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A model for prediction of spatial farm structure

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  • Hoveid, Oyvind
  • Stokstad, Grete

Abstract

Spatial micro structure and its change over time is recorded for Norwegian farm firms. Relative strong correlations between geographically close neighbors are expected, either because growing farms swallow the smaller ones, or because they are affected by some spatially related unobserved factors. Strong correlations over time are also expected because of prevalent family farming. The paper proposes a state-of-the-art Markov chain model in order to predict the spatial and temporal micro structure taking account of both non-stationarity and spatio/temporal correlations by means of techniques from non-linear state space modeling and Gaussian Markov random fields. The model and the complete data set is then a device with which one can investigate the consequences of ignoring spatial and/or temporal correlations, both with complete data and with more sparsely sampled data, like FADN panels or USDA's repeated cross-sections (ARMS).

Suggested Citation

  • Hoveid, Oyvind & Stokstad, Grete, "undated". "A model for prediction of spatial farm structure," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114529, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae11:114529
    DOI: 10.22004/ag.econ.114529
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    References listed on IDEAS

    as
    1. 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.
    2. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
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