Disease, Downturns, and Wellbeing: Economic History and the Long-Run Impacts of COVID-19
Vellore Arthi, John Parman | September, 20
How might COVID-19 affect human capital and wellbeing in the long run? The COVID-19 pandemic has already imposed a heavy human cost—taken together, this public health crisis and its attendant economic downturn appear poised to dwarf the scope, scale, and disruptiveness of most modern pandemics. What evidence we do have about other modern pandemics is largely limited to short-run impacts. Consequently, recent experience can do little to help us anticipate and respond to COVID-19’s potential long-run impact on individuals over decades and even generations. History, however, offers a solution. Historical crises offer closer analogues to COVID-19 in each of its key dimensions—as a global pandemic, as a global recession—and offer the runway necessary to study the life-course and intergenerational outcomes. In this paper, we review the evidence on the long-run effects on health, labor, and human capital of both historical pandemics (with a focus on the 1918 Influenza Pandemic) and historical recessions (with a focus on the Great Depression). We conclude by discussing how past crises can inform our approach to COVID-19—helping tell us what to look for, what to prepare for, and what data we ought to collect now.
How Valuable are Civil Liberties? Evidence from Gang Injunctions and Housing Prices
in Southern California
Emily Owens, Michelle D. Mioduszewski, Christopher J. Bates | August, 2020
Place-based and proactive policing strategies can reduce crime. However, the broader net impacts of these policies on targeted communities has yet to be quantified, meaning there is little empirical evidence on if, or when, policing is socially beneficial. Using a spatial discontinuity in constraints on police actions created by civil gang injunctions and temporal variation in when injunctions are enacted, we find that aggressive policing can reduce, rather than increase, people’s desire to live in affected neighborhoods. Mover demographics suggest that homebuyers perceive injunction areas as safe places, but where negative police encounters are common. Dividing our sample by pre-injunction crime rates suggest that net willingness-to-pay to avoid aggressive police encounters falls as the possible expected benefit from crime reduction increases.
Understanding Socioeconomic Disparities in Travel Behavior during the COVID-19 Pandemic
Rebecca Brough, Matthew Freedman, and David C. Phillips | June, 2020
We document the magnitudes of and mechanisms behind socioeconomic differences in travel behavior during the COVID-19 pandemic. We focus on King County, Washington, one of the rst places in the U.S. where COVID-19 was detected. We leverage novel and rich administrative and survey data on travel volumes, modes, and preferences for different demographic groups. Large average declines in travel, and in public transit use in particular, due to the pandemic and related policy responses mask substantial heterogeneity across socioeconomic groups. Travel intensity declined considerably less among less-educated and lower-income individuals, even after accounting for mode substitution and variation across neighborhoods in the impacts of public transit service reductions. The relative inability of less-educated and lower-income individuals to cease commuting explains at least half of the difference in travel responses across groups.
Older Workers Need Not Apply? Ageist Language in Job Ads and Age Discrimination in
Ian Burn, Patrick Button, Luis Munguia Corella, and David Neumark | May, 2020
We study the relationships between ageist stereotypes – as reflected in the language used in job ads – and age discrimination in hiring, exploiting the text of job ads and differences in callbacks to older and younger job applicants from a resume (correspondence study) field experiment (Neumark, Burn, and Button, 2019). Our analysis uses methods from computational linguistics and machine learning to directly identify, in a field-experiment setting, ageist stereotypes that underlie age discrimination in hiring. The methods we develop provide a framework for applied researchers analyzing textual data, highlighting the usefulness of various computer science techniques for empirical economics research. We find evidence that language related to stereotypes of older workers sometimes predicts discrimination against older workers. For men, our evidence points to age stereotypes about all three categories we consider – health, personality, and skill – predicting age discrimination, and for women, age stereotypes about personality. In general, the evidence is much stronger for men, and our results for men are quite consistent with the industrial psychology literature on age stereotypes.