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Is Affordable Housing Moving Mobile? Analyzing the Impact of COVID-19 on Demand for Manufactured Housing
By Jair Coleridge Soman Alleyne
As demand for affordable housing continues to increase in America, manufactured homes provide a private solution to this problem. Research has shown that manufactured home prices are largely dependent on the price of local housing substitutes as well as other geographic hedonic factors. This paper looks at the impact of Covid-19 on the manufactured housing market to determine the effects that economic shocks have on the demand for manufactured housing. Conditional on wanting to buy a house, we use a logistic model to examine the probability that an individual purchases a manufactured home and whether this probability increases at times of high unemployment and economic uncertainty. Due to the nature of our data, although the impact of Covid as a disease is difficult to measure, we do find decreased income and increased unemployment to be a factor increasing the likelihood of purchasing a manufactured home. We also find that in 2020, demand for manufactured housing increased significantly compared to the years prior.
Advisors: Professor Charles Becker, Professor Michelle Connolly | JEL Codes: R2, R21, I32
Municipal and Cooperative Internet on Broadband Entry and Competition
by Tianjiu Zuo
The broadband market is unique for municipal (government-owned) and cooperative (member-owned) competitors. Their participation, however, raises conflict of interest concerns. Both municipalities and cooperatives are often owners of utility poles that are an essential input for broadband deployment. Internet service providers (ISPs) must lease pole attachment space. While most pole attachment rates are regulated, municipal and cooperative pole owners are exempt by Section 224 of the Telecommunications Act. This paper, therefore, studies the competitive effects of municipal and cooperative ISPs, and the effect of potential entry by municipal and cooperative electric utilities (non-ISPs), on broadband entry and quality. I add to the existing literature by building a dataset of municipal and cooperative non-ISP service areas, designing a method to clean the Federal Communications Commission’s (FCC) broadband data, developing a novel geographic entry threat model, and analyzing municipalities and cooperatives in conjunction. I categorize markets into three types: rural, urban clusters (2,500 to 50,000 people), and urbanized areas (≥ 50,000 people). Looking at Illinois from June 2015 to June 2018, I find that the presence of a municipal ISP lowers the probability of market entry and service quality in urbanized areas. The presence of a cooperative ISP lowers the probability of market entry and service quality in rural areas and urban clusters. The presence of a municipal non-ISP has little to no effect on the probability of market entry or service quality. The presence of a cooperative non-ISP appears to increase the probability of market entry in rural and urbanized areas, but depress service quality in urbanized areas, though these effects could be attributed to bad data.
Advisor: Professor Michelle Connolly | JEL Codes: L32, L41, L96
Predictors of Student Loan Repayments: A Comparison Between Public, Private For-Profit and Private Nonprofit Schools
by Mannat Bakshi and Arjun Ahluwalia
Using a sample of over 3,500 colleges from the College Scorecard Dataset , we investigate the association of average federal student loan repayment rates with institutional, regional, and student demographic characteristics of colleges. We consider educational cohorts from 2010 to 2016 at public, private for-profit, and private non-profit institutions. Our data do not allow us to see individual student characteristics, hence we control for traits of the average student in each college and focus on institutional traits that impact repayment rates. Our controls for demographics are consistent with prior research on student loan repayment rates (Lochner and Monge-Naranjo, 2014; Kelchen and Li, 2017).
We ran a Random Effects panel regression to determine how institutional, regional, and student demographic characteristics impact repayment rates. We see an important influence of the institution attended. Institution selectivity (lower admission and withdrawal rates) is associated with higher average repayment. Furthermore, the highest degree awarded is a more significant variable when it comes to describing the variation in repayment rates for public schools; private for-profit schools exhibit lower repayment rates and private nonprofit schools exhibit higher repayment rates regardless of the highest degree awarded. This could be due to a combination of signaling and screening effects. Local income and unemployment impact repayment for the average student in public and for-profit schools, but not in private non-profit schools.
A noticeable institutional finding is that, even after controlling for average school demographics, for-profit schools exhibit lower repayment rates across all types of degree-granting programs. Attending a for-profit school may be a negative signal of ability or value to potential employers. Median family income positively affects repayment twice as much for for-profit schools compared to other school types. These finding on for-profit institutions help explain Obama’s “crack down on for-profit career training colleges” (Simon & Emma, 2014).
Advisor: Professor Genna Miller | JEL Codes: I2, I22, I26
The Effects of Health IT Innovation on Throughput Efficiency in the Emergency Department
By Michael Levin
Overcrowding in United States hospitals’ emergency departments (EDs) has been identified as a significant barrier to receiving high-quality emergency care, resulting from many EDs struggling to properly triage, diagnose, and treat emergency patients in a timely and effective manner. Priority is now being placed on research that explores the effectiveness of possible solutions, such as heightened adoption of IT to advance operational workflow and care services related to diagnostics and information accessibility, with the goal of improving what is called throughput efficiency. However, high costs of technological process innovation as well as usability challenges still impede wide-spanning and rapid implementation of these disruptive solutions. This paper will contribute to the pursuit of better understanding the value of adopting health IT (HIT) to improve ED throughput efficiency.
Using hospital visit data, I investigate two ways in which ED throughput activity changes due to increased HIT sophistication. First, I use a probit model to estimate any statistically and economically significant decreases in the probability of ED mortality resulting from greater HIT sophistication. Second, my analysis turns to workflow efficiency, using a negative binomial regression model to estimate the impact of HIT sophistication on reducing ED waiting room times. The results show a negative and statistically significant (p < 0.01) association between the presence of HIT and the probability of mortality in the ED. However, the marginal impact of an increase in sophistication from basic HIT functionality to advanced HIT functionality was not meaningful. Finally, I do not find a statistically significant impact of HIT sophistication on expected waiting room time. Together, these findings suggest that although technological progress is trending in the right direction to ultimately have a wide-sweeping impact on ED throughput, more progress must be made in order for HIT to directly move the needle on confronting healthcare’s greatest challenges.
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Advisors: Professor Ryan McDevitt, Professor Michelle Connolly | JEL Codes: I1, I18, O33
Redefining Resource Allocation in Computing Systems
By Jacob Chasan
A new kernel1 is in town. The current industry-standard for resource allocation on computers does not take the user’s preferences into account, rather programs are given access to resources based on the time that each requested to be run. Although this system can lead to solutions that minimize the time it takes for a program to receive an allocation, it often leads to an incentive misalignment between the programs and the user. This misalignment is exacerbated as the current queue based systems have no inherent mechanism to prevent a tragedy of the commons issue, whereby programs take more resources from the system than the value they provide to the user. By shifting to a market-based approach, where computing resources are allocated to programs based on how much utility the user receives from each program, the incentives of the programs and the users align. With inherent market mechanisms to keep the incentives aligned, this new paradigm leads to at least superior levels of utility for a user.
1As described in subsequent parts of this paper, the kernel is the core program within an operating system which is given the authority to allocate the hardware resources amongst the programs on the computer.
Advisors: Professor Benjamin C. Lee, Professor Atila Abdulkadiroglu, Professor Michelle Connolly | JEL Codes: C8, C80
Taxing Marijuana and the Road to Reparations: Comparing the Colorado and Illinois Cannabis Markets
By Tommaso Carlo Filippo Babucci
Although still prohibited at the federal level, cannabis can now be found on the shelves of recreational dispensaries across thirty-three U.S states. This thesis examines the development of this legal market from both historical and empirical perspectives. Using a new data set, it estimates the determinants of cannabis sales and tax revenues in the Colorado market and analyzes the incidence of a single tax increase. The results, which suggest that legal cannabis behaves like a luxury good, are used to analyze the potential for cannabis-funded reparations programs in Illinois, which recently approved recreational sales of cannabis.
Advisors: Professor Connel Fullenkamp | JEL Codes: H2, R50, L15
Nonprofit Location, Survival, and Success: A Case Study of El Sistema USA
By Andie Carroll
As nonprofits work to serve their communities, they must choose a place to locate that best suits their needs and the needs of the population they aim to serve. Locational characteristics such as median income and population density have been shown to impact how many nonprofits choose to locate in a given area. However, few studies have examined the impact of locational characteristics on how nonprofits survive and thrive. This study examines the impact of geographic and demographic factors on nonprofit survival and success through a case study of El Sistema USA (ESUSA), a nationwide network of music education programs with the goal of helping underserved youth. The study analyzes panel survey data from 131 El Sistema-inspired programs in the U.S. from 2005 to 2018 along with demographic data from the American Community Survey, charitable giving data from the IRS, and GIS data compiled through a review of ESUSA program websites. By using regression models of ESUSA program survival and success (defined by more students served and higher program budgets), this study found that ESUSA programs in areas of more need are more likely to survive and thrive.
Advisors: Professor Lorrie Schmid, Professor Michelle Connolly | JEL Codes: L3, L31, D23
Variability in Jury Awards for Noneconomic Damages in Motor Vehicle Negligence Cases
By Max Cherman
I analyze the efficiency of jury awards for noneconomic compensatory damages awarded to automobile accident victims suffering nonfatal injuries bringing motor vehicle negligence tort claims. Data from 1002 Jury Verdict Research (JVR) case abstracts was narrowed down to 218 observations of plaintiffs receiving noneconomic damages awards at trials involving motor vehicle negligence from 1988-2019 across the United States. Using age-specific value of life estimations, functional capacity losses associated with plaintiffs’ injuries, and productivity losses, I estimate an ‘expected’ noneconomic damages award that serves as a benchmark against which I compare observed awards. I regress the natural log of the ratio of observed to ‘expected’ awards on injury- severity-level indicator variables and other controls, thus attempting to find whether juries award disproportionately high or low noneconomic damages awards in accordance with plaintiff, defendant, or case-specific factors. I conclude that juries award disproportionate noneconomic damages at the opposite ends of the injury severity spectrum, with plaintiffs suffering severe injuries receiving disproportionately high awards. I also find that juries punish business and government entity plaintiffs. These results serve as evidence that jury decision-making is indeed significantly impacted by hindsight bias in large-value cases and attempts to punish supposedly wealthier defendants, creating inconsistency (variability) in compensatory damages award determinations.
Advisors: Professor Christopher Timmins, Professor Kent Kimbrough | JEL Codes: K1, K13, Q51
Navigating the Maize of Poverty: Intra-Household Allocation and Investment in Children’s Human Capital in Tanzania
By Saheel Chodavadia
Intra-household resource allocation influences investment in children’s human capital and hence influences long-term poverty levels. I study how climate shocks in Tanzania shift intra-household bargaining power and investment in children’s human capital. Past empirical work finds that bargaining power is associated with income, assets, education, and other often unobservable factors. Anthropological evidence from Tanzania suggests that male decision-makers in poor households control most income and own most assets. Conditioning on changes in total household resources due to climate shocks, I find evidence consistent with climate shocks increasing female bargaining power through a reduction in male decision-maker’s income. Specifically, climate shocks in households with more educated women increase investment in children’s education and improve anthropometric measures of health. Lastly, I comment on the usefulness of relative education as a proxy for bargaining power in contexts of data and cultural limitations on distinct assets and income streams for decision-makers.
Advisors: Professor Robert Garlick, Professor Michelle Connolly | JEL Codes: D0, D13, I20
The Upstream and Downstream Effects of Government Industrial Policy in the Rare Earth Elements Industry
By Charles Daniel
The Chinese government has found considerable success in stimulating economic modernization through its industrial policy. The development of the rare earths industry, in both upstream and downstream markets, exemplifies this success. Rare earths are a group of metals whose natural properties make them critical for many pieces of modern technology. Upstream, Chinese raw rare earth producers extracted minimal output in 1985; by 2001 they accounted for more than 90 percent of global production. China stimulated this growth beginning in 1990 with implicit and explicit subsidies for rare earth producers, which enabled them to enter the market and produce at lower marginal costs than other world firms. These lower costs enabled Chinese producers to assume a market-leading position, and this paper explains the resulting developments in the upstream rare earth market through the Stackelberg model, which describes sequential quantity competition. In 2006, China introduced an additional policy of export quotas on rare earths, intended to benefit downstream Chinese firms. These firms depend on rare earths as inputs for the final goods (such as batteries and personal electronics) they produce. After the quota announcement, Chinese downstream firms benefitted from continued unrestricted access to rare earths, while non-Chinese downstream firms faced higher costs on the world market for rare earth inputs. This paper uses the Bertrand model, in which firms compete on prices, to examine the subsequent effects on these downstream markets. While Chinese rare earth producers were harmed by the export quotas, the combination of the subsidy and the export quotas enabled China to complete its economic goals: to first gain leverage in the rare earths industry, and to second transition its economy toward higher-value products and services.
Advisors: Professor Alexander Pfaff, Professor Michelle Connolly | JEL Codes: L5, L52, L13