A Framework for Modelling Whole-Farm Financial Risk

We consider the limitations of optimisation analyses that ignore farm-level financial risks arising from combinations of high fixed costs, including debt burdens and highly variable local weather and prices. A sequential multivariate analysis method is used to compute cumulative distribution functions of decadal whole-farm cash balances for a farm facing highly variable prices and weather, and a level of opening debt. This enables direct probabilistic projections of long-term whole-farm financial viability typical of the Coolamon area in New South Wales. We contrast this with a partial-budgeting linear programming study using average annual prices and weather for the same farm. Our focus is on the effects of varying sheep stocking rates, given different pasture compositions in rotation with cropping under weather and price variations over time and different levels of starting debt. We show how best practice recommendations based on partial costing might mislead by ignoring the powerful cumulative effects of input variability and compounding debts. Increasing production, often already near the achievable water-limited potential, can be of far lower priority than reducing costs and lowering heavy debt burdens. We demonstrate that whole-farm financial risk profiles of a farm's options provide a richer, more meaningful basis for sound advice