IDEAS home Printed from https://ideas.repec.org/p/ags/eaae89/234612.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/234612/files/Kempen%20et%20al%202005%20A%20Statistical%20Approach%20for%20Spatial%20Disaggregation%20of%20Crop%20Production%20in%20the%20EU%20.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.234612?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    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 115982, European Association of Agricultural Economists.
    3. 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.
    4. 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.
    5. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. de Figueiredo, Erik Alencar & Ziegelmann, Flávio Augusto, 2010. "Estimating income mobility using census data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4897-4903.
    2. Wu, Ximing & Perloff, Jeffrey M., 2007. "Information-Theoretic Deconvolution Approximation of Treatment Effect Distribution," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt6bm6n30x, Department of Agricultural & Resource Economics, UC Berkeley.
    3. Xavier, Antonio & Martins, Maria de Belem Costa Freitas & Fragoso, Rui Manuel de Sousa, 2011. "Recovery of Incomplete Data of Statistical Livestock Number Applying an Entropy Approach," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115790, European Association of Agricultural Economists.
    4. António Xavier & Rui Fragoso & Maria Belém Costa Freitas & Maria Socorro Rosário, 2019. "An Approach Using Entropy and Supervised Classifications to Disaggregate Agricultural Data at a Local Level," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(4), pages 763-779, December.
    5. António Xavier & Rui Fragoso & Maria De Belém Costa Freitas & Maria Do Socorro Rosário & Florentino Valente, 2018. "A Minimum Cross-Entropy Approach to Disaggregate Agricultural Data at the Field Level," Land, MDPI, vol. 7(2), pages 1-16, May.
    6. Thanasis Stengos & Ximing Wu, 2010. "Information-Theoretic Distribution Test with Application to Normality," Econometric Reviews, Taylor & Francis Journals, vol. 29(3), pages 307-329.
    7. Holly, Alberto & Monfort, Alain & Rockinger, Michael, 2011. "Fourth order pseudo maximum likelihood methods," Journal of Econometrics, Elsevier, vol. 162(2), pages 278-293, June.
    8. van Akkeren, Marco & Judge, George & Mittelhammer, Ron, 2002. "Generalized moment based estimation and inference," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 127-148, March.
    9. Kim, Jae-Young, 2014. "An alternative quasi likelihood approach, Bayesian analysis and data-based inference for model specification," Journal of Econometrics, Elsevier, vol. 178(P1), pages 132-145.
    10. Rui Fragoso & Maria Leonor da Silva Carvalho, 2013. "Estimation of cost allocation coefficients at the farm level using an entropy approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(9), pages 1893-1906, September.
    11. Aebi, Robert & Neusser, Klaus & Steiner, Peter, 1999. "Evaluating Theories of the Income Dynamics: A Probabilistic Approach," Economics Series 61, Institute for Advanced Studies.
    12. repec:cfe:wpcefa:2016_06 is not listed on IDEAS
    13. Lips, Markus, 2014. "Disproportionate joint cost allocation at individual-farm level using maximum entropy," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182851, European Association of Agricultural Economists.
    14. Tran, Dat Q. & Kurkalova, Lyubov A., 2017. "Testing for complementarity between the use of continuous no-till and cover crops: an application of Entropy approach," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259149, Agricultural and Applied Economics Association.
    15. Cook, Larry & Harslett, Philip, 2015. "An introduction to entropy estimation of parameters in economic models," Conference papers 332651, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    16. Qiuqiong Huang & Richard Howitt & Scott Rozelle, 2012. "Estimating production technology for policy analysis: trading off precision and heterogeneity," Journal of Productivity Analysis, Springer, vol. 38(2), pages 219-233, October.
    17. Raja Chakir, 2009. "Spatial Downscaling of Agricultural Land-Use Data: An Econometric Approach Using Cross Entropy," Land Economics, University of Wisconsin Press, vol. 85(2), pages 238-251.
    18. Heckelei, Thomas & Mittelhammer, Ronald C. & Jansson, Torbjorn, 2008. "A Bayesian Alternative To Generalized Cross Entropy Solutions For Underdetermined Econometric Models," Discussion Papers 56973, University of Bonn, Institute for Food and Resource Economics.
    19. repec:lrk:lrkwkp:fiirs016 is not listed on IDEAS
    20. Steven F. Lehrer & Tian Xie, 2022. "The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success," Management Science, INFORMS, vol. 68(1), pages 189-210, January.
    21. Das, Debojyoti & Bhatia, Vaneet & Kumar, Surya Bhushan & Basu, Sankarshan, 2022. "Do precious metals hedge crude oil volatility jumps?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    22. Marsh, Thomas L. & Mittelhammer, Ronald C., 2001. "Adaptive Truncated Estimaton Applied To Maximum Entropy," 2001 Annual Meeting, July 8-11, 2001, Logan, Utah 36169, Western Agricultural Economics Association.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:eaae89:234612. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/eaaeeea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.