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Sample Calibration of the Online CFM Survey

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  • Marie-Hélène Felt
  • David Laferrière

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.

Suggested Citation

  • Marie-Hélène Felt & David Laferrière, 2020. "Sample Calibration of the Online CFM Survey," Technical Reports 118, Bank of Canada.
    • Handle: RePEc:bca:bocatr:118
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    References listed on IDEAS

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    1. Jean‐François Beaumont & Zdenek Patak, 2012. "On the Generalized Bootstrap for Sample Surveys with Special Attention to Poisson Sampling," International Statistical Review, International Statistical Institute, vol. 80(1), pages 127-148, April.
    2. Heng Chen & Marie-Hélène Felt & Kim P. Huynh, 2017. "Retail payment innovations and cash usage: accounting for attrition by using refreshment samples," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 503-530, February.
    3. Christopher Henry & Kim Huynh & Gradon Nicholls & Mitchell Nicholson, 2019. "2018 Bitcoin Omnibus Survey: Awareness and Usage," Discussion Papers 2019-10, Bank of Canada.
    4. Kyle Vincent, 2015. "2013 Methods-of-Payment Survey: Sample Calibration Analysis," Technical Reports 103, Bank of Canada.
    5. Marie-Hélène Felt, 2018. "A Look Inside the Box: Combining Aggregate and Marginal Distributions to Identify Joint Distributions," Staff Working Papers 18-29, Bank of Canada.
    6. Christopher Henry & Kim Huynh & Angelika Welte, 2018. "2017 Methods-of-Payment Survey Report," Discussion Papers 18-17, Bank of Canada.
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    More about this item

    Keywords

    Econometric and statistical methods;

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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