Number of Automated Teller Machines in Selected European Countries: Exploration of Trends and Development Indicators Impacts

  • Anita Pavković
  • Ksenija Dumičić
  • Berislav Žmuk
Conference paper
Part of the Springer Proceedings in Business and Economics book series (SPBE)


The main aim of the paper is to discover and compare variability and trends in the number of Automated Teller Machines (ATMs) over time in the recent history in the European Union member states, as well as to enlighten the influence of selected development indicators, which could explain the change in the No. of ATMs as the dependent variable in the regression model. The main variable under study is defined as the “No. of Automated Teller Machines—ATMs per 100,000 adults” (No. of ATMs). Using the regression modelling in analysing the impact of selected development indicators on the dependent variable No. of ATMs for the 28 EU countries in 2014, two OLS estimated multiple liner regression models, each with three independent variables, were built. Firstly, the economic development level indicator “GDP per capita, given as the PPP in current international $”, secondly, the ICT development level indicator the “No. of Internet users per 100 people”; and, finally, selected “digital banking development indicators”, are used as the regressors. The multiple regression models are analysed, showing that most of the independent variables are positively correlated with the “No. of ATMs”, with the exception of the “No. of Internet users per 100 people”. The conducted panel analysis revealed that the impact of selected independent variables on the No. of ATMs is quite similar to the impact observed in previously developed regression models.


Automated teller machines (ATM) Payment and terminal transactions GDP per capita Internet penetration rate Multiple linear regression modelling 



This work has been in part supported by the Croatian Science Foundation under the project STatistical Modelling for REspoNse to Crisis and Economic GrowTH in WeStern Balkan Countries—STRENGTHS (project no. IP-2013-9402).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Anita Pavković
    • 1
  • Ksenija Dumičić
    • 2
  • Berislav Žmuk
    • 2
  1. 1.Department of Finance, Faculty of Economics and BusinessUniversity of ZagrebZagrebCroatia
  2. 2.Department of Statistics, Faculty of Economics and BusinessUniversity of ZagrebZagrebCroatia

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