Racial Salary Discrimination in the NBA 2010-2011 Season

     In my research paper I plan on analyzing data collected from the NBA to try and see if there was racial salary discrimination in the NBA in the 2010-2011 season.  Beginning in the late 1970s, many studies have been conducted to try and answer this question.  In reading the attempts, it seems that when the first studies began, this racial salary discrimination did exist in the NBA.  However, as time has gone by, the studies have reported varying findings; Some saying that it exists, while other findings expelling this notion.

     According to NBA.com, the NBA is currently composed of about 83.7 percent non-white players, leaving just 16.3 percent of the NBA being white.  This number is staggering considering the role of racial equality in our everyday lives.  However, the NBA is a profit maximizing company, and the teams in the league are also profit maximizing.  Because of this, the best players are paid the most money because of the revenue they will bring to their organizations.  Because of this, I plan on comparing the salaries of bench players in hopes of generalizing the performance statistics and focusing on the differences in the race of these individual players compared to others.


Poor Economics, Chapter 5

     Chapter 5 of Poor Economics analyzes the role of contraceptives in economies around the world.  It is interesting to read the chapter and see how a woman’s decision to use/not use a contraceptive is predominantly shaped by other social pressures that one would not normally think of.  Whether a woman was given a voucher for contraceptives in front of her husband or alone is an example of a scenario in  which these social pressures surface.

     The most noteworthy statistic I came across in the reading was on page 120 which stated that “in China more than half the elderly lived with their children in 2008, and that fraction increases to 70 percent for those who had seven or eight children.”  Perhaps the text is correct when saying that this is very uncommon in the western world, which is why it caught my attention.  It may be a stretch, but after reading this statistic I think it would be interesting to see if living with younger generations can actually increase one’s life.

     To begin, I would use cross-sectional quantitative data to begin my regression.  My regression would include a dummy variable such as health at time beginning to live with family (1-5), along with other variables including age, number of children, and if they were married or not.  My regression would look something like

                               “YAddedYears= A + B1age+B2PrevHealth+B3Marriage+B4#ofChildren+Ei”

     I would expect my dummy variable to have a positive relationship with the independent variable because I think that the better health you had when first moving into the house would one would stay healthier longer and thus, the years added to their lives would increase.  I’m not entirely sure I would actually be able to measure a variable such as this one but it definitely would call into question if younger generations can keep the elderly younger and healthier for a longer period of time.

Racial Discrimination in Pro Sports


The above article uses Nielsen television ratings to see if there is a discrimination in professional sports by which teams get the most television time and also how much companies spend on advertising during the games being televised. Specifically, “in this study, we examine whether patterns of television viewing are systematically correlated with the racial composition of teams in the National Basketball Association (NBA).”

The article begins by citing other previous studies of sports and racial discrimination, highlighting that many of the studies in the 1980s dealt with the price of non-white vs. white baseball cards.  Also previously mentioned and studied is the negative correlation between the amount of African American people in the surrounding area of an arena and the attendances at that arena’s NBA team’s games.  In this study, the authors found that the advertising revenue value of whites increases with the size of the viewing market.  This was also seen in a previous study that the salaries of white NBA players tend to increase more rapidly than those of black players as the population of the local metropolitan area increases. However, in this study there is a large population effect. “According to our estimates, in moving from the smallest NBA market (San Antonio) to the largest market (New York City), the advertising revenue gap between whites and blacks widens by nearly 52% of the league-wide salary average.”  These results were almost double what the hypothesis was.

This article will be helpful in finding out if there is a racial discrimination in NBA salaries by thinking about the market size of the cities where the teams are.  A smaller market team will have to pay their players less, because they have less capital than the larger teams.  Thus, I might have to weed out the largest market teams and the smallest to settle upon a mean that would not hinder my results.

Poor Economics: Higher Education

In Poor Economics, Banerjee and Duflo examinethe role of education in other countries.  Overall, the main issue is that the level of quality education is drastically lower than where it should be.  To fix this, there are two sides to this argument: Supply-siders argue “that we have to find a way to get into a classroom, ideally taught by a well-trained teacher, and the rest will take care of itself” (73).  Demand-siders counter that “when the benefits of education become high enough, enrollment will go up, without the state having to push it” (76).  While the two sides debate, the parents of these children suffering from inadequate education only care about it if their child’s schooling will lead to a government job.  believe an education is only worthwhile if it will eventually lead to a government job. In fact, even the governments in these areas do not feel the need to revamp the education system and hire better teachers.

While reading this chapter, I thought about an article I had read in Time Magazine last month, http://www.time.com/time/nation/article/0,8599,2043312,00.html.  In it, the Andrew J. Rotherham looks at the international tests given to countries across the world and how in the results the United States lagged in the middle of the pack.  However, Shanghai, China received the highest grades, thus producing the smartest kids.  Rotherman takes an interesting approach to bringing the statistics down to earth.  First, Shanghai, China is where the smartest kids in China go to learn, which skews their numbers.  Also, after looking closely at the data the US is in the middle of the pack in reading and science, and is slightly below average in math.  While these statistics are not worth commendation, they’re not exactly terrible in the global perspective.

No, this does not have much to do with the Poor Economics chapter on the surface.  However, Rotherman brings up the point that only about 60% of African-American and Hispanic teens are graduating from high school.  Further, only about 1 in 7 high schoolers in low-income families earn their diploma.  These facts beg the question, is the United States succesfully educating the youth?  Are they generating enough of an interest in education in low-income, urban areas?  How significantly have these numbers changed over the last few decades?

Racial Discrimination in the NBA

For my final project for the class, I would like to look at the racial discrimination in the National Basketball Association, namely in salary.  In my hypothesis, I think that overall, white professional basketball players receive a lower salary than African-American professional basketball players that produce similar statistics on the court.  Obviously, the best players sell more tickets and merchandise and should get paid more that the decent to mediocre players, but I think that given two players with similar statistics and the only true difference being race, African-American players get paid more in salary.

For my data, I would like to take into account many statistics from the players that will allow me to pool players together in certain groups.  The statistics I plan to take into account are: draft position, playing position (Guard, Forward, Center, etc.), points, rebounds, assists, steals, blocks, turnovers, PEM (a statistic used by the NBA to assess the performance of an individual player), and race.  Then, by grouping these players separated by race, I can take the mean of their salaries and compare them with the opposing set of players to find my results.

To get this data, I will write an e-mail to Aaron Barzilai who authored the article “Assessing the Relative Value of Draft Position in the NBA Draft.”  All of the statistics I wish to use are in his data set, except race and salary.  However, those two statistics can be found on the NBA’s official website (NBA.com).  As a basketball player all of my life, I find this question both very interesting and a good way to assess the knowledge I gain in Quantitative Methods.

Drug Dealing: Not All It’s Cracked Up To Be

I first read Freakonomics about three years ago in a freshman economics class and was very impressed with how Levitt and Dubner go about answering such interesting questions in an economic-based way.  Chapter 3 of the book focuses on the percieved notion that drug dealers make a lot of money and Levitt and Dubner flip the notion by asking, “If this is true, why do most drug dealers still live at home with their moms.”

The chapter starts out with the story of an economist from the University of Chicago named Sid that started going around asking black prople how they felt about being black.  In the proces, Sid stumbled upon an abandoned building where he ran into the street gang called the Black Disciples. After holding im hostage for a day, Sid noticed the sophistication of the crack business they were operating and decided he wanted to confront the leader J.T. about studying the gang.

Six years, numerous shootings, thousands of dollars, and hundreds of deaths and drug deals later, Sid was given, as a form of personal cleansing from a member who was going to be killed, the financial records from the gang’s business from the past four years.  Upon reading the records, Sid noticed that the gang was run much more professionally than just a drug ring.  J.T., a college graduate with a degree in business, had kept track of every financial transaction the gang had made over the previous four years.

In the records, Sid saw that 20% of the gang’s finances went to the “board of directors,” a group of 20 gang members that were in charge of all the different sets. J.T. was in charge of one set, and only a 12 block selling market.  While J.T. made about $100,000 tax-free, the rest of the gang made very little money.  The people just below J.T. did decently well, but the people working the streets ,”foot soldiers,” only made about $7 an hour.  Below them were about 200 people that were associated with the gang, but only made about $3.30 an hour.

The point of the chapter is to show that yes, while drug rings are profitable, unless you are one of the people at the top of the pyramid, you will not make enough money to live comfortably.  It may seem to a young teen in Chicago that it is profitable, but getting to the top is extremely competitive, much like it is in corporate America.  Therefore, because of the elite competition to get to the top of the drug ring, most drug dealers still live at home with their moms.

Poor Economics Chapter 3

The title of chapter three in Poor Economics by Banerjee and Duflo is “Low Hanging Fruit for Better (Global) Health.”  The title refers to the low-hanging fruit as the inexpensive preventatives that can be used by people in poor areas to prevent the contraction and spreading of viruses and diseases.  In their study, they found that people in these areas are more likely to spend money on curing an already infected disease, rather than take the proper initiatives to prevent them.

The first example of these low-hanging fruits in the health system are the use of ORS or chlorine to stop diarrhea in these poor areas.  ORS, a combination of sugars and salts, and chlorine can both be added to the water sources of villages and individual homes to stop the spread of diarrhea in these areas.  Relatively cheap, these seem like they would be used extensively; however, many households choose not to use these because of the negative financial benefit it has, regardless of the long term financial and health benefits it would employ.

Like ORS and chlorine, beds nets used in the prevention of initial contraction and the further spreading of malaria is also examined by the authors.  In the study, they set up scattered places where bed nets were being sold at different prices from free to the PSI price.  The study showed that while the free bed nets were taken at a high percent, when the price rose even slightly, the percentages of nets bought dropped radically.

Finally, the authors cite the apparant belief in these poor areas that free means worthless.  William Easterly writes in The White Man’s Burden that bed nets have been used as wedding veils, while toilets given to households to set up as part of a piped water source have been used as flowerpots.

In conclusion, the poor are trapped by lack of information, weak beliefs, and procrastination.  While they seem inferior, people in the west do the same things, just in different ways.  Our New Years Eve resolutions to get fit often end soon after they begin, even though being in shape will bring us health in the future.  With this in mind, while people around the world are given ladders to help them get out of their own health trap, they often do not fully utilize them or even know how to start their climb.