Evaluation of Statistical Matching and Selected SAE Methods

Using Micro Census and EU-SILC Data
2015
ISBN: 978-3-658-08223-9
Verlag: Springer

Buch, Englisch, 101 Seiten, Paperback, Format (B × H): 148 mm x 210 mm, Gewicht: 1607 g

Reihe: BestMasters

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.

Zielgruppe

Research

Autoren/Hrsg.

Puchner, Verena

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Demographie, Demoskopie
• Sozialwissenschaften Soziologie | Soziale Arbeit Spezielle Soziologie Soziale Ungleichheit, Armut, Rassismus

Inhaltsverzeichnis

Regression Models Including Selected Small Area Methods.- Statistical Matching.- Application to Poverty Estimation Using EU-SILC and Micro Census Data.- Bootstrap Methods.

Über Autor(innen)

Verena Puchner obtained her master’s degree at Technical University of Vienna under the supervision of Priv.-Doz. Dipl.-Ing. Dr. techn. Matthias Templ. At present, she works as a data miner and consultant.