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Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level

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  • Wolfgang Britz
  • Linda Arata

Abstract

This study belongs to the barely explored research strand of “Econometric Mathematical Programming” and presents a simultaneous estimation of the cost function and of the farmers’ risk attitude parameter in a programming model setup. Resource and policy constraints of the model are allowed to be not binding. We use crop shares as decision variables to avoid scale bias and we consider price and crop yield variances separately. The model is formulated as a bi‐level programming model and the empirical application concerns three unbalanced panels of specialized arable farms observed for at least three consecutive years in Northern Italy, in the Cologne‐Aachen area in Germany and in the Grandes‐Cultures area in France over the time period 1995–2007. We achieve a quite satisfactory fit in the estimation exercise and find own and cross price elasticities from sensitivity experiments in reasonable ranges. We also propose a novel approach to derive confidence intervals around parameter estimates for Econometric Mathematical Programming.

Suggested Citation

  • Wolfgang Britz & Linda Arata, 2019. "Econometric mathematical programming: an application to the estimation of costs and risk preferences at farm level," Agricultural Economics, International Association of Agricultural Economists, vol. 50(2), pages 191-206, March.
    • Handle: RePEc:bla:agecon:v:50:y:2019:i:2:p:191-206
    DOI: 10.1111/agec.12476
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    References listed on IDEAS

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    1. Shyam Kumar Basnet & Torbjörn Jansson & Thomas Heckelei, 2021. "A Bayesian econometrics and risk programming approach for analysing the impact of decoupled payments in the European Union," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 65(3), pages 729-759, July.
    2. Athanasios Petsakos & Stelios Rozakis, 2022. "Models and muddles: comment on ‘Calibration of agricultural risk programming models using positive mathematical programming’," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(3), pages 713-728, July.
    3. Obafèmi P. Koutchadé & Alain Carpentier & Fabienne Femenia, 2021. "Modeling Corners, Kinks, and Jumps in Crop Acreage Choices: Impacts of the EU Support to Protein Crops," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(4), pages 1502-1524, August.

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