The Russian Maternity Capital Policy: Two Models
by Jackson Cooksey
Abstract
Between 1991 and 2007 the Russian Federation experienced a decrease in population and a drop in total fertility rate below population replacement levels. In 2007 the government, citing the importance of forestalling this decline, implemented the Russian Maternity Capital Policy, a one-time subsidy to those families who have a second or higher order birth. Study aims to analyze the impact of this policy on the total fertility rate of the Russian Federation to better understand post-Soviet trends in fertility and gain insight into how effective similar policies will be in the future if implemented elsewhere. This study uses two models to assess the policy. First, a novel difference-indifference- in-difference model is developed to add to existing literature on the policy. Second, a synthetic control model is developed generate a counterfactual to measure causal effects of the policy on total fertility rate in Russia. Difference-in-difference-indifference estimations show the policy having a 0% to 3.5% positive effect on fertility, and the synthetic control model results show that the policy had a large impact on fertility in the mid-2010s but this change has declined since 2019.
Professor Charles Becker, Faculty Advisor
JEL Codes: J, J1, J11, J12, J13
Labor Market Effects of the Minimum Wage in South Korea
by Alec Ashforth
Abstract
This paper analyzes survey data from businesses regarding individual worker earnings, hours, and characteristics from 1971 to 1998 in order to estimate the labor market effects of the minimum wage in South Korea. Since the minimum wage was only implemented in manufacturing, construction, and mining industries, we are able to compare earnings and hours of workers in these industries with workers in other industries using both a difference-in-differences and a synthetic control approach. Additionally, we test to see if the minimum wage had heterogeneous effects based on an individual worker’s gender, level of education, experience, and payment period.
Professor Arnaud Maurel, Faculty Advisor
Professor Kent Kimbrough, Faculty Advisor
JEL Codes: J31, J38, O15
Predicting the Work Task Replacement Effects of the Adoption of Machine Learning Technology
by Shreya Hurli
Abstract
This paper develops a methodology to attempt to predict which tasks in the workforce will be resistant to the replacement of labor by machine learning technology in the near future given current technology and technology adoption trends. Tasks are individual activities completed as parts of a job. Prior research in the field suggests that characteristics of tasks (non-roteness, creativity, analysis/cognitive work) that make them harder for machine learning technology to complete are good predictors of whether those tasks will be resistant to replacement in the workforce. This study utilizes O*NET (Occupational Information Network) task description and education data from October 2015 to August 2020 and Bureau of Labor Statistics salary data to use task characteristics to predict tasks’ resistance to replacement. Normalized scores, average salaries, and average worker education levels are calculated to quantify the relative presence or absence of non-roteness, creativity, and cognitive work in a task. This paper then uses the calculated scores, salary, and education data, as well as a number of interaction terms as inputs to a support vector machine (SVM) model to predict which tasks will be resistant to decline in their shares of workplace tasks weighted by the jobs under which the tasks fall. Using task characteristics, the SVM predicts that just approximately 39% of tasks are likely to be resistant to replacement. These tasks tend to be highly non-deterministic (very non-rote, analytical/cognitive, and/or creative) in nature.
Professor David Berger, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: J23, J24, O33
Analysis of Brain Diagnoses and the Incidence of Chronic Traumatic Encephalopathy (CTE)
by Arjun Lakhanpal
Abstract
Chronic traumatic encephalopathy (CTE) has become a significant area of scientific inquiry in relation to various sports with contact exposure, specifically boxing and professional football, resulting from many individuals who participated in these sports being diagnosed with CTE neuropathology after death. This paper contributes to the CTE literature by analyzing the various predictors of the progression of neurodegenerative disorders, including CTE, that are associated with a history of head impact exposure. In addition, it analyzes how manner of death shifts depending on an individual’s clinical brain diagnosis, which is a decision based upon the clinical record and case review of a patient.
Through data from the NIH NeuroBioBank, the VA-BU-CLF Brain Bank, and data self-collected from living individuals with symptoms associated with CTE, this paper explores an analysis of various brain diagnoses through a large control population and small subset of athletes and veterans. Logistic regression models are established to analyze explanatory variables of clinical brain diagnosis, manner of death, and CTE presence and severity.
These logistic regression models confirm previous research surrounding the potential racial influence present in Black populations with schizophrenia related diagnoses and illustrate the degree to which neurodegenerative disorders, specifically Parkinson’s Disease, are influenced by increased age. Specific to CTE, the analysis conducted through the sample population illustrates the influence of an extra year of football played at the professional level, while counteracting existing literature regarding the association between position and CTE.
Professor Jason Luck,Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: I10, Z20, J15
Impacts of Housing Interventions on Neighborhoods in Durham County
by Cassandra Turk
Abstract
Housing intervention models intended to revitalize neighborhoods and empower homeowners are frequently observed in cities across the United States. To determine the efficacy of these programs, this study analyzes the effects of a housing intervention on the price of the home and the changes in neighborhood characteristics that may lead to neighborhood stability or instability in the long run, including the home prices, the racial makeup, the median income, and crime rates of the neighborhood. To study these characteristics and how they interact with interventions, I implement a propensity score matching model to reduce variation in unobservable characteristics and to isolate the effect of interventions on the block group characteristics of interest. In addition, I implement a non-parametric kernel regression to allow for the possibility of a non-linear relationship between home prices and home interventions. The results show significant evidence that interventions increase neighborhood home values at the bottom 10th percentile and at the median of each block group, suggesting that housing interventions do serve to increase the quality of the neighborhood. However, there is evidence that these effects taper off after a certain percent of the households in the neighborhood have been intervened upon, reducing the marginal benefit of completing a new housing intervention.
Professor Christopher Timmins, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: R2, R23, J10
Maternal Grandparent Living Arrangements and the Motherhood Wage Penalty for Mothers in China
by Mary Wang
Abstract
Living arrangements of mothers in China significantly impact their annual wages and motherhood wage penalties. I study how the presence of mothers’ parents, or the maternal grandparents, affect mothers’ wages for each child living in the mothers’ households. Existing literature finds that mothers in China not only experience a motherhood wage penalty, but also observe wage impacts from the living arrangements of their family members, such as the paternal and maternal grandparents. Although existing research on motherhood wage penalties references the China Health and Nutrition Survey, I use data from the China Family Panel Studies, the most recent and comprehensive panel survey that reflects the social and economic transformations of contemporary China. To extend and update the analysis of living arrangements on the motherhood wage penalty, I present evidence of the impact of living arrangements on the motherhood wage penalty, distinguishing between the presence of the maternal grandmother, maternal grandfather, and both maternal grandparents. While I find clear evidence that the presence of the maternal grandmother in the household counters the motherhood wage penalty, due to the lack of data on single mothers, I am not able to find conclusive evidence of a difference in the impact of grandparents on the motherhood wage penalty for single mothers compared with married mothers.
Professor Peter Arcidiacono, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: J12, J16, J21
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
Hedonic Pricing in the Sneaker Resale Market
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
An Unequal Dream: The Mortgage Rate Premium Paid by Black Communities
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
For Love of the Game: A Study of Tournament Theory and Intrinsic Motivation in Dota 2
By YAO Shengjie
This paper studies the effect of intrinsic motivation on the extrinsic incentives specified by tournament structure in tournament theory in the context of e-sports. It incorporates tournament theory and motivation crowding theory in the same framework, something that past literature have hinted towards but never formally done so. It also uses an e-sports dataset, a type of dataset that few academics in the past have dealt with, but one that offers many interesting potentials. Results weakly show that crowding-in occurs in e-sports, but the effects of tournament structure on performance are inconclusive in the context of this paper. Implications of this paper lie mainly in the possibility for future academics to utilise e-sports data for research.
Advisors: Professor Grace Kim | JEL Codes: J31, J33, J41, M51, M52, Z20
