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A Gras Variant Solving For Minimum Information Loss


  • Andre Lemelin


The fundamental idea in Junius and Oosterhaven (2003) is to break down the information contained in the a priori data into two parts: algebraic signs, and absolute values. This approach is well grounded in information theory, and provides a basis on which to solve the problem of adjusting matrices with negative entries. However, Junius and Oosterhaven (2003) have formulated a target function that is not equivalent to the Kullback and Leibler (1951) cross-entropy measure, and so is not a representation of the minimum information loss principle. Neither is the alternative target function proposed by Lenzen et al. (2007). This paper develops the exact Kullback and Leibler cross-entropy measure. In addition, following the constrained optimization approach, this paper applies the same principle to solve adjustment problems where row-sums, column-sums or both are constrained to zero.

Suggested Citation

  • Andre Lemelin, 2009. "A Gras Variant Solving For Minimum Information Loss," Economic Systems Research, Taylor & Francis Journals, vol. 21(4), pages 399-408.
  • Handle: RePEc:taf:ecsysr:v:21:y:2009:i:4:p:399-408 DOI: 10.1080/09535311003589310

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    References listed on IDEAS

    1. Rutherford, Thomas F, 1999. "Applied General Equilibrium Modeling with MPSGE as a GAMS Subsystem: An Overview of the Modeling Framework and Syntax," Computational Economics, Springer;Society for Computational Economics, vol. 14(1-2), pages 1-46, October.
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