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Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage

Author

Listed:
  • Christopher S. Henry

    (CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne)

  • Tamás Ilyés

Abstract

For central banks who study the use of cash, acceptance of card payments is an important factor. Surveys to measure levels of card acceptance and the costs of payments can be complicated and expensive. In this paper, we exploit a novel data set from Hungary to see the effect of stratified random sampling on estimates of payment card acceptance and usage. Using the Online Cashier Registry, a database linking the universe of merchant cash registers in Hungary, we create merchant and transaction level data sets. We compare county (geographic), industry and store size stratifications to simulate the usual stratification criteria for merchant surveys and see the effect on estimates of card acceptance for different sample sizes. Further, we estimate logistic regression models of card acceptance/usage to see how stratification biases estimates of key determinants of card acceptance/usage.

Suggested Citation

  • Christopher S. Henry & Tamás Ilyés, 2019. "Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage," Post-Print hal-03182306, HAL.
    • Handle: RePEc:hal:journl:hal-03182306
    DOI: 10.1108/S0731-905320190000039002
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    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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