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- W2000232464 abstract "The aim of this paper is to formulate an analytical–informational–theoretical approach which, given the incomplete nature of the available micro-level data, can be used to provide disaggregated values of a given variable. A functional relationship between the variable to be disaggregated and the available variables/indicators at the area level is specified through a combination of different macro- and micro-data sources. Data disaggregation is accomplished by considering two different cases. In the first case, sub-area level information on the variable of interest is available, and a generalized maximum entropy approach is employed to estimate the optimal disaggregate model. In the second case, we assume that the sub-area level information is partial and/or incomplete, and we estimate the model on a smaller scale by developing a generalized cross-entropy-based formulation. The proposed spatial-disaggregation approach is used in relation to an Italian data set in order to compute the value-added per manufa..." @default.
- W2000232464 created "2016-06-24" @default.
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- W2000232464 date "2010-10-21" @default.
- W2000232464 modified "2023-09-27" @default.
- W2000232464 title "Data disaggregation procedures within a maximum entropy framework" @default.
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- W2000232464 doi "https://doi.org/10.1080/02664760903199489" @default.
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