Introducing ABARES farmpredict

ABARES Working Paper

Published 17 October 2019

Authors: Neal Hughes, Wei Ying Soh, Chris Boult, Kenton Lawson, Manann Donoghoe, Haydn Valle and Will Chancellor

This paper will be available until 17 April 2020

What is farmpredict?

ABARES has developed a new model, farmpredict which can simulate the effects of price and climate variability on the production and profitability of Australian broadacre farms (Hughes et al. 2019). farmpredict simulates the production of outputs (e.g., wheat, beef cattle, wool etc.), the use of inputs (e.g., fuel, fertiliser, labour etc.) and changes in farm stocks (e.g., livestock and grain) at a farm level, given information on farm fixed inputs (e.g., land and capital), input and output prices and prevailing climate conditions (Figure 1).

For questions relating to this working paper, please contact Neal Hughes.

Figure 1: An overview of farmpredict: ABARES broadacre farm microsimulation model
 

Source: ABARES

farmpredict is a statistical model developed using historical farm survey data from ABARES Australian Agricultural and Grazing Industry Survey (AAGIS), linked to location specific climate data from the Bureau of Meteorology (BoM). farmpredict provides coverage of all major broadacre farming regions and industries including, extensive cropping and livestock (beef and sheep) and mixed farming types (Figure 2).

Map: Australian Agricultural and Grazing Industries Survey (AAGIS) zones and regions

Map: Australian Agricultural and Grazing Industries Survey (AAGIS) zones and regions

What can farmpredict be used for?

ABARES farmpredict model has a range of potential applications including:

  • Historical analysis: the model can be used to measure historical trends in farm productivity and profits controlling for the effects of external factors particularly climate and price variability.  Recently farmpredict has been used to measure the effects of changes in climate conditions on farm profits (Figure 3).
  • Farm risk analysis: The model can also be used to the exposure of farm businesses to climate and price risk. This type of information has a range of potential uses including designing farm insurance products, informing government drought programs, and farm business financial risk assessment
  • Forecasting: Plans are currently underway to link farmpredict to BOM seasonal climate forecasts and ABARES commodity price forecasts, in order to produce short-term (3-12 month) forecasts for Australian broadacre farm production and profits. These forecasts can also serve as an indicator for current and impending drought exposure.
  • Climate change projections: Finally the model can be used to simulate long-term climate projections. These projections would provide an indication of how current farms with current technology would perform under future climate conditions. These results could help indicate which regions, industries and farm types will be under pressure to adapt to future climate change.

Future extensions and related work

farmpredict version 1.0 is already being applied in a number of on-going projects. Various enhancements are also in-progress including linking the model to BOM seasonal climate forecasts (from the ACCESS-S2 climate model) and extending the model to the dairy sector via ABARES Australian Dairy Industry Survey.

ABARES is also collaborating with the Australian Bureau of Statistics (ABS) on a Data Integration Partnership for Australia (DIPA) project ‘Effect of drought on Australian farms’. This project will develop models similar in style to farmpredict but on a much larger scale.

This project will integrate data from the ABS agricultural census, with Australian Tax Office (ATO) financial data from the ABS BLADE to construct database with production and financial information covering essentially all Australian farm business.  

The resulting models (due for completion in June 2020) will have a range of applications, including developing new indicators of farm drought exposure for use in development of parametric farm insurance products.

Download this working paper

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Last reviewed: 9 December 2019
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