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The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Nonresponse

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  • Stan Hatko

Abstract

Nonresponse is a considerable challenge in the Retailer Survey on the Cost of Payment Methods conducted by the Bank of Canada in 2015. There are two types of nonresponse in this survey: unit nonresponse, in which a business does not reply to the entire survey, and item nonresponse, in which a business does not respond to particular questions within the survey. Both types may create a bias when computing statistics such as means and weighted totals for different variables. This technical report analyzes solutions to fix the problem of nonresponse in the survey data. Unit nonresponse is addressed through response probability adjustment, in which response probabilities are modelled using logistic regression (a clustering approach for the unit response probabilities is also considered) and are used in the construction of a set of survey weights. Item nonresponse is addressed through imputation, in which the gradient boosting machine (GBM) and extreme gradient boosting (XGBoost) algorithms are used to predict missing values for variables of interest.

Suggested Citation

  • Stan Hatko, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Nonresponse," Technical Reports 107, Bank of Canada.
    • Handle: RePEc:bca:bocatr:107
    DOI: 10.34989/tr-107
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    References listed on IDEAS

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    1. repec:mpr:mprres:4937 is not listed on IDEAS
    2. Angelika Welte, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Sampling," Technical Reports 108, Bank of Canada.
    3. Friedman, Jerome H., 2002. "Stochastic gradient boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 367-378, February.
    4. Carlos Arango & Varya Taylor, 2008. "Merchant Acceptance, Costs, and Perceptions of Retail Payments: A Canadian Survey," Discussion Papers 08-12, Bank of Canada.
    5. Jens Keilwagen & Ivo Grosse & Jan Grau, 2014. "Area under Precision-Recall Curves for Weighted and Unweighted Data," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-13, March.
    6. Valéry Dongmo Jiongo, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Estimation of the Total Private Cost for Large Businesses," Technical Reports 110, Bank of Canada.
    7. Heng Chen & Rallye Shen, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Calibration for Single-Location Retailers," Technical Reports 109, Bank of Canada.
    8. repec:mpr:mprres:4780 is not listed on IDEAS
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    Cited by:

    1. Fung, Ben & Huynh, Kim P. & Nield, Kerry & Welte, Angelika, 2018. "Merchant acceptance of cash and credit cards at the point of sale," Journal of Payments Strategy & Systems, Henry Stewart Publications, vol. 12(2), pages 150-165, July.
    2. Heng Chen & Rallye Shen, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Calibration for Single-Location Retailers," Technical Reports 109, Bank of Canada.

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    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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