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Acceptance of Payment Cards by Retailers in Hungary Based on Data of Online Cash Registers

Author

Listed:
  • Tamás Ilyés

    (Magyar Nemzeti Bank)

  • Lóránt Varga

    (Magyar Nemzeti Bank)

Abstract

In our study we examined payment card acceptance in the Hungarian retail sector based on a receipt-level, detailed dataset derived from online cash registers. The main objective of our research was to identify the primary explanatory variables and to test conventional card acceptance hypotheses. For the purposes of our analysis, we relied on anonymised online cash register data provided by the National Tax and Customs Administration (NTCA) for the year 2016. Covering an extremely broad section of the Hungarian retail sector, with nearly 3.8 billion data points the database provides a basis for complex and robust analyses. We tested storelevel monthly aggregate data with county and network attributes. Based on the robust results of the research, we found that store size can be considered the most important explanatory variable behind card acceptance decisions; however, the correlation is not linear. The marginal effect of size is negligible among small and large-sized stores, but there is a strong positive correlation among mid-sized stores. We also analysed the effect of the store’s customer base and other attributes, and although numerous effects proved to be statistically significant, they wielded negligible influence in card acceptance decisions. On the other hand, being open on Sundays – a subjective variable that was used as a proxy for store ownership – had a significant negative effect on card acceptance decisions.

Suggested Citation

  • Tamás Ilyés & Lóránt Varga, 2018. "Acceptance of Payment Cards by Retailers in Hungary Based on Data of Online Cash Registers," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 17(1), pages 83-109.
    • Handle: RePEc:mnb:finrev:v:17:y:2018:i:1:p:83-109
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    References listed on IDEAS

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    Cited by:

    1. László Kajdi & István Nemecskó, 2020. "Regional Features of Card Payments in Hungary," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 19(1), pages 65-89.
    2. Vivien Deak & Laszlo Kajdi & Istvan Nemecsko, 2021. "Analysis of Retailer and Corporate Payment Habits in Hungary," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 20(2), pages 33-59.
    3. Polasik, Michał & Huterska, Agnieszka & Iftikhar, Rehan & Mikula, Štěpán, 2020. "The impact of Payment Services Directive 2 on the PayTech sector development in Europe," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 385-401.

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    More about this item

    Keywords

    payment transactions; card acceptance; payment methods; decision models; logistic regression;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis

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