Social and Decision Sciences
Carnegie Mellon University
Porter Hall 208-H
5000 Forbes Avenue
Pittsburgh, PA 15213
Institutional Affiliation: Carnegie Mellon University
NBER Working Papers and Publications
|November 2019||Moved to Vote: The Long-Run Effects of Neighborhoods on Political Participation|
with Eric Chyn: w26515
How does one's childhood neighborhood shape political engagement later in life? We leverage a natural experiment that moved children out of disadvantaged neighborhoods to study effects on their voting behavior more than a decade later. Using linked administrative data, we find that children who were displaced by public housing demolitions and moved using housing vouchers are 12 percent (3.3 percentage points) more likely to vote in adulthood, relative to their non-displaced peers. We argue that this result is unlikely to be driven by changes in incarceration or in their parents' outcomes, but rather by improvements in education and labor market outcomes, and perhaps by socialization. These results suggest that, in addition to reducing economic inequality, housing assistance programs that i...
|Racial Disparities in Voting Wait Times: Evidence from Smartphone Data|
with M. Keith Chen, 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.
|June 2019||Inaccurate Statistical Discrimination|
with J. Aislinn Bohren, Alex Imas, Devin G. Pope: w25935
Discrimination has been widely studied in economics and other disciplines. In addition to identifying evidence of discrimination, economists often categorize the source of discrimination as either taste-based or statistical. Categorizing discrimination in this way can be valuable for policy design and welfare analysis. We argue that a further categorization is important and needed. Specifically, in many situations economic agents may have inaccurate beliefs about the expected productivity or performance of a social group. This motivates our proposed distinction between accurate (based on correct beliefs) and inaccurate (based on incorrect beliefs) statistical discrimination. We do a thorough review of the discrimination literature and argue that this distinction is rarely discussed. Using ...