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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

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
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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

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
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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

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
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Description
This study examines the economic impact of the opioid crisis in the United States. Primarily testing the years 2007-2018, I gathered data from the Census Bureau, Centers for Disease Control, and Kaiser Family Foundation in order to examine the relative impact of a one dollar increase in GDP per Capita

This study examines the economic impact of the opioid crisis in the United States. Primarily testing the years 2007-2018, I gathered data from the Census Bureau, Centers for Disease Control, and Kaiser Family Foundation in order to examine the relative impact of a one dollar increase in GDP per Capita on the death rates caused by opioids. By implementing a fixed-effects panel data design, I regressed deaths on GDP per Capita while holding the following constant: population, U.S. retail opioid prescriptions per 100 people, annual average unemployment rate, percent of the population that is Caucasian, and percent of the population that is male. I found that GDP per Capita and opioid related deaths are negatively correlated, meaning that with every additional person dying from opioids, GDP per capita decreases. The finding of this research is important because opioid overdose is harmful to society, as U.S. life expectancy is consistently dropping as opioid death rates rise. Increasing awareness on this topic can help prevent misuse and the overall reduction in opioid related deaths.
ContributorsRavi, Ritika Lisa (Author) / Goegan, Brian (Thesis director) / Hill, John (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description

Abstract
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs)
towards opioid overdose management and to assess the effect of online training on opioid
overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and
respond to opioid overdose situations.

Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid
Overdose Attitude

Abstract
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs)
towards opioid overdose management and to assess the effect of online training on opioid
overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and
respond to opioid overdose situations.

Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid
Overdose Attitude Scale (OOAS) surveys were administered electronically to five BHTs in
2020. Data obtained were de-identified. Comparisons between responses to pre-and post-surveys questions were carried out using the standardized Wilcoxon signed-rank statistical test(z). This study was conducted in a residential treatment center (RTC) with the institutional review board's approval from Arizona State University. BHTs aged 18 years and above, working at this RTC were included in the study.

Interventions: An online training was provided on opioid overdose response (OOR) and
naloxone administration and on when to refer patients with opioid use disorder (OUD) for
medication-assisted treatment.

Results: Compared to the pre-intervention surveys, the BHTs showed significant improvements
in attitudes on the overall score on the OOAS (mean= 26.4 ± 13.1; 95% CI = 10.1 - 42.7; z =
2.02; p = 0.043) and significant improvement in knowledge on the OOKS (mean= 10.6 ± 6.5;
95% CI = 2.5 – 18.7; z =2.02, p = 0.043).

Conclusions and Relevance: Training BHTs working in an RTC on opioid overdose response is
effective in increasing attitudes and knowledge related to opioid overdose management. opioid
overdose reversal in RTCs.

Keywords: Naloxone, opioid overdose, overdose education, overdose response program

ContributorsQuie, Georgette (Author) / Guthery, Ann (Thesis advisor)
Created2021-04-12
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Description
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs) towards opioid overdose management and to assess the effect of online training on opioid overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and respond to opioid overdose situations. Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid Overdose Attitude

Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs) towards opioid overdose management and to assess the effect of online training on opioid overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and respond to opioid overdose situations. Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid Overdose Attitude Scale (OOAS) surveys were administered electronically to five BHTs in 2020. Data obtained were de-identified. Comparisons between responses to pre-and post-surveys questions were carried out using the standardized Wilcoxon signed-rank statistical test(z). This study was conducted in a residential treatment center (RTC) with the institutional review board's approval from Arizona State University. BHTs aged 18 years and above, working at this RTC were included in the study. Interventions: An online training was provided on opioid overdose response (OOR) and naloxone administration and on when to refer patients with opioid use disorder (OUD) for medication-assisted treatment. Results: Compared to the pre-intervention surveys, the BHTs showed significant improvements in attitudes on the overall score on the OOAS (mean= 26.4 ± 13.1; 95% CI = 10.1 - 42.7; z = 2.02; p = 0.043) and significant improvement in knowledge on the OOKS (mean= 10.6 ± 6.5; 95% CI = 2.5 – 18.7; z =2.02, p = 0.043). Conclusions and Relevance: Training BHTs working in an RTC on opioid overdose response is effective in increasing attitudes and knowledge related to opioid overdose management. opioid overdose reversal in RTCs.
Created2021-04-12