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Sport Economics

by: Ms. Demario Johnston

Sport Economics MBAS 6310

Ms. Demario Johnston
GPA 3.66

Craig Depken Ii

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Craig Depken Ii
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This 106 page Class Notes was uploaded by Ms. Demario Johnston on Sunday October 25, 2015. The Class Notes belongs to MBAS 6310 at University of North Carolina - Charlotte taught by Craig Depken Ii in Fall. Since its upload, it has received 9 views. For similar materials see /class/228900/mbas-6310-university-of-north-carolina-charlotte in Smgt Sport Management at University of North Carolina - Charlotte.


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Date Created: 10/25/15
Sports on Campus MBAS 6310 Craig A Depken II UNC Charlotte Sports on Campus 7 p129 Athletics and the Academy l College athletics plays a vital role on some campuses n n h V Sanford Stadium Athens GAcap 92746 enrollment 34180 I and a less vital role on other campuses mg on Campus 7 p 229 History of College Sports I Sports is a big deal on many campuses today but that wasn t always the case I In the late 1800s and early 1900s sports on campus goes through a rough patch I Several sports were played in the earlier days rowing baseball swimming shooting track and football but they are generally smalltime and intermittent I In 1905 there were 10 deaths and more than 150 serious injuries in football I From 19001905 71 collegehigh school athletes killed in football I Columbia and other schools ban the game I President Teddy Roosevelt steps in and tells the Ivy League schools to come up with a compromise to save the game I The committee comes up with new rules to make the game more safe fonNard pass free catch line of scrimmage several other rules that saved the game I This process leads to the Intercollegiate Athletic Association In 1910 the name is changed to the NCAA Sports on Campus 7 p329 College Sports and its Detractors I There were a number of early detractors about the role of sports on campus In general there wereare two types of detractors gt Aesthetic Sport is low art and detracts valuable timeeffort from educational mission gt Economic Sports diverts limited money from academics to athletic department I Consider this headline from the April 17 1908 New York Times FOOTBALL NO VALUE IN LIFE TRAINING President Eliot of Harvard Says Game Does Not Develop Serviceable Qualities WOULD LIMIT CONTESTS Suggests Only Two Intercollegiate Games in Any One Sport Be Played During a Season l Eliot suggests students should only play sports they can play into old age He claims playing football is a waste of energy as you can t play when you are older than 23 I In 1929 the Carnegie Foundation Report is released gt Highly critical of intercollegiate competition gt Primarily an aesthetic criticism gt The report has little direct impact but does get people talking Sports on Campus 7 p429 Post WWII Experience I After VWVII the number of football teams grows from 220 to 600 l Open bidding for players destroys the amateur spirit I Many teams are openly funded by local businessmen Tulsa is funded by oil tycoons I There is an explosion of bowl games gt 4060 games each year in mid 1940s these days critics claim 30 games is too many gt Some interesting bowls Glass Bowl in Toledo the Vulcan Bowl in Birmingham The Yam Bowl in Dallas The Papoose Bowl in Okla City gt Little HardinSimmons plays in 3 bowl games in 1948 The Grape CA The Camellia FL and the Arkansas Shrine l Calls to ban bowls were unsuccessful so the NCAA agrees to sanction bowl games and essentially become a cartel manager Sports on Campus 7 p529 Sports Revenue Then and Now I Yale was one of the more profitable sports programs in the early 1900s I The New York Times on June 19 1906 reports revenues and costs for four sports at Yale Sport Year Real Revenues Real Expenditures Real Profits Football 1904 113789432 70907812 42881620 Baseball 1905 45695551 38639298 7056253 Track 1905 6217116 16476186 10259070 Rowing 1905 25607348 45444555 19837207 Football 2006 256505400 54333500 202171900 Baseball 2006 NA 11276300 Track 2006 NA 14555600 Rowing 2006 NA 17768000 Measured in 2006 dollars I Yale earned 32040 757k in 2006 dollars from Harvard 19000 450k from Princeton and 7000 165k from Columbia l Football hotel and meal charges 6379 151k Sports on Campus 7 p629 Football Revenue Today I At many schools football and men s basketball provide sufficient profits to subsidize nonnet revenue generating sports However this is not always the case I 20032004 academic year Sport Average profit Largest Profit Largest Loss Football 295m 3461m Texas 324m Central Florida Women s Sports 374m 16m Tulane 1065m Ohio State I FBS conferences by profit Conference Ave Football Profit Conference Ave Football Profit Southeastern 184m Mountain West 642k Big Ten 148m Conference USA 544k Big XII 112m Western Athletic 531 k Pacific Ten 678m Sun Belt 382k ACC 576m MAC 14m Big East 275m l The BCS conferences split about 110 million in bowl payouts that year while smaller conferences split about 6m amongst themselves I Do these dollar figures provide bad incentives Sports on Campus 7 p729 Incentives Created by Bowl Payouts l One incentive of the bowl payouts might be to reduce competitive balance in certain conferences l Paul and Weinbach 2008 BCS format promotes less competitive balance in midmajors and more competitive balance in BCS conferences l Intuition gt A midmajor can only get a BCS bid if they are in the top 12 of BCS poll eg Hawai i in 2007 To do this one team must dominate the midmajor gt A BCS conference can get two teams into BCS bowls SEC and Big XII in 200708 season To do this the BCS conference needs a little more parity I If lack of competitive balance helps a conference secure a BCS berth it might hurt attendance which suggests a possible tradeoff for a midmajor conference I Depken and VWson 2008 Reduced competitive balance corresponds with increased attendance in midmajors and decreased attendance in BCS conferences l Thus competitive imbalance seems to be profit enhancing for midmajor conferences This seems at odds with most theories of how leagues operate Sports on Campus 7 p829 Cheating in the NCAA l A more worrisome incentive of the bowl payouts is cheating on the NCAA agreement particularly in recruitment efforts I Why would schools cheat when they know that the NCAA looks for cheaters l Twopart reason 1 Enforcement is less than 100 some cheating is never caught and prosecuted 2 Punishment is most often borne by those who didn t do the cheating different than speeding l Assume cheating yields immediate benefits but the costs vary depending on whether you get caught Let the chances of getting caught be p E 0 1 I Let c be the constant marginal cost of cheating and F be the fine paid when caught TCpFc1 pccpF and TBb l Cheating occurs if TB 2 T0 or b 2 c l pF I As b l c T F T and p T then cheating will decrease I As b T c i F l and p i then cheating will increase Sports on Campus 7 p929 Deterring Cheating in the NCAA l Cheating is deterred by increasing F or p l Increasing p costs money increasing F does not I To deter cheating choose a fine that sets net total benefit of cheating equal to zero b c l pF 9 0 p F 2 I An Example Benefits of cheating are 1 m costs are 20000 for scholarship 50000 for a new car p 010 I What fine deters cheating 1 000 000 g 20 000 50 000 010F 1000000 70000 010 F 2 9300000 F I If p 030 then the penalty only has to be N 3m I But this introduces an agency problem if those who commit the crime do not do the time Sports on Campus 7 p1029 Deterring Cheating in the NCAA l Penalties include lost scholarships postseason bans lost television appearances direct fines to the department and the death penalty l The NCAA monitors approximately 800 schools 300 in Division I with fifteen fulltime investigators That is 53 schools per monitor or a little more than one per week I It is unlikely that a single monitor would find a violation in a given week Therefore the NCAA relies heavily on whistleblowers faculty students fans athletes coaches boosters and competitors l The NCAA does raise F according to the type of cheating undertaken l The whistleblowers are used to increase p l Fleisher Goff Shughart and Tollison 1988 NCAA uses volatility of winning percentage as a proxy for cheating Programs that experience dramatic increases in success are more likely to be investigated and found in violation l Depken and Vl lson 2006 NCAA enforcement increases competitive balance but NCAA punishment decreases competitive balance On net NCAA efforts improve competitive balance by an average of 68 Sports on Campus 7 p1129 Recent Violations in the NCAA l A sample of schools punished in football and basketball since 1997 Conference School Football Basketball SEC University of Alabama 2002 1999 University of Arkansas 2003 1997 2003 Auburn University 2004 University of Georgia 1997 2002 2004 University of Kentucky 2002 Louisiana State University 1998 Mississippi State University 2004 Big XII Baylor University 2005 2005 University of Colorado 2002 University of Kansas 2006 2006 Kansas State University 1999 1997 Texas Tech University 1998 1998 University of Oklahoma 2006 I Is there more cheating where there are more benefits Is there more cheating where the NCAA looks for cheating Is there more punishment where there are more whistleblowers Sports on Campus 7 p1229 The Impact of Sports on Campus l Several studies have investigated the relationship of athletics with various aspects of campus I The literature can be split into three parts gt Noneconomics Focus is on sociology and history of sport sport from the point of view of the administration often negative views of sports as low art gt Agnostic sports economics Papersresearchers who undertake positive analysis of sports on campus with little agenda and apply theory and empirical analysis in this pursuit gt Antisports economics Papersresearchers who feel sports on campus are a distraction and use theory and empirical analysis to prove their point I There are several popular beliefs and assertions concerning sports on campus Most research focuses on football and men s basketball and to a lesser extent women s basketball I The literature is reviewed on the following slides Sports on Campus 7 p1329 Football and Academics Popular Belief Preponderance of Evidence Having successful footballbasketball team positively affects student applica tions and enrollment Commonly called the quotFlutie Effectquot the argument is that high visibility asso ciated with footballbasketball success provides widespread national advertis ing that expands size of applicant pool and therefore size and quality of enter ing classes 0 Many anecdotes and most evidence documents at least a shortterm positive effect upon applications 0 A winning conference record and being ranked in top 20 increases applications The evidence on the effect of winning national championship is less clear 0 Getting into the NCAA bball tournament and progress ing into advanced rounds boosts applications in the sub sequent year Effects may not be longlasting 0 Effects seem to be more significant for private institu tions Sports on Campus 7 p1429 Football and Academics Popular Belief Preponderance of Evidence Institutions reclassifying to higher divi sion increase diversity of student popu lation Reclassifying schools increase the number of Black and nonHispanic men but not the proportion of total enroll ment 0 Having successful football team posi tively affects student quality 0 Argument is that high visibility provides advertising that widens and deepens of the pool of potential students thereby al lowing institutions to be more selective 0 Most early research did not support this proposition 0 There is more recent support for it hypothesized to be due to the expanded national media coverage for foot ball as a result of the establishment of the BCS and an expanded inventory of postseason bowl games 0 Applications appear to increase among students with both low and high SAT scores Institutions can leverage larger applicant pool through selective admissions to cre ate higher overall SAT student profile 0 However the overall effect is small an institution with an average level of success can expect to increase its SAT scores by 3 Sports on Campus 7 p1529 Football and Academics Popular Belief Preponderance of Evidence Successful footballbasketball team pos Most studies do not support this proposition although itively impacts overall graduation rates a few support the proposition that graduation rates are as students become more engaged with positively affected by football but not basketball social life of the campus A successful football team negatively im There appears to be evidence in support of this prior to pacts the graduation rate of football play the imposition of practice limits and minimum admission ers requirements but not since the adoption of Proposition 48 Successful football or basketball teams No evidence for this negatively impact overall graduation rates as students focus on sports rather than academics Sports on Campus 7 p1629 Football and Academics Popular Belief Preponderance of Evidence Having a football team increases state appropriations 0 FBS schools receive higher appropriations than non FBS schools 0 Some evidence that success in any given year in creases appropriations to public schools in the following year particularly if a prominent win is posted against an instate rival Successful football team positively af fects alumni giving rates and total dollars received from alumni 0 Some studies show support for rates of alumni giv ing increase for schools in major football conferences Alumni giving rates do not appear to be affected by bas ketball success 0 The evidence is weak on total alumni giving being pos itively affected by football winning percentage Some studies find evidence that total giving increases after a bowl game or NCAA basketball tournament Sports on Campus 7 p1729 Football and Academics Popular Belief Preponderance of Evidence Successful football programs positively affect overall financial contributions The evidence is quite mixed but it appears that only gifts to athletic programs depend in any way on successful athletic teams Institutions that reclassify up realize fi nancial gains 0 An NCAA study of 25 upgrading institutions from 1993 to 2003 found that most were losing money before re classifying Revenues increased after reclassification but they were subsumed by cost increases 0 Value of reclassification is an unquantifiable perceived increase in prestige Sports on Campus 7 p1829 Football and Academics Popular Belief Preponderance of Evidence Having football team positively influ ences reputational scores in college ranking surveys 0 Schools with Division football teams tend to fare better in reputation surveys of administrators but the effect is small 0 Membership in a major conference does appear to pos itively affect peer assessment rankings in the US News and World Report survey 0 Evidence suggests that an upset of a Division school by a nonDivision school can obliterate the advantage of having a Division football team in terms of the outcomes of reputational surveys 0 Once membership in a BCS conference has been achieved there appears to be no significant additional positive influence on the academic quality rankings of universities as a result of football success Sports on Campus 7 p1929 Football and Academics Popular Belief Preponderance of Evidence Institutions that suffer NCAA sanctions will suffer a reduction in donations One study of a single institution supports this proposition for football One multischool study supports it for bas ketball Successful football team negatively im pacts the academic success of faculty Research is exclusively on economics faculty and is mixed Hard to believe that there is a direct impact Per haps indirect if rewards to research are lower Successful football team positively af fects attendance at women s basketball games in same school Having a football team regardless of divisional affilia tion or past success increases attendance at women s games by approximately 400 people per game Sports on Campus 7 p2029 Gender Equity The Economics of Title IX I Title IX is part of the 1972 Education Amendments to the 1964 Civil Rights Act quotNo person in the United States shall on the basis of sex be excluded from participation in be denied the benefits of or be subjected to discrimination under any education program or activity receiving Federal financial assistancequot I In 1979 Congress deals explicitly with athletics Schools must comply to the antidiscrimination language in Title IX by 1 Proportionality School must try to get the percentage of women in sports to be roughly equal to the percentage of women in the student population Office of Civil Rights of the Department of Education currently uses a i5 rule 2 Program Expansion School must show that it is making a goodfaith effort to increase the opportunities of the underrepresented sex This is hard to interpret and hard to get through because it would call for increases in athletic department budgets 3 Accommodation School must show that the student body is satisfied with the current level of opportunities This is difficult to use as well because only one dissatisfied person is all that it takes to find a school in violation of Title IX Sports on Campus 7 p2129 Popular Opinion of Title IX I From a Gallup Opinion Poll Is nu Ix Respanslble m 3th ln Wumen39s 5mm an 511anth m you mm 1 IX w my yquot m 0mm 1 mnnv pm in me last law mmy mm mm n m Dunn Mn main 1mm majarincmr am no m mm mm 1 mlrmrlacmn 0 not upturnx am mu m m mm m m ix m m 2w m m 539 mm mm mm ml Nu mm nutmlm mm lanlnralall WW I What does this mean for Title IX proponents and Title IX critics Spozts on Campus 7 p 2229 Gender Equity The Economics of Title IX l Most Title IX complaints come through proportionality because it is relatively easy to calculate and compare the numbers I Using a percentage as a measuring stick introduces a potential problem there are two elements of a percentage eg Women W0menAthletes Women l M en I There are two ways this percentage can increase I This is the box that many schools find themselves in when it comes to Title IX compliance l Adding a new program to the athletic department will increase the number of overall athletes and the number of women athletes However if the sport is not strong enough to generate its own revenues then it must be subsidized from somewhere I If extra money is not forthcoming some teams might have to be discontinued even as women s teams are added I If true this is a zerosum game all that is won by one side is lost by the other side Sports on Campus 7 p2329 Gender Equity The Economics of Title IX I By most objective measures Title IX has had a dramatic impact on female sports participation High School Varsity Athletes Year 197172 200001 Increase Female 294015 2784154 847 Male 3666917 3921069 69 Collegiate Varsity Athletes Female 29972 150916 403 Male 170384 208866 23 I To many subjectively Title IX hasn t been enforced as vigorously as it could I Still others argue that spending might be more important than sports opportunities I From 1980 to mid 1990 s women s sports grew rather dramatically in Division I from 2011 teams to 2575 teams 28 increase I Number of men s teams over this time period remains static in net at around 2853 However around 350 teams are disbanded and about an equal number of teams are promoted to Division I status Sports on Campus 7 p2429 Spending Disparities Real but Meaningful I There is disparity in institutional spending on men s and women s sports Division Division II Category Men Women Ratio Men Women Ratio Scholarships 1411400 1055500 134 392100 268000 146 Recruiting 184200 85900 214 18900 10100 187 Head Coach Salaries 484900 330500 147 136700 114500 119 Operating Expense 882100 486200 181 225600 115100 196 I Are these disparities meaningful Are they caused by one or few sports football and basketball Sports on Campus 7 p2529 Gender Equity The Economics of Title IX l Nevertheless Title IX has been blamed for the discontinuation of many men s teams Year University Sports Reason 2009 Hawaii UH can t drop a women s sport until it comes CostsProportionality into compliance with Title IX 2009 Vermont Baseball and Softball Costs 2009 Maine Men s Soccer Women s Volleyball Costs 2009 Northern Iowa Men s Baseball Costs 2009 UT Martin Men s Tennis CostsProportionality 2006 James Madison Men s swimming cross country indoor and out CostsProportionality door track gymnastics wrestling and archery Women s gymnastics fencing and archery 2006 Slippery Rock Men s and women s swimming men s and CostsProportionality women s water polo women s field hockey men s golf men s tennis and wrestling 2003 Fairfield U Men s football hockey Costs 2000 New Mexico Men s wrestling gymnastics and swimming Costs 2000 BYU Men s wrestling and gymnastics Costs Sports on Campus 7 p2629 Discontinued Football Teams I Since 1917 at least 179 football programs have been discontinued Some for cost reasons some for attendance reasons some because the collegeuniversity went out of business I Since 1972 at least 90 programs discontinued I Who has lost the most teams I California 15 New York 9Texas 5V sconsin 5 Pennsylvania 5 New Jersey 4 l Every year has seen at least one team discontinue play however the years with the most teams dropped 1951 38 19794 1984 6 1993 and 1994 5 l Bigger names that dropped football Seton Hall 1982 St John s 2002 Texas Arlington 1986 Wichita State 1987 Xavier 1984 I From 20062009 Allen SC La Salle Mansfield Paul Quinn St Peter s NJ Iona Colorado College Principia PA Western Washington no big loss I New teams UNC Charlotte Georgia State South Alabama UT San Antonio Sports on Campus 7 p2729 Gender Equity in Athletics l A free and efficient market would lead to a different number of teams for each college This is where normative judgement takes over people might not like what the market provides and will push for regulation or intervention to make things better I Consider the following picture 13 I NC 11 10 4 B1 K 9 g 6 MB0 xx xx OANwbO l I l 2345678910 Womens Teams 0 1 I If MB1 is used instead of MBO or viceversa the wrong number of teams is indicated l Surveys indicate that women in general are less concerned with sports overall but that those women who are interested in sports seem equally interested as men Sports on Campus 7 p2829 Gender Equity The Economics of Title IX l Economists consider actions to speak louder than words I General Axiom of Revealed Preference People may say one thing and do another What they do reflects their preferences their income and prices In a sense GARP suggests that we don t believe what people say believe what they do I The WNBA vs NBA is a good example Most surveys show that the majority of the population support the idea of professional women s sports What about GARP in this case I In 2000 gt The Houston Rockets charge 105 Houston Comets charge 3250 gt The WNBA had a 7030 female to male ratio in arena Interestingly on television the audience was about 5050 gt The WNBA schedule was 32 games vs 82 games for the NBA gt Average attendance to WNBA was 10207 fans whereas NBA averaged 19052 fans gt Houston Comets disbanded after 2008 season I While women s sports are much more popular than they were thirty years ago the market still suggests that consumers value women s sports less than corresponding men s sports I What does this imply about women s sports and women athletes I What does this imply about the politics of women s sports Sports on Campus 7 p2929 The Players MBAS 6310 Craig A Depken II UNC Charlotte The Players 7 p1111 The Players l The biggest issues in sports center on the players their wages their behavior on and off the field their loyalty to their teamsfans l The focus on the players is perhaps naturally more intense than on the team owners I The average salaries in major sports Sport Ave Salary 2007 Players MLB 29m 842 NFL 13m 1696 NBA 29m 464 NHL 13m 1110 PGA 1 03m 34m top 30 256 LPGA 237k 1 m top 30 190 I Can these salaries be justified on positive or normative terms I Positive If players are paid more than they are worth someone is behaving irrationally l Normative If players shouldn t be paid as much who should get the money instead Fans Owners Politicians The Players 7 p2111 Player Salaries I To analyze workerplayer salaries we turn to the field of labor economics l A good example comes from Pigou 1920 p 520 0 Mu M l FIG 13 l Supply comes from households Demand comes from firms I An equilibrium occurs when supply equals demand I The demand for labor reflects labor s value to the firm It is downward sloping because of the Law of Diminishing Returns The supply of labor reflects the opportunity cost of the household It is upward sloping because of increasing opportunity cost The Players 7 p3111 Player Salaries l Each player s salary is determined via negotiation although that negotiation may be onesided l The Player or her representative negotiates with the Team Owner or his representative l The Player pushes for a higher salary but how high can she push I The Team Owner pushes for a lower salary but how low can he push I Ultimately owner and player agree to a salary or negotiations break down The Players 7 p4111 How high is too high I A firm hires inputs which are combined with technology to produce output Q I In the case of a sports team inputs are players coaches trainers grounds keepers and a stadium and output can be measured in wins I Each input s contribution to overall wins is called marginal product I For example the Marginal Product of Labor AC2 MPL 2 AL Z where L is the labor effortquantity of player 2 l Generally speaking additional output is not intrinsically worth much to the firm I However additional output does provide value to the firm because it can be sold on the market The Players 7 p5111 How high is too High l The value of an input s contribution to output is called Marginal Revenue Product AC2 ALi MRPz39zPX where P is the price of output I The higher the MRP the more the input is worth to the firm and viceversa l A worker s MRP has two components P and MPLZ gt MRP can be low if P is low andor MPL is low gt MRP can be high if P is high andor MPL is high I It might seem unfair or wrong that a teacher is paid considerably less than an athlete but the wages are driven by MRPs not by aesthetics The Players 7 p6111 How high is too high I If all workers are identical then MPL are identical l Yet even if MPL are equal MRP will not be Why I The Law of Diminishing Marginal Returns gt gt Consider a team with 7 pitchers all win 20 games in succession not realistic I know Beyond the novelty of having a 140 win season in baseball the UOH suggests the value of the 135th win will be less than the 100th win ceteris paribus Thus as the seventh pitcher is winning his 20 games those games will not necessarily be worth as much as the games won by the first or second pitcher This in turn suggests that the seventh pitcher is not worth as much to the firm as the first or second pitcher The Players 7 p7111 How high is too high I An alternative the price of output stays the same and MPLZ differs across players Worker M PLZ P M RP Max Wage 1 10 20 200 2 8 20 160 3 4 20 80 4 1 20 20 5 05 20 10 l The demand for labor by the firm is the MRP of labor The firm is only willing to pay up to the MRP of the marginal worker I MPL doesn t have to be linear there can be big dropoffs in MPL gt How many centers do you need on a basketball team gt How many caddies does a golfer need gt How many assistant coaches does a manager need gt Other examples The Players 7 p8111 How low is too low I A firm can offer any salary it wishes but the worker is not dutybound to accept that wage l Every worker has a reservation wage the least for which they will work l The supply of labor is upward sloping as an extra hour worked increases the opportunity cost of working and thus the worker must be paid more on the margin to work more I The supply curve is abbreviated at my and the minimum number of hours the worker is willing to work Lrreservation hours The Players 7 p9111 Labor Markets I If all workers are homogenous the wage is determined by supply and demand w x SS E MC r 111 z f MRP E D D quotI L L S S M C I w SSZMC w MRP E DD The Players 7 p10111 Labor Markets I What if MRP changes instead of MC MRPE DD L 111 SS E w z 1 w The Players 7 p11111 Labor Markets II I The supply and demand model helps with general directional predictions gt If MRP increases wages tend to increase along with amount of labor hired gt If MC increases wages increase but the amount of labor offered tends to decrease l However sports labor is not homogeneous and thus the supply and demand model might need some tweaking gt There are relatively few sellers athletes gt There are relatively few buyers firms gt There are high transaction costs negotiations gt Athletes are generally not homogeneous not perfect substitutes gt There is no free entryexit in the market years of training to qualify gt Buyers do not have perfect information athletes have more information The Players 7 p12111 Labor Markets II I Perhaps a bilateral negotiation framework is better I The reservation wage and a player s MRP determine the socalled contract zone Acceptable to Worker Low Wages R MRP High Wages Acceptable to Firm Low Wages WR MRP High Wages Acceptable to Firm The Players P 13111 3 U I Labor Markets II I What influences the ability to negotiate a likely increases with player age experience quality number of teams bidding on the player player heterogeneity how unique is the player negotiating agent I How can we know anything about oz MRP or the player s reservation wage l One way is to measure the difference between a player s actual wage and his estimated marginal revenue product The closer the wage is to MRP we can infer that the player has greater negotiating strength I This requires a method of estimating marginal revenue product Economists have developed three ways of estimating MRP The Players 7 p14111 Labor Markets ll 1 Scully 1974 Estimate the marginal revenue of a win and then estimate the marginal influence of various production statistics on wins I This two step method estimates marginal product of a player as a weighted sum of his various production statistics and combines that with the marginal value of a win I For example suppose we estimate that each win is worth 100000 to a team I We also estimate that a hit yields 001 wins a homerun yields 05 wins and a walk yields 002 wins I If a player has 100 hits 20 homeruns and 50 walks the player would have a marginal product of wins of 100 x 001 20 x 05 50 x 002 1 10 1 12wins l The player would then have an estimated MRP 12 X 100000 2 12m The Players 7 p15111 Labor Markets ll 2 3 Krautman 1999 Estimate the marginal value of various player statistics by relating the wages earned on the freeagent market which should be approximately equal to the player s greatest MRP amongst all teams and use these marginal values to determine a player s actual MRP I For example we might estimate that in the freeagent market each home run is worth 20000 each hit is worth 10000 and each walk is worth 1500 I A player with 100 hits 20 home runs and 50 walks would then have an estimated freeagent wage of 100 x 10 000 20 x 20 000 50 x 1500 2 1475000 A third way is to directly estimate the dollar value of various production statistics This is a hybrid approach which directly estimates the marginal value of each statistic This approach requires revenue figures whereas approach 2 only requires player salary data Once an estimate of MRP is determined it can be compared to actual salary to determine how much the player is paid of his estimated MRP One way to compare players is through the ratio of MRP to wage what AC Pigou 1920 called exploitation M RP Exploitation W The Players 7 p16111 MRP in MLB I Consider these estimates of MRP for baseball players in Major League Baseball from 19901997 Estimated Variable Coefficient tstatistic Hit 2885260 249678 Home Run 20828500 449521 Offensive Walk 3616540 180961 Offensive Strikeout 2395620 173505 Pitcher s Strikeout 4879970 348772 Opponent s Homerun 14422800 303908 I From these results each hit is worth 28852 in revenue each home run is worth 208285 each offensive walk is worth 36000 while each offensive strikeout reduces revenue by 24000 For pitchers each strikeout increases revenue by 48799 but each home run allowed reduces revenues by 144228 The Players 7 p17111 MRP in MLB l Using these estimates it is possible to determine whether a player is paid too much or not Publicly available salary figures are reasonably accurate and can be obtained at many websites including USA Today ESPN and Baseball Reference I Consider that in 1997 Mark McGuire was paid 715m 923m in 2007 dollars by the Oakland Athletics Was he over paid in that year I His statistics that year were Category Yearly Total Dollar Value Hits 104 300067040 Home Runs 34 708169000 Offensive Walks 58 209759320 Offensive Strikeouts 98 234770760 Total 9832246 I From these numbers it seems that McGuire was actually underpaid which we might expect if team owners are rational and a player doesn t suffer a seasonending injury early in the season The Players 7 p18111 MRP in MLB I In the end the 715 million he was paid in 1997 doesn t seem so out of line when we see how his performance generated money for the owners of the Oakland Athletics l McGuire s Hicksian Exploitation ratio would then be 983715 2 137 Is this high or low I We might think that McGuire s reputation as a homerun hitter and a reasonable first baseman he was a multipletime Allstar player would give him the ability to negotiate his salary closer to his MRP l Calculating the Hicksian exploitation for 5804 MLB players from 19901997 Variable Obs Mean Std Err 95 Conf Interval Exploitation 5804 471 965 57111757 Estimated MRP 5804 1985206 3041142 731396175e07 Salary 5804 9370956 1276837 109009237500 l Estimated MRP had a mean of 22 million and the average salary was 1 47m Exploitation averaged 471 indicating that the average player was worth about five times his wage The Players 7 p19111 Hicksian Exploitation in MLB l The level of exploitation differed dramatically across players standard deviation 965 based on different baseball skills value to the firm and negotiating skills I What might influence exploitation l Whether a player was under reserve first six years player experience and experience squared whether the player went to college whether the player is a Southpaw Variable Parameter Reserve No college Experience Experience2 Le y Constant 2813 0448 0335 000955 1608 5012 The Players 7 p20111 MRP in MLB l The results suggest the following gt A player who is under the reserve clause had no college no experience and was a right handed thrower would have an average exploitation of approximately 83 501228130448 gt A player who is not under the reserve clause Le a free agent would have an exploitation measure that was 2813 units less gt If a player did not attend college their exploitation measure is 045 higher gt For every year of experience a player s exploitation measure declines directly by 055 but this decreases at a decreasing rate ie AE z t w 0335 000955 EXP AEXP A player with 10 years of experience would have an average level of exploitation that would be 0335 x 10 000955 x 100 335 0955 2395 lower ceteris paribus gt A lefthanded thrower has an exploitation measure that is 16 units less ie lefthanded throwers are paid closer to their marginal revenue product can you provide a good reason for this result The Players 7 p21111 Household Labor Supply I It seems natural that as wages increase the household will want to work more hours I Economists assume households split their limited time between consumption not working and work not consuming I This suggests a bit of tension between hours spent working and hours spent consuming I There are two offsetting impacts of a wage increase on decision to work more 1 Substitution effect As wages increase household is motivated to work more hours dedicate fewer hours to consumption 2 Income effect As wages increase the household can earn the same income while working fewer hours will reduce the hours worked I If an increase in wages more than offsets the opportunity cost for working the substitution effect dominates the labor supply curve is upward sloping I If an increase in wages does not offset the opportunity cost of working the income effect dominates the labor supply curve is downward sloping The Players 7 p22111 Household Labor Supply I How can a curve be both upward and downward sloping For some wage rates different for every worker the substitution effect dominates and at other wage rates again different for every worker the income effect dominates I For some wage rates the individual s supply curve bends back on itself U S gt wr Sub gt Inc LT L U S The Players 7 p23111 Household Labor Supply l What s so important about the backward bending supply curve in the context of sports I It s possible that two different wages yield the same amount of labor games played hours playingtraining effort level Lo I At L0 there are two wages that will elicit that level of effort a higher wage and a lower wage The Players 7 p24111 Household Labor Supply l A player could sign a big contract and end up on the backward bending portion of their labor supply curve Their effort drops and people accuse him of shirking Krautman 1990 shows that players generally do not shirk after signing a big contract Rather they seem to regress to their mean productivity either from below or from above Observability bias makes it seem that big time contracts are associated with shirking l Other examples of being on the backward bending portion of labor supply gt Tiger Woods does not play every golf tournament on the PGA tour gt Barry Bonds did not play every day during his last season for the San Francisco Giants gt Latrell Spreewell didn t always practice with his team gt Terrell Owens didn t always practice with the Dallas Cowboys The Players 7 p25111 The Reserve Clause l Thus far we have acted as if the sports labor market is relatively free This is not the case I The beginning of professional baseball in particular was characterized by a freeagent market Team owners quickly recognized that bidding on players increased salaries and reduced profits I In 1887 team owners formally introduced the socalled Reserve Clausequot l The Reserve Clause was the last line of a player s annual contract which tied the player to his team indefinitely l Players could negotiate a little with their team owners but generally didn t have that much leverage except for sitting out I What is the expected impact of the reserve clause gt Salaries will decline gt No change in player movement gt No change in competitive balance gt Increase in the amount of training a team commits to the player The Players 7 p26111 The End of the Reserve Clause l Throughout the twentieth century there was considerable labormanagement tension centered on the reserve clause l The Players League is formed in 1890 as a protest against the reserve clause Folds after one year I In 1969 Curt Flood of the St Louis Cardinals sues Major League Baseball to stop his pending trade to the Philadelphia Phillies l Flood sues under antitrust legislation and a 14th amendment violation l His case is dismissed by the Supreme Court in 1972 but serves as a wakeup call to the players and the owners Arguably his case was very instrumental in bringing about the end of the reserve system I The reserve clause is weakened in 1974 by arbitration l The reserve clause was removed in 1976 after Andy Messersmith and Dave McNally threatened to sue major league baseball I In 1980 Nolan Ryan signs the first true 1m contract worth about 25m in 2007 dollars I Free agency is now available available to players with six or more years of MLB service all other players operate under the reserve clause The Players 7 p27111 0 Here are annual household expenditures for spectator sports and other recreational activities Type of expenditure 2000 2001 2002 2003 2004 2005 Total recreation expenditures 5857 6040 6299 6599 7084 7563 Percent of total personal consumption 87 86 86 86 86 87 Books and maps 337 346 371 387 406 422 Magazines newspapers and sheet music 350 350 351 363 396 438 Nondurable toys and sport supplies 566 576 592 606 635 672 Admissions to speci ed spectator amusements 304 322 348 360 374 383 Motion picture theaters 86 90 96 99 99 97 Legitimate theaters and opera and entertainments of nonpro t institutions 103 109 117 119 124 127 Spectator Sports 115 124 135 143 151 159 Clubs and fraternal organizations except insurance 190 200 211 222 223 235 Commercial participant amusements 758 796 837 912 1007 1073 Pari mutuel net receipts 50 51 53 52 56 62 Values in billions Source Statistical Abstract 2008 table 1206 0 It is also interesting to compare spectator sports to other industries 2000 2001 2002 2003 2004 2005 Spectator sports 21590 22434 24380 25083 26274 27363 Car washes 9518 10228 10487 11058 11076 11392 22382 22465 23686 24631 27289 Readymix concrete manufacturing 21726 Values in millions Source Bureau of Economic Analysis Gross Domestic Product by Industry 0 It is also interesting to compare spectator sports to other retail sectors 2006 12487 2005 Funeral homes and funeral services 12140 Automotive equipment rental and leasing 46053 43643 Video tape and disc rental 9833 9507 2004 11705 41126 10604 2003 2002 2001 12016 11049 10882 37007 35779 36035 10053 9364 9584 Values in millions Source US Census Bureau Service Annual Survey 2006 various tables o Scatter plot and tted regression line of MLB attendance against host city per capita income MLB Attendance and Per Capita Income 1990 2005 O O O LO 0 I O O C 8 8 v 3 E E 8 00 8 U E 9 0 g 0 o 3 l g o C lt O O O 20000 30000 40000 50000 Real Per Capita Income O O O LO 0 8 I c Ev o 0 g d 00 r 0 0 00 o o 00 o o o E 8 39 00 8 39 0 g 0 C O 039 D 0 C U E O 2 39 E O O O 20000 30000 40000 50000 Real Per Capita Income o attendance Fitted values 0 Using the data describing major league baseball 1 estimated a multiple regression model with per capita income current season s win percentage last season s win percentage the number of non baseball franchises in the host city and a variable that takes a value of 1 if the team lowered its ticket prices from one season to the next and zero otherwise reg attendance rincome win lagwin comps subs lowertix Source SS df MS Number of obs 342 F 6 335 2851 Model 588897308 6 981495513 Prob gt F 00000 Residual 115317934 335 344232639 R squared 03380 Adj Rsquared 03262 Total 174207665 341 510872918 Root MSE 58671 attendance Coef Std Err t PgtItI 95 Conf Interval rincome I 0131353 0053829 244 0015 0025467 0237238 win I 3509 5002015 702 0000 2525068 4492931 lagwin I 2869897 5293329 542 0000 1828662 3911132 comps I 2375974 2348492 101 0312 2243677 6995624 subs I 1258735 7628068 165 0100 275923 2417597 lowertix I 6563158 6759914 097 0332 1986039 673407 cons I 1344359 3224284 417 0000 1978599 7101199 0 Here are some actual regression results from Fan Loyalty and Stadium Funding Evidence from Major League Baseball77 Depken7 CA7 Joumal of Sports Economics7 2000 Ordinary LeastSquares Variable Description Coefficient Stdl Error tStatistic Intercept 1469 2198 PAVE Ticket Price 0451 011 4110 CONAVE Concession Price 0098 002 4190 FRAGE Franchise Age 0006 003 020 CITYTEN City Tenure 0063 003 2110 STAGE Stadium Age 0087 002 4135 WIN Winning 0739 012 6115 LAGWIN Last Season Win 0389 013 2199 POP City Population 0163 003 543 INCOME City Income 0957 021 4155 PLAYERC Team Payroll 0286 006 4176 LEAGUE League 0055 003 1183 CAPACITY Stadium Capacity 0266 008 21325 YR90 1990 0212 007 3102 YR91 1991 0193 006 3121 YR92 1992 0073 006 1121 YR93 1993 0203 006 3138 YR95 1995 0129 006 2115 YR96 1996 0055 006 091 R2 0696 N Number of Obsl 174 Dependent Variable is logAttendance All continuous variables transformed into logarithms indicates signi cance at the 005 010 level buy M J 4m 1m m V Emmaquot The Managers Craig A Depken II UNC Charlotte The Managers 7 p129 The PrincipalAgent Problem I Why do managers exist Why don t teams operate without the help of coachesmanagers l Managers partially solve a PrincipalAgent PA Problem I PA Problem How to align incentives so that the actions of one person the agent yield maximum benefit for another agent the principal I PA problem is one of hidden information and hidden action The principal doesn t know what the agent is doing but observes the outcome of the agent s actions The Managers 7 p229 The PrincipalAgent Problem I Ifthe agent s actions yield a benefit to the principal of 100 could the agent have done more for the principal I Perhaps the agent took 25 of benefit from the principal in the form of shirking less effort or bad behavior I Unfortunately agents tend to do what is in their best interest not necessarily what s in the best interest of the principal I Principals can create incentives to encourage the agent to behave as the principals want The Managers 7 p329 PrincipalAgent Problems in Sports I The PA problem is most pronounced in publicly traded firms shareholders want management to max profits but management might want to max trips to Morocco l However there are a number of PA problems in sports gt Fans P want players A to play hard gt Team Owners P want players A to win gt Team Owners P want trainers A to not lie about player health gt Players P want their representatives A to negotiate highest salary gt Fans P want officials A to be honest gt Fans P want players A to be clean I How can the team owner get players to play hard and try to win I How can fans get players to stay clean The Managers 7 p429 The PrincipalAgent Problem I Create incentive clauses in player contracts eg hit 50 home runs and earn a bonus of 1 m l Incentive clauses help the principal but agents don t like them agents prefer a higher fixed salary I Consider Ricky Williams and the New Orleans Saints gt Saints traded all of their 1999 draft picks for Vl lliams only time in history gt Vl lliam s contract was negotiated by Rapper Master P s No Limit Sports gt Contract has 8Mplus signing bonus gt Contract has incentives worth between 11m68m gt Vl lliams doesn t meet any incentives gt Vl lliams is traded after three years and never makes the BIG BIG money The Managers 7 p529 The PrincipalAgent Problem I It might be possible to write an incentivebased contract for every player on the team I However giving all the players on a team different incentives can cause a breakdown in team performance through peer effects gt A baseball player might swing for the fence rather than bunt gt A quarterback might throw when the best strategy is to run gt Jimmie Johnson might drive for himself and fail to help draft his teammate Jeff Gordon l Most sports movies consider this problem There is no ME in TEAM I In other words how to coordinate player behavior The Managers 7 p629 The Manager as a Partial Solution l One solution is to have a manager who is charged with calling the shots on the field and perhaps making playerpersonnel decisions I Players then coordinate their behaviors through the manager I It is important paramount that the manager be able to penalize a player for not sacrificing their shortrun interests to the longrun interests of the team I Moreover the manager can inform the team owner about the quality and intensity of the effort put forth by the players something about which players would naturally try to mislead the team owner The Managers 7 p729 Who Monitors the Monitors l Managers introduce another PrincipalAgent problem think of the movie Major League do managers behave consistent with teamowner objectives I How does the team owner know if the manager is putting forth high quality and intense effort I Unlike in the case of players managers are easier to monitor Why I Managers are hired and paid to coordinate player actions inputs to produce wins output Thus a manager can be judged on their relative or absolute ability to produce wins given the inputs with which they work The Managers 7 p829 Are Player Managers an Answer I Initially many managers were player managers they played and made strategic and personnel decisions during the game I The benefits of a player manager gt Less expensive in terms of salary gt Might know more about how a particular game is evolving gt Might have an easier time communicating with players gt Might have a more contemporary view of strategy I Costs of a player manager V Might be distracted by playing V Might be prone to favor one or few players at the expense of the team gt Might favor himself as a player gt Might be more allied with players than owner gt Might mislead the owner about player effort The Managers 7 p929 Player Managers Throughout History I The percentage of managers who were player managers by year in MLB F pctplyrmgr 6 I 4 I O 183950 1 93900 1 93950 203900 yearlD l Notice the dropoff after the late 19405 The Managers 7 p1029 Why Not Use a Player Manager I The autonomous manager implies that the costs exceed the benefits of the player manager gt As labor relations become more strained team owners want managers in their camp rather than in the players camp gt It is harder to remove a manager when he is a player gt It is harder to remove a player when he is a manager gt Player managers were not as good as autonomous managers I How can we measure the quality of a manager I Total wins Win percentage Both are strongly related to the quality of the players The Managers 7 p1129 Managerial Quality How can we gauge the quality of a manager Some might suggest looking at total wins However the longer a manager keeps his job the more he will likely win and the more he will likely lose Some might want to look at winning percentage What about people who managed very few games and won them all Ten managers managed 1 2 or 3 games and won them all They are nonames and wouldn t be considered the best managers The Managers 7 p1229 l Ifwe restrict our attention to those managers with more than 2000 games managed here are the top ten Last Name First Name Total Games V nning Percentage McCarthy Joe 3458 614517 Selee Frank 2146 5983225 McGraw John 4711 5864997 Lopez Al 2414 5840928 Weaver Earl 2540 5826772 Wright Harry 21 10 5805687 Anson Cap 2243 5777976 Clarke Fred 2783 5756378 Johnson Davey 2036 5638507 Cox Bobby 4019 5610849 I While there are a few names recognizable to modern baseball fans many of these managers managed in the early 20th century The Managers 7 p1329 What s in a Manager I During the Braves remarkable 14 straight division titles it seemed anyone could have managed the team I What exactly did Bobby Cox bring to the situation gt Expenence gt Temperament gt Knowledge of the book gt Intuition gt An Xfactor I Is it possible to separate the contribution of the manager from that of the players I It is possible using productivity economics The Managers 7 p1429 Measuring Managerial Quality I An r w J inpms l Point A Actual combination ofinputs used to produce Q l Point B A more efficient combination of inputs to produce Q less x1 and x2 I u A 5 quotVirginsderailL 39 L M u zquot Fl but 1 z I LA uywemgwmswww Stochastic Frontier Analysis I We can operationalize the graphical idea of technical efficiency using what is called Stochastic Frontier Analysis I Stochastic frontier analysis is rather sophisticated but in a nutshell P P P Estimate a production function output as a function of inputs Estimate the maximum wins for a team given its inputs 217 The difference between actual wins and potential wins 11 W1 is a combination of random elements bad luck and managerial incompetence The smaller the managerial incompetence the more efficient the manager is given the players he has to coach The Managers 7 p1629 A Production Function for MLB l Following Scully 1974 define the production function for wins in MLB as W5o 1SA 2SW where SA is slugging average SW is strikeout towalk ratio and e is comprised of random elements and managerial inefficiency l After we estimate this regression model we can predict the maximum number of wins a team is expected to win given its SA and SW l Using data for 991 years of data for 51 MLB managers who managed 2000 games through 2007 Variable Coefficient sa 1006 sw 0028 Constant 0169 l Higher SA and SW yield higher win percentage Whewl The Managers 7 p1729 Managerial Efficiency in MLB I How efficient are the longest serving managers Obs Mean Std Dev Min Max Technical Efficiency 991 852482 04371 7738903 9704429 l Amongst these 51 managers average technical efficiency was 85 minimum 77 maximum 97 l Thus the average 2000 game manager won 85 of the games they were predicted to win given the players they were managing I Is this good or bad It is hard to make comparisons but when compared to all of the managers they are considerably better on average The Managers 7 p1829 Managerial Efficiency in MLB I Here are the five most and five least efficient managers 2000 games Last Name First Name First Year Technical Efficiency Wright Harry 1871 9704429 Selee Frank 1890 9548272 Hanlon Ned 1889 9442857 Clarke Fred 1897 9333097 Griffith Clark 1901 9313238 Robinson Frank 1975 7990444 Piniella Lou 1986 7990173 Bochy Bruce 1995 7955401 Kelly Tom 1986 793575 Garner Phil 1992 7738903 l Notice that the most efficient managers all come from the early years of baseball The Managers 7 p1929 Were Player Managers More Efficient l Applying this technique to data for 637 managers through 2007 each manager s average efficiency was related to years managed Played MLB YN Player Manager YN Variable Parameter Years Managed 00015 Manager Only 00099 Player Manager 00339 Constant 05476 R2 014 l The average manager improved 01 in efficiency for each year of experience I Managers who did not play in the MLB were about 1 more efficient than those who did I Player managers were on average 34 more efficient than their autonomous counterparts The Managers 7 p2029 Do Efficient Coaches get Paid More I Does efficiency translate into a higher salary for a coach I H1 High salary coaches are more efficient efficiency wage model I H2 High salary coaches are less efficient reputation depreciation model I H1 suggests that coaches continue to perform well up to and AFTER they receive a big contract I H2 suggests that coaches perform well up to getting a big contract but aftenNards depreciate their good reputation The Managers 7 p2129 Managerial Efficiency in NCAA Football l Following Depken and Vl lson 2007 anin3 2 80 l llnTOTPTS l glnINVOPPPTS l 83RATE l e where TOTPTS is the total number of points scored by the team INVOPPPTS is the inverse of the total points surrendered by the team and RATE is a thirdparty team rating which takes into consideration the strength of the team s opponents especially inconference l Using data describing 117 D1A programs for 2006 Variable Coefficient lntotpts 0697 lninvtotopp 0573 Rate 0002 Constant 2452 Observations 117 The Managers 7 p2229 Managerial Efficiency in NCAA Football l The five most and five least efficient coaches in 2006 Rank School Coach Salary Technical Efficiency 1 Arkansas St Steve Roberts 189655 9638122 2 Florida Atlantic Howard Schnellenberger 353147 9460093 3 Ohio U Frank Solich 262172 9442407 4 Kent Doug Martin 150200 9386421 5 LouisianaLafay Ricky Bustle 194250 9368176 113 Memphis Tommy West 925000 440453 114 Colorado Dan Hawkins 1098500 4384085 115 Illinois Ron Zook 1241750 4377666 116 Stanford Walt Harris 3475994 117 E Michigan Jeff Genyk 425000 3168943 I Only one of the top ten coaches is from a BCS school Maryland The Managers 7 p2329 Coaching Efficiency and Salary I Is there a nonlinear relationship between efficiency and salary Variable Parameter Technical Efficiency 6274837 Technical Efficiency2 4991192 BCS Conference gtlt TE 983874 Constant 1261771 Observations 105 R2 044 Dependent variable Salary l Coaches in BCS conferences earn about 983k more for the same level of efficiencyl The value of efficiency is worth that much more in the BCS I It does not appear that coaches are cashing in their efficiency reputation The Managers 7 p2429 A different approach JC Bradbury investigates the impact of Leo Mazzone on the Braves Pitching staff Instead of estimating a production function JCB takes advantage of two sets of natural experiments gt Players came to and left the Braves during Mazzone s career gt Mazzone left the Braves to go to the Orioles Mazzone s Atlanta players were then coached by someone else Our previous analysis looked across teams and coaches whereas JCB compares players before and after playing for Mazzone JCB finds that pitchers improved when they played for the BravesMazzone JCB finds that pitchers regressed when they left the BravesMazonne JCB interprets this as evidence that Mazzone did more than simply provide a training regimen which players would not forget The Managers 7 p2529 Peer Effects A Role for Managers l Managers try to mitigate potentially debilitating negative peer effects I However managers are often constrained in what they can do team owners might not trade a problem player rosters are limited in size and composition I Can we identify negative peer effects when managers choose the players I Depken and Haglund under revision investigate the impact of disparity in runner quality on the performance of NCAA relay teams I Is there any nonlinear relationship between average team member quality and team performance gt Potential for freeriding on the part of low quality runners gt Potential for hotdogging and selfish behavior on the part of high quality runners The Managers 7 p2629 Peer Effects A Role for Managers I We specify a team production function as TIME g lAVERANK gAVERANKZ yOTHERVARS e l Using a thirdparty ranking NCAA relay runners based on their previous performances we can create an average team member quality measure for each relay team I We hypothesize that gt l lt 0 As average quality improves so too does team performance gt g 0 No evidence of peer effects gt g gt 0 Negative peer effects ave quality T eventually performance l gt g lt 0 Positive peer effects ave quality T performance T even more The Managers 7 p2729 Managers and Peer Effects The Managers 7 1 2529 Managers and Peer Effects l The results suggest that simply putting the best players on a relay team does not guarantee the highest team performance I This might provide a justification for a coachmanager the coach determines a who will be on the team and b how to get the team members to work together I Those coaches who are better at getting teams to work together or are better at producing wins given a set of players are worth more The Managers 7 p2929 April 24 2006 New Stadiums and Team Finances Evidence from the National Football League Dr Crai A De ken 11 Associate Professor Department ofEconomics University ofTexas atArlington UTA Motivation In 1971 Texas Stadium cost approximately 2400 per seat in 2000 dollars In 2004 Arlington voters agree to pay 325 million towards a new Cowboys stadium est construction costs 8666 per seat Most economic research on publicly nanced stadiums focuses on how a new stadium in uences various aspects of the host city in an attempt to determine if public expenditure is justified Subsidy proponents point to hardtomeasure public bene ts from hosting a bigleague team Subsidy critics point to easiert0 measure private benefits to the team owner UTA Arguments For and Against Public Funding of a Stadium M Economic development Increased employment and earnings Tourism to host city Hostmg megaevents Super Bowl Reputation as a big time city 1 eam might relocate Local civic pride and quality of life Stadium costs can be exported through sales and excise taxes Against Benefits of the stadium are typically overestimated and the costs ated undere st1m Team owner can raise capital in private financial markets eg Selling stocks andor bonds Stadiums are expensive ways to spur limited economic growth Threat to relocate has little credibility Public property rights hard to define Public funding is a wealth transfer to team owner UTA Existing Economic Research 0 Despite aHCCdOL39dl evruence and claims by highly paid consultants economists have found little evidence that stadiums improve 7 Percapita income 7 Unemployment rates 7 Tourism rates 7 Local business relocations 7 Intercity business relocations 7 Sales tax revenues 7 Property tax revenues Yet stadiums are clearly assets and provide value to someone Whom UTA De ning the Bene ts of a New Stadium 0 Private Bene ts those internalized by the team owner or other economic entityperson 7 In the form of revenues jobs higher earnings 7 Require well de ned property rights Public Bene ts those dif cult to allocate to specific people and enjoyed by the public at large 7 In the form of quality of life city pride and notori t4 7 Usually lack well de ned property rights UTA Determining Propem Rights Property rights are determined in contract negotiations between the franchise owner and the host city Over the past fifteen years 7 Franchise owners keep the majority of revenues from parking concessions advertising anu luxury boxes 7 Franchise owners often acquire low rent payments lower sales taxes on tickets and less res onsibilitv for maintenance and renovations These negotiations can raise tens of millions of dollars a year in revenues for the team owners Forbes 200 UTA New Stadiums and Owner Incentives What does a team owner do with additional revenue from a new stadium 7 Fan Perspective Use additional revenue to buy better more expensive players and improve team quality Salary cap might preclude this from happening 7 Owner Perspective Maintain or reduce payroll and use extra revenue to increase pro ts and franchise s value This is known as a principalagent problem 7 If revenues increase in a new stadium the team owner the agent may not improve the quality of the team counter to what the fans the principal want 0 Why would an owner not want to improve team quality UTA New Stadiums and Incentives Fans respond to higher lower team quality but in different ways 0 Some fans are fair weather in the sense they only attend when the team is good Other fans are loyal in the sense that they attend even when the teaquot is bad Depken 2000 measures the relative intensity of fair weather to lo al fans as a measure of fan lo alt Cowboys rank 7th out of 34 US teams UTA Variables Investigated HOW 1065 a new stadium impact Attendance Team Quality Prices Team Pro ts Team revenues Team value Data from 19912003 in professional football Teams grouped by New and Old Stadiums New btadium de ned as less than SIX years 010 UTA New Stadiums and Season Attendance 540000 530000 520000 510000 500000 490000 480000 470000 Attendance Average Annual Attendance I NFL Average I New Stadiums I Old Stadiums Teams in new stadiums average 36000 more people per season 9000 per game New Stadiums and Team Win Team Win Percentages I NFL Average I New Stadiums I Old Stadiums Teams in new stadiums do not Win more games UTA New Stadiums and Prices 2000 Dollars 4 04 5147 Concessions 4 people Average Ticket Price 1a Stadiums I NFL Average I New Stadiums Teams in new stadiums charge 12 more for an average ticket Teams in new stadiums charge 150 more per person in concessions UTA Millions 2000 Dollars New Stadiums and Team Revenues 160 G ate Revenue Total Revenue l NFL Average I New Stadiums l Old Stadiums Teams in new stadiums average 1517m more in gate revenue Teams in new stadiums average 4445m more in total revenue UTA m r 3 39339 Q o o o N m E S b Ab ANNMM omomomom New Stadiums and Team Pro ts Team Pro t I NFL Average I New Stadiums I Old Stadiums Teams in new stadiums average 1957m more in profits UTA Millions 2000 Dollars New Stadiums and Team Values Team Book Value I NFL Average I New Stadiums I Old Stadiums New stadium increases book value 3942m on average UTA Conclusions Data from 19912003 indicate that NFL team owners stand to gain considerably from new stadiums especially when publicly funded How Team owners hold property rights to most of the stadium s measurable bene ts If stadiums were like other assets during the 1990 s then 1015 annual return might be reasonable On average a new stadium increases team profit by 1957m Team owner contributes 63m on average 31 return on investment Public contributes 230m on average Are public bene m between 23m to 345m per year 1015 Percapita public bene ts are likely less than percapita public costs UTA


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