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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/1137 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/1137 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/1137 archive 351 disk0/00/00/11/24 2016-01-15 01:46:21 2021-08-27 17:09:24 2016-01-15 01:46:21 monograph show 2 Forslund P. Schoettner J. AL0350 pub iis_mig iis_pop prog_hss The collection of disaggregated data is in most economic areas an expensive as well as a time-consuming procedure. If real data could be replaced by estimations from data on a highly aggregated level, much effort could be saved. The entropy maximizing method can be used to estimate interregional migration flow matrices for the whole population or subgroups of the population, when the available data are in an aggregated form. This means estimating the elements of matrices in which individuals a reclassified according to two or more discrete variables. Matrices of this form are called contingency tables. In this paper we present the entropy-maximizing method and test its validity for different levels of data aggregation. The tests are carried out by means of information theory and the chi-square distribution. For the tests we have used data from two of the countries that produce disaggregated data, Sweden and Austria. 1979-07 published WP-79-059 WP-79-059 2365 public working_paper IIASA, Laxenburg, Austria 37 FALSE info:eu-repo/semantics/book