This paper is intended to identify a correlation between the winning percentage of sports teams in the four major professional sports leagues in the United States and the GDP per capita of their respective cities. We initially compiled fifteen years of franchise performance along with economic data from the Federal Reserve Bank of St. Louis to analyze this relationship. After converting the data into a language recognized by Stata, the regression tool we used, we ran multiple regressions to find relevant correlations based off of our inputs. This paper will show the value of the economic impact of strong or weak performance throughout various economic cycles through data analysis and conclusions drawn from the results of the regression analysis.

Since the emergence of behavioral economics, our understanding of human behavior and decision-making has improved through the widespread use of conducting experiments. In tandem, behavioral and experimental economists seek to merge psychology and emotion into economic thought to better understand the agents that comprise our economic systems. Vernon Smith, a Nobel Prize winning experimental economist, wrote an article on how economic agents in asset market experiments create bubbles (commonly referred to as "booms and busts" or "market crashes"). This study builds on Smith's work and seeks to better understand how participants behave when given information about the expected outcome of the experiment, and thus how external information affects an individual's expectations and behavior in financial markets. Upon the completion of the experiments and analyzing the results, 7 of the 14 experiments with the same parameters ended with the outcome consistent with the researcher's hypotheses. These results conclude that providing participants with different contextual information regarding outcome hypotheses affected their expectations, price speculations, and strategy development when approaching an asset market.

The goal of our study is to identify socio-economic risk factors for depressive disorder and poor mental health by statistically analyzing survey data from the CDC. The identification of risk groups in a particular demographic could aid in the development of targeted interventions to improve overall quality of mental health in the United States. In our analysis, we studied the influences and correlations of socioeconomic factors that regulate the risk of developing Depressive Disorders and overall poor mental health. Using the statistical software STATA, we ran a regression model of selected independent socio-economic variables with the dependent mental health variables. The independent variables of the statistical model include Income, Race, State, Age, Marital Status, Sex, Education, BMI, Smoker Status, and Alcohol Consumption. Once the regression coefficients were found, we illustrated the data in graphs and heat maps to qualitatively provide visuals of the prevalence of depression in the U.S. demography. Our study indicates that the low-income and under-educated populations who are everyday smokers, obese, and/or are in divorced or separated relationships should be of main concern. A suggestion for mental health organizations would be to support counseling and therapeutic efforts as secondary care for those in smoking cessation programs, weight management programs, marriage counseling, or divorce assistance group. General improvement in alleviating poverty and increasing education could additionally show progress in counter-acting the prevalence of depressive disorder and also improve overall mental health. The identification of these target groups and socio-economic risk factors are critical in developing future preventative measures.

The NBA Draft has become one of the most exciting and unique events in sports. Draft decisions are so monumental; so crucial to be right, so disastrous to be wrong. The purpose of this project is to build a model that would help teams to predict which types of players perform at a high level upon entering the league. By using regression analysis to predict the rookie year PER (performance efficiency rating) as a dependent variable, teams would have some idea of whether their rookies were underperforming, excelling, or performing at a level they could expect. The independent variables and their statistical significance could help answer a host of questions that front offices have about players: If a player came from a worse conference, can we expect them to have a harder time adjusting? Will their shorter wingspan have a negative effect on their play in the NBA? Do guards or forwards tend to have higher PERs upon entering the league? To answer these questions, I've gathered data on every first round NBA draft pick from 2001-2014 who played at least one season of Division 1 NCAA basketball. The data consist of anthropometric measurements (height, wingspan, standing reach, etc.), NBA draft combine results (agility drills, sprint times, etc.) and their college statistics per 40 minutes in their final season of college basketball (points, rebounds, assist-to-turnover ratio, etc.). I then separated the data into seven different sets: aggregate, backcourt, frontcourt, guard, wing, forward, and big. For each of these data sets, I built a predictive model for rookie PER. In doing so, I aimed to gain both a broad understanding of what factors lead to translation of college basketball play to professional play, and also a precise understanding of how those factors change for each distinct position.

This paper examines the ISDS provision, which is a part of a growing number of investment treaties and trade agreements. I define ISDS itself, the idea and purpose, and how it began a few centuries ago to its modern evolved version. I take a look at the recent trends and discover its growth in usage over the past two decades. I analyze the results of ISDS decisions that state the most common winner of claims is the respondent, or sued government. The texts of the trade agreements NAFTA and TPP are examined closely. While the NAFTA was the introduction of ISDS in a major international agreement, the scope of its usage and its effect on countries was more reflected in the TPP. I study the impact of ISDS provisions on foreign direct investment (FDI) flows; multiple papers suggest the impact to be positive. But there are many elements related to ISDS that affect FDI like the strength of the ISDS provisions, characteristics of the host country, the status of the treaty in question, and the time period. Weaker provisions are shown to affect FDI flows on a greater scale, stronger provisions have a significant impact given the treaty or agreement in question is ratified. Additionally, agreements signed or ratified in the past 14 years have more impact on FDI, except for those with strong provisions in signed agreements. Also, weaker form provisions have a larger impact on FDI flows into developed, less developed, OECD, and non-OECD countries but stronger ISDS only meaningfully impacts developed countries. Lastly, several noteworthy cases are discussed that have had varying results. Limits of arbitration have been tested resulting in decades long litigation, investors have taken advantage of ISDS; countries' laws have been protected by ISDS; awards to investors are almost always much smaller than their claimed compensations.

The NBA operates under a unique system with both forms of the salary cap. The league has a team salary cap that sets a limit that teams can spend on their entire roster. The NBA has a soft cap and a luxury tax system, meaning if teams spend over a determined amount, they are taxed for the salaries in excess. The league also has a player salary cap. The 1999 NBA collective bargaining agreement first introduced the individual player salary cap in the league. This cap sets a limit on what the best players can earn, otherwise known as the maximum contract. In an economic system with a soft team cap, the introduction of the player salary cap has important implications. The stated outcome of such a salary cap is to improve competitive balance and better distribute star players throughout the league. This study evaluated the 1990-2015 regular seasons to measure the impact of the player salary cap on competitive balance, the distribution of team payrolls, and the dispersion of star players. In accordance with the Rottenberg's invariance hypothesis, the player salary cap has hurt the players and benefited the owners by redistributing income from one party to the other, without impacting the distribution of talent in the league. The rule change has not affected competitive balance, while team payrolls have converged and star players have become more dispersed throughout the league. These changes hurt the league overall, preventing the maximization of revenues. Despite this inefficiency, the chance of the league moving to eliminate the player salary cap is low.

This paper analyzes the relationship between fatal shootings and several types of legislation. The purpose of this analysis is to determine which gun laws have been more effective at minimizing gun deaths. The following types of firearm legislation were analyzed in the final regression: open carry, concealed carry with a permit, concealed carry without a permit and bans on assault weapons. Through the analysis of these gun laws, the final regression results concluded that gun laws that allow citizens to conceal their weapons, such as concealed carry with or without permit, as well as assault weapon bans typically decrease the amount of firearm deaths, whereas open carrying of firearms typically increases the amount of firearm deaths.

Beginning with the publication of Moneyball by Michael Lewis in 2003, the use of sabermetrics \u2014 the application of statistical analysis to baseball records - has exploded in major league front offices. Executives Billy Beane, Paul DePoedesta, and Theo Epstein are notable figures that have been successful in incorporating sabermetrics to their team's philosophy, resulting in playoff appearances and championship success. The competitive market of baseball, once dominated by the collusion of owners, now promotes innovative thought to analytically develop competitive advantages. The tiered economic payrolls of Major League Baseball (MLB) has created an environment in which large-market teams are capable of "buying" championships through the acquisition of the best available talent in free agency, and small-market teams are pushed to "build" championships through the drafting and systematic farming of high-school and college level players. The use of sabermetrics promotes both models of success \u2014 buying and building \u2014 by unbiasedly determining a player's productivity. The objective of this paper is to develop a regression-based predictive model that can be used by Majors League Baseball teams to forecast the MLB career average offensive performance of college baseball players from specific conferences. The development of this model required multiple tasks: I. Data was obtained from The Baseball Cube, a baseball records database providing both College and MLB data. II. Modifications to the data were applied to adjust for year-to-year formatting, a missing variable for seasons played, the presence of missing values, and to correct league identifiers. III. Evaluation of multiple offensive productivity models capable of handling the obtained dataset and regression forecasting technique. IV. SAS software was used to create the regression models and analyze the residuals for any irregularities or normality violations. The results of this paper find that there is a relationship between Division 1 collegiate baseball conferences and average career offensive productivity in Major Leagues Baseball, with the SEC having the most accurate reflection of performance.

Early in the development of American's interest in athletics there has been a conditioning of the mind toward promoting and rewarding male athletes, while ignoring and undercutting female athletes. There is substantial evidence of the existence of monetary and promotional time given to male athletes and very little support given to their female counterparts. The gender pay gap in professional sports is a culmination of gender discrimination within the entire sports realm. It appears to start at the high school level, continue on into the collegiate sector, and is finally magnified in the professional arena. In high school, male sport's programs are given preference to game and practice times, locations, as well as promotions. In college, male athletic programs are advertised and highlighted as being the premier events to go to. This is also seen in college bookstores with the dominating male event merchandise for sale. In the professional arena, the astronomical value of male athletes' salaries, which go into the multi-millions, makes the gender pay gap glaring. These discrepancies between men and women at each level of sport are in part caused by the underlying informal systems or societal norms and values currently present and encouraged in American culture and communities. These informal systems are often countered by formal systems, such as Title IX. Change cannot truly take place until the two systems are aligned. Thankfully, society today seems to be headed in a more equitable direction; therefore, promoting hope and promise for a more equal future between male and female athletes and their programs.

Phoenix, Arizona is the sixth largest city in the United States. However, the city has never had a MLS team. In 1996, Major League Soccer was founded with ten clubs. Now the league plans to expand from twenty-four to twenty-eight. With multiple teams joining the league, why shouldn't Phoenix be the next market to expand the MLS? This project will analyze if the Phoenix market could host a profitable team. There have been a handful of lower division professional soccer teams in Arizona, but none of them have been sustainable, let alone make it to the MLS. Why is that? What are the steps to create an MLS Franchise? Through researching the factors behind soccer's increased popularity in United States and the history of professional soccer in Arizona perform a market analysis of Arizona's soccer fan base, ownership group, and MLS stadium potential.