Uncertainty and the size distribution of rewards from innovation |
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Authors: | F. M. Scherer Dietmar Harhoff Jörg Kukies |
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Affiliation: | John F. Kennedy School of Government, Harvard University, Cambridge, MA 02138, USA (e-mail: mike_scherer@harvard.edu), US Universit?t München, D-80539 München, Germany, DE Graduate School of Business, University of Chicago, Chicago, USA, US
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Abstract: | Previous research has shown that the distribution of profit outcomes from technological innovations is highly skew. This paper builds upon those detailed findings to ask: what stochastic processes can plausibly be inferred to have generated the observed distributions? After reviewing the evidence, this paper reports on several stochastic model simulations, including a pure Gibrat random walk with monthly changes approximating those observed for high-technology startup company stocks and a more richly specified model blending internal and external market uncertainties. The most highly specified simulations suggest that the set of profit potentials tapped by innovators is itself skew-distributed and that the number of entrants into innovation races is more likely to be independent of market size than stochastically dependent upon it. |
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Keywords: | : Innovation – Risk – Uncertainty – Skew distributions – Gibrat's Law |
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