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Using alterative whole-farm modelling approaches to assess farm enterprise selection, risk and welfare


  • Komarek, Adam M.
  • MacAulay, T. Gordon


Using an expected mean-variance model the changes in farm enterprise levels and indirect utility were examined under conditions of risk aversion, budget constraints and gross margin variance. An extension of the comparative statics of the expected mean-variance model was adopted by introducing a budget constraint into the constrained optimisation problem. A 10-year expected mean-variance whole-farm model was solved for a farm in the wheat-sheep zone of Australia to provide an empirical example. Results were obtained using no planning horizon (the static model) and then with a five-year rolling planning horizon (the dynamic model). In addition, enterprise levels were constrained to match levels observed on the farm so as to compare incomes between the constrained and unconstrained models. For a cash constrained, risk averse, farmer it was found that they are likely to have larger expenditures than less risk averse operators in order to obtain the same indirect utility. Enterprise levels differed between the dynamic and static models, and a dynamic model was used to help explain inter-temporal decision-making. Risk aversion reduced the set of possible welfare improving production activities available to a farmer.

Suggested Citation

  • Komarek, Adam M. & MacAulay, T. Gordon, 2011. "Using alterative whole-farm modelling approaches to assess farm enterprise selection, risk and welfare," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100574, Australian Agricultural and Resource Economics Society.
  • Handle: RePEc:ags:aare11:100574

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    Whole-farm modelling; enterprise selection; risk.; Farm Management; Q12; C61;

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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