Abstract
This paper combines international economics and network theory to provide a new understanding of the dynamics of interdependent global networks. A stochastic actor-based modeling framework is used to analyze the co-evolution of the mature business network of beer trade and the emerging network of food sector investment using longitudinal time series data from 2003 to 2011 across 178 nations. Controlling for 1) exogenous effects economic development, regionalism and urban growth; and 2) endogenous effects reciprocity, preferential attachment and local clustering, the statistically significant results support that beer trade is a strong predictor for food investment. Reverse causality tests showed no robust results.
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