Evaluation of Statistical Matching and Selected SAE Methods - Using Micro Census and EU-SILC Data (Paperback, 2015 ed.)

Verena Puchner evaluates and compares statistical matching and selected SAE methods. Due to the fact that poverty estimation at regional level based on EU-SILC samples is not of adequate accuracy, the quality of the estimations should be improved by additionally incorporating micro census data. The aim is to find the best method for the estimation of poverty in terms of small bias and small variance with the aid of a simulated artificial "close-to-reality" population. Variables of interest are imputed into the micro census data sets with the help of the EU-SILC samples through regression models including selected unit-level small area methods and statistical matching methods. Poverty indicators are then estimated. The author evaluates and compares the bias and variance for the direct estimator and the various methods. The variance is desired to be reduced by the larger sample size of the micro census.

General

Imprint:	Springer Spektrum
Country of origin:	Germany
Series:	BestMasters
Release date:	December 2014
First published:	2015
Authors:	Verena Puchner
Dimensions:	210 x 148 x 7mm (L x W x T)
Format:	Paperback
Pages:	101
Edition:	2015 ed.
ISBN-13:	978-3-658-08223-9
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	3-658-08223-2
Barcode:	9783658082239

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