A Look at Women’s Participation in Sports in Maryland Two-Year Colleges

ABSTRACT

Much research has been conducted on college athletics.  The populations studied most often are four-year, NCAA member institutions.  In higher education, 40 percent of the institutions in the United States are two-year colleges.  These two-year colleges enroll more than ten million students annually (IPEDS, 2002).  Although 56 percent of the students enrolled in these institutions are women, little research exists that examines the participation in two-year college athletic programs.  The purpose of this study was to examine the degree of participation and opportunity for female students and coaches at two-year colleges within the state of Maryland.  With 18 institutions reporting participation data, results of this study showed that female students participate in far fewer numbers in Maryland than do male students.  Results of this study also showed that relatively few women hold administrative or coaching positions within existing sport programs.

INTRODUCTION

Over the last thirty-two years, female students have seen substantial gains in sports participation opportunities.  These gains came as a result of the federally mandated legislation know as Title IX of the Education Amendments of 1972.  Since the passage of this legislation, opportunities for girls and women to compete in sports have increased dramatically.  According to a longitudinal study by Acosta and Carpenter (1996), participation opportunities for women athletes by the late 1990’s hit an all-time high.  Increased female athletic participation is evident at all levels of sport, including high schools, colleges, and universities (NFSHSA, 2001; NCAA, 2000).

Much research (Acosta & Carpenter, 1996; Carpenter, 2003; Fitzgerald, 2003; Kramer & Marinelli, 1993) has been conducted with regards to college athletics, opportunity, and participation.  The populations studied most often are four-year, National Collegiate Athletic Association (NCAA) member institutions.  Within higher education, the two-year (also referred to as community or junior) college is taking on a greater significance.  According to a study by the U.S. Department of Education (2002), 40% of the institutions of higher education in the United States are now two-year colleges.  These two-year colleges enroll more than 10 million students annually.  Many of the athletes at these two-year colleges go on to star in major four-year athletic programs (Douchant, 2002). Although 56% of the students enrolled in these institutions are women, little research exists that examines the two-year college athletic program (Smith, 1997).  Thus, the specific purpose of this study was to examine the degree of participation and opportunity for female students and coaches at two-year colleges within the state of Maryland.

Overview of Title IX

The impetus for the change in opportunity and participation for females can be attributed to the passage of the Education Amendments Act of 1972 and its Title IX provision.  Title IX was enacted to help remedy past discriminatory practices. Title IX of the Educational Amendments Act of 1972 states that: “No person in the United States shall, on the basis of sex be excluded from participation in, or denied the benefits of, or be subjected to discrimination under any educational program or activity receiving federal aid” (Title IX, n.d., para. 1).

The passage of Title IX and the threat of litigation have resulted in the vast improvement in opportunities for girls and women in sport.  With regard to intercollegiate athletics, three primary areas determine if an institution is in compliance: athletic financial assistance, accommodation of interest and abilities, and equity in other specified program areas.

A three-part test for compliance is used in determining whether the required number of participation opportunities is being provided.
An institution must show:

  • that the intercollegiate participation opportunities for its students of each sex are substantially proportionate to its male and female undergraduate enrollments; or
  • a history and continuing practice of program expansion responsive to developing interests and abilities of members of the “underrepresented sex”; or
  • that the interests and abilities of the “underrepresented sex” are fully and effectively accommodated by the existing program (Carpenter, 2003).

Compliance is established when an institution can demonstrate that it has satisfied any one of these three tests.

Title IX requires that, for an institution to be in compliance, the interest and abilities of both sexes must be accommodated.  This includes the institution’s obligation to provide a sufficient number of participation opportunities for male and female athletes.  “Participation opportunities” are defined as the number of slots on teams as determined by the number of athletes on each team.  This definition is important because athletic directors at two-year institutions often define participation by the number of teams offered and not by the number of participants (Mumford, 1998).  According to Title IX policy interpretations and recent judicial decisions, participation in the intercollegiate sports program by women should be substantially proportionate to the number of women enrolled at the given institution.  For example, if 70 percent of the students enrolled at an institution are women, then approximately 70 percent of the students participating in intercollegiate athletics should be women (Lichtman, 1997).

The impact of Title IX policy has been felt a great deal more at the four-year level than at the two-year level of college athletics (Mumford, 1998).  Although many students have benefited from this federal policy, the consequences of this policy have also been unpleasant to many institutions.  Institutions have been subjected to expensive court battles as a result of lawsuits filed by female student-athletes and coaches.  Litigation from lawsuits has risen dramatically.  The costs and consequences of these lawsuits have had a negative impact on institutions.  Institutions found in violation of Title IX have been forced to pay expensive monetary damages, attorney fees, and program support funding.  These awards have been reported as high as $1 million (Fitzgerald, 2003).

Courts have also taken more control of athletic decision making.  They have ordered specific actions, such as hiring coaches and providing practice and other facilities.  In some instances, the litigation of one Title IX claim has generated even more claims (Kramer & Marinelli, 1993).

Research Questions

With the goal of exploring women’s participation in collegiate sports in mind, the purpose of the study was to determine the degree of participation and opportunity at two-year colleges within the state of Maryland for female student athletes and coaches.
Specific research questions which guided the study were:

  • What does the leadership, in terms of the gender of administrators, and coaches, look like at these institutions?
  • At what rates do women and men participate in two-year collegiate athletic programs?  Is their participation in proportion to that of the general student body population or are women underrepresented?
  • Are Maryland two-year colleges in compliance with Title IX?  If so, how?

Methodology

Respondents

Respondents for this study were athletic directors of all two-year colleges with membership in the Maryland Junior College Athletic Conference (MD JUCO).  The MD JUCO is comprised of 18 two-year colleges in the state of Maryland.

Instrumentation

A survey instrument was used in this study to gather demographic data on the leaders (athletic directors and coaches) of two-year colleges in the state of Maryland.  The survey instrument consisted of 33 items containing both closed-ended and open-ended questions.  The survey instrument was also designed to collect institutional programmatic information about coaching and intercollegiate sport opportunities.  Data was gathered for comparative purposes only.  Confidentiality of responses was guaranteed to all respondents.  The overall return rate of the survey was 83 %, which included responses from 15 subjects.

Procedure

Athletic directors (n=18) employed at degree-granting two-year colleges in the state of Maryland (MD JUCO) were mailed a cover letter, consent form, questionnaire, and a stamped self-return envelope.  Three weeks following the initial mailing, a reminder letter, survey, and stamped self-return envelope was sent to all subjects who had not responded (non-respondents).

Another method of gathering data was the review of related documents and archival records.  Documents used to gather data included the MD JUCO website, college catalogs, minutes from MD JUCO meetings, National Junior College Athletic Association (NJCAA) Student Eligibility Forms, the NJCAA 2000-2001 Handbook & Casebook, and the NJCAA website. This method of data gathering provided complementary information to that obtained in the surveys.  In this manner, the researcher could triangulate and cross-check data provided by the survey (Wolcott, 1994).

RESULTS

Administration

The gender of athletic directors in Maryland two-year colleges included 16 men (89%) and two women (11%).  The ethnic background of the athletic directors included 17 Caucasian (94%) and one African-American (6%).

Participation

Respondents were asked to identify the number of teams offered at their institution for men and women.  They were also asked to indicate the total number of student-athletes that participated on those teams.  On average, two-year colleges in Maryland sponsored seven teams per institution (four teams for men and three teams for women).  On average, 96 student-athletes participate across those seven teams (65 male and 31 female). Respondents stated that 134 teams were offered by their institutions.  Of the 134 total teams, 69 teams (51%) were offered for men and 65 teams (49%) were offered for women.  A total of 1,719 student athletes participated on those 134 teams.  Of that number, 1166 participants (68%) were male and 553 participants (32%) were female.

Coaches

Respondents were asked to identify the number of coaches at their institution.  They were also asked to specify whether these coaches were employed on a full or part-time basis.  On average, colleges employed seven coaches per institution. Respondents stated that 117 coaches were employed at Maryland institutions.  Of the 117 total coaches, 22 coaches (19%) were employed full-time at the institutions and 97 coaches (81%) were employed on a part-time basis.

DISCUSSION

This study examined the participation opportunities for female students and coaches in Maryland two-year colleges. The criteria used to measure participation opportunities were based on Title IX guidelines. With regards to Title IX guidelines, the first test (Proportionate Athletic Opportunity) is referred to as a “safe harbor.” The safe harbor test is the measuring stick most often used by institutions to show Title IX compliance (Davis, 2003).

To demonstrate compliance, Maryland two-year institutions must show that the numbers of male and female participants in its intercollegiate sports program are substantially proportionate to its male and female enrollments. If this is the case, no further inquiry needs to be made.

Maryland JUCO institutions do not meet the requirements for compliance based on this first test.  Women comprise 61% of the total enrollment in the Maryland Community College institutions. Men comprise 39% of the total enrollment (see Figure 1 – Appendix A). Women comprise 32% of the total student-athlete population. Men comprise 68% of the total student-athlete population (see Figure 2 – Appendix B). All of the two-year colleges, all 18 institutions, had more male than female participants.

Title IX obligates institutions to provide a sufficient number of participation opportunities for individuals of each sex.  Looking at the number of teams offered gives the appearance of near compliance.  Of the teams offered for students, 49% of the teams (n=65) are for women and 51% of the teams (n=69) are for men.  Looking at the number of participants on each team shows a much different picture. Looking at the number of participants shows that Maryland two-year colleges are not in compliance.  Of the number of participants on the teams, 32% of the participants (n=553) are female and 68% of the participants (n=1166) are male.

One aspect that stands out in this data is that the institutions have relatively small athletic programs.  As a result, they offer very limited opportunities for men or women to participate in sports.  The number of sport offerings was small in comparison to four-year institutions and high schools in the state.

A second important observation from the data is that most of the two-year colleges in Maryland employ their coaches on a part-time basis, as these coaches often hold other full-time jobs outside of the college.  Of the head coaches at two-year colleges in the state, 81% are part-time.  Given the limited resources of many two-year colleges, it is economically advantageous to hire coaches in this manner.  Coaches in two-year colleges are often paid by stipend or released time from teaching or administrative duties.  In some cases, the amount of the stipend is set for a specific coaching position with no relationship to the coach’s background or experience (Bichy, 1997).

The majority of the women’s teams in Maryland two-year colleges are coached by men.  According to the Equity in Athletics Disclosure Act of 1998 (n.d.), women comprise only 23 % of the coaches in the Maryland JUCO. This is significant because the majority of the female student-athletes in the state never get the opportunity to be coached by a woman.  The exclusion of women from the coaching ranks can provide fuel and support for the myth that male coaches are more capable than female coaches (Mumford, 1998).

Concluding Comments

The purpose of this study was to examine the participation of women in sports in Maryland two-year colleges.  Current national participation trends at the high school and college level show that women’s sports participation has increased dramatically and women are participating in sports in record numbers.  However, women remain underrepresented.  In Maryland two-year colleges, that is the case as well.  Female students participate in far fewer numbers in Maryland than do men.  In this area, Maryland’s two-year colleges are not in compliance with Title IX.

More concerns may arise as further examination is made in the areas of administration and coaching.  In these two areas of leadership, the two-year colleges in Maryland have maintained the status quo.  The athletic directors and coaches of these two-year colleges remain mostly Caucasian and mostly male.  Although women have made adequate gains on the playing field, they continue to be left behind in a dramatic fashion, when it comes to coaching or leadership opportunities.  In these areas, Maryland’s two-year colleges are not performing well at all.

References

Acosta, R.  & Carpenter, L.  (1996). Women in intercollegiate sport: A longitudinal study – nineteen year update, 1977-1996.  Unpublished manuscript, Brooklyn College: Brooklyn, NY.

Bichy, T.  (1997). Athletic/gender equity.  Unpublished manuscript, Montgomery College: Rockville, MD.

Carpenter, L.  (2003). Gender equity: Opportunities to participate.  In D. Cotton & J. Wolohan (Eds.), Law for Recreation and Sport Managers (pp. 548-558).  Dubuque, IA: Kendall/Hunt Publishing Company.

Davis, M.  (2003, March 5). Title IX review concludes with competing reports. Retrieved October 1, 2004, from the Education Week website: http://www.edweek.org

Douchant, M.  (2002, March 25).  Junior college jewels. Retrieved October 6, 2004, form the College Sporting News website: http://www.collegesportingnews.com

Equity in Athletics Disclosure Act of 1998 (n.d.).  Retrieved November 1, 2004, from U.S. Department Education, Office of Postsecondary Education website: http://ope.ed.gov/Athletics/index.asp

Fitzgerald, M.  (2003). Gender equity: Coaching and administration.  In D. Cotton & J. Wolohan (Eds.), Law for Recreation and Sport Managers (pp. 548-558).  Dubuque, IA: Kendall/Hunt Publishing Company.

Higher Education General Information Survey.  (2002, November).  Retrieved February 21, 2004, from the U. S. Department of Education, National Center for Educational Statistics website: http://www.nces.ed.gov/programs/digest/d02/tables/dt243.asp

Integrated Postsecondary Education Data Systems.  (2002, December).  Retrieved February 21, 2004, from the U.S. Department of Education, National Center for Educational Statistics website: http://www.nces.ed.gov/programs/digest/d02/tables/dt243.asp.

Kramer, W. & Marinelli, M.  (1993, September).  Title IX in intercollegiate athletics: Litigation risks facing colleges and universities.  Washington, DC: Baker & Botts L. L. P.

Lichtman, B.  (1997). Playing fair: What school leaders need to know about title ix and gender discrimination in athletic programs.  The American School Board Journal, 184 (8), 27.

Mumford, V.  (1998). Teams on paper: Title IX compliance in the Maryland junior college athletic conference.  Ann Arbor, MI: UMI

National Collegiate Athletic Association.  (2000, June 7).  NCAA sports participation numbers show largest increase in fourteen years [On-line].  Available: http://www.ncaa.org/releases/makemenu.cgi?research.

National Federation of State High School Associations.  (2001). Sports participation survey [On-line].  Available: http://www.nfhs.org.

Smith, H.  (1997, November). Association report: 2YC3 a federal perspective on community colleges.  Journal of Chemical Education, 74 (11), 1264.

Title IX of the Education Amendments of 1972. (n.d.).  Retrieved February 19, 2004, from U.S. Department of Labor, Office of the Assistant Secretary for Administration and Management website: http://www.dol.gov/oasam/regs/statutes/titleix.htm

Wolcott, H.  (1994). Transforming qualitative data: Description, analysis, and interpretation.  Thousand Oaks, CA: Sage.

APPENDIX A
General Enrollment by Gender in Maryland Two-Year Colleges
Figure 1. Enrollment by Gender
Figure One

APPENDIX B
Total Athletes on Teams by Gender in Maryland Two-Year Colleges
Figure 2. Total Athletes on Teams
Figure 2

Necessary Education for the Success of Athletics Directors: NCAA Presidents’ Perceptions

Consumer Discrimination in the NBA Trading-Card Market

Submitted by: Philip Broyles & Bradley Keen

Abstract

This research examines consumer discrimination in the NBA trading-card market. Using a sample of 298 NBA trading cards for the 1991-92 season, we find that race does not affect whether a trading cards sell above the common-player price. This is consistent with previous research on NBA trading cards. However, it was found that among players with common-player priced cards (average players), blacks out perform whites in points-per-game and assists-per-game. Further research is needed to see if black-white performance differences are related to discrimination in entry or retention in the NBA.

Introduction

Of the major professional sports, basketball may seem the least likely place for racial discrimination. Since its integration in the 1940s, professional basketball has achieved the highest level of African American representation of the major professional sports in the United States. Today over 80 percent of NBA players are African American. Moreover, many of the most celebrated athletes today, such as Michael Jordan and Kobe Bryant, are African American basketball players. It is therefore surprising that numerous studies provide evidence of discrimination in the NBA labor market.

Labor market discrimination is defined as unequal treatment of equally qualified workers. A great deal of research on labor market discrimination has focused on the racial pay differences of NBA athletes (see Kahn, 2000, 1991). The results vary greatly. Rockwood and Asher (1976) and Mogul (1977, 1981) found no significant difference in white and black player’s salaries in the 1970s. Using a sample from the early 1980s, Scott et al. (1985) also found no relationship between player’s race and earnings. These studies, however, were based on small samples of athletes (N<30). Studies with larger samples from the 1980s consistently show a significant relationship between race and earnings. Kahn and Sherer (1988) found that white players earned 21-25 percent more than their black counterparts. Similarly, Wallace (1988) found that white players earned 18 percent more than black players and Koch and Vander (1988) found the difference to be 12 percent. Recent research by Hamilton (1997) suggests that differences in pay between black and white players may be disappearing. Using a sample of players from the 1994-95 season, Hamilton found that black players out-earned whites through the 75th percentile but at the top (90th percentile) whites were paid slightly more than blacks.

Kahn (2000) suggests that consumer discrimination may explain some of the racial pay gap observed in basketball. If fans are prejudiced against African Americans, teams may hire more white players or pay white players more. There is evidence from the 1980s that is consistent with this hypothesis. Numerous studies show that black players lower revenues or attendance (Kahn, 1991). For example, Kahn and Sherer (1988) found that during the 1980-86 period, white players generated as many as 13,000 additional fans per year. And other researchers have found that the racial makeup of NBA teams was similar to the racial composition of the area in which they were located (Burdekin and Idson, 1991; Hoang and Rascher, 1999). More recent research suggests that consumer discrimination may be on the decline. Dey (1997) found that in the 1987-93 period, white players only brought in an average of 60 additional fans per season.

Few studies have examined consumer discrimination more directly. One exception is a study by Stone and Warren (1999), which examines the price of NBA players’ trading cards. Using a sample of 258 NBA players from the 1976-77 season, they found that the price of NBA trading cards did not vary by player’s race. Their methodology, however, was based on the assumption that consumer discrimination is pervasive throughout the ability distribution. It is possible that card collectors only discriminate against the star athletes. Consumers may have discriminatory preferences for white stars but no real preference among black and white athletes of average ability. If this is the case, then the trading cards of white stars will be valued more than the cards of black stars. This hypothesis is consistent with Hamilton’s (1997) research on earnings discrimination, which showed that white players only had an advantage over black players at the superstar level-at the top of the earnings distribution. To further understand this issue, we examine a sample of 298 NBA trading cards produced in 1992.

Data and Methodology

Our sample consists of a complete set of Fleer NBA trading cards issued in 1992. We picked Fleer over other brands because they have been producing basketball cards the longest time and have had NBA production rights since 1986. Specialty cards (coaches, multiple players and so forth) were eliminated from the set, leaving a final sample of 298 cards representing NBA players active during the 1991-92 season-all have since retired. Eighty percent of the trading cards are of black NBA players.

The value of a player’s card is determined largely by the performance of the player. Unlike studies of other labor markets, job performance of professional athletes can be precisely measured. Comprehensive basketball statistics are kept for all facets of the game. In this study, we use multiple measure of performance, including field goal percentage, three-point field goal percentage, free throw percentage, rebounds per game, assists per game, points per game and games played. The performance data was collected from The Official NBA Encyclopedia (2000), which is a comprehensive source on basketball statistics. Additional information was collected from The Sporting News Official NBA Register (2000, 2001).

The value of a player’s card is also determined by the scarcity of the card, which is related to the age of the card and the number of cards. The influence of scarcity on card prices is minimal when a single set of cards is considered because cards from the same set are produced in the same number and are the same age-though there may be some small difference in the actual number of cards in circulation because cards are lost over time. Because we have selected trading cards from a single set, scarcity will not be a major determinant in the price of the cards we are examining.

A couple other factors also affect the value of cards. First, the condition of the card affects the value of player’s cards. Cards in better condition are worth more that others. To control for this effect, we examine cards in mint condition. Second, rookie cards are often worth more than other cards. Cards that mark the debut of a player are highly prized by collectors, especially those of star players. To control for this bias, we use a dummy variable to indicate rookie status. There are 42 (14%) rookie cards in the sample.

Several price guides exist for basketball trading cards. The most comprehensive and respected source for trading card prices is Beckett’s price guide. We use the Beckett 2003 Official Price Guide for Basketball Cards to determine the price for trading cards in mint condition. Most cards sell at the “common player” price, which is the minimum value of a card and is not related to performance of a player. Of the cards in our sample, 213 (71%) have the common-player price, only 85 (29%) are priced higher. The common-player price is $.05 and the maximum mint value for the sample is $2.00. Because a large number of cards in the sample are valued at the common-player price and because there is small variation among those cards priced above the common-player price, we can essentially identify two groups for comparison: average players (those with common-player priced cards) and star players (those with higher priced cards). Therefore, card price is coded as a dummy variable, contrasting common-player priced cards with higher priced cards.

Findings

Table 1 reports the descriptive statistics for the performance variables by race. Overall, there is little difference between the performance of black players and white players, with the exception of points-per-game. Black players score just under two points more per game than do white players. Black players appear to outperform white players slightly in rebounds-per-game and assists-per-game, but the differences are not statistically significant. Black players also play more games, on average, than do white players.

A linear regression was run to see if performance differences between black and white players affected the value of trading cards. Table 2 presents the results for the logistic regression. As the results in Table 2 indicate, three of the major performance variables are statistically significant: rebounds-per-game, points-per-game, assists-per-game. Each of these variables increases the odds that a trading card is worth more than the common-player price. For example, an increase of one point per game increases the odds of a trading card being worth more than the common-player price by 26 percent. Performance variables based on shooting percentages are not significant. Field goal and free throw percentages have no affect on whether cards are worth more than the common-player price. However, the number of games played also increases the odds that a card is worth more than the common-player price. And, as expected, rookie cards are more likely to be priced above common-player price, too.

Consistent with Stone and Warren (1999), race of the player has no significant effect on the value of NBA trading cards in our sample. Although the beta coefficient for race suggests that being white increases the odds that the player’s trading card is worth more than the common-player price, the coefficient is not statistically significant. Trading card enthusiasts do not value white NBA stars more than black stars. These findings lend to the mounting evidence that consumer discrimination may be declining in professional basketball.

Although it appears that consumers do not discriminate against black stars, it is still possible that consumers discriminate against average black players. To explore this issue, we calculated black and white means of performance variables for trading cards that were priced at the common-player price. Table 3 presents the means for the 213 cards that were priced at the common-player price. The results show that average black players outperform white players in points-per game and assists-per-game. The differences are rather small. Black players average almost two more points per game and less than one assist more per game than white players. Nonetheless, it appears that blacks must perform better than whites to retain a place on the bench. This may reflect consumer discrimination. Coaches may keep white players who don’t perform as well to appease white fans. It may also reflect employer discrimination by coaches. Coaches may have higher expectations for black players than for white players. Further research is needed to disentangle these processes.

Conclusion

This research adds to the mounting evidence that consumer discrimination in the professional basketball is on the wane. Similar to Stone and Warren (1999), little evidence was found of discrimination in the trading card market. Trading-card collectors show little preference for white stars over black stars. This may largely be due to the rise of popular superstars like Magic Johnson and Michael Jordan, whose celebrity appeal crosses racial lines. Fans today can identify with, and desire to emulate, black NBA stars.

Future research should examine the role of these performance differences in entry and retention discrimination.

References

  1. Beckett, James (2002), Beckett 2003 Official Price Guide for Basketball Cards, New York: The Crown Publishing Group.
  2. Burdekin, Richard C. K. and Todd L. Idson, (1991) “Customer Preferences, Attendance and the Racial Structure of Professional Basketball Teams,” Applied Economics, 23:179-186.
  3. Dey, Matthew S., (1997), “Racial Differences in National Basketball Association Players’ Salaries: Another Look,” The American Economist, 19 (3):293-318.
  4. Hamilton, Barton Hughes, (1997),”Racial Discrimination and Professional Basketball Salaries in the 1990s,” Applied Economic, 29:287-296.
  5. Hoang, Ha and Dan Rasher, (1997), “The NBA, Exit Discrimination, and Career Earnings,” Industrial Relations, 38 (1):69-91.
  6. Hubbard, Jan., (ed.), (2000), The Official NBA Encyclopedia, New York: Doubleday.
  7. Kahn, Lawrence M., (2000), “A Level Playing Field? Sports and Discrimination,” Pp. 115-130 in William S. Kern (ed.), The Economics of Sport Kalamazoo, MI: W.E. Upjohn Institute for Employment Research.
  8. Kahn, Lawrence M. (1991), “Discrimination in Professional Sports: A Survey of the Literature,” Industrial and Labor Relations Review, 44 (April):395-418.
  9. Kahn, Lawrence M., and Peter D. Sherer, (1988), “Racial Differences in Professional Basketball Players Compensation,” Journal of Labor Economics, 6 (1):40-61.
  10. Koch, James V., and C. Warren Vander Hill, (1988), “Is there Discrimination in the ‘Black Man’s Game’?” Social Science Quarterly, 69 (1) 83-94.
  11. Mogul, Robert G., (1981), “Salary Discrimination in Professional Sports,” Atlantic Economic Journal, 21(3):106-110.
    12. Robert G., (1976), “A Note on Racial Discrimination in Professional Basketball: A Reevaluation of the Evidence,” American Economist, 21 (2):71-71.
  12. Paur, Jeff, David Walton, John Gardella and John Hareas (eds.), (2000), The Sporting News 2001-2002 Official NBA Register, St. Louis: The Sporting News.
  13. Rockwood, Charles E. and Ephraim Asher, (1976), “Racial Discrimination in Professional Basketball Revisited,” American Economist, 20 (1):59-64.
  14. Scott, Frank A., Jr., James E. Long and Ken Somppi, (1985), “Salary vs. Marginal Revenue Product under Monopsony and Competition: The Case of Professional Basketball,” Atlantic Economic Revue, 13 (3):50-59.
  15. Stone, Eric W. and Ronald S. Warren, (1997), “Customer Discrimination in Professional Basketball: Evidence from the Trading-Card Market,” Applied Economics, 31 (6): 679-686.
  16. Wallace, Michael, (1988), “Labor Market Structure and Salary Determination among Professional Basketball Players,” Work and Occupations, 15 (3):294-312.
  17. Walton, David and John Gardella (eds.), (2000), The Sporting News Official NBA Register 2002-2003 Edition, St. Louis: The Sporting News.
TABLE 1. Means for Performance Variables by Race (N=298)
Means Standard Deviation 
Number of Games Played

 

Black

White

712.67

658.24

326.13

328.30

Field Goal Percentage Black

White

.466

.469

.040

.037

Three Point Percentage Black

White

.238

.268

.116

.143

Free Throw Percentage Black

White

.743

.757

.077

.093

Rebounds Per Game Black

White

4.36

4.02

2.48

2.32

Assists Per Game Black

White

2.59

2.12

2.00

1.90

Points Per Game* Black

White

10.75

8.99

4.92

5.00

*Statistically significant difference between means at the .05 level

 

TABLE 2. Logistic Regression Coefficients
Variable Beta Standard Error 
Constant -6.961 4.188
Race .616 .541
Rookie Card 3.436* .649
Center -1.349 .765
Number of Games Played .003* .001
Field Goal Percentage -7.629 7.147
Three-Point Field Goal Percentage 2.164 2.380
Free Throw Percentage .947 3.621
Rebounds Per Game .432* .129
Assists Per Game .278* .111
Points Per Game .228* .064
-2 Log Likelihood 194.781
*p < .01

 

TABLE 3. Means for Performance Variables by Race for Average Players (N=213) 
Means Standard Deviation 
Number of Games Played

 

Black

White

629.59

570.82

316.15

306.85

Field Goal Percentage Black

White

.462

.463

.042

.036

Three Point Percentage Black

White

.224

.246

.115

.146

Free Throw Percentage Black

White

.737

.738

.079

.096

Rebounds Per Game Black

White

3.76

3.68

2.00

2.09

Assists Per Game* Black

White

2.19

1.67

1.67

1.50

Points Per Game* Black

White

9.10

7.37

3.89

4.16

*Statistically significant difference between means at the .05 level

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