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Solution Manual For Sports Economics, 1st Edition

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    Chapter One Study Questions 1. According to Thorstein Veblen, who primarily played sports in the latter 19th century? Solution: The wealthy or the leisure class primarily played sports in the latter 19 th century. 2. How many boys and girls play high school sports today? Solution : More than 4 million boy s and more than 3 million girls play high school sports today. 3. How does viewership of the Super Bowl (the biggest game in American football) compare to viewership of a regular - season soccer match (international football) in Spain? Solution : Viewership for the Super Bowl is 160 million , while viewership for a regular - season soccer match in Spain is 40 0 million. 4. What percentage of sports fans are women? What percentage of the sports media are women? Solution: Thirty to 45% of sports fans are women ; 10% of the sports media are women . 5. According to former President Barack Obama (and he was far from alone in making this argument), what is the relationship between player salaries and ticket prices? Solution : Higher player salaries cause higher ticket prices. 6. According to Humphreys and Ruseski (2009), what is the size of the U.S. sports market?

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    Solution: The size of the U.S. sports market is $44 to $60 billion . 7. According to John Maynard Keynes, what is the purpose of economic analysis (according to Alfred Marshall)? What does an economist need to engage in such an analysis? If we apply this perspective to the study of sports economics, what does an economist need to study sports? Solution: According to Keynes, Marshall says that the purpose of economic analysis is to apply the theory to “current economic life.” To do this, one must know the facts of the industry. So to study sports, an economist needs to know sports in addition to economics. 8. What are the tongue - in - cheek steps to the Marshallian method? How can they be applied to the question that was the starting point for this chapter? Solution: Use mathematics as a shorthand language rather than as an engine of inquiry , and keep at it until you are done. Translate into English and illustrate by examples that are important in real life. The question at the beginning of the chapter is , W hat determine s ticket prices in professional sports? The Marshallian method was applied through out the chapter, first formulating a demand curve, then stating it in Eng lish, and then examining real - world data to see how this works. 9. What are the key words in the definition of supply and demand? Solution: You must be “willing and able.” To be in supply or demand of a good , you have to be able and willing to participate in the market.

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    10. With respect to the demand for baseball tickets, what are factors that:  cause movement along the demand curve? Solution: A change in the price of the good causes movement along the demand curve.  cause the demand curve to shift? Solution: A change in any demand factor besides the price of the good will cause the demand curve to shift . This includes personal income, market size, change s in quality of the good, and so on . 11. What part of the demand curve changes when the curve is shifted? What part of the demand curve should not change? Solution: The y - intercept changes when the curve shifts. The slope does not change. 12. What has determined the price of Honus Wagner’s baseball card over time? Be able to illustrate this story (i.e., draw a supply and demand graph). Solution: As incomes have increased among baseball fans, d emand for the card has increased . But since only a certain number of cards were printed, s upply has remained fixed. With a fixed supply, demand solely determines the price, so the price of the cards ha s increased significantly. At a 2013 auction, one of Wagner’s cards sold for $2.1 million.

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    13. How is the market period different from the normal period in Marshall’s analysis of prices? Solution: Market period is when supplied is fixed , so prices are determined entirely by changes in demand . Normal period has an upward - sloping supply curve. 14. Why did Nike take Reebok to court over the production of Tim Tebow jerseys in the S pring of 2012? Be able to illustrate th is story. Solution: Nike had the right to make and sell the jersey. If Reebok also made the jersey, supply would increase and the price of the jersey would decline.

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    15. According to Ma rshall’s supply and demand model , what determines the price of tickets in the NBA? Be able to illustrate this story. Solution: P rice of tickets is determined by demand . 16. How does the NBA’s salary cap impact quantity demand and quantity supplied of labor in the NBA’s player market? What is the intent of this cap? According to the text, what is the actual impact of this cap?

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    Solution: The NBA’s salary cap is a price ceiling set below the equilibrium wage for the NBA player’s market. With this price ceiling in place, no team can offer more money than the NBA maximum even though it might be willing to pay this maximum. This cap was intended to prevent the richest NBA teams from assembling a team that would dominate the league. By forcing the price of stars below the equilibrium wage, all teams should be able to acquire top talent. But in reality, star players consider factors besides the wage in determining where they will play, such as their chances of winning a title. So the policy falls short of preventing a team that dominates the league. 17. Is there a “right” price for labor? Utilize the perspective of John Stuart Mill in answering this question. Solution: There is no “ right ” price for labor. What labor is paid depends on the laws of society. 18. What is the difference between positive and normative economics (according to John Neville Keynes)? How are “morality” and “economics” summarized by Steven Levitt and Stephen Dubner? Solution: Positive economics is the study of “ what is ,” and normative economics is the study of “ what ought to be. ” Morality, it could be argued, represents the way that people would like the world to work — whereas economics represents how it actually does work. 19. What is deductive reasoning? What is inductive reasoning?

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    Solution: Deductive reasoning is m oving from the general to the specific. With deductive reasoning one begins with basic principles and then logically derives a model of how the world works. Inductive reasons begins with data and then derives a theory. 20. According to Marshall, what is the basic approach to economics? Solution: Economics is not dogma, and it is not a collection of universal truths. The tools of economics, including both deductive and inductive reasoning, simply provide us with the means to uncover how the world appears to work. Thought Questions 1. Tim Tebow ’ s NFL career ended with the New York Jets in 2012. How would his lack of success with the Jets impact the pric e of his Jets jersey? Now imagine Tebow becomes a media celebrity in New York when his athletic career finally ends (currently he is a minor league baseball player). How might that impact the price of this jersey? If Tebow becomes a media celebrity in New York, could we deduce the price of his Jets jersey in the future (i.e. , ascertain its value without analyzing data)? Solution: His lack of success in football lowers demand for the jersey and therefore lowers the price. But media success might cause demand to increase. If both events happened, the price of Tebow ’ s jersey could not be simply deduced. 2. At the conclusion of the 2016 college football season, the University of Alabama ’ s football team had existed for 113 years, appeared in 66 bowl games, and won 26

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    conference titles. Utilize what you know about the NCAA ’ s limit on compensation of college athletes to explain the dominance of this football team. Solution: Because all NCAA schools essentially pay the same wage, athletes use a different criteria to select their school. The most obvious criteria is the likelihood that the team will win. That means the top athletes , who have the most choices , tend to choose the same schools with a history of winning. And that means schools like Alabama will persistently win. Math Questions 1. Define the elements of the following equation: P = a 0 – a 1 × Q d . Solution: P = dependent variable Q d = independent variable a 0 = y - intercept a 1 = slope coefficient 2. Given P = $150 – 0.005 × Q d as the demand for a professional sports team: a. If P = $60, what is Q d ? Solution: 18,000 b. If P = $40, what is Q d ? Solution: 22,000 3. Imagine these two possible changes from the demand curve listed in Question 2: a. P = $175 – 0.005 × Q d

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    b. P = $125 – 0.005 × Q d For each, identify whether Question 3 (a) or 3 (b) would be consistent with the following stated changes: i. increase in the size of the market where the team plays Solution: a ii. decrease in the per - capita income in the market where the team plays Solution: b iii. move to a newer stadium Solution: a iv. decline in the quality of players employed by the team Solution: b 4. Define the elements of the following equation: P = b 0 + b 1 × Q S . Solution: P = price of a good Q S = quantity supplied of a good b 0 = y - intercept b 1 = slope coefficient

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    Chapter Two Study Questions Study Questions (D eductive ) 1. For any given price, how would the following changes impact a team’s revenue? a. Increase in the size of the market Solution: revenue increases b. Building a new stadium Solution: revenue increases c. Decline in the quality of the team’s roster Solution: revenue declines 2. For a typical firm, what is the shape of the marginal cost curve? Why does it have this shape? Solution: Upward - sloping. This is be cause of the l aw of d iminishing r eturns. As a firm expands , it must hire more labor to produce th e additional output. Because capital is fixed, the productivity of labor declines and the marginal cost increases. 3. For a sports team, what might the shape of the marginal cost curve be? Why does it have this shape? Solution: It is zero until a team reaches capacity. Then it is vertical. This is because adding additional fans (i.e. , increasing output for a team) essentially costs nothing until a team reaches capacity. T hen the cost is essentially infinite. 4. What is the profit - maximizing rule? Solution: Marginal revenue equal s marginal cost Study Questions ( Inductive ) 5. Given Wins = a 0 + a 1 × Population + e i what is the regression term that describes each element in this equation? a. Wins Solution: dependent variable b. a 0

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    Solution: y - intercept or constant term c. a 1 Solution: slope coefficient d. Population Solution: independent variable e. e i Solution: error term 6. What is a “constant term”? Why is this term included in a regression equation , and what information does it convey? Solution: The constant term is the y - intercept. It is the value of the dependent variable when the independent variables are zero. It is included to enforce a zero mean for the error term. But it doesn ’ t convey any practical information because zero values for the independent variables are often outside the realm of what is possible. 7. We have a rule - of - thumb that a t - statistic should be, in absolute value, greater than 2. Explain the reasoning behind this rule. Solution: We are 95% certain that the true value of any estimated coefficient is within 2 standard errors of the coefficient. So if a coefficient is 8 and the standard error is 6, we are 95% certain that the true value of the coefficient is between - 4 and 20. Such a range would mean that the true value could be negative, zero, or positive. In other words, we don ’ t really know the direction of the relationship. But if the standard error w ere 2, then the true value would lie between 4 and 12. Now we would be 95% certain that the true value is not zero and not negative. Now imagine that the standard error is 4. In that instance, the confidence interval would extend from 0 to 16. So zero is on the edge of our interval. In this instance the t - statistic — or the coefficient divided by the standard error — would be 2. So if the t - stat istic is 2, zero lies on the edge of the confidence interval and can ’ t be eliminated. Hence we prefer a value that in absolute terms is greater than 2. 8. How do we calculate R - squared? What does this tell us? Solution: R - squared is either ESS / TSS or 1 − (RSS/TSS) It tells us the percentage of the dependent variable explained by our model.

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    9. What is the relationship between market size and win in North American pro sports? Answer this question using both deductive and inductive analysis. Solution: Deductive analysis says that market size and wins are strongly linked. Inductive analysis of the four major North American sports leagues failed to find a strong empirical link . 10. Use the following econometric model and results to answer th e s e question s . Dependent Variable: Team Winning Percentage from the WNBA (1997 ‒ 2013) a. Interpret each slope coefficient. Solution: An additional point scored per game will increase winning percentage by 3.15%. An additional point surrendered per game will decrease winning percentage by 3.11%. b. For which variables are we at least 95% certain that the coefficient is different than zero? Solution: Points Scored and Points Surrendered c. Explain the reasoning behind your answer. Solution: To answer this question , you need to calculate the t - statistic. The t - statistic for points per game is 31.5. For points surrendered per game , it is − 28.27. Both values are greater than 2 in absolute terms , so both coefficients — according to our rule - of - thumb — are statistically significant. d. For which variables are we not at least 95% certain that the coefficient is different than zero? Explain the reasoning behind your answer. Solution: None e. Calculate the R 2 and interpret your answer.

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    Solution: Explained s um of s quares is 4.609. So R - s quared is 4.609/5.5652 , which is 0.828. 11. What is the relationship between payroll and wins in MLB, the NFL, NBA, and NHL? Is the deductive study consistent with the inductive study? Solution: P ayroll does not explain as much as 25% of the variation in winning percentage and fails to explain 75% of the variation in winning percentage. The deductive model suggests that payroll is very important to team wins. But the empirical analysis — or the inductive analysis — suggests a different story. 12. When we estimate the model in Question 10 for the NBA , we see a higher explanatory power than what we do for MLB, the NFL, and the NHL. Why is explanatory power higher for the NBA? Why are we unable to explain 100% of the variation in winning percentage with points scored and points surrendered per game? Solution: The NBA has fewer blowouts than the other three leagues. In each game decided by more than 1 point , there are points scored and surrendered that do not actually impact the outcome of the game. These excess points reduce our explanatory power. 13. What factors should we consider in evaluating a regression? Should we make sure the regression conforms to prior beliefs? Solution: These are listed in the text. And prior beliefs are not part of our list. We have to allow our empirical analysis to change what we think about the world. 14. What is the difference between statistical significance and economic significance? Solution: Statistical significance tells us if the estimated coefficient is different from zero. Econ omic significance is what we think about when we wonder how large of an effect we have uncovered. Thought Questions 1. W hy do NFL, NBA, and NHL teams tend to sell ou t while MLB teams do not? Solution: The NFL, NBA, and NHL appear to reach a profit - maximizing level of attendance beyond the capacity of the stadium/arena where they play. This is not the story in baseball. 2. According to deductive reasoning, how successful should the New York Mets be on the field relative to the Detroit Tigers? From 1962 to 2016, the Mets won 48.1% of their

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    regular season games while the Tigers won 49.9% of their contests. Do these records match your deductive reasoning? Why or why not? Solution: The Mets — playing in a much bigger market — should be much more successful. The inductive reasoning, though, tells us that there is more to team success than market size. 3. Consider the following regression for the WNBA: Wins = b 0 + b 1 × Points per Game + e i Dependent Variable: Team Winning Percentage from the WNBA (1997 ‒ 2013) a. What is the 95% and 99% confidence interval around ( b 1 )? Solution: The 95% confidence interval ranges from 0.006 to 0.013. The 99% confidence interval — or three standard errors in each direction — is 0.005 to 0.014. b. Is ( b 1 ) statistically significant? Solution: By our rule - of - thumb (i.e. , the t - stat istic must be greater than 2) , we would conclude it is statistically significant. The t - stat istic is 6.195. c. According to the results below, what is the chance that ( b 1 ) could equal 0.0315? Solution: Less than 1%. A value of 0.0315 is outside the 99% confidence interval. d. What lesson do we learn when we compare the results belo w to the results from Question 10 above? Solution: If you do not specify a model correctly , you can be very misled. The estimated coefficient in the model below is statistically significant. And the range possible is not even close to what we see when we specify the model correctly. This highlights why specifying a model correctly is so important and how we have to be careful interpreting a model.

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    Math Questions 1. If P = a 0 – a 1 × Q , what is the equation for total revenue? Solution: TR = P × Q , so TR = [ a 0 – a 1 × Q ] × Q TR = a 0 × Q – a 1 × Q 2 2. If P = $150 – 0.005 × Q , what is the equation for total revenue? Solution: TR = $150 × Q – 0.005 × Q 2 3. Complete the following table: 4. If P = $ 50 – 0.005 × Q , a. what is the equation for marginal revenue? Solution: MR = $ 50 – 0.01 × Q b. how many tickets will the team sell when it maximizes revenue? Solution: To answer this, set MR = 0 and solve for Q : 50,000 c. what will the price be when the team maximizes revenue? Solution: $25 d. how much revenue will the team earn when it maximizes revenue? Solution: $1,250,000

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