By J. K. Sengupta
Jati ok. Sengupta examines the industry dynamics of the evolution of and the impression of recent expertise with R&D and information capital. The publication builds the idea of recommendations within the contexts of the high-tech industries of this day resembling computing and telecommunications.
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Extra info for Competition and Growth: Innovations and Selection in Industry Evolution
This hypothesis tests that the higher deciles of the efﬁciency distribution generate smaller increases in efﬁciency than the lower deciles. This idea has been applied by Mazzucato (2000) in a series of simulation studies based on a differential equation model cj (t + 1) − 1 = −λ(1 − sj (t)), cj (t) λ > 0. This assumes that the speed of cost reduction of an efﬁcient ﬁrm j falls as its market share increases. The adjustment parameter λ determines the speed with which intra-industry costs converge to a minimum cost.
This idea has been applied by Mazzucato (2000) in a series of simulation studies based on a differential equation model cj (t + 1) − 1 = −λ(1 − sj (t)), cj (t) λ > 0. This assumes that the speed of cost reduction of an efﬁcient ﬁrm j falls as its market share increases. The adjustment parameter λ determines the speed with which intra-industry costs converge to a minimum cost. It is an industry-speciﬁc parameter which can be interpreted as the strength of spillover of knowledge and diffusion, that is, the degree of technological opportunity available.
The more general case of cost structures may be easily generalized. The demand function is assumed to be continuous with a negative slope and the cost function is assumed to be strictly convex and continuous. 9) where Q−i = Q − qi . The Cournot–Nash (CN) equilibrium is then deﬁned by f (Q(n)) + qi f (Q(n)) − C (qi (n)) = 0, i = 1, 2, . 10a) where prime denotes derivatives. 10a). He assumed that a symmetric and positive CN equilibrium uniquely exists for each n, so that at qi (n) = q(n) for all i = 1, 2, .