Improving agricultural statistics
The productivity, competitiveness, sustainability and profitability of Australian agriculture is enhanced by accurate, timely and reliable agricultural statistics to inform decision-making. Statistics are used to inform management and investment decisions on farm and by government and industry to determine funding arrangements, provide market intelligence, aid planning for emergency responses and guide long-term investment strategies.
In 2015, the National Agricultural Statistics Review (NASR) found that although the current agricultural statistics system has informed government and stakeholder needs for more than a century, there are concerns about the capacity for the system to efficiently meet current and future information needs. To address these concerns, the review recommended a number of actions that would deliver a modern agricultural statistics system that underpins the future profitability of Australia’s agriculture, fisheries and forestry industries.
In response to the review, the Australian Bureau of Statistics and the Department of Agriculture, Water and the Environment, through its research arm, ABARES, are leading efforts between government and industry to develop and implement a modernisation strategy.
The Australian Bureau of Statistics and the Department of Agriculture have developed a Roadmap to improve the agricultural statistics system to guide and coordinate the longer term changes required to deliver a modernised agricultural statistics system.
Modernisation will ensure the sustainability of the agricultural statistics system by reducing survey burden, reducing data collection costs and improving the quality of statistics. This will be achieved by implementing a collect once use multiple times model through cooperation and collaboration between agricultural data holders, in government and industry, and by leveraging the significant investment in ABS technical infrastructure.
February 2018, Agricultural Statistics Roundtable – Government and industry stakeholders met to discuss opportunities to advance the improvement of the agricultural statistics system. Discussions were focussed on identifying key priorities and opportunities for collaboration to progress the modernisation strategy in 2018–19 and beyond.
An assessment of the agricultural statistics system in Australia and its adequacy for informing decision-making, planning and policy making, both now and into the future.
The SBTP is responsible for designing and developing the next generation of statistical business processes and supporting infrastructure. This will provide a platform to reduce costs and burden on providers, integrate datasets to develop new statistical products more rapidly and improve data accessibility.
The DIPA is an investment to maximise the use and value of the Government’s data assets. Through data integration and analysis, the DIPA creates new insights into important and complex policy questions.
A Research and Development Corporation led project to facilitate the development of digital agriculture in Australia, foster the establishment of appropriate legal frameworks, data systems and access to critical datasets and identify the communication systems required to deliver the benefits of digital agriculture.
The Agricultural Data Integration Project
The Agricultural Data Integration Project (AgDIP) is a long-term collaboration between ABARES and the Australian Bureau of Statistics (ABS) to develop, integrate and analyse new large-scale farm level agricultural data sets.
The AgDIP establishes a new national database of Australian farms, including information on agricultural production, business financial outcomes, weather conditions and commodity prices over the period 2000-01 to 2017-18. This database has significant long-term value to government and could inform a wide range of agricultural and environmental issues of relevance to Australian farms.
The project represents an important milestone both for efforts to extract the best possible value and insight from existing government datasets, and for the development of a new, modern approach to agricultural data and statistics that delivers more to industry and government users, while reducing the respondent burden associated with surveys.
The key achievements of the AgDIP to date include the construction of the Farm-level Longitudinal Agricultural Dataset (FLAD), the integration of FLAD with the ABS Business Longitudinal Agricultural Data Environment (BLADE) and the development of new predictive models linking farm outcomes with climate conditions.
In this report five case studies are presented to demonstrate the potential of the AgDIP data / models. In each case more research would be required to confirm, test and expand the results. The case studies include: Trends in Australian crop production, Small area statistics for WA wheat, Effects of drought on cropping farms, Index-based drought insurance for cropping farms, water productivity in the Murray-Darling Basin.