Sheep Updates 2005 ©Chief Executive Officer of the Department of Agriculture WHEN YOU’RE ON A GOOD THING, DO IT BETTER: An economic analysis of sheep breed profitability. Emma Kopke, DAWA Ross Kingwell, DAWA John Young, Farming Systems Analysis Service ABSTRACT Favourable prices for lamb and mutton since 2001 have sparked Australian farmers’ interest in sheep breeds such as the Dohne Merino and South African Meat Merino that are better suited to meat production than the Merino. In this analysis, historical commodity price data and a whole-farm bio- economic model have been used to assess the likely profitability of these breeds in a southern coastal region of Western Australia. Results indicate that a Merino flock is likely to generate significantly greater profits than a Dohne or SAMM flock, however the variance of profit for the Merino is also likely to be greater. If micron premiums remain low, there is little economic merit in disinvesting in Merinos to fully switch to either of the two alternatives. AIM To identify the robustness of profitability of the Australian Merino, the Dohne Merino and South African Meat Merino. METHOD MIDAS is a whole-farm, profit-maximizing model that calculates optimal farm management practices given a set of production relationships provided by the user. Optimal combinations of enterprises are found through using detailed biological, technical and financial information to compare the relative profitability of various enterprise combinations. For a full description of MIDAS see Kingwell and Pannell Error! Reference source not found.. The South Coast version of the model (SC-MIDAS) was used in this analysis. It is based on a typical mixed crop and livestock farming system in the region north of Albany to east of Esperance (medium rainfall: 400-500 mm). Assumed farm size is 2500 ha. Pure bred self-replacing Australian Merino (Merino), Dohne Merino (Dohne) and South African Meat Merino (SAMM) flocks were examined. Up to 33% of wether and surplus ewe lambs were allowed to be sold as prime lambs in the Merino flock and up to 90% in the Dohne and SAMM flocks. The impact on farm profit of movements in prices of crops, wool and sheepmeat 1 was examined. Real historical monthly commodity price data were collated and the correlations between commodity prices were calculated. Probability distributions of prices for all commodities were simulated using the software package @RISK 2 . Commodity price scenarios were inputs into MIDAS and probability distributions of profit were generated. The risk of variation in the price differential between fine and broad wool was not built in to the simulation performed by @RISK. For this reason, fibre diameter premium risk was modelled separately. Two scenarios for micron premium were considered: a) most likely scenario - similar to the long term (10 year average), where there has been a significant premium for finer wool; and b) worst case scenario - similar to the short term (3 year average), where there has been little price differential between broader/finer wools. 1 SAMM ewes (mutton) and wethers (shippers) were assumed to attract a 20% premium ($/head) over Merinos. Dohnes were assumed to attract a 10% premium ($/head) over Merinos (2.) 2 To overcome some period differences in the dataset, the correlation matrix was made consistent within @Risk (3). The sampling technique used to generate the data was Latin Hypercube. This sampling technique uses stratified sampling, and was chosen for increased sampling efficiency and faster runtime (3). To ensure convergence in sampling, 5000 iterations of commodity prices were run.