Methodological News, Jun 2021

Features important work and developments in ABS methodologies


This issue contains two articles:

  • Trade statistics innovation program
  • Supply chain network model

Trade statistics innovation program

The Trade Statistics Innovation Program is cultivating new data sources to meet emerging information needs. 

The global pandemic and geopolitical changes have increased Australia's exposure to fluctuations in international supply chains. As a trade-dependent nation operating in a fluid environment, there is heightened demand for more informative, timely, and dynamic statistics. 

As a relatively remote island nation, almost all of Australia's trade moves by ship. While data from customs declarations show arrivals, departures and intended destination, they do not include details of a ship's journey. In contrast, the Automated Identification System (AIS) used in collision avoidance by commercial ships provides detailed real-time data on ship movements. For example, if a ship is diverted en route from its original destination, the AIS data can identify this in real time. 

Through collaboration with the United Nation Statistics Division, the ABS has acquired access to AIS data. We are exploring using AIS data to improve the timeliness and accuracy of trade statistics. By collaborating with international partners and harnessing cloud computing infrastructure, the ABS can use new data sources to tackle a wide array of problems.

The possibilities for AIS data as a research tool are numerous and continue to be explored. Possible applications include:

  • Identifying and treating errors in administrative data
  • Measuring port congestion
  • Improving estimates on the final value of exports
  • Identifying the seasonality of supply 
  • Measuring ship fuel consumption


The ABS is currently conducting a proof of concept study using AIS data. The study aims to improve estimates of final export value and identify bottlenecks in trade routes by investigating port congestion. The primary method involves cluster analysis to highlight suboptimal pathing and data integration to improve data quality. Ultimately this work will strengthen existing ABS estimates and support dynamic decision making.

For more information, please contact Harry Raymond.

Supply chain network model

Policy makers depend on an increasing array of information to design resilient policies. The growing interconnectedness of people, companies, and nations has led to an increasingly complex policy space. The COVID-19 pandemic provided some clear examples of this complexity, including the importance of understanding supply chains and the dynamic flows from business to business.

While traditional data analysis for policymaking touches on complexity, the ABS is working to quantify, understand and provide greater insights into these types of complex networks.

The ABS is currently conducting a feasibility study based on network reconstruction methods developed by the Dutch Central Bureau of Statistics to describe the network of flows between businesses. This new study draws on a range of administrative data and aims to construct a policy-relevant and statistically defensible model of Australian supply chain networks.

Although still in the prototype stage, the ABS model of supply chains presents promising opportunities. Even with limited information on foreign businesses, the model could provide new insights into the health and stability of the Australian economy. For the ABS, this may include the potential for developing new economic indicators. For policymakers, the model could be used to simulate the effects of policy implementation. The structure of the supply chains could also be examined over time – providing rich insights into structural changes in the economy. Finally, a fully-developed network model could shed light on critical supply-chain risks by identifying vulnerabilities.

For more information, please contact Harry Raymond.

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Previous releases

Releases from June 2021 onwards can be accessed under research.

Issues up to March 2021 can be found under past releases.

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