The U.S. Food and Drug Administration’s Orphan Drug Designation (ODD) program, established in 1983, aims to stimulate innovation for rare diseases by offering incentives such as tax credits, user fee waivers, and seven years of market exclusivity. While the program has spurred investment in treatments for small patient populations, its application at the drug-indication level creates opportunities for strategic behavior. Using a novel panel dataset from Cortellis Competitive Intelligence, we document how firms combine rare and non-rare indications within single drug development projects to exploit economies of scope and, in some cases, to extend market exclusivity beyond the regulation’s intent.

Descriptive evidence reveals frequent indication expansion during clinical development, particularly among partial orphan projects (mix of both rare and larger-market diseases). Building on these patterns, we develop an econometric framework to estimate the causal impact of ODD on drug development outcomes and to identify spillovers to non-orphan indications. Our results inform the policy debate on whether current ODD incentives effectively promote socially valuable innovation or inadvertently invite strategic behavior that dilutes program efficiency.

This paper studies how patent trading affects innovation in the U.S. pharmaceutical industry. I construct a novel dataset linking the timing of patent transfers to drug development stages and show that 82% of trades occur before launch, and that such trades significantly increase success rates. To interpret these patterns, I develop and estimate a dynamic model where firms differ in stage-specific expertise and can trade patents under search frictions and transaction costs. The model reveals that transferring patents to experienced firms raises success rates and innovation value, but trade frictions hinder efficient transfers. Counterfactuals show that reducing transaction costs boosts launch rates and innovation value, while targeted subsidies at specific stages outperform uniform ones in efficiency and cost-effectiveness.

Does technology trade encourage or discourage innovations? Previous studies indicate that technology trade increases welfare by reallocating patents to better matched firms. Using patent application and reassignment data in the U.S. pharmaceutical industry, this paper develops a dynamic structural model to estimate the impact of patent trade on subsequent innovation decisions. The patents bought by a firm can be used as a substitute to own innovation, or as a complement to speed up the development of new ideas. By allowing the patents created within the firm and bought from others to work differently on a firm’s production of goods and on generating new ideas, I find evidence that both patented and non patented knowledge capital (KC) positively contribute to the production of output, though the former has much stronger effect in the production of ideas. While self-generated KC plays a complementary role in future innovation, the KC bought from others is used as substitutes to self-generated KC. A counterfactual exercise is conducted to predict how frictions in the patent market affect future innovation outcomes. Lowering transaction cost in the patent trade market by 50%, I find both producers and non producers participate more actively in the market but in a different way. Producers increase more the stock of patent bought while non producers increase the stock of patent selling. In the long run, lower transaction cost has negative impact on producer’s innovation decisions but increases non producer’s patentable innovation ideas.