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A Bayesian Framework For Optimal Input Allocation With An Uncertain Stochastic Production Function

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  • William E. Griffiths

Abstract

A Bayesian approach is used to provide a framework for optimal input allocation for a stochastic production function with uncertain parameters. The chosen production function is a single-input version of a function which can exhibit positive or negative marginal risk. The sensitivity of optimal input allocation to the degree of risk aversion, the marginal risk parameter, and the assumed level of uncertainty about the parameters is examined. Using an example problem it is shown that parameter uncertainty will not always lead to a lower input level when a producer is risk averse. Some problems with the production function specification are uncovered, as is the incompatibility of some expected utility and stochastic assumptions.
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Suggested Citation

  • William E. Griffiths, 1986. "A Bayesian Framework For Optimal Input Allocation With An Uncertain Stochastic Production Function," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 30(2-3), pages 128-152, 08-12.
    • Handle: RePEc:bla:ajarec:v:30:y:1986:i:2-3:p:128-152
    DOI: j.1467-8489.1986.tb00661.x
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    Cited by:

    1. William E. Griffiths & Jock R. Anderson & K.B. Hamal, 1987. "Subjective Distributions As Econometric Response Data," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 31(2), pages 127-141, August.
    2. Wall, Charles A. & Fisher, Brian S., 1988. "Supply Response and the Theory of Production and Profit Functions," Review of Marketing and Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 56(03), pages 1-22, December.

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