Racing To Invest? The Dynamics of Competition in Ethical Drug Discovery

Recent advances in the theoretical literature have greatly expanded our understanding of the forces that shape the competitive dynamics of research and development, but a paucity of sufficiently detailed empirical data has left these insights relatively untested. We draw on unusually detailed qualitative and quantitative infernal data provided at the research program level by 10 major pharmaceutical firms to explore the usefulness of the modern literature as a source of insight into the dynamics of competition in ethical drug discovery. Our analysis focuses on one particularly compelling aspect of the literature: the suggestion that in “winner take all situations,” competition in R&D becomes a Prisoner's Dilemma, leading to overinvestment in research. Without adequate measures of the social return to innovation, we can say nothing about whether there is “too much” or “too little” research undertaken by the industry, but our results do not support the suggestion that R&D investment in drug discovery is driven by the “tit‐for‐tat” or simple reaction function models hinted at by the institutional literature. First, R&D investment is only weakly correlated across firms once common responses to exogenous shocks are accounted far, and second, rivals' R&D results are positively correlated with own research productivity, which we interpret as evidence for extensive R&D spillovers rather than the depletion externality implied by “winner take all” models. These results are not, of themselves, sufficient to reject the hypothesis that investment behavior in the industry is driven by strategic considerations since there is theoretical support for a wide variety of observable behavior as equilibrium outcomes of strategic interaction. Nonetheless, they suggest that the more extreme forms of rent dissipation identified in the literature are probably poor characterizations of the reality of competition in pharmaceuticals. Our results point both to the need to develop theories that incorporate richer models of possible payoff structures, adjustment costs, and firm heterogeneity and to the need to collect empirical data that is comprehensive enough to enable one to test them.