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Does it pay to be unethical? The case of performance enhancing drugs in MLB.

I. Introduction

For years, college of business professors have claimed that while unethical behavior may lead to short-run gains, it diminishes long run profits. Eventually, customers and suppliers migrate away from untrustworthy businesses and managers and toward those who operate "ethically" (Ferrell, 2004). Ethics, of course, is loosely defined. Simply "not breaking laws" does not imply ethical behavior. Stakeholders must look beyond their business and customer base to determine the impact of their decisions on society. Some corporate decision makers have engaged in behavior that yields positive impacts that reverberate through their community, such as Chick-Fil-A, while others have triggered negative externalities that changed the way society views business, such as the executives at Enron and a host of financial companies (Boyles, 2008).

In this paper, the question of "does it pay to be unethical?" is investigated from the framework of Major League Baseball (MLB). The issue is first addressed from a public goods perspective focusing on the marginal benefit and marginal costs of steroid use. Then, using career data compiled in the 2005 season, regression analysis is performed to estimate the affect of steroids on player salaries. The results reveal the financial impact of performance enhancing drugs (PEDs) on player salaries. But, the long-term implications of steroid use on future earnings, reputation, and physical health will take time to surface.

II. Overview of the Issue

In 1994, MLB Commissioner Bud Selig proposed random drug testing for MLB players. But the economic woes of the owners coupled with the opposition of the MLB players association caused Selig to table the matter. Up until that point there had not been any notable issues with performance enhancing drugs. But, that story was soon to change. In 1998, Mark McGwire and Sammy Sosa's home-run race brought national attention to baseball as the new era of power was born. Three years later Barry Bonds rewrote the record books as he toppled McGwire's homerun record with 73 round-trippers in one season. A few years later each of these players were indicted for steroid use. Why did these players choose to take PEDs? Did the perceived marginal benefits of their actions outweigh the marginal costs of being caught?

For some players it is clear that the marginal benefit dwarfed the marginal cost. Brady Anderson, a former Major League Baseball player, has been accused but not indicted for his use of steroids. His home-run production went from 18 in 1995 to 50 in 1996! (1) At the end of 1997 he signed a 5 year contract worth over $30 million. His home-run production never even came close to 50 again, but he continued to receive a $6 million salary for the next five seasons. While the evidence against Anderson is inconclusive, the marginal benefit of a player having a banner year (or hitting more homeruns) can be measured by the increase in his salary. The marginal cost is measured by the punishment of getting caught, which in Anderson's case never happened.

After hitting 52 home-runs in 1995 and 58 in 1996, Mark McGwire, who later admitted to using performance enhancement drugs, left Oakland to sign a four year $40 million contract with St. Louis. McGwire earned over $75 million in his MLB career. After admitting his use of banned, performance-enhancing drugs McGwire was not punished by a court of law. According to legal experts, his testimony to Congress was vague, but he didn't lie, which left the court with inconclusive evidence. In McGwire's case, the use of the drugs was not administered in an illegal manner; furthermore, by the time of his testimony no court could hear his case given the statute of limitations on the issue. (2) While being temporarily shunned by society, having an asterisk next to his career statistics in the MLB record books, losing endorsement deals, and possibly being kept from entering the Hall of Fame are embarrassing and humbling, it is clear that McGwire obtained financial prosperity and narcissist benefits from his steroid use, even if it was temporary.

In the late 1990s, the McGwire case and others forced Major League Baseball to make a choice; they could seek out and punish steroid users or continue to let the players use these performance enhancement drugs. The benefit of the drug prevention program was maintaining the purity of the sport. Baseball has a rich tradition as America's favorite pastime which includes statistics that can be traced back to the late 1800s, and fan loyalty that spans across generations.

The predominant cost of MLB enforcing a steroid policy was lost short term profit. During the steroid era, the turnstiles at MLB ballparks were swirling as fans congregated to watch the homerun fireworks. In 1993, prior to the steroid explosion, attendance at major league ball parks rose to 70 million. In August 1994, attendance was on a pace comparable to the 1993 season but the MLB players union went on strike and the league shut down. The fans were turned off by the strike. They couldn't understand how players could complain about making the league average $1.2 million a season. (3) By 1995, attendance dropped to 50 million, a 30 percent decline from 1993. The MLB stakeholders were in need of an injection and the McGwire/Sosa home-run race of 1998 provided the necessary fix. Over 70.8 million fans filed into MLB ball parks and millions hovered around their televisions to watch the shattering of Roger Maris' perceivably unbreakable home-run record. (4) Team profits increased as television revenue and ticket sales grew. Owners watched their franchise values increase from an average of $111 million in 1994 to $286 million in 2001 (Haupert, 2010). If the players were tested at that time, and an anti-drug policy was enforced, the owners would have lost their long awaited profits and the sport may have suffered indefinitely.

The other costs of enforcing the performance enhancing drug policy were operational, such as the expense of screening players for drugs and the potential litigation costs that would have ensued with the players union if a player was caught. Clearly, the benefits of enforcing a strict drug policy were pretty low and the cost of enforcing the drug policy was high. With this in mind, owners and league officials decided not to enforce an anti-doping policy at that time.

But eventually, the negative press overcame the sport. In 2003, a link was exposed between Bay Area Laboratory Co-operative (BALCO) and Greg Anderson, the personal trainer of Barry Bonds. BALCO, a nutritional supplements company, was engaged in the production of a previously undetectable anabolic steroid known as THG. (5) As a result of the investigation, Bonds and Jason Giambi, another all-star MLB player, were issued subpoenas by a federal grand jury (Staudohar, 2005). In 2004, this negative exposure led the owners and players union to an agreement on a mandatory drug screening policy which was to begin in the 2005 season. But, the punishments for offenders were still soft.

Shortly after the league's policy change, Jose Canseco's tell-all book Juiced: Wild Times, Rampant Roids, Smash Hits and How Baseball Got Big implicated a variety of star players detailing their use of steroids. (6) He claimed that 80 percent of MLB players used steroids! Canseco's controversial peek at the insides of baseball sparked a Congressional investigation that led to the Mitchell Report. The accompanying Senate hearings that followed added teeth to the allegations of MLB drugging. As a result, the period that was revered for its home-run production and power hitting was dubbed as the "steroid era." (7)

III. Ethics and Profits--Literature Review

The marginal benefit of steroid use can be measured in terms of salary enhancements and endorsements. Grossman et. al. (2007) estimate the improved on-base-percentage of players who use PEDs leads to an additional $2 million per season. They multiply this figure by 6 which is the average length of an MLB player's career (Shall and Smith, 2000), to arrive at $12 million in marginal salary increases. Some of the accused players were not only icons on the field, but they were also held in high regard by the general public off of the field. This admiration grew into corporate endorsements that measured into the millions of dollars. During the season that Barry Bonds captured the home-run record, he landed lucrative advertising contracts with Master Card and KFC. (8) Mark McGwire's record breaking home run was worth an estimated $25 million in endorsement deals. (9) As Rafael Palmeiro approached the 500 career homerun milestone, he supplemented his five year $45 million contract with an endorsement agreement with Viagra. The financial incentives of performing above the margin were evident to the players, but the risks of using steroids to obtain levels of greatness may have been underestimated.

The marginal cost of steroid use considers the probability of getting caught along with the lost wages, both present and future. The probability of being caught increased in 2005 when the MLB players association and league administrators agreed to year round testing, and tougher penalties for steroid users. These penalties commence with a 50 game suspension after the first offense of testing positive, and conclude with a lifetime ban from the game after the third offense (Grossman et. al., 2007). MLB's drug policy was intended to change player behavior by increasing the likelihood of being caught and issuing harsher consequences. This policy by MLB is consistent with the literature on shirking (Shapiro and Stiglitz, 1984). Researchers find that workers who are more closely monitored will alter their shirking (cheating) behavior (Frey, 1993). Yet, if left alone, employees (players) have an incentive to maximize their own utility (Alchian and Demsetz, 1972). That is what the players of the 1990s were doing. They assumed that the benefits of cheating outweighed the costs. If PEDs enable players to achieve their goals at a minimum cost then one should expect players to engage in such rational activity.

The second component of the marginal cost function is the lost wages of players who test positive for steroid use. These lost wages could stem from salaries reductions and fines to cancelled endorsement deals. Bloomberg estimated that PEDs cost Barry Bonds $10 million in endorsement opportunities. (10) Jason Giambi, an admitted steroid user, lost about $4 million in endorsements in 2004. (11) The seven time Cy Young award winner Roger Clemens lost $3 million in endorsements after being accused of taking HGH. And, Alex Rodriguez, another accused steroid user, lost his deal with Pepsi, and will not likely attract other companies because of the allegations against him. (12)

Each of these players has also reduced his chances of being inducted into the Baseball Hall of Fame. They have tainted their celebrity status for future endorsement opportunities, and ruined their hard earned reputations. Even though the use of PEDs did not stop the fans from attending MLB games during the steroid era, players who gain a competitive advantage by partaking in illegal and unethical behavior are not as marketable as players with clean reputations. (13) According to David Sweet, an NBC Contributor, "... a steroid accusation is the kiss of death to companies wanting to put a ballplayer in its ads." (14)

Companies that are viewed as ethical enjoy some advantages over their competitors including, a better rapport with customers and the community (Ferrell, 2004). Research indicates the improved rapport from ethical interactions with customers result in positive corporate profits (Donaldson, 2003). McMurrian and Matulich (2006) agree that ethical behavior leads to customer loyalty and customer loyalty leads to corporate profit. Therefore, players who appear ethical are easier to market, such as Derek Jeter who earned $10 million in endorsements in 2010. (15)

IV. Ethics in Sports: Are the marginal costs decreasing?

From a societal standpoint, people want to believe that ethics matter. The public desires unethical business practices to be revealed and punished. Fans want the players who follow the rules to win. But time after time in sports, fans witness unethical behavior and loose interpretation of the rules that result in "injustice" on and off the field. The recent spectacle of the 2010 FIFA World Cup is a prime example. Players fall to the ground, rolling, holding their heads as if they had been elbowed or kicked by their opponent. Referees respond to their antics by ejecting the accused players or issuing yellow cards (warnings). Upon review, the replay reveals that the entire display was an act. And it worked! Regardless of our business models and empirical support for ethical behavior, games are not always won by the team playing fair and players who cheat do not always lose.

Unethical behavior has stained baseball since its earliest days. In 1919, gambling was brought to the forefront by the Chicago "Black Sox" scandal, and more recently, PEDs have polluted the sport. Yet, what has changed over the years is the fan's reaction to the unethical accusations. In 1919, the fans were appalled by the vindictive and greedy behavior of the baseball players who threw the World Series for money. The league responded by banning eight Chicago White Sox players for life! In recent times the punishments are much lighter. In 2009, Manny Ramirez, the Los Angeles Dodgers star outfielder was banned for 50 games for testing positive to a banned substance known as HCG. After the suspension, Manny reappeared to the game as a hero. The ESPN crew and the Governor of New Mexico were in attendance at the first game of Ramirez's rehabilitation tour which started in the minor league. Ramirez also took the suspension lightly as he stated, "I didn't kill nobody, I didn't rape nobody, so that's it, I'm just going to come and play the game." (16) Alex Rodriguez, the New York Yankees star third basemen, who admitted to using steroids from 2001-2003, was not even punished by MLB league officials. (17) As long as he continues to produce, the city embraces him as a star. Jason Giambi was greeted with a standing ovation on opening day after the details of his steroid use was exposed in the off-season.

Feinberg's (2009) research indicated that fans rationalize harsher penalties for substance using players whose performance is enhanced than for players who are performing at the "average" level. In other words, the star players should be more harshly punished for using performance enhancing drugs. This result is consistent with other literature that suggests attitudes toward cheaters are more sympathetic when the cheater needs to cheat to survive (Jensen et. al., 2002). Yet, these recent examples reveal that fans would rather win than punish their stars. In 2009, the national economic woes and overall reductions in league attendance did not deter the Los Angeles Dodgers fans from flocking to the ball park to support Manny Ramirez and his teammates in their quest of a World Series. The Dodgers had record attendance figures for the season.

V. Salary Equation and Model

In this paper, the link between performance, steroids, and salaries is explored. The objective is to estimate the benefits of experimenting with performance enhancing drugs. In a competitive labor market for ball players, where neither the employee (player) nor the employer (owner) has significant bargaining power, salaries are determined by the interaction of the demand for players and the supply of players. The value of a player to his team is a key factor in determining the size of his salary. The player's productivity affects how many games his team wins, and wins provide economic value to the franchise. The marginal productivity of players is represented in the salary equations by the player's actual performance statistics. The market value of victories to a team is represented by the market size of the franchise. It is assumed that the larger the market, the greater the value of a win to the owner. Larger market teams are rewarded with lucrative television contracts, game receipts, merchandise sales, and concessions. Players of a given quality create more value for their teams in larger markets than in smaller markets. However, the incentive to engage in steroid use is independent of market size. Players in smaller markets have an incentive to obtain a position in a large market, while players in larger markets want to stay there.

The salary equation estimated in this paper relates the wages earned by a particular player in a given year to selected measures of his career performance through the previous season. His past performances provide an indication of what to expect from him in the contract year, the compilation of above average performance statistics offers a player additional bargaining strength in his salary negotiations with management.

The survey includes non-pitchers, referred to as "hitters" in the 2005 season. These players must have played in 2004 and received a contract in 2005. Therefore, 2005 rookies are not included. The other group that is excluded is players who have been in the league for three years or less. The exclusion of that group is inconsequential being that they do not have bargaining power. After a player's third year of service, if he and his team cannot settle on a contract their case goes to an arbitrator. The salary is then determined by a third party and both sides must accept the proposed terms. Salary and performance data for 2005 and supporting years were acquired through publicly available data sets assembled by USA Today. Population data were acquired from the Department of the Census in the U.S. and Canada. Performance data for each player reflect his career productivity through the end of the 2004 season.

Two variables were chosen to represent the player's productivity at the plate, slugging average and on-base-percentage plus slugging average (OPS). Slugging average is the ratio of the total number of bases achieved on hits divided by the number of official times at bat. The measure incorporates both a player's batting average and his power.

The book Moneyball revealed the value of a player who gets on base and adds to his team's success in other ways besides hits and power. (18) Prior to the book, astute owners could obtain the services of players who contributed in "other ways" for a below market price. Since the book's release, the OPS, the on-base-percentage plus slugging average--which includes sacrifice flies, bunts, and walks--has replaced the batting average in economic literature in determining a player's value to his team (Yates, 2008; Hakes and Sauer, 2006). Once the general managers realized the importance of OPS to winning, they began to base their salaries on this broader measure of what a player does at the plate to help his team win.

The variable stolen-bases-per-game is also included in the hitter's salary equation. Demmink (2009) completed a comprehensive study that estimated the value of stealing bases to winning games. His research observed that stealing bases was a worthwhile risk and, if successful, helped a team win an additional 3.65 games per season. Stolen bases can also serve as an instrument for a player's speed. Speed contributes to a team's success on both offense and defense.

Speed enhances a player's defensive prowess since it implies he will be able to cover more ground when fielding batted balls. The desire for speed became more prevalent with the advent of artificial tuff. In 1966, artificial turf was introduced to MLB in the Houston Astrodome. By 1977, seven National League teams and three American League teams played on artificial surfaces. This advancement of plastic grass inspired owners, particularly in the National League, to pay premiums for speedy players. (19) As time passed, artificial turf was phased out of ball parks. Today, there are only three stadiums featuring artificial grass and all of them are in the American League. To capture the impact of speed on a player's productivity, the hitter's salary equation includes the player's stolen-bases-per-game ratio.

Since annual salaries are more closely tied to career statistics than performance statistics of the preceding season (Hoaglin and Velleman, 1995), the career measure of each of these marginal productivity variables is used in the regression analysis of the salary equations.

The second component of the marginal revenue product of labor is the "value of the product." The size of the team's statistical metropolitan area (SMSA) serves as a proxy variable to the value of a win. Research indicates team revenues such as gate receipts, television contracts, and concessions are impacted by the size of their metropolitan market. Higher team revenue leads to greater value of the product. Sommers and Quinton (1982) determined that the marginal revenue product of a win is greater in larger markets than in smaller markets. Scully (1989), using 1984 data, found that team revenue is directly related to market size. Burger and Walters (2003), using 1995 to 1999 data, discovered that market size positively impacts team revenue. Since, in general, a win carries a higher value in a large market than in a small market, holding everything else constant, a player will be paid more by a large market team than by a small market team for a given contribution to his team's performance.

Another determinant of a player's value is the consistency of his contribution to his team. The player who performs regularly will be more valuable than the player who is used sparingly.

Combining the value of the product with the marginal product, we estimate the following salary equation for hitters:

In(salary) (Hitter) = [[alpha].sub.0] + [[alpha].sub.1] ln(slugging [average.sub.i]) + [[alpha].sub.2] ln([OPS.sub.i]) + [[alpha].sub.3] ln(stolen [bases.sub.i]) + [[alpha].sub.4] ln(at bat [pct.sub.i]) + [[alpha].sub.5] ln(years in [majors.sub.i]) + [[alpha].sub.6] ln([population.sub.i]) + [[alpha].sub.7] NL + [[alpha].sub.8] PED + [e.sub.1] (EQ. 1)

The variables ln(slugging average), SA, ln (OPS), and ln(stolen bases) are the logarithms of player i's career slugging average, OPS, and career stolen-bases-per-game average, SBPG, respectively. Logarithms are used to account for the non-linear relationship between average players and superstars (Hoaglin and Velleman, 1995). Each of these performance measures is based on the player's career productivity in the major leagues through the end of the previous season.

A length-of-service variable appears in the salary equation to capture the seniority effect of a player accumulating years of experience. The variable In (years in major), YRMJ, is the logarithm of the number of years the player has participated in the major leagues. The variable ln(at bat percentage) ABPCT represents the logarithm of the player's percentage of team's at bats during his career. That percentage is calculated by dividing the player's career at bats by the product of the number of years that he has played in the major leagues times 5500, the average number of total at bats accumulated by a team over the course of a 162 game season. The variable In(population), the logarithm of the SMSA where a player performs, is added to the salary equation to provide an estimate of the value of a win. The In(population), POP, represents the log of the SMSA in which the clubs operate.

Performance Enhancing Drugs (PED) is included in the salary equation to denote the players who were either named in the Mitchell Report or who have been indentified in additional literature as steroid users. Accused players received a "1" while all others were given a "0."

The final independent variable specified in each salary equation is a dummy variable for membership in the National League, NL. This variable is given the value of "1" if the player is a member of a National League team and "0" if he plays for an American League club.

The 2005 season was selected for a variety of reasons. Data on specific players' PED consumption was not released until 2004. Since that time, more names have leaked out allowing the sample size to grow to 26 of the 278 players. Many of the accused players have since retired. Going back five years improves the sample size. Also, the policy change which began in the 2005 season skews the marginal costs of being caught from a player's perspective. With these factors in mind, salary data from 2005 based on career performance provides the most consistent and recent data available to investigate the impact of PEDs on salaries from a cost benefit perspective.

The value of including other components of salary determination such as years of contract (Marburger, 1994), contract length (Meltzer, 2005; Krautmann and Oppenheimer, 2002), incentive measures (Maxcy et. al, 2002), position, and player race (Johnson, 1992; Sommers, 1990) is understood. While, some of these variables were included in trial estimations, there inclusion clouds the emphasis of measuring the use of performance enhancement drugs on salaries and maintaining a parsimonious model. (20)

Results

Table 1 displays the results of three regressions that estimated the salaries of MLB bargaining hitters for the 2005 season. The estimates posted in Column I use slugging average as a proxy for hitting productivity. Column II shows the results using OPS as an instrument for hitting productivity. And, Column III uses both measures. It appears that owners are still more likely to compensate players based on their slugging as opposed to their ability to get on base with the walk or contribute to the team's success with sacrifice flies or bunts. Power sells tickets.

In their first three years players have very little bargaining power in salary negotiations. While there are some exceptions, such as former international players, the league sets the salary with the player's union and the players are bound to the team. Starting in their fourth season the players begin to negotiate with their teams based on their performance. After eliminating league newcomers, the sample of players falls to 279.

The estimates for market size, log pop, reveal that after accounting for other factors, size of the SMSA is not statistically significant. Players who perform in small or large metropolitan areas are not compensated differently than their performance statistics support. The sign of the population measure is positive but not significant. In each of the equations years in the majors, experience, yields a positive and significant impact on player salaries. The coefficient of .231 is based on an average of 8.3 years in the major league. An additional year in the league would add $207,068 to a player's salary. Players who have been in the league a long time tend to gain fan support and add value to the team.

The at-bat percentage measures a player's consistency. A player with a higher percentage may have spent less time on the disabled list or provided more steady production at the plate. The typical player in the survey accounts for about 6 percent of his team's at-bats. Lead-off hitters and some resilient stars, like Albert Pujols, take 10 percent of the team's at-bats. If a player's percentage of at-bats were to increase from 6 to 8, then he could expect an increase of over $800,000 in his salary. Owners reward consistency and reliability with higher salaries. In each of the three equations, stolen bases per game are not significant; this may be a result of the transition from artificial turf to grass. While speed may help teams win, holding other factors constant, speed is not rewarded with financial compensation. There are no statistically significant differences in salaries between leagues. The NL dummy variable is insignificant in each equation.

Since Moneyball shook the baseball world by revealing inefficiency in the market for players, many studies have abandoned the slugging average for determining player salaries and replaced it with OPS. In this study using the 2005 sample, the slugging average appears to explain salary levels better than the OPS. The coefficient of the log SA is 3.44. Therefore, if a player's slugging average were to increase from the survey average 429 to 529, his move to stardom would result in an over $2 million increase in annual salary. The r-squared using the Column I equation which includes slugging average is .82, while the r-squared of Column II using the OPS is .75. When both measures of player productivity are included in the model the slugging average is significant and the OPS is not. It appears owners, agents, and players continue to value slugging average during salary negotiations.

Nearly 10 percent, 26, of the 279 players in the survey have been named or suspended for use of performance enhancing drugs. Obviously, this number may not reflect the true pandemic of steroid use during the 1995-2004 home run era. In this study, only players who have been formally accused were assigned a "one" while all other players were given a "zero." In each of the equations, the coefficient of the PED variable is positive and significantly different from zero. Players who have used steroids have earned higher salaries than players with comparable performance statistics who have not used steroids.

Of course, there is some interaction between steroids and the other variables in the salary equation which may cloud the specific impact of PEDs on player compensation. In a separate regressions, the impact of PEDs was estimated on two performance measures along with All-Star appearances (see Table 2). Using a simple model of

ln[(SA).sub.i] = [[alpha].sub.0] + [[alpha].sub.1] ln(slugging [average.sup.o i]) + [[alpha].sub.1] ln(years in [majors.sub.i]) + [[alpha].sub.1] PED + e (EQ. 2)

Where ln(SA) is the log of the player's slugging average, ln(slugging [average.sub.o i]) is the player's slugging average in his rookie year, and PED denotes the player's who were indicted for use of performance enhancing drugs. (21) The same model was estimated using the OPS as the dependant variable. A third equation evaluated the correlation between All-Star Appearances (ASA) and PEDs.

PEDs were shown to be positively correlated with slugging average but no correlation was found between PEDs and OPS. PEDs impact salaries through increases in slugging average. (22) The data also shows PEDs are positively correlated with allstar appearance. In 2004, 40 percent of the all-stars starters either admitted to or have been formally accused of using PEDs. In fact, of the 22 MVP awarded between 1995 and 2005, eight of the eleven American League winners were implicated for using PEDs, and six of the eleven National League winners were indicted on PED use.

The impact of steroids on salaries can be determined using the averages for each of the independent variables along with the PED dummy. Combining the coefficients of the equation estimates in Column I of Table 1 with the averages from each variable, it was determined that the average salary of the players in the survey was $2.4 million in 2005. When the value of the PED variable "1" was inserted in the equation, the estimated salary increased to $3.1 million for the season. To test for consistency, a second less direct approach was employed to estimate the impact of PEDs on player salaries. Since the PEDs increase slugging average (SA) and slugging average is positively correlated with salaries, one would expect PEDs to increase salaries through their impact on SA. The SA without steroids was .429, with steroids this rose to .460. This increase in slugging average pushed the average salary from $2.4 million to $3.07 million. Using either approach, it appears that steroid use adds approximately $700,000 to the average player's salary. If we view this estimate in terms of percent increases, steroids bump salaries by about 29 percent.

Given the interactive effect of steroids on other factors that contribute to player salaries and the potential selection bias of the survey, it is difficult to pinpoint the impact that steroids alone have on wages. Yet, as an exercise, Manny Ramirez's career statistics in 2005 are implemented into the salary equation to estimate his predicted salary. With the inclusion of his PED use (a dummy value of 1) he should earn $15.6 million for the season. Without the steroid dummy his salary would have been $12.1 million. In Manny Ramirez's case the model estimates that steroids contributed $3.5 million to his earnings. His actual salary was $22 million which provides one reason why the Boston Red Sox were willing to trade to him to the Los Angeles Dodgers and very few teams were willing to pay Ramirez his asking price. In another example, using the statistics of Johnny Damon, a non-steroid using player, the model estimates that he should have earned $4.6 million in 2005. PEDs would have increased his salary to $5.9 million. Damon's actual salary was $8.2 million. Damon had a difficult to measure on-the-field presence that appealed to the fans. He and his agent were able to capitalize on his popularity.

Conclusion

This paper discusses the marginal benefits and marginal costs of players consuming performance enhancing drugs. After the strike of 1994 baseball, owners were committed to revitalizing MLB. The strike damaged the image of the players causing fans to scatter and league attendance to fall. In 1998, the race to beat Roger Maris' single season home run record sparked a new power era in baseball. Fans were captivated by the resurgence of the long ball. The stadium seats were once again filled, television sets were tuned in, and team profits rose. With no official drug policy in place, owners turned their heads as the players juiced up for the next game.

As juiced up players landed lucrative contracts, they fully recognized how their new and improved power hitting supplemented their salaries. Using career data accumulated through 2005, steroid use was found to increase the average player's slugging average from .428 to .460, which led to an approximately $700,000 increase in the average steroid-using-player's salary, a 29 percent increase. The expected marginal benefits of PEDs appeared to outweigh the costs, and the players acted accordingly to pad their pockets. But eventually the purity of the game came into question, and the owners and players were forced to address the steroid issue. They joined together to increase the costs of using steroids by initiating additional testing and stiffer penalties for violators. These additional costs extended beyond salary reductions and fines, to the legacy of the steroid user.

The hope is that MLB has put this "steroid era" behind them. This case should emphasize that ethical behavior is rewarded in the long run, and unethical behavior has, at the very minimum, long term repercussions. The penalties authenticated in the new anti-drug policy of MLB should discourage future players from partaking in the type of behavior that enveloped some of the best players in the game during the "steroid era."

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Krautmann, Anthony C. and Margaret Oppenheimer. "Contract Length and the Return to Performance in Major League Baseball." Journal of Sports Economics 1 (Feb. 2002): 6-17.

Marburger, Daniel R. "Bargaining Power and the Structure of Salaries in Major League Baseball." Managerial and Decision Economics 5 (Sep.-Oct. 1994): 433-441.

Maxcy, Joel G., R.D. Fort, and A. C. Krautmann. "The Effectiveness of Incentive Mechanisms in Major League Baseball." Journal of Sports Economics 3 (Aug. 2002): 246-255.

McMurrian, Robert C. and Erika Matulich (2006) "Building Customer Value And Profitability With Business Ethics," Journal of Business and Economics Research. Vol. 4, No. 11, p. 11-18.

Meltzer, Josh. (2005). "Average Salary and Contract Length in Major League Baseball: When do they Diverge?" Abstract. Stanford University Department of Economics http://economics. stanford.edu/files/Theses/Theses_2005/Meltzer.pdf, retrieved September 8, 2010.

Pantuosco, Louis J., Stone, Gary L. (2010). "Babe Ruth as a Free Agent: What the Old-Time Greats Would Earn in Today's Labor Market for Baseball Players," The American Economist. Forthcoming Fall. Vol. 55, No. 2.

Schall, Teddy and Gary Smith. Career Trajectories in Baseball. Chance. Fall 2000, pgs. 35.38. http://www.economics.pomona.edu/Gary Smith/BBcareers/careers.html. retrieved June 8, 2010.

Scully, Gerald W. The business of Major League Baseball. Chicago: University of Chicago Press (1989).

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Staudohar, Paul D. (2005). "Performance-Enhancing Drugs in Baseball" Labor Law Journal, vol. 56(2), p 139-149.

Tobin, Roger (2008). "On the Potential of a Chemical Bonds: Possible Effects of Steroids on Home Run Production in Baseball," American Journal of Physics vol. 76 p. 15-20.

Yates, Phillip A. (2008) "Estimating Situational Effects on OPS," Journal of Quantitative Analysis in Sports: Vol. 4: Issue 2 Article 2.

Data References

http://sports.espn.go.com/mlb/news/story?id=1760890

http://www.baseball-almanac.com/players/player.php?p=anderbr01

http://www.baseballchronology.com/baseball/Teams/Background/Attendance/

http://www.baseballssteroidera.com/bse-list-steroid-hgh-users- baseball.html

http://www.baseball-reference.com/players/

Notes

(1.) http://goodmenproject.com/sports-2/all-steroid-steam-brady-anderson/

(2.) http://www.worldlawdirect.com/forum/law-news/ 33765-does-mark-mcgwire-deserve-further-pun ishment.html

(3.) After adjusting for inflation the $1.2 million in 1994 dollars equates to $1.75million in 2010 dollars.

(4.) http://www.ballparksofbaseball.com/attendance. htm

(5.) Bay Area lab owner's troubled past--Success coupled with tax difficulties and unraveling family life Mark Fainaru-Wada, San Francisco Chronicle, 10/26/03

(6.) Jose Canseco (2005) Juiced: Wild Times, Rampant Roids, Smash Hits & How Baseball Got Big. Harper Collins Publishers Inc. New York, NY

(7.) Complete Mitchell Report can be found at http://files.mlb.com/mitchrpt.pdf.

(8.) http://www.bizjournals.com/sanfrancisco/stories/ 2002/05/13/newscolumn3.html

(9.) http://articles.latimes.com/1998/sep/10/business/ fi-21250

(10.) http://www.bloomberg.com/apps/news?pid=new sarchive&sid=agT4P0sEgdRM

(11.) http://sports.espn.go.com/mlb/news/story?id=2074289

(12.) http://www.sportsbusinessdaily.com/Daily/ Issues/2009/02/Issue-98/Sponsorships-Advertis ing-Marketing/The-A-Rod-Story-Steroid-Alle gations-Could-Hurt-Current-Deals.aspx

(13.) That is why Derek Jeter is the most marketed MLB player.

(14.) http://nbcsports.msnbc.com/id/29083443/

(15.) http://sportsillustrated.cnn.com/specials/fortunate 50-2010/index.html

(16.) http://www.syracuse.com/today/index.ssf/2009/ 07/manny_ramirez_returns_from_sus.html

(17.) http://www.draftdaysuit.com/2009/09/12/mlb-will-not-punish-alex- rodriguez-for-steroid-use/

(18.) Lewis, Michael. Moneyball: The Art of Winning an Unfair Game, WW Norton & Company, New York 2004

(19.) http://www.andrewclem.com/Baseball/turf.html

(20.) Table 3 contains the equation for pitchers in 2005. The results show no significant salary difference between the 22 pitchers who were accused of steroid use and the other 261 pitchers. See Pantuosco and Stone (2010) for justification of the pitcher salary equation. Including the other variables, such as position, was not significant and did not impact the estimates.

(21.) The rookie year was determined by the first year the player appeared in more than 15 games and had more than 50 at-bats.

(22.) See Tobin, 2008 for a detail analysis of the impact of steroids on home run production.

by Louis J. Pantuosco

Professor of Economics, Winthrop University. pantuosco@winthrop.edu
TABLE 1.
Regression Estimates of Log Salary for Bargaining
Hitters, 2005

              Bargaining    Bargaining    Bargaining
                Hitters       Hitters       Hitters

intercept      -4.98 ***      2.99 ***      -5.13 ***
               (0.99)        (0.67)         (1.03)
log pop         0.087         0.089          0.088
               (0.06)        (0.07)         (0.06)
log yrmj        0.231 **      0.326 ***      0.235 **
               (0.10)        (0.12)         (0.10)
log sbpg        0.019        -0.028          0.019
               (0.02)        (0.03)         (0.02)
nl             -0.019        -0.056         -0.022
               (0.04)        (0.04)         (0.04)
log abpct       0.976 ***     1.42 ***       0.971 ***
               (0.10)        (0.11)         (0.11)
Log SA          3.44 ***                     3.39 ***
               (0.34)                       (0.35)
Log OPS                       0.526 ***      0.098
                             (0.19)         (0.17)
ped             0.112 *       0.187 ***      0.109 *
               (0.06)        (0.07)         (0.06)
[R.sup.2]       0.82           .75            .82
DF               279           279            279

Standard errors in parentheses

* significant at the .10 level

** significant at the .05 level

*** significant at the .01 level

TABLE 2.
Regression Results: The Impact of Performance
Enhancing Drugs

                LSA         OPS         ASA

intercept    1.76 ***      2.26 ***   -10.9 ***
            (0.019)       (0.035)      (2.54)
PED           .0279 ***    0.033        1.79 ***
            (0.009)       (0.022)      (0.33)
log yrmj     0.084 ***     0.049**      4.31 ***
            (0.006)       (0.016)      (0.51)
log SAo      0.256 ***     0.182 **
            (0.03)        (0.076)
log OPS                                 2.79 ***
                                       (0.88)
[R.sup.2]     .73           .27

** significant at the .05 level

*** significant at the .01 level

TABLE 3.
Regression Estimates of Log Salary for Bargaining
Pitchers, 2005

                   Bargaining Pitchers

intercept            2.95 ***
                    (0.28)
log pop              0.200 ***
                    (0.07)
log yrmj             0.584 ***
                    (0.09)
log innings pct      0.936 ***
                    (0.08)
nl                  -0.045
                    (0.04)
log sw ratio         0.850 ***
                    (0.17)
ped                  0.073
                    (0.07)
RZ                   0.75
DF                 283

Standard errors in parentheses

* significant at the .10 level

** significant at the .05 level

*** significant at the .01 level
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