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- All Subjects: Arizona
- Creators: Economics Program in CLAS
Description
Many fear that the growth of automation and artificial intelligence will lead to massive unemployment since human labor would no longer be needed. Although automation does displace workers from their current jobs, it is unclear the total net effect on jobs this period of advancement will have. One possible solution to help displaced workers is a Universal Basic Income. A Universal Basic Income(UBI) is a set payment paid to all members of society regardless of working status. Compared to current unemployment programs, a Universal Basic Income does not restrict participants in how to spend the money and is more inclusive. This paper examines the effects of a UBI on a person's motivation to work through a study on current college students. There is reason to believe that a Universal Basic Income will lead to fewer people working as people may become dependent on a base payment to meet their basic needs and not look for work. In addition, some people may drop out of their current jobs and rely on a UBI as their main form of income. The current literature does not offer a consensus opinion on this relationship and more studies are being completed with the threat of mass unemployment looming. This study shows the effects of a UBI on participants' willingness to work and then applies these results to the current economic model. With these results and new economic model, a decision about future policies surrounding a UBI can be made.
ContributorsAgarwal, Raghav (Author) / Pulido Hernadez, Carlos (Thesis director) / Foster, William (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
Elections in the United States are highly decentralized with vast powers given to the states to control laws surrounding voter registration, primary procedures, and polling places even in elections of federal officials. There are many individual factors that predict a person's likelihood of voting including race, education, and age. Historically disenfranchised groups are still disproportionately affected by restrictive voter registration and ID laws which can suppress their turnout. Less understood is how election-day polling place accessibility affects turnout. Absentee and early voting increase accessibility for all voters, but 47 states still rely on election-day polling places. I study how the geographic allocation of polling places and the number of voters assigned to each (polling place load) in Maricopa County, Arizona has affected turnout in primary and general elections between 2006 and 2016 while controlling for the demographics of voting precincts. This represents a significant data problem; voting precincts changed three times during the time studied and polling places themselves can change every election. To aid in analysis, I created a visualization that allows for the exploration of polling place load, precinct demographics, and polling place accessibility metrics in a map view of the county. I find through a spatial regression model that increasing the load on a polling place can decrease the election-day turnout and prohibitively large distances to the polling place have a similar effect. The effect is more pronounced during general elections and is present at varying levels during each of the 12 elections studied. Finally, I discuss how early voting options appear to have little positive effect on overall turnout and may in fact decrease it.
ContributorsHansen, Brett Joseph (Author) / Maciejewski, Ross (Thesis director) / Grubesic, Anthony (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
The growing Hispanic population in Phoenix, Arizona frequently lacks financial resources which may limit their access to health care. The goal of this study was to identify the ideal factors in a health insurance plan for the Hispanic/Latino population in Phoenix, AZ. A survey was designed to gather information regarding demographics, health insurance, preferences, and affordability. The survey was completed by 260 participants. Several multivariate regressions were run using SAS Statistical Software. The final model generated explained 4.48% of the variation in the data set. It showed that an individual who identified as Hispanic/Latino was 8.2% less likely to have health insurance. In addition, an individual who identified as a US Citizen was 23% more likely to have health insurance. To improve access and enrollment among the Hispanic/Latino population, further investigation is needed to identify relevant communication techniques that increase enrollment among this high-risk community.
ContributorsToo, Rachel Yun-May (Author) / Whisner, Corrie (Thesis director) / Calvin, Samantha (Committee member) / Cook, Aaron (Committee member) / Economics Program in CLAS (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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
Education is known for being powerful in reducing poverty, improving health, promoting healthier economies, and providing peaceful and productive opportunities for young people worldwide. It’s a key to success that has been threatened in the state of Arizona through low funding, teacher shortages, and a lack of resources. Inadequate learning environments further educational inequalities and hinder academic achievement among students. In finding a solution, the objectives of education policy in Arizona are analyzed from an economic and equity standpoint.
ContributorsHernandez Martinez, Chelsea (Author) / Bizuneh, Abyssinia (Co-author) / Bolosan, Kaleo (Co-author) / O'Connor, Brendan (Thesis director) / Garcia, David (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Criminology and Criminal Justice (Contributor) / Division of Teacher Preparation (Contributor) / School of Transborder Studies (Contributor)
Created2023-05
Description
The 2020 U.S. Presidential Election was a presidential election unlike any other in modern U.S. history for several reasons. In the rare defeat of an incumbent president, Joseph Biden secured the title of President of the United States over President Donald Trump. In this victory, Biden flipped several historic battleground states in his favor, in addition to two formerly safe conservative states: Arizona and Georgia. This research seeks to examine the role that the mobilization of voters from working class and majority-minority state legislative districts played in determining the outcome of the election in Arizona and Georgia.
ContributorsHuerta, Marco (Author) / Hero, Rodney (Thesis director) / Dempsey, Matthew (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / Economics Program in CLAS (Contributor)
Created2022-05
Description
With the coming advances of computational power, algorithmic trading has become one of the primary strategies to trading on the stock market. To understand why and how these strategies have been effective, this project has taken a look at the complete process of creating tools and applications to analyze and predict stock prices in order to perform low-frequency trading. The project is composed of three main components. The first component is integrating several public resources to acquire and process financial trading data and store it in order to complete the other components. Alpha Vantage API, a free open source application, provides an accurate and comprehensive dataset of features for each stock ticker requested. The second component is researching, prototyping, and implementing various trading algorithms in code. We began by focusing on the Mean Reversion algorithm as a proof of concept algorithm to develop meaningful trading strategies and identify patterns within our datasets. To augment our market prediction power (“alpha”), we implemented a Long Short-Term Memory recurrent neural network. Neural Networks are an incredibly effective but often complex tool used frequently in data science when traditional methods are found lacking. Following the implementation, the last component is to optimize, analyze, compare, and contrast all of the algorithms and identify key features to conclude the overall effectiveness of each algorithm. We were able to identify conclusively which aspects of each algorithm provided better alpha and create an entire pipeline to automate this process for live trading implementation. An additional reason for automation is to provide an educational framework such that any who may be interested in quantitative finance in the future can leverage this project to gain further insight.
ContributorsYurowkin, Alexander (Co-author) / Kumar, Rohit (Co-author) / Welfert, Bruno (Thesis director) / Li, Baoxin (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Apple’s HomeKit framework centralizes control of smart home devices and allows users to create home automations based on predefined rules. For example, a user can add a rule to turn off all the lights in their house whenever they leave. Currently, these rules must be added through a graphical user interface provided by Apple or a third-party app on iOS. This thesis describes how a text-based language provides users with a more expressive means of creating complex home automations and successfully implements such a language. Rules created using this text-based format are parsed and interpreted into rules that can be added directly into HomeKit. This thesis also explores how security features should be implemented with this text-based approach. Since automations are run by the system without user interaction, it is important to consider how the system itself can provide functionality to address the unintended consequences that may result from running an automation. This is especially important for the text-based approach since its increase in expressiveness makes it easier for a user to make a mistake in programming that leads to a security concern. The proposed method for preventing unintended side effects is using a simulation to run every automation prior to actually running the automation on real-world devices. This approach allows users to code some conditions that must be satisfied in order for the automation to run on devices in the home. This thesis describes the creation of such a program that successfully simulates every device in the home. There were limitations, however, with Apple's HomeKit framework, which made it impractical to match the state of simulated devices to real devices in the home. Without being able to match the current state of the home to the current state of the simulation, this method cannot satisfy the goal of ensuring that certain adverse effects will not occur as a result of automations. Other smart home control platforms that provide more extensibility could be used to create this simulation-based security approach. Perhaps as Apple continues to open up their HomeKit platform to developers, this approach may be feasible within Apple's ecosystem at some point in the future.
ContributorsSharp, Trevor Ryan (Co-author) / Sharp, Trevor (Co-author) / Bazzi, Rida (Thesis director) / Doupe, Adam (Committee member) / Economics Program in CLAS (Contributor) / Department of Management and Entrepreneurship (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Greenhouse gas emissions (GHG) continue to contribute heavily to global warming. It is estimated that the international community has only until 2050 to eliminate total carbon emissions or risk irreversible climate change. Arizona, despite its vast solar energy resources, is particularly behind in the global transition to carbon-free energy. This paper looks to explore issues that may be preventing Arizona from an efficient transition to carbon-free generation technologies. Identifiable factors include outdated state energy generation standards, lack of oversight and accountability of Arizona’s electricity industry regulatory body, and the ability for regulated utilities to take advantage of “dark money” campaign contributions. Various recommendations for mitigating the factors preventing Arizona from a carbon-free future are presented. Possibilities such as modernizing state energy generation standards, increasing oversight and accountability of Arizona’s electricity industry regulatory body, and potential market restructuring which would do away with the traditional regulated utility framework are explored. The goal is to inform readers of the issues plaguing the Arizona energy industry and recommend potential solutions moving forward.
ContributorsWaller, Troy (Author) / Sheriff, Glenn (Thesis director) / Rule, Troy (Committee member) / Economics Program in CLAS (Contributor) / Dean, W.P. Carey School of Business (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12