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1 Dairy Production Department, Teagasc, Moorepark Production Research Centre, Fermoy, Co. Cork, Ireland
2 Department of Agribusiness, Extension and Rural Development, Faculty of Agriculture, University College Dublin, Belfield, Dublin 4, Ireland
3 Department of Animal Science, Faculty of Agriculture, University College Dublin, Belfield, Dublin 4, Ireland
Corresponding author: L. Shalloo; e-mail: lshalloo{at}moorepark.teagasc.ie.
A stochastic budgetary simulation model of a dairy farm was developed to allow investigation of the effects of varying biological, technical, and physical processes on farm profitability. The model integrates animal inventory and valuation, milk supply, feed requirement, land and labor utilization, and economic analysis. A key model output is the estimated distribution of farm profitability, which is a function of total receipts from milk, calves, and cull cows less all variable and fixed costs (including an imputed cost for labor). An application of the model was demonstrated by modeling 2 calving patterns: a mean calving date of February 24 (S1) and a mean calving date of January 27 (S2). Monte Carlo simulation was used to determine the influence of variation in milk price, concentrate cost, and silage quality on farm profitability under each scenario. Model validation was conducted by comparing the results from the model against data collected from 21 commercial dairy farms. The net farm profit with S1 was 
53,547, and that with S2 was 51,687; the annual EU milk quota was 468,000 kg, and farm size was 40 ha. Monte Carlo simulation showed that the S1 scenario was stochastically dominant over the S2 scenario. Sensitivity analyses showed that farm profit was most sensitive to changes in milk price. The partial coefficients of determination were 99.2, 0.7, and 0.1% for milk price, concentrate cost, and silage quality, respectively, in S1; the corresponding values in S2 were 97.6, 2.3, and 0.1%. Validations of the model showed that it could be used with confidence to study systems of milk production under Irish conditions.
Key Words: whole-farm stochastic budgeting • Monte Carlo simulation • milk production system
Abbreviation key: CDF = cumulative probability distribution function, CSO = Central Statistics Office, DairyMIS = dairy management information system, MDSM = Moorepark Dairy System Model, NE = net energy, S1 = mean calving date February 24, S2 = mean calving date January 27
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