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Estimating Ex Ante Cost Functions for Stochastic Technologies

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  • Robert G Chambers
  • Teresa Serra

Abstract

This paper revisits the problem of estimating ex ante cost functions previously studied by Pope and Just in 1996, as well as Moschini in 2001. An ex ante cost function that generalizes their ex ante cost functions is introduced, and an econometric procedure for estimating a flexible approximation to it is developed. That generalized cost function is economically relevant not only for the Pope and Just 1996 choice setting, but for general producer risk preferences, general stochastic technologies, and general forms of price uncertainty. An econometric strategy for estimating the resulting cost structure that adapts Moschini’s 2001 “full-information” approach is developed, followed by an econometric application to U.S. agriculture.

Suggested Citation

  • Robert G Chambers & Teresa Serra, 2019. "Estimating Ex Ante Cost Functions for Stochastic Technologies," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 101(3), pages 807-824.
    • Handle: RePEc:oup:ajagec:v:101:y:2019:i:3:p:807-824.
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    File URL: http://hdl.handle.net/10.1093/ajae/aay068
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    Cited by:

    1. Robert G. Chambers & Simone Pieralli, 2020. "The Sources of Measured US Agricultural Productivity Growth: Weather, Technological Change, and Adaptation," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1198-1226, August.
    2. Maximilian Koppenberg, 2023. "Markups, organic agriculture and downstream concentration at the example of European dairy farmers," Agricultural Economics, International Association of Agricultural Economists, vol. 54(2), pages 161-178, March.

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