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2013 Methods-of-Payment Survey: Sample Calibration Analysis

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  • Kyle Vincent

Abstract

Sample calibration is a procedure that utilizes sample and national-level demographic distribution information to weight survey participants. The objective of calibration is to weight the sample so that it is demographically representative of the target population. This technical report details our calibration analysis for the 2013 Methods-of-Payment survey questionnaire sample. The analysis makes use of a variety of variables, with corresponding distributions from the 2011 National Household Survey and 2012 Canadian Internet Use Survey. Our primary objective is to seek a sensible set of variables for calibration and to propose a set of final weights that meet a validation criterion. A raking ratio calibration procedure is used in the analysis. We base calibration on candidate variables and nesting of pairs of variables chosen within the context of the study. An imputation strategy is implemented to account for the relatively few missing observations. Three samples are obtained for the survey and we summarize an analysis that suggests that calibration should be based on the full/collapsed data set. We describe our research on several validation criteria and, after testing the calibration procedure, report our proposed set of final weights.

Suggested Citation

  • Kyle Vincent, 2015. "2013 Methods-of-Payment Survey: Sample Calibration Analysis," Technical Reports 103, Bank of Canada.
    • Handle: RePEc:bca:bocatr:103
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    File URL: https://www.bankofcanada.ca/wp-content/uploads/2015/04/tr103.pdf
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    References listed on IDEAS

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    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Marco Angrisani & Kevin Foster & Marcin Hitczenko, 2013. "The 2010 Survey of Consumer Payment Choice: Technical Appendix," Consumer Payments Research Data Reports 2013-03, Federal Reserve Bank of Atlanta.
    3. Christopher Henry & Kim Huynh & Rallye Shen, 2015. "2013 Methods-of-Payment Survey Results," Discussion Papers 15-4, Bank of Canada.
    4. Heng Chen & Q. Rallye Shen, 2019. "Variance Estimation for Survey-Weighted Data Using Bootstrap Resampling Methods: 2013 Methods-of-Payment Survey Questionnaire," Advances in Econometrics, in: The Econometrics of Complex Survey Data, volume 39, pages 87-106, Emerald Group Publishing Limited.
    5. D'Arrigo, Julia & Skinner, Chris J., 2010. "Linearization variance estimation for generalized raking estimators in the presence of nonresponse," LSE Research Online Documents on Economics 39120, London School of Economics and Political Science, LSE Library.
    6. Kevin Foster & Scott Schuh & Hanbing Zhang, 2013. "The 2010 Survey of Consumer Payment Choice," Research Data Report 13-2, Federal Reserve Bank of Boston.
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    Cited by:

    1. Marie-Hélène Felt & David Laferrière, 2020. "Sample Calibration of the Online CFM Survey," Technical Reports 118, Bank of Canada.
    2. Christopher Henry & Kim Huynh & Angelika Welte, 2018. "2017 Methods-of-Payment Survey Report," Discussion Papers 18-17, Bank of Canada.
    3. Heng Chen & Marie-Hélène Felt & Christopher Henry, 2018. "2017 Methods-of-Payment Survey: Sample Calibration and Variance Estimation," Technical Reports 114, Bank of Canada.

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    More about this item

    Keywords

    Central bank research;

    JEL classification:

    • 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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