Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020.

The collapse of economic activity in 2020 from COVID-19 has been immense. An important question is how much of that collapse resulted from government-imposed restrictions versus people voluntarily choosing to stay home to avoid infection. This paper examines the drivers of the economic slowdown using cellular phone records data on customer visits to more than 2.25 million individual businesses across 110 different industries. Comparing consumer behavior over the crisis within the same commuting zones but across state and county boundaries with different policy regimes suggests that legal shutdown orders account for only a modest share of the massive changes to consumer behavior (and that tracking county-level policy conditions is significantly more accurate than using state-level policies alone). While overall consumer traffic fell by 60 percentage points, legal restrictions explain only 7 percentage points of this. Individual choices were far more important and seem tied to fears of infection. Traffic started dropping before the legal orders were in place; was highly influenced by the number of COVID deaths reported in the county; and showed a clear shift by consumers away from busier, more crowded stores toward smaller, less busy stores in the same industry. States that repealed their shutdown orders saw symmetric, modest recoveries in consumer visits, further supporting the small estimated effect of policy. Although the shutdown orders had little aggregate impact, they did have a significant effect in reallocating consumer visits away from "nonessential" to "essential" businesses and from restaurants and bars toward groceries and other food sellers.

Health Care Exceptionalism? Performance and Allocation in the US Health Care Sector.

The conventional wisdom for the healthcare sector is that idiosyncratic features leave little scope for market forces to allocate consumers to higher performance producers. However, we find robust evidence - across several different conditions and performance measures - that higher quality hospitals have higher market shares and grow more over time. The relationship between performance and allocation is stronger among patients who have greater scope for hospital choice, suggesting that patient demand plays an important role in allocation. Our findings suggest that healthcare may have more in common with "traditional" sectors subject to market forces than often assumed.

Geographic Variation in Rosiglitazone Use Surrounding FDA Warnings in the Department of Veterans Affairs.

BACKGROUND: Geographic variation in the use of prescription drugs, particularly those deemed harmful by the FDA, may lead to variation in patient exposure to adverse drug events. One such drug is the glucose-lowering drug rosiglitazone, for which the FDA issued a safety alert on May 21, 2007, following the publication of a meta-analysis that suggested a 43% increase in the risk of myocardial infarction with the use of rosiglitazone. This alert was followed by a black box warning on August 14, 2007, that was updated 3 months later. While large declines have been documented in rosiglitazone use in clinical practice, little is known about how the use of rosiglitazone and other glucose-lowering drugs varied within the Department of Veterans Affairs (VA), surrounding the FDA alerts. Understanding this variation within integrated health care systems is essential to formulating policies that enhance patient protection and quality of care. OBJECTIVE: To document variation in the use of rosiglitazone and other glucose- lowering drugs across 21 Veterans Integrated Service Networks (VISNs). METHODS: We conducted a retrospective analysis of drug use patterns for all major diabetes drugs in a national cohort of 550,550 veterans with diabetes from 2003 to 2008. This included the time periods when rosiglitazone was added to (November 2003) and removed from (October 2007) the VA national formulary (VANF). We employed multivariable logistic regression models to statistically estimate the association between a patient's location and the patient's odds of using rosiglitazone. RESULTS: Aggregate rosiglitazone use increased monotonically from 7.7%, in the quarter it was added to the VANF (November 4, 2003), to a peak of 15.3% in the quarter when the FDA issued the safety alert. Rosiglitazone use decreased sharply afterwards, reaching 3.4% by the end of the study period (September 30, 2008). The use of pioglitazone, another glucose-lowering drug in the same class as rosiglitazone, was low when the FDA issued the safety alert (0.4%) but increased sharply afterwards, reaching 3.6% by the end of the study period. Insulin use increased monotonically; metformin use remained relatively flat; and sulfonylurea use exhibited a general declining trend throughout the study period. Statistically significant geographic variation was observed in rosiglitazone use throughout the study period. The prevalence range, defined as the range of minimum to maximum use across VISNs was 3.7%-12.4% in the first quarter (January 1 to March 31, 2003); 1.0%-5.5% in the last quarter of study period (July 1 to September 30, 2008); and reached a peak of 9.6%-25.5% in the quarter when the FDA safety alert was issued (April 1 to March 31, 2007). In 5 VISNs, peak rosiglitazone use occurred before the FDA issued the safety alert. The odds ratio of using rosiglitazone in a given VISN varied from 0.55 (95% CI = 0.52-0.59; VISN 10) to 1.58 (95% CI = 1.50-1.66; VISN 15), with VISN 1 being the reference region. The variation was higher in the periods after the FDA issued the safety alert. Much less variation was observed in the use of pioglitazone, metformin, sulfonylurea, and insulin. CONCLUSIONS: Our results show statistically significant variation in the way VISNs within the VA responded to the FDA alerts, suggesting a need for mechanisms that disseminate information and guidelines for drug use in a consistent and reliable manner. Further study of regions that adopted ideal practices earlier may provide lessons for regional leadership and practice culture within integrated health care systems.

Network structure of production.

Complex social networks have received increasing attention from researchers. Recent work has focused on mechanisms that produce scale-free networks. We theoretically and empirically characterize the buyer-supplier network of the US economy and find that purely scale-free models have trouble matching key attributes of the network. We construct an alternative model that incorporates realistic features of firms' buyer-supplier relationships and estimate the model's parameters using microdata on firms' self-reported customers. This alternative framework is better able to match the attributes of the actual economic network and aids in further understanding several important economic phenomena.