The impact of policy effects on the Hungarian payments card market

Abstract

As a major electronic alternative to cash, central banks and state administrations often support the development of card payments with regulatory and public policy steps. Hungary was extremely active in this field by executing POS-terminal installation programmes or setting limits to interchange fees a year before the European regulation. Within this study we investigate, how these measures contributed to the recent evolution of Hungary's payment card market. Using the comprehensive dataset of the Central Bank of Hungary, we provide empirical evidence using time-series analysis methods, that both policy steps had a significant positive effect on the domestic card payments scene.

The Strength of the Indonesian Card Market's Reaction to the National Payment Gateway's Implementation

“…This is a quantitative study with empirical evidence that uses the ARIMA/SARIMA model, followed by the addition of exogenous variables (explanatory variables) to accommodate the ceteris paribus effect on the model (so that the model becomes ARIMAX/SARIMAX), as found in previous studies (Górka, 2018;Kajdi & Kiss, 2021).…”

“…Furthermore, we denote a value of "0" for the COVID variable until the announcement of the first COVID-19 case in Indonesia, which is March 2020, and a value of "1" in the future. The selection of these variables is a modification of the research (Górka, 2018;Kajdi & Kiss, 2021), by equating the selection of exogenous RSI variables with household consumption, and the implementation period of GPN (NSICCS and GPN dummy variables) with interchange change fees, as well as adding the COVID variable to account for the COVID-19 pandemic in Indonesia.…”

“…To answer the previously described research questions, we discovered relevant previous research, specifically research (Górka, 2018;Kajdi & Kiss, 2021) that used the ARIMA-X/SARIMA-X time series analysis method, specifically the ARIMA/SARIMA model added with explanatory variables to accommodate the ceteris paribus effect in the economy.…”

“…The ARIMA-X/SARIMA-X time series forecasting model was developed for two-sided payment card market variables: on the supply side, the number of merchants accepting card transactions (Górka, 2018;Kajdi & Kiss, 2021), the number of EDC/POS machines (Górka, 2018), and the transaction value of card payments (Górka, 2018;Kajdi & Kiss, 2021) and the transaction value of card payments (Górka, 2018). Tariffs/transaction costs (Górka, 2018;Kajdi & Kiss, 2021) and household consumption are the exogenous variables used (Kajdi & Kiss, 2021).…”

“…The forecasting model developed by the two studies is identical, with past performance of the number of merchants receiving card transactions, the number of cards, and the number of card transactions having a significant effect on current and future performance (Górka, 2018;Kajdi & Kiss, 2021). The exogenous variable of household consumption has a significant impact on the number of cards (Kajdi & Kiss, 2021), and the tariff/transaction fee has a significant impact on the number of cards (Górka, 2018;Kajdi & Kiss, 2021) and the value of card transactions (Górka, 2018), but not on the number of merchants who accept card transactions and the number of EDC/POS machines (Kajdi & Kiss, 2021).…”