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Modelling Farmers’ Behaviour Toward Risk in a Large Scale Positive Mathematical Programming (PMP) Model

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Advances in Applied Economic Research

Part of the book series: Springer Proceedings in Business and Economics ((SPBE))

Abstract

Agricultural production is characterized for being a risky business due to weather variability, market instability, plant diseases as well as climate change and political economy uncertainty. The modelling of risk at farm level is not new, however, the inclusion of risk in Positive Mathematical Programming (PMP) models is particularly challenging. Most of the few existing PMP-risk approaches have been conducted at farm-type level and for a very limited and specific sample of farms. This implies that the modelling of risk and uncertainty at individual farm level and in a large scale system is still a challenging task. The aim of this paper is to formulate, estimate and test a robust methodology for explicitly modelling risk to be incorporated in an EU-wide individual farm model for Common Agricultural Policy (CAP) analysis, named IFM-CAP. Results show that there is a clear trade-off between the behavioural model (BM) and the behavioural risk model (BRM). Albeit the results show that both alternatives provide very close estimates, the latter increases three times the computation time required for estimation. Despite this, we are convinced that the modelling of risk is crucial to better understand farmer behaviour and to accurately evaluate the impacts of risk management related policies (i.e. insurance schemes).

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Notes

  1. 1.

    For a review on PMP models, see Henry de Frahan et al. (2007), Mérel and Bucaram (2010), Paris (2011) and Heckelei et al. (2012).

  2. 2.

    The symbol \( \circ \) indicates the Hadamard product.

  3. 3.

    The calibration of the PMP models is implemented with R. The key calibration algorithms have been taken from two R libraries: quadprog and Alabama.

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Acknowledgment

The authors are grateful to the Economic Analysis of EU Agriculture Unit E.3 of the European Commission for granting access to the farm-level FADN data. The authors are solely responsible for the content of the paper. The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Parliament or the European Commission.

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Authors and Affiliations

  1. Department of Economic Analysis, Ivie and ERICES, University of Valencia, Avda. de los Naranjos s/n. Edificio Departamental Orienta, 46022, Valencia, Spain

    Iván Arribas

  2. European Commission, Joint Research Centre (JRC), Institute for Prospective Technological Studies (IPTS), Edificio Expo. C/Inca Garcilaso, 41092, Seville, Spain

    Kamel Louhichi, Ángel Perni & Sergio Gómez-y-Paloma

  3. Department of Economic Analysis and ERICES, University of Valencia, Avda. de los Naranjos s/n. Edificio Departamental Orienta, 46022, Valencia, Spain

    José Vila

Authors
  1. Iván Arribas
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  2. Kamel Louhichi
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  3. Ángel Perni
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  4. José Vila
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  5. Sergio Gómez-y-Paloma
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Corresponding author

Correspondence to Ángel Perni .

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Editors and Affiliations

  1. Department of International Trade, Western Macedonia University of Applied Sciences, Kastoria, Greece

    Nicholas Tsounis

  2. Department of International Trade, Western Macedonia University of Applied Sciences, Kastoria, Greece

    Aspasia Vlachvei

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Arribas, I., Louhichi, K., Perni, Á., Vila, J., Gómez-y-Paloma, S. (2017). Modelling Farmers’ Behaviour Toward Risk in a Large Scale Positive Mathematical Programming (PMP) Model. In: Tsounis, N., Vlachvei, A. (eds) Advances in Applied Economic Research. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-48454-9_42

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