Weber, Michael.
Avoid Filling Swiss Cheese with Whipped Cream Imputation Techniques and Evaluation Procedures for Cross-Country Time Series / Michael Weber. [electronic resource] : Michael Weber. - Washington, D.C. : International Monetary Fund, 2011. - 1 online resource (27 p.) - IMF Working Papers; Working Paper ; No. 11/151 . - IMF Working Papers; Working Paper ; No. 11/151 .
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.
1455270504 : 18.00 USD
1018-5941
10.5089/9781455270507.001 doi
Algorithms
Cluster Analysis
Econometric Modeling: Other
Estimation
Imputation Quality
Missing Data
Austria
Belgium
Netherlands
South Africa
Avoid Filling Swiss Cheese with Whipped Cream Imputation Techniques and Evaluation Procedures for Cross-Country Time Series / Michael Weber. [electronic resource] : Michael Weber. - Washington, D.C. : International Monetary Fund, 2011. - 1 online resource (27 p.) - IMF Working Papers; Working Paper ; No. 11/151 . - IMF Working Papers; Working Paper ; No. 11/151 .
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.
1455270504 : 18.00 USD
1018-5941
10.5089/9781455270507.001 doi
Algorithms
Cluster Analysis
Econometric Modeling: Other
Estimation
Imputation Quality
Missing Data
Austria
Belgium
Netherlands
South Africa