Posted: February 15th, 2023
Geographical Distribution of Economic Impact: Sporting Events in Small Cities Jesyca Salgado-Barandela1, Angel Barajas2, and Patricio Sanchez-Fernandez2 1 Organización de Empresas y Comercialización, Universidade de Santiago de Compostela, Spain
2 Economía Financiera y Contabilidad, Universidade de Vigo, Spain
Jesyca Salgado-Barandela is a professor in the department of Business Organization and Marketing at Universidade de San- tiago de Compostela. Her research interests include the economy of sport, sport tourism, and the economic impact of events. Angel Barajas is a professor in the department of Financial Economics and Accounting at Universidade de Vigo. His research interests include the valuation of companies and intangibles, the economy of sport, and the economic impact of events. Patricio Sanchez-Fernandez is a professor in the department of Financial Economics and Accounting at Universidade de Vigo. His research interests include economic development, the economy of sport, and the economic impact of events.
Abstract There are limitations in determining the economic impact of sporting events that need to be considered. One of these is represented by first-round leakages. This work focuses on explaining first-round leakages in the economic impact of sporting events on small cities. Seeking to identify this type of leakage, we estimated the spatial distribution of the economic impact of two small-sized events organized in a town with a population of 24,248 inhabitants. The results showed a first-round leakage exceeding €300,000 and identified higher average attendee expenditure in a more developed city adjacent to the host city. Moreover, an exploratory analysis concerning the influence of leakage in final spending was performed. Finally, the elements that would increase the probability of leakage were studied. Overall, the current case study highlighted the importance of considering the existence of leakage. Keywords: spatial distribution, economic impact, first-round leakages, medium-size events, small events, sport events DOI: http://doi.org/10.32731/IJSF/181.022023.04
Introduction Medium and small-sized events are a phenomenon that attracts the attention of sporting event organizers and the scien- tific community alike. Some researchers believe these events have a greater economic impact because they do not require large investments (Malchrowicz-Mośko & Póczta, 2018; Ziakas & Costa, 2011) and are more sustainable (Gibson et al., 2012; Malchrowicz-Mośko & Póczta, 2018). These types of events also have the ability to participate in the economic development of cities (Gibson et al., 2012; Taks et al., 2013; Veltri et al., 2009) and develop tourism (Csobán & Serra, 2014; Chalip & McGuirty, 2004).
Matheson (2006a) explained the advantages of small events over mega-events, focusing on four main aspects. The first is that small events have a lower possibility of producing tourism displacement. Secondly, they involve lower organization and security costs. A third aspect is their lower chance of causing deviations in the normal patterns of the local economy; this makes the estimation of the indirect impact through multipliers more precise. Fourth, Matheson (2006a) highlighted lower media pressure on these events. Hence, the incentive to show inflated data on economic impact is lower too.
Studies are increasingly focusing their analysis on medium and small-sized events. Works estimating the economic impact of these types of events include those developed by Taks et al. (2011) for the 2005 Pan-American Junior Athletic Championships and that by Sánchez et al. (2016) for the Spanish Winter Open Master Swimming Championship 2015, identifying, in both cases, a positive economic impact. Mondello and Rishe (2004) analyzed the determinants of econom- ic impact for different amateur events. Taks et al. (2013) and Gibson et al. (2003) studied the spending behavior of those attending medium and small-sized events. Salgado, Sánchez, Pérez, and Barajas (2018) applied the contingent valuation method to identify the willingness of attendees to pay for attending the Spanish Spring Open Absolute Swimming Cham- pionship 2017, finding that spectators were willing to pay for a ticket to attend the event.
International Journal of Sport Finance, 2023, 18, 45–53, © 2023, West Virginia University
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Medium and small-sized events represent an opportunity for cities to develop a brand image strategy that boosts local tourism and economy (Malchrowicz-Mośko & Póczta, 2018) in addition to achieving these objectives in a more sustain- able way (Csobán & Serra, 2014; Duglio & Beltramo, 2017). Getz and Page (2016) explained the need for greater respon- sibility, transparency, and integrity in strategic policies and investments linked to the organization of sporting events. When attempting to measure economic impact, it is important to consider possible limitations in small cities, which may result from leaks or tourism displacement. As Agha and Rascher (2016) and Siegfried and Zimbalist (2002) explained, the level of leakage in smaller territories is higher given the lower presence of goods and services at a local level.
Measuring the leakage effect requires knowledge of the geographical distribution of spending. Then, it would be pos- sible to determine which part of the direct economic repercussion generated by sports tourists stays in the host city of the event and which goes to the surrounding cities. The geographical distribution of spending has not been addressed in depth in economic impact studies. The main aim of this study was to provide insights on the geographical distribution of the economic impact of sporting events to identify the existence of first-round leakages into cities surrounding the host city. To contribute to this debate, this work analyzes two events organized in Marin (Spain) in 2018. Marin is a town of 24,248 inhabitants that proposed a strategy to attract sporting events and ultimately bring tourism into the area. The events under analysis were the Spanish Kickboxing Championship Tatami Sports (held from May 11–13, 2018) and the Spanish Basketball Championship for Boys Clubs (held from June 10–16, 2018). The empirical analysis was made up of two parts. First, the first-round leakage was estimated for the two proposed events. Second, an exploratory analysis was carried out identifying the sociodemographic variables that explained the existence of leakage. The main findings of the paper are as follows: 1) the most developed urban center may benefit a higher economic impact than the town hosting the event; 2) attendees who produced money leakage spent around 30% more than those who spent only in the city hosting the event; and 3) the type of event, the origin of the attendees, the length of stay, and age influenced the generation of a greater or lesser first-round leakage.
The article is organized as follows. First, the literature review is oriented to identify the literature that has analyzed the geographical distribution of tourist spending at sporting events. Second, the database and the methodology used in the article are presented. Then, the results are explained and discussed. Finally, the conclusions are provided.
Theoretical Background The correct estimation of the economic impact of an event implies considering a set of aspects studied in detail by Crompton (1995, 2006). He mentioned five aspects, which include using sales instead of household-income multipliers, the misrepresentation of employment multipliers, using incremental instead of normal multiplier coefficients, the use of “fudged” multiplier coefficients, and confusion of turnover and multiplier. Matheson (2006b) identified three factors that must be considered to avoid inaccurate estimates of the economic impact of an event: substitution effect, crowding-out effect, and leakage effect. The substitution effect occurs when the expenditure made in the territory is not solely motivated by the event (Crompton, 1995; Matheson, 2006b). Preuss et al. (2010) developed a careful analysis of the identification of attendees having an impact to correctly measure the substitution effect. To measure the substitution effect, it is necessary to identify the existence of attendees whose spending is not motivated exclusively by the event—in other words, attendees whose expense would have been generated even if the event had not occurred.
The crowding-out effect refers to the potential expenditure displaced by the event, which occurs when the organization of the event discourages the attendance of regular tourists from the area (Barclay, 2009; Crompton, 1995, 2006; Matheson 2006b). For their part, Coates and Depken (2009) identified other possible displacement effects of the event: the hun- ker-down and the skedaddle effects. The former occurs when residents stay at home because of the event, and the latter is generated when residents go to other territories to escape the negative effects of the event. Economic impact studies neglect the measurement of these types of effects. In this sense, Scott and Turco (2009) developed a model of consumer evaluation that allows for the estimation of the crowding-out effect of an event. Applying the model to the 2009 US Wom- en’s Open Golf Championship, these authors identified a slight displacement of tourism.
The leakage effect occurs when the creation of direct income in the territory has no effect on the local economy in the form of indirect income (Matheson, 2006b). As Barclay (2009) and Agha and Rasher (2016) explained, money can leave
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the economy for two reasons. It may simply be “natural” for this to happen because no local economy has everything it needs, and some products and services must be imported from other territories. Something similar happens with the em- ployment of non-local personnel; part of the money inevitably goes to the points of origin of these workers. Another type of leakage generated by aspects linked to event management occurs when the organization of the event generates expenses outside the territory to either acquire products or hire services (Agha & Rasher, 2016; Barclay, 2009).
Davies et al. (2013) explained that “In estimating an event’s direct expenditure on a host economy, researchers need to consider immediate (direct) leakages according to the ultimate location of expenditures connected with an event” (p. 37). This is what the authors define as first-round leakages.
An example that may be more frequent in small cities is the leakage generated by limited lodging capacity. Tourism displacement occurs if the city cannot absorb the demand for accommodation generated by the event. This in turn results in the leakage of direct money into other territories.
Knowing the spatial distribution of the economic impact generated by an event allows measurement of this type of leakage. Getz and Page (2008, 2016) stressed the importance of studying space and time in sport tourism. However, the literature dealing with the geographical distribution of economic impact is scarce.
Collins et al. (2018) and Lee et al. (2017) explained that this issue is scarcely studied in the scientific literature as opposed to the more usual aggregate estimate of the economic impact. Current studies on spatial distribution develop two research lines. Connell and Page (2006) and Daniels (2007) studied the spatial effect in the economic impact of events having more than one host location. They identified a two-fold impact of events held in the most populated counties with more devel- oped urban centers as compared to the impact of events taking place in smaller counties. On the other hand, Herrero et al. (2006) and Lee et al. (2017) studied the leakages of money to other cities during the celebration of an event. Lee et al. (2017) showed that the host region received 80% of the impact while neighboring regions received only 20%. A previous study by Herrero et al. (2006) found that the economic impact of Salamanca 2002, as the European Capital of Culture, benefitted the host region with a 70% economic impact while 20% went to the rest of country and 10% went abroad.
Another phenomenon yet to be quantitatively analyzed, which is becoming increasingly common, is the case of small cities developing a tourism strategy through the organization of sport events. In this context, the level of leakage is higher. In this sense, the results found by Herrero et al. (2006) and Lee et al. (2017) may be challenged.
Data and Methodology To develop the empirical part, different methodological tools were applied. First, the data regarding spending made by the athletes was collected to estimate the initial injection of money. Buning et al. (2016) and Frechtling (2006) defined the initial injection into the economy as the new money generated by visitors in the territory hosting the event. Based on the estimate of the initial injection of money, distinguishing according to geographical areas, the geographical distribution of spending can be measured, and it can be identified if there is a first-round leak.
Second, an exploratory analysis was carried out. On the one hand, the influence of leaks on final expenditure of attend- ees was analyzed using ordinary least squares (OLS) regression. On the other hand, a logistic regression was applied to determine which variables increased the probability of the generation of leaks. The variables used coincided with the vari- ables commonly analyzed in studies with similar characteristics (e.g., Salgado et al., 2018; Salgado et al., 2020). Obtaining the necessary data for the application of the methodology required the design of a survey. The survey was previously vali- dated by experts in the field in addition to being applied in previous studies on the economic impact of events. The survey included questions that allowed the necessary data to determine the spatial distribution of the impact to be obtained.
The survey contained four sections and 24 questions. The first part of the questionnaire identified whether the person under survey was a resident in the host city. Resident attendees were accounted for, but they were not surveyed. Non-res- ident attendees answered two questions to identify the presence of casuals and time-switchers. Matheson (2006) defined casuals as those who were already visiting the host territory and attended the event instead of carrying out another activity in the area, and time-switchers as those who had planned to visit the territory anyway and who changed the date to coincide with the celebration of the event. In this way, the study only considered non-resident attendees whose main motivation was to attend the event. The premise of economic impact establishes that they are the only attendees that inject
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new money into the territory (Preuss et al., 2010). To make a correct estimate of the direct economic impact of the event, only the expense of non-resident attendees whose main motivation for traveling to the host territory is to attend the event should be considered.
The second part of the survey asked questions about the place of accommodation, days spent in the city, length of stay, and activities carried out in addition to attending the event. However, the most important aspect of this section was the identification of the expense made by the attendees. Specifically, it asked about the amount of money the respondent intended to spend. Three types of distinct questions were proposed to handle the data as rigorously as possible. First, the respondent was requested to classify the expenditure (accommodation, maintenance, tourism, transport, shopping, others). If unable to distribute the expense, the respondent must state an amount. If no response was given to this second option, the respondent was provided with spending intervals to indicate the one in which the expense was located. Finally, attendees who were staying in surrounding cities were asked if they had any expenses in the host city.
The third part focused on knowing the touristic side of the respondents. Although this was not quantifiable, it served as a guide for a potential future impact on tourism and consequent economic performance. The survey inquired whether respondents had ever visited the city before and asked them to assess how satisfied they were with the image of the host city, the event, and the organization of the event.
The fourth part included sociodemographic aspects such as age, sex, profession, education level, and annual individual income. This section also requested the number of people accompanying the respondent.
A total of 537 people were surveyed (282 at the kickboxing championship and 255 at the basketball championship). This implies a 5% margin of error at a 95% confidence level. To guarantee survey randomness, the interviewers address one out of every three people in each area at different times throughout the day.
Out of the total surveys conducted at both events, 95.53% of the attendees were non-residents, and the remaining 4.47% were residents. At the kickboxing championship, casuals and time-switchers represented 0.74% of the sample. In the case of the basketball championship, no attendee of this type was identified.
Results The attendances at the basketball and kickboxing championships were an estimated 845 and 668 spectators, respectively. In the first case, the attendees were counted at each match of the first qualifying round (this was possible because at each match the number of attendees did not exceed 60 persons, and they did not repeat their attendance until they began the following rounds). In the case of the kickboxing championship, the total number of attendees was provided by the orga- nizers of the event, considering ticket sales. The resident spectators whose expenses cannot be considered were deducted from these data. In addition, in the case of kickboxing, the percentage of casuals and time-switchers (0.74%) was also deducted. The final result was a total of 809 spectators with an economic impact for the basketball championship and 632 for the kickboxing championship.
Regarding expenses, the average expenditure made by attendees was determined for each event. Given the three alter- natives provided as an answer, a joint response rate of 83.3% was obtained for both events. Both the average expenditure data and the number of attendees were estimated for three distinct cases (Table 1). The first was the number of attendees staying in the host city (Marin). Second were attendees who did not spend the night on occasion of the event. These were attendees who returned to their place of residence on the same day and made their expenditure in the host city. Third were the attendees who stayed in neighboring cities.
The data collected in the survey showed that attendees not staying in the host city practically performed no spending in it. This circumstance responds to what Daniels (2007) explained using the central place theory. This theory explains that those attending an event turn to the most develop
SOLUTION
The geographical distribution of economic impact can vary widely depending on the nature of the economic activity, the size of the economy, and the specific geographic region in question. However, some general patterns and trends can be observed.
In most economies, economic activity tends to be concentrated in urban areas, where there is a greater concentration of businesses, infrastructure, and skilled labor. As a result, urban areas tend to have a greater economic impact than rural areas. This can be seen in the way that urban areas are often the centers of commerce, finance, and industry.
However, the distribution of economic impact within urban areas can also vary widely. In many cities, there are areas of concentrated wealth and poverty, with some neighborhoods experiencing significant economic growth and development, while others are struggling with poverty and unemployment.
At the national level, the distribution of economic impact can also vary depending on the size and structure of the economy. In many countries, there are significant regional differences in economic activity and development, with some regions experiencing higher levels of growth and development than others. This can be influenced by a range of factors, including the availability of natural resources, the level of infra
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