M. Keith Chen
110 Westwood Plaza
Cornell Hall, Suite C513
Los Angeles, CA 90095
Institutional Affiliation: University of California at Los Angeles
NBER Working Papers and Publications
|May 2020||Geographic Mobility in America: Evidence from Cell Phone Data|
with Devin G. Pope: w27072
Traveling beyond the immediate surroundings of one’s residence can lead to greater exposure to new ideas and information, jobs, and greater transmission of disease. In this paper, we document the geographic mobility of individuals in the U.S., and how this mobility varies across U.S. cities, regions, and income classes. Using geolocation data for ~1.7 million smartphone users over a 10-month period, we compute different measures of mobility, including the total distance traveled, the median daily distance traveled, the maximum distance traveled from one’s home, and the number of unique haunts visited. We find large differences across cities and income groups. For example, people in New York travel 38% fewer total kilometers and visit 14% fewer block-sized areas than people in Atlanta. And,...
|November 2019||Racial Disparities in Voting Wait Times: Evidence from Smartphone Data|
with Kareem Haggag, Devin G. Pope, Ryne Rohla: w26487
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.
|March 2017||The Value of Flexible Work: Evidence from Uber Drivers|
with Judith A. Chevalier, Peter E. Rossi, Emily Oehlsen: w23296
Participation in non-traditional work arrangements has increased dramatically over the last decade, including in settings where new technologies lower the transaction costs of providing labor flexibly. One prominent example of flexible work is the ride-sharing company Uber, which allows drivers to provide (or not provide) rides anytime they are willing to accept prevailing wages for providing this service. An Uber-style arrangement offers workers flexibility in both setting a customized work schedule and also adjusting the schedule from week to week, day to day, and hour to hour. Using data on hourly earnings for Uber drivers, we document the ways in which drivers utilize this real-time flexibility and we estimate the driver surplus generated by this flexibility. We estimate how drivers’ r...
Published: M. Keith Chen & Judith A. Chevalier & Peter E. Rossi & Emily Oehlsen, 2019. "The Value of Flexible Work: Evidence from Uber Drivers," Journal of Political Economy, vol 127(6), pages 2735-2794.