Statistics Directorate

STES Timeliness Framework: Data Imputation Methods

 

Back to STES Timeliness Framework

This page contains links to detailed documentation on data imputation methods which can assist in improving timeliness or reducing costs in the production of short-term economic statistics. The papers below provide detailed information on methods relevant to this topic which have been implemented within statistical organisations.  Issues covered include:

•   Sophisticated methods (e.g. regression or ARIMA modelling) to impute for non respondents which enable accurate estimates to be produced at lower response rates
•   Imputation for item non response

Primary papers

The papers below focus primarily on the issue of data imputation methods.  They may also contain information on other statistical processes defined in the STES Timeliness Framework .

Improvement in Timeliness for Turnover in Other Services and Production in Construction at Statistics Finland (2005)

Generalised Edit and Imputation System for Economic Surveys at Statistics Canada (2005)

Improving Imputation Methods for the Employment Cost Index at the BLS (2006)

Improving Timeliness & Accuracy for Manufacturing Turnover Growth at Statistics Netherlands (2005)

Improving Timeliness of Industrial Short-Term Statistics using Time Series Analysis at Statistics Netherlands  (2003)

Imputation Methods, Sample Design and Estimation for the BLS Job Openings and Labor Turnover Survey  (2001)

Changes to the Quarterly Wholesale Trade Survey at Statistics New Zealand  (2003)

Secondary papers

The papers below refer to the issue of data imputation methods to some extent.  They also provide more detail on other statistical processes defined in the STES Timeliness Framework .

Automated Editing System for Short-term Business Surveys in Slovenia (2005)

Developments in Data Editing, Imputation, Respondent Follow Up and using VAT Data at Statistics Netherlands  (2003)

Changes to the Quarterly Retail Trade Survey at Statistics New Zealand  (2004)

Changes to the Quarterly Economic Survey of Manufacturing at Statistics New Zealand  (2002)

Using a Two Phased Design in the Canadian Retail Commodity Survey  (2002)

An Integrated System for Data Input Processing at the U.S. Bureau of Census  (2000)

Queries and the submission of new papers

Questions on the content of or how to use this framework should be sent to stat.contact@oecd.org

 

 

 

 

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