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Trends in the French commercial farm population

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Author Info

  • Madior Fall

    (Paris School of Economics, INRA-LEA, Paris, France)

  • Laurent Piet

    ()
    (UMR SMART INRA-Agrocampus Ouest, 4 allée Adolphe Bobierre, CS 61103, 35011 Rennes cedex, France)

  • Muriel Roger

    (Paris School of Economics, INRA-LEA, Paris, France)

Abstract

Knowledge and projection of farm numbers and the structure of their population is an important issue for agricultural economists and policy makers. Although Markov chain models have enjoyed decades of popularity in forecasting total farm numbers, they generally fail to provide a detailed insight of the farm population’s structure; to overcome this caveat we estimate a parametric distribution of the utilized agricultural area of French commercial farms. Our method provides detailed information on the structure of the population and accounts for the specificity of off-land farming. We also model the influence of variables such as the farm’s legal status, type of farming and farm holder’s age. The estimation leads to a relevant description of the entire population of professional farm. When compared with the 2005 Farm Structure Survey data, our simulations based on FADN data display a close match across a number of key variables.

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File URL: http://www.raestud.eu/pdf/REAE-91-3-Fall-Piet-Roger.pdf
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Bibliographic Info

Article provided by INRA Department of Economics in its journal Review of Agricultural and Environmental Studies.

Volume (Year): 91 (2010)
Issue (Month): 3 ()
Pages: 279-295

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Handle: RePEc:rae:jourae:v:91:y:2010:i:3:p:279-295

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Postal: 4, Allée Adolphe Bobierre, CS 61103, 35011 Rennes Cedex
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Web page: http://www.necplus.eu/action/displayJournal?jid=RAE
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Keywords: farm structures; farm size distribution; maximum likelihood and simulation;

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  1. Karantininis, Kostas, 2002. "Information-based estimators for the non-stationary transition probability matrix: an application to the Danish pork industry," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 275-290, March.
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