Abstract
The Olympic Games are the largest, highest-profile, and most expensive megaevent hosted by cities and nations. Average sports-related costs of hosting are $12.0 billion. Non-sports-related costs are typically several times that. Every Olympics since 1960 has run over budget, at an average of 172 percent in real terms, the highest overrun on record for any type of megaproject. The paper tests theoretical statistical distributions against empirical data for the costs of the Games, in order to explain the cost risks faced by host cities and nations. It is documented, for the first time, that cost and cost overrun for the Games follow a power-law distribution. Olympic costs are subject to infinite mean and variance, with dire consequences for predictability and planning. We name this phenomenon "regression to the tail": it is only a matter of time until a new extreme event occurs, with an overrun larger than the largest so far, and thus more disruptive and less plannable. The generative mechanism for the Olympic power law is identified as strong convexity prompted by six causal drivers: irreversibility, fixed deadlines, the Blank Check Syndrome, tight coupling, long planning horizons, and an Eternal Beginner Syndrome. The power law explains why the Games are so difficult to plan and manage successfully, and why cities and nations should think twice before hosting. Based on the power law, two heuristics are identified for better decision making on hosting. Finally, the paper develops measures for good practice in planning and managing the Games, including how to mitigate the extreme risks of the Olympic power law.
Highlights
The Olympic Games are the largest, highest-profile, and most expensive megaevent hosted by cities and nations
We cannot count on organizers, the International Olympic Committee (IOC), and governments to provide us with reliable information about the real costs, cost overruns, and cost risks of the Olympic Games
While conventional thinking is that a lognormal distribution is thin-tailed, because it has all the moments, it behaves like a power law at a r > 0.4 (Taleb, 2020: 139 ff), which is the case for our Olympic costs dataset
Summary
The Olympic Games are the largest, highest-profile, and most expensive megaevent hosted by cities and nations. As our data show they are, financial risks should be taken explicitly into account when cities decide whether to bid to host the Olympic games.
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