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According to endogenous growth theory, permanent changes in certain policy variables have permanent effects on the rate of economic growth. Empirically, however, U. S. growth rates exhibit no large persistent changes. Therefore, the determinants of long-run growth highlighted by a specific growth model must similarly exhibit no large persistent changes, or the persistent movement in these variables must be offsetting. Otherwise, the growth model is inconsistent with time series evidence. This paper argues that many AK-style models and R&D-based models of endogenous growth are rejected by this criterion. The rejection of the R&D-based models is particularly strong. I.

I begin this essay by reflecting on my early paper (Nelson, 1859), and Ken’s (Arrow, 1962), as period pieces. These papers certainly have been influential in shaping the discussion of science and technology policy over the last forty years, at least among economists, but at the time they were written, economists were just beginning to get into analysis of the key processes and institutions involved in technological advance. A lot has been learned since that time, and the discussion has become much more sophisticated. I will highlight two of those intellectual developments: the growing recognition that technological advance must be understood as an evolutionary process, and recognition that the institutions involved in that process include much more than the simple market institutions on which economists usually focus. Then I turn to the contemporary policy arena that is the focus of this conference: issues relating to intellectual property. Both to link the discussion to my old paper, and because my own recent research has been focused there, I shall focus particularly on the patenting of “science”. Finally, I will consider the institutional division of labor in research and development, and argue that the question of what should be private and what should be public about science and technology cannot be explored adequately without explicit consideration of mechanisms of funding, and of who is expected to do the work under what terms. I will focus particularly on the role of universities in the system of institutions that do R and D. 2

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What working memory is for Citation for published version: Logie, RH 1997, 'What working memory is for ' Behavioral and Brain Sciences, vol 20, no. 1, pp. 28. Link: Link to publication record in Edinburgh Research Explorer

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the mission of improving DoD’s understanding of the national security implications of the Information Age. Focusing upon improving both the state of the art and the state of the practice of command and control, the CCRP helps DoD take full advantage of the opportunities afforded by emerging

We analyze a large-scale custom software effort, the Worm Community system (WCS), a collaborative system designed for a geographically dispersed community of geneticists. There were complex challenges in creating this infrastructural tool, ranging from simple lack of resources to complex organizational and intellectual communication failures and tradeoffs. Despite high user satisfaction with the system and interface, and extensive user needs assessment, feedback and analysis, many users experienced difficulties in signing on and use. The study was conducted during a time of unprecedented growth in the Internet and its utilities (1991-1994), and many respondents turned to the World Wide Web for their information exchange. Using Bateson’s model of levels of learning, we analyze the levels of infrastructural complexity involved in system access and designeruser communication. We analyze the connection between systems development aimed at supporting specific forms of collaborative knowledge work, local organizational transformation, and large-scale infrastructural change.

Abstract not found