Downloaded by guest on September 28, 2021 www.pnas.org/cgi/doi/10.1073/pnas.2009412117 a Weill A. income Joakim by differentiated strongly emergency declarations COVID-19 to responses distancing Social ogrncalne ehnssmgtivledfeecsin is differences policies involve distancing might social Mechanisms challenge. to long-run responses a behavioral with exhibit it. ated also against buffer preexisting they could that and that distancing show (4) social we healthcare the here of to less and dis- access (5)], the less conditions of to health impacts due health and [e.g., double economic ease be a the to to implies to appear capacity vulnerable This communities most lower lower-income shocks. COVID-19: a health of have and burden and economic (3) with outcomes cope health experi- already worse communities ence lower-income generally, urgency More the to (2). insurance—adds health employer-based grow- critically, predominantly Rapidly benefits—most of accrued. system a has in toll are unemployment full effects ing the such before if ameliorated especially be risk, to COVID-19 whether greater systematically identify are to communities to exposed lower-income need consistent extent urgent what an to is is and of There finding sources data. difference This device three mobile from income. metrics state distancing with social dramatically following across intensity but distancing overall, in social substantial increases COVID- that is the social declarations show during in emergency We States levels differences pandemic. 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COVID-19 distributional exhibit the stark of communities with burden pandemic double income a lower distancing—suggests social finding—that less this core Combining healthcare. shown our to has with access preexisting lower of research areas and levels Previous conditions higher poorest health have most. communities the to income measures, lower mobile to that multiple least pandemic income: from for the by before went while, distancing mobile mobile, social most docu- of from least we ordering went orders, the areas focusing emergency in Wealthy design reversal state study a to event ment subsequent an behavior and Using sources, on data measures. areas, quantiles, mobility poorer income across and than holds areas pattern more wealthier general that this significantly find we mobility pings, derived decreased location measures device mobility mobile Using from income. by declarations varies emergency substantially severe state-level virus, that US the show following (SARS-CoV-2) We distancing of (COVID-19). social 2 2019 transmission disease coronavirus coronavirus the one causes which reduce syndrome are measures to respiratory distancing tools acute 2020) social 11, primary vaccine, May review the a for (received of of 2020 absence 20, July the approved and In NJ, Princeton, University, Princeton Massey, S. Douglas by Edited 95616 CA Davis, California, 94305; CA Stanford, giutrladRsuc cnmc,Uiest fClfri,Dvs A95616; CA Davis, California, of University Economics, Resource and Agricultural 9,ntoa n oa oenet rudtewrdhave world the around governments local (COVID- 2019 and disease national coronavirus of 19), threat the to response n nakn h ehnsstruhwihicm sassoci- is income which through mechanisms the Unpacking | COVID-19 a,1 c eateto cnmc,Uiest fClfri,SnaBraa A916 and 93106; CA Barbara, Santa California, of University Economics, of Department | atiuStigler Matthieu , oildistancing social b lve Deschenes Olivier , c n ihe .Springborn R. Michael and , 1 oeiaie ies . C BY-NC-ND) (CC 4.0 NoDerivatives License distributed under is article access open This interest.y and competing management.y no O.D., project declare M.S., provided authors J.A.W., M.R.S. The and data; J.A.W. analyzed and paper; M.S. the and wrote J.A.W. M.R.S. 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ECONOMIC SCIENCES BRIEF REPORT Completely at Home (%) Device Exposure (number) pare income-differentiated responses to the state declaration. Coefficient estimates for days preceding each state’s declara- 50 tion inform us about potential pretrends, that is, changes in 200 behavior ahead of the policy announcement. In a classical event 40 study analysis, substantial pretrends are a source of concern, for 150 example, indicating prepolicy response. 30 100 Fig. 2 shows event study estimates of the change in the four separate mobility measures (each panel) relative to the 20 50 state emergency declaration date. Estimates for each measure (panel) are differentiated by county income quantile (lines within each panel). We find that pretrends are absent from our pre- Median Distance Traveled (km) Retail and Recreation (rel. baseline) ferred social distancing measure “completely at home” as well as 25 “device exposure.” In contrast, for “median distance traveled,” we find that individuals in wealthier counties show substantial 7 behavior change before their state’s declaration, while “retail 0 and recreation” shows an early pretrend that is then absent in 6 the 2 wk before the event. Postevent, however, for the majority of measures, we estimate large and persistent social distancing −25 5 behavior that is also strongly differentiated by income quintile. For example, for “completely home,” relative to the postdeclara- 4 tion average for all counties, the top income quintile response is Jan Feb Mar Apr Jan Feb Mar Apr essentially doubled, while the bottom income quintile response Date is halved. Substantially more social distancing for the top income Income quintile: 0−20% 20−40% 40−60% 60−80% 80−100% quintile is also apparent for “device exposure” and “retail and recreation.” Fig. 1. Daily mean mobility measures in the United States from mobile Explicitly identifying the relationship between social distanc- devices for weekdays from January 1 to April 21, 2020 by quintiles of median ing and reductions in COVID-19 incidence is a key long-run income at the census tract (Left) or county (Right) level. Thicker lines indi- research need. However, the likely presence of two-way feed- cate the top and bottom quintile. Each panel shows a different measure of social distancing behavior. Data are from SafeGraph, PlaceIQ, and Google. back between distancing and disease will require a creative and comprehensive approach for responsible causal inference. While state emergency declarations were typically the first major steps taken in most jurisdictions, states also took subsequent measures, measure of social distancing, the income differential is reversed and thousands of counties and cities took steps at a finer spatial after March: Individuals in the wealthiest census tracts shift from scale; a longer-run exhaustive accounting of the policy drivers of least to the most likely to completely stay at home, and vice versa distancing should account for these. for the poorest census tracts. Overall, we show that social distancing following states’ emer- The “device exposure” measure provides a proxy captur- gency declarations is substantial and strongly differentiated by ing how often people are going to places combined with how crowded those places are. We found that the prepan- demic income–mobility disparity—where high-income counties have substantially higher exposure—converges to parity under the pandemic. The “median distance traveled” income pattern diverges from the income-ranked relationship observed for other measures. This distance increases and then decreases as income quintile increases; that is, middle-income quintile travelers typi- cally move farther in a day than the lowest and highest income quintile. This pattern holds before and after the arrival of the pandemic, with the highest income quintile again showing the biggest change in behavior consistent with social distancing. The time series discussed above suggest that income differences are key determinants of mobile devices-based mobility measures. However, poorer and wealthier census tracts (or counties) are located in areas with different characteristics, where measures inducing social distancing may have been mandated at different times. To address both concerns in a multivariate framework, we use a panel regression analysis with an event study design to estimate how social distancing behaviors are related to state emergency declarations, and how the response varies by income group (Eq. 1). The event study model includes county fixed effect to control for the main effect of time-invariant county-specific factors such as income and population density, and also includes day fixed effects to control for temporal shocks common to all counties (e.g., federal policies). Furthermore, as is standard with event study designs, we estimate the dynamic impact of the man- dates by including lags and leads of the event date (12). More Fig. 2. Event study estimates of the change in a mobility measure (each specifically, we estimate a separate response for each of 20 days panel) relative to state emergency declarations, differentiated by median before and after an emergency declaration (normalized to occur income quintile at the census tract (Left) or county (Right) level. Error bars at relative day 0), for each income quintile, allowing us to com- represent 90% CIs. State declaration occurs at day k = 0.

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ECONOMIC SCIENCES BRIEF REPORT