COVID and Cities
Friday, Jan. 7, 2022 3:45 PM - 5:45 PM (EST)
- Chair: Edward Glaeser, Harvard University
The Impact of the Coronavirus Pandemic on New York City Real Estate: First Evidence
AbstractConcerns about the lingering novel Coronavirus may have led to long-term structural change in desired dwelling locations in some large U.S. cities, such as New York City. Densely concentrated neighborhoods may be at higher risk of virus contagion, giving more individuals incentives to move out. We investigate whether this pandemic-induced disamenity adversely affected real estate prices of one- or two-family owner-occupied properties across New York City. First, OLS hedonic results indicate that greater COVID case numbers are concentrated in neighborhoods with lower-valued properties. Second, we use a repeat-sales approach for the period 2003 to 2020, and we find that both the fear of contagion and pandemic-induced income effects adversely impacted home sale prices. Estimates suggest sale prices fell by roughly $60,000 or around 8% in response to both of the following: 1,000 additional infections per 100,000 residents; and a 10-percentage point increase in unemployment in a given MODZCTA. These price effects were more pronounced during the second wave of infections. Based on cumulative MODZCTA infection rates through 2020, the estimated COVID-19 price discount ranged from approximately 1% to 50% in the most affected neighborhoods, and averaged 14%. Interestingly, the fear of contagion effect intensified in the more affluent, but less densely populated NYC neighborhoods, while the income effect was more pronounced in the most densely populated neighborhoods with more rental properties and greater population shares of foreign-born residents. This disparity implies the pandemic led to inequality between homeowners in lower-priced and higher-priced neighborhoods.
Direct and Spillover Effects from Staggered Adoption of Health Policies: Evidence from COVID-19 Stay at Home Orders
AbstractLittle is known about the impact of public health regulations across borders. We estimate the direct and spillover effects of Stay-at-Home- Orders (SHO) on mobility to contain the spread of COVID-19 at the U.S. county level. Adopting counties should experience a decline in mobility due to the direct effect, while neighbors may experience a spillover. We propose a modified difference-in-difference contiguous-county triplets regression design, comparing both a county that adopted the SHO and its neighbor that did not to a neighbor's neighbor (\hinterland"") county. We find that mobility in neighboring counties declined by a third to a half as much as in the directly treated county. These spillovers are concentrated in triplets sharing the same media sources. Using mobility data, we decompose the neighboring counties' decline in mobility into a reduction in external visits from the treated county and a comparably larger voluntary reduction in the neighboring county's own traffic. Together, our results suggest that SHOs operate through information-sharing and illustrate the quantitative importance of voluntary social distancing. The finding that spillovers are positive casts doubt on the argument that a nationally coordinated policy response would have accomplished a greater reduction in mobility and contacts.
The Geography of Remote Work
AbstractWe show that cities with higher population density specialize in high-skill service jobs that can be done remotely. The urban and industry bias of remote work potential shaped the COVID-19 pandemic’s economic impact. Many high skill service workers started to work remotely, withdrawing spending from big-city consumer service industries dependent on their demand. As a result, low-skill service workers in big cities bore most of the recent pandemic’s economic impact. Our findings have broader implications for the distributional consequences of the U.S. economy’s transition to more remote work.
- R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location