Drink driving, experience goods, and video games
Posted October 19, 2007on:
Some Canadian developers are making a computer game which simulates driving home drunk. They and police think it will be a great educational tool, showing teenagers how dangerous it is to drive while intoxicated. I’m not sure if I completely agree.
Assume that this game will realistically represent driving while drunk. As some people do get home when driving drunk, there must be some probability of getting home without crashing. Since teenagers can play this game over and over again, they can get better at not crashing in the game, which may make them think that they are less likely to crash when they actually drink and drive. Now it might do this, or it might just give teenagers a false belief of being good at drunk driving (given that the road and obstacles will be different on your home road). However, if our teenagers are rational this shouldn’t be the problem (as they will update their beliefs appropriately), the problem is that drunk driving is an experience good with negative externalities.
People who haven’t gone drunk driving don’t know how likely it would be that they would crash, they are uncertain (they don’t know the probability density function and so base probabilities on arbitrary beliefs). Once someone has consumed drunk driving, they gain information, and they know what the risks are when they drive. Now if current social advertising his mis-led teenagers, to believe that the risks are greater than they truly, a situation with no computer game may be preferable to a situation where kids have played the game.
Although full information is usually preferable, teenagers decision to drink drive has a negative externality which is the damage they cause when they crash. By showing kids the true probability of crashing, we increase their consumption of drink driving (assuming that their prior belief was that it was more likely they would crash) to the point where the social cost outweighs the social benefit of their driving activity.
However, there might still be scope for the game and full information. If we can ‘tax’ the negative externality, we can bring the quantity of drink driving down to the socially optimal level. This would require having police fining people when they catch them drink driving. The fine would have to equal [‘cost of outcomes’ x ‘probability of outcomes’]/[probability of being caught and fined]. In this case the driver takes on the full social cost of their drunken activity, and so will only consume the socially optimal amount. The problem with apply this rule come from quantifying the costs. If a drunk driver kills someone, what is the cost of that in monetary terms?
Ultimately, given the difficulty of quantifying outcomes, I think this may be the case where mis-information (at least a focus on the negatives) may be the best way to improve social outcomes. Discuss 🙂