A common tactic to estimate willingness-to-travel exploits variation in the relative proximity of consumers to supplier locations. The validity of these estimates relies on the exogeneity of that consumer-supplier distance. We argue that distance to suppliers is endogenous because suppliers strategically choose locations to target consumers; we introduce a novel instrument to address this form of endogeneity. Using geolocation data from millions of smartphones, we estimate consumer preferences for specific retail chains across income groups and regions. We show that accounting for distance endogeneity significantly alters willingness-to-travel measures. Contrary to the prevailing “retail apocalypse” narrative, we find that consumer surplus per trip to general merchandise stores did not significantly decline from 2010 to 2019. For the lowest-income consumers, the expansion of national chains, particularly dollar stores, nearly compensates for the closure of traditional department stores and regional chains. Notably, failing to account for distance endogeneity leads to the erroneous conclusion that lower-income households experienced statistically significant consumer surplus declines.
We use geospatial data to examine the unprecedented national program currently underway in the United States to distribute and administer vaccines against COVID-19. We quantify the impact of the proposed federal partnership with the company Dollar General to serve as vaccination sites and compare vaccine access with Dollar General to the current Federal Retail Pharmacy Partnership Program. Although dollar stores have been viewed with skepticism and controversy in the policy sector, we show that, relative to the locations of the current federal program, Dollar General stores are disproportionately likely to be located in Census tracts with high social vulnerability; using these stores as vaccination sites would greatly decrease the distance to vaccines for both low-income and minority households. We consider a hypothetical alternative partnership with Dollar Tree and show that adding these stores to the vaccination program would be similarly valuable, but impact different geographic areas than the Dollar General partnership. Adding Dollar General to the current pharmacy partners greatly surpasses the goal set by the Biden administration of having 90% of the population within 5 miles of a vaccine site. We discuss the potential benefits of leveraging these partnerships for other vaccinations, including against influenza.
We examine the potential for exploiting retailer location choice in targeting health interventions. Using geospatial data, we quantify proximity to vaccines created by a U.S. federal program distributing COVID-19 vaccines to commercial retail pharmacies. We assess the distributional impacts of a proposal to provide vaccines at Dollar General, a low-priced general merchandise retailer. Adding Dollar General to the federal program would substantially decrease the distance to vaccine sites for low-income, rural, and minority U.S. households, groups for which COVID-19 vaccine take-up has been disproportionately slow.
Recent literature suggests the power of interventions to change habits. In a dense slum in Nairobi, we adopt best practices from the habit literature to encourage toilet use instead of alternatives that damage community health. Offering subsidies increased toilet usage, effects continue for one month after discounts end, but erode thereafter. Treatments designed to induce habit formation (marketing, time-limited discounts encouraging repetition, discounts for longer periods, targeting `habitual types’) generated no greater persistence. We see some persistent behavior change due to learning about the new toilet option. It appears difficult to induce pro-social behavior without private benefits through habit change.
Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in U.S. nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, Washington to other skilled nursing facilities. The full extent of staff connections between nursing homes—and the role these connections serve in spreading a highly contagious respiratory infection—is currently unknown given the lack of centralized data on cross-facility employment. We perform the first large-scale analysis of nursing home connections via shared staff and contractors using device-level geolocation data from 50 million smartphones, and find that 5.1 percent of smartphone users who visit a nursing home for at least one hour also visit another facility during our 11-week study period—even after visitor restrictions were imposed. We construct network measures of connectedness and estimate that nursing homes, on average, share connections with 7 other facilities. Controlling for demographic and other factors, a home’s staff-network connections and its centrality within the greater network strongly predict COVID-19 cases. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Multivariate regressions comparing demographically and geographically similar nursing homes suggest that 49 percent of COVID cases among nursing home residents are attributable to staff movement between facilities.