文章基本信息

标题：UPDATING AND ESTIMATING A SOCIAL ACCOUNTING MATRIX USING CROSS ENTROPY METHODS
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作者：Robinson, Sherman ; Cattaneo, Andrea ; El-Said, Moataz 等
期刊名称：Journal of Food Distribution Research
印刷版ISSN：0047-245X
出版年度：2000
期号：SUPPL
出版社：Food Distribution Research Society
摘要：The problem in estimating a social accounting matrix (SAM) for a recent year is to find an efficient and cost-effective way to incorporate and reconcile information from a variety of sources, including data from prior years. Based on information theory, the paper presents a flexible “cross entropy” (CE) approach to estimating a consistent SAM starting from inconsistent data estimated with error, a common experience in many countries. The method represents an efficient information processing rule—using only and all information available. It allows incorporating errors in variables, inequality constraints, and prior knowledge about any part of the SAM. An example is presented applying the CE approach to data from Mozambique, using a Monte Carlo approach to compare the CE approach to the standard RAS method and to evaluate the gains in precision from utilizing additional information.
关键词：Entropy; cross entropy; social accounting matrices; SAM; input- output; RAS;Monte Carlo simulations