1 / 8

Re-Editing of Data in Canadian Business Surveys

Re-Editing of Data in Canadian Business Surveys. UN/ECE Work Session on Statistical Data Editing Bonn, 25-27 September, 2006. Eric Rancourt. Outline. Background Examples Consistency vs Accuracy Current efforts and possible avenues Conclusion. Background. Surveys

dempster
Download Presentation

Re-Editing of Data in Canadian Business Surveys

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Re-Editing of Data in Canadian Business Surveys UN/ECE Work Session on Statistical Data Editing Bonn, 25-27 September, 2006 Eric Rancourt

  2. Outline • Background • Examples • Consistency vs Accuracy • Current efforts and possible avenues • Conclusion

  3. Background Surveys Concept → collection → nonresponse → editing Administrative data Concept → collection → nonresponse → editing Joint use: Further editing of the combined file

  4. Examples Annual survey: Tax replacement for 50% of sampled units Monthlies: Tax replacement (ratio adjustment) for 50% of sampled units Some degree of re-editing in each case to increase consistency.

  5. Consistency vs Accuracy • Consistency of sources or • Accuracy of each source individually → Are they mutually exclusive? → How to balance the two?

  6. Current efforts • Chart of accounts (COA) to better link tax and survey concepts/data. • Data integration project (DIP) to optimize the sample design (including estimation) • Improved quality measures

  7. Other potential avenues Problem similar to • Increasing noise to protect confidentiality • Using subsequent panels to (re)impute past data in longitudinal surveys

  8. Conclusion • Important to refocus on principles of editing (understand process; know quality; not to correct data) • Need for guidelines on balancing consistency and accuracy

More Related