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Incorporating risk in a positive mathematical programming framework: a dual approach |
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| Authors: | Linda Arata Michele Donati Paolo Sckokai Filippo Arfini |
| Affiliation: | 1. Department of Agricultural and Food Economics, Università Cattolica del Sacro Cuore, Piacenza, Italy;2. Department of Biosciences, Università degli Studi di Parma, Parma, Italy;3. Department of Economics, Università degli Studi di Parma, Parma, Italy |
| 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. |
| Keywords: | agri‐environmental schemes farm behaviour positive mathematical programming risk aversion |
