Assessing economic and fiscal impacts of sports complex in a small US county

Abstract

Due to the high demand for various forms of sports tourism, destinations have used sports-related events to attract more tourists to boost the regional economy. This study examines economic impacts (EIs) and fiscal impacts of the sports complex in a small county, and further verifies that its economic and fiscal impacts are of significance. Depending on a low or high demand scenario, approximately US$10.5 or 15 million in revenue supported 703 or 919 jobs (direct) in the impact area, with value added US$12.6 or 18.1 million, respectively. More specifically, an additional 66 or 90 indirect and 53 or 76 induced jobs were created with an impact of US$3.4 or 4.8 million. In total, the sports complex can support substantial employment (822 or 1085 jobs) and EIs (US$42 or 61 million) annually for the impact area. Lastly, US$336,000 or 443,000 in fiscal impacts was also generated.

Keywords

economic impact Economic Modeling Specialist International (EMSI)fiscal impact regional economic model sports complex

Introduction

Sports events are a significant motivator of sports tourism and can be used as one of the development strategies, as well as marketing plans of most regional destinations (Cheung et al., 2016). The impacts of planned sports events become more important in regional tourism for destination competitiveness (Getz, 2008). Concerning regional sports tourism development, for example, sports complexes can serve as an asset by hosting various sports events (e.g. sports tournaments) to attract various out-of-town visitors (tourists) to the region and further generating economic impacts (EIs) to benefit the local community (Beckman and Traynor, 2019; Cheung et al., 2016). Especially, tourists who visit a regional area to participate in sports events spend money on different items including lodging, food and beverages, entrance fee (e.g. ticketing), retail shopping (e.g. gifts), parking, recreation (entertainment), and other spending. All of this spending by tourists have a positive impact on the regional and surrounding areas (Bracalente et al., 2011). This is new money that stimulates regional economic activities through linkages of sports tourism with other sectors of the economy in the region. Due to the high demand for various forms of sports tourism, therefore, these days, destinations have used sports-related events to attract more tourists to boost the regional economy, which further improves local residents’ quality of life (Wäsche and Woll, 2013).

Prior studies have examined EIs of various tourism contexts in decades, such as academic tourism (Barra et al., 2018; Lopez et al., 2016; Martínez-Roget et al., 2013), the arts in the community (Stoddard et al., 2006), cultural event (Bracalente et al., 2011; Campoy-Muñoz et al., 2017; Sánchez et al., 2017; Young et al., 2010), low-cost carriers (Pratt and Schuckert, 2019), mega sports event (Huang et al., 2014), national park (Saayman and Saayman, 2006), religious event (Mahadevan, 2017), special event (Beckman and Traynor, 2019), and yacht charter tourism (Alcover et al., 2011). Yet, research focusing on the EIs of a sports complex on a small county with respect to tourists spending is scant (Getz, 2008). To bridge that gap, this study analyzes potential tourists’ spending patterns in relation to the sports complex in Grenada County, Mississippi. Multiplier effects, including job supported, per capita income and fiscal impact resulting from tourists’ activities associated with a sports complex are further examined. Sports events (or sports complex) can be the platform for economic regeneration in many small cities (Gratton and Kokolakakis, 1997). Moreover, sports events can give an impetus to destinations’ renewal via sports complex developments by attracting tourists to hosting destinations (Carlsen and Taylor, 2003). Essentially, identifying EIs, as well as fiscal impacts of a sports complex from tourists’ spending can become vital for various stakeholders and organizations including community developers, local businesses, and the economy. The rationale is that this information can help these decision makers formulate strategic plans to reach their development goals (Daniels et al., 2004).

How to define tourists to distinguish from locals

Planned events (e.g. sports events) are all created for a purpose (Getz, 2008). Some events are planned for public celebration to foster local residents’ pride and cohesion, while others are for competition, fund generation, entertainment, or socializing. Often, they require special-purpose facilities like sports complexes. Especially, sports tournaments in a sports complex induce amateur or professional athletes and spectators including local residents and tourists to the hosting destination. It is critical to distinguish local residents who could be either athletes or spectators from tourists to determine the injection of new money into the local economy (Crompton et al., 2001). As previous research suggested, local residents who reside inside of the impact area should not be included in the EI study because tourists are the driver of EIs (Bonn and Harrington, 2008; Crompton et al., 2001; Kim and Miller, 2017).

Crompton et al. (2001) noted that those who are casual (visitors who travel to the impact area for a primary purpose other than attending sports events) should be excluded in the EI study because of the expenditure by this group in the local economy that would not have otherwise occurred in the area (Cheung et al., 2016; Preuss, 2011). Additionally, visiting friends and relatives (VFR) often travel to a local area to visit or stay with friends or relatives and might attend a sports event in relation to the sports complex. However, this group is also less likely to spend money on a hotel or motel (Croes and Severt, 2007). This way, only visitors whose primary purpose is to attend a sports event with the sports complex are included in the EI study. In this study, especially, tourists were considered by the questions by asking (1) their home zip code, as well as (2) distances traveled from their home¹ (at least more than 50 miles) to differentiate between local residents and tourists (Smith and Costello, 2009; Yu et al., 2012). In other words, those who reside at a zip code within the EI area are classed as local residents.

Visitors to a sports complex can enhance a local economy by bringing in “new” money that flows through the local economy (Bonn and Harrington, 2008; Cheung et al., 2016; Crompton et al., 2001; Preuss, 2011). Economic input–output analysis generates estimates of these indirect EIs referred to as “multiplier effects” or commonly known as “ripple effects.” Multiplier effects measure the impact on output, income, and employment resulting from an increase in final demand (Rickman and Schwer, 1995). An increase in final demand, that is an additional dollar of output or employee compensation or one additional job in the sector, results in a total increase in output, income, or employment in the local economy equal to its multiplier. In this regard, multipliers estimate the amount of direct, indirect, and induced effects on income or employment that result from each additional dollar of output, additional job, and additional dollar of employee compensation in a sector (Bonn and Harrington, 2008). In the case of the EI of the sports complex, direct EI is created by tourists, whereas indirect EI is considered additional jobs and payroll created or supported in the surrounding economy as a result of the purchase of inputs by shops, hotels, and restaurants where tourists stay and shop. Lastly, induced economic effect consists of changes in economic activity resulting from household spending of income earned directly or indirectly as a result of tourists’ spending in the impact area.

Methodology

The samples for this EI study were randomly collected from two grocery stores in Grenada County, Mississippi. To include a variety of tourists who are more likely to represent the general population, the grocery stores in the region were chosen because they draw out-of-town visitors from neighboring counties, as well as all over cities around 50–100 miles distance from Grenada County. The intercept survey (face-to-face) was run for 2 days over several weekends. Prior to the data collection, four research assistants were trained regarding the purpose of the study. The research assistants were separately assigned to two different grocery stores, and they selected a random number from the random table on each day of collecting the data. If a random number was five, for example, a participant who walked into an entrance in the grocery store at the five-time was asked to complete a self-administered questionnaire. The survey took an average of 8 min to complete, and the refusal rate was 45%, which included those who refused to complete the survey.

Based on the data from the Convention and Visitors Bureau in Grenada County, Mississippi, the total tourists, including amateur and professional athletes and spectators for the low (60,000 tourists) and high (70,000 tourists) demand scenarios were determined. According to the Sports Facilities Advisory (2017), sports complexes provide different types of sports activities for local residents and tourists. The Grenada sports complex include a total of 12 baseball/softball fields and 5 soccer multiuse fields that could be used for football and track and field. In addition, tournament-based indoor sports facilities are composed of four basketball/volleyball courts, one swimming pool, and eight bowling lanes. In particular, to examine tourists’ spending patterns, the participants were asked to estimate their spending in seven categories: lodging, food and beverages, entrance fee, retail shopping (e.g. gifts), parking, and recreation (entertainment). Other spending category was also added to measure potential visitors’ miscellaneous spending in the impact area (Stynes and White, 2006).

Economic Modeling Specialist International² (EMSI) is used to estimate EIs of the sports complex in the region (Kim and Miller, 2017). As shown in Table 1, each of the spending categories surveyed was assigned to one of the NAICS industry codes on EMSI economic model, and further used to estimate the EI of the sports complex in Grenada County. For example, the industry classification for food and beverages “NAICS code: 722310” spending amount was US$7,967,400 (low demand) and US$9,295,300 (high demand), respectively. Similarly, the lodging except casino hotels, and motels with an industrial classification code “NAICS code: 721110” spending amount was US$6,345,000 (low demand) and US$7,402,500 (high demand). For this study, only 65% of the total estimated spending was used to calculate the EI (Stynes, 1997). The estimated total spending for each low and high demand scenario was calculated to show the difference between the two scenarios in relation to the sports complex. This calculation was determined by the total number of estimated tourists multiplied by the average expenditure for each spending category.

Table 1.

Spending by tourists based on surveyed respondents (low vs. high demand scenario).

NAICS code	Description	Model input
			Total spending (US$)
		Per person spending (US$)	Low demand^a	High demand^b
721110	Lodging	105.75	6,345,000	7,402,500
722310	Food and beverages	132.79^c	7,967,400	9,295,300
485999	Transportation	96.27^d	5,776,200	6,738,900
453220	Shopping	100.74	6,044,400	7,051,800
713990	Recreation	27.56	1,653,600	1,929,200
812990	Other spending	76.22	4,573,200	5,335,400
	Total	539.33	32,359,800	37,753,100

^a Low demand scenario with 60,000 estimated tourists.

^b High demand scenario with 70,000 estimated tourists.

^c Food and beverages includes carryout food (US$55.65).

^d The total amount of transportation includes parking fee (US$13.89) and rental expenses (US$34.50).

Results

A total of 227 samples were collected with 24 incomplete questionnaires being discarded, resulting in 89.4% (203 samples) completed surveys being obtained. The respondents were composed of 118 female (58.6%) with an average age of about 41.2 years. The majority of the respondents were African American (55.6%), followed by White (40.9%). About 41% (N = 83) of the respondents indicated that they held a high school degree and 31.7% a 2-year college degree and most respondents reported that their annual income was less than US$20,000, while the average income of the respondents was US$42,665.

As shown in Table 2, in the low demand scenario, the sports complex was expected to generate over US$10.5 million in revenue, supporting 703 direct jobs. The sports complex created 66 indirect jobs along with 53 induced jobs. Overall, the total employment impact was estimated to create 822 jobs, which further generates US$13,909,054 in labor income³ in the region. Interestingly, the top industries affected by the sports complex were transit and ground passenger transportation (186 jobs), all other food and drinking places (180 jobs), other personal services (129 jobs), hotels and motels (91 jobs), and retail—miscellaneous stores (84 jobs) (see Table 3).

Table 2.

Overall EI resulting (low vs. high demand scenario).

Impact type	Employment		Labor income (US$)		Total value added (US$)		Output (US$)
Impact type	LD^a	HD^b	LD	HD	LD	HD	LD	HD
Direct effect	703	919	10,507,840	15,036,492	12,578,809	18,123,214	29,343,199	43,086,164
Indirect effect	66	90	1,911,206	2,665,951	3,171,166	4,418,661	6,925,686	9,602,096
Induced effect	53	76	1,490,008	2,123,125	3,091,386	4,404,295	5,742,401	8,181,652
Total effect	822	1085	13,909,054	19,825,569	18,841,359	26,946,169	42,011,286	6,0869,911

Note: EI: economic impact; LD: low demand; HD: high demand. The multipliers for income and employment are 1.19 and 1.10.

^a LD with 60,000 estimated tourists.

^b HD with 70,000 estimated tourists.

Table 3.

Top 10 industries affected by sports tourism (low demand scenario).

Sector	Description	Employment	Labor income (US$)	Value added (US$)	Total output (US$)
412	Transit and ground passenger transportation	186	228	210,683	5,778,211
503	All other food and drinking places	180	5,064,437	4,804,251	8,058,219
512	Other personal services	129	2,666,995	2,793,455	4,622,432
499	Hotels and motels	91	1,052,183	2,388,073	6,357,069
406	Retail—miscellaneous stores	84	1,306,758	1,716,846	2,963,215
496	Other amusement and recreation facilities	35	5,11,310	752,325	1,699,405
464	Employment services	10	252,787	373,176	569,321
440	Real estate	8	128,990	539,689	997,304
438	Insurance agencies, brokerages	8	134,236	205,164	919,099
502	Limited-service restaurants	5	77,185	172,933	364,624

Additionally, concerning the estimated amount of earnings and consumption the local labor force may produce, the sports complex generated US$10,507,840 in direct effects, US$1,911,206 in indirect effects, and US$1,490,008 in induced effects. Overall, the total effect of labor income was estimated at US$13,909,054. On the other hand, the total value added, which is a more conservative measure of economic activity in the region, the sports complex generated US$12,578,809 in direct effects, US$3,171,166 in indirect effects, and US$3,091,386 in induced effects. Thus, the total effect of value added was estimated at US$18,841,359, that is the increase in the gross regional product due to tourists’ sports-related activities in the region, whereas the total effect of output was estimated at US$42,011,286 in business sales revenues.

Similarly, the EI of the sports complex was estimated with the high demand scenario. As shown in Table 2, the results indicate that the sports complex was projected to generate over US$15 million in revenue, which supported 919 direct jobs along with 90 indirect and 76 induced jobs. Overall, the total employment impact was expected to create 1085 jobs, which generated US$19,825,569 in labor income in the region. The breakdown of job creations in top industries affected by the sports complex were transit and ground passenger transportation (217 jobs), followed by all other food and drinking places (211 jobs), other personal services (150 jobs), hotels and motels (106 jobs), and retail—miscellaneous stores (98 jobs) (see Table 4).

Table 4.

Top 10 industries affected by sports tourism (high demand scenario).

Sector	Description	Employment	Labor income (US$)	Value added (US$)	Total output (US$)
412	Transit and ground passenger transportation	217	266	245,824	6,742,005
503	All other food and drinking places	211	5,915,744	5,611,821	9,412,766
512	Other personal services	150	3,117,600	3,265,427	5,403,420
499	Hotels and motels	106	1,227,832	2,786,732	7,418,304
406	Retail—miscellaneous stores	98	1,530,832	2,011,240	3,471,327
57	Construction of new commercial properties	85	2,552,469	3,226,325	8,000,000
496	Other amusement and recreation facilities	40	588,605	866,054	1,956,302
453	Other computer-related services	15	265,896	289,924	1,002,952
464	Employment services	14	362,387	534,975	816,161
440	Real estate	10	168,873	706,558	1,305,666

The local labor force produced was US$15,036,492 in direct effects, US$2,655,951 in indirect effects, and US$2,123,125 in induced effects. The total effect of labor income was projected to generate US$19,825,569. In addition, the sports complex generated US$26,946,169 total value-added effect in the region (e.g. US$18,123,214 in direct effects, US$4,418,661 in indirect effects, and US$4,404,295 in induced effects). Lastly, the total effect of output was projected to produce US$60,869,911 business sales revenues due to the spending by tourists in the region.

Lastly, an estimate of the fiscal impact was determined by multiplying the total new spending by tourists in the region by 4.84%. By considering direct and indirect linkages within the regional economy, this approach can capture the dynamics of the local economy although fiscal impact analysis has several different methods including the per capita multiplier method, case study analysis, or the service standard method (Burchell and Listokin, 1973; Deller et al., 1997). With new spending by all visitors to the sports complex, the sports complex generated US$336,000 (low demand) or US$443,000 (high demand) in fiscal impacts or tax revenues⁴ for Grenada County; a breakdown of the total tax revenue resulting from the sports complex is provided in Table 5.

Table 5.

The breakdown of the total tax revenue by two different demand scenarios.

	Employee compensation	Proprietor income	Tax on production and imports	Households	Corporations
Dividends					105^a; 173^b
Social ins.: tax—employee contribution	0^a; 0^b
Social ins.: tax—employer contribution	0^a; 0^b
Tax on production and imports: sales tax			0^a; 0^b
Tax on production and imports: property tax			301,042^a;394,039^b
Tax on production and imports: motor vehicle license			0^a; 0^b
Tax on production and imports: severance tax			0^a; 0^b
Tax on production and imports: other taxes			10,098^a;13,218^b
Tax on production and imports: S/L non-taxes			0^a; 0^b
Corporate profits tax					0^a; 0^b
Personal tax: income tax				0^a; 0^b
Personal tax: non-taxes (fines and fees)				22,482^a;31,988^b
Personal tax: motor vehicle license				0^a; 0^b
Personal tax: property taxes				2167^a;3084^b
Personal tax: other tax (fish/hunt)				0^a; 0^b
Total	0^a; 0^b	0^a; 0^b	311,141^a;407,257^b	24,650^a;35,072^b	106^a;173^b

^a Low demand scenario with 60,000 estimated tourists.

^b High demand scenario with 70,000 estimated tourists.

Conclusions and discussion

This study examines EIs and fiscal impacts of the sports complex in a small county, and further verifies that its economic and fiscal impacts are of significance. To estimate the EI of the complex in a small county, average expenditures of tourists were determined based on the intercept survey results. As previous research (Cheung et al., 2016; Croes and Severt, 2007; Crompton et al., 2001; Preuss, 2011) suggested, casual and VFR were excluded for this study to estimate the EI. Overall, the results show that depending on the low or high demand scenario, approximately US$10.5 or 15 million in revenue supported 703 or 919 jobs (direct) in the EI impact area, with value added US$12.6 or 18.1 million, respectively. More specifically, depending on the low or high demand scenario, an additional 66 or 90 indirect and 53 or 76 induced jobs were created with an impact of US$3.4 or 4.8 million. In total, the sports complex can support substantial employment (822 or 1085 jobs) and EIs (US$42 or 61 million) annually for the impact area. Lastly, concerning fiscal impact, US$336,000 or 443,000 in fiscal impacts (e.g. various tax revenues) was generated. Essentially, Grenada County can bring additional tax revenue from the sports complex from taxes on production and imports, corporations, and households including personal income tax.

Sports complex can provide a unique combination asset in a small county or destination, with sports events or sports tournaments, to create a competitive sports tourism destination in the region. In other words, the sports complex should serve as a community asset by hosting various sports tournaments, improving residents’ quality of life, and further generating economic and fiscal impact in order to benefit the local community. Based on this result, therefore, a small county or destination should aggressively pursue sports events with a sports complex under a sports tourism strategy, which may be facilitated by staffs within the Destination Marketing Organization (Daniels et al., 2004). This initiative can generate both an increase in bidding on sports and other events and a higher profile for the county (Getz, 2008) that results in more significant economic and fiscal impacts on the hosting destination.

As Tyrrell and Johnston (2001) noted, future research should consider other expenditures (e.g. sponsorships and vendors) beyond tourist spending because sports tourism or sports complex also attracts various vendors and can offer sponsorship opportunities. Typically, vendor contracts are either a fee or a percentage of the total sales, which also generate economic or fiscal impacts in hosting destinations. As such, it is important to consider expenditures other than tourists’ spending. In addition, targeted employment area (TEA) analysis would be a useful extension of this study. As Daniels et al. (2004: 197) noted, “economic impact analysts should consider other methods of employment change assessment.” In fact, TEA analysis can help EI researchers to trace employment changes within the EI area by recognizing unemployment rate changes (TEA, 2018).

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Sungsoo Kim

Notes

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