ISSN:
1432-1386
Keywords:
Key words: Innovation – Risk – Uncertainty – Skew distributions – Gibrat's Law
;
JEL-classification: O31, C15
Source:
Springer Online Journal Archives 1860-2000
Topics:
Economics
Notes:
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.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/s001910050011
