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. Acknowledgement : Financial support from the German Research Foundation (DFG) within Collaborative Research Centre 990 Ecological and Socioeconomic Functions of Tropical Rainforest Transformation Systems in Sumatra, Indonesia (CRC990) is greatly appreciated. Thomas Kopp thanks DFG for generous support within project KO 5269/1-1. Valuable assistance in literature search was provided by Stefan Moser.


Issue Date:
2018-07
Publication Type:
Conference Paper/ Presentation
DOI and Other Identifiers:
Record Identifier:
https://ageconsearch.umn.edu/record/277130
Language:
English
JEL Codes:
C65; Q12




 Record created 2018-10-02, last modified 2020-10-28

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