Damage vs. Risk Perception: Why do House Prices Recover After Hurricane? (Job Market Paper)
I study house price dynamics following Hurricane Sandy to explain the common puzzling finding of a price drop, followed by a complete price recovery. Applying a quasi-experimental difference-in-differences research design on Zillow parcel-level sales, I show using FEMA data that the extent of direct damages drives the decline in house prices. The extent of remodeling expenditures, based on building permits, is found to be responsible for causing the return of prices to pre-storm levels. Comparing flood insurance take-up rates in the affected and non-affected areas within the floodplains, I find there is no revision in perceived risk.
To Dodd-Frank and Back: Regulatory Burden and the Economic Growth, Regulatory Relief, and Consumer Protection Act, Joint work with Joseph Santos, The American Economist (Accepted)
We measure the regulatory burden Dodd-Frank imposes and the regulatory relief Economic Growth, Regulatory Relief, and Consumer Protection Act (EGRRCPA) affords. We analyze burden and relief on various measures of bank performance. And we emphasize community-bank holding companies (BHC). Based on data in the Consolidated Financial Statements for Holding Companies (FR-Y9C) reports from 1991 to 2019 and a model of a price-taking intermediary, we parsimoniously specify each performance measure as a function of BHC-specific observable variables, BHC-specific unobservable heterogeneity, Dodd-Frank regulation, and EGRRCPA relief. On balance, we find Dodd-Frank reduces loans per as- sets and loans per employee, while it increases non-interest expenses. Meanwhile, EGRRCPA provides some regulatory relief. For example, for mid-sized community BHCs, the implementation of EGRRCPA increases return on assets by roughly 23 basis points annually.
The Effects of Public Transit on Employment Outcomes
This paper studies the effects of having access to light rail stations on residents’ employment at the census block level using the Dallas light rail system as a case study. Utilizing the variation between the 1983 historical proposal and its current system, I implement the staggered difference-in-differences estimation. My main outcome variable is the total number of employed residents from the Longitudinal Employer-Household Dynamics (LEHD) Origin-Destination Employment Statistics data. I find no evidence that proximity to stations will boost the employment outcome of census blocks in all three measures of buffer: 1/4-mile, 1/2-mile, and 1-mile radius.
Work in Progress