Natural Resources Research Articles

Improved whole-farm planning for mixed-enterprise systems in Australia using a four-stage Stochastic Model with Recourse

Document Type

Article

Publication Date

8-15-2023

Journal Title

Australian Farm Business Management Journal

ISSN

1449-7875

Keywords

Risk modelling, Discrete stochastic programming, Farming systems, Farm management tactics, Australian Farm Optimisation Model

Disciplines

Agribusiness | Agricultural and Resource Economics | Agricultural Economics | Agricultural Science | Agronomy and Crop Sciences | Animal Sciences | Climate | Data Science | Natural Resource Economics | Natural Resources Management and Policy | Operations and Supply Chain Management | Risk Analysis | Statistical Models | Sustainability

Abstract

Farm management occurs against a backdrop of weather-year variation. In Australian mixed enterprise farming systems, how important is it for farm optimisation models to capture this variation and the management tactics matched to that variation? This study compares two whole farm optimisation models of an Australian mixed enterprise farming system. One model represents weather-year variation and the short-term tactical management responses tailored to the unfolding weather-year conditions. The other model is a traditional deterministic steady state model that employs the key assumption that every year is an expected weather-year. Both models require the farm manager to select a profit-maximising suite of enterprises and activities relevant to either the expected weather-year or the suite of weather-years that typify weather-year variation where the farm is located. Comparison of the models’ results reveals key differences in farm strategy, farm tactics and farm profit. The model that includes tactics aligned to the weather-year variation reveals that tactical decision-making increases expected farm profit by about 18 per cent.

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