Quantifying the ‘Un-quantifiable’: Valuing the Intangible Impacts of Hosting the Summer Olympic Games

Giles Atkinson*

Department of Geography and Environment, London School of Economics and Political Science, Houghton Street, London, WC2A 2AE, United Kingdom, e-mail: g.atkinson@lse.ac.uk. (*Corresponding author.)

Susana Mourato

Department of Environmental Science and Technology, Imperial College of Science, Technology and Medicine.

First Draft, January 2005: Please do not cite/ do not quote Abstract The Summer Olympic Games, it is argued, is a significant cultural good as well as a popular sporting spectacle; it provides the impetus for environmental and economic improvements in the host city, gives a boost to national pride and so on. This paper examines whether there is an economic basis for such claims. To date, attempts to quantify the benefits of hosting major sporting events have focused exclusively on tangible gains; those benefits associated with a clearly identifiable cash-flow. The evidence suggests that genuinely additional tangible benefits tend to fall short of corresponding measures of cost. Therefore, using a contingent valuation survey, we test the proposition that the size of the intangible (net) benefits of the London 2012 Bid might justify staging the event on cost-benefit grounds. Respondents, drawn from London, Manchester and Glasgow, were asked for their willingness to pay (WTP) to host the 2012 Olympic Games in London on the basis of the intangible impacts that this event might provide. A number of interesting issues characterise this application of the CV method. First, in order to familiarise respondents, in a contingent market, with the notion of intangible impacts, they were asked to consider and rate, in terms of relative importance, a number of intangible benefits and intangible costs. Second, respondents’ WTP is likely to be conditional on uncertainties about a number of factors such as perceived ability of the host nation to successfully deliver intangible benefits the event, how long the payment period would be and whether a bid itself will be successful. While such considerations might be controllable within the CV scenario, we also elicit information which allows us to investigate to what extent such priors influence WTP values. Third, the event itself is hosted by a specific city and, moreover, is concentrated at a particular location in the host city. Whether intangible impacts are primarily enjoyed by (certain parts of) the host city population rather than the wider country is arguable. Hence, we investigate whether WTP varies across geographical contexts and whether these differences can be explained by characteristics and attitudes of respondents that are observable because of information elicited in a CV questionnaire. Acknowledgements

The authors gratefully acknowledge financial support from the UK Department of Culture, Media and Sports (DCMS). We would also like to thank Ece Ozdemoglu, David Pearce and Stefan Syzmanski for valuable advice. The findings, interpretations and conclusions are those of the authors and are not to be attributed to DCMS.

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1. Introduction The Summer Olympic Games, it is argued, is a significant cultural good as well as a popular sporting spectacle; it provides the impetus for environmental and economic improvements in the host city, gives a boost to national pride and so on. This paper examines whether there is an economic basis for such claims. This is important because hosting the Olympics is an increasingly costly proposition. Indeed, the direct investment outlays themselves rate alongside those incurred by any number of major infrastructure projects. To date, attempts to quantify the benefits of hosting major sporting events have focused exclusively on tangible gains; those benefits associated with a clearly identifiable cash-flow. The evidence suggests that genuinely additional tangible benefits tend to fall short of corresponding measures of cost. Any defence of hosting cost-benefit grounds therefore must fall back on the assertion that intangible (or non-market) benefits are, at least, large enough to tilt the appraisal towards a positive net benefit estimate. The extent to which such propositions have been subjected to meaningful empirical investigation is, however, another matter. Indeed, intangible impacts have typically regarded as ‘unquantifiable’ in applied work on this issue to date. Therefore, using a contingent valuation survey, we test the proposition that the size of the intangible (net) benefits of the London 2012 Bid is non-trivial. Despite the popularity of the CV method in the field of environmental management, application of this technique to the context of sporting events and competition is rare. As such, this is the first stated preference study to measure the intangible impacts of hosting a major sporting event. Respondents, drawn from London, Manchester and Glasgow, were asked for their willingness to pay (WTP) to host the 2012 Olympic Games in London on the basis of the intangible impacts that this event might provide. A number of interesting issues characterise this application of the CV method. First, in order to familiarise respondents, in a contingent market, with the notion of intangible impacts, respondents were asked to consider and rate, in terms of their relative importance, a number of intangible benefits and intangible costs. Second, respondents’ WTP is likely to be conditional on uncertainties about a number of factors such as perceived ability of the host nation to successfully deliver intangible benefits the event, how long the payment period would be and whether a bid itself will be successful. While such considerations might be controllable within the CV scenario, we also elicit information which allows us to investigate to what extent such priors influence WTP values. Third, the event itself is hosted by a specific city and, moreover, is concentrated at a particular location in the host city. Whether intangible impacts are primarily enjoyed by (certain parts of) the host city population rather than the wider country is arguable. Hence, we investigate whether WTP varies across geographical contexts and whether any differences can be explained by characteristics and attitudes of respondents that are observable because of information elicited in a CV questionnaire.

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2. Brief Review of Past Studies A recent and authoritative discussion of the economic consequences of hosting the Summer Olympics by Preuss (2004) is that the (real) costs of hosting the Games – for a variety of reasons – has grown considerably. Yet, even given the context of these spiralling costs, governments from around the world remain ever eager as ever to compete against one another to host the Summer Olympics as well as other major sporting events. Indeed, a recent report by the UK House of Commons Select Committee on Culture, Media and Sport concluded that: “International sporting events … can promote economic and social development and bring a ‘feel-good’ factor. There is no doubt that seeking to stage events is worthwhile.” (House of Commons, 1999, para. 47). This assertion, however, appears to sit ill at ease with the more circumspect conclusions of the economic literature on hosting major events. Recent assessments generally have not been supportive that the benefits justify costs (Baarde and Matheson, 2002; see, for a recent review of this evidence, Syzmanski, 2004). Yet, there is an important caveat here. Economic assessments to date have all been based on comparing tangible benefits of hosting these events with the likely costs. Tangible benefits are those categories of benefit that are associated with an “easily” identifiable economic transaction (e.g. additional tourist revenue, jobs created and so on). While there is significant debate about the extent to which some of these categories of tangible impact genuinely can be construed as an economic gain, one issue is that this focus misses out on a potentially wider range of intangible impacts. Some of these impacts will be benefits – such as local environmental improvements and unifying the population of the host city and nation – while some of these impacts will be costs – such as increased congestion, disruption and safety risks. The point is, however, that for all of these intangible costs and benefits there is no straightforward way to measure their social value. The typical approach as in ARUP (2002) is to note the probable importance of intangible benefits but then to say that these are largely un-quantifiable in economic terms. Therefore, the question remains whether these intangible benefits are large enough to swing the balance in cost-benefit appraisals of hosting major sporting events. Shaffer et al. (2003) pose this question in speculating about how much are British Columbians willing to pay for the pleasure of hosting and attending the 2010 Vancouver Winter Games? However, the authors are not able to provide an answer to their interesting question. One approach would be to undertake an implicit cost-benefit analysis. For example, it could be asked if the intangible benefits of an event are at least as large as (likely) net financial losses? Of course, by definition, it is impossible to answer this question unequivocally. That is, while this is at a starting point for thinking about the worth of intangible benefits as a quantifiable concept, it is no substitute for more direct evidence.1

1 It should be noted that in the London case the decision to bid for the 2012 Games has already been made. Knowing the value of intangible benefits (or benefits in general) is thus only useful from the perspective of whether ex post that decision was justified (in economic terms) and for providing information as regards the decision to bid for future major events. Moreover, while it would be interesting to know the relative social value of hosting the event in London vis-à-vis other UK cities, the London 2012 Bid is, it appears, the only feasible project.

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It is worth noting that the International Olympic Committee (IOC) conducts its opinion poll in order to ascertain support in a prospective host city for staging the its Olympic event. The key indicator that is sought is a simple one; that is, is support greater or less than 70 per cent of the host city’s population? On the one hand, household responses to this question might reflect, to some extent, their perceptions about the extent of tangible and intangible benefits of hosting as well as some assessment of the likely costs they will face. On the other hand, while the IOC’s intention is to gauge (and avoid) what it perceives to be likely high levels of opposition, from an economic perspective, this approach says nothing about the intensity of household preferences towards hosting the Olympics.2 In other words, it tells us little about whether households believe that the benefits of hosting the event are at least commensurate with the costs. The link between assessing claims about the magnitude of intangible impacts and the economic appraisal of hosting events could be facilitated by stated preference methods such as contingent valuation (CV). CV is a stated preference technique commonly used to measure the welfare impacts of changes in public policies or projects: by means of a questionnaire, respondents are asked for their willingness to pay (WTP) to secure an improvement or, alternatively, to avoid an undesirable change. The values elicited are contingent on the scenario and information provided in the survey. Despite the popularity of the CV method in the field of environmental management, application of this technique to the context of sporting events and competition is rare. Applications of CV to the context of hosting sporting events and sport are rare. Exceptions include a study by Johnson and Whitehead (2000), which examined respondents’ WTP for a new arena for University of Kentucky basketball team. Similarly, Johnson et al. (2002) asked respondents their WTP to buy the Pittsburgh Penguins National Hockey League team a new arena. In the former, a majority of respondents unwilling to pay higher taxes for new arena while, in the latter, the WTP of “non-users” accounted for roughly three-quarters of the total value expressed. In both cases, the costs of building the new arenas could not be justified by the benefits indicating that intangible benefits might not always be widespread. A number of studies have looked at some cultural assets or events. For example, Fleischer and Felsenstein (2002) assess the WTP of Israelis to host of the Eurovision Song Contest in 1999 using a CV survey. Interestingly, this study finds that – aggregated across the Israeli population – across the intangible benefits of the Song Contest were crucial in generating an overall or net benefit of hosting the event. Yet, to our knowledge there have been no assessments of the non-market value of major sporting events using stated preference methods.

2 An ICM Poll for the Greater London Authority, conducted in October 2004, augments this simple approach by asking London households the following question: “Is 38p a week extra in Council Taxes a reasonable way of funding the London Olympics?” While interesting, that survey did attempt to estimate (maximum) willingness to pay by constructing a contingent market (specifying timing of payment, benefits which are received, budgetary reminders and so on).

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3. Study Description 3.1 Intangible Benefits and Costs Intangible impacts are those effects, which accrue to the ‘well-being’ of households but do not have a market price or where the price of the good and service is below what most households would pay to secure its provision. Benefits will be enjoyed by ‘users’ who (plan to) directly experience the event as a result of attending one or more of its sporting competitions. The experience, for many, will be more indirect and largely will entail the more passive activity of following media broadcasts, in the comfort of their homes, of the unfolding events. However, Boardman and Hargreaves-Heap (1999) have argued that televised broadcasting of major sporting events itself creates important intangible benefits in the form of the generation of shared and memorable experiences. We might speculate then that there could be a premium attached to this benefit if the Games are held in the viewers’ own country, so long as the event is considered to be a success. In both the cases of the active spectator and the armchair viewer or listener the point is that the (future) price paid (e.g. ticket price or relevant proportion of the licence fee or subscription charge) might not adequately reflect WTP (Pearce, 2004). It is also worth bearing in mind that the Olympics is a unique global sporting and cultural event. It is therefore conceivable that “non-users” enjoy a gain in well-being simply from knowing that the Games is being held in country. In practice, ‘non-use’ is likely to be a matter of degree and non-users might be defined rather as those households who experience the event very rarely or not at all. For both ‘users’ and ‘non-users’, beneficiaries, therefore, could be residents of host city and beyond. However, it seems to be a reasonable expectation that the former will derive the largest benefit. Measuring the benefits that might arise from hosting the Olympics is not simply matter of finding out how much individuals would pay now for benefits, which will be enjoyed during roughly one month of the summer in 2012. That is, while it is reasonable to speculate that most of the benefits will be enjoyed at around this time, what households are valuing is essentially an uneven stream of benefits.3 For example, some intangible plausibly will be realised before the event itself. Indeed, some degree of what is commonly claimed to be a feel-good factor could arise once the successful bid is awarded the Games. One notion of a successful Olympics is the provision of some enduring legacy (Preuss, 2004). Typically, this has been interpreted as the continued use of the sporting infrastructure (e.g. various stadia) and perhaps an environmental legacy in the sense of ‘enhanced’ local land- and waterscapes. However, one other intangible form that a legacy could take is in the shape of shared memories and experiences. Of course, prior to the event a household’s valuation of these benefits is likely to be conditioned by its assessment of the likelihood that the event will be well-organised and managed. Media reports in the run-up to Athens 2004 were full of references to unfinished stadia. Memories of London’s Millennium Dome demonstrate that not only may benefits not arise as envisaged but that also a perceived unsuccessful event can become synonymous with cautionary tales about plans to host future major events

3 Preuss (2004) makes this point in the context of the tangible benefits of hosting the Olympics.

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such as the Olympic Games. Given that organisational success or failure is likely to play some part in determining perceptions about an event’s success (or otherwise), uncertainty about this element of staging a major event is likely to condition household valuations. It cannot be taken for granted that the public will place weight exclusively on the positively value of holding the 2012 Games in London (i.e. they are willing to pay a positive amount to secure these benefits or are not being willing to pay because they do not care about these benefits). There are likely to be intangible costs or disadvantages to hosting the Games, such as disruption and inconvenience during construction of any Games-related infrastructure, increases in congestion or heightened security risks during the event. In principle, it is conceivable that some people might, on balance, view holding the Games as a ‘disbenefit’ in that they could be willing to pay some amount to maintain the status quo (i.e. not to have the 2012 Games held in London). There are at least two distinguishing characteristics of these disbenefits. First, with regards to their geographical incidence, many of these categories of disbenefit arguably do not impinge on the quality of life of those who live or work outside of the host city. That is, other things equal, residents and workers in the host city will suffer a disproportionate amount of the disbenefits that might arise. There are exceptions of course. Households in the rest of the country plausibly might resent the concentration of ‘Olympic–induced’ investment and attention in the host city. After all, it is the host city that is the primary focus of the Olympic project – e.g. Barcelona 1992, Sydney 2000 – rather than the host country. More generally, households that do not enjoy sport might suffer as a result of perceived excessive coverage of the event and its preparations and this effect might occur regardless of geographical location. Second, with regards to the timing of disbenefits, a number of these impacts predominately will arise during the event itself. Examples might include overcrowding due to an influx of visitors to the host city. 3.2 Contingent Market In a typical CV study, a policy scenario is proposed to respondents and their WTP to attain it is subsequently elicited. More specifically, in our study, respondents were asked to consider the intangible benefits and costs to themselves and their household of London hosting the Summer Olympic Games in 2012. In order to facilitate this WTP elicitation, respondents were presented with a number of broad categories of intangible benefit and then a number of broad categories of intangible costs. Respondents were asked to consider in turn these categories of intangible benefits and then intangible costs and, moreover, to assign each benefit (cost) a score, out of 100, reflecting the respondent’s opinion about the relative important of that category. Each of these categories was included and grouped on the basis of a review of the relevant literature, expert consultation and the views of the public as elicited in focus groups and cognitive (in-depth, one-to-one) interviews. For intangible benefits, these included seven categories as follows: (a) Uniting people/ feel good factor/ national pride: defined as the anticipation of the event (i.e. the excitement of Olympics, boosting nation’s morale and image), excitement during event (flags display, people watching and talking about events together, increased

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medal success for national athletes, potential for creation of national heroes), shared memories after event; (b) Improving awareness of disability: defined as experiences of the 12-day Paralympics, people overcoming adversity, showing benefits of sports to everyone; (c) Motivating/ inspiring children: defined as inspiring children to play sports, giving them something to do, sports champions as role models; (d) Legacy of sports facilities: creation of local facilities for children, new stadiums and sports venues (in London and other parts of the country) which could be continued to be used after the events; (e) Environmental improvements: defined as the speeding up of planned environmental regeneration, creation of new green spaces and recreational areas, revitalised river and canal network; (f) Promoting healthy living: defined as the promotion of healthy diet and nutrition, benefits of sports and outdoor activities; (g) Cultural and social events: defined the experience of a series of cultural and social festivals across the country to accompany the Olympics, boosting knowledge and understanding of the nation’s culture and diversity. For intangible benefits, these included seven categories as follows: (a) Crowding: defined as increased congestion in streets, transport, public spaces, restaurants, pubs and so on during the Olympics itself; (b) Increased risk of petty theft: such as pickpockets, purse snatching and so on; (c) Increased safety and security risks: defined as the perception of heightened risks from terrorism and other safety threats; (d) Local disruption during construction: defined as noise and dirt around Olympic construction sites and along transport routes; (e) Transport delays: defined as longer journey times during the Olympics; (f) Excessive media coverage: defined as perceived over-coverage of Olympic events in media and news Each respondent was asked his or her WTP for hosting the 2012 Summer Olympic Games in London. Given, for example, that there are intangible costs as well as benefits, it is entirely possible that the London 2012 Bid might constitute a good for some households and a bad for other households. In principle, it would be possible to measure the extent to which those with negative preferences are willing to pay to retain the status quo. Indeed, if this is not done then measures of a proposal’s benefits that are likely to be biased upwards. However, careful testing of the questionnaire indicated that respondents who were not supportive of the bid did not necessarily wish to translate this preference into a negative WTP. Hence, we have not sought to measure negative WTP in this study. For respondents who were residents of London, the payment vehicle for this change was an increase in the household’s annual Council Tax bill. This payment was justified to respondents as a contribution to the costs of hosting the event. Regarding how long this payment would continue, we adopted a split sample split sample design in which each London respondent was either told that the Council Tax rise would last for ten years only or the payment period was left unspecified. The reason for this split sample test was as follows. The convention in many CV studies would be for the period to be specified (whether this be a one-off payment or spread over a number of years). There is some uncertainty in the case of financing of London 2012 about how long, in reality, London households actually might pay. Of course, none of this should make any difference from the perspective of how WTP responses are used in policy analysis. That is, respondents would be expected to increase (decrease) their annual WTP amounts if the payment period specified was 5 years (20 years) instead of 10

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years. However, it would be useful to test the sensitivity of WTP responses to the period over which payments can be spread. For respondents who were residents of either Manchester or Glasgow, the payment vehicle for this change was a ten-year contribution to a voluntary fund. As previously, this payment was justified to respondents as a contribution to the costs of hosting the event. Strictly speaking, other things being equal, these different payment vehicles might be expected to elicit different estimates of WTP given that the former is a coercive payment vehicle and the latter is a non-coercive payment vehicle. Nevertheless, as noted by Champ et al. (2002), payment vehicle choice is also a practical matter about what respondents find credible. While local tax rises in London are a natural (and much discussed) vehicle for financing (part of) the costs of hosting the Olympics, this is not true for other parts of the country (nor is it the case that alternative tax instruments are credible vehicles). However, voluntary payment methods such as a designated national lottery scheme are considered to be credible. Given that the national lottery is a rather exclusive payment method (given that many households would not buy lottery tickets whatever the circumstances), a more general voluntary payment vehicle was used here. Respondents were asked whether or not they willing to pay something towards the costs of staging of the Olympics. If the respondent gave a positive response to this question then WTP further was elicited by means of a payment ladder where respondents were asked to tick the amounts that they would be willing to pay.4 Respondents who were willing to pay less than £1 were subsequently asked whether their WTP was zero or a very small amount between 0 and £1. Hence, information about the lower end of the (positive) WTP distribution was also collected. 4. Results 4.1 Sample Characteristics In all, 602 face-to-face interviews were conducted in London with a further 151 and 152 interviews being conducted in Manchester and Glasgow respectively. Within London, respondents were drawn from and identified as residing in East London, West London, Central London, North London and South London. All interviews were carried out in September, 2004. A number of protest responses have been excluded from our analysis: that is, zero valuations that were defined as ‘protests’ to the contingent market. Protesters were identified as respondents who refused to offer a payment for reasons such as “I already pay enough taxes” or “the government/local council should pay for this”. In all there were 44 (i.e. 7%) responses for the London sample and 13 (9%) and 6 (4%) responses respectively from the Manchester and Glasgow samples that could be classified as protests in this way. Table 1 presents a summary of selected sample demographic and socio-economic variables as well as data on the degree of support, in principle, for the London 2012 Bid.

4 A payment card approach is consistent with the recently published UK Government guidelines (Bateman et al. 2002) which recommend using either a payment card or dichotomous choice approach. A recent and authoritative US manual by Champ et al. (2003) also asserts that payment cards could be more fruitfully employed in CV research than has been the case.

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[TABLE 1 ABOUT HERE.] 4.2 Ranking of Intangible Benefits and Costs In order to facilitate this WTP elicitation, respondents were asked to consider seven categories of intangible benefit and then six categories of intangible costs and to assign each benefit (cost) a score, out of 100, reflecting the respondent’s opinion about the relative important of that category. (The sequence in which these categories were presented varied across respondents so as to minimise the chances that ratings are influenced by card order.) A summary of these findings are presented in Table 2. Clearly, there are a number of ways in which these data could be described. In Table 2, the percentage scores for each benefit (or cost) category are presented as a simple mean average. In addition, the mean rank order of each category is also presented. It should be noted that for the former (latter), a higher (lower) value indicates that a given category is rated as being more important. [TABLE 2 ABOUT HERE.] Turning firstly to the intangible benefits, for the London sample, the table shows that the highest rated benefit categories are (in order of importance): “motivating/ inspiring children”; “united people/ feel-good factor/ national pride”; and, the “legacy of sporting facilities”. This is followed by “awareness of disability” and “environmental improvements”. The categories of “promoting healthy living” followed by “cultural and social events” are ranked the lowest in terms of their apparent importance to respondents. Interestingly, these conclusions do not change to any great extent whether made on the basis of the mean scores or mean ranks. There also appears to be some uniformity of opinion across the cities as well. The three top ranked benefit categories are the same for the London, Manchester and Glasgow samples. Some differences do exist in that, for example, the Glasgow sample appears to give more importance to “promoting healthy living” and less importance to “environmental improvements”. With regard to intangible costs, for the London sample – which includes those who arguably will be most affected by these impacts – “transport delays”, “increased safety and security risks” and “crowding” are reckoned to be the most important categories. This is followed by “local disruption” and “increased risk of petty theft” with “excessive media coverage” coming a ‘distant’ last in terms of its importance for the average respondent. There appears to be some differences with the Manchester and Glasgow samples, although in both cases “increased safety and security risks” are similarly ranked highest in the latter. 4.3 WTP Results Details of the WTP responses are presented in Table 3. The columns labeled ‘frequency’ provide details of exactly how many individuals ticked the corresponding money amount as the highest they were prepared to pay to secure the 2012 Olympic Games for London. The columns labeled ‘cumulative’ report the number of respondents who were willing to pay at least this amount. The ‘survival’ column describes the percentage of the sample at each value on the payment card who were

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willing to pay at least this amount. The results show that the proportion of people willing to pay clearly decreases with the amount presented. [TABLE 3 ABOUT HERE.] Table 4 (columns 2 and 3) reports the non-parametric mean and median of the WTP amounts ticked in the payment card. The results show that (per annum) mean WTP is higher in London (£22) than in Manchester (£12) or Glasgow (£11). Moreover, the difference between WTP in London and elsewhere is significant at the 1% level (p>0.000 in both cases). The difference between WTP in Manchester and Glasgow is, however, not statistically significant; at least on the basis of these non-parametric estimates. For the 5 different areas of London, Table 4 also shows that mean WTP is highest in South London (£27) followed by East London (£26), North London (£24), West London and Central London (both £17). Many of the events are to be staged in the East of London (if the London 2012 Bid is accepted). This might suggest that a greater share of intangible benefits will be enjoyed in this area of the host city. However, such speculations are complicated if it also the case that residents in this part of London share more of the intangible costs. Table 4 appears to indicate that few of the differences in mean WTP across these areas of London are statistically significant. Exceptions to this are between East and West London (p>0.031) and between East and Central London (p>0.014). Another result from Table 4 (columns 2 and 3) is the disparity found between mean and median WTP values, with the median being significantly smaller than the mean in all cases. This reveals that mean WTP values are skewed and driven by a relatively small number of individuals with high WTP. [TABLE 4 ABOUT HERE.] In order to determine the factors that are important in determining WTP differences we need to model the data parametrically. As noted by Cameron and Huppert (1989), payment ladder data can be analysed parametrically with interval data maximum likelihood models. When a respondent i chooses payment t1i from the payment ladder that means that he/she is willing to pay as much as t1i but not as much as the next number up in the ladder, tui. Hence, the probability that a respondent picks t1i is the probability that willingness to pay lies between t1i and tui: P(t1i) = P(t1i ≤ WTP < tui) (1)

Since WTP is non-negative and its distribution is skewed, it is customary to use a lognormal conditional distribution. Hence, in the context of a payment ladder, logWTPi will lie between log t1i and log tui. In a parametric model, log WTPi is generally specified as: log WTPi = xi’β + εi (2)

where εi is distributed normally, with mean 0 and standard deviation σ. Then, the probability of choosing t1i can be written as (Cameron and Huppert, 1989): P(t1i) = Φ ((log tui - xi’β)/σ) – Φ ((log t1i - xi’β)/σ) (3)

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where Φ is the standard normal cumulative density function. The corresponding log likelihood function can be written as:

log L = ∑=

T

i 1

log [Φ ((log tui- xi’β)/σ) – Φ ((log t1i - xi’β)/σ)] (4)

Once the optimal values of β and σ have been estimated, mean and median WTP can be calculated as (Cameron and Huppert, 1989; Hanemann and Kanninen, 1999): median WTP = exp(xi’β) (5)

mean WTP = exp(xi’β) exp(σ2/2) (6) [TABLE 5 ABOUT HERE.] The final set of variables used in the models discussed below is presented in Table 5. The first type of variables included is demographic and socio-economic indicators such as sex, age and income as well as where a respondent’s household is located. The expectation is that higher income levels are positively related to WTP. It might be speculated upon that the WTP of respondents outside of London will be less than those living in the host city. This will depend, however, on whether WTP differences between those in different parts of the country are captured by other variables included in the models. Similar issues arise in terms of expectations about WTP differences across different locations in London. We hold no priors in relation to the other demographic variables. It is likely that the respondents’ attitudes and intentions towards the event will also influence their WTP. Thus, another set of variables relates to whether respondents support the London 2012 Bid, whether they might plan to attend any of the live sporting events and whether they believe the benefits of hosting the event to be widely enjoyed. In each case, these variables would be expected to positively related to WTP. In addition, given that our survey was administered relatively soon after the Athens 2004 Games it is instructive to test whether this had any bearing on respondents’ WTP values. Two variables have been included in this respect: the frequency with which a respondent watched this recent event on television and whether or not a respondent stated that their responses had been influenced by Athens 2004. A fourth, and final, type of variable is associated with a number of uncertainties that WTP might be conditional on. Respondents might be expected to be willing to pay more if they believe that London 2012 will be as well organised as previous Olympics. Expectations about the likelihood of London 2012 Bid actually beating its competing cities may or may not influence WTP as we discuss further below. Finally, those respondents who believed (where relevant) that they would be paying for a longer time period (i.e. more than 10 years) would be expected to be willing to pay less in that they are, in effect, spreading payments reflecting their total WTP (present) value over a longer time horizon. Table 6 contains the results of the econometric modelling for both the pooled data (column 2: model 1) from the London, Manchester and Glasgow samples and the London sample only (column 3: model 2).

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There is statistically significant evidence (for both models) that WTP is likely to reside in a higher interval if a respondent supports the 2012 UK/ London Olympics Bid (“Support”). A respondent believing that intangible benefits were more important than tangible benefits and further that benefits are enjoyed more widely than just sports fans and spectators (“Intangibles”) is similarly more likely to have their WTP reside in a higher interval. The link between perceiving that these intangible benefits are widespread could be taken as implying a broader (e.g. altruistic) component to household WTP values. That is, a respondent values hosting the event more highly if it delivers intangible benefits which are widely consumed. Direct use values are relevant to respondents’ WTP, however, as evidenced by the statistically significant relationship between anticipation of attending one or more live Olympics events (“Spectate”) and WTP. However, the Athens 2004 Games do not appear to have influenced, in any particular direction, respondents’ WTP (“Athens” and “Watchedtv_2004”). There is evidence that perceptions about whether the organisation of the event will be at least just as successful as other recent Olympics Games (“Organise”) has a significant bearing on WTP (both models). Successful and competent organisation of the Games will determine to what extent intangible benefits are enjoyed. Thus we would expect that a respondent’s faith in the ability of the UK and London to ‘deliver’ and organise a successful Games to have a positive bearing on chosen values on the payment ladder (and thus on the interval in which willingness to pay is located). This, indeed, appears to have been the case given the highly significant and positive sign on this coefficient. At least for the London only sample (model 2), a respondent’s expectations about whether the London 2012 Bid will be accepted (“Bid_success”). Strictly speaking, respondents were not being asked to pay for an uncertain event; that is, there was no element of risk specified in the contingent market presented to respondents, However, given on-going speculation in the media about the chances of the London 2012 Bid vis-à-vis its rivals, respondents might plausibly weight their WTP response according to their prior expectations about the likelihood of the Bid succeeding. For model (2) (but not for model (1)), the finding is that those with a higher degree of confidence that London will be chosen to host the 2012 Olympics are more likely to have a value for WTP lying within a higher interval. With regards to the sensitivity of (annual) WTP values to the timing of payments, Table 6 (both models) indicates that a respondent’s perception that that this time period is greater than 10 years (“Timepay”) results in WTP being more likely to reside in a lower interval. This uncertainty did not characterise the contingent market for all respondents, only those who received the version of the questionnaire which did not explicitly specify the payment period. This scenario was not strictly speaking indefinite. Rather it was open-ended in the sense of not specifying the payment period. Respondents might reasonably interpret this in their own way (given the lack of explicit guidance). By asking respondents how long they thought they were paying for, we can provide a further test of “time insensitivity”. Interestingly, those respondents (in this open-ended version) who perceived that their payments would have been over a period in excess of 10 years, or did not know how long this period would be, are more likely to have their willingness to pay residing in a lower interval. This is the finding that we would expect in that it indicates that respondents’ answers are sensitive to how long a time period their WTP values would be paid over.

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A positive coefficient on income is the standard economic prediction and it is confirmed in this analysis (both models). Age and gender of respondents do not appear to influence WTP however. There is statistically significant evidence that WTP is likely to reside in a lower interval if a respondent resides in either Manchester or Glasgow (model 1: respectively, “Manchester” and “Glasgow”). In certain respects, this is as expected. While WTP of residents in these cities may be significantly different than zero, we might expect that WTP is lower in these locations given that most of the 2012 events, and the surrounding excitement, will take place in the UK capital. This is basically the finding here. This also means that WTP differences across cities are not accounted for by observable differences in characteristics and attitudes of respondents across these cities. It is the dummy variable reflecting location that is capturing this effect. Using equations 5 and 6 we calculated the parametric mean and median WTP values implied by model (1) in Table 6. The findings are reported in the last two columns in Table 4. This indicates in money terms that, for a “standard” respondent (with equivalent characteristics, attitudes and so on), WTP differs markedly across cities. By contrast, model (2) in Table 6 which looks only at the London sample, indicates that relative to the baseline of respondents located in East London, none of the location dummies are significant. Again, Table 4 reports the parametric mean and median WTP values across London locations implied by model (2). This makes clear that while there are no significant differences between WTP in East London and the rest of the city, there are some differences when making comparisons between areas other than East. 5. Discussion and Conclusions In environmental applications of the contingent valuation (CV) method, measuring intangible impacts of environmental changes has become almost commonplace. A growing literature has sought also to apply this method to cultural goods. In this paper, we have presented a CV application of the proposal for London to host a major global – indeed, perhaps the major – sporting event, the 2012 Summer Olympics. In doing so, we have focused on the intangible impacts of this event. These have been much discussed elsewhere but seldom, if ever, quantified to any meaningful extent. Some of these intangible impacts manifest themselves in familiar ‘objects’. In the case of benefits, there will be environmental ‘improvements’ as local landscapes around the proposed sites for events are altered. In the case of costs, increased congestion and disruption may occur. Other categories of intangible impacts are somewhat more abstruse but perhaps no less important. This is because these impacts have the potential to be experienced by a wider population than just those in the host city. Examples might include the ‘feel-good’ factor and the sense of pride and shared memories of hosting a successful event. We have included all of these categories of intangible benefit and cost in our study. The willingness to pay (WTP) of respondents for secure the 2012 Summer Olympics Games for London is itself contingent on a number of factors. First, there is geography. The event itself is associated with a single host city (although certain competitions take place across the country). However, certain categories of intangible impact might plausibly be valued by households outside of London. While our sample of respondents in Manchester and Glasgow is relatively

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small our non-parametric and parametric findings indicate that WTP is non-trivial in both of these cities. However, WTP for a standard respondent in these cities is notably lower than in London. This also means that WTP differences are not accounted for by observable differences in characteristics and attitudes of respondents across these cities. By contrast, WTP across standard respondents from other parts of London, relative to the east of the city where the events will be mostly concentrated, does appear to differ mainly as a result of observable differences rather than the ‘simple catch-all’ variable reflecting where the respondent’s household is located. Second, hosting the Summer Olympics shares a number of features of many major infrastructure projects. The valuation of intangible benefits (and costs) is conditioned by expectations about how well or successfully managed the project will be. For example, we show a strong relationship between WTP and respondents’ attitudes about whether London 2012 would be as well-organised as previous events. There was also some evidence, based on the London sample only, that WTP values were also conditioned by respondent uncertainty about whether the London would be awarded the 2012 Olympics. In this case, respondents appeared to be allowing extraneous notions of risk (i.e. not specified in the contingent market) to temper their responses. However, given that we collected data on respondents’ assessment of the Bid’s chances of success we can explicitly assess the extent of this influence. With regards to the timing of payments, given the scope for cost overruns and so on, the timescale of any attempt by the relevant authorities to capture the value of hosting the event may also be uncertain. For those respondents faced with a unspecified (i.e. open-ended) payment period, we find that WTP is lower if that a respondent perceived that (or was uncertain about) their payment was to be stretched over a long time period then their WTP is somewhat lower. This appears to indicate an implicit sensitivity to the timing of payments.

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References ARUP (2002) “London Olympics 2012 Costs and Benefits”, ARUP, London. Baade R. and Matheson V. (2002) “Bidding for the Olympics: Fool’s Gold?” in Barros C. Ibrahim M. and Szymanski S. (eds.) Transatlantic Sports, Edward Elgar, Cheltenham. Bateman, I., Carson, R.T. Day, B. Hanemann, M. Hanley, N. Hett, T. Jones-Lee, M. Loomes, G. Mourato, S. Ozdemiroglu, E. Pearce, D.W. Sugden, R. and Swanson, J. (2002) Economic Valuation with Stated Preference Techniques: A Manual, Edward Elgar, Cheltenham. Boardman, A.E. and Hargreaves-Heap, S.P. (1999) “Network Externalities and Government Restrictions of Satellite Broadcasting of Key Sporting Events”, Journal of Cultural Economics, 23: 161-181. Champ, P.A. Flores, N.E. Brown, T. and Chivers, J. (1996) “Contingent Valuation and Incentives”, Land Economics, 78(4): 591-604. Champ, P.A. Boyle, K.J. and Brown, T.C. (eds.) (2003) A Primer on Nonmarket Valuation, Kluwer Academic Publishers, Dordrecht. Fleischer, A. and Felsenstein, D. (2002) “Cost-Benefit Analysis Using Economic Surpluses: A Case Study of a Televised Event”, Journal of Cultural Economics, 26: 139-156. House of Commons (1999) Select Committee on Culture, Media and Sport – Fourth Report, House of Commons, London. Johnson, B.K. Groothuis, P.A. and Whitehead, J.C. (2000) “The Value of Public Goods Generated by a Major League Sports Team: The CVM Approach”, Journal of Sports Economics. Johnson, B.K. and Whitehead, J.C. (2000) “The Value of Public Goods from Sports Stadiums: The CVM Approach”, Contemporary Economic Policy, 18(1): 48-58. Preuss, H. (2004) The Economics of Staging the Olympics: A Comparison of the Games 1972-2008, Edward Elgar, Cheltenham. Shaffer, M. Greer, A. Mauboules, C. (2003) “Olympic Costs and Benefits: A Cost-Benefit Analysis of the Proposed Vancouver 2010 Winter Olympic and Paralympic Games”, Canadian Centre for Policy Alternatives, Vancouver. Syzmanski, S. (2004) Imperial College London.

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Table 1: Summary of Sample Characteristics

London Sample

Manchester Sample

Glasgow Sample

Total number of individuals 558 138 146

Males 48% 47% 56%

Average age (using mid-point of intervals)

40 years 39 years 39 years

Education: None 7.1% 8.1% 10.4%

Primary school 30.9% 35.8% 43.7%

GCSE/ O’ levels/ CSE 20.3% 22.7% 28.4%

A’ levels or vocational training 6.1% 6.5% 5.6%

Professional Degree 25.1% 21.9% 10.4%

College or University 10.5% 5.1% 1.4%

Higher Degree (Masters, PhD etc.) 7.1% 8.1% 10.4%

Socioeconomic group: ABC1 60% 43% 38%

C2DE 40% 57% 62%

Average monthly household income (using mid-points of intervals)

£2,670 £2,467 £1,983

Income non-response 19.4% 23.2% 24.7%

Support: Strongly supportive of the London 2012 Bid 7.7% 1.5% 1.4%

Supportive 5.0% 0.8% 2.1%

Indifferent 8.2% 10.9% 16.0%

Against 31.7% 42.0% 42.3%

Strongly against the London 2012 Bid 47.3% 44.9% 38.2%

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Table 2: Intangible Impacts to People of Hosting the Olympic Games In 2012

Category of Intangible Impact London

Mean score

Mean rank

Manchester

Mean score

Mean rank

Glasgow

Mean score

Mean rank

Uniting people/ feel good factor/ national pride

16.87

2.91

18.01

2.77

17.59

2.63

Improving awareness of disability 13.77

3.13

14.68

3.03

13.97

3.13

Motivating/ inspiring children 18.85

2.57

16.54

2.70

18.68

2.39

Legacy of sports facilities 16.07

2.86

16.62

2.81

16.52

2.98

Environmental improvements 13.94

3.15

14.69

3.25

10.55

3.60

Promoting healthy living 11.94

3.43

11.87

3.38

13.57

3.09

Ben

efit

s

Cultural and social events 8.39

3.97

7.57

4.21

9.47

3.78

Crowding 17.64

2.54

17.74

2.52

17.65

2.48

Increased risk of petty theft 16.25

2.81

16.47

2.84

17.45

2.68

Increased safety and security risks 18.88

2.50

18.20

2.66

23.18

2.35

Local disruption during construction 17.17

2.72

18.80

2.62

15.09

2.89

Transport delays 20.24

2.42

18.69

2.47

15.57

2.75

Cos

ts

Excessive media coverage 8.75

3.81

8.84

3.80

10.41

3.40

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Table 3: Details of Payment Ladder Responses

London Sample

(N=558)

Manchester Sample

(N=138)

Glasgow Sample

(N=146)

WTP

(£)

Freq Cumul Surviv Freq Cumul Surviv Freq Cumul Surviv

0 59 10.57 10.57 10 7.25 7.25 18 12.33 12.33

0.10 1 0.18 10.75 1 0.72 7.97 0 12.33 12.33

0.20 2 0.36 11.11 1 0.72 8.7 0 12.33 12.33

0.25 0 0.36 11.11 1 0.72 9.42 0 12.33 12.33

0.30 0 0.36 11.11 1 0.72 10.14 0 12.33 12.33

0.50 2 0.36 11.47 10 7.25 17.39 19 13.01 25.34

1 58 10.39 21.86 20 14.49 31.88 25 17.12 42.47

2 30 5.38 27.24 8 5.8 37.68 11 7.53 50

5 82 14.7 41.94 32 23.19 60.87 20 13.7 63.7

10 80 14.34 56.27 22 15.94 76.81 21 14.38 78.08

15 30 5.38 61.65 5 3.62 80.43 7 4.79 82.88

20 54 9.68 71.33 6 4.35 84.78 8 5.48 88.36

25 26 4.66 75.99 3 2.17 86.96 3 2.05 90.41

30 10 1.79 77.78 4 2.9 89.86 2 1.37 91.78

40 12 2.15 79.93 1 0.72 90.58 1 0.68 92.47

50 60 10.75 90.68 8 5.8 96.38 6 4.11 96.58

60 8 1.43 92.11 1 0.72 97.1 1 0.68 97.26

80 3 0.54 92.65 1 0.72 97.83 0 0.68 97.26

100 34 6.09 98.75 2 1.45 99.28 3 2.05 99.32

+100 7 1.25 100 1 0.72 100 1 0.68 100 Notes: 1. WTP refers to the highest amount the respondents would be willing to pay 2. Freq: frequency; Cumul: cumulative frequency; Surv: survival probability

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Table 4: Summary Statistics for WTP (£ /household/ year)

Non-parametric statistics Parametric statistics

Variable Mean

(95% CI)

Median

Mean

(95% CI)

Median

WTP: London 21.95

(19.58-24.32)

10

24.17

(21.46-27.22)

11

WTP: Manchester

12.40

(8.98-15.83)

5

12.53

(9.20-17.05)

6

WTP: Glasgow 10.87

(7.58-14.15)

4

8.00

(6.00-10.69)

4

WTP: East London 25.55

(20.01-31.08)

10 21.93

(17.00-28.30) 11

WTP: West London 17.02

(12.00-22.03)

8 16.19

(12.30-21.30) 8

WTP: Central London 17.02

(13.27-20.93)

10 23.68

(19.28-29.08) 12

WTP: South London 27.32

(20.71-33.92)

15 25.13

(19.08-33.10 12

WTP: North London 23.82

(18.08-29.56)

10 27.51

(20.60-36.74) 14

Notes: (1) C.I.: confidence interval (2) Parametric estimates for London, Manchester and Glasgow estimated from model (1) in Table

6. Parametric estimates for East, West, Central, South and North London estimated from model (2) in Table 6.

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Table 5: Description of Independent Variables in Interval Data Model Variable Description

Sex = 1 if Male

Age Mid-point of age band (years)

Age2 Square of mid-point of age band

Income Mid-point of income band (£)

Manchester = 1 if Resident of Manchester

Glasgow = 1 if Resident of Glasgow

Organise = 1 if Thinks that London 2012 would be better or at least as well organised as most of recent host cities

Timepay = 1 if Payment period is more than 10 years

Bid_success = 1 if Bid will be almost certainly unsuccessful (less than 10% chance of success)

= 2 if Likely to be unsuccessful (around 25% chance of success)

= 3 if Not sure one way or the other (50% chance of success)

= 4 if Likely to be successful (around 75% chance of success)

= 5 if Almost certainly successful (over 90% chance of success)

Spectate = 1 if Almost certain not to attend any live events

= 2 if Likely not to attend any live events

= 3 if Not sure

= 4 if Will try to watch some live events

= 5 if Certain to attend as many live events as possible

Support = 1 if Strongly against the London 2012 Bid

= 2 if Somewhat against

= 3 if Indifferent

= 4 if Somewhat supportive

= 5 if Strongly supportive of the London 2012 Bid

Intangibles = 1 if Stated that intangible benefits were more important than tangible benefits and believes that benefits are enjoyed more widely than just sports fans and spectators

Athens = 1 if If stated that was influenced by Athens 2004

Watchedtv_2004 = 1 if Not at all

= 2 if Occasionally

= 3 if I watched certain events

= 4 if I watched a fair amount

= 5 if I watched as much as I could

West_London = 1 if Resident of West London

Central_London = 1 if Resident of Central London

North_London = 1 if Resident of North London

South_London = 1 if Resident of South London

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Table 6: Interval Data Model

Variable (1) Pooled Data (2) London Sample Only

Constant -1.0888* (0.6702)

-0.9047 (0.7336)

Sex -0.1624 (0.1071)

-0.0698 (0.1175)

Age 0.0174 (0.0308)

-0.0047 (0.0339)

Age2 -0.0002 (0.0004)

0.0001 (0.0004)

Income 0.0001*** (0.0000)

0.0001*** (0.0000)

Manchester -0.6572*** (0.1693) −

Glasgow -1.1051*** (0.1609)

−

Organise 0.4518** (0.1456)

0.3502** (0.1577)

Timepay -0.7858*** (0.1957)

-0.7873*** (0.1902)

Bid_success 0.0803 (0.0601)

0.1628*** (0.0631)

Spectate 0.1699*** (0.0473)

0.1454*** (0.0575)

Support 0.4345*** (0.0669)

0.4136*** (0.0747)

Intangibles 0.3898*** (0.1218)

0.5938*** (0.1292)

Athens -0.0606 (0.1217)

-0.0077 (0.1342)

Watchedtv_2004 0.0504 (0.0437)

0.0372 (0.0494)

West_London −

-0.3036 (0.1906)

Central_London − 0.0765 (0.1658)

North_London − 0.1362 (0.1889)

South_London − 0.2267 (0.1965)

σ 1.328058 1.187907 Log likelihood -1661.7796 -1114.81 N 664 446 Notes:

1. Dependent variable: logWTP 2. Pooled data includes responses from London, Manchester and Glasgow samples 3. *** significant at 1% level; ** significant at 5% level; * significant at 10% level