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Conclusions

Thinking carefully about the way in which ideas are different from other economic goods leads to a profound change in the way we understand economic growth. The nonrivalry of ideas implies that increasing returns to scale is likely to characterize pro­duction possibilities.

This leads to a world in which scale itself can serve as a source of long run growth. The more inventors we have, the more ideas we discover, and the richer we all are. This also leads to a world where the first fundamental welfare theorem no long necessarily holds. Perfectly competitive markets may not lead to the optimal allocation of resources. This means that other institutions may be needed to improve welfare. The patent system and research universities are examples of such institutions, but there is little reason to think we have found the best institutions - after all these institutions are themselves ideas.

While we have made much progress in understanding economic growth in a world where ideas are important, there remain many open, interesting research questions. The first is “What is the shape of the idea production function?” How do ideas get produced? The combinatorial calculations of Romer (1993) and Weitzman (1998) are fascinating and suggestive. The current research practice of modeling the idea production function as a stable Cobb-Douglas combination of research and the existing stock of ideas is el­egant, but at this point we have little reason to believe that it is correct. One insight that illustrates the incompleteness of our knowledge is that there is no reason why research productivity in the idea production function should be a smooth, monotonic function of the stock of ideas. One can easily imagine that some ideas lead to a domino-like un­raveling of phenomena that were previously mysterious, much like the general purpose technologies of Helpman (1998).

Indeed, perhaps the decoding of the human genome or the continued boom in information technology will lead to a large upward shift in the production function for ideas.[37] On the other hand, one can equally imagine situ­ations where research productivity unexpectedly stagnates, if not forever then at least for a long time. Progress in the time it takes to travel from New York to San Francisco represents a good example of this.

A second unresolved research question is “What is the long-run elasticity of output per worker with respect to population?”. That is, how large are increasing returns to scale. This parameter (labeled γ in the main models of this chapter) is crucially related to the long-run rate of growth of the economy. Estimating it precisely would not only provide confirmation of idea-based growth theory but would also help us in accounting for the sources of economic growth.

Finally, a policy-related question: “What are better institutions and policies for en­couraging the efficient amount of research?”. There is a large, suggestive literature on social rates of return to research and on the extent to which firms might underinvest in research. Still, none of these individual studies is especially compelling, and more accurate estimates of these gaps would be valuable. To the extent that the returns to research do not reflect the marginal benefit to society, better institutions might improve allocations.

Acknowledgements

I am grateful to Philippe Aghion and Paul Romer for helpful comments, and to the National Science Foundation for research support.

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Source: Aghion Philippe, Durlauf Steven N. (eds.). Handbook of Economic Growth. Volume 1. Part B.North-Holland,2005. — p. 1061-1822. 2005
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