Monday, June 11, 2007
How do you weigh the cost of the change (extra travelling time for some) against the benefits (fewer people such as myself killed or injured)?
NSW and Victoria do it differently.
NSW is intentionally lax in its enforcement of speed rules. It is thought to allow a margin of 10 per cent over the speed limit before issuing a fine. Victoria is strict. As little as 3 km/h over the speed limit and you're gone.
The free-and-easy approach of NSW appears to come with a cost... We can't be sure that road rules are the reason, but it has a higher rate of road deaths than Victoria. It gets a benefit of saved travelling time but at a cost: extra lives lost.
Using the hourly wage rate it ought to be possible to put a dollar value on the benefit it gets from each life lost, in other words to work out the value that NSW places on human life.
As far as I know, no-one has done the calculation. But it has been done in the United States, in circumstances that were more clearcut. As a fuel- saving measure during the energy crisis of 1974, the Nixon administration imposed a low nationwide speed limit of just 55 miles an hour (88km/h). Road deaths plummeted.
After 1987, each state again became free to lift the limit on its rural interstate roads. Most boosted their limit to 65mph (104km/h). But seven left it unchanged at 55mph (88km/h).
Princeton economist Orley Ashenfelter and Chicago economist Michael Greenstone examined what happened in the states that boosted the limit. Their findings are chilling.
First, the actual increase in speed in the states that boosted the limit was low, averaging just 2mph (3km/h) on the roads affected. That's because a lot of the drivers on those roads were already speeding.
Second, that small increase in speed pushed up deaths by an astounding 36 per cent.
The states that boosted the limit appeared to have valued each life it destroyed at around $2million. I think I am worth more than that. I want more cameras.
Orley Ashenfelter and Michael Greenstone, Using Mandated Speed Limits to Measure the Value of a Statistical Life. Princeton University, Department of Economics, Working Paper number 463, April 2002.