Matching Items (7)
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- All Subjects: Analysis
- All Subjects: Probability
- All Subjects: Third Parties
- Creators: Goegan, Brian
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
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.
ContributorsAndl, Tyler (Co-author) / Shirk, Brandon (Co-author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
This paper intends to analyze the National Football League (NFL) and the role stadiums play within it. The NFL, being the nation's largest professional sports league, has experienced a large amount of volatility over the past couple of decades. Teams have relocated a significant number of times and stadium projects have grown in size, cost, and frequency. Because of these observations, we chose to focus in on this particular sports league in order to answer our many questions surrounding the role of a professional sports stadium in the economics of a city. We seek to understand the economics these sports stadiums impact on the league and the cities they reside in. To do this, we compiled data of NFL franchise wins, average ticket prices, stadiums, and franchise values, while researching the stadium building process and referencing the opinions of leading sports economists across the nation. Next, we discussed the process of building a stadium, which entails the core steps of design, construction, cost, and funding. We discuss tax-exempt municipal bonds, and explain what an impact economic analysis is and how teams use them to get cities to support their projects. Moreover, we discuss the threats of relocation and how the NFL can exert pressure on stadium project decisions. Finally, we talk about the future of the NFL, with a new trend of empty stadiums and make predictions for upcoming relocation destinations. Based on these findings, we draw conclusions on the economics of sports stadiums and offer our opinion on the current state of the NFL.
ContributorsGuillen, Sergio (Co-author) / Willms, Jacob (Co-author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
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.
ContributorsBadger, Mathew Bernard (Author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / Department of Economics (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
In this work we analyze just what makes the topic of third party voting so intriguing to voters and why it is different than voting for one of the major parties in American politics. First, we will discuss briefly the history of politics in America and what makes it exciting. Next, we will outline some of the works by other political and economic professionals such as Hotelling, Lichtman and Rietz. Finally, using the framework described beforehand this paper will analyze the different stances that voters, candidates, and others involved in the political process of voting have regarding the topic of third party voting.
ContributorsMcElroy, Elizabeth (Co-author) / Beardsley, James (Co-author) / Foster, William (Thesis director) / Goegan, Brian (Committee member) / Department of Economics (Contributor) / School of International Letters and Cultures (Contributor) / Economics Program in CLAS (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Cannabis use has been purported to cause an amotivation-like syndrome among users. The purpose of this study was to investigate whether third party observers noticed amotivation among cannabis users. Participants in this study were 72 undergraduate university students, with a mean age of M=19.20 years old (SD=2.00). Participants nominated Informants who knew them well and these informants completed a version of the 18-item Apathy Evaluation Scale. Results indicated that more frequent cannabis use was associated with higher informant-reported levels of amotivation, even when controlling for age, sex, psychotic-like experiences, SES, alcohol use, tobacco use, other drug use, and depression symptoms (β=0.34, 95% CI: 0.04, 0.64, p=.027). A lack of motivation severe enough to be visible by a third party has the potential to have negative social impacts on individuals who use cannabis regularly.
ContributorsWhite, Makita Marie (Author) / Meier, Madeline (Thesis director) / Glenberg, Arthur (Committee member) / Pardini, Dustin (Committee member) / School of Art (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This paper proposes that voter decision making is determined by more than just the policy positions adopted by the candidates in the election as proposed by Antony Downs (1957). Using a vector valued voting model proposed by William Foster (2014), voter behavior can be described by a mathematical model. Voters assign scores to candidates based on both policy and non-policy considerations, then voters then decide which candidate they support based on which has a higher candidate score. The traditional assumption that most of the population will vote is replaced by a function describing the probability of voting based on candidate scores assigned by individual voters. If the voter's likelihood of voting is not certain, but rather modelled by a sigmoid curve, it has radical implications on party decisions and actions taken during an election cycle. The model also includes a significant interaction term between the candidate scores and the differential between the scores which enhances the Downsian model. The thesis is proposed in a similar manner to Downs' original presentation, including several allegorical and hypothetical examples of the model in action. The results of the model reveal that single issue voters can have a significant impact on election outcomes, and that the weight of non-policy considerations is high enough that political parties would spend large sums of money on campaigning. Future research will include creating an experiment to verify the interaction terms, as well as adjusting the model for individual costs so that more empirical analysis may be completed.
ContributorsCoulter, Jarod Maxwell (Author) / Foster, William (Thesis director) / Goegan, Brian (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This paper analyzes responses to a survey using a modified fourfold pattern of preference to determine if implicit information, once made explicit, is practically significant in nudging irrational decision makers towards more rational decisions. Respondents chose between two scenarios and an option for indifference for each of the four questions from the fourfold pattern with expected value being implicit information. Then respondents were asked familiarity with expected value and given the same four questions again but with the expected value for each scenario then explicitly given. Respondents were asked to give feedback if their answers had changed and if the addition of the explicit information was the reason for that change. Results found the addition of the explicit information in the form of expected value to be practically significant with ~90% of respondents who changed their answers giving that for the reason. In the implicit section of the survey, three out of four of the questions had a response majority of lower expected value answers given compared to the alternative. In the explicit section of the survey, all four questions achieved a response majority of higher expected value answers given compared to the alternative. In moving from the implicit to the explicit section, for each question, the scenario with lower expected value experienced a decrease in percentage of responses, and the scenario with higher expected value and indifference between the scenarios both experienced an increase in percentage of responses.
ContributorsJohnson, Matthew (Author) / Goegan, Brian (Thesis director) / Foster, William (Committee member) / School of Sustainability (Contributor) / Economics Program in CLAS (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05