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on Evolutionary Economics |
| By: | Oded Galor; Stelios Michalopoulos |
| Abstract: | This research suggests that the evolution of entrepreneurial spirit played a significant role in the process of economic development and the dynamics of inequality within and across societies. The study argues that entrepreneurial spirit evolved non-monotonically in the course of human history. In early stages of development, the rise in income generated an evolutionary advantage to entrepreneurial, growth promoting traits and their increased representation accelerated the pace of technological progress and the process of economic development. Natural selection therefore had magnified growth promoting activities in relatively wealthier economies as well as within the upper segments of societies, enlarging the income gap within as well as across societies. In mature stages of development, however, non-entrepreneurial individuals gained an evolutionary advantage, diminishing the growth potential of advanced economies and contributing to the convergence of the intermediate level economies to the advanced ones. |
| Keywords: | Elasticity of Substitution, Growth, Technological Progress, Evolution, Natural Selection |
| JEL: | O11 O14 O33 O40 J11 J13 |
| Date: | 2009 |
| URL: | http://d.repec.org/n?u=RePEc:cca:wpaper:111&r=evo |
| By: | Protopapas, M.K.; Kosmatopoulos, E.B.; Battaglia, F. |
| Abstract: | We use co-evolutionary genetic algorithms to model the players' learning process in several Cournot models, and evaluate them in terms of their convergence to the Nash Equilibrium. The ``social-learning'' versions of the two co-evolutionary algorithms we introduce, establish Nash Equilibrium in those models, in contrast to the ``individual learning'' versions which, as we see here, do not imply the convergence of the players' strategies to the Nash outcome. When players use ``canonical co-evolutionary genetic algorithms'' as learning algorithms, the process of the game is an ergodic Markov Chain, and therefore we analyze simulation results using both the relevant methodology and more general statistical tests, to find that in the ``social'' case, states leading to NE play are highly frequent at the stationary distribution of the chain, in contrast to the ``individual learning'' case, when NE is not reached at all in our simulations; to find that the expected Hamming distance of the states at the limiting distribution from the ``NE state'' is significantly smaller in the ``social'' than in the ``individual learning case''; to estimate the expected time that the ``social'' algorithms need to get to the ``NE state'' and verify their robustness and finally to show that a large fraction of the games played are indeed at the Nash Equilibrium. |
| Keywords: | Genetic Algorithms; Cournot oligopoly; Evolutionary Game Theory; Nash Equilibrium |
| JEL: | C73 |
| Date: | 2009–05–22 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:15375&r=evo |
| By: | Luo, Guo Ying |
| Abstract: | This paper builds an evolutionary model of an industry where firms produce differentiated products. Firms have different average cost functions and different demand functions. Firms are assumed to be totally irrational in the sense that firms enter the industry regardless of the existence of profits; firms' outputs are randomly determined rather than generated from profit maximization problems; and firms exit the industry if their wealth is negative. It shows that without purposive profit maximization assumption, monopolistic competition still evolves in the long run. The only long run survivors are those that possess the most efficient technology, face the most favorable market conditions and produce at their profit maximizing outputs. This paper modifies and supports the classic argument for the derivation of monopolistic competition. |
| Keywords: | Evolution; Natural Selection; Irrationality; Monopolistic Competition; Survival of the Fittest; Market Rationality |
| JEL: | D21 L11 D43 |
| Date: | 2009–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:15357&r=evo |