Towards golden rule of capital accumulation: A genetic algorithm approach

Abstract

The current study deals with maximizing consumption per worker in connection with the economic growth of society. The traditional Solow model based approach is well-studied and computationally complex. The present work proposes a Genetic Algorithm (GA) based consumption maximization in attaining the Golden rule. An objective function derived from traditional Solow model based on depreciation rate and amount of accumulated capital is utilized. The current study considered a constant output per worker to incorporate a constant efficiency level of labor. Different ranges of Depreciation rate and accumulated capital are tested to check the stability of the proposed GA based optimization process. The mean error and standard deviation in optimization process is utilized as a performance metric. The experimental results suggested that GA is very fast and is able to produce economically significant result with an average mean error 0.142% and standard deviation 0.021%.