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.

Arata, L., Donati, M., Sckokai, P., Arfini, F., Incorporating risk in a positive mathematical programming framework: a dual approach, <<THE AUSTRALIAN JOURNAL OF AGRICULTURAL AND RESOURCE ECONOMICS>>, 2017; 61 (2): 265-284. [doi:10.1111/1467-8489.12199] [http://hdl.handle.net/10807/98617]

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

Arata, Linda
Primo
;
Sckokai, Paolo
Penultimo
;
Arfini, Filippo
Ultimo
2017

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.
Inglese
Arata, L., Donati, M., Sckokai, P., Arfini, F., Incorporating risk in a positive mathematical programming framework: a dual approach, <<THE AUSTRALIAN JOURNAL OF AGRICULTURAL AND RESOURCE ECONOMICS>>, 2017; 61 (2): 265-284. [doi:10.1111/1467-8489.12199] [http://hdl.handle.net/10807/98617]
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10807/98617
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