ATM networks and cash usage

Abstract

This article deals with the issue of how the market structure in banking affects the choice of the means of payment. In particular, the demand for cash is analysed from this point of view. The analysis is based on a simple spatial transactions model in which banks’ optimization problem is solved. The solution quite clearly shows that monopoly banks have an incentive to restrict the number of ATMs to a minimum. More generally, the number of ATMs depends on competitiveness in the banking sector. The predictions of the theoretical analysis are tested using a panel data from 20 Organization for Economic Co-operation and Development (OECD) countries for the period 1988 to 2003. Empirical analysis shows that there is a strong and robust relationship between the number of ATM networks and the number of ATMs (in relation to populations). Moreover, it can be shown that the demand for cash depends on the number of ATMs, ATM networks and the popularity of other means of payment. Thus, the use of cash can be pretty well explained in the transaction demand framework assuming that the market structure and technical environment is properly controlled.

Acknowledgements

Useful comments from Juha Tarkka, Jouko Vilmunen and Karlo Kauko, and participants of the FMG Workshop on Financial Regulation and Payment Systems, in September 2006, especially Leo van Hove, are gratefully acknowledged. Viren also thanks the Yrjö Jahnsson Foundation for financial support.

Notes

¹ The use of ATM fees is analysed e.g. in McAndrews (2001).

² The cash back facility in shops in Finland is quite limited–in some other countries, however, it is more widespread.

³ Whitesell (1992) is perhaps the first who has analysed banks’ role if payment system choices. His key variable is the size/frequency of transactions which, as we see later, makes it different from our model.

⁴ See Snellman (2006) for a survey of different models of payment media choice.

⁵ Empirical studies support the idea that cash dominates in small transactions but one cannot find a cleat cut-off point in terms of the size of the transaction such that the use of money would simply cease after that point. See Viren (1994) and more recently Bounie and Francois (2006) and Stix (2003) for details. As for firms, which are not handled here, see Hirvonen and Viren (1996) and Viren (1996).

⁶ In practice, this kind of fee is not usually charged from the customer but from the seller. Even if this is the case, the incidence of the fee could be quite the same as in the customer charge case. Even if there was no formal fee, we may assume that debit cards require some monitoring or transactions cost. If there were no costs whatsoever in using debit cards and if everybody could get a card we would end up with a corner solution.

⁷ In a (Salop) circle case, basically the same result would emerge, only that we would have b _max = 1/πA.

⁸ Obviously, s _i (·) would also depend on all relevant price parameters. The role of v, in particular, could be important not only in generating revenues but also in selecting customers. Having low values of A and v would possibly attract customers with large deposits and small amount of transaction services.

⁹ The nature of trade-off can be seen by multiplying the first two terms on the right-hand side of Equation 9 by s(A).

¹⁰ The exact formulas are available upon request from the authors.

¹¹ The derivation of the figure is based on the following parameter values: v = 0.001, z = 1000, T = 10, r = 0.03, i = 0.01, w = 10 000, N = 1000.

¹² Here we abstain from studying the direct effects of ATM networks on banks’ efficiency and costs. That may be motivated by the fact the effects seem quite ambiguous (Damar, 2006).

¹³ Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Luxembourg, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, the UK and the USA.

¹⁴ A detailed account of data and data sources is available from the authors upon request.

¹⁵ In our estimation, we used the data on ATM networks that are available in the ECB and BIS statistics. However, there are some exceptions. The number of ATM networks is one in Germany because it has been changed from four to one backwards in the statistics of the year 2004. According to the Central Bank of Germany, this has been done because the interpretation of ATM network has changed. So, there have not been any changes in the real number of ATM networks. Italy seems to show quite a similar case because they have changed the number of ATM networks backwards from one to four (four networks since 1996 or 1999, depending on the data source). We used four networks for Italy since 1996, and before that n.a. For Japan, we used the data for the period 1988 to 1999 because there have been changes in the method of data collection, and the post-2000 data are not consistent with the earlier data. For Finland, the number of ATM networks reported in the statistics has been one since 1994. However, there have been two other, small networks that were closed down in 2004. Because networks have been interoperable, we have not changed the reported values.

¹⁶ The Hausman tests for correlation of random effects with the Right-hand Side (RHS) variables indicated that the null hypothesis of zero correlation can be rejected–not very decisively but anyway with test statistics that exceeds the 5% critical level. Thus, from this point of view the fixed effects specification is slightly preferred in interpreting the results.

¹⁷ The development of the demand for cash represents some sort of puzzle because cash balances keep increasing in spite of all technical innovations. The best explanation for this phenomenon is probably an increase in money hoarding for various tax, social security and grey economy reasons (e.g. Boeschoten, 1992, Alanon and Gomez-Antonio, 2005). To model these factors, is a challenging task.