The concept of evidence-based policy-making is appealing. It certainly beats prejudice-based policy-making or bribery-based policy-making. But while the general idea is to be applauded, political decisions can only be as good as the evidence they are based on. In the realm of public health, where politicians are under constant pressure to legislate, there is a growing tendency to treat speculation as science.
For example, last year it was earnestly predicted that a ban on below-cost alcohol would “save 21 lives a year”. In a country of 62 million souls and half a million annual deaths, 21 is statistically indistinguishable from zero, but since this peculiarly precise figure came from a professor of public health at Sheffield University, disbelief was suspended. If the appeal to authority was not enough, credibility was secured by the fact that a computer model was involved.
The same computer predicts that minimum pricing for alcohol will save 60 lives a year in Scotland. Again, this is far too low a number ever to be tested in the real world, but if you don’t like that number, you can choose from plenty of others. The Sheffield model has variously predicted that 900, 3,393, “more than 1,000” or “nearly 10,000” lives a year will be "saved" by minimum pricing in England. It told Panorama that the policy will save 5,000 lives a year amongst the over-65 age group alone, although this was later retracted (the Sheffield academics blamed "human error").
These ever-changing estimates have had a profound effect on the debate about minimum pricing. The public has been given the impression that the life-saving benefits of the policy have been scientifically established. They have not. Computer models are only as good as the assumptions they are based on and, as a new Adam Smith Institute report shows, the Sheffield alcohol model is based on some very questionable assumptions indeed.