Byline: Jerry Taylor, SPECIAL TO THE WASHINGTON TIMES
Another salvo in the war over America's SUVs was fired recently when Jeffrey Runge, a doctor who just so
happens to head the Bush administration's National Highway Traffic Safety Administration, declared that SUVs pose an "astounding" threat to their owners due to their proclivity to roll over and that strict new regulations may be in the offing.
"The thing that I don't understand is people, when they choose to buy a vehicle, they might go sit in it and say, 'Gee, I feel safe,' " said Dr. Runge. "Well, sorry, but you know gut instinct is great for a lot of stuff, but it's not very good for buying a safe automobile."
Well, medical doctors may be great at a lot of stuff, but they're not necessarily very good at assessing non-medical data. The public, in fact, is right and Dr. Runge, in fact, is wrong.
It is true that SUVs are more dangerous to be in should they roll over than are most passenger vehicles. But only 3 percent of all accidents involve roll-overs.
If you're driving an SUV and get into an accident, most of the time it will involve hitting (or getting hit by) something. Accordingly, drivers are right not to worry too much about rolling over in their vehicles, particularly because it can be avoided simply by eschewing NASCAR racing practices when making sharp turns.
The "gut instinct" of SUV owners that increased safety in one- or two-car collisions more than offsets the risk of roll-overs was validated last October in a remarkable study published by the National Bureau of Economic Research and authored by University of Michigan economist Michelle White. Miss White managed to secure data regarding each and every automotive accident reported to the police between 1995-99. She examined three types of crashes: those involving two vehicles, those involving a single vehicle, and those involving a vehicle striking a pedestrian or bicyclist.
Vehicles were divided into five categories: cars, SUVs, pickups and minivans, large trucks, and buses. She then performed a regression analysis of the data, controlling for seatbelt use, urban and rural conditions, weather, time of day, negligence, age of the drivers, road type, speed, and number of vehicular occupants. …