Abstract
The international trade in commodities forms a complex network of economic interdependencies. This network now plays a central role in promoting global economic development and security. However, significant asymmetries have been noted in terms of access to this network, and in the unequal distribution of the benefits and risks accrued from the system as a whole. Understanding the statistical properties and dynamics of the trade network have therefore, become important tools for investigating a multitude of real-world policy concerns relevant to economics, public policy, and international development. This thesis focuses on investigating three of these issues---market growth, price inequality, and supply risks. The first of these projects focuses on modelling the growth of commodity markets, and the resulting effect on network topology. The second, looks at how asymmetries in network can lead to varying prices for the same good, and explores the implications for developing more equitable market structures. The final project contributes to our understanding of how export restrictions affect the network structure of trade and how these risks can undermine global food security. Throughout, a network science approach is employed, whereby trade is modelled as a graph-like structure, with the topology of trade being the primary focus of analysis. To support this approach, we introduce several theoretical models, and apply simulations on both real-world, and artificially produced trade network data. The outcome of this research improves on our ability to identify and target key participants within a market, and predict policies that favour more stable and equitable structures that better facilitate trade.