Housing Price Dynamics 2
Paper Session
Sunday, Jan. 5, 2025 1:00 PM - 3:00 PM (PST)
- Chair: Paul Anglin, University of Guelph
The Effect of Targeted Subsidies on the Location Choice of Housing Voucher Recipients: Evidence from the Small-Area Fair Market Rents
Abstract
This paper investigates the scalability of the Small Area Fair Market Rent (SAFMR) policy, a reform to the Housing Choice Voucher (HCV) program designed to reduce poverty concentration by adjusting subsidy caps based on ZIP code-level rents. The SAFMR policy, initially piloted in the Dallas metropolitan area, successfully reduced poverty rates among voucher recipients by enabling moves to lower-poverty neighborhoods. Using HUD administrative data on 280,000 voucher recipients from 2017 to 2019, we extend this analysis to evaluate the SAFMR mandate across 15 metropolitan areas, assessing its broader applicability. Our findings reveal that new voucher recipients are significantly more likely to move to lower-poverty neighborhoods, while existing recipients exhibit stable mobility rates of less than 10% annually. Among movers, we observe reduced exposure to poverty, though racial disparities persist. Notably, White households are twice as likely to move to lower-poverty neighborhoods, reinforcing patterns of racial segregation. We find that local factors significantly influence policy effectiveness across Metros, emphasizing the need to consider contextual differences when scaling housing interventions. This research underscores the critical need to address mobility constraints among low-income populations as a determinant of policy success and offers valuable insights into the challenges of replicating the successes of an experiment across diverse settings.Persistence of Market Conditions in Real Estate Markets
Abstract
We show how using commonly reported measures of real estate market conditions can improve the accuracy of price predictions. The standard model of competitive markets asserts that excess demand causes price(s) to adjust to an equilibrium with little delay. In an illiquid market, such as the market for real estate, attaining an equilibrium may take significantly more time. That fact implies that data on market conditions could be informative. A better understanding of the adjustment process in a real estate market could also lead to buying or selling strategies which are better informed.This paper has two parts. The first part uses different types of models to focus on the conceptual distinction between an exogenous variable and an endogenous variable. Based on this distinction, we offer six hypotheses on why the effects of market conditions might differ between cities. The second part uses vector auto-regression to study the persistence of several variables, with a particular focus on an inflation-adjusted price index and two popular measures of excess demand (the ratio of sales to new listings and “Months of Inventory”). Using monthly data on residential real estate markets in 31 Canadian cities, we find that excess demand affects prices contemporaneously, that changes in measured excess demand persist for a significant period of time and that they affect prices with a lag. We also find evidence of a statistically significant feedback effect, in some cities, from changes in prices to the measures of excess demand.
A Tale of Two U.S. House Price Booms
Abstract
Real US house prices boomed to similar extents in both the early 2000s and in the years following the outbreak of the COVID-19 pandemic, albeit for different reasons. The former boom was set in motion by higher demand arising from a combination of low interest rates and laxer mortgage credit standards. In contrast, the more recent boom arose from higher housing demand - stemming from lower mortgage interest rates and a pandemic-related rise in the demand for space and increased work-from-home (WFH) - pressing up against a less elastic supply of housing. The mortgage rate “lock in” effect reduced the supply of existing homes for sale. In both episodes, extrapolative house price expectations amplified the runup in prices. e establish these results using a house price-to-rent framework and quarterly data spanning four decades. We estimate the determinants of long-run house prices and their dynamic behavior over several business cycles. We find that while the much of the house price increases this decade was induced by earlier low interest rates which have since rebounded, the rise in WFH and mortgage rate lock-in effects prevented much of the prior run-up from unwinding. We estimate that WHF and mortgage rate lock-in effects boosted the house price-to-rent ratio by about 10 percent and up to 8 percent respectively in the long-run. The model results suggest that the deviation of the house price-to-rent ratio from its longer-run, fundamental value is small.Discussant(s)
Yichen Su
,
Southern Methodist University
Diana Mok
,
University of Guelph
Chongyu Wang
,
Florida State University
George Galster
,
Wayne State University
JEL Classifications
- R0 - General