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Comparing Environmental Impact of Alternative CAP Scenarios Estimated Through an Artificial Neural Network

Author

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  • Andrea BONFIGLIO

    ([n.a.])

Abstract

The paper aims to assess environmental impact produced by alternative Common Agricultural Policy (CAP) scenarios in the Italian Marche region for the period 2000-2002. Scenarios concern alternative hypotheses about direct payments for arable crops related to Agenda 2000. For this aim, a Multilayer Feedforward Neural Network model (MFNN) was applied. Different from traditional models, MFNN is able to analyze complex patterns quickly and with a high degree of accuracy. Moreover, MFNN makes assumptions about neither the underlying population nor the existence of optimising behaviour and uses the data to develop an internal representation of the complexity characterising the system analysed. The results indicate that direct payments produced positive environmental effects compared to the hypothesis of absence of direct payments. Moreover, they show that it would have been even better, from an environmental point of view, if Agenda 2000 had been more radical in comparison to the 1992 Mac Sharry reform, by introducing decoupled direct payments.

Suggested Citation

  • Andrea BONFIGLIO, 2006. "Comparing Environmental Impact of Alternative CAP Scenarios Estimated Through an Artificial Neural Network," Working Papers 269, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
  • Handle: RePEc:anc:wpaper:269
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    File URL: http://docs.dises.univpm.it/web/quaderni/pdf/269.pdf
    File Function: First version, 2006
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    References listed on IDEAS

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    1. Nowrouz Kohzadi & Milton S. Boyd & Iebeling Kaastra & Bahman S. Kermanshahi & David Scuse, 1995. "Neural Networks for Forecasting: An Introduction," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 43(3), pages 463-474, November.
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    Cited by:

    1. Ugo FRATESI, 2010. "The National and International Effects;of Regional Policy Choices: Agglomeration Economies, Peripherality and Territorial Characteristics," Working Papers 344, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    2. Luca RICCETTI, 2010. "Minimum Tracking Error Volatility," Working Papers 340, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    3. Fabio FIORILLO & Agnese SACCHI, 2010. "I Want to Free-ride. An Opportunistic View on Decentralization Versus Centralization Problem," Working Papers 346, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.

    More about this item

    Keywords

    common agricultural policy; direct payments; environmental impact; neural networks;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices

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