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This report studies the participation rates of the sports of Rugby League and Football. It uses the Economic theory of Income-leisure trade off to analyse the different demographic groups of participants in both sports and looks to find the reasons why the participation rate for each demographic is like it is. The main factor found is the cost of time and monetary cost of participating in sport. This is because it is linked to the participant’s income. Two policy possibilities are identified, which look at how reducing the price of participating and shortening the sports could make them more accessible and ultimately improve participation rates among the demographics of socio-economic classification, age and gender.
1. Income-Leisure Trade Off Model
The Income-Leisure Trade Off model has basic assumptions. One is that the theory says that people make choices to maximise their utility (U), through leisure time (L) and consuming income (I) (through work hours) (see equation 1.1) (Downward 2009).
(Equation 1.1) U=U(I,L)
The other assumption of the model is that Income and Leisure are “normal goods”, which means when income increases, the demand for them increases. Therefore, people want to consume more leisure and income. As they are normal goods, people may substitute more of one for less of the other (Downward 2009).
People’s choices are constrained by income and time. The constraint of time (T) is shown in equation 1.2, which indicates how work (W) (which produces income) and leisure (L) must be traded off as together they equal time. Therefore, if you have more of one, you must have less of the other. Labour_economics-shortrun_supply_smaller.png
(Equation 1.2) T=W+L
Figure (Source: Mousely.com)There’s only 24 hours in a day, so there’s a choice whether to trade more income for less leisure or vice versa to deal with this constraint. For example, if you work for 12 hours in a day, you will be left with 12 hours leisure (Point A on figure 1). If you work for 6 hours, you choose 18 hours leisure time. Therefore, the model is based on trading off income (work hours) for an extra hour of leisure.
Another constraint is the wage rate, (the rate of pay per unit of time) which influences income and this constrains how much leisure you consume. In equation 1.3, Income (I) is shown as being determined by the wage rate (w) times by amount of work (W). (Downward 2009)
(Equation 1.3) I=wW
If the wage rate increases, income increases and vice versa. For example, the wage rate is £10 per hour and maximum utility is 24 hours. If you work for 24 hours and consume no leisure, you generate £240 income. If you do no work, you generate no income. People find their perfect combination (any point on the iC curve in Figure 1) in between like 12 work hours and 12 leisure hours or 8 work hours and 16 leisure hours and so on. It is the choice of whether to generate more income (through work) or to consume more leisure.
The cost of leisure is equal to the wage rate, because for every hour you consumed leisure and didn’t work, you lose £10 as you could have generated £10 income (see equations 1.4 and 1.5).
(Equation 1.4) (Equation 1.5)
1.3 The Model’s Predictions
To make predictions about the choices people make, the model assumes all people maximise their utility and that there is no wasted time. Maximum utility is 24 hours because there’s only 24 hours in a day. Two predictions, the income and substitution effects are the predictions made from this model (Downward 2009).
1.3.1 The Income Effect
The income effect is based on the idea that as income increases (which means the wage rate increases), demand for work decreases because you can get paid the same to do less work and so demand for leisure increases (Downward 2009).
(Equation 1.6) (Equation 1.7)
Equations 1.6 and 1.7 show that as the wage rate increased you could spend 4 hours less working and still earn the same income and consume 4 hours more leisure.
(Equation 1.8) (Equation 1.9)
L=10 hours L=4 hours
If wage rate falls, demand for work increases and the demand for leisure decreases (see equations 1.8 and 1.9).
1.3.2 The Substitution Effect
The Substitution Effect is the idea that because the wage rate has increased the value of an hour (time) has increased. Therefore, the price of leisure has increased. This means that demand for leisure falls because it’s a normal good and the demand for income increases meaning more people will want to work more. If the wage rate falls, then the opposite happens, demand for leisure increases and demand for work decreases. (Downward 2009)
2. Participation Data
2.1 The Data Set
The data regarding Football and Rugby League players, will be used to analyse the issue of participation in sports. This will be completed by looking at the demographics gender, age and socio-economic classification to see which groups have highest participation rates.
Table 1 shows the data set for both sports. The data is from the Active People Survey (APS 1). The percentages are not participation rates of the total population, they are the percentage of the participants of the sport from that demographic. For example, in the Football data, the 91.08% is indicating that 91.08% of football participants were male.
Age Classifcation (years)
Socio-Economic Classification (NS-SEC)
NS-SEC 1,2: Managerial and professional
NS-SEC 3: Intermediate occupations
NS-SEC 4: Small employers and own account workers
NS-SEC 5: Lower supervisory and technical occupations
NS-SEC 6,7: Routine / semi-routine occupations
NS-SEC 8: Ever worked / long term unemployed
NS-SEC 9: Inadequately described / not classified
Table 1: Participation Rates depending upon demographic classification groups (Source: Active People Survey 2005-2006)
2.2 Description of the Data
In terms of gender, both Football and Rugby League have more males participating than females, 91.08% of football participants are male and 8.92% are female, whereas 90.48% of Rugby League participants are male and 9.52% are female.
Looking at the age demographic, more football participants are aged 16-24 (50.8%) than any other age group and there is a decrease in football participants as you get older. This is consistent in Rugby league as 70.35% of participants are between the ages of 16-24 and the percentage of participants decreases all the way until the 65 plus age group, where there are no participants.
The data regarding socio-economic classification shows that In football 26.68% of participants are from managerial and professional occupations (NS-SEC 1,2) and 22.13% are from routine/semi routine occupations (NS-SEC 6,7). Similarly, in Rugby League the highest percentage of participants come from routine/semi routine occupations (NS-SEC 6,7) with 24.37% of participants from that group and managerial and professional occupations (NS-SEC 1,2) with 18.44% of participants from that group.
3. Interpreting the Data
In both sports at least 90% of the participants are male, therefore the sports are being played more by males than females. The general trend means that in terms of participating the males have more leisure time because there are more male participants. This should mean that the males are working for less time and considering the income effect, males may earn a higher wage rate which would mean that women had to work more hours to earn the same income. This indicates that they would have less time for leisure and would look for less time intensive leisure, which team sports aren’t. However, the income effect applied here says females have less time to consume leisure so may just participate in other sports. However, if you look at the data using the substitution effect, there would be more leisure demanded by females because the wage rate is lower and they would substitute work for leisure. The data shows that this isn’t the case so here the income effect must be dominating over the substitution effect.
The demographic of age has interesting statistics linked to it. The model says that you trade off work for leisure time, the data for both sports indicates that age is linked to participation. This is because when you are younger, you participate more. According to the model’s explanation of this data, you will see that as you get older you do more work and less leisure. However, as you get older you should earn more money because you are being promoted and you will be getting a pay rise (or increase in your wage rate) as well as people retiring, which should mean that you work less and consume more leisure, but the data doesn’t back this up. This can be seen as one of the limitations of the model. When using wages of participants to try to predict their leisure participation it is good, however, when it comes to predicting individual preferences it is not as strong.
3.3 Socio-Economic Classification
In the data, you see that there are more participants from the managerial and professional occupations group. The theory suggests that this is the income effect in action because they are being paid more for their labour, which means that they can do less work for more income. Due to this, their individual demand for leisure goes up and therefore the demand for rugby league and football increases from this group, which means that they consume more leisure. However, as you move further down the classification, you generally find people earning a lower wage rate, which means that they have to work longer to make the same money. Therefore, they will have to trade off their leisure time to work and this means that sports such as Rugby league and Football may not be what they demand and instead they want something that would be quicker and easier to set up, like keep fit/gym for example. This means that the demand for the two sports is lower as you move down to intermediate occupations (NS-SEC 3) and small employers and own account workers (NS-SEC 4).
The income effect trend is not consistent throughout the data. There are in both sports high participation rates of routine/semi routine occupations (NS-SEC 6,7). This includes part-time work, which means that the people in this classification do not work regularly or do not work as many hours as some other classifications. The model would say that the substitution effect is dominating. The wage rate is less so an hour of time is worth less value and the price of leisure has decreased. Therefore, they are demanding/consuming more leisure and the demand for work is less so people have substituted work for leisure. By having more leisure time, they are in a better position to play these team sports, because they require a longer commitment to play in as opposed to individual sports like the gym.
4. Future Policy regarding participation
The income-leisure trade off theory which is used throughout this report suggests some possibilities which are needed to enable further participation.
The model is focused on wages/wage rate. It encounters difficulties when trying to predict preferences using different variables/demographics if wages/socio-economic classification is not used. Therefore, much of what the theory predicts looks at wages.
The first policy possibility would be to look at the cost of participating in terms of time. If there were shorter formats of football and rugby league available, you may see more participation from the people who have less leisure time because they have the opportunity to use up less leisure time by consuming the activity. This should see the demand for the sport increase in certain socio-economic classifications.
The second policy possibility which could further participation in football and rugby league is to offer the sports at a cheaper price. This is because people who are from a lower socio-economic classification may not be participating because they don’t see the value that they are getting from it. If the price was lower, more people may substitute leisure hours in place of work as they wouldn’t need as much income to maximise their utility. Therefore, lowering the price of 5-a-side football and rugby league club membership should make a difference to the rate of participation in both sports.
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