Sample Calibration of the Online CFM Survey

Marie-Helene Felt and David Laferrière

No 118, Technical Reports from Bank of Canada

Abstract: 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.

Keywords: Econometric; and; statistical; methods (search for similar items in EconPapers)
JEL-codes: C C8 C81 C83 (search for similar items in EconPapers)
Pages: 62 pages
Date: 2020
New Economics Papers: this item is included in nep-big, nep-cmp and nep-pay
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Persistent link: https://EconPapers.repec.org/RePEc:bca:bocatr:118

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