Hackl, Peter, Denk, Michaela. 2004. Data Integration: Techniques and Evaluation. Austrian Journal of Statistics. 33 135-152.

RIS

@ARTICLE{Hackl2004,
title = {Data Integration: Techniques and Evaluation},
author = {Peter Hackl and Michaela Denk},
year = {2004},
doi = {https://doi.org/10.17713/ajs.v33i1&2.435},
url = {https://www.ajs.or.at/index.php/ajs/article/view/vol33%2C%20no1%262%20-%208},
volume = {33},
language = {EN},
pages = {135-152},
journal = {Austrian Journal of Statistics},
abstract = {Within the DIECOFIS framework, ec3, the Division of Business Statistics from the Vienna University of Economics and Business Administration and ISTAT worked together to find methods to create a comprehensive database of enterprise data required for taxation microsimulations via integration of existing disparate enterprise data sources. This paper provides an overview of the broad spectrum of investigated methodology (including exact and statistical matching as well as imputation) and related statistical quality indicators, and emphasises the relevance of data integration, especially for official statistics, as a means of using available information more efficiently and improving the quality of a statistical agency’s products. Finally, an outlook on an empirical study comparing different exact matching procedures in the maintenance of Statistics Austria’s Business Register is presented.},
}