Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage

Christopher Henry and Tamás Ilyés

A chapter in The Econometrics of Complex Survey Data, 2019, vol. 39, pp 35-57 from Emerald Group Publishing Limited

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.

Keywords: Payment methods; card acceptance; stratified random sampling; big data; logistic regression; payment choice; C44; D22; D12; G20; C55; C83 (search for similar items in EconPapers)
Date: 2019
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Working Paper: Effectiveness of Stratified Random Sampling for Payment Card Acceptance and Usage (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:eme:aecozz:s0731-905320190000039002

DOI: 10.1108/S0731-905320190000039002

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