On Balance: Can Cost Benefit Analysis Tell Us If Our City Should Host the Olympics? It Does. But Could Do It Better.

February 13, 2019

By: Jérôme Massiani

There is growing skepticism among both academics and government officials about the benefits of large-scale sport and cultural events. Although Input-Output (IO) has long been the dominant approach to estimating the impacts of these events, the method faces criticism for both its lack of realism and the incompleteness of its results. Consequently, economists have begun to turn to two alternative approaches: computable general equilibrium (CGE) and cost-benefit analysis. These approaches can take into account effects not captured within an IO framework. They also often produce strikingly different results than those obtained using an IO model. This post reports some preliminary results from ongoing research evaluating nearly 60 studies that use cost-benefit methods to evaluate events. More complete results will be presented at the Society for Benefit-Cost Analysis Conference in March 2019.

An IO approach is fundamentally a multiplier approach, converting expenditures (on infrastructure, for example) into gross production in the host city. One limitation is that IO treats expenditures, such as those for infrastructure or by the local population, as fully additional; since this approach does not take account of substitution (i.e., that these resources have been diverted from other uses), it may overstate the favorable economic impact of an event. Another concern is IO’s focus only on gross domestic product and other related impacts, rather than on welfare, which also recognizes externalities and opportunity costs (Massiani 2018).

The earliest examples of the use of cost-benefit analysis and CGE to evaluate mega-events appeared in the 1980s and 1990s, respectively. Since then, almost 60 cost-benefit analyses of mega events of different sizes have been conducted. (For an examination of the use of CGE in evaluating mega-events, see Massiani (2018a).)

One of the earliest studies of the differences between cost-benefit and IO analyses of a specific event found that the two approaches yielded very different results. Specifically, the IO analysis for the City of Windsor, Ontario “indicated that the 2005 Pan-American Junior Athletic Championships generated a net increase in economic activity in the city of $5.6 million. The CBA showed a negative net benefit of $2.4 million” (Taks et al. 2011). The net benefit of this event was found to be even more negative in subsequent recalculations by de Nooij (2014). Other negative net-benefit results have been found for events such as the Vancouver 2010 Winter Olympics, and most of the different scenarios considered for the Australian bid for the FIFA (soccer) World Cup 2022.

To date, however, no systematic and critical survey of such studies has been conducted. Our review, which is designed to begin to fill that gap, suggests that most cost-benefit analyses of mega-events find a negative outcome: the costs exceed the benefits. Small events, which do not require a significant investment in infrastructure, are more likely to produce positive net benefits for the local population, as are events generating a high surplus. For instance, the Tasmanian Audit Office undertook a systematic cost-benefit analysis of state-funded events (Tasmania Auditor General Office 2016); this study found positive net benefits due to an assumed surplus of 7 AUD for each 10 AUD spent by the local population, combined with the low infrastructure requirements of the events being evaluated. Under less favorable assumptions, the results of a cost-benefit analysis are very often negative.

Part of the difficulty in comparing and evaluating existing studies is that no widely-accepted methodology exists for conducting a cost-benefit analysis of mega events. Some initial steps have been taken to develop guidelines; for example, guidelines have recently been published in the Netherlands by Schenk et al. (2018) and in New South Wales by the Treasury (discussed in Massiani, 2018b). But we are still far from having clear standards against which we can evaluate existing studies.

In general, cost-benefit methodologies vary considerably across existing studies. Some studies consider tourist expenditures as benefits, others only the generated added value. Some consider positive employment impacts but do not consider the opportunity cost of working time. Often, the residual value of infrastructure is neglected, and sometimes the services these facilities provide after the event are not considered. Security costs are sometimes considered, other times not (in the best case, the authors comment that this is due to lack of data). Similarly, cost assumptions are often not checked for realism and the risk of cost overruns.

Interestingly, we see little attention to the opportunity costs of public funding, and negative externalities (such as congestion) are rarely considered in the cost-benefit studies. By contrast, some studies estimate that a mega-event generates a positive externality in the form of the enjoyment derived by the local population, even for those who do not attend the event: for example, the pleasure of Dutch citizens in hosting a world class event (De Nooij 2012). As another example, Barget and Gouguet (2010) estimate that the value to the French population of hosting a Rugby World Cup represents 40% of the event benefits. When considered, this type of non-use value strongly influences evaluation outcomes.

On the whole, cost-benefit analysis seems a promising method for deciding whether Paris or Milan or other cities should host the Olympic games, an International Exhibition, or another event. Not by chance, the Mayor of Milan recently suggested that a cost-benefit study was needed of the Italian bid for the 2026 Winter Olympics. The cost-benefit framework has the advantage of making large benefits and costs visible, which would stay covert in an IO or CGE approach. Cost-benefit analysis also has the capacity to incorporate elements of approaches like IO and CGE, provided this is done in a way that is consistent with the social welfare framework. Additional research is needed, however, to develop sound cost-benefit methods capable of providing robust policy recommendations for mega-events.

Jérôme Massiani is assistant Professor at Ca' Foscari University in Venice. He has more than 20 years of experience evaluating topics such as environment and mobility. He has recently focused some of his research on the benefits of so-called mega events.


  • Barget, E. and Gouguet, J.-J. (2010) L’accueil des grands événements sportifs: quel impact économique ou quelle utilité sociale pour les régions ? L’exemple de la coupe du monde de rugby 2007 en France, Région et Développement, 31, pp. 93–118.
  • Massiani, J. (2018) I promessi soldi. L’impatto economico dei grandi eventi in Italia da Torino 2006 a Milano 2015, Ca’ Foscari Edizioni. Venezia.
  • Massiani, J. (2018a) Assessing the economic impact of mega events using Computable General Equilibrium models: Promises and compromises, Economic Modelling, 75, pp. 1–9. DOI: 10.1016/j.econmod.2018.05.021.
  • Massiani, J. (2018b) Comments on the New South Wales framework paper for the Application of Cost Benefit Analysis to Major Events. Mimeo.
  • Nooij, M. de (2012) ‘Een alternatieve maatschappelijke kosten-batenanalyse van het organiseren van de Olympische Spelen in Nederland in 2028’, TPEdigitaal. 6(1)
  • Nooij, M. de (2014) Economic impact analysis versus Cost Benefit Analysis for a medium sized sport event - A further improvement. SSRN working paper.
  • Schenk, S. et al. (2018) Handreiking MKBA sportevenementen. Een handreiking voor het ex-ante en ex-post in kaart brengen van de maatschappelijke kosten en baten van sportevenementen. Nederlandse SportRaad.
  • Taks, M. et al. (2011) Economic impact analysis versus cost benefit analysis: The case of a medium-sized sport event, International Journal of Sport Finance, 6(3), pp. 187–203.
  • Tasmania Auditor General Office (2016) Event funding, Report of the Auditor-General. No. 4 of 2016-17.