Text

Evaluation of Statistical Matching and Selected SAE Methods Using Micro Census and EU-SILC Data

---

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.

---

Availability

No copy data

Detail Information

Series Title

-

Call Number

-

Publisher

: ., 2015

Collation

6 b/w illustrations

Language

English

ISBN/ISSN

978-3-658-08224-6

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

-

Subject(s)

Probability Theory
Computational Mathematics and Numerical Analysis
Applications of Mathematics

Specific Detail Info

-

Statement of Responsibility

Verena Puchner

Other Information

Cataloger

agus

Source

-

Validator

-

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment