Thomas Kopp and Jan Salecker: Identifying Influential Traders by Agent Based Modelling
Understanding individual traders’ channel choices is important to policy makers because it yields information on which channels are effective in transmitting information. Since trading networks are characterised by feedback mechanisms along several dimensions they can be understood as complex adaptive systems. Conventional approaches, such as regression analysis, face severe drawbacks when modelling these since endogeneity is omnipresent. Instead, they are best studied via agent based modelling. This paper applies an ABM to the empirical example of rubber trade in Indonesia, which is a dense network. Results indicate that the decision for traders' channel choices are mostly driven by physical distance and debt obligations, and to a minor extent by peer-interaction.