Abstract
Threshold cointegration is introduced as an econometric technique to model the impact of trade disruptions on spatial price transmission in commodity markets so that market participants and policy makers can understand the global impact of trade disruptions on prices. The threshold cointegration technique that is employed is flexible in that it allows the number of thresholds and their location to be determined endogenously and the threshold variable to be exogenous to the system. We innovate on the threshold cointegration technique by selecting a measure of trade disruptions as the threshold variable. This innovation can be used for any commodity market that is spatially connected due to arbitrage; however, to illustrate its usefulness we apply the technique to trade disruptions for canola traded between Canada and China using weekly data between 2014 and 2019 and find that canola trade disruptions between Canada and China impacted global price transmission and resulted in market fragmentation.
Highlights
Trade disruption in commodity markets is not rare
These examples highlight the importance of having an appropriate model to investigate the impact of trade disruptions on spatial price transmission in commodity markets so that market participants and policy makers can understand the global impact on prices
This paper introduces threshold cointegration as an econometric technique to model the impact of trade disruptions on spatial price transmission in commodity markets and applies threshold cointegration to trade disruptions of canola traded between Canada and China
Summary
Trade disruption in commodity markets is not rare. For example, there was a disruption of wheat traded between the US and Canada in the early 1990s (Alston et al 1994) and between the US, EU, and Australia in the late 1990s (Balzer and Stiegert 1999). Reasons for the trade disruptions listed as examples include quotas, domestic subsidies, boarder closures due to bovine spongiform encephalopathy (BSE), country of origin labelling and biosecurity. These examples highlight the importance of having an appropriate model to investigate the impact of trade disruptions on spatial price transmission in commodity markets so that market participants and policy makers can understand the global impact on prices. This paper introduces threshold cointegration as an econometric technique to model the impact of trade disruptions on spatial price transmission in commodity markets and applies threshold cointegration to trade disruptions of canola traded between Canada (currently the world’s largest canola exporter) and China (currently the world’s second largest canola importer and Canada’s largest buyer).
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
