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A Methodological Note on the Estimation of Programming Models

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  • Heckelei, Thomas
  • Wolff, Hendrik
Abstract
The paper introduces a general methodological approach for the estimation of constrained optimisation models in agricultural supply analysis. It is based on optimality conditions of the desired programming model and shows a conceptual advantage compared to Positive Mathematical Programming in the context of well posed estimation problems. Moreover, it closes the empirical and methodological gap between programming models and duality based functional models with explicit allocation of fixed factors. Monte Carlo simulations are performed with a maximum entropy estimator to evaluate the functionality of the approach as well as the impact of empirically relevant prior information in small sample situations.

Suggested Citation

  • Heckelei, Thomas & Wolff, Hendrik, 2002. "A Methodological Note on the Estimation of Programming Models," 2002 International Congress, August 28-31, 2002, Zaragoza, Spain 24896, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae02:24896
    DOI: 10.22004/ag.econ.24896
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    References listed on IDEAS

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    1. Moro, Daniele & Sckokai, Paolo, 1999. "Modelling the CAP Arable Crop Regime in Italy : Degree of Decoupling and Impact of Agenda 2000," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 53.
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    5. Heckelei, Thomas & Britz, Wolfgang, 2000. "Positive Mathematical Programming with Multiple Data Points: A Cross-Sectional Estimation Procedure," Cahiers d'Economie et de Sociologie Rurales (CESR), Institut National de la Recherche Agronomique (INRA), vol. 57.
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    9. Barkaoui, Ahmed & Butault, Jean-Pierre, 2000. "Cereals and Oilseeds Supply within the EU, under AGENDA 2000: A Positive Mathematical Programming Application," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 1(2), pages 1-12, August.
    10. Yves Léon & Ludo Peeters & Maurice Quinqu & Yves Surry, 1999. "The use of maximum entropy to estimate input-output coefficients from regional farm accounting data," Post-Print hal-01931589, HAL.
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