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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:. Promotion of physical activity is now central to public policy concerns
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Paper presented to the GHS user group meeting 13th March 2009
What has happened over time? Should we seek to promote this?
In the UK a ‘Twin track’ approach
Increase mass participation
Enhance international success
Game Plan 2002
Increase quantity and quality
Creating a talent identification
and development pathway
A first class successful
A fit, active population
Sport England Analysis of Determinants of Participation (2004)
Sport England Strategy 2008-11
Buildon school provision → work with NGBs → develop community sport → Excel, Sustain, Grow
Marginal utility mediated through marginal productivity as
dUit = (δUit /δPit)(δPit /δxit)dxit + (δUit /δit)(δPit /δit)dit + (δUit /δPit)(δPit /δCit)dCit +
(δUit /δPit)(δPit /δSit)dSit
Can integrate time cost explicitly in a simple way e.g. add wst and wct to r.h.s. so that
economic shadow price includes time (If ws ≠wc then an element of ‘depreciation’ so that per period allocations are different).
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!).
*Studies used either Factor analysis of Cluster analysis to group activities.
**Study used cluster analysis to identify lifestyles
The General Household Survey (GHS) was the data source for the research.
Some analysis done in Downward and Riordan (forthcoming, 2009)
Pooled data, not a panel, from 5 different years of GHS Survey
Tobit Model: But:
if Numsportit* ≤ 0 Numsportit = 0
if Numsportit* > 0 Numsportit = Numsportit*
Heckman Model to distinguish decisions/correct for sample bias:
Where u is N(0, σ)
v is N(0, 1)
Corr (u, v) = ρ