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Sample calibration of the online CFM survey / by Marie-Hélène Felt and David Laferrière.FB3-1/118-2020E-PDF

"The Bank of Canada’s Currency Department has used the Canadian Financial Monitor (CFM) survey since 2009 to track Canadians’ cash usage, payment card ownership and usage, and the adoption of payment innovations. A new online CFM survey was launched in 2018. Because it uses non-probability sampling for data collection, selection bias is very likely. We outline various methods for obtaining survey weights and discuss the associated conditions necessary for these weights to eliminate selection bias. In the end, we obtain calibration weights for the 2018 and 2019 online CFM samples. Our final weights improve upon the default weights provided by the survey company in several ways: (i) we choose the calibration variables based on a fully documented selection procedure that employs machine learning techniques; (ii) we use very up-to-date calibration totals; (iii) for each survey year we obtain two sets of weights, one for the full yearly sample of CFM respondents, the other for the sub-sample of CFM respondents who also filled in the methods-of-payment module of the survey"--Abstract.

Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.890568&sl=0

Publication information
Department/Agency
  • Bank of Canada, issuing body.
TitleSample calibration of the online CFM survey / by Marie-Hélène Felt and David Laferrière.
Series title
  • Technical report = Rapport technique, 1919-689X ; no. 118
Publication typeMonograph - View Master Record
Language[English]
FormatDigital text
Electronic document
Note(s)
  • "Last updated: August 11, 2020."
  • Includes bibliographical references (pages 24-26).
  • Includes abstract in French.
Publishing information
  • Ottawa, Ontario, Canada : Bank of Canada = Banque du Canada, 2020.
  • ©2020
Author / Contributor
  • Felt, Marie-Hélène, author.
Description1 online resource (ii, 59 pages) : graphs (some colour).
Catalogue number
  • FB3-1/118-2020E-PDF
Subject terms
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