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The evolution of farm size distribution: revisiting the Markov chain model

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  • Piet, Laurent

Abstract

In this paper, a continuous version of the Markov Chain Model (MCM) is proposed to project the number and the population structure of farms. It is then applied to the population of professional French farms. Rather than working directly with transition probabilities as in the traditional, discontinuous, MCM, this approach relies on the close but not identical concept of growth rate probabilities and exploits the Gibrat’s law of proportionate effects which appears to be supported by the French data. It is shown that the proposed continuous MCM is a more general approach, since it enables to derive more in-depth detail on the distribution of the projected population and the traditional MCM transition probability matrix can be easily reconstructed from the estimated growth rate probabilities. Though the continuous MCM is presented in this paper in a stationary framework, it should be possible to develop a non-stationary version in a similar way traditional MCMs are now made non-stationary.

Suggested Citation

  • Piet, Laurent, 2008. "The evolution of farm size distribution: revisiting the Markov chain model," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44269, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae08:44269
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    File URL: http://purl.umn.edu/44269
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    References listed on IDEAS

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    Cited by:

    1. Mikkel Bojesen & Hans Skov-Petersen & Morten Gylling, 2013. "Forecasting the potential of Danish biogas production: spatial representation of Markov chains," IFRO Working Paper 2013/16, University of Copenhagen, Department of Food and Resource Economics.
    2. Landi, Chiara & Stefani, Gianluca & Rocchi, Benedetto & Lombardi, Ginevra V. & Giampaolo, Sabina, 2013. "Determinants of Structural Change in the agricultural sector: An Empirical Analysis of Farm Exit in Tuscany," 2013 Second Congress, June 6-7, 2013, Parma, Italy 149893, Italian Association of Agricultural and Applied Economics (AIEAA).
    3. Zimmermann, Andrea & Heckelei, Thomas, 2012. "Differences of farm structural change across European regions," Discussion Papers 162879, University of Bonn, Institute for Food and Resource Economics.
    4. Alexander Gocht & Norbert Röder & Sebastian Neuenfeldt & Hugo Storm & Thomas Heckelei, 2012. "Modelling farm structural change: A feasibility study for ex-post modelling utilizing FADN and FSS data in Germany and developing an ex-ante forecast module for the CAPRI farm type layer baseline," JRC Working Papers JRC75524, Joint Research Centre (Seville site).

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    Keywords

    Farm size distribution; Gibrat’s law; Markov Chain Model; Farm Management;

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