Publications

The COVID-19 Pandemic: Government vs. Community Action Across the United States

Published in Covid Economics: Vetted and Real-Time Papers 7 (CEPR), 2020

Are lockdown policies effective at inducing physical distancing to counter the spread of COVID-19? Can less restrictive measures that rely on voluntary community action achieve a similar effect? Using data from 40 million mobile devices, we find that a lockdown increases the percentage of people who stay at home by 8% across US counties. Grouping states with similar outbreak trajectories together and using an instrumental variables approach, we show that time spent at home can increase by as much as 39%. Moreover, we show that individuals engage in limited physical distancing even in the absence of such policies, once the virus takes hold in their area. Our analysis suggests that non-causal estimates of lockdown policies’ effects can yield biased results. We show that counties where people have less distrust in science, are more highly educated, or have higher incomes see a substantially higher uptake of voluntary physical distancing. This suggests that the targeted promotion of distancing among less responsive groups may be as effective as across-the-board lockdowns, while also being less damaging to the economy.

Media: Bocconi Knowledge

The Impact of ECB Quantitative Easing on Income Inequality in the Netherlands: a First Assessment

Published in Bank- en Financiewezen / Revue Bancaire et Financiere, 2018

This article looks at the impact of the 2015 European Central Bank unconventional monetary policy (UMP) on income inequality in the Netherlands. To that end, it uses a panel survey from the Dutch central bank to decompose the contributions of selected UMP channels to the change in household income between two periods (11-13 / 14-16). It finds that UMP's effect through these channels was strongly equalizing. The only two other papers on the topic find similar results for other euro area countries.


Working Papers

Profiling Insurrection: Characterizing Collective Action Using Mobile Device Data

Published at University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2021-13, January 31, 2021

We develop a novel approach for estimating spatially dispersed community-level participation in mass protest. This methodology is used to investigate factors associated with participation in the `March to Save America' event in Washington, D.C. on January 6, 2021. This study combines granular location data from more than 40 million mobile devices with novel measures of community-level voting patterns, the location of organized hate groups, and the entire georeferenced digital archive of the social media platform Parler. We find evidence that partisanship, socio-political isolation, proximity to chapters of the Proud Boys organization, and the local activity on Parler are robustly associated with protest participation. Our research fills a prominent gap in the study of collective action: identifying and studying communities involved in mass-scale events that escalate into violent insurrection.

Media: The Daily Beast, BFI, UChicago News

Unmasking Partisanship: How Polarization Influences Public Responses to Collective Risk

Published at University of Chicago, Becker Friedman Institute for Economics Working Paper No. 2020-102, July 31, 2020

Political polarization and competing narratives can undermine public policy implementation. Partisanship may play a particularly important role in shaping heterogeneous responses to collective risk during periods of crisis when political agents manipulate signals received by the public (i.e., alternative facts). We study these dynamics in the United States, focusing on how partisanship has influenced the use of face masks to stem the spread of COVID-19. Using a wealth of micro-level data, machine learning approaches, and a novel quasi-experimental design, we document four facts: (1) mask use is robustly correlated with partisanship; (2) the impact of partisanship on mask use is not offset by local policy interventions; (3) partisanship is the single most important predictor of local mask use, not COVID severity or local policies; (4) Trump's unexpected mask use at Walter Reed on July 11, 2020 significantly increased social media engagement with and positive sentiment towards mask-related topics. These results unmask how partisanship undermines effective public responses to collective risk and how messaging by political agents can increase public engagement with mask use.

Media: Vox EU, Time magazine, UChicago News, Washington Post

Using Mobile Device Traces to Improve Near-Real Time Data Collection During the George Floyd Protests

Published at SSRN, June 07, 2020

This research note presents a method for using mobile device trace data to improve collection of data on spontaneously erupting protest activity and related events. Based on this method, it presents a highly granular dataset of such activity for the George Floyd Protests in the United States. We use anonymous aggregated mobile device trace data to identify device surges—anomalous changes in the number of devices in a small geographic area—consistent with the assembly of a large number of individuals. Preliminary estimates from ongoing data collection of protest sites and scale are presented. Establishing better measures of where and when protests occur across and within cities improves researchers’ understanding of the downstream political and social consequences of mobilization.

Media: USA Today Ipsos

The Cost of Staying Open: Voluntary Social Distancing and Lockdowns in the US

Published at Economics Series Working Papers 910, University of Oxford, Department of Economics, June 01, 2020

In combating the spread of COVID-19, some governments have been reluctant to adopt lockdown policies due to their perceived economic costs. Such costs can, however, arise even in the absence of restrictive policies, if individuals' independent reaction to the virus slows down the economy. This paper finds that imposing lockdowns leads to lower overall costs to the economy than staying open. We combine detailed location trace data from 40 million mobile devices with difference-in-differences estimations and a modification of the epidemiological SIR model that allows for societal and political response to the virus. In that way, we show that voluntary reaction incurs substantial economic costs, while the additional economic costs arising from lockdown policies are small compared to their large benefits in terms of reduced medical costs. Our results hold for practically all realistic estimates of lockdown efficiency and voluntary response strength. We quantify the counterfactual costs of voluntary social distancing for various US states that implemented lockdowns. For the US as a whole, we estimate that lockdowns reduce the costs of the pandemic by 1.7% of annual GDP per capita, compared to purely voluntary responses.

Media: Vox EU, video

Belief in Science Influences Physical Distancing in Response to COVID-19 Lockdown Policies

Published at Revise & Resubmit, April 28, 2020

Physical distancing reduces transmission risks and slows the spread of COVID-19. Local and regional governments in the United States have issued shelter-in-place policies to mandate physical distancing. Yet compliance with these policies is uneven and may be influenced by beliefs about science and topics of scientific consensus. We theorize that individuals skeptical about the human causes of climate change are less likely to comply with physical distancing orders. Using county-day measures of physical distancing derived from cellphone location data, we demonstrate that the proportion of people who stay at home after lockdown policies go into effect is significantly lower in counties with a high concentration of climate change skeptics. These results are consistent when we study how belief in science influences physical distancing across as well as within Democratic and Republican counties. Our findings suggest public health interventions and messaging about risks associated with COVID-19 that take into account local attitudes towards science may be more effective.