Abstract
Under a resource-based view of the firm, economic agents transform resources from one form into another. These transformations can be viewed as the application of technology. The relationships between the technologies present in an economy can be modeled by a transformation network. The size and structure of these networks can describe the “economic complexity” of a society. In this paper, we use an agent-based computational economics model to investigate how the density of a transformation network affects the economic performance of its underlying artificial economy, as measured by the GDP. Our results show that the mean and median GDP of this economy increases as the density of its transformation network increases; furthermore, the cause of this increase is related to the number and type of cycles and sinks in the network. Our results suggest that economies with a high degree of economic complexity perform better than simpler economies with lower economic complexity.
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Hollander, C.D., Garibay, I., O’Neal, T. (2012). Transformation Networks: A study of how technological complexity impacts economic performance. In: Teglio, A., Alfarano, S., Camacho-Cuena, E., Ginés-Vilar, M. (eds) Managing Market Complexity. Lecture Notes in Economics and Mathematical Systems, vol 662. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31301-1_2
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DOI: https://doi.org/10.1007/978-3-642-31301-1_2
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