In this study we develop a new methodological proposal to incorporate risk into a farm-level positive mathematical programming (PMP) model. We estimate simultaneously the farm nonlinear cost function and a farmer-specific coefficient of absolute risk aversion as well as the resource shadow prices. The model is applied to a sample of representative arable crop farms from the Emilia-Romagna region in Italy. The estimation results confirm the calibration ability of the model and reveal the values of the individual risk aversion coefficients. We use the model to simulate different scenarios of crop price volatility, in order to explore the potential risk management role of an agri-environmental scheme.

Incorporating risk in a positive mathematical programming framework: a dual approach / Arata, Linda; Donati, Michele; Sckokai, Paolo; Arfini, Filippo. - In: THE AUSTRALIAN JOURNAL OF AGRICULTURAL AND RESOURCE ECONOMICS. - ISSN 1364-985X. - 61:2(2017), pp. 265-284. [10.1111/1467-8489.12199]

Incorporating risk in a positive mathematical programming framework: a dual approach

DONATI, Michele;ARFINI, Filippo
2017-01-01

Abstract

In this study we develop a new methodological proposal to incorporate risk into a farm-level positive mathematical programming (PMP) model. We estimate simultaneously the farm nonlinear cost function and a farmer-specific coefficient of absolute risk aversion as well as the resource shadow prices. The model is applied to a sample of representative arable crop farms from the Emilia-Romagna region in Italy. The estimation results confirm the calibration ability of the model and reveal the values of the individual risk aversion coefficients. We use the model to simulate different scenarios of crop price volatility, in order to explore the potential risk management role of an agri-environmental scheme.
2017
Incorporating risk in a positive mathematical programming framework: a dual approach / Arata, Linda; Donati, Michele; Sckokai, Paolo; Arfini, Filippo. - In: THE AUSTRALIAN JOURNAL OF AGRICULTURAL AND RESOURCE ECONOMICS. - ISSN 1364-985X. - 61:2(2017), pp. 265-284. [10.1111/1467-8489.12199]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2832773
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