2016 Honors Thesis Abstracts
Yuhao (Jeremy) Fan
In this paper, I analyze the consumer’s credit card consumption data from a commercial bank in China. To do so, I refer to the SMC model proposed by Schimittlein et al. in 1987. I am proposing an extension to the model to incorporate the credit card spending amount into the model. I use transaction frequency, recency (defined as how recent a customer has used the credit card) and spending amount data to model consumer credit card consumptions and estimate parameters with the data. I get reliable estimates from the model. I introduce a value measure that is less informative but easier to compute than traditional CLV measures, to measure consumers’ contribution to the credit card issuer (the value of credit cards). I define the value measure of a credit card as the expected spending amount next month conditional on the card still active in this month. I further regress the value measures against the characteristics information of consumers and credit card to examine which characteristics information are the best predictors of values of the credit cards. I find that characteristic information is not useful estimates of the value measure of a credit card. Rather, the on-going value of a credit card is best explained by prior consumption records.
Over the past 15 to 20 years, financial inclusion has gained traction as an area of study that is pertinent to ensuring inclusive economic growth and reducing wealth inequality. Participation in the financial mainstream by maintaining a standard bank account, enables households to build savings, accrue wealth, build credit, expand business enterprises and invest in education. To date, much of the research on why 7.7% of all American households are unbanked has analyzed the problem as a question of consumer choice. I hypothesize that the characteristics of a local banking market, and the banks that comprise it, also influence the prevalence of account ownership among potential customers. To analyze the factors that influence account ownership, I use a weighted least-squares grouped logit regression and data from the 2014 FDIC Summary of Deposits, the US Census Bureau’s 2014 American Community Survey and 2014 Community Research Data from the Corporation for Economic Development. My research constitutes the first empirical analysis of and attempt at modeling unbanked rates. My findings suggest that variations in local banking communities do have significant impacts on unbanked rates.
Racial residential segregation in St Louis has profound economic consequences. In addition to a limited access to jobs and quality of schools, segregation may play an important role in property value. Changing racial composition of neighborhoods can increase or decrease property values depending on who is moving in. This analysis will tackle the question: do property values drop when black families move in? Moreover, I will attempt to distinguish between race and socioeconomic status as the primary driver of property value appreciation in racially transitioning neighborhoods. The results of this study support the Racial Proxy Hypothesis: a theory that states that property values may drop when blacks move in because of deteriorating neighborhood socioeconomic conditions rather than racial prejudice.