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A Statistical Approach for Spatial Disaggregation of Crop Production in the EU

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  • Kempen, Markus
  • Heckelei, Thomas
  • Britz, Wolfgang
  • Adrian, Leip
  • Koeble, Renate

Abstract

In this paper we describe a procedure for disaggregating agricultural land use choices at NUTS 2 level to about 18.000 homogeneous spatial units completely covering the usable agricultural area of the EU. The disaggregation procedure uses 40.000 sampling points and aggregate data from administrative regions and requires two steps: First, we employ crop specific, spatial binary choice models to regress land use decisions on local natural conditions (soil, relief, climate) based on the sample information. Results allow predicting crop shares in each spatial unit. Second, consistency with data from administrative regions is achieved by maximising the posterior density of crop shares subject to aggregating equations using the forecast distributions as prior information. Comparison with actual crop shares shows the validity of the procedure.

Suggested Citation

  • Kempen, Markus & Heckelei, Thomas & Britz, Wolfgang & Adrian, Leip & Koeble, Renate, 2005. "A Statistical Approach for Spatial Disaggregation of Crop Production in the EU," 89th Seminar, February 2-5, 2005, Parma, Italy 234612, European Association of Agricultural Economists.
    • Handle: RePEc:ags:eaae89:234612
    DOI: 10.22004/ag.econ.234612
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    References listed on IDEAS

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    1. Richard Howitt & Arnaud Reynaud, 2003. "Spatial disaggregation of agricultural production data using maximum entropy," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 30(3), pages 359-387, September.
    2. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    3. Gerald Nelson & Alessandro De Pinto & Virginia Harris & Steven Stone, 2004. "Land Use and Road Improvements: A Spatial Perspective," International Regional Science Review, , vol. 27(3), pages 297-325, July.
    4. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
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    Cited by:

    1. Gocht, Alexander & Roder, Norbert, 2011. "Salvage the treasure of geographic information in Farm census data," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115982, European Association of Agricultural Economists.
    2. Gocht, Alexander & Roder, Norbert, 2011. "Salvage the treasure of geographic information in Farm census data," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114824, European Association of Agricultural Economists.
    3. Gocht, Alexander & Roeder, Norbert, 2010. "Recovering Localized Information On Agricultural Structure Underlying Data Confidentiality Regulations - Potentials Of Different Data Aggregation And Segregation Techniques," 50th Annual Conference, Braunschweig, Germany, September 29-October 1, 2010 93975, German Association of Agricultural Economists (GEWISOLA).
    4. Alexander Gocht & Pavel Ciaian & Maria Bielza & Jean-Michel Terres & Norbert Röder & Mihaly Himics & Guna Salputra, 2017. "EU-wide Economic and Environmental Impacts of CAP Greening with High Spatial and Farm-type Detail," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 651-681, September.
    5. Elbersen, Berien S. & Kempen, Markus & van Diepen, C.A. & Andersen, Erling & Hazeu, Gerard W. & Verhoog, A. David, 2006. "Protocols for spatial allocation of farm types," Reports 9285, Wageningen University, SEAMLESS: System for Environmental and Agricultural Modelling; Linking European Science and Society.

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