Competition and innovation, which comprise the driving force of modern economies, have long been an issue in the economics literature. This thesis mainly highlights these two factors in relation to public policy as applied to various analytical frameworks: (i) technology transfer scheme including a grant-back clause when innovation is cumulative (Chapters 1 and 2); (ii) universities that conduct both research and teaching activities (Chapter 3); and (iii) the relationship between competition and productivity (Chapter 4).
Chapter 1 considers desirable technology transfer in a stream of cumulative innovation. Technology competition is likely to generate social overincentives for innovation. It is demonstrated that a grant-back clause with an appropriate distribution of profits can mitigate social overinvestment in the initial and follow-on technologies.
Chapter 2 analyzes the effect of a grant-back clause on incentives to innovate in accordance with the attributes of innovation: severable (non-infringing) and non-severable (infringing). It is illustrated that a grant-back clause under severable innovation can be socially beneficial because it increases the original licensor’s incentive to license.
In Chapter 3, a higher education industry model is examined, where universities conduct research and teaching activities to generate research output and student enrollment. The paradoxical result is that when there is strong substitutability between these two activities, a reduction in not only student enrollment but also research output can occur in response to an increase in research funds. Additionally, this theoretical analysis is motivated by the empirical challenge using the U.S. higher educational institutions data.
Chapter 4 investigates the causal relationship between the effect of competition and TFP growth based on the Japanese industry-level panel data. It finds that although a positive effect of competition is observable in manufacturing industries, such an effect in non-manufacturing industries may be negative in part of the sample period
