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Table 2 Studies on sport expenditure (in chronological order)

From: Socio-economic patterns of sport demand and ageing

Author

Aim and method of the study

Central findings

Lamb et al. [36]

Analysis of the influence of sport participation on sport expenditure and effects of gender, age, and social class on sport participation (Great Britain); n = 1,364; longitudinal study; t-test and ANOVA.

Men spend more on sport than women—youngest age group (16–24) spend twice as much as the oldest group (55+)—middle class spends more than working class (but not for men).

Dardis, Soberon-Ferrer, and Patro [15]

Investigation of the impact of household socio-economic determinants (income, family lifecycle, education, race) on leisure expenditure (USA); n = 2,088 households; tobit analysis.

Income has significant positive impact—older households spend less than younger ones—number of adults in the household has significant positive effect—education of the household has significant positive impact.

Weber et al. [64]

Analysis of the determinants of sport expenditure (Germany); n = 2,866; descriptive.

Positive influence of income and educational level—men spend more on sport than women—expenditure decrease with increasing age—expenditure increases with increasing amount of sport activities.

Taks, Renson, and Vanreusel [58]

Examination of the determinants of consumer expenses in active sports participation (Belgium); n = 900; correlation and regression analysis.

Expenses are directly related to a person’s active sport commitment, this especially applies to total time spending—older participants spend more than younger ones—income correlates positively with expenses—educational level and socio-professional status correlate negatively with expenses—time is the strongest determinant to explain expenses in sports—the higher the participation, the more spending.

Davies [16]

Examination of spending on sports-related goods and services (UK); n = 5,079; correlation analysis.

Frequency of sport participation is no explanatory variable for increased spending on sport-related goods and services.

Breuer and Hovemann [8]

Examination of financial capacity of different sports and if sport expenditure depends on the structure of sport demand (Germany); n = 1,092; correlation analysis

Men’s individual expenditure is higher than women’s—amount of money at free disposal and amount of physical activity are predictors for sport expenditure—age and motivation have no effect.

Cirkel et al. [13]

Analysis of income and expenses of elderly people (Germany); Literature review.

Education and income influence sport expenditure—men spend more money on sports than women.

Lera-López and Rapún-Gárate [38]

Analysis of indicators (time and its constraints and socio-demographic variables) of consumer expenditure on sport (Spain); n = 700; tobit model.

Women spend less on sports than men—people with higher level of education spend more on sports—age and size of household have strong negative association with sports expenditure—age: non-linear relationship—larger households report lower per capita spending—population size is a strong predictor.

Lera-López and Rapún-Gárate [39]

Analysis of links between participation and expenditure (Spain); n = 700; ordered probit model to identify frequency of sport participation in the previous year; tobit model to examine consumer expenditure.

Participation decreases being female and/or employed, but increases with age—spending decreases being female, but increases with education and income—consumer expenditure on sports is determined by gender, education, and income level.

Breuer and Schlesinger [9]

Examination of age-dependent consumption and demand for sporting goods with regards to socio-economic and demographic determinants (Germany); n = 24,515; ANOVA.

Demand for sporting goods does not differ significantly throughout the different age groups—men spend more on sporting goods than women—positive impact of educational level—expenditure rises with higher income.

Lera-López and Rapún-Gárate [40]

Analysis of socio-demographic and economic variables regarding sport participation and consumer expenditure (Spain); n = 700; ordered probit models.

Men spend more on sport than women—age is negatively related to sport consumption—educational level is positively related to sport consumption—influence of income on sport expenditure—employed spend more on sports as well as higher skilled workers and managers.

Wicker, Breuer, and Pawlowski [66]

Analysis of the predictors (income, human capital, years of participation, level of performance, time of participation, age, and gender) of sport expenditure of members of non-profit sports clubs (Germany); n = 10,013; regression analysis

Sport specific analyses: big differences in expenditure between sports (e.g. badminton vs. equestrian)—personal income, level of performance, and weekly time of participation are the main predictors of sport specific expenditure.