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Duality Theory for Variable Costs in Joint Production

Author

Listed:
  • Jeffrey T. LaFrance
  • Rulon D. Pope

Abstract

Duality methods for incomplete systems of consumer demand equations are adapted to the dual structure of variable cost functions in joint production. This allows identification of necessary and sufficient restrictions on technology and cost so that conditional factor demands can be written as functions of input prices, fixed inputs, and cost. These are observable when variable inputs are chosen and committed to production, hence the identified restrictions allow ex ante conditional demands to be studied using observable data. This class of production technologies is consistent with all von Neumann--Morgenstern utility functions when ex post production and/or output prices are uncertain. Copyright 2010, Oxford University Press.

Suggested Citation

  • Jeffrey T. LaFrance & Rulon D. Pope, 2010. "Duality Theory for Variable Costs in Joint Production," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(3), pages 755-762.
    • Handle: RePEc:oup:ajagec:v:92:y:2010:i:3:p:755-762
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    File URL: http://hdl.handle.net/10.1093/ajae/aap040
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    Cited by:

    1. Santeramo, Fabio Gaetano, 2014. "On the estimation of supply and demand elasticities of agricultural commodites," AGRODEP technical notes TN-10, International Food Policy Research Institute (IFPRI).
    2. Jeffrey LaFrance & Rulon Pope & Jesse Tack, 2011. "Risk Response in Agriculture," NBER Chapters, in: The Intended and Unintended Effects of US Agricultural and Biotechnology Policies, pages 143-186, National Bureau of Economic Research, Inc.
    3. Thomas, N., 2021. "Alternative Crop Management Methods to Increase Crop Productivity and Farmer Utility," 2021 Conference, August 17-31, 2021, Virtual 315042, International Association of Agricultural Economists.
    4. Adélaïde Fadhuile & Stéphane Lemarié & Alain Pirotte, 2016. "Disaggregating the Demand for Pesticides: Does it Matter?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(2), pages 223-252, June.
    5. Jesse Tack & Rulon Pope & Jeffrey LaFrance & Timothy Graciano & Scott Colby, 2012. "Intertemporal Risk Management in Agriculture," Monash Economics Working Papers 16-12, Monash University, Department of Economics.
    6. Jesse Tack & Rulon Pope & Jeffrey LaFrance & Ricardo Cavazos, 2012. "Flexible Specification and Robust Estimation of Input Demand Systems," Monash Economics Working Papers 48-12, Monash University, Department of Economics.
    7. Jesse B. Tack & Rulon D. Pope & Jeffrey T. LaFrance & Ricardo H. Cavazos, 2015. "Modelling an aggregate agricultural panel with application to US farm input demands," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 42(3), pages 371-396.
    8. Raushan Bokusheva & Lajos Baráth, 2024. "State‐contingent production technology formulation: Identifying states of nature using reduced‐form econometric models of crop yield," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 805-827, March.
    9. Eldon V. Ball & Ricardo Cavazos & Jeffrey T. LaFrance & Rulon Pope & Jesse Tack, 2010. "Aggregation and Arbitrage in Joint Production," Monash Economics Working Papers archive-22, Monash University, Department of Economics.

    More about this item

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • D2 - Microeconomics - - Production and Organizations
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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