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Free keywords:
Innovation; Risk; Uncertainty; Skew distributions; Gibrat's Law
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.
