economics of sport exam 2012-13 marking scheme

BMAN 31391 Economics of Sport Examination 2012-13Marking scheme

1. An economic impact report commissioned by Visa in 2011 predicts that the Olympic and Paralympic Games to be held in London in 2012 would give a £5.1 billion boost to UK economy.

(a) Explain how an economic impact report into a “mega-event” such as the Olympics is constructed and how the above figure may have been arrived at. (25 Marks)

(b) Discuss why many economists are sceptical of the type of analysis that is presented in most economic impact assessments. (25 Marks)

(a) An answer to this question may include all, or some, of the following:

Discussion of why countries are so keen to bid for “mega events” ➔ prestige/politics ➔ urban generation.

Information about the claims made for the economic impact of London 2012 (i.e. David Cameron claimed £15bn impact over 4 years)

Explanation of an economic impact study. Two types were covered:o Extra money flowing into country (ticket sales, TV rights, etc. )o Extra income generation (employment, hotels, catering, etc).

(b) An answer to this question may include all, or some, of the following:

Explanation of a cost benefit analysis incl. concepts such as opp. cost & consumer surplus.

Discussion of the weaknesses of economic impact study Discussion of the weaknesses of a CBA Difference between ex post and ex ante studies. Numerical example showing the difference between an economic impact study

and a CBA (a numerical example such as this was presented to students in the course).

Throughout the question, please credit any valid alternative point

Assessment Criteria for (a) & (b) MARKS

(25)Completely inappropriate answer 0Little understanding of the specific demands of the questionVery little recognition of relevant economic theory.Relevant terms not defined.No attempt at diagrammatic analysisSignificant errors.

1-7

Some understanding of the specific demands of the question.Some recognition of relevant economic theory.

8- 13

1

Some relevant terms defined.Reasonable attempt at diagrammatic analysisSome errors. Some real world examples used

Understanding of the specific demands of the question.Relevant economic theory explained and developed.Relevant economic terms defined.Very good diagrammatic analysisFew errors.Good examples used.

13-19

Clear understanding of the specific demands of the question.Relevant economic theory clearly explained and developed.Relevant economic terms clearly defined.No major errors.Excellent, well explained diagrammatic analysisMany good examples used.

20-25

2. Explain the concepts of absolute and relative productivity in individual sports and discuss how these concepts help us to understand the observed pattern of rewards in tournaments. (50 Marks)

An answer to this question may include all, or some, of the following:

Definitions of absolute and relative productivity with sports examples. Analysis of why relative prod. is used as the basis for rewards. Examples of nonlinear reward patterns in rank order tournaments. Assumptions of tournament theory (participants max utility, organizers want

max. effort from entrants). Explanation of increasing marginal cost of effort with diagram. Explanation of how rewards are set to elicit max effort with diagram. Negative externalities of tournaments (drugs, etc.) Exceptions to non-linear rewards systems (motor sport).


Assessment Criteria MARKS


1-15

Some understanding of the specific demands of the question.Some recognition of relevant economic theory.Some relevant terms defined.Reasonable attempt at diagrammatic analysis

16-30

2

Some errors. Some real world examples used


31-40


40-50

3. (a) Use the Scully model to illustrate how a sports organisation can profit maximize. (30 marks)


The Scully Model of Profit Maximization Scully’s 1995 analysis (book: The Market Structure of Sports) of the theoretical relationship between a club’s winning percentage, ticket prices, attendance and profits is a good exposition of the π max hypothesis.

The diagrams below are based on the assumption that all teams have identical supply functions for talent. In practice this assumption does not strictly hold → the teams in the largest media markets (Real Madrid, Man U) have the advantage that high-profile players know that hey can get more income from commercial endorsements.

Nevertheless we start from the position of an equal cost of hiring.

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P

C

MC(T)

MR(T) D(T)

Te

W

1W

eW

2

Revenue, cost

Win percentage

Figure 1 (a)

The marginal cost of acquiring player talent (T) is given by MC(T).

Demand for wins by a team depends on a number of factors such as the size of the franchise market and the elasticity of its fans’ demand for wins. The elasticity of demand for wins is influenced particularly by real income per capita in the locality and the number of competing sports. Loyal fans turn up no matter how the team is doing so a city with many loyal fans would have an inelastic demand for wins. Conversely, fickle fans would have an elastic demand for wins.

In this model the term we represents a πmax winning percentage where MC(T) = MR(T), the marginal revenue derived from a particular level of talent, with Te, being the πmax level of talent required to produce this outcome.

However playing success has a random component due to injuries, mistakes by the referee, or a mismatch between managerial skills and players. Thus us a range of win percentages associated with Te talent such as w1 – w2. In turn this range gives rise to variation in attendance between A1 and A2 in Fig. 1(b).

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0

A1

A2

A3

attendance

win percentagew1 w2 w3

A

Figure 1(b)

0

Π1

Πe

Π2

Profit

Win percentagew1 w2 w3

Π(T) = TR − TC

Figure 1(c)

Π0

Since Scully assumes that revenue is proportional to the team’s winning percentage as indicated by Π(T) in Figure 1 (c), but that costs are fixed for the season, teams will make positive profits for winning percentages above or close to the profit maximising level, we, as shown by Π0.

In Europe a complicating factor that changes the πmax level of talent is that clubs compete within a national league but also in European competitions → clubs might

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acquire more talent than can be justified for domestic competition in order to compete successfully and maximize overall profits.

International club competitions are likely to make domestic competitions much less stable because clubs don’t know if they will qualify for Europe. We will discuss this complicating factor when we look at labour markets.

Scully’s model focuses on the proportion of games won. Fans may be more interested in their team contending for a championship. These are not the same → in an evenly balanced league a team with nearly 50% wins could be in contention while in a highly unbalanced league a team with 60% wins could be out of contention.

Whitney (1988) argues that if fans care primarily about championships, then a shorter season or a smaller league will enhance the role of chance in determining outcomes and increase uncertainty of outcome. Similarly, the play-offs common in many leagues will help to sustain fan interest.

When teams are located in franchises (cities) of widely differing population sizes Scully’s model implies cross team variations in the demand for talent. It is profitable for clubs in large cities to win more often than teams in small cities → the MR generated by an additional win is higher in a larger city. So strictly following the rules of πmax might cause some small city teams to have no chance of winning a league trophy.

Such deliberate mediocrity would be not be acceptable to fans however, and could never be openly declared.


(b) Discuss the tension between profit and win maximization for sports organisations. (20 marks)

(b) This is a very open question and it is difficult to be prescriptive about the content. Marks should be awarded on the basis of the quality of the economic reasoning and inclusion of some of the discussions covered in the course. Issues that could be included are:

Differences in structure between N.American & European sports leagues. Promotion/relegation as an incentive to win max. Higher broadcasting revenues as an incentive to win max. Cultural/historical differences between N.American & European sports. Possible use of Sloane model.


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Assessment Criteria

A (30) B (20)Completely inappropriate answer 0 0Little understanding of the specific demands of the questionVery little recognition of relevant economic theory.Relevant terms not defined.No attempt at diagrammatic analysisSignificant errors.

1-10 1-6

Some understanding of the specific demands of the question.Some recognition of relevant economic theory.Some relevant terms defined.Reasonable attempt at diagrammatic analysisSome errors. Some real world examples used

12-18 7-12


19-25 13-16


25-30 17-20

4. The broadcasting of sport and the issuing of sports broadcasting rights is quite heavily regulated. Use economic reasoning to explain why. (50 marks)


Discussion of regulation in sports broadcasting with examples, i.e.o “Blackouts” in US sports.o EU comp. authorities restriction on number of EPL games to be bid for

by BSkyB.o UK comp authorities veto on BSkyB buying Man U.o “Listing” of Major sports events in Europe.

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o Collective vs individual sale of sports rights by clubs/franchises.o Revenue sharing of broadcast revenue. o Barriers to entry being removed by new technology (digital, internet).

Economic rationale for these regulations in terms of:o Restriction of monopoly power ➔ diagram(s) could be used here.o fostering of competitive balance ➔ diagram(s) could be used here.




1-15


16-30


31-40


40-50

5. Explain the Coase theorem and the invariance thesis as they apply to sports labour markets and discuss how you would test these theories in a sports context. (50 marks)

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A basic answer for 25 marks will contain the following elements:

Description of the Coase theorem/invariance thesis with example Application of Coase theorem/invariance thesis to sport with example(s) Discussion of whether observed outcomes in sport support the Coase

theorem/invariance thesis, for example after Bosman/free agency.

Further marks can be awarded for the following:

Including a diagram to illustrate the invariance thesis in sport (the Fort/Quirk diagram was used in the lecture).

A high quality discussion of whether observed outcomes correspond to the predictions of the CT, possibly with data or very good real-world examples.



1-15


16-30


31-40


40-50

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6. Given the league tables below show how you would assess any change in competitive balance in this league between 2006-7 and 2011-12.

ENGLISH BASKETBALL LEAGUE DIVISION ONE (MEN) LEAGUE TABLE 2006-07Team Wins Losses Games Points

Worthing Thunder 21 1 22 42Reading Rockets 19 3 22 38

Manchester Magic 17 5 22 34London Leopards 13 9 22 26

PAWS London Capitals 13 9 22 26UH West Herts Warriors 11 11 22 22

Sheffield Arrows 11 11 22 22Solent Stars 7 15 22 14

Coventry Crusaders 6 16 22 12Kings Lynn Fury 5 17 22 10

Tees Valley Mohawks 5 17 22 10Northampton Neptunes 4 18 22 8

ENGLISH BASKETBALL LEAGUE DIVISION ONE (MEN) LEAGUE TABLE 2011-12Team Wins Losses Games Points

BA London Leopards 20 4 24 40Bristol Academy Flyers 18 6 24 36

Derby Trailblazers 16 8 24 32Worthing Thunder 16 8 24 32Leicester Warriors 15 9 24 30Bradford Dragons 15 9 24 30Reading Rockets 14 10 24 28

Medway Park Crusaders 12 12 24 24Brixton Topcats 11 13 24 22Leeds Carnegie 10 14 24 20

Tees Valley Mohawks 4 20 24 8Westminster Warriors 3 21 24 6

PAWS London Capitals 2 22 24 4

Three methods were covered in the course, and for a mark of 40+ all three must be used and be correct. The methods are:

Standard Deviation of Win % (SDWP)

The formula for the SDWP within a single season is:

sw , t=√∑i=1

N

(WPCT i , t−0 .500 )2

N

10

where:

WPCTi,t = the winning percentage of the ith team in the league in year t0.500 = is the average winning percentage of all teams for the yearN = the number of teams in the league

Standard Deviation Ratio (SDR)

SDWP not much use when looking at a league where the number of teams has changed (as in the question). The SDR controls for this characteristic of the SDWP and provides a useful comparison of WPCTs over time. The SDR is the standard deviation of winning percent in a perfectly balanced league.

Suppose the probability any team beats another literally is 0.5 (“on any given day any team can beat any other” It ends up that the standard deviation of winning percent in this version of a perfectly balanced league is

0 .5√m

where m is the length of the season measured in games. If we divide the actual standard deviation by the standard deviation for a balanced league, we have controlled

for any changes in season length by the denominator √m .

Therefore the SDR is:

SDR= SDWP0. 5/√m

C5 ratio.

In a standard industry, the five firm concentration ratio measures the extent to whichan industry is dominated by the five largest companies. When applied to a sports league, the five club concentration ratio measures inequality between the top five clubs and the rest of the league and may be calculated using the following formula:

C5 ratio =total number of points by top 5 clubstotal number of points won by by all clubs

=∑i=1

5

Si

where Si is the share of points of the ith club. The C5 ratio is a function of the numberof firms or clubs in an industry or league and the degree of inequality between the top5 clubs and the rest where increases in the index reflect a reduction in competitive

balance and increased domination by the top five clubs

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ENGLISH BASKETBALL LEAGUE DIVISION ONE (MEN) LEAGUE TABLE 2011-12Team WPCT WPCT-0.5 WPCT-0.5002

1BA London Leopards

0.833333333

0.333333333 0.111111111

2

Bristol Academy Flyers 0.75 0.25 0.0625

3Derby Trailblazers

0.666666667

0.166666667 0.027777778

4Worthing Thunder

0.666666667

0.166666667 0.027777778

5Leicester Warriors 0.625 0.125 0.015625

6Bradford Dragons 0.625 0.125 0.015625

7Reading Rockets

0.583333333

0.083333333 0.006944444

8Medway Park Crusaders 0.5 0 0

9Brixton Topcats

0.458333333

-0.04166666

7 0.001736111

10Leeds Carnegie

0.416666667

-0.08333333

3 0.006944444

11Tees Valley Mohawks

0.166666667

-0.33333333

3 0.111111111

12Westminster Warriors 0.125 -0.375 0.140625

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PAWS London Capitals

0.083333333

-0.41666666

7 0.1736111110.5 SUM 0.701388889

SUM/N 0.053952991

SQRT 0.232277832SDWP

2.275848672 SDRC5 numerator 170C5 denominator 312

c50.54487179

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ENGLISH BASKETBALL LEAGUE DIVISION ONE (MEN) LEAGUE TABLE 2006-07Team WPCT WPCT-0.5 WPCT-0.5002

1 Worthing Thunder0.95454545

50.45454545

5 0.20661157

2 Reading Rockets0.86363636

40.36363636

4 0.132231405

3 Manchester Magic0.77272727

30.27272727

3 0.074380165

4 London Leopards0.59090909

10.09090909

1 0.0082644635 PAWS London Capitals 0.59090909 0.09090909 0.008264463

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1 16 UH West Herts Warriors 0.5 0 07 Sheffield Arrows 0.5 0 0

8 Solent Stars0.31818181

8

-0.18181818

2 0.033057851

9 Coventry Crusaders0.27272727

3

-0.22727272

7 0.051652893

10 Kings Lynn Fury0.22727272

7

-0.27272727

3 0.074380165

11 Tees Valley Mohawks0.22727272

7

-0.27272727

3 0.074380165

12 Northampton Neptunes0.18181818

2

-0.31818181

8 0.1012396690.5 SUM 0.76446281

SUM/N 0.063705234

SQRT0.25239895

8 SDWP2.36771210

4 SDR

C5 numerator 166C5 denominator 264c5 0.628787879

Conclusions:

SDWP 06-07 = 0.25 SDWP 11-12 = 0.23 league became marginally more competitive. Std deviation of win% became smaller.

SDR tells us the same story. Needed to use this because numbers of teams and games changed.

C5 ratio number of points going to the top 5 teams decreased from 63% to 54%. Also suggests the league became more competitive.

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Learning Outcomes/ Question matrix

Q1 Q2 Q3 Q4 Q5 Q6i. Critically evaluate the theoretical literature relating to economics of sport;

X X X X X X

Demonstrate an awareness of /the distinctive characteristics of labour and product markets in professional team sports, and their implications for economic analysis;

X X X X

Demonstrate an appreciation of the role of the empirical work in testing the various theories;

X X X X

Understand the implications of theoretical and empirical work in the economics of sport for policy issues including competitive structure in sport leagues, free agency and player mobility, and the financing of professional sport.

X X X

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economics of sport exam 2012-13 marking scheme

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