Presentation on theme: "Loughborough London School of Sport & Exercise Sciences The Economics of Sports Participation: Some Longitudinal Analysis. Paper presented to the GHS user."— Presentation transcript:
Loughborough London School of Sport & Exercise Sciences The Economics of Sports Participation: Some Longitudinal Analysis. Paper presented to the GHS user group meeting 13 th March 2009 Paul Downward & Joe Riordan
Background: 1.Promotion of physical activity is now central to public policy concerns 2.Relatively Little economic analysis and large-scale data testing 3.Builds upon Downward (2007); Downward and Riordan (2007) to analyse (and seek advice?) Participation decisions Social interactions Over time THAT IS……………………………….
Why do we do this? What has happened over time? Should we seek to promote this?
Policy Context Sport England Analysis of Determinants of Participation (2004) In the UK a Twin track approach Increase mass participation Enhance international success Increase quantity and quality of participation Creating a talent identification and development pathway A fit, active population A first class successful sporting nation Sport England Strategy 2008-11 Build on school provision work with NGBs develop community sport Excel, Sustain, Grow DCMS Game Plan 2002
Literature/Theory Heterodox: –Gratton and Tice (1991) explore the psychological foundations of consumer choice in sport and, in particular, learning by doing (Scitovsky, 1976; Earl, 1986, 1983). –Post Keynesian consumer analysis draws upon this concept and also insights from the studies of Leisure by Veblen (1925) and Galbraith (1958) and, by implication, Bourdieu (1984, 1988, 1991) that individual preferences are shaped by social values. –Prior experience in sports activities is likely to raise participation in any specific activity, and that social interactions, or lifestyles, will also affect participation. Uncertainty, preferences evolve, social constraints
Literature/Theory Neoclassical –Income-Leisure Trade off of Labour Supply (Gratton and Taylor, 2000) –Becker (1965, 1974). The latter paper is directly concerned with the accumulation of personal-consumption capital and social interactions in consumption.
Literature/Theory Marginal utility mediated through marginal productivity as dU it = (δU it /δP it )(δP it /δx it )dx it + (δU it /δ it )(δP it /δ it )d it + (δU it /δP it )(δP it /δC it )dC it + (δU it /δP it )(δP it /δS it )dS it
Literature/Theory Can integrate time cost explicitly in a simple way e.g. add w s t and w c t to r.h.s. so that economic shadow price includes time (If w s w c then an element of depreciation so that per period allocations are different).
Literature/Theory In general this suggests that sports participation will be likely to vary directly with the acquisition of specific personal consumption and social capital, and also with the decline in any initial obstacles to participation through time (no reinvestment!).
Empirical Work CountryAuthorTheoryIndicative Findings USCicchetti et al (1969) Neoclassical Demand Age (-); Non-white (-); Male (+); Income (+); Education (+); Facility supply (+) USAdams et al (1966) Neoclassical Demand Age (-); Income (+); Male (+); Education (+); White (+); USStempel (2005)BourdieuIncome (+); Education (+) USHumphreys andRuseski (2006) BeckerAge (-); Married (-); Children (-); Income (+); Employed (-); Retired (+); Education (+); Female (-); White (+); Urban (+); Health (+);
Empirical Work CountryAuthorTheoryIndicative Findings UKGratton and Tice (undated) HeterodoxMale (+); Age (-); Socio-economic status (+); Income (+); Illness (-); Number of Activities (+) UKFarrell and Shields (2002) (Implicit Becker Household preferences) Male (+); Age (-); Married (-) Children for males (+); Infant (-); Ethnic Minority (-); Education (+); Drinling (+); Smoking (-); Health (+); Income (+); Unemployment (+); Household membership (+) UKSturgis and Jackson (2003) UnstatedAge (-); Number of Adults in the household (-); Income (+); Male (+); London/SE (+); Own House (+); Education (+) UKDownward (2007)Neoclassical and Heterodox Working (+); Skills/Professional (+); Education (+); Married (+); Regions not SE (+); Male (+); White (+); Health (+); Smoking (-); Drinking (+); Access to vehicle (+); Age (-); Children (-); Number of Adults in the household (-); Income (+); Work hours (-); Unpaid work hours (-) Volunteering (+); number of leisure activities (+) UKDownward and Riordan (2007)** Becker and Heterodox Age (-); Skills/Professional (+); Drinking (+); Regions not SE (-); Access to a vehicle (+); Sports, other club membership (+); Volunteer (-); Number of sports (+); Sport lifestyle (-)
Empirical Work CountryAuthorTheoryIndicative Findings FlandersScheerder et al (2005a)* BourdieuAge (-); Female (-); Class (+); Family size (+); Urban (+) FlandersScheerder et al (2005b)* BourdieuHumanities school (-); Parents participating in sport (+) FlandersTaks and Scheerer (2007)* Bourdieu/Market segmentation Female (-); Age (+); Socio-economic (+);Parents participating in sport (+) In sport (+) 5. Age (-); Socio-economic (+); Parents participating in sport (+) AustraliaStratton et al (2005)No explicit theoryAge (-); male (+); State (+); Suburb (+); Professional (+); Income (+); Socio- economic (+) Couple no children (+); Single (+); Education (+); English speaker (+); Health (+); Easy transport (-); Not safe environment (-); Weekly contact family friends (-) NorwaySkille (2005)BourdieuFemale (-); Academic school (+); Active family members (+); Volunteer family members (+); Peer and Media information (+)
GermanyBreuer (2006)BeckerIncome (+); Working time (-); Education (+); Age (-); Immigrant (-); GermanyLechner (2008)No explicit theory Males: German (+); Education (+); Year (-); Technical occupation (-); autonomy at work (+); never smoked (+); High life satisfaction (+); Unemployment (+) Females: Year (-); German (+); Children 10 years (+); Family income (+); Office work (-); low autonomy at work (-); autonomy at work (+); illness (+); unemployment (+); inhabitants per km 2 (+); City centre (-) Empirical Work * Studies used either Factor analysis of Cluster analysis to group activities. **Study used cluster analysis to identify lifestyles
Empirical Work Increase ParticipationDecrease Participation 1.Male 2.Socio-economic status 3.Income 4.Health 5.Education 6.Transport 7.Drinking 1.Smoking 2.Children 3.Marital status 4.Work hours 5.Ethnicity Time (Investment; preferences shifting)? Social Interactions (groups of characteristics)?
Data\Variables The General Household Survey (GHS) was the data source for the research. A continuous survey, which began in 1971, and is conducted by the Office for National Statistics. It collects data on a range of topics, by face-to-face interview, from private households in Great Britain. As well as core topics such as household and family characteristics, education, health, income and demographics, it also investigates other topics, such as Sport and Leisure, periodically. Data from the 1980, 1986, 1990, 1996/7, 2002 are available. Some analysis done in Downward and Riordan (forthcoming, 2009) But only 22 activities participated in or not over the last four weeks Conformity? –Income a problem. Household and individual data, gross and net. A series of net income per week per individual identified by proportionate adjustment. This was deflated by the Retail Price Index for the year. –Some socio-economic; regional characteristics identifiable at more aggregate levels –Odd patterns of participation
1996/7 -2002 1.40 Activities 2.Easier to match variables Pooled data, not a panel, from 5 different years of GHS Survey
Empirical Strategy Cluster Analysis (Two-Step) –Personal Consumption capital; Social Characteristics Regression analysis (Controlled for household selection; robust errors) –Individual factors, plus cluster membership variable. –Participation Decision Ln(P it /1-P it ) = β 0 + β j X jit + v it –Number of Sports Numsport it = α 0 + α j X jt + u it Adequate strategy?
Empirical Strategy: Selection? Tobit Model: But: Lacks robust SE corrections, cluster sampling and weighting options Numsport* it = α 0 + α j X jit + u it if Numsport it * 0 Numsport it = 0 if Numsport it * > 0 Numsport it = Numsport it * Heckman Model to distinguish decisions/correct for sample bias: (H1) Numsport* it = α 0 + α j X jit + u it Numsport i > 0 only if P it =1. (H2) P it = β 0 + β j X jit + v it P it = 1 and 0 otherwise Whereu is N(0, σ) v is N(0, 1) Corr (u, v) = ρ It could be the case that the choice set comprises voluntary decisions to participate on any number of independent occasions which could include not at all
Discussion Some standard drivers of participation receive large-scale empirical support –Income –Human capital – education; employment –Health –Minor impact of family (aggregate measure?) –Evidence that social and consumption characteristics matter –Age (-); Sex (M>F) Time? –Cohort variable suggests declining general interest in sport –Interaction effects suggest reducing impact of traditional constraints/choices except BAME when allow for lifestyles Access to a given sport seems to be easing (policy?) –Combined effects are decline.