Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- Creators: Department of Economics
Description
This thesis project provides a thorough cost-benefit analysis of the golf industry in Arizona. We begin by examining the economic, environmental, and social costs that the industry requires. One of the largest costs of the industry is water consumption. Golf courses in Arizona are currently finding ways to reduce water consumption through various methods, such as turf reduction and increasing the usage of drip irrigation. However, even at current levels of consumption, golf only consumes 1.9% of water in Arizona, compared to the 69% consumed by agriculture. Of the water consumed by the golf industry, 26.3% is wastewater, otherwise known as effluent water. Since the population in Arizona is projected to grow significantly over the next decade, the amount of effluent water produced will also increase. Due to this, we recommend that the golf industry move towards using as much effluent water as possible to conserve clean water sources. Additionally, we examine land allocation and agricultural tradeoffs to the state. Most golf courses are built in urban areas that would not be suitable for agriculture. The same land could be used to build a public park, but this would not provide as many economic benefits to the state. Many courses also act as floodplains which protect the communities surrounding them from flooding. These floodplains have proven to be crucial to protect from occasional flash floods by diverting the excess water away from homes. We also discuss golf's primary social cost in terms of its perception as being a sport played exclusively by privileged and wealthy people. This is proven to be false due to many non-profit organizations centered around the game, as well as municipal courses that provide affordable options for all citizens who want to play. We provide an in-depth analysis of the benefits that the industry provides to the state and its citizens primarily through business and tax revenue, employment, and property values. Including multiplier effects, the golf industry contributed 42,000 full- and part-time jobs, $3.9 billion in sales, $1.5 billion in labor income, and $2.1 billion value added in 2014. An estimated $72 million in state and local taxes were generated from golf facilities alone, without including taxes from indirectly impacted businesses. This tax revenue provides a great benefit to the public sector and increases Arizona's GDP. Also, much of this economic contribution is from the golf tourism industry, which brings new revenue into the state that would otherwise not exist. Golf courses also increase the surrounding real estate prices anywhere from 4.8% to 28%, providing a positive externality to community members in addition to scenic views. Finally, we provide a case study of the Waste Management Phoenix Open (WMO) to illustrate the impact of Arizona's single largest golf event each year. In 2017, the event brought an estimated $389 million into Arizona's economy in one week alone. Also, it regularly hosts massive crowds with a record-breaking 719,179 people attending the event in 2018. The WMO has also taken a "Zero Waste Challenge" to promote eco-friendly and sustainable practices by diverting all of the waste and materials produced by the tournament from landfills. The WMO has been dubbed both the "Greatest Show On Grass" and the "Greenest Show On Grass" due to the entertainment value provided as well as its effort to improve the environment.
ContributorsShershenovich, Andrew (Co-author) / Wilhelm, Spencer (Co-author) / Goegan, Brian (Thesis director) / Van Poucke, Rory (Committee member) / Department of Finance (Contributor) / W.P. Carey School of Business (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
Since 2014, the legal marijuana industry has flourished in Colorado, the first state to ever legalize its recreational use in the United States. It is necessary to fully understand the economic impact of the implementation of the recreational system as well as the characteristics of the market for lawmakers, business owners, and voters to make educated decisions on future legislation. This report will delve into these matters in an objective manner to provide all the stakeholders in any present or future recreational marijuana market (users, business owners, legislators) with accurate information on the current state of the industry. Starting with an introduction of the history of marijuana in the United States, as well as the factors that led to its illegality, offers insight into the past and current laws currently impacting the recreational marijuana market in Colorado, with special emphasis on the state regulatory framework in place at this time. The analysis will include an in-depth examination of the current market forces at play in the recreational marijuana market, including technological, sociological, and economic factors, with a look at current business-level strategies for marijuana businesses and the threats arising from alcohol and tobacco, the drug's main substitutes. This report will explain the tax framework in place in Colorado, and investigate trends in market sales and tax revenues, including detailed statistics on the distribution of tax revenue throughout the state. A comprehensive analysis of the legislative issues the market faces, both in Colorado and across the country, will thoroughly indicate the major problems the industry must overcome in the future, or whether it can do so at all. These will include difficulties in the banking, taxation, insurance, and bankruptcy systems that marijuana-related businesses currently face.
ContributorsDosad, Jay (Author) / Goegan, Brian (Thesis director) / Foster, William (Committee member) / Sandra Day O'Connor College of Law (Contributor) / W.P. Carey School of Business (Contributor) / 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
Today, statistical analysis can be used for a variety of different reasons. In sports, more particularly baseball, there is an increasing necessity to have better up to date analysis of players and their performance as they attempt to make it to the Major League. Athletes are constantly moving around within one or more organizations. Since they are moving around so often, clubs spend an ample amount of time determining whether or not it is for their benefit and betterment of the organization as a whole. The objective of this thesis is to utilize previous baseball statistics in StataSE to determine performance levels of players who played at the major league level. From these, regression-based performance models will be used to predict whether or not Major League Baseball organizations effectively and efficiently move players around from their farm systems to the big leagues. From this, teams will be able to see whether or not they in fact make the right decisions during the season. Several tasks were accomplished to achieve this outcome: 1. First, data was obtained from the Baseball-Reference statistics database and sorted in google sheets in order for me to perform analysis anywhere. 2. Next, all 1,354 players that entered the major leagues in the year 2016, were assessed as to whether or not they started in a given league and stayed, got promoted from the minor leagues to the majors, or demoted from the majors to the minor leagues. 3. Based off of prior baseball knowledge and offensive performance quantifications only, players' abilities were evaluated and only those who were called up or sent down were included in the overall analysis. 4. The statistical analysis software application, StataSE, was used to create a further analyze if any of the four major regression assumptions were violated. It was determined that logistic regression models would produce better results than that of a standard, linear OLS model. After testing multiple models, and slightly refining my hypothesis, the adjustments made developed a more accurate analysis of whether organizations were making an efficient move sending a player down to promote another player up. After producing the model, I decided to investigate at what level a player was deemed to be no longer able to perform at a Major League Baseball level.
ContributorsHayes, Andrew Joseph (Author) / Goegan, Brian (Thesis director) / Marburger, Daniel (Committee member) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The goal of this thesis is to conduct a descriptive analysis of the gross domestic product (GDP) sector composition of countries around the world and their respective levels of economic development with consideration of their geographic locations, economic growth over time, and their economic sizes. This analysis will be centered around exploring the differences of the GDP composition of countries at different levels of development, testing the consensus that developed countries tend to be focused on the services sector in comparison to less developed ones, who trend towards focus on the agricultural one. These findings will be primarily attained through use of data interpretation and regression analysis utilizing the statistical software packages of Stata and Excel. Results and analysis are to be supported by powerful data visualizations created in Tableau and the careful examination of said visualizations.
Due to the sheer amount of macro-economic factors and the case specific incidences involved in the determination of a country’s level of economic development, this thesis will focus entirely on the descriptive analysis of the relationship between a country’s GDP sector composition within the agricultural, industrial, and services sectors and their level of economic development measured in GDP per capita. This study will explore the relationship between GDP per capita and geographic regions, growth over time, and economic size as well. These relationships will be used to determine if said factors need to be controlled for when analyzing the relationship between a country’s sector composition and its level of development. A better understanding of what countries look like at all levels of development helps build a complete picture of a what makes a country successful and could be used in future studies that seek to predict economic success based on more and/or separate variables.
Due to the sheer amount of macro-economic factors and the case specific incidences involved in the determination of a country’s level of economic development, this thesis will focus entirely on the descriptive analysis of the relationship between a country’s GDP sector composition within the agricultural, industrial, and services sectors and their level of economic development measured in GDP per capita. This study will explore the relationship between GDP per capita and geographic regions, growth over time, and economic size as well. These relationships will be used to determine if said factors need to be controlled for when analyzing the relationship between a country’s sector composition and its level of development. A better understanding of what countries look like at all levels of development helps build a complete picture of a what makes a country successful and could be used in future studies that seek to predict economic success based on more and/or separate variables.
ContributorsStojsin, Rastko (Author) / Goegan, Brian (Thesis director) / Lopez, Andres Diaz (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
A global trend towards cashlessness following the increase in technological advances in financial transactions lends way to a discussion of its various impacts on society. As part of this discussion, it is important to consider how this trend influences crime rates. The purpose of this project is to specifically investigate the relationship between a cashless society and the robbery rate. Using data collected from the World Bank’s Global Financial Inclusions Index and the United Nations Office of Drugs and Crime, we implemented a multilinear regression to observe this relationship across countries (n = 29). We aimed to do this by regressing the robbery rate on cashlessness and controlling for other related variables, such as gross domestic product and corruption. We found that as a country becomes more cashless, the robbery rate decreases (β = -677.8379, p = 0.071), thus providing an incentive for countries to join this global trend. We also conducted tests for heteroscedasticity and multicollinearity. Overall, our results indicate that a reduction in the amount of cash circulating within a country negatively impacts robbery rates.
ContributorsChoksi, Aashini S (Co-author) / Elliott, Keeley (Co-author) / Goegan, Brian (Thesis director) / McDaniel, Cara (Committee member) / School of International Letters and Cultures (Contributor) / Department of Economics (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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 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
Description
The FIFA World Cup is one of the most anticipated, inspiring, and intense sporting events in the world. Soccer has integrated itself not only in sports circles, but also in politics, commerce, and society as a whole. The sport has about two hundred million active players and is still growing, especially in areas such as North America and Asia. As of mid-2007, FIFA’s membership included 208-member associations, making it not only one of the largest and most powerful sports governing bodies, but also one of the most popular in the world.
Since 1930—with the exception of the break for World War II—every four years, the world’s best national teams face off in a soccer tournament. The last two tournaments hosted by South Africa in 2010 and Brazil in 2014 will be the emphasis of this paper. Each tournament featured the thirty-two countries and captured a television audience of over three billion people throughout the month-long tournament, one billion of which tuned in for the final. For comparison, the Super Bowl XLIX where the New England Patriots defeated the Seattle Seahawks 28 to 24 was the most watched event in United States’ history with a viewership of 114.4 million people.
Countries spend years planning and preparing to win a bid to host one of these mega events. Bids are often times awarded eight to twelve years in advance. There has been a recent trend of developing countries hosting the FIFA World Cups and the future bids already awarded follow that trend. Many people ask the question of whether all the money spent on infrastructure, construction, and tourism to host this tournament and gain international exposure are really worth it? Simply put, the 2010 FIFA World Cup was valuable to South Africa while the 2014 FIFA World Cup was not worth the costs to Brazil.
Since 1930—with the exception of the break for World War II—every four years, the world’s best national teams face off in a soccer tournament. The last two tournaments hosted by South Africa in 2010 and Brazil in 2014 will be the emphasis of this paper. Each tournament featured the thirty-two countries and captured a television audience of over three billion people throughout the month-long tournament, one billion of which tuned in for the final. For comparison, the Super Bowl XLIX where the New England Patriots defeated the Seattle Seahawks 28 to 24 was the most watched event in United States’ history with a viewership of 114.4 million people.
Countries spend years planning and preparing to win a bid to host one of these mega events. Bids are often times awarded eight to twelve years in advance. There has been a recent trend of developing countries hosting the FIFA World Cups and the future bids already awarded follow that trend. Many people ask the question of whether all the money spent on infrastructure, construction, and tourism to host this tournament and gain international exposure are really worth it? Simply put, the 2010 FIFA World Cup was valuable to South Africa while the 2014 FIFA World Cup was not worth the costs to Brazil.
ContributorsLooney, Andrew (Author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / Department of Economics (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Only an Executive Summary of the project is included.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs and obstacles to consider. This topic is extremely pertinent today as the advent of big data increases and the use of machine learning and artificial intelligence is expanding across industries and functional roles. The approach I took was to expand on a project I championed as a Microsoft intern where I facilitated the integration of a forecasting machine learning model firsthand into the business. I supplement my findings from the experience with research on machine learning as a disruptive technology. This paper will not delve into the technical aspects of coding a machine model, but rather provide a holistic overview of developing the model from a business perspective. My findings show that, while the advantages of machine learning are large and widespread, a lack of visibility and transparency into the algorithms behind machine learning, the necessity for large amounts of data, and the overall complexity of creating accurate models are all tradeoffs to consider when deciding whether or not machine learning is suitable for a certain objective. The results of this paper are important in order to increase the understanding of any business professional on the capabilities and obstacles of integrating machine learning into their business operations.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs and obstacles to consider. This topic is extremely pertinent today as the advent of big data increases and the use of machine learning and artificial intelligence is expanding across industries and functional roles. The approach I took was to expand on a project I championed as a Microsoft intern where I facilitated the integration of a forecasting machine learning model firsthand into the business. I supplement my findings from the experience with research on machine learning as a disruptive technology. This paper will not delve into the technical aspects of coding a machine model, but rather provide a holistic overview of developing the model from a business perspective. My findings show that, while the advantages of machine learning are large and widespread, a lack of visibility and transparency into the algorithms behind machine learning, the necessity for large amounts of data, and the overall complexity of creating accurate models are all tradeoffs to consider when deciding whether or not machine learning is suitable for a certain objective. The results of this paper are important in order to increase the understanding of any business professional on the capabilities and obstacles of integrating machine learning into their business operations.
ContributorsVerma, Ria (Author) / Goegan, Brian (Thesis director) / Moore, James (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05