My research focuses on three aspects of household behavior in the housing market: second generation immigrant decisions of whether to own or rent, and the effect of risky borrowers' adverse selection into down payment assistance and the assistance characteristics on loan defaults.
My first essay "Homeownership Achievement of Second Generation Immigrants Accounting for Social Network Effects" is the first one to study the homeownership of second generation immigrants. Using the National Longitudinal Survey of Youth 1979, my paper identifies a lower propensity to own a house for native born individuals with immigrant parents compared with native-born individuals with native-born parents. I find that a metric to account for ethnic social networks (using the geographic clustering of Hispanics) can help explain the homeownership rate difference between these two groups. My estimation results show that networks of Hispanic homeowners increase the likelihood of homeownership for a Hispanic household, and the network effect is even larger for second generation Hispanics. This result suggests that the effect of knowledge spillover on homeownership decision results not only from the concentration of Spanish speakers, but also through other channels such as social activities which are rarely discussed in the literature.
Wealth levels are another important factors that affect households' homeownership decisions. Various government programs have been developed in the United States to provide down payment assistance (DPA) to low-moderate income borrowers to help them achieve homeownership. However loans with a DPA are often found to have a higher default risk than loans without a DPA. My second essay "High Default Risk on Down Payment Assistance Program: Adverse Selection vs. Program Characteristics?" examines to what extent are higher default rates due to the selection of riskier borrowers into DPAs and characteristics of the DPA program itself. This study addresses this question using monthly panel data of the Ohio Housing Finance Agency's (OHFA) Mortgage Revenue Bond (MRB) first-time home buyer program with two forms of DPAs. To identify the cause of default, I use a two-step algorithm for dynamic choices first proposed in Bajari, Benkard and Levin (2007). I first estimate the choice of DPAs using a multinomial logit model, and the probability of default using a survival model to examine the effect of assistance characteristics on loan defaults. Next I use the estimated survival function to generate borrowers' hypothetical choices based on simulated state transitions, and use the simulated data to recover parameters of a dynamic model of loan default. These estimated parameters measure borrowers' relative utility and risk tolerance of non-housing consumption, and the result indicates that risky borrowers select into DPAs. Based on the results of my empirical and dynamic estimations, I find that both adverse selection and DPA program characteristics increase the likelihood of DPA loans defaulting. A policy implication is that to improve DPA loans' performance, we can either require a lower monthly debt ratio to reduce the risk that is created by the program characteristics, or impose a minimum credit score requirement to reduce the adverse selection. The second policy is more effective, but it may deprive many low credit borrowers' opportunity of achieving homeownership.