LA Lakers’ salaries, 2003-04 Shaquille O’Neal 28,515,000 Kobe Bryant 13,500,000 Gary Payton 4,917,000 Rick Fox 4,549,000 Devean George 4,545,000 Derek Fisher 3,000,000 Stanislav Medvedenko 1,500,000 Karl Malone 1,483,000 Kareem Rush 1,096,000 Bryon Russell 1,070,000 Samaki Walker 1,400,000 Brian Cook 752,000 Jamal Sampson 583,000 Luke Walton 366,000 Ime Oduka 366,000 LA Clippers’ salaries, 2003-04 Elton Brand 10,960,000 Cory Maggette 5,475,000 Pedrag Drobnjak 2,500,000 Chris Kaman 2,394,000 Keyon Dooling 2,256,000 Chris Wilcox 2,066,000 Marko Jaric 1,900,000 Quentin Richardson 1,805,000 Melvin Ely 1,628,000 Olden Polynice 1,070,000 Doug Overton 974,000 Eddy House 775,000 Matt Barnes 366,000 Josh Moore 366,000 Core principles of the economic way of thinking • People optimize – they try to maximize some objective, subject to constraints, i.e. to the fundamental fact that they can’t have everything they want. The object of maximization often is, but need not be, money. • This leads to the idea of efficiency, or how to create the most value. • Value is often best thought of as the sum of producer surplus (space between price line and supply curve) and consumer surplus (space between price line and demand curve). Markets and the creation of value • Unrestricted operation of markets generally create the most value. There are three exceptions: • (1) Restricted competition. In markets where there is imperfect competition and restricted entry, the price will not be the competitive one. • (2) Externalities. When an action or transaction affects others, those costs or benefits are not properly internalized by the price system. • (3) Public goods. Some goods are nonrivalrous and nonexclusive, and are therefore underprovided. (More to come in unit on stadiums and mega-events.) Regression – the basics • Regression is a statistical technique to measure the extent of the relationship between variables that theories say are supposed to be related. Wages, for example, might be related to years of experience and to education. Mathematically, we might write w = f(t,s). • There are two criteria that are often used in regressions: • (1) Statistical significance for particular variables. Is the relation between a single right-hand variable (schooling, say) and the left- hand variable (wages) strong enough in the data that it is probably not due to random chance? • (2) Overall explanatory power of the model. Usually measured by R2, a figure which varies between 0 and 1. A high R2 means that movement in the right-hand variables coincides with most of the movement in the left-hand one. An R2 of close to zero means that collectively little of the movement in the right-hand variables coincides with movement in the left-hand ones. NFL, 1996 Gate Revenue Mean: $23 million Variance: $14.97 million Broadcast Revenue Mean: $43 million Variance: $40.41 million Licensing Revenue Mean: $6 million Variance: $58.61 million MLB, 1996 Gate Revenue Mean: $25.73 million Variance: $140.144 million Broadcast Revenue Mean: $25.23 million Variance: $93.69 million Licensing Revenue Mean: $12.65 million Variance: $41.74 million NBA, 1996 Gate Revenue Mean: $23 million Variance: $64.07 million Broadcast Revenue Mean: $21 million Variance: $27.06 million Licensing Revenue Mean: $8 million Variance: $26.97 million Economic idea: vertical and horizontal integration. • Vertical Integration occurs when a company in one stage of a production process purchases a firm in another stage. • Horizontal Integration occurs when one company at a particular level of the production process (especially the final product) purchases another company at the same stage. • Accounting profits are money in (total revenue) minus money out. • Economic profits are total revenue minus opportunity cost of resources used. Economic ideas: Standardization and network externalities • A network externality is when the benefits a consumer derives from owning a product depend on the number of other users. Standardization enables gains from network externalities. Examples: fax machines operating on a common standard, the Windows operating system. • In this case, a “product” is the number of teams playing by the same set of rules. The more players playing by a given set of rules, the more appealing the product is. Economic idea: Path dependence • Path dependence occurs when the product that arrives first is able to maintain dominance because it becomes the industry standard, even if it is inferior. The costs of adopting a technology that others don’t use are too great. Superior technologies thus can’t get off the ground. • Alleged examples: The QWERTY typewriter, DOS/Windows, the VHS videocassette. • A sports league, from the point of view of setting rules, thus represents a tradeoff – gains from single set of rules, possible losses from rules being inferior. Economic Idea: Productive Efficiency – For a given amount of inputs, how close does a firm come to achieving the maximum level of output? Equivalently, for a given amount of input, how close does a firm come to producing it at minimum cost? Sample Production Function for the NBA To measure productive efficiency, first estimate a production function relating wins to statistical productivity. Then for each team, use its statistical productivity and the production-function estimates to calculate an expected number of wins. The gap between these two is the total inefficiency in the use of inputs. A higher number indicates better coaching. Ruggiero et al. Winning percentage = 2.116 + 1.175 * Slugging percentage + 0.501 * Batting average + 0.054 * Stolen bases + 7.465 * Fielding percentage – 0.826 * ERA Ruggiero et al. Table 14.4, Efficiency in Win Production AL NL Oakland .863 Philadelphia .832 Boston .839 Houston .830 California .836 St. Louis .829 New York .836 Colorado .822 Chicago .833 San Diego .819 Baltimore .832 San Francisco .813 Detroit .830 New York .809 Milwaukee .825 Atlanta .808 Texas .808 Los Angeles .806 Kansas City .805 Cincinnati .805 Cleveland .804 Chicago .800 Minnesota .804 Florida .795 Toronto .791 Montreal .793 Seattle .784 Pittsburgh .793 Source: Lawrence Hadley, Marc Poitras, John Ruggiero and Scott Knowles, “Performance Evaluation of National Football League Teams,” Managerial and Decision Economics 21, 2000, 63- 70. Source: Lawrence Hadley et al. Source: Hadley et al. Above-average coaches Below-average coaches 1. John Madden John McKay 2. Art Shell Dick Nolan 3. Don Shula Bart Starr 4. Bud Grant Sam Wyche 5. Chuck Knox 6. Joe Gibbs 7. Dan Reeves 8. Tom Landry 9. Mike Ditka Source: Hadley et al. Arbitration and Free Agency: Hadley and Gustafson (1991) • Question: How do arbitration and free agency affect player salaries? • Test: for a given level of statistical productivity, are pre-arbitration, arbitration and free-agent players paid differently? Source: Hadley and Gustafson Hadley and Gustafson, Figure 1. Hadley and Gustafson, Figure 2. Measures of competitive balance • Dispersion of team winning percentage in a season • Concentration of championship titles • Dispersion of lifetime franchise winning percentage Quirk and Fort, Table 7.1. Quirk and Fort, Table 7.1 (continued). • Economic idea: A Lorenz Curve relates the percentage of the population to the percentage of some other variable it possesses. A 45-degree line represents perfectly equal distribution of the other variable. Most commonly used example: distribution of income. Source: http://www.chicagofed.org/publications/economicperspectives/2000/2qep1.pdf Why does competitive imbalance exist at equilibrium? • Dynasties and dominant teams have value for fans, too. • Resistance of major-franchise owners. • Owners substantially maximize profits, and Coase theorem applies. Economic Idea: The Coase Theorem explores whether the initial distribution of property rights matters with respect to its final use. He argues that as long as transaction costs are low, the initial allocation of a right to a particular piece of property does not matter. Applications include legal disputes, especially nuisance suits, allocation of broadcast frequencies, and many others. Ways to improve competitive balance • Universally used: - Reverse-order draft - League-wide TV contracts • Less widely used - Salary caps (NBA, NHL, NFL) - Soft salary cap: exemption for own free agents. - Hard salary cap: no exemption. - Reverse-order scheduling (NFL only) - Luxury taxes (MLB only) • Seldom used - More franchises Problems of salary caps • Owners cheat. • Benefits mostly low-end and highest-end players. • Given franchise-entry restrictions, it is more efficient for bigger cities, with bigger audiences, to win more. • Disincentive to improve. Economic Idea: Marginal Revenue Product is the addition to a firm’s revenue by a particular worker, equivalent to his marginal product (i.e., his addition to output) times the unit price of the output. Economic theory holds that in perfect competition workers’ wages will always be bid up to marginal revenue product. If workers are paid less than MRP, it is a sign of market inefficiency. Scully (1974) – Estimating MRP A three-stage process: - Step 1: Find the relation between a team’s statistical production and its winning percentage. - Step 2: Find the relation between wins and team revenue. - Step 3: Estimate a player’s contribution to team statistics, therefore to wins, and therefore to revenue. Scully (1974) (continued) • Scully, estimated relation between winning percentage and player statistical performance PCTWIN = 37.24 + 0.92 * SLUGGING + 0.90 * K/W – 38.57 * NL + 43.78 * CONTEND – 75.64 * OUT • Estimated relation between wins, team revenue REVENUE = -1,735,890 + 10,330 PCTWIN + 494,585 * POPULATION + 512 * FAN INTENSITY + 580,913 * NL – 762,248 * OLD PARK - 58,523 * BLACK PLAYERS PCT • One player’s MRP assumed to be: 1/12 * SLUGGING * $10,330 (position players) 1/8 * K/W * $10,330 (starting pitchers) Scully (1974) (continued) • There is now a predicted relation between statistical production and salaries if players are paid MRP. • Next step: Regress actual individual salaries on statistical productivity and these other considerations. Compare what typical players are actually paid to what they should be paid according to the MRP they generate. End result (Table 2): The least talented players were actually overpaid after deducting their maintenance costs (transportation, training equipment, etc.) Their “net MRP” (gross additions to revenue minus these costs) was negative. But average and star players got only about 15-25 percent of their net MRP. “The most radical proposal is a completely free labor market with all contracts for a full season being negotiated off-season. The proposal would eliminate player economic rents. Organized baseball argues that such a scheme would destroy the game. They point to the rich owner, who could not be prevented from buying all of the good players. They argue that investments in teams would be unattractive. Teams would fold and no buyers would be found. They also forecast the end of player development and minor league subsidies and hence long-term damage to the sport.” - Scully (1974), p. 930. “The Wages of Sin…” (Jones et al.) • Question: What are the features of a hockey player that teams are willing to pay for? Is violent play one of them? • Test: Regress hockey salaries on measure of experience, playing skill, physical size and market structure. “Playing skill” includes penalty minutes, which for most players should have a negative effect on salary. Defensemen and forwards are assumed to have different salary equations. • An econometric technique called “switching regression” allows you to look at a group of observations and see if they can be allocated into two distinct groups (“goons” versus non- goons). • After conducting the regressions, such differences exist. In other words, there are two different salary processes determining the compensation of goons and non-goons. Goons are clearly a distinctive input into win production. Statistical differences in the two groups: Scoring Forwards Non-goons: 0.74 points/game Goons: 0.31 points/game Defensemen Non-goons: 0.51 points/game Goons: 0.25 points/game Penalty Minutes Forwards Non-goons: 0.88 minutes/game Goons: 3.14 minutes/game Defensemen Non-goons: 0.98 minutes/game Goons: 2.31 minutes/game Determinants of pay for non-goons • Forwards – Points per game and penalty minutes are positively significant for goons and non-goons. But experience is only significant for non-goons, suggesting that there is a greater search cost problem in identifying quality non-goon players that doesn’t exist with goons. • Defensemen - Experience, penalty minutes and weight are positive and significant determinants of salary. But scoring is only significant for non-goons. What determines your probability of being in the goon category? • A “probit” estimation finds that weight and penalty minutes are positively and significant determinants, while scoring is, for defensemen at least, negatively and significantly correlated. The marginal product of figure skaters • Economic idea: Revealed preference refers to the use of people’s choices to infer their preferences, rather than vice versa. Economic idea – the elasticity of demand measures the responsiveness of quantity demanded to changes in price. When a small change in price (in either direction) causes a big change in quantity (always in the other direction), we say that demand is very elastic. When a big change in price causes a small change in quantity, demand is very inelastic. Elasticity of demand is a function of the number and quality of the available substitutes. • “We’re not really going to worry about what the hell [the fans] think about us. They really don’t matter to us. They can boo us every day, but they’re still going to ask for our autographs if they see us on the street. That’s why they’re fans and we’re NBA players.” - Former Portland Trailblazer Bonzi Wells. The economics of rank-order tournaments • Assumption: Workers/competitors can’t be paid their marginal revenue products because MRPs and effort are unobservable. The only thing the firm can observe is the relative order of output (i.e., who produces the most, who produces the second-most, etc.) • The marginal cost of effort by the worker, while unobservable, is known by the worker and is forever increasing. In other words, the marginal cost of effort is always getting bigger. • Therefore, to obtain significant effort the prizes to finishing high in the ranking must be large, and then must decline quickly as the final ranking increases. In other words, the top finisher must be paid much more than the second-place finisher, who must get significantly more than the third-place finisher, etc. PGA Prize Structure (Ehrenberg and Bonnano) • Two tests of whether the tournament model describes PGA rewards: - (1) Does more prize money induce better scores (i.e., more effort)? - (2) Do individual players try harder when the marginal reward to effort is greater? Ehrenberg and Bognanno • Testing (1): - Regress scores on measures of course difficulty, golfer skill and rewards. All variables are significant in the expected direction. It takes more work to do well on a harder course, and prize money reflects that. - If the tournament is a major, then for a given starting position, golfer skill and monetary reward scores are better. • Testing (2): - Look at a player’s ranking entering the last day of the tournament. Use available prize money and number of golfers near him in the standings to calculate the marginal reward of effort, where effort is assumed to mean a given number of improvement in strokes. “It may cost you $5 million to get to the track, but it might cost you an additional $3 million for a few tenths better lap times…It’s pretty cost-effective to a certain point, but that extra little bit is where it is starting to get overwhelming.” Bill Elliott, driver and owner. Von Allmen • Thus, old NASCAR point system is rising, but not as much as PGA. Why? • (1) Improving performance in NASCAR is so expensive that success early in the season could be largely determinative of later success, • (2) There is a negative externality to one type of increased effort – riskier driving. The compensation system must keep this under control. Economic idea: two models of strikes • The resistance model: Each side in a labor dispute has some threat point, i.e. an ability to maintain a standoff. This is a function of alternatives available without production. Example: rival leagues such as the USFL always bring dramatic salary escalation. • The length of a strike and the resulting wage increase are a function of the strength of each side’s threat point. The asymmetric information model: Only management knows the true profit level, and they have an incentive to overstate it. A strike is a way to solicit this information from management. A long strike is a sign profits are low, and a quick settlement indicates that management is understating them. If labor usually wins that is an implication that management does in fact have a lot of profits not being distributed as compensation. A history of North American sports work stoppages • 1972: MLB strike nominally over pensions, really over an attempt to crush MLBPA, which was increasingly assertive. Almost complete victory for players. • 1987: NFL strike primarily over free agency. NFL resorted to replacement players for several games. Eventually threat of striker defections led to owners winning. • 1994: NHL lockout over free agency and salary cap. Rookie salary cap and limits on free agency resulted. • 1994: MLB lockout over salary cap, which was fought successfully in favor of a luxury tax. • 1998: NBA lockout over player desires to eliminate salary cap and draft. In the end salary cap was tightened with restrictions on pay related to years in league. Owners helped by contract requiring NBC and TNT to continue to make payments during lockout. • 2004-5: NHL lockout over salary cap, which owners got. Average salaries, 2001-2 (NHL 2002-3) • NFL 1,200,000* • NBA 4,500,000 • MLB 2,550,000 • NHL 1,640,000 *NFL contracts not guaranteed. Free-agency rules • MLB: Unlimited after six years, arbitration years 3-6, reserve clause years 0-2. • NFL: Eligibility after four years, subject to franchise-player exception. • NBA: Teams have right of first refusal after four years, players unrestricted after five. • NHL: After seven years players become free agents. Salary caps • NFL: 64% of revenues, plus prorated signing bonuses. • NBA: 55% of revenues Plus Larry Bird exception. Separate cap on rookie salaries. • NHL: 54-57% of revenues, depending on how big revenues are. Team salaries must be between $21-$39 million. • MLB: No cap, but luxury tax starting at $117 million payroll. Economic idea: economic theories of discrimination • Taste for discrimination: Firms pay less for workers certain groups either because firm owners don’t like them (employer discrimination) or because customers don’t (customer discrimination). • Statistical discrimination: Firms are in principle willing to pay workers according to productivity (assuming customer discrimination doesn’t exist), but group membership is used as a statistical shortcut when individual productivity data are too costly. Older tests of customer discrimination • Baseball cards – do people pay more for white players with equal career statistics? • All-Star voting – do fans vote more for white players with equal career statistics? • In both cases the answer is yes, with diminishing margins (perhaps to zero now) over time. Testing for employer discrimination: To what extent to workers from some groups get paid less because they are less qualified, versus because they are being discriminated against? The “Oaxaca decomposition”: To try to estimate how much of a wage difference between two groups is due to discrimination and how much to differences in qualifications, multiply the higher- paid group’s regression coefficients times the lower-paid group’s average qualifications. This tells us what the lower-paid group would make if it had the qualifications of the higher-paid group. Any wage difference that remains after doing this is a rough measure of discrimination. Kahn • Fundamental question: do black football players get paid less than white ones, after standardizing for other relevant differences? • Test: Regress players’ salaries on player-skill measures (Pro Bowl appearances, draft position, injuries), market size, injuries, experience measures and race. • Years in league, games started, draft position, Pro Bowl appearances and being white are positively and significantly related. Number of injuries, and being white multiplied by the fraction of the city that is nonwhite, are negatively and significantly related. Kahn (continued) • However: most salary difference is due to positional segregation. Once player position is controlled for, race effects are not statistically significant. • Other things equal, whites make more in cities with bigger white population percentages, nonwhites make more in cities with bigger nonwhite pop. percentages. Hoang and Rascher • Question: Do white players stay in league longer, after standardizing for other relevant differences? • Test: Regress probability of exiting league in a given year of one’s career on player statistics, injuries, team record, draft position, race, experience measures, and player position. • Result: Points/minute, number of injuries, games played, and being white are negatively and significantly correlated with the probability of exiting the league. Lower position in draft is positively and significantly correlated. Why? Customer or employer discrimination? • Test: Regress number of black (white) players on team as function of percentage of city’s population that is black (white). This turns out to be a significantly positive predictor of team’s racial makeup. • Regress attendance on winning percentage, arena size, and extent to which city has more whites and team has more whites. Kanazawa and Funk • Another test for customer discrimination: relation between the number of white players and TV ratings. • Test: Regress Nielsen ratings of locally televised games on quality of both teams and their players, game time, market size, degree of competition from other sports, number of whites in the city, and number of white players on each team. • Result: Quality, prime-time games, market size, number of white players positively and significantly correlated. Degree of competition negatively and significantly correlated. From: Kanazawa and Funk (2001) Aldrich et al. – Discrimination in favor of black quarterbacks • Overall, Monday Night Football games with at least one black starting quarterback have Nielsen ratings at least as high as those with 2 white QBs, despite generally featuring smaller-market teams. • Standardizing for week in season, QB ratings and rushing yards, average team scoring and team wins, the presence of a black QB still has a statistically significant, positive effect on ratings – approximately two million viewers out of roughly 20,000,000. • Effect is most pronounced for males age 18-34. • Over time, having a black QB has gone from making a team less likely to more likely to be scheduled on MNF. Why? • Own-race effect (preference of black viewers for black QB)? Unlikely. Black viewership of MNF would have to increase 67% to account for this. • It is thus probably significantly due to increased white viewership, which may therefore be a taste for diversity. • Because whites are a minority in the NBA, the Kanazawa/Funk results – greater viewership when there are more white NBA players – can be interpreted in the same way. Shmanske – Male and female golfers • Question: Male golfers are better-paid than female golfers. Is it because men put out a more attractive product, or is it because of intrinsic customer discrimination? • Test: Conduct Oaxaca decomposition to see what female players would be paid if they played like males. Shmankse – Comparison of PGA and LPGA tours, 1999 • Events – 45 PGA events, with none less than 3 rounds and 2 with 5 rounds. 36 LPGA events, 12 of which have only three rounds. • Average yardage: 6998 (PGA), 6282 (LPGA) • Average purse: 2,144,444 (PGA), $788,500 (LPGA) Shmankse – Comparison of PGA and LPGA tours, 1999 (continued) • Average putts/round: 29.148 (PGA), 30.300 (LPGA) • Average score: 70.902 vs. 72.918 • Average driving distance: 271.25 vs. 236.63 • Greens in regulation: 65.624% vs. 64.035%. • Drive accuracy: 69.774% vs. 69.065%. • Sand saves: 52.455% vs. 39.208%. Shmanske (continued) • Oaxaca decomposition indicates that the percentage of LPGA compensation due to differing payment for the same amount greens in regulation, sand saves and the number of putts is actually negative – i.e., LPGA golfers are paid more for a given amount of these skills than PGA golfers. (PGA golfers are paid more for a given amount of driving distance and accuracy.) • Overall, the amount of the compensation gap explained by differential PGA golfer productivity is 129%. In other words, given their productivity LPGA golfers are actually compensated 29% more than PGA golfers. Economic idea: Moral hazard occurs when one party to a contractual relationship has incentives to behave in a way that harm the second party, and when the first party’s behavior cannot be observed. When he fails to perform the way the second party wants him to, he is said to shirk. Examples: insurance, agricultural labor, committee members or participants in group projects. The trick is to come up with a contract that provides the first party with the proper incentives. Economic idea: Market failure • Market failure occurs when voluntary exchange does not lead resources to be used in the way that creates the most value. In theory (a critical qualifier), government can restrict or redirect resource use to enhance overall social welfare. Two of the three types of market failure • Externalities occur when the effects of a transaction spill over and affect nonparticipants. (Example: network externality, typically positive.) • Public goods are goods with two features: • (1) They are nonrivalrous, meaning consumption by one person doesn’t leave less available for others. • (2) They are nonexcludable, meaning nonpayers can’t be excluded from consumption. They are thus subject to free-riding, an unwillingness to pay the full value of the good. • Public goods, for these reasons, are under-provided by the market. The Cincinnati Stadium Deals – Paul Brown Stadium • Paul Brown Stadium • The process • 1993 – Mike Brown is paying $2,500,000 annually in rent to be the second tenant at Riverfront Stadium. He gets no income from parking or advertising, while many teams got 100 percent of it. He threatens for the first time to move the Bengals. • 1994 – The Bengals are revealed to have the worst stadium revenue deal of all NFL teams, at $53,000,000 annually. (Dallas, a luxury-box pioneer, led with $101,000,000.) Brown agrees to stay if the Bengals have a new stadium in place by 2000. • 1995 and 1996, throughout – Mike Brown threatens to move the Bengals, especially to Baltimore. • June 30, 1995: At seven minutes until midnight, Brown’s deadline for Cincinnati to reach a decision, the City Council passes a deal for a new stadium to be financed by a one-cent increase in the sales tax, later changed to a half-cent in 1996. Paul Brown Stadium (continued) • The process (continued) • March, 1996: After public protest, a referendum is held on a half-cent increase, combined with a property-tax rollback, to fund two stadiums for $544,000,000, an estimate that would prove to be ridiculously low. With Art Modell’s help, referendum passes with 60 percent approval. • 1997: A new dispute arises over city-owned land in the middle of the proposed stadium site. City council refuses to transfer the land until Brown negotiates a better deal regarding surrounding construction rights. Brown says cough the land up by 1/31/98 or he is gone. • Feb. 1, 1998, 1:00 AM: The land is transferred. • Mid-2000: Lease changed to eliminate county responsibility for ticket shortfalls, but requiring county to pick up Bengals federal tax obligations. • August, 2000: After huge cost overruns, stadium opens. • Summer, 2004: Hamilton County sues Bengals and NFL for unfair lease. Paul Brown Stadium (continued) • The contract: • - County pays all maintenance other than on game day. • - County pays for new technology as soon as 14 other stadiums get it, or 7 get it with public funds. • - Bengals get all concession and advertising revenue. • - Bengals can veto events and get 50% of revenue from any other events (concerts, high- school games, etc.) Paul Brown Stadium (continued) • The costs • - Bengals contributed $25 million (through seat licenses) of $455 million construction expense. • - From 2009-2026 (with ten-year Bengals option), Bengals will pay no rent. • - By overseeing construction, Hamilton County brought about $50 million on cost overruns. • - Sales-tax revenue less than expected, perhaps forcing a choice between funding stadium from general revenues or canceling the property-tax cut that was given in exchange for the sales-tax increase. Projected $8 million (or more) shortfall by 2007. • Sales tax has already been extended 16 years longer than originally planned. Great American Ballpark • Naming rights: $75,000,000 over thirty years. • Estimated cost: $361 million, after eliminating upper-deck sunscreen, front-entrance canopy, cheaper counter tops in the luxury boxes and other cost-cutting measures, as well as re- tendering some construction contracts. It was $11 million under budget, as opposed to $51 million over budget for Paul Brown Stadium. Public subsidy was $300 million. • But Reds paid for any cost overruns, which were then unsurprisingly few. Why can cities be expected to overpay? • Entry limitation gives franchises market power. • Winner’s curse problem – without a strategy to correct for the problem, the party that ones an auction for an asset of unknown value is likely to be the one that most overestimated its value. The economic impact of mega-events • Direct benefit: People come to town and spend on hotels, restaurants, etc. • Direct benefit: Multiplier effects. • Indirect benefit: For Super Bowl in particular, corporate movers and shakers get a chance to scout out the city as a business location. Reasons for doubt: • Cost: From 1995-2003, cities spent $6.4 billion on stadium construction and refurbishment. Reliant Stadium in Houston, for example, cost over $400 million. Mega-events also require extra public services, which are often not included in the calculations. • Crowding out: The opportunity cost of a mega-event guest is that some other guest might not be using the hotel room and attending the restaurants. People who might otherwise visit a city for some other reason will refuse to do so when the Super Bowl is in town. • Substitutions: Much of the income is from local residents, who are not spending it elsewhere in the local economy. • Leakage: Many of the employment and spending effects to some extent benefit people outside the area. Source: Robert A. Baade and Victor A. Matheson, “Super Bowl or Super (Hyper)Bole: Assessing the Economic Impact of America’s Premier Sports Event” The evidence • Phil Porter (1999) - Look at cities that host Super Bowl. Compare retail sales and sales taxes to what those cities had a year earlier. Finding: no detectable effect. - Hotel rental rates are the same, although room prices are higher. • Baade and Matheson (2003) - Use a regression to measure the relation between income growth in a group of host cities as a function of other variables (new business hiring, e.g.) and whether or not the city hosted a mega-event. Finding: At most, benefits are 25 percent of what the NFL claims. • “Thanks to Super Bowl XXXIII, there was a $670 million increase in taxable sales in South Florida compared to the equivalent January-February period in 1998.” – NFL, 1999. • But nominal sales taxes grow anyway because of population, inflation and expected economic growth. According to one study (Baade and Matheson 2005), accounting for these lowers impact of 1998 Super Bowl to $37 million. Source: http://www.argmax.com/mt_blog/archive/000269.php. “Wright State University will be a catalyst for educational excellence in the Miami Valley, meeting the need for an educated citizenry dedicated to lifelong learning and service. To those ends, as a metropolitan university, Wright State will provide: access to scholarship and learning; economic and technological development; leadership in health, education, and human services; cultural enhancement, and international understanding while fostering collegial involvement and responsibility for continuous improvement of education and research.” - The WSU mission statement Multi-Sport Male Athletes Multi-Sport Female Athletes I AM a DIE-HARD Clemson Alum and fan. I love everything about the University. In the issue of football, I've always been against firing any of our coaches because changes bring a lot of instability; case in point, Vince Dooley at Georgia, Barry Switzer at Oklahoma, and of course, Danny Ford at CU. But enough is enough! I've supported Coach West since he first became our coach, but I haven't seen any signs of improvement or that he is the man to take CU football BACK TO THE TOP. I'm sorry to say it. I didn't even realize that we are ONLY VERY few wins above .500. I guess I've been fooled by the fact that we have been going to bowl games (AND LOSING). I think this year is JUDGMENT YEAR for Coach West. Mediocrity is unacceptable at Clemson University. Speaking of mediocrity, our chicken "friends," who at one time made fun of us for scheduling Ball State, seemed to have shown once again just how pathetic they are. After glancing at my brand new issue of Sporting News, it caught my eye that those u SCum chickens have scheduled TWO (2, I say) Mid-American teams this year. Well, I guess even when Kentucky and Vandy have gained a leg up on you, chickens have no choice but to RETREAT to a more comforting area by TRYING (and I do mean TRYING) to beat up on Mid-American teams; break a chicken leg. CLEMSON U owns U SCum chickens! Go Tigers!! Tiger (18.104.22.168) USA - Monday, June 22, 1998 at 17:57:30 (EDT) Unidentified poster named “Tiger,” on a Clemson University sports web site. • “Education.” - University of Chicago president Robert Hutchins, when asked what the university could provide to excite students after it dropped the football team. • “A college racing stable makes as much sense as college football. The jockey could carry the college colors; the students could cheer; the alumni could bet; and the horse wouldn’t have to pass a history test.” - Hutchins again, when asked to assess the consistency of intercollegiate football with the university’s mission. “The NCAA television plan on its face constitutes a restraint upon the operation of a free market, and the District Court's findings establish that the plan has operated to raise price and reduce output, both of which are unresponsive to consumer preference. Under the Rule of Reason, these hallmarks of anticompetitive behavior place upon the NCAA a heavy burden of establishing an affirmative defense that competitively justifies this apparent deviation from the operations of a free market. The NCAA's argument that its television plan can have no significant anticompetitive effect since it has no market power must be rejected.” - NCAA v. Board of Regents of U. of Oklahoma, 1984, 468 U.S. 85; 104 S. Ct. 2948 . "It is clear from the evidence that were it not for the NCAA controls, many more college football games would be televised. This is particularly true at the local level. Because of NCAA controls, local stations are often unable to televise games which they would like to, even when the games are not being televised at the network level. The circumstances which would allow so-called exception telecasts arise infrequently for many schools, and the evidence is clear that local broadcasts of college football would occur far more frequently were it not for the NCAA controls. This is not a surprising result. Indeed, this horizontal agreement to limit the availability of games to potential broadcasters is the very essence of NCAA's agreements with the networks. The evidence establishes the fact that the networks are actually paying the large fees because the NCAA agrees to limit production. If the NCAA would not agree to limit production, the networks would not pay so large a fee. Because NCAA limits production, the networks need not fear that their broadcasts will have to compete head-to-head with other college football telecasts, either on the other networks or on various local stations. Therefore, the Court concludes that the membership of NCAA has agreed to limit production to a level far below that which would occur in a free market situation." - NCAA v. Regents of OU. We find that the problems of big-time college sports have grown rather than diminished. The most glaring elements of the problems outlined in this report - academic transgressions, a financial arms race, and commercialization - are all evidence of the widening chasm between higher education's ideals and big-time college sports. Clearly, more NCAA rules are not the means to restoring the balance between athletics and academics on our nation's campuses. Instead, the Commission proposes a new "one- plus-three" model for these new times - a Coalition of Presidents, directed toward an agenda of academic reform, de-escalation of the athletics arms race, and de-emphasis of the commercialization of intercollegiate athletics. - Knight Foundation Commission on Intercollegiate Athletics, June 2001 Problems associated with big-time college athletics • Admissions standards • Displacement of other students • Low graduation rates • Academic dishonesty – Cheating on assignments – Easy courses • Point shaving. Adjusted Admission Advantages GPA Bottom Third of Class Athlete SAT Divergence Fig. 2.6b – Division III Athlete 2.6a Ivy League Athlete Fig. 2.6c Division IA Private Athlete Fig. 2.6d Division IA Public Athlete Recent efforts to reform admission standards • 1986: Proposition 48 required that admitted athletes have 2.0 high-school GPA and at least 700 (15) on SAT (ACT). • 1992: In response to protests, Proposition 16 allows some tradeoffs between standardized-test scores and GPA. • 1999: In Cureton et al. v. NCAA, a federal district judge holds that Prop. 16 violates federal civil-rights laws on “disparate impact” grounds. • Although decision is later overturned on procedural grounds, a federal appeals court without overturning the reasoning that led to the decision. In 2002, the NCAA drops any minimum SAT score requirement. Displacement • At selective co-ed liberal-arts schools in one study, athletes are one-third of male and one- fifth of female students. • At same schools walk-ons are almost nonexistent. • According to one study in Social Science Quarterly, to be an athlete is worth about 200 SAT points at five elite private colleges. (For comparison, being a legacy is worth 160 points, being black is worth 230 points, being Hispanic is worth 185 points, and being Asian is worth -50 points. Displacement – Graduation rates of athletes and other students, 1996-97 freshman cohort • Overall: 59% • Athletes: 60% overall, 70% female, 55% male. • Basketball: 44% overall, 52% female, 41% male. • Football: 54% Six-Year Graduation Rate Academic dishonesty - cheating • “In the two years I was there, I never did anything. The coaches knew. Everybody knew. We used to make jokes about it. ... I would go over there some nights and get, like, four papers done. The coaches would be laughing about it.” - Russ Archambault, Minnesota basketball player, in The Cincinnati Enquirer, 3/11/99 Academic dishonesty – joke classes. Excerpts from final exam, Jim Harrick Jr.'s “Coaching Principles and Strategies of Basketball” class, Fall 2001, University of Georgia. • 1. How many goals are on a basketball court? • a. 1 • b. 2 • c. 3 • d. 4 • 2. How many players are allowed to play at one time on any one team in a regulation game? • a. 2 • b. 3 • c. 4 • d. 5 The Harrick final (continued) • 3. In what league to (sic) the Georgia Bulldogs compete? • a. ACC • b. Big Ten • c. SEC • d. Pac 10 • 5. How many halves are in a college basketball game? • a. 1 • b. 2 • c. 3 • d. 4 The Harrick final (continued) • 8. How many points does a 3-point field goal account for in a Basketball Game? • a. 1 • b. 2 • c. 3 • d. 4 • 11. What is the name of the exam which all high school seniors in the State of Georgia must pass? • a. Eye Exam • b. How Do The Grits Taste Exam • c. Bug Control Exam • d. Georgia Exit Exam Given substantial reputational costs, why have athletics? • Alumni donations (McCormick and Tinsley, “Athletics and Academics…”) • To distract students while research is emphasized (Sperber) • To promote undergraduate enrollment (Osborne; McCormick and Tinsley, “Athletics vs. Academics…”) Economic idea - signaling • Signaling occurs when you have a desirable characteristic that is unobservable to someone who values it. You can signal when your characteristic can be proven to the observer by engaging in an activity that is too costly for someone without the characteristic You might be a potential high-quality employee, in contrast to other low-quality applicants, but the employer can’t tell which you are just from the qualifications he can observe. But if only high-quality applicants can graduate from college, you may incur the expense of a degree, even if what you learn has no relevance for the job for which you are applying. McCormick and Tinsley, “Athletics and Academics…” • Colleges provide two types of value to students: • Production (human) capital: Improvement in students’ skills enable them to earn more money after they graduate. • Consumption capital – College is enjoyable, and the memories of these experiences provide utility over the alum’s entire life. • Once a student graduates, his college can still make his degree valuable by signaling. The need to signal occurs when some valuable attribute of a seller is unobservable, but there is some costly procedure that he can pay for that can differentiate between high-value and low-value sellers. In this case, athletics are said to be a way of signaling that the university intends to continue maintaining Clemson academic quality, and hence a way to encourage alums to continue to donate. McCormick and Tinsley, “Athletics and Academics…” (continued) • Test of above hypotheses: • Regress per-alum contributions to Clemson U. athletic programs in each S. Carolina county. • Findings: Contributions are: - positively and significantly correlated with income (because richer people give more); - positively and significantly correlated with number of farms in county (because Clemson is first and foremost an agricultural university, meaning that farmers have more incentive to preserve the value of the Clemson name); McCormick and Tinsley, “Athletics and Academics…” (findings, continued) • Contributions are: - negatively and significantly correlated with population; small towns don’t need the signal value of a college degree as much; - positively and significantly correlated with athletic contributions. - The last finding suggests that academics and athletics are complements, not substitutes. People are willing to contribute to both of them simultaneously. Sperber: “Beer and Circus” • Thesis: major research universities value research. They are hostile to undergraduate teaching, which they view as a distraction, but need the tuition money, especially as state funding is declining. Big-time athletics is a distraction that keeps the tuition money rolling in while allowing the faculty to put out second-rate teaching without student complaint, thus enabling faculty to concentrate on research. Sperber’s evidence that undergraduate education is de- emphasized at universities with athletics, especially, Big State Universities • Star professors get lower teaching “loads.” • Despite a huge surplus of Ph.D.s in most fields, more and more universities create and promote doctoral programs. • Many courses, especially ones with many undergraduates, are mostly taught by adjuncts, “gypsy faculty” and graduate students. • Principles courses, the most basic and important knowledge in any field, are the most likely to be taught in huge sections with little faculty contact. • At many Big State Universities (BSUs), high grades are traded for low expectations. • Small honors programs are emphasized in university publicity, when in principle this is what should be offered to all undergraduates. “The Honors Program exists to serve the needs of capable, hardworking, ambitious students who want to make the most of their undergraduate education. In addition to offering Honors classes, the Honors Program provides several other services for Wright State's outstanding students. You may be surprised to learn of some of the things the Honors Program can do for you. - Small classes - Selective enrollment - Priority registration - Student lounge and study area - Special advising - Strong peer group - Honors housing - Opportunities for travel, leadership development, and community service” From the WSU Honors Program Web site. How to distract undergraduates (Sperber) • College sports provides utility via game attendance, watching games on television, celebrating after victories. Many students in Sperber’s surveys report that sports was the best part of college at BSUs. • Alcohol is an independent distraction in its own right, and interacts with sports and the Greek system. - 80% of fraternity members “binge drink” at least occasionally and they average 20.3 drinks/week in one study. - There are 94 liquor stores within one mile of the University of Iowa campus. - In regression analysis by others, best predictors of alcohol use and abuse in campus are big dorms, the size of the Greek community and Division I status. “Party, Party, Party [at LSU]: Nearly every [student] organization on campus hosts parties throughout the year…[For football weekends] all of the campus streets are closed to accommodate the massive number of people tailgating, drinking, and partying…Such frenetic activity and enthusiasm extend to all aspects of student life at LSU, and often preclude more serious activity like studying. What is a typical weekend schedule? Friday – drink, fall asleep in someone else’s bathtub; Saturday – leave bathtub, watch the game, drink; Sunday – drink lightly.” - The Insider’s Guide to the Colleges, 2000 edition. “Every semester here I have encountered a professor who uses an overhead projector and writes continuously on it for the whole class, every class. No questions allowed, no eye contact made. I always feel compelled to ask the profs why they do not simply hand out all the notes they’re going to write on the overhead at the beginning of the semester, and just let the students show up for the tests? Not one of these instructors has ever answered the question. They just walk away from me.” - One Indiana University student’s response to Prof. Sperber’s survey. Top Party Schools, 2003, Princeton Review • Colorado • Wisconsin • Indiana • Illinois • Washington and Lee University • Texas-Austin • The University of the South • DePauw University • Saint Bonaventure • Florida McCormick and Tinsley (Athletics vs. Academics) • Question: Is big-time college athletics negatively related to academic quality? - Test: Regress SAT scores of incoming freshmen (measure of student quality) on membership in big-time athletic conferences and on other measures of school quality. • Results: • Tuition is positively and significantly related to SAT scores. • Professors’ salary is positively and significantly related. • Age of the school is positively and significantly related. • University endowment per enrolled student is positively and significantly related. • Student/faculty ratio is negatively related, but only marginally significantly. • Membership in a big-time athletic conference is positively and significantly related. Conclusion: While the market for universities appears to respond to consumer desires, athletics also seems to perform an advertising function. Athletic effort and academic quality are friends, not foes. Osborne, “Motivating College Athletics • Question: What is the relation between athletic spending and school’s attractiveness? Source: http://www.ncaa.org/library/research/i_ii_rev_exp/2002/d1_d2_revenues_expenses.pdf. Top 20 D-I schools, athletic spending per undergraduate student, 2002 Temple Hampton Vanderbilt Stanford Syracuse Lafayette Tulsa Colgate Wofford Virginia Wake Forest Holy Cross Furman Richmond Southern Tennessee Oregon St. Army Northwestern Miami (FL) Bottom twenty D-I schools, athletic spending per undergraduate S. Alabama Illinois-Chicago Long Beach St. Cal-Irvine CSU-Sacramento Florida International Florida Atlantic Southwest Texas St. Central Michigan Penn Wisconsin-Milwaukee Chicago St. Texas-Arlington IUPUI Cal St.-Fullerton UC-Santa Barbara Cornell UT-San Antonio SE Louisiana St. Bonaventure Osborne • Test: Regress tuition per student (a measure of ability to pass price along) on several university features: athletic, teaching and school’s own research spending. • Result: It is positively and significantly related to teaching and athletic spending, not significantly related to research spending. • Test: Regress SAT scores of applicants on spending measures, joint effect of teaching and research spending and public-university status. • Result: Teaching, research and athletic spending are positive and significant. But the joint effect of teaching and research is negative, suggesting that more spending on research, while it raises SAT scores by itself, lowers the effectiveness of teaching. Implication: research effort comes at the expense of teaching. Economic idea: cartel A cartel consists of independent producers who cooperate to restrain output or increase price rather than compete. Examples: OPEC, mafia garbage contracting in New York City. Cartels are subject to defections because of the prisoners’ dilemma problem. This problem occurs when breaking an agreement is profitable for each party even if they would both be better off if they both stuck to the agreement. Does the NCAA restrict output or price? • Brown (1996, on reading list in section IVC) estimates that a premium college football player generated between $400,000-$600,000 in 1988-89. • The same author estimates elsewhere that in 2003-4 Jameer Nelson generated perhaps $1,000,000 in revenue for St. Joseph’s University. How does the NCAA police its cartel (DeBrock and Hendricks)? Assumptions: • Individual schools make more money from better teams. • But the total revenue pool increases when there is more competitive balance. DeBrock and Hendricks (continued) • Implications of previous assumptions: • (1) The NCAA should admit more members up to a point, but then place entry barriers. The more members there are, the more unbalanced competition becomes beyond a certain point. • (2) In addition, once the number of members has been decided on the NCAA will enact minimum quality standards and maximum quality standards. DeBrock and Hendricks (continued) • To achieve (1), the NCAA creates separate divisions and requires more investment in college athletics to move up into a higher division. • To achieve (2), the NCAA limits scholarships and coaching staff. Are college athletes exploited? In economics, the only way to interpret this question is to ask whether their pay is less than their marginal product. Outside of economics, one might ask whether student-athletes are led to make bad choices because they are deceived by college athletic promises. Brown (athletes’ MRPs) • Question 1: What is the MRP of a premium college football player? • To answer, regress a team’s revenues from ticket sales, TV and radio, donations and miscellaneous sources on number of premium players (which the author defines as players drafted by the NFL), on the size of the city in which it is located, on its past AP poll ranking and on the ranking that season of its opponents. • Opposition quality, NFL picks and the team’s own ranking in previous years are statistically significant. A premium player generates between $400,000-$600,000 in annual revenue. • His compensation consists of tuition, books and the increase in his value acquired from the human and physical capital he acquires while he is there. Brown (continued) • Another finding is that the number of premium players obtained is positively related to the percentage of its team admissions that are “special authority” -- i.e. lower- standards -- admissions, and negatively related to team high-school GPA. • Admitting one player (without yet knowing whether he will be premium) on special authority increases revenue by $90,000-$126,000. • Decreasing the team’s high-school GPA requirements by 0.21 increases revenues between $800,000-$1,120,000. • Inference: colleges have a clear incentive to admit players with less chance of doing well in school in order to improve team revenues. But what about athletics overall and student prospects? (Long and Caudill) • Athletics and future earnings potential: • On the one hand, college athletics may divert time in college from classroom-based human- capital acquisition, due to demands of practice and games. • On the other hand, college athletics provides some human capital on its own, e.g. enhancing self-discipline, teamwork. • In addition, even if college athletics does not provide this human capital, it may serve as a costly signal of greater existing possession of the above traits. Long and Caudill (continued) • Test: Regress annual income on various demographic characteristics, extent of education, college GPA, self- reported measures of ambition and goals, and whether or not student received a varsity letter in athletics. • Result: For males, earnings positively and significantly associated with athletics, being married, having children, working for a big company, college grades, having a graduate degree, and personal characteristics. They are negatively related to working part-time. Black males also earn less than others. Athletics increases income by about 4%. For females, athletics is statistically insignificant. The other variables have the same effect, except that black females earn higher wages than non-black females after standardizing for other characteristics. Long and Caudill (continued) • With respect to graduation probability, athletics, high-school grades, ACT scores, parental income and education and personal characteristics are positively and significantly related. For females, athletics is again significant in addition to the other variables that are statistically significant for men. • Conclusion: for athletics overall, it is hard to argue that exploitation exists in terms of the university’s athletic goals distracting students from improving their earnings prospects. Theories of international trade • Comparative-advantage theory says that nations have different levels of technology or different resource bases. Each nation maximizes its prosperity by specializing in what they do relatively well. • Product-lifecycle theory says that all advanced nations have production structures that are roughly the same, and all pass through the same stages on the way to becoming modern. Comparative advantage in the Olympics (Tcha and Pershin) • Over three Olympics, define six sport groups: swimming, track and field, weightlifting, ball games, gymnastics, other. • Specialization is defined as the percentage of medals a country wins in one group divided by the total medals available in that group. Top performers overall Swimming Track Weights Ball Games Costa Rica Bahamas Iran Ghana Hong Kong Ethiopia Turkey India Iceland Jamaica Israel Indonesia Ireland Namibia Greece Argentina New Zealand Zambia Algeria Lithuania Gymnastics Ukraine Belarus China Japan Greece Tcha and Pershin (continued) • Result (1) Comparative advantage in Olympic success. Left-hand variable is relative specialization in medals. Right- hand variables are land mass, coast length, altitude, GDP, GDP per capita, and dummy variables for former communist countries, Asia and Africa. • Swimming: only Asia dummy is significant. • Track: Land mass, altitude, temperature, per capita income and Africa dummy are positive and significant. Coastline is negative and significant. • Weights: Temperature, GDP, Asia and Africa are positive and significant. Altitude, GDP per capita, communist, Asian and African dummies are negative and significant. • Ball games: Population is positive and significant. • Gymnastics: Communist dummy is positive and significant. Tcha and Pershin (continued) • Result (2): Richer nations have less variance in their specialization than poor ones do. Specifically, the variance in comparative advantage across sports in a given country is a negative and significant function of its per capita GDP. Poorer nations specialize in only a small number of sports, rich countries spread out their success more. Osborne, “Baseball’s International…” • Question: Can comparative-advantage or product-lifecycle theory explain the statistical productivity patterns of different countries that contribute to the major leagues? • Statistical problem: unit of analysis. Should all players be equally weighted, or should total statistical productivity for a country be simply added together? Foreign-born players, 1950, 1970, 2002 1950 1970 2002 Aruba 0 0 2 Australia 0 0 3 Canada 6 7 10 Colombia 0 0 3 Cuba 9 24 11 Dom. Republic 0 16 74 Japan 0 0 11 Korea 0 0 2 Mexico 2 6 18 Neth. Antilles 0 0 2 Nicaragua 0 0 2 Panama 0 8 7 Puerto Rico 1 23 38 Venezuela 1 11 38 U.S. Virgin Islands 0 3 1 San Pedro de Macoris, 1962-2002 Positions Games Right-handed pitchers 2053 Left-handed pitchers 73 First Base 1071 Second base 4926 Shortstop 5644 Third base 1791 Outfield 6075 Catcher 79 Designated hitter 1546 Measuring Specialization – A Country’s Player’s At-Bats/Innings Pitched as Measure Test 1: Add all player productivity together. A player with 3000 AB will therefore contribute much more to a country’s total productivity than a player with 100 career AB. What is produced, in international-trade terms, is therefore major-league statistical output. Test 2: Assume that what is produced is major- league players, regardless of career length. Take each player’s productivity as a separate unweighted observation. Relative at-bats/innings pitched 1940-59 1960-79 1980-2002 Overall 3.826486 3.77804 3.911677 Dom. Rep. 1.986451 1.358929 Mexico 1.352569 0.263868 Venezuela 13.31242 2.002334 Puerto Rico 1.112291 3.210672 3.004303 Cuba 0.991405 1.654358 1.283594 Canada 0.530192 0.201441 0.387893 Osborne - hitting for average and power • Because nations do not generally stay on the same side of 1 in their relative production of batting average and HR/AB, the conclusion is that these are not skills governed by comparative advantage. • Only possible exception is Puerto Rico batting average, but overall comparative- advantage model performs poorly by these measures, in this specification. Osborne (continued) • But by method 2, in which each player is analyzed separately, results are different. • Using a statistical technique called analysis of variance, it is shown that there are sustained country differences in average hitting, and changes over time in power hitting. The latter is a skill developed later, as product-lifecycle theory would predict. • Specifically, Puerto Rico and Venezuela consistently produce more hits than expected, and Canada and Mexico produce fewer. Every nation except Canada produces more HR/AB from one interval to the next. Osborne (continued) – specialization within pitching • Test 1 : specialization in handedness. No pattern is shown. The only strange result is that the Dom. Rep. produces surprisingly few left-handers between 1980- 2002. • Specialization in strikeouts and walks: again, analysis of variance shows no detectable pattern. • Same holds for Games started/Total appearances, a measure of specialization in starting. • Conclusion: The differences in human capital required to produce different types of pitching do not appear to be significant. Table 8 Lefties and righties Dom. Rep. Mexico Venezuela P.R. Cuba Canada 1940-59 7/31 4/19 (.226) (.211) 1960-79 3/20 1/14* 6/16 3/22 6/25 (.150) (.071) (.375) (.136) (.240) 1980-02 22/136** 26/41* 11/41 9/36 4/16 10/30 (.162) (.366) (.268) (.250) (.250) (.333) Note: * denotes statistical significance at ten-percent level. ** denotes statistical significance at one-percent level. Specialization by position • Test: Use multinomial distribution to see if distribution of players is statistically different from random chance. Table 10 Multinomial Х2 components, fielding Cuba Pitchers 1B/3B 2B/SS OF C DH Total 1940-59 1.4 0.233 .305 .001 .343 N/A 2.282 (n = 56) 1960-79 .694 .601 7.079(+) .086 .006 .624 9.090 (n = 52) 1980-02 .75 .004 1.277 .297 .355 .243 2.926 (n = 30) Puerto Rico Pitchers 1B/3B 2B/SS OF C DH Total 1940-59 .167 .25 .694 .375 .014 N/A 1.500 (n = 15) 1960-79 5.143(-) 1.052 9.163(+) 3.665(+) 0.917 .030 29.970*** (n = 70) 1980-02 9.345(-) 1.792(-) 18.608(+) .004 12.330(+) 0.747 31.729*** (n = 149) Canada Pitchers 1B/3B 2B/SS OF C DH Total 1940-59 3.003(+) 1.633(-) 4.800(-) 0.450 0.067 N/A 9.953* (n = 32) 1960-79 10.548(+) .706 1.676 3.841(-) .852 .396 18.017*** (n = 33) 1980-02 5.518(+) 4.281(-) 2.251(-) .114 .066 .019 12.249** (n = 49) Mexico Pitchers 1B/3B 2B/SS OF C DH Total 1960-79 .236 .063 .595 2.442(-) .602 .001 3.939 (n = 26) 1980-02 7.014(+) .092 1.049 6.776(-) 1.400 .585 16.966*** (n = 64) Dominican Republic Pitchers 1B/3B 2B/SS OF C DH Total 1960-79 1.329 .323 6.190(+) .708 1.282 .708 10.540* (n = 59) 1980-2002 .918 14.909(-)34.197(+) 3.472(-) .137 4.989(+) 58.622*** (n = 306) Venezuela Pitchers 1B/3B 2B/SS OF C DH Total 1960-79 1.376 .002 4.960(+) .089 .198 .252 6.877 (n = 21) 1980-02 .229 2.284(-) 17.329(+) 3.569(-) 4.097(+) 4.158(-) 31.666*** (n = 126) Positional specialization patterns • The Dominican Republic and Venezuela produce middle infielders. • Puerto Rico and Venezuela produce catchers. • Canada produces pitchers. • Puerto Rico produces outfielders. Osborne (conclusions) • The pattern of specialization in pitching versus hitting clearly conforms to a comparative-advantage interpretation, as does specialization in fielding positions. • Specialization within pitching and hitting is not detectable, although power hitting is a late-stage industry in the product-lifecycle sense. Economic idea: An efficient market occurs when profits (or expected profits) have been eliminated by competition. Efficient financial markets – e.g., stock markets, currency markets – occur when no trading strategy offers expected profits over any period of time. This is a question of information. Do trading markets collectively reveal all available information? We must distinguish between perfect information, which eliminates all uncertainty beforehand, and symmetric information, which allows uncertainty, but where all traders, observing the market price, have the same expected probability of making money. Symmetric information does not eliminate uncertainty, but it means that all available information is revealed via the asset’s price. Thus, no strategy can expect to earn profits. Economic idea: Rationality. Rational economic agents have consistent preferences, and act in accordance with those preferences, given those constraints. Most propositions in economics about choices people make and the effects of various kinds of economic policy, assume that decision-makers are rational. When they are irrational in a systematic way, markets need not be efficient. Example of irrationality: the magical-thinking prisoners’ dilemma • In a prisoners’ dilemma game, when told that partner has defected in advance, 97% of players defect. • When told that partner has cooperated in advance, 16% cooperate. • When told that partner has already chosen strategy, but not told what strategy is, more people (37%) choose cooperate. • Often interpreted as a belief in “magical thinking” – that a decision to cooperate could cause the other player to choose cooperate, even though he has already made his choice. Test 1 of streakiness: Does the probability of a made shot vary with the fate of the previous shot? • Mathematically, is Pr(Hitt|Hitt-1) > Pr(Hitt|Misst-1), given player’s general probability of making a shot? • Test: Use last three shots. Compare probability of a hit given 0,1,2 or 3 hits in the last three shots. If there is streakiness then for any player the probability should be increasing in the number of previous hits. • Only for one player out of eight is there any such correlation. Test 2 of streakiness: how many runs of consecutive misses or makes are there for each player? • A run is a streak of identical results. For example, HHHMMMMH contains three runs; HMHMHHMM contains six. Streakiness would imply relatively few runs. • There is no significant difference between actual and expected number of runs for eight players over 48 home games. One has more than expected, i.e. the opposite of streakiness. But, perhaps the lack of correlation is due to hot players taking harder shots, or being more aggressively defensed. • Test 1: Look for streakiness in free-throw shooting. • Result: For the Boston Celtics over two seasons no player has a statistically significant difference between his chance of making a second free throw given that he made or missed the prior one. • Test 2: Let college basketball players take shots (and bet on the results) from a single spot on the floor. There is again no evidence of the results of prior shots affecting chances of making the current one. • But players mistakenly believe they can predict results – i.e., they think they’re hot when they’re not. Players can bet a larger amount when they’re more confident they’ll make shot and less otherwise. Only 5/26 had a statistically sig. relation between bets and outcomes, and one player’s relationship was negative. Overall, there was no relation. But the way both players and observers on the sidelines bet is highly related to the outcome of the previous shot. Conclusion: there is no hot hand, but people often mistakenly think they are observing one. A clear sign of a sustained consistent mistake, which is a sign of irrational behavior. • Irrationality – college names Sports betting offers a test of the efficient markets hypothesis. The price of a stock or currency is equivalent to the odd on or the point spread of a game. If betting markets are efficient, no betting strategy should yield expected profits. This is a possible result even with irrationality, as long as some people are less irrational (even perfectly rational) and can take advantage of the mistakes of those who aren’t. Preliminary question: Do independent ratings of teams or individuals reflect their true strength? Answer: only imperfectly. NCAA Men’s Tournament Records By Seed (1985-2004) RECORD WIN % SEED 1 328-94 .777 2 238-103 .698 3 172-105 .621 4 146-106 .579 5 128-108 .542 6 145-106 .578 7 92-108 .460 8 82-107 .434 9 63-107 .371 10 70-107 .395 11 46-106 .303 12 44-104 .297 13 21-83 .202 14 16-84 16 15 4-85 .045 16 0-84 .000 Source: http://www.tournamentfacts.com/id19.htm Boulier and Stickler – testing the ability of tennis seedings to predict match outcomes • First: Use regression to create expected probability of the higher seed winning. If information were perfect higher seeds would always win. If information is symmetric then the probability that a higher seed wins is always greater than 0.5, but declines as the higher seed is less and less strong. For example, the estimated probability that a 1 should beat a 16 is higher than the estimated chance that a 5 should beat a 12. Boulier and Steckler - Overall winning percentage, 1985-1995, seeds in Grand Slam tennis tournaments (rankings among seeds in parentheses) Men Women 1 .756 (#2) .891 (#1) 2 .810 (#1) .810 (#2) 3 .705 (#3) .615 (#4) 4 .674 (#4) .565 (#5) 5 .614 (#5) .632 (#3) 6 .600 (#6) .532 (#7) 7 .500 (#10) .544 (#6) 8 .487 (#11) .491 (#8) 9 .577 (#8) .459 (#9) 10 .452 (#12) .411 (#10) 11 .541 (#9) .333 (#12) 12 .594 (#7) .353 (#11) 13 .258 (#15) .276 (#13) 14 .375 (#14) .231 (#15) 15 .421 (#13) .217 (#16) 16 .150 (#17) .273 (#14) Unseeded .163 (#16) .111 (#17) Appearances (out of 44) in round of 16 by seeded tennis players, 1985-1995 Men’s Women’s 1 38 (#1) 43 (#1) 2 36 (#2) 32 (#2) 3 33 (#4) 36 (#4) 4 34 (#3) 38 (#3) 5 19 (#10) 29 (#6) 6 22 (#8) 29 (#6) 7 23 (#7) 32 (#5) 8 20 (#9) 29 (#6) 9 24 (#5) 20 (#12) 10 19 (#10) 22 (#10) 11 18 (#13) 26 (#9) 12 16 (#15) 22 (#10) 13 24 (#5) 21 (#14) 14 19 (#10) 20 (#12) 15 12 (#16) 18 (#15) 16 17 (#14) 16 (#16) Boulier and Stickler – A Brier score measures how close to perfection the estimate probabilities are. • Defined as: n = number of observations pi = estimated probability of higher seed winning di = 1 if higher seed wins, 0 if higher seed loses. Boulier and Stickler • 0 is thus a perfect Brier score. Actual Brier scores: • Women’s tennis 0.140 • Men’s tennis 0.160 • Women’s NCAA basketball: 0.170 • Men’s NCAA basketball: 0.180. • Conclusion: because of consistent errors in seedings as predictors of victory, they do not completely use available information. The basics of gambling markets • Football and basketball bets are placed against point spreads. In other words, you bet as to whether the favored team will win by at least a certain number of points. • Bookmakers generally adjust the line – the point spread against which you bet – to equalize the money bet on each side. • Bookmakers take a commission for every bet, so that bettors have to win roughly 52.5 percent of the time to break even. Zuber, Gandar and Bowers • Question: do profit opportunities exist in NFL betting markets? • Solution: regress actual winning margins on statistics available before the game is played. • Problem: For the model to be profitable it must not simply look backward, i.e. it must not simply conduct bets within the sample. Instead, out of sample tests must be conducted, where the model’s predictions are used to test games not included in the regression used to create the model. • Solution: come up with a predicted point spread for first half of 1983 season, then test it using games in the second half of season. Zuber, Gandar and Bowers (results) • Home team’s predicted victory margin = 1.547 + .047*Net yards rushing + .044*Net yards passing + .697*Net previous wins – 2.299*Net fumbles – 2.619*Net interceptions -.424*Net penalties - .217*Net pass play percentage -.319*Net number of rookies • All variables are statistically significant in the expected direction. • The winning percentage when the model has a prediction at least 0.5 points different from the betting line is 59 percent, which is economically profitable. Conclusion: the market for NFL betting is not efficient. Gandar, Dare, Brown and Zuber. • Question: Do markets improve in efficiency as trading proceeds? In other words, are profitable opportunities eliminated over the course of trading? • The strong version of the efficient-markets hypothesis (EMH) requires that prevailing prices always reflect all available information about asset prices, so that opening betting lines should never change. • But a weaker version of EMH contends that prices eventually incorporate all available information. • Implication: There should be no way to make money on closing betting lines, although there may be using opening lines. Gandar, Dare, Brown and Zuber (continued) • Finding 1: 80% of opening lines change. Of these, 40% move 0.5 points, 31% move 1 point, 29% move more than one point. Implication: strong EMH does not hold, unless these movements are random. • Are they? To test this, see whether closing lines better predict results than opening lines. Difference in forecast error, opening and closing lines, NBA, 1986- 1994 Season Avg. Opening Error Avg. Closing Error 1985-86 8.85 8.76 1986-87 9.16 9.06 1987-88 8.72 8.68 1988-89 8.99 8.92 1989-90 8.88 8.76 1990-91 8.93 8.87 1991-92 9.06 8.92 1992-93 9.22 9.21 1993-94 9.14 9.01 All seasons 9.00 8.92 Home team winning percentages versus line for different changes in opening and closing lines, NBA, 1985-1994 Line change Home team beats opening Home team Line beats closing line <-4 0.25 0.46 -3.5 0.37 0.43 -3 0.39 0.49 -2.5 0.43 0.54 -2 0.37 0.43 -1.5 0.43 0.49 -1 0.47 0.51 -0.5 0.48 0.5 0 0.51 0.51 +0.5 0.51 0.49 +1 0.53 0.49 +1.5 0.59 0.52 +2 0.58 0.48 +2.5 0.69 0.56 +3 0.52 0.36 +3.5 0.57 0.47 >+4 0.74 0.69 Gandar, Dare, Brown and Zuber (conclusions) • Closing lines are more accurate than opening ones. Thus, traders capitalize on available information to achieve more accurate price. • When opening line never moves, favored team covers point spread almost exactly 50% of time. • Collectively, when opening line changes in direction of home team by any amount, you win by betting on the home team against the opening line 54% of time. When the opening line changes against the home team, then if you bet against the home team on the opening line you win 55% of time. These are both statistically significant. • Conclusion: while this paper does not identify a strategy to win against the opening line, it indicates that such opportunities exist. Since closing lines do not present profitable opportunities, the market moves to efficiency. The weak version of the EMH is supported. NFL betting - Osborne • Basic approach: instead of regressing victory margins on team statistics, simply regress them on the bottom line – points scored and allowed in previous games by the two teams. Osborne (betting, continued) • Regress the margin of victory on average points scored and allowed by home and road team in previous games in that season, starting with week six. Use 1980-1990 to estimate results. • All four variables statistically significant, but the R2 (percentage of variance in margins explained by variance in points scored and allowed in previous games) is small, less than 10 percent. Osborne (betting, continued) • The same regression of the betting line on these measures of previous performance during the season explains over 70 percent of the variance in that variable. • Implication: bookmakers use this information extensively to set the line, but game results are still highly unpredictable. Osborne (betting, continued) • To test for profits (as usual) use the model’s predicted margins to try to predict the margin in games outside the sample period. • Betting with the predicted margin overall wins 51.2 percent of the time, which is not profitable. But betting with at least a 3-point difference between predicted margin and betting line wins 57.5 percent of the time, and betting with at least a 5-point difference wins 54.3 percent of the time. • In another version of the model (in which regression is updated every week), results are roughly the same. However, error in model’s predictions declines until bottoming out in roughly week 15. It then rises in weeks 16-17. • Implication: over the course of the season, bettors get better at predicting game results. However, in last two weeks of season many teams have been eliminated or clinched playoff spots by then. They engage in many experiments (e.g., trying out new players) and this makes games harder to predict. Biases in sports betting that have been found in the economic literature • The favorite/long shot bias: cognitive scientists have discovered that people systematically overestimate the chances of some low- probability events (e.g., plane crashes, winning the lottery). One sports example is the chance that a big underdog will win. Bettors in horse racing and football tend to over-bet on long shots and under- bet on favorites. • The referent bias: People tend to evaluate comparisons on the basis of the reference for comparison. They might give different answers, for example, to the question “By how much do you think the Dolphins will beat or lose to the Cowboys” then “By how much do you think the Cowboys will lose to or beat the Dolphins?” In each case the first team mentioned will be the focus, and people will either overestimate its strengths (if it is favored) or its weaknesses (if it is the underdog). If betting by one team’s fans dominate, then if it is favored the spread will be too high and if it is an underdog the predicted loss margin will also be too high.
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