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Spatial Downscaling of Agricultural Land-Use Data: An Econometric Approach Using Cross Entropy

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  • Raja Chakir

Abstract

We propose a spatial disaggregation tool to help researchers make the best use of aggregated data in studies of land use. The proposed approach uses parcel-level agricultural data in conjunction with biophysical processes to break down agricultural regional data to the pixel level. It is a two-step procedure. First, we estimate a land-use model using a multinomial logit model. Second, we disaggregate the observed regional data using a generalized cross-entropy approach, taking the first-step predictions as priors. This procedure is applied to the French Picardie region. Results indicate a significant correlation between observed and estimated land-use shares.

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  • 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.
  • Handle: RePEc:uwp:landec:v:85:y:2009:i:2:p:238-251
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    4. Lungarska, Anna & Chakir, Raja, 2018. "Climate-induced Land Use Change in France: Impacts of Agricultural Adaptation and Climate Change Mitigation," Ecological Economics, Elsevier, vol. 147(C), pages 134-154.
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    12. Wade, Tara & Kurkalova, Lyubov A. & Secchi, Silvia, 2012. "Using the logit model with aggregated choice data in estimation of Iowa corn farmers’ conservation tillage subsidies," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124974, Agricultural and Applied Economics Association.
    13. Zack Dorner & Dean Hyslop, 2014. "Modelling Changing Rural Land Use in New Zealand 1997 to 2008 Using a Multinomial Logit Approach," Working Papers 14_12, Motu Economic and Public Policy Research.
    14. Petsakos, Athanasios & Jayet, Pierre-Alain, 2010. "Evaluating the efficiency of a N-input tax under different policy scenarios at different scales," 120th Seminar, September 2-4, 2010, Chania, Crete 109397, European Association of Agricultural Economists.
    15. Britz, Wolfgang & Heckelei, Thomas, 2008. "Recent Developments In Eu Policies – Challenges For Partial Equilibrium Models," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6315, European Association of Agricultural Economists.
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    17. Valentin Bellassen & Jean-Sauveur Ay & Mohamed Hilal, 2020. "The drivers of spatial cropping patterns in Burgundy," Working Papers hal-02894116, HAL.
    18. Cyril Bourgeois & Pierre-Alain Jayet & Florence Habets & Pascal Viennot, 2018. "Estimating the Marginal Social Value of Agriculturally Driven Nitrate Concentrations in an Aquifer: A Combined Theoretical-Applied Approach," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-30, January.
    19. Anna Lungarska & Pierre-Alain Jayet, 2018. "Impact of Spatial Differentiation of Nitrogen Taxes on French Farms’ Compliance Costs," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 69(1), pages 1-21, January.
    20. Britz, Wolfgang, 2008. "EU-wide spatial down-scaling of results of regional economic models to analyze environmental impacts," 107th Seminar, January 30-February 1, 2008, Sevilla, Spain 6677, European Association of Agricultural Economists.
    21. Lungarska, Anna & Jayet, Pierre-Alain, 2014. "Geographical Labeling of Agri-Food Products and its Incidence on the Cross-Sectional Approach to Climate Change Impacts Assessment," 2014 International Congress, August 26-29, 2014, Ljubljana, Slovenia 182746, European Association of Agricultural Economists.
    22. Pierre-Alain Jayet & Delphine Barberis & Pierre Humblot & Anna Lungarska, 2018. "Spatializing the results of a bioeconomic model on water demand for irrigation needs [Spatialisation de la demande en eau d’irrigation estimée par un modèle bioéconomique]," Post-Print hal-02617894, HAL.
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    24. Fezzi, Carlo & Bateman, Ian J., 2009. "Structural Agricultural Land Use Modelling," 2009 Conference, August 16-22, 2009, Beijing, China 51423, International Association of Agricultural Economists.
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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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