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A Latent Budget Analysis Approach to Classification: Examples from Economics

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  • Larrosa, Juan MC

Abstract

Latent budget analysis is a classification technique that allows clustering identification by using compositional data. This paper presents examples of how this technique deals with the unit-sum constraint by establishing an initial independence model to which subsequent models are compared in terms of their relative fitness degree. In fact, latent budget analysis does not impose linearity, homogeneity, or even specific distributions on data. Results help to understand some important relationships between capital stock composition and income or food diet composition in a heterogeneous sample of countries.

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File URL: http://mpra.ub.uni-muenchen.de/12569/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 12569.

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Date of creation: 15 Sep 2005
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Handle: RePEc:pra:mprapa:12569

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Keywords: Latent budget analysis; compositional data; food composition; capital composition;

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  1. Michael Greenacre, 2008. "Correspondence analysis of raw data," Economics Working Papers 1112, Department of Economics and Business, Universitat Pompeu Fabra, revised Jul 2009.
  2. Mooijaart, Ab & van der Heijden, Peter G. M. & van der Ark, L. Andries, 1999. "A least squares algorithm for a mixture model for compositional data," Computational Statistics & Data Analysis, Elsevier, vol. 30(4), pages 359-379, June.
  3. Juan Manuel Larrosa, 2003. "A Compositional Statistical Analysis of Capital per Worker," Macroeconomics 0301006, EconWPA.
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