arXiv subjects

M. Keith Chen

Publications and source records attributed to M. Keith Chen.

5 recordsLinked to original sources

arXiv2022

Smartphone Data Reveal Neighborhood-Level Racial Disparities in Police Presence

While extensive, research on policing in America has focused on documented actions such as stops and arrests -- less is known about patrolling and presence. We map the movements of over ten thousand police officers across twenty-one of America's largest cities by combining anonymized smartphone data with station and precinct boundaries. Police spend considerably more time in Black neighborhoods, a disparity which persists after controlling for density, socioeconomics, and crime-driven demand for policing. Our results suggest that roughly half of observed racial disparities in arrests are associated with this exposure disparity, which is lower in cities with more supervisor (but not officer) diversity.

econ.GN↗

arXiv2020

Racial Disparities in Voting Wait Times: Evidence from Smartphone Data

Equal access to voting is a core feature of democratic government. Using data from millions of smartphone users, we quantify a racial disparity in voting wait times across a nationwide sample of polling places during the 2016 U.S. presidential election. Relative to entirely-white neighborhoods, residents of entirely-black neighborhoods waited 29% longer to vote and were 74% more likely to spend more than 30 minutes at their polling place. This disparity holds when comparing predominantly white and black polling places within the same states and counties, and survives numerous robustness and placebo tests. We shed light on the mechanism for these results and discuss how geospatial data can be an effective tool to both measure and monitor these disparities going forward.

econ.GN↗

arXiv2020

Nursing Home Staff Networks and COVID-19

Nursing homes and other long term-care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes---and the crucial role these connections serve in spreading a highly contagious respiratory infection---is currently unknown given the lack of centralized data on cross-facility nursing home employment. In this paper, we perform the first large-scale analysis of nursing home connections via shared staff using device-level geolocation data from 30 million smartphones, and find that 7 percent of smartphones appearing in a nursing home also appeared in at least one other facility---even after visitor restrictions were imposed. We construct network measures of nursing home connectedness and estimate that nursing homes have, on average, connections with 15 other facilities. Controlling for demographic and other factors, a home's staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Results suggest that eliminating staff linkages between nursing homes could reduce COVID-19 infections in nursing homes by 44 percent.

econ.GN↗

arXiv2020

Causal Estimation of Stay-at-Home Orders on SARS-CoV-2 Transmission

Accurately estimating the effectiveness of stay-at-home orders (SHOs) on reducing social contact and disease spread is crucial for mitigating pandemics. Leveraging individual-level location data for 10 million smartphones, we observe that by April 30th---when nine in ten Americans were under a SHO---daily movement had fallen 70% from pre-COVID levels. One-quarter of this decline is causally attributable to SHOs, with wide demographic differences in compliance, most notably by political affiliation. Likely Trump voters reduce movement by 9% following a local SHO, compared to a 21% reduction among their Clinton-voting neighbors, who face similar exposure risks and identical government orders. Linking social distancing behavior with an epidemic model, we estimate that reductions in movement have causally reduced SARS-CoV-2 transmission rates by 49%.

physics.soc-ph↗

arXiv2018

The Effect of Partisanship and Political Advertising on Close Family Ties

Research on growing American political polarization and antipathy primarily studies public institutions and political processes, ignoring private effects including strained family ties. Using anonymized smartphone-location data and precinct-level voting, we show that Thanksgiving dinners attended by opposing-party precinct residents were 30-50 minutes shorter than same-party dinners. This decline from a mean of 257 minutes survives extensive spatial and demographic controls. Dinner reductions in 2016 tripled for travelers from media markets with heavy political advertising --- an effect not observed in 2015 --- implying a relationship to election-related behavior. Effects appear asymmetric: while fewer Democratic-precinct residents traveled in 2016 than 2015, political differences shortened Thanksgiving dinners more among Republican-precinct residents. Nationwide, 34 million person-hours of cross-partisan Thanksgiving discourse were lost in 2016 to partisan effects.

econ.EM↗