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The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Calibration for Single-Location Retailers

Author

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  • Heng Chen
  • Rallye Shen

Abstract

Calibrated weights are created to (a) reduce the nonresponse bias; (b) reduce the coverage error; and (c) make the weighted estimates from the sample consistent with the target population in terms of certain key variables. This technical report details our calibration analysis of singlelocation retailers for the Retailer Survey on the Cost of Payment Methods. We first compare two types of calibration approaches, consisting of (1) traditional calibration, in which calibration is implemented after explicit nonresponse modelling, and (2) nonresponse-embedded calibration, where the nonresponse correction is automatically built in (Särndal and Lundström, 2005). After carefully selecting auxiliary variables, we find minor differences between these two methods. We also examine the effects of trimming, sample size, smoothing and influential units on the calibrated weights, and show that our calibration is robust in view of these considerations.

Suggested Citation

  • 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.
    • Handle: RePEc:bca:bocatr:109
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    References listed on IDEAS

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    1. Wu C. & Sitter R. R, 2001. "A Model-Calibration Approach to Using Complete Auxiliary Information From Survey Data," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 185-193, March.
    2. Daniele Pacifico, 2011. "SREWEIGHT: Stata module for survey reweighting," Statistical Software Components S457312, Boston College Department of Economics, revised 23 Jan 2014.
    3. Stan Hatko, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Nonresponse," Technical Reports 107, Bank of Canada.
    4. 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.
    5. Anneke Kosse & Heng Chen & Marie-Hélène Felt & Valéry Dongmo Jiongo & Kerry Nield & Angelika Welte, 2017. "The Costs of Point-of-Sale Payments in Canada," Discussion Papers 17-4, Bank of Canada.
    6. Jean-François Beaumont, 2008. "A new approach to weighting and inference in sample surveys," Biometrika, Biometrika Trust, vol. 95(3), pages 539-553.
    7. Angelika Welte, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Sampling," Technical Reports 108, Bank of Canada.
    8. Stanislav Kolenikov, 2014. "Calibrating survey data using iterative proportional fitting (raking)," Stata Journal, StataCorp LP, vol. 14(1), pages 22-59, March.
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    Citations

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    Cited by:

    1. Kim Huynh & Gradon Nicholls & Mitchell Nicholson, 2019. "2018 Merchant Acceptance Survey," Staff Analytical Notes 2019-31, Bank of Canada.
    2. Stan Hatko, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Nonresponse," Technical Reports 107, Bank of Canada.
    3. 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.
    4. 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.
    5. Angelika Welte, 2017. "The Bank of Canada 2015 Retailer Survey on the Cost of Payment Methods: Sampling," Technical Reports 108, Bank of Canada.
    6. Angelika Welte & Jozsef Molnar, 2021. "The market for acquiring card payments from small and medium-sized Canadian merchants," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(2), pages 87-97, April.
    7. Angelika Welte & Joy Wu, 2023. "The 2021–22 Merchant Acceptance Survey Pilot Study," Discussion Papers 2023-1, Bank of Canada.

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    More about this item

    Keywords

    E-Money; Econometric and statistical methods;

    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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