Where You Live and Where You Move: A Cross-City Comparison of the Effects of Gentrification and How these Effects Are Tied to Racial History
By Divya Juneja
This thesis compares the effects of gentrification on school and air quality in ten cities to see whether cities with larger amounts of white flight post-World War II exhibited worse gentrification effects on renters. I find that renters in high white flight cities more consistently experience school quality downgrades—likely attributed to moving from gentrifying neighborhoods to worse neighborhoods. High white flight meant widespread de-investment across neighborhoods which could have lowered the school quality experienced by displaced renters. Gentrification did not consistently affect air quality in any way related to white flight, meaning confounding variables could have influence.
Advisors: Professor Christopher Timmins, Professor Alison Hagy | JEL Codes: R2, R3, J11
By Kevin Ma and Matthew Treiber
This paper explores the secondary resale market for high-end and limited-edition sneakers, specifically analyzing the determinants that affect what value sneakers trade for in the secondary market. While it is common knowledge that the sneaker resale market is a thriving and active secondary market, there is little to no empirical research about what exactly causes such sneakers to sell for exorbitant prices in the resale market. The study utilizes a hedonic pricing approach to investigate the determinants of sneaker resale price. We use a dataset of sneaker resale transactions from the online marketplace StockX between the years of 2016 and 2020 as the basis for our research. After analyzing the results, we have determined that the amount of “hype” that surrounds a sneaker as well as supply scarcity are statistically significant factors when determining the resale price premium a particular sneaker commands in the secondary market. This work adds to the sparse literature on the sneaker resale industry and brings an econometrics-approach to determining the price a given pair of sneakers commands in the resale market.
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Advisors: Professor Kyle Jurado, Professor Michelle Connolly, Professor Grace Kim| JEL Codes: C2, C20, J19
By Michael Nicholson
This paper analyzes loan pricing discrimination against predominantly black communities in U.S. mortgage markets. Building on previous literature, this paper posits that ceteris paribus predominantly black communities continue to face economically significant discrimination in mortgage pricing. Ultimately, this paper concludes that predominantly black communities face 10-14 basis points of pricing discrimination in mortgage loans which corresponds to 12.6-17.6% higher rate spreads. This estimation comes after accounting for geographic and lender effects, borrower quality, tract-level characteristics, and loan type. These results confirm past findings of pricing discrimination and illustrate yet another financial barrier for black households in this country.
Advisors: Professor Emma Rasiel, Professor Kent Kimbrough | JEL Codes: R2, J15, G21
By William Song and Theresa Tong
A substantial body of literature on the wage effects of marriage finds that married American men earn anywhere from 10% to 40% higher wages than unmarried men on average, while married American women earn up to 7% less than unmarried women, even after controlling for traits such as background, education, and number of children. Because this literature focuses heavily on men born in a single time period, we study both men and women in two different generational cohorts of Americans (Baby Boomers and Millennials) from the National Longitudinal Surveys of Youth to examine how the wage effects of marriage differ between genders and across time. Using a fixed effects approach, we find that Millennial women—but not Baby Boomer women—experience an increase in wages after marriage, and we replicate the finding from the literature that men experience an increase in wages after marriage as well. However, after controlling for wage trajectory-based selection into marriage by using a modified fixed effects approach that allows wage trajectories to vary by individual, we find that the wage effects of marriage are no longer statistically significant for any group in our data, suggesting that the wage differences between married and unmarried individuals found in previous studies are primarily a result of selection.
Advisors: Professor Marjorie McElroy, Professor Michelle Connolly | JEL Codes: C33; D13; J12; J13; J22; J30
Asylum Determination within the European Union (EU): Whether Capacity and Social Constraints Impact the Likelihood of Refugee Status Determination
By Louden Paul Richason
This paper analyzes whether capacity and social constraints impact acceptance rates for asylum seekers in the European Union from 2000-2016. Theoretically people should receive asylum based on the criteria outlined in international law – a well founded fear of persecution – but the influx and distribution of applicants in the European Union suggests that this may not hold in practice. For a group of pre identified “legitimate” asylum cases, this paper finds that surges in applications in a country (i.e. capacity constraints) have a positive and statistically significant correlation with acceptance rates, while the percentage of migrants in a country (i.e. social constraints) has a negative and statistically significant correlation with acceptance rates. This suggests that the burden of proof becomes easier during a surge in total applications in a country. However, as the international migrant stock in that country increases, it is more difficult for that same group of applicants to receive asylum.
Advisors: Professor Suzanne Shanahan, Professor Michelle Connolly | JEL Codes: D73, D78, F22, H12, J11, J15, K37, O52
Immigrant Workers in a Changing Labor Environment: A study on how technology is reshaping immigrant earnings
By Grace Peterson
This research determines how automation affects immigrant wages in the US and how closely this impact follows the skills-biased technical change (SBTC) hypothesis. The present study addresses this question using American Community Survey (ACS) data from 2012 to 2016 and a job automation probability index to explain technological change. This research leverages OLS regressions to evaluate real wage drivers, grouping data by year, immigration status, and education level. According to the SBTC hypothesis, high skill immigrant wages should be less negatively affected by technological change than low skill immigrant wages. Univariate analysis suggests that the SBTC hypothesis is even stronger for US = immigrants than native-borns, as high skill immigrants have a lower average probability than low skill immigrants of having their jobs automated, and the difference in effect on high versus low skilled workers is larger for immigrant than native-borns. However, multivariate analysis asserts that technological change affects low skill immigrants’ wages less than high skilled individuals’ wages, which counters the SBTC hypothesis.
Advisors: Professor Grace Kim | JEL Codes: J15, J24, J31, J61, E24
By Hemal Pragneshbhai Patel
The effect of the economic collapse on health has been extensively documented in Russia since the dissolution of the Soviet Union. The proportion of stunted children in Russia increased substantially in this period, but no study has investigated the mechanisms by which this economic collapse impacted child health outcomes. This paper uses an OLS regression followed by a Binder-Oaxaca decomposition to determine the specific economic factors that significantly contributed to this decrease in child heights.
Advisors: Professor Charles Becker | JEL Codes: I1; I14; J13
ICT Behavior at the Periphery: Exploring the Social Effect of the Digital Divide through Interest in Video Streaming
By Erik W. Hanson and Justin C. LoTurco
We investigate the factors that influence changes in consumer behavior with regard to video streaming. We focus our analysis on the effect of bandwidth impairment to explore a potential consequence of the digital divide. To measure the change in relative popularity of video streaming services, we use Google Trends data as a proxy. We then investigate whether broadband speed improvements in rural vs. urban regions affect the proxy differently. We find that increasing the broadband speeds in rural regions appears to stimulate greater interest in video streaming than equivalent speed increases in urban regions.
Advisors: Professor Michelle Connolly, Professor Grace Kim | JEL Codes: C33; J11; L96
Does Media Coverage of Sexual Assault Cases Cause Victims to Go to the Police? Evidence from FBI Data and Google Trends
By Harry Elworthy
This paper investigates the effect that national news coverage of prominent sexual assaults has on the reporting decisions of sexual assault victims. Estimates are based on time series data of reports made to police stations in the US from 2008 to 2016 and Google Trends data of search volume, along with an identification strategy that uses a number of individual high profile sexual assault allegations and related events as instruments. By removing assaults that occurred on the day that they were reported, I estimate the effect of coverage only on the reporting of assaults, and not on assaults themselves. A significant positive effect of news coverage on sexual assault reporting is found using several specifications. Back-of-the-envelope calculations suggest that there were between 31 and 121 additional reports of sexual assault for each of the 38 high profile events captured. No evidence is found to suggest that these additional reports of sexual assault have different arrest rates to other reports, indicating that there are not a significant number of false reports. This paper adds to current literature on the sexual assault reporting decision by considering the effect of news coverage and by using different methods of inference to previous papers.
Advisor: Professor Patrick Bayer | JEL Codes: D91, J16, K42, L86, Z13