IPRs, Technological Development, and Economic Development

In the year 2000 some $142 billion in royalties were paid internationally by users of a specific piece of knowledge that were protected under Intellectual Property Right law (IPR) to those parties that owned these rights. Under current circumstances where knowledge & innovation play an increasingly significant role in the economy (Foray & Lundvall 1996, Cowan, David and Foray 2000, Cooke 2002, Dolfsma & Soete 2006, Dolfsma 2005). IPRs have become increasingly prominent in debates and are almost unanimously deemed to favor economic development by policymakers, and certainly by policymakers in developed countries. While it has been acknowledged that some parties may benefit more from a system of IPRs than others, in relative terms a Pareto improvement is the expected outcome (Langford 1997). This has not always been the case. In addition, the academic (economic) community is almost unanimous about the system of IPR overshooting its goals. This has been the motivation to include IPRs in the WTO negotiations. The TRIPS agreement (Trade-Related Aspects of Intellectual Property Rights) has resulted in 1994 from these negotiations. Especially during the 1990s the number of patents granted has grown tremendously despite the fact that many a scholar still supports Machlup’s (1958, p.28) conclusion that:“it would be irresponsible, on the basis of our present knowledge of its consequences, to recommend instituting one. But since we have had a patent system for a long time, it would be irresponsible, on the basis of our present knowledge, to recommend abolishing it.â€From other corners, where specific effects of IPRs are considered, a different and less circumspect sound may be heard. Examples of this are attempts to make available HIV/AIDS drugs at a reduced price compared to what the pharmaceutical companies that have the patents on these drugs demand. I will focus on patents.Empirical and theoretical findings bearing on the question of IPRs’ effect on technological development, and thus prospect for economic development, are reviewed. Static and dynamic effects are distinguished. Areas where static effects may be expected include transfer of knowledge, balance of payment effects, effects for large as opposed to small firms, and effect on the ‘extent of the market’. Areas for dynamic effects include technological development and technological preemption. The list may not be exhaustive, and effects are interlocking: they may be mutually reinforcing or they may conflict. I will mostly focus on ‘dynamic’ effects.Economic Dynamics;IPRs;Intellectual Property Rights;Technological Development

Towards a Dynamic (Schumpeterian) Welfare Economics

For an economy where knowledge plays an increasingly important role in shaping its dynamics, economics needs a dynamic (Schumpeterian) welfare theory. This paper sketches the role of knowledge in an economy and argues that a static Paretian welfare economics is inadequate, or at least needs to be supplemented. As suggested by the work of Schumpeter, a dynamic welfare economics acknowledges the role of knowledge. In a dynamic welfare economics, I suggest, different costs of communication are central, indicating that knowledge may not be readily diffused or exchanged. Recent developments in Intellectual Property Right (IPR) law are evaluated to determine the extent to which they affect communication costs and thus future economic welfare.communication;knowledge economy;IPR;communication costs;welfare theory

Lock-in & Break-out from Technological Trajectories: Modeling and policy implications

Arthur [1,2] provided a model to explain the circumstances that lead to technological lock-in into a specific trajectory. We contribute substantially to this area of research by investigating the circumstances under which technological development may break-out of a trajectory. We argue that for this to happen, a third selection mechanism--beyond those of the market and of technology--needs to upset the lock-in. We model the interaction, or mutual shaping among three selection mechanisms, and thus this paper also allows for a better understanding of when a technology will lock-in into a trajectory, when a technology may break-out of a lock-in, and when competing technologies may co-exist in a balance. As a system is conceptualized to gain a (third) degree of freedom, the possibility of bifurcation is introduced into the model. The equations, in which interactions between competition and selection mechanisms can be modeled, allow one to specify conditions for lock-in, competitive balance, and break-out

Currents and Sub-currents in the River of Innovations - Explaining Innovativeness using New-Product Announcements

In their seminal paper, Acs and Audretsch (1988) analyze innovation patterns across industries and identify several determinants of innovativeness, both positive and negative. Their work is seminal if only because of the unique data they use to measure innovativeness: new-product announcements. They show that industry concentration, degree of unionization would hamper innovation; industries characterized by increased shares of skilled labor and large firms provide favorable conditions for innovation. By analyzing a new and more consciously compiled database, we re-examine their original claims. Our results largely support the findings of Acs & Audretsch, but diverge from them in one important way. We suggest that the large firms do not contribute more to a industry’s innovativeness than small firms – a vindication of the Schumpeter Mark I perspective. In addition, we analyze micro-level data of individual firms. Firms within different sub-groups respond differently to their competitive environment. We show that less dedicated innovators prove more susceptible to environmental factors than more committed innovators. In addition, an unfavorable competitive environment decreases the likelihood that less successful innovators will announce new products.Innovation;Innovation Sub-Currents;New-Product Announcements;Schumpeter Mark I

Technology Push, Demand Pull And The Shaping Of Technological Paradigms - Patterns In The Development Of Computing Technology

An assumption generally subscribed in evolutionary economics is thatnew technological paradigms arise from advances is science anddevelopments in technological knowledge. Demand only influences theselection among competing paradigms, and the course the paradigm afterits inception. In this paper we argue that this view needs to beadapted. We demonstrate that in the history of computing technology inthe 20th century a distinction can be made between periods in whicheither demand or knowledge development was the dominant enabler ofinnovation. In the demand enabled periods new technological (sub-)paradigms in computing technology have emerged as well.enablers of innovation;history of computing;technological paradigms

The Geography of Innovativeness - New product announcements in The Netherlands

In contrast to findings in other countries, and surprisingly in view of the literature, innovation in the Netherlands is not spread geographically according either to relevant labour market characteristics or to localized agglomeration economies. Instead, statistical analysis shows that the Netherlands is an urban field, and that the regional knowledge infrastructure ? universities of technology in particular - is the only variable that can offer an explanation of innovative activity throughout the country. By analysing similar relationships for younger firms, we are able to make a quite strong case about causation. We estimate these regional spillovers using the Literature Based Innovation Output indicator by screening two successive volumes of 43 specialist trade journals for product announcements. Output indicators for innovativeness ? except for patents, which have well-known disadvantages as an indicator ? are not often used in the relevant literature, partly because they are not readily available. Our analysis offers the possibility to assess how consistent the use of input versus output indicators of innovativeness is in the analysis of the geographical spread of innovative activity.