Benefit Spillovers and Higher Education Financing: An Empirical Analysis of Brain Drain and State-Level Investment in Public Universities
By Chinmany G. Pandit
This paper analyzes the impact of out-migration of college graduates on state higher education investment. A three-stage least squares regression model with state and year fixed effects is developed and estimated, addressing the relationship between state legislative appropriations, tuition, and educated out-migration across 49 U.S. states from 2006-2015. The results support the notion that states respond negatively to benefit spillovers in higher education: for every one percent increase in the rate of educated out-migration, state appropriations decrease by 1.92 percent (roughly $140 per student). These findings suggest that an education subsidy
provided to states may be necessary to prevent underinvestment in higher education.
Advisor: Thomas Nechyba | JEL Codes: H7, H75, I22, I28, R23
By Neelesh T. Moorthy
I assess whether forward citations—how often patents are cited by subsequent patents—reliably capture patent quality. A high-quality invention might lack forward citations if there are no competing, patenting firms. This introduces measurement error in using citations to measure patent value. I test whether greater competition makes forward citations better measures of patent quality, with eight and twelve-year patent renewal rates serving as my benchmark measures of patent quality. Patent data come from the manufacturing survey in Cohen, Nelson, and Walsh (2000). I conduct logit regressions of patent renewal on forward citations and the number of competitors faced by surveyed manufacturing labs. While the regression results do not support the competition hypothesis, they confirm that forward citations positively predict renewal. They also lend insight into firms’ strategic renewal decisions.
Advisors: Wesley Cohen and Michelle Connolly | JEL Codes: O31, O34
By M. Thomas Marshall Jr.
When deciding on housing location, people theoretically optimize for the best location given their commute time, housing cost, income, as well as other factors. Stutzer and Frey (2008) suggest that this is not true in some nations, such as in their investigation of Germany, with their results showing that the cost of an average commute is equivalent to 35.4% of the average income. This paper investigates the impact of commute time on the well-being of individuals in the United States, correcting for various other factors that determine housing choice such as race,
age, and whether they have a child living at home. The results of this study are clearly that the relationship found between commuting time and well-being cannot be proven to be statistically significant from zero, so there is not any evidence against optimization.
Advisor: Kent Kimbrough | JEL Codes: D12, D61, R31, R41
By Shihab Osman Malik and Faisal Bandar Alsaadi
This study examines the relationship between the fixed exchange rate regime, economic growth, and output volatility in oil-‐‑producing Saudi Arabia over the post-‐‑Bretton Woods period (1973–2016). We assess the implications of the current exchange rate regime on macroeconomic and growth performance, and evaluate its sustainability in the context of oil-‐‑dependency and market dynamics. We develop and employ a theoretical framework and empirical specification based on previous literature to find that for Saudi Arabia, the fix is associated with faster growth and lower output volatility. We believe the result is primarily driven by the credibility of the fix in terms of establishing a strong nominal anchor and monetary policy framework.
Advisor: Lori Leachman | JEL Codes: E42, F31, F36, F41, O53
By Christopher G. MacGibbon
This thesis develops a new Multi-Horizon Moment Conditions test for evaluating multi-horizon forecast optimality. The test is based on the variances, covariances and autocovariances of optimal forecast errors that should have a non-zero relationship for multi-horizon forecasts. A simulation study is conducted to determine the test’s size and power properties. Also, the effects of combining the Multi-Horizon Moment Conditions test and the well-known Mincer-Zarnowitz and zero autocorrelation tests into one forecast optimality test are examined. Lastly, an empirical study evaluating forecast optimality for four multi-horizon forecasts made by the Survey of Professional Forecasters is included.
Advisors: Andrew Patton, Grace Kim and Kent Kimbrough | JEL Codes: G1, G17, G00
By Elizabeth Lim, Akshaya Trivedi and Frances Mitchell
On March 29, 2016, the FCC initiated its first ever two-sided spectrum auction. The auction closed approximately one year later, having repurposed a total of 84 megahertz (MHz) of spectrum. The “Incentive Auction” included three primary components: (1) a reverse auction where broadcasters bid on the price at which they would voluntarily relinquish their current spectrum usage rights, (2) a forward ascending clock auction for flexible use wireless licenses which determined the winning bids for licenses within a given geographic region, and (3) an assignment phase, where winning bidders from the forward auction participated in single-bid, second price sealed auctions to determine the exact frequencies individual licenses would be assigned within that geographic region. The reverse auction and the forward auction together constituted a “stage.” To guarantee that sufficient MHz were cleared, the auction included a “final stage rule” which, if not met, triggered a clearing of the previous stage and the start of a new stage. This rule led to a total of four stages taking place in the Incentive Auction before the final assignment phase took place. Even at first glance, the Incentive Auction is unique among FCC spectrum auctions. Here we consider the estimated true valuation for these licenses based on market conditions. We further compare these results to more recent outcomes in previous FCC spectrum auctions for wireless services to determine if this novel auction mechanism
impacted auction outcomes.
Advisor: Michelle Connolly | JEL Codes: L5, O3, K2, D44, L96
By Anna Katherine Kropf
Recent economic literature suggests that entrepreneurship in technological fields can spur economic growth, making it a popular topic for city development officials. Yet, this increasingly popular phenomenon is met by many economic questions. One of those questions is which characteristics of metropolitan areas are attractive to entrepreneurs. To answer the question of attractiveness on both the small business and corporate levels, I compare across two case studies: Amazon’s search for a second headquarters and Google’s tech hub network. Using principal component analysis, I statistically deduce seven components of attractiveness from an original 34 variables. These components are then weighted using three methods—a case study, a survey, and an empirical method—to produce comparable indices of attractiveness. Generally, I find that sizeable population and healthy economy are the strongest components. However, the statistically insignificant components that can change an urban area’s ranking considerably are talent and geographic network effects. Ultimately, creating policy to maximize these aspects can change a city’s innovative
Advisor: Dr. Charles Becker | JEL Codes: O, O3, R, R1, R11
By Michael J. Kiffel
The literature on the performance differential between passively and actively managed equity mutual funds is thorough: passively managed funds generally outperform their active counterparts except in the rare presence of highly-skilled managers. However, there exists limited academic research regarding fixed income mutual funds. This study utilizes the Fama-French bond risk factors, TERM and DEF, in a dual-step multivariate linear regression analysis to determine this performance differential between passively and actively managed bond mutual funds. The funds are comprised of either corporate or government bonds, spanning three categorizations of average maturities. Overall, it is determined that passively managed bond funds offer higher net returns than those offered by actively managed funds. Additionally, the regressions demonstrated that DEF possesses a high degree of predictive power and statistical
Advisor: Edward Tower | JEL Codes: C55, G10, G11
By Michael Karamardian
Because Medicare’s prospective payment system for long-term acute-care hospitals (LTCHs) makes a large lump-sum form of payment once patients reach a minimum length-ofstay threshold, LTCHs have a unique opportunity to maximize profits by strategically discharging patients as soon as the payment is received. This analysis explores how the level of competition between LTCHs in geographic markets affects the probability of a patient being strategically discharged. The results show that patients at LTCHs in more competitive markets have a lower probability of being strategically discharged than at those in less competitive markets, suggesting increased competition could help save Medicare funding.
Advisors: Kent Kimbrough and James Roberts | JEL Codes: D22, I11, I18
By Aakash Jain
Previous research has shown that ambient temperature affects human metabolism and behavior. Inspired by these findings, this study examines the effect of lagged annual temperatures in the United States on average reported BMI. The results indicate that higher temperatures in the future will lead to increases in average BMI. A conservative estimate suggests that a 1 °C increase in temperature sustained for 10 years would result in a 0.15 unit increase in average BMI and an additional $15.5 billion in annual health care expenditure.
Advisor: Billy Pizer | JEL Codes: Q5, Q54, I1, I10