This dissertation is composed of two related chapters dealing with research and development. I evaluate the effects of the Research and Experimentation Tax Credit on the Chemicals Industry and then examine the determinants of research joint ventures and technological licenses. The first chapter evaluates the equilibrium effects of the Research and Experimentation Tax Credit, taking into consideration firm interactions. The tax credit was put into place to counteract the underinvestment in private R & D caused by firms not internalizing the benefits of technological spillovers from their research. However, this rationale ignored the impact of product market competition. I propose and estimate a structural dynamic oligopoly model of competition in intellectual assets to capture the impact of interactions between firms in the industry. I estimate the dynamic parameters of the model using methods from Bajari, Benkard, and Levin (2007). I build upon previous estimators by incorporating unobserved firm-level heterogeneity using techniques from Arcidiacono and Miller (2007). I use publicly available panel data on firms' R & D expenditures and their patenting activities to measure innovations. In the data, I observe firms that persistently invest more in research and generate more innovations than other firms that are observationally similar. I model this heterogeneity as an unobserved state that raises a firm's research productivity. In my analysis, I find that increased investment in R & D by more advanced firms due to the subsidy, was largely offset by decreases by smaller firms because of the substitutability of knowledge in product market. This greatly reduced the effectiveness of the policy to spur innovation and limited its impact on social welfare. The second chapter examines the cooperation between innovating firms either through technology licensing or research joint ventures. Both of these types of arrangements help to facilitate the dissemination of productive knowledge permitting the increased application of beneficial innovations. As opposed to the first chapter which considers how untargeted, and unintended transfers of knowledge in the form of spillovers, effected an industry, this chapter examines directed transfers of knowledge. I analyze a cross industry data set of joint ventures and technology licensing deals to examine how industry features affect the manner in which knowledge is shared and how the sharing effects research capabilities of deal participants.