Abstract: We analyze wartime prosthetic device patents to investigate how procurement policy affects the cost, quality, and quantity of medical innovation.  Analyzing whether inventions emphasize cost and/or quality requires generating new data.  We do this by first hand-coding the economic traits emphasized in 1,200 patent documents.  We then train a machine learning algorithm and apply the trained models to a century's worth of medical and mechanical patents that form our analysis sample.  In our analysis of these new data, we find that the relatively stingy, fixed-price contracts of the Civil War era led inventors to focus broadly on reducing costs, while the less cost-conscious procurement contracts of World War I did not.  We provide a conceptual framework that highlights the economic forces that drive this key finding. We also find that inventors emphasized dimensions of product quality (e.g., a prosthetic's appearance or comfort) that aligned with differences in buyers' preferences across wars.   Finally, we find that the Civil War and World War I procurement shocks led to substantial increases in the quantity of prosthetic device patenting relative to patenting in other medical and mechanical technology classes.  We conclude that procurement environments can significantly shape the scientific problems with which inventors engage, including the choice to innovate on quality or cost.

(first author with Aaron Boussina, Supreeth Shashikumar, Gabriel Wardi, Christopher Longhurst, Shamim Nemati)

Journal of Medical Internet Research, 2023, 25(e43486)

Research Question: Are there ways to embed economics into AI models used in health care settings? Our research takes a cost-benefit approach to optimize the use of an AI algorithm that alerts healthcare providers to sepsis cases within a specific diagnostic group, such as heart disease. Our simulations show potential cost savings of $4.6 billion and higher accuracy using our implementation.

Working Papers

 Abstract: How does FDA regulation affect innovation and market concentration? I examine this question by exploiting FDA deregulation events that affected certain medical device types but not others. I collect comprehensive data on medical device innovation, device safety, firm entry, prices, and regulatory changes and enhance these data using text analysis methods. My analysis of these data reveals three key findings. First, deregulation events significantly increased the quantity and quality of new technologies in affected medical device types relative to controls. These increases are particularly strong among small and inexperienced firms. Second, these events increased firm entry and reduced prices for medical procedures that utilize affected medical device types. Finally, rates of serious injuries and deaths attributable to defective devices did not significantly increase following these events. Interestingly, deregulating certain device types was associated with reduced adverse event rates, possibly due to firms increasing their emphasis on product safety in response to increased litigation risk.

Works in Progress

The Long-Run Impacts of Regulated Price Cuts: Evidence from Medicare

(with Yunan Ji)

Abstract: We examine how regulated price cuts affect innovation, market structure, and product quality. We exploit a series of Medicare price cuts for durable medical equipment (DME), which lowered the Medicare reimbursement prices of some DME categories by 21%, leaving others unaffected. Following the price cuts, new device introductions fell by 25%, indicating a price elasticity of 1.2, accompanied by a decrease in patenting and R&D spending. Entry by domestic manufacturers decreased by 76% while production offshoring increased. These shifts resulted in deteriorated product quality, evidenced by increased repair and replacement rates and adverse event reports. Our findings highlight the importance of considering these long-run consequences when designing price regulations.

Social Media Outreach and SNAP Take-Up

Abstract: In a California field experiment, I examined the impact of Facebook outreach that encouraged enrollment in the Supplemental Nutritional Assistance Program (SNAP). Over 16,000 eligible non-participants were randomly assigned to control and treatment groups, with the latter exposed to ads highlighting SNAP's benefits, a streamlined application process, or efforts to reduce stigma. Despite these efforts, the campaign did not measurably impact enrollment. Reflecting a scenario not uncommon in outreach efforts, the outreach sample inadvertently included some individuals already enrolled in SNAP, leading to temporary disenrollments within this subgroup.

Other Publications