Fake product reviews — and the manipulation of reputation systems by sellers more broadly — are a widespread issue for two-sided platforms. Authors study two primary channels through which such manipulation can affect market outcomes: (i) creating misinformation about the reviewed product, and (ii) breeding mistrust in ratings system overall. To examine these in the Amazon.com marketplace, authors measure misinformation by observing products purchasing fake reviews and measure mistrust by eliciting shoppers’ beliefs about the prevalence of fake reviews on Amazon through an incentivized survey experiment. These are incorporated into a structural model of demand in which consumers form beliefs about product quality based on observed reviews and perceptions about their trustworthiness. 

Findings: Counterfactual policy simulations indicate that fake reviews reduce consumer welfare, shift sales from honest to dishonest sellers, and ultimately harm the platform. Welfare losses arise primarily from misinformation that leads to worse purchases. While mistrust also leads to purchasing mistakes, the consumer harms of mistrust are largely offset by increased price competition under a weakened ratings system. Finally, authors identify key limitations in platforms’ incentives to police manipulation and evaluate enforcement alternatives.

Adequate staffing is critical to the effective operation of health care facilities. Yet, most nursing homes staff below the levels that clinicians, researchers, and advocates consider adequate. Various state and federal proposals have aimed to raise staffing through payment reforms and staffing regulations. To understand the impacts of such policies on patient health, authors study a recent Illinois payment reform aimed at increasing staffing at Medicaid-serving facilities.

Findings: In this case-control study, authors found that a Medicaid policy that incentivized high staffing levels was associated with modest improvement in some dimensions of patient health. However, even modest effects are extremely meaningful at scale: these estimates suggest that if a similar reform were adopted nationally, there would be 6,142 fewer hospitalizations each year. While these findings are promising, they leave considerable room for further research. 

Inspections are a common tool for acquiring information and incentivizing compliance. Although inspections are typically unannounced, their timing often follows a predictable schedule. Authors study how this predictability shapes firm effort and patient outcomes in U.S. nursing homes, leveraging detailed administrative data on staffing, care, and health outcomes. Nursing homes "slack" in the low-risk period following an inspection and ramp up effort as their next inspection approaches. Patient survival mirrors this pattern, suggesting that these fluctuations in effort have meaningful consequences for the quality of patient care. Authors embed these estimates in a dynamic model capturing how inspection regimes incentivize effort and provide information about quality. 

Findings: Estimates indicate that moving to unpredictable inspections could induce as much additional effort as increasing the frequency of inspections by 12%, while only minimally reducing their informational value.

Governments and firms often employ soft spending limits to restrict overspending while still allowing exceptions on a case-by-case basis. This paper studies a Medicare policy which capped per-patient physical therapy spending, with exceptions for patients with documented medical need.  

Findings: The cap reduced spending by 8% without harming patient health, with the targeting improvements driven by Medicare discretion in granting exceptions rather than improved provider screening. However, the documentation requirement also introduced horizontal inequity: conditional on need, lower-income and minority patients were more likely to be screened out, as they tended to see providers with poorer documentation practices.