Economics of doping – as a research area – has grown considerably after Breivik’s pioneering work [Breivik, 1987]. A good source for understanding this branch of literature is his excellent review [Breivik, 2015].
Following the notation in [Haugen, 2004], the following 3 dimensions and their connection are assumed crucial for fighting doping: a, the positive utility involved in winning a competition, r, the probability of being exposed as a doper and c, the “cost” or dis utility of exposure. Then, based on a very simple imperfect complete information game model, the following inequalities are crucial:
If , everybody take drugs, if everybody are clean.
Then, the argument takes an empirical turn, judging realistic values of a, r and c – typically concluding by very large a’s (top athletes earn a lot of money), small c and r, not very hard punishment (suspensions) and few doping tests. Hence, doping is hard to fight.
From a regulative point of view (how to improve the fight against doping in sports), the simple inequalities (1) are also convenient. Obviously, one could introduce more doping tests and/or more precise doping tests to increase r. Alternatively, one could make penalties harsher both longer suspensions and/or introduce fines to increase c. Both strategies will of course make the product r · c bigger and eventually induce the inequality sign to shift. Certainly, one unpleasant characteristic of such regulative means is costs.
As mentioned by the World Anti Doping Agency (WADA) several times, increasing the number of doping tests, as well as their quality cost money. Punishing athletes harder (increasing c) is a less costly strategy, which has become more frequently discussed, but at the same time harder to agree on. The reason for this ought to be evident: recruiting athletes to sport if one could loose the fortune and glory that drove most young athletes into sport may have dangerous consequences on the supply side Recruiting young talents may be far harder.
An alternative, and immediately seemingly more appealing one, can also be associated to inequalities (1).
Instead of making the right hand side bigger, one could achieve the same effect by decreasing the left hand side – decreasing a. Or, in a more advanced context (with more than two athletes – see e.g. [Haugen et al., 2013]) change the shape on the prize functions typically with more egalitarian prize distributions.
For instance, in this context, the difference between linear or non-linear prize functions turns out to be decisive.
However, also this approach has many obstacles.
Apart from the fact that reducing prizes for athletes may have adverse effects on athlete recruitment, the problem of effort may hit more egalitarian prizes. Why would athletes train hard and do their best in a competition if second or third place produces almost as much “utility” as winning. Obviously, spectators prefer serious athletes trying their best to win. See for instance [Tullock, 1980] for a more in-depth discussion of this dimension.
A simple temporary conclusion could hence be that traditional means of fighting doping all have adverse side effects, either cost or adverse long-term effects on demand or supply. As a consequence, alternative regulative means should be of interest.