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European Review of Agriculture Economics Vol 30 (3) (2003) pp.359-387
© 2003 Oxford University Press and the Foundation for the European Review of Agricultural Economics

Spatial disaggregation of agricultural production data using maximum entropy

Richard Howitt and Arnaud Reynaud

University of California at Davis, Davis, CA, USA
Université de Toulouse, Toulouse, France

Summary

We develop a dynamic data-consistent method to estimate agricultural land use choices at a disaggregate (district) level, using more aggregate (regional-level) data. The disaggregation procedure consists of two steps. First, we estimate a dynamic model of land use at the regional level, then we disaggregate outcomes of the aggregate model using maximum entropy (ME). The ME disaggregation procedure is applied to a sample of California data including six districts and eight crops. The disaggregation procedure results in the recovery of district-level cropping areas with an average prediction error of 16.2 per cent.

Keywords: disaggregation, Bayesian method, maximum entropy, land use, Markov process


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