Disaggregation of Statistical Livestock Data Using the Entropy Approach

António Xavier,Rui Fragoso,Maria De Belém Costa Freitas

doi:10.1155/2014/397675

António Xavier, Rui Fragoso + Show 1 more

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https://doi.org/10.1155/2014/397675

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Abstract

A process of agricultural data disaggregation is developed to address the lack of updated disaggregated data concerning main livestock categories at subregional and county level in the Alentejo Region, southern Portugal. The model developed considers that the number of livestock units is a function of the agricultural and forest occupation, and data concerning the existing agricultural and forest occupation, as well as the conversion of livestock numbers into normal heads, are needed in order to find this relation. The weight of each livestock class is estimated using a dynamic process based on a generalized maximum entropy model and on a crossentropy minimization model, which comprises two stages. The model was applied to the county of Castelo de Vide and their results were validated in cross reference to real data from different sources.

Highlights

Disaggregated statistical information is necessary to have a correct analysis of spatial patterns inside each country, but data on agricultural and forest occupation and production are frequently found only at national and subnational level [1,2,3,4], and oftentimes this problem does not have an appropriate and accurate solution
The first one is due to the almost complete lack of data on the classes of conversion into normal heads (NH) in the General Agricultural Census (GAC) of 1989, which makes the application of the methodology be only done correctly after 1999, despite the fact that its application to the 1990s can be made with partial inclusion of livestock intended for breeding
The methodology used enables us to solve the problem of lack of data regarding the main categories of breeding livestock with satisfactory results

Summary

Introduction

Disaggregated statistical information is necessary to have a correct analysis of spatial patterns inside each country, but data on agricultural and forest occupation and production are frequently found only at national and subnational level [1,2,3,4], and oftentimes this problem does not have an appropriate and accurate solution. In Portugal, southern Europe, apart from the general lack of data on agricultural and forest occupation, there is a need for up-to-date data on livestock numbers [2]. Planning and devising of a clear and sustainable rural development policy call for the availability of disaggregated information [4], at least when it comes to the numbers of livestock intended for breeding, mainly in regions where these variables have a great importance for the farmers’ income

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