as the dependent variable. Our analyses focus on the interpretation of key policy variables, especially the association between safety-belt laws and administrative license revocation laws on fatalities. Evaluation of statistical significance of parameters, elasticities derived from the models and total fatalities associated with changes in key variables are examined. Results suggest that negative binomial models tend to be more robust and display less variation in results than those linear regression models that account for serial correlation. From a policy perspective, we found no evidence that passage of administrative license revocation laws that automatically suspend the license of a drunk driver have been effective while laws requiring safety-belt usage have been effective. Our results suggest that providing confidence intervals on elasticity estimates and estimated fatalities would provide policy makers with greater confidence in the results of model estimates.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Transportation Research Part E: Logistics and Transportation Review.
Volume (Year): 41 (2005)
Issue (Month): 5 (September)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Xiaokun Wang & Kara Kockelman, 2007. "Specification and estimation of a spatially and temporally autocorrelated seemingly unrelated regression model: application to crash rates in China," Transportation, Springer, vol. 34(3), pages 281-300, May.
- Robert Noland & Mohammed Quddus & Washington Ochieng, 2008. "The effect of the London congestion charge on road casualties: an intervention analysis," Transportation, Springer, vol. 35(1), pages 73-91, January.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.