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Comparative statics for state-contingent technologies


  • Chambers, Robert G.
  • Quiggin, John


The implications of supermodularity for comparative-static analysis in a generalized version of the separable-effort representation of a firm facing stochastic prices and a stochastic technology are. Previous analysis is generalized in two ways. General risk-averse, as opposed to expected-utility, preferences are considered. The stochastic technology is represented by an Arrow-Debreu state-space representation. It is shown that results familiar from the theory of the price taking firm in the absence of risk generalize to the uncertain case.

Suggested Citation

  • Chambers, Robert G. & Quiggin, John, 2003. "Comparative statics for state-contingent technologies," Risk and Sustainable Management Group Working Papers 150351, University of Queensland, School of Economics.
  • Handle: RePEc:ags:uqsers:150351

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    References listed on IDEAS

    1. Susan Athey, 2002. "Monotone Comparative Statics under Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 117(1), pages 187-223.
    2. Sandmo, Agnar, 1971. "On the Theory of the Competitive Firm under Price Uncertainty," American Economic Review, American Economic Association, vol. 61(1), pages 65-73, March.
    3. Milgrom, Paul & Shannon, Chris, 1994. "Monotone Comparative Statics," Econometrica, Econometric Society, vol. 62(1), pages 157-180, January.
    4. Milgrom, Paul, 1994. "Comparing Optima: Do Simplifying Assumptions Affect Conclusions?," Journal of Political Economy, University of Chicago Press, vol. 102(3), pages 607-615, June.
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    Cited by:

    1. Susan Athey, 2002. "Monotone Comparative Statics under Uncertainty," The Quarterly Journal of Economics, Oxford University Press, vol. 117(1), pages 187-223.

    More about this item


    risk aversion; production; supermodularity; Production Economics; Risk and Uncertainty; D21; D81;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty


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