Cover IMF Working Papers
Avoid Filling Swiss Cheese with Whipped Cream: Imputation Techniques and Evaluation Procedures for Cross-Country Time Series
Author:
Mr. Michael Webernull

Search for other papers by Mr. Michael Weber in
Current site
Google Scholar
PubMedClose
and
Ms. Michaela Denk
Search for other papers by Ms. Michaela Denk in
Current site
Google Scholar
PubMedClose
Series:
IMF Working Papers
Volume/Issue:
Volume 2011: Issue 151
Language:
English
Publication Date:
01 Jun 2011
DOI:
https://doi.org/10.5089/9781455270507.001
ISBN:
9781455270507
ISSN:
1018-5941
Pages:
27
Keywords:
WP; time series data; data pattern; imputed dataset; cross-sectional time series; data augmentation; data technique; expected value; information criteria; quality report; time series model
Legal-disclaimer:
IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.
Download PDF (736.5 KB) Download Epub
International organizations collect data from national authorities to create multivariate cross-sectional time series for their analyses. As data from countries with not yet well-established statistical systems may be incomplete, the bridging of data gaps is a crucial challenge. This paper investigates data structures and missing data patterns in the cross-sectional time series framework, reviews missing value imputation techniques used for micro data in official statistics, and discusses their applicability to cross-sectional time series. It presents statistical methods and quality indicators that enable the (comparative) evaluation of imputation processes and completed datasets.
  • Collapse
  • Expand
Cover IMF Working Papers
IMF Working Papers
ISSN:
1018-5941
Publisher:
International Monetary Fund
Volume 2011: Issue 151