Original Research Article
Exploring Risk Judgments in a Trade Dispute Using Bayesian Networks
Article first published online: 4 FEB 2014
© 2014 Society for Risk Analysis
Volume 34, Issue 6, pages 1095–1111, June 2014
How to Cite
Wintle, B. C. and Nicholson, A. (2014), Exploring Risk Judgments in a Trade Dispute Using Bayesian Networks. Risk Analysis, 34: 1095–1111. doi: 10.1111/risa.12172
- Issue published online: 26 JUN 2014
- Article first published online: 4 FEB 2014
- Bayesian network;
- decision support;
- import risk analysis;
- risk perception;
Bayesian networks (BNs) are graphical modeling tools that are generally recommended for exploring what-if scenarios, visualizing systems and problems, and for communication between stakeholders during decision making. In this article, we investigate their potential for exploring different perspectives in trade disputes. To do so, we draw on a specific case study that was arbitrated by the World Trade Organization (WTO): the Australia-New Zealand apples dispute. The dispute centered on disagreement about judgments contained within Australia's 2006 import risk analysis (IRA).
We built a range of BNs of increasing complexity that modeled various approaches to undertaking IRAs, from the basic qualitative and semi-quantitative risk analyses routinely performed in government agencies, to the more complex quantitative simulation undertaken by Australia in the apples dispute. We found the BNs useful for exploring disagreements under uncertainty because they are probabilistic and transparently represent steps in the analysis. Different scenarios and evidence can easily be entered. Specifically, we explore the sensitivity of the risk output to different judgments (particularly volume of trade). Thus, we explore how BNs could usefully aid WTO dispute settlement.
We conclude that BNs are preferable to basic qualitative and semi-quantitative risk analyses because they offer an accessible interface and are mathematically sound. However, most current BN modeling tools are limited compared with complex simulations, as was used in the 2006 apples IRA. Although complex simulations may be more accurate, they are a black box for stakeholders. BNs have the potential to be a transparent aid to complex decision making, but they are currently computationally limited. Recent technological software developments are promising.