Intergenerational Economic Transfers and Wealth Inequality in the United States
by Parinay Gupta
Abstract
Using longitudinal data from Panel Study of Income Dynamics (PSID) from 2007-2021, this paper investigates the role of economic transfers (inheritances and gifts) in asset accumulation processes of US households, in both short-term and long-term. Analysis is done through dimensions of race, wealth quartile, and age. Examining quartiles reveals significant wealth disparities, mirrored in income and education levels. Racially, White households consistently hold higher wealth, income, and educational levels compared to Black households, indicating systematic racial disparities. Multivariate analysis uncovers relationships between socio-economic factors and wealth. Past wealth positively influences future accumulation, except for the lowest quartile. Labor income negatively impacts wealth, particularly in lowest quartile, potentially indicating poverty traps and dissaving, while asset income positively affects quartiles except the lowest, in both short-term and long-term. Total expenditure initially reduces wealth but reverses in quartiles except the lowest in both time frames. Race is significantly associated with wealth, with young Black households consistently disadvantaged, though this reverses for the wealthiest quartile and in longerterm. Age correlates positively with wealth. Transfers’ (inheritances and gifts) impact varies across quartiles, showing diminishing returns and switching signs as wealth quartile increases, indicating differential returns for upper quartiles. Noteworthy is the positive association between transfers received 8-10 years ago and current wealth, irrespective of age and wealth quartile, highlighting their significant long-term role in wealth accumulation.
Professor William Darity, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: D14, D31, J15
The Case for Clemency: Differential Impacts of Pretrial Detention on Case and Crime Outcomes
by George Rateb
Abstract
About half-million of individuals in US jails are detained pretrial while legally presumed
innocent. Using data on quasi-randomly assigned bail judges in the third-largest court system in
the U.S., we study the impact of pretrial detention on defendants’ court and crime outcomes
between 2008 and 2012. We supplement our primary analysis to document patterns on bail
amounts and how they differentially impact Black defendants relative to their white and Hispanic
counterparts. Instrumental variable estimates suggest that pretrial detention increases the
likelihood of being found guilty, mainly driven by the uptake of guilty pleas, especially for
minorities. By linking court and jail data, we provide mechanistic evidence that jail time is
positively correlated with the uptake of these guilty pleas. To the best of our knowledge, these
findings have not been empirically documented due to a lack of previous data availability.
Professor Bocar Ba, Faculty Advisor
Professor Michelle Connolly, Faculty Advisor
JEL Codes: C26; J15; K14
Subprime’s Long shadow: Understanding subprime lending’s role in the St. Louis vacancy crisis
by Glen David Morgenstern
Abstract
Using loan-level data, this analysis attempts to connect the events of the subprime home loan boom to the current vacancy crisis in St. Louis, Missouri. Borrowers in Black areas in the north of St. Louis City and St. Louis County received subprime home loans at higher rates during the subprime boom period of 2003-2007 than those in White areas, with differences in balloon loans especially stark. Specifically, borrowers in Black neighborhoods received subprime loans more frequently than those with equal FICO scores in White neighborhoods. As a result of these differential loan terms, North City and inner ring “First Suburb” areas saw more foreclosure and
borrower payment delinquency, which in turn were highly associated with home vacancy, controlling for other risk factors. However, foreclosure was no longer a significant predictor of home vacancy
after controlling for demographic factors and FICO score, indicating that the unequal loan terms may have driven much of the increase in home vacancy in the St. Louis area since the Great Recession.
Professor Charles Becker, Faculty Advisor
JEL Codes: R1; R3; R11; R31; J1; J15
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
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
Female Labor Force Participation in Turkic Countries: A Study of Azerbaijan and Turkey
By Natasha Jo Torrens
Encouraging female labor force participation (FLFP) should be a goal of any country attempting to increase their productive capacity. Understanding the determinants and motivations of labor force participation requires isolating the factors that influence a woman’s decision to enter or leave formal employment. In this thesis, I utilize data from the Demographics and Health Surveys to explain the role of social conservatism in promoting or limiting participation in the labor force. I focus on ever-married women in Azerbaijan and Turkey to provide a lens through which to explain the unexpectedly low FLFP of Turkey. Though most prior research attempts to explain Turkey’s low FLFP rate by comparisons to other OECD countries, my study looks at Turkey through the context of other Turkic cultures to explore cultural factors driving labor force participation for ever-married women. This study finds a negative correlation between conservatism and the likelihood of participating in the labor force for ever married women in Azerbaijan, and a larger, positive relationship in Turkey.
Advisors: Professor Charles Becker, Professor Didem Havlioğlu, Professor Kent Kimrbough | JEL Codes: C50, J16, N95
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
Endogeneity in the Decision to Migrate: Changes in the Self-Selection of Puerto Rican Migrants before, during, and after the Great Recession
By Aasha Reddy
Migrants self-select on characteristics such as income. We use the U.S. Census’ ACS and PRCS to study changes in selection patterns of Puerto Rican migrants to the to the U.S. mainland (50 states) before, during, and after the Great Recession (2005 to 2016). We construct counterfactual income densities to compare incomes of Puerto Rican migrants to the mainland versus incomes of island residents under equivalent returns to skill. We examine where Puerto Rican migrants to the mainland tend to fall in the island’s income distribution and find that Puerto Rican migrants tend to come from the top 20% of the island’s income distribution. This pattern remained stable with little to no effect of the Great Recession on selectivity patterns.
Advisors: William Darity and Michelle Connolly | JEL Codes: J15, J61, O15
The Effect of Minority History on Racial Disparities in the Mortgage Market: A Case Study of Durham and New Haven
By Jisoo Yoon
In the aftermath of the housing market crash, the concentration of subprime mortgage loans in minority neighborhoods is a current and long-standing issue. This study investigates the presence of racial disparities in mortgage markets by examining two cities with contrasting histories of African American and Hispanic establishment: Durham, North Carolina and New Haven, Connecticut. This study examines data by the Home Mortgage Disclosure Act (HMDA), and distills the effect of minority legacy on the perception of racial risk by using econometric instruments to separate the behavior of national lenders and local lenders. The econometric methods allow national lenders to reflect objective risk measures and neighborhood race dynamics, while local lenders reflect subjective attitudes towards certain races. With its longer history of African American presence, Durham shows a positive attitude towards Black borrowers at the local level, while New Haven shows a more favorable attitude towards its Hispanic residents. Nonetheless, racial legacy also materializes as a negative factor in the form of increased residential segregation and spillover effects. Furthermore, a temporal variation analysis of pre- and post-mortgage market reform data affirms the disappearance of racial bias and continued presence of spillover risk in Durham.
Advisor: Christopher Timmins | JEL Codes: C01, G21, J15, R21, R23, R31 | Tagged: Econometrics, Mortgages, Economics of Minorities, Races, Census, Migration, Population, Neighborhood Characteristics, Housing Supply and Market
