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The Use of ATMs in Bank Strategy: Is The re a Customer Relationship Effect? by Nadia Massoud* Anthony Saunders** Barry Scholnick* First Draft: May 2003 School of Business, Unive rsity Of Alberta* Stern School of Business, NYU** We would like to thank Rob Engle........ for their comments. We also would like to acknowledge the financial support of SHRC under grant No....., National Research Program on Financial Services & Public Policy at York university and the Salomon Center for the Study of Financial Institutions at NYU. I. Introduction Although the number of U.S. banks continues to decline there has been sustained growth in ATM networks and the number of ATMs. According to Dove (2002) virtually every U.S. bank is now a member of a shared network (such as Pulse, NYCE and Cirrus). Moreover, the number of ATMs had grown to over 324,000 as of the end of 2001 (see, Sienkiewicz (2002)). This proliferation of ATMs has occurred despite apparent complaints by bankers about the fixed and variable costs associated with the new ATMs added to their networks (Dove, 2002). One possible reason for the willingness of bankers to keep adding ATMs is that the revenue generated from these machines, in the form of direct surcharges to non-bank customers (so-called foreign customers) as well as other fees 1 outweighs the costs of ATM addition. Indeed, since April 1996 banks that are members of shared networks have generally been free to set their own surcharges for nonbank (foreign) customer use of their ATMs 2 (see, Hannan, Kiser, Prager, McAndrews (2002)). Thus, one reason underlying ATM proliferation is that foreign (non-bank) customer surcharges –so called ATM surcharges- have made adding ATMs to a bank’s network profitable, even in the presence of higher marginal costs. Indeed, revenues from surcharges were estimated to exceed $2 billion in 2001 alone (Dove 2002). Industry observers and economist have labeled this the “direct effect” on bank profits resulting from surcharging (see, for example, Dove (2002), Hannan, et al (2002) and Massoud and Bernhardt (2002a and 2002b)). Increasingly, however, bankers and economists are arguing that there is also a second, or indirect effect, that emanates from ATM proliferation and surcharging. Indeed, one strik ing 1 Other fee revenues includes a fee charged to a bank’s own customer who uses another bank’s ATMs (a so -called foreign fee) as well as interchange fees paid by the customers bank to the ATM owner when the bank’s own customer uses the owners ATM. The latter fee is usually set by the network and is constant across all banks in a network. Other fees that may be paid or charged include: own -bank ATM fee (wh ich is rare), POS fee, card fee and switch fee (see Stavins, 2000 p. 15). 2 Until April 1996 major shared networks such as Cirrus and Plus prohibited ATM surcharges on other network bank customers. Th is surcharge ban was eliminated in April 1996 and surcharges began to proliferate soon after. Moreover, surcharging was prohibited in a nu mber of states prior to 1996 (Prager 2001). 2 result of a recent Dove (2002) survey of banks is that over 50% of large financial institutions recognized that there may be an “indirect effect” or customer relationship effect from ATMs that can generate additional profits 3 for a bank. This indirect effect has been recognized in the theoretical papers of Massoud and Bernhardt (2002a and 2002b) and McAndrews (2002). While greater ATM proliferation may well attract more customers, due to considerations of convenience, the indirect impact of surcharges on total bank profits may be less clear. The argument here is that if consumers are forced to pay higher surcharge fees they face an incentive to switch to the bank charging the higher fees so as to avoid paying those fees. This is because only “foreign” customers, who are not account members of that bank, will pay an ATM surcharge. If this switching behavior occurs, then these customers will presumably purchase a variety of other bank products, which in turn will increase bank revenue and profits. While a variety of papers in the literature (Massoud and Bernhardt (2002a), 2002b) McAndrews (2002) and Hannan et al (2002)) have described or modeled the direct and indirect effects, this paper is the first to specifically test for the impact of these effects o n bank profitability. We are able to do this because we have access to a unique data set containing information, among other things, on bank ATM surcharges, ATM network size, ATM geographic dispersion, monthly total ATM transactions, the percentage of foreigners using ATMs for each of these banks and other key bank ATM variables. Specifically, the major contribution of this paper is that it estimates how strategic variables controlled by bank managers, in this case ATM surcharges and ATM network size, impact various outcomes that are of importance to bank profitability, through either the direct or indirect effect described above. Of particular interest is how a bank’s ATM surcharges 3 According to Dove (2002) report 50% of large financial institutional recognized that ATM deployment and pricing could be used to attract customers to other bank products. For examp le, a banker quoted fro m the Dove report p. 110 regarding the advantages underlying extensive ATM networks observed that such networks provided a bank with “the ability to leverage 18 million transactions per month into cross -sell opportunities for our products and services.” 3 (and ATM network size) impact its overall profitability – return on equity (ROE) and return on assets (ROA)– and its direct operational profitability from running its ATM network (ATM profits). While the impact of surcharges on a bank’s overall profitability (ROA or ROE) may be higher when surcharges increase, because of either the direct or indirect effects, ATM profitability will reflect the impact of the direct effect only. In addition, we believe we are the first to trace whether there is also evidence consistent with the impact of an indirect effect of ATMs on bank profitability. This is done by examining a two-step process. In the first step, we examine how bank surcharges (and ATM networks) impact the percentage of ATM users that are not bank customers (so-called foreign customers). A finding of a high surcharge being associated with low foreign percent usage would be consistent with (high) surcharges inducing foreign customers - especially those of small banks with limited networks --to switch their deposit accounts to larger banks’ charging relatively high surcharges so as to avoid such transaction costs. The second step is to analyze how surcharges (and ATM network size) impact the demand for bank services. A finding of a link between ATM strategic variables and the demand for bank services would be consistent with an indirect affect – one that appears to reflect a customer relationship effect. To proxy for bank services we analyze the sensitivity of depositor growth, total deposits and total loans to ATM surcharges and network size. Analyzing the effect of strategic ATM variables on bank profitability and the impact of the direct and indirect channels is different from much of the prior empirical research in this literature, which has tended to focus on conditions (e.g., bank size, market concentration etc..) under which a bank may or may not impose a surcharge and/or whether it is high or low (e.g., 4 Hannan et al, (2002), Stavins (2000)), rather than investigating the impact that ATM surcharges (and network size) have on bank profitability. Section 2 of this paper briefly provides an overview of ATM growth and pricing. Section 3 reviews the previous literature. Section 4 presents a model that shows how key ATM strategic variables (the surcharge and network size) affect: (i) bank profitability, (ii) the degree of foreign usage of a bank’s ATM networks and (iii) the demand for key bank products. Section 5 discusses the hypotheses and empirical methodology to be tested. Section 6 discusses the empirical results and finally Section 7 is a summary and conclusion. An Appendix to the paper describes in detail the data employed in this study from Dove Consulting (1999) and (2002)) – henceforth Dove. 2. ATMs The number of ATMs has grown significantly since being introduced in the late 1960s. For example, the number of ATMs stood at 324,000 in 2001 versus 83,000 in 1991. There have been at least 3 phases of growth identified (see Dove (2002)). The first phase was pre-1996, i.e., pre-independent surcharging, when there was relatively modest growth in ATMs. The second phase was 1996 to approximately 1998 when there was rapid ATM growth following the relaxation of restrictions on individual bank surcharges in 1996. The most recent period (i.e., post 1998) has reflected slower growth again. 4 When a consumer uses ATMs’ of banks other than his or her own (a so-called foreign consumer) he or she is charged at least two separate fees: (i) a surcharge fee by the bank which owns the ATM and (ii) a foreign fee by his or her own bank for using ATMs of other banks. 5 4 According to Dove (2002) the evolution of ATMs has followed the familiar “S” shape common to many innovations. 5 Stavins (2002) discusses other ATM related fees such as the interchange fee paid by banks. 5 Prior to 1996 banks’ were generally restricted by ATM shared networks from leveling surcharge fees on foreign customers who used ATMs in the shared network other than those of their own bank. Since that time, however, the number of banks charging such fees to foreign users has increased rapidly. By 1998 (only two years later) 78% of US banks were imposing surcharge fees (Stavins (2000)). In the Dove (2002) Survey more than 90% of the banks surveyed in 2001 imposed surcharges. Consequently, the surcharge fee has formed a key element in much of the prior ATM literature – discussed below in Section 3 -- and forms a central element of this paper. 3. Previous Literature on ATMs Following the dramatic increase in the number of banks applying a surcharge to their foreign customers, there has also been an increase in research on this issue. Massoud and Bernhardt (2000a and 2000b) and McAndrews (2002) have developed theoretical models which introduce and analyze the idea of the indirect effect of ATM surcharging on bank profitability. Other research, e.g., by Hannan et al (2002), Prager (1999), Stavins (2000) Prager (2001) have examined various empirical elements of ATM pricing. Specifically, in some of these papers (e.g., Hannan et al (2002) and Stavins (2000)) the empirical tests aim to identify factors that determine either the size of a bank’s ATM surcharge and/or whether a bank sets a surcharge or not 6 6 Hannan et al (2002) discuss in some detail the direct effect (“d irect revenue generation”) and the indirect effect (“strategic motive of attracting customers who wish to avoid paying surcharges”). However, given the nature of their data they are unable to directly test these hypotheses. They use a logit regression to examine which factors and market characteristics will impact the choice of whether or not to impose a surcharge. They find, for example, that the probability of surcharging decreases with ATM share in the market and ATM density while increasing with the importance of minorit ies in the market population and if the state liberalized early on its regulations on surcharging. They also find the rate of in-migration to the local banking market has significantly positive effects on surcharges. This is consistent with an indirect effect being present i.e., surcharges can induce switching by depositors. Stavins (2000) focuses on the size of ATM networks on surcharges and other fees. 6 This paper takes a different approach, in that it seeks to examine how a bank’s strategic choice of ATM surcharge and its size of ATM network affect bank profitability. In other words, while much of the literature has attempted to explain surcharging levels, our paper examines whether or not surcharging impacts key outcomes such as bank profitability. In this way we are better able to directly test the possible total impact, as well as the direct and indirect effects, of surcharging on bank profitability and service demand. One reason for our ability to examine this broader issue is that our data (described in detail in the Appendix) derived fro m market surveys by Dove ((1999), (2002)) provides both time-series and cross sectional information on bank surcharges and ATM network size. When combined with Call Report data on bank profitability, bank services and capital adequacy we are able to develop dynamic insights into how bank strategic variables impact a bank, and in particular, whether or not an indirect effect is present. Both the Hannan et al (2002) and Stavins (2000) studies are constrained to analyzing a single cross-section of bank surcharges and network size. 7 Moreover, the empirical question posed by Hannan et al (2002) -- the factors determining whether or not a bank imposes a surcharge -- was clearly of importance in the context of their 1997 database, when only about half the banks in their survey imposed surcharges. However, the very large increase in the proportion of banks using independent surcharges since 1997 leads us to ask a different question in this paper – what has been the impact that these surcharges on bank outcomes and, in particular, on bank profitability? The empirical research by Prager (2001) examines the issue of whether consumers from small banks will switch to larger banks in order to avoid paying a surcharge. This paper does not use bank level data but rather examines state level data comparing the market share of small 7 For example, in Hannan et al (2002), information about surcharges was collected by Moebs Services in 1997 (on behalf of the Federal Reserve Board) by telephone survey. Stavins (2000) uses data from a survey of financial institutions conducted by Bank Rate Monitor in May 1997. 7 banks in states (markets) with and without surcharging over the period 1987 to 1995. She concludes that small banks actually did a better job of retaining deposit market share in the presence of surcharging than in its absence. Prager uses this evidence to argue against an indirect effect. Prager does attempt to examine how surcharging may impact small bank profitability, but once again the analysis in conducted in terms of a comparison across marke ts (states), with and without surcharging, rather than at the individual bank level. Finally, Prager’s study covers a period prior to the liberalization of ATM surcharging and the dramatic growth in ATMs that occurred after 1996. By comparison our study uses data from the 1996-2001 period. 4. The Theoretical Model To establish a framework for an empirical analysis and hypotheses regarding the total, direct and indirect effects of bank ATM strategic choice variables we utilize the theoretical framework of Massoud and Bernhardt (2002b). In Massoud and Bernhardt (2002b) a spatial game is considered between two banks, A and B. Each bank is associated with a distinctive spatial line of length Q and each bank chooses the density of its ATM network on a distinctive line where ATM services can be obtained. There is a measure n of bank consumers. Consumers are distinguished by how much they value one bank intrinsically. The relative valuation for bank A is uniformly distributed over the range [-m,m]. In addition to providing bank deposits and other products banks provide ATM services for members and non- members (so called foreign users). First, consumers establish a bank account at a local branch. Consumers are then hit with a bank-specific location shock that is uniformly distributed over the range [0,Q]. Each customer receives incremental utility M from consuming bank services. The transportation cost of acquiring a service is Td where d is the 8 distance traveled to the closest ATM and T is an incremental transportation cost. Each Bank chooses its own ATM network size, j , bank “service” fees, F j and an ATM service fee to members and non- members, P j ( ) where 1 for members and 0 for non- members. Here bank “service” and associated service fees (F j) are broadly defined to include the spread on investing in assets backed by relatively low cost deposits. Stavins (2002) among others argues that the fee banks charge their own customers for using their own ATM machines is invariably zero. Timing of the game follows 3 stages: Stage 1, banks maximize profits by choosing the density of their ATM locations and the prices charged for different services (e.g. ATM surcharge to foreign users). Stage 2, each consumer chooses a bank at which to establish an account. Stage 3, each consumer receives a bank-specific location shock and chooses where to obtain his/her ATM service. The expected profit function of Bank A is A N A F A N B y A (0)( p A (0) C ATM ) AC , 8 (1) Where N j is the number of bank j’s customers, C ATM is the marginal cost of providing ATM services to non- members, C is the cost of installing each ATM machines, y A (0) is the percent of foreigners as customers, (i.e. bank B customers in this game using bank A’s ATMs) and p A (0) is the ATM surcharge fee bank A charges bank B customers. The first term in equation (1) is the bank’s profit from members use of bank products such as deposits and loans, the second term is the profit from non- members (i.e. foreigners) who use bank A’s ATM service and the last term is the cost of installing the ATM network. 8 For simp licity, we consider a reduced form of the profit function where the in -branch service fee and the ATM service fees for members are set to be equal to their marginal cost. This simp lification is introduced after recognizing that banks in equilibriu m charge their members two part prices (Massoud and Bernhardt 2002a and 2002b). 9 When a bank chooses its optimal ATM surcharge it takes into consideration how that surcharge would directly impact its profitability -- which depends on foreign customers demand elasticity. It also takes into account the indirect effect on its profitability. That is, the effect of ATM pricing on a bank’s profitability can be decomposed into two effects: a direct and a indirect effect. Bank Surcharge The effects of a marginal change in the ATM surcharges on a bank’s profitability is shown by the following first order condition: A N N y A (0) A A F A A B y A (0)( p A (0) C ATM ) N B A ( p A (0) C ATM ) y A (0) p (0) p (0) p (0) A p (0) (2) Where N A N y A (0) 0, A B 0 and A 0 p (0) A p (0) p (0) The first two terms, in equation (2), show the indirect effect of ATM surcharges on bank A’s profitability, where N A F A is the increase in bank-account membership and bank service A p (0) purchases induced by a marginally higher surcharge times the bank service “fee” or profit extracted, and N B y A (0)( p A (0) C ATM ) is the loss in surcharge revenues from those foreign A p (0) customers (i.e. bank B customers in this model) who switch bank- membership to bank A, due to the increase in ATM surcharges. The last term in equation (2), y A (0) N B A ( p A (0) C ATM ) y A (0) , p (0) shows the direct effect of ATM surcharges on bank A’s profitability which is the impact of increasing ATM surcharges on surcharge profits from (foreign) customers who continue to establish bank accounts at bank B. The last term in equation (2) or the direct effect can be rewritten in terms of non- members ATM demand elasticity, : 10 ( p A (0) C ATM ) the sign of this term depends on ( p A (0) C ATM ) . If this term y A (0) N B 1 sign 1 p A (0) p A (0) is non-negative, ( p A (0) C ATM ) p A (0) p A (0) 1 0 , then it implies that and 1. p A (0) p (0) C ATM A p (0) C ATM A Given that in general a monopoly operates in a price region such that the elasticity exceeds one 9 , then this inequality p A (0) should hold which implies that ATM profits are 1 p A (0) C ATM positively related to ATM surcharges. Note also that, N A 0 , shows that an increase in the p A (0) ATM surcharge increases a bank’s customer base because of switching, that N B shows that 0 p A ( 0 ) an increase in the ATM surcharge reduces a rival bank’s customer base and y A (0) shows 0 p A (0) that an increase in the ATM surcharge reduces a bank’s market share of non-member (foreign) customers. Bank ATM network The effect of size of a bank’s ATM network on a bank’s profitability is shown by the following first order condition: A N A A N B A y A (0) F y (0)( p A (0) C ATM ) N B ( p A (0) C ATM ) C (3) A A A A Where N A N y A (0) reflects the relative size of bank A’s ATM network. Here 0, B 0, 0 and A A A A again we can decompose the effect of the size of a bank’s ATM network on bank profitability into direct and indirect effects. The direct effect is captured by the third and the fourth terms of y A (0) equation (3), i.e. N B ( p A (0) C ATM ) C , which shows how a marginal increase in a bank’s A ATM network would increase bank revenue from non- member (foreign) users of ATMs. The direct effect would be positive if the marginal increase in ATM revenue is higher than the cost of adding one more ATM to the network, that is y A (0) N B ( p A (0) C ATM ) C . A 9 Tirole (1988), page 66, where elasticity of demand is lo wer than 1, the monopolist’s revenue -- and his profits -- are decreasing in quantities. 11 The indirect effect is captured by the first two terms in equation (3), where N A F A shows A how a larger ATM network would increase a bank’s customer base (bank produc t purchases) because of switching and N B y A (0)( p A (0) C ATM ) shows the marginal loss in ATM surcharge A revenues because of foreign customer switching to become bank customers. Note that N A 0 shows an increase in a bank’s ATM network increases its ability to expand its A customer base, also N B 0 shows that an increase in a bank’s ATM network would decrease A the customers bank account base of a rival bank (here bank B). Finally, y A (0) shows that a 0 A larger ATM network would increase the market share of non- member (foreign) users of ATM’s. One of the main implications of the Massoud and Bernhardt (2002b) model is that banks tend to over-provide ATM’s because they extract profits more efficiently from bank members through bank service fees and other income (such as the spread on deposits) rather than from ATM use by (foreign) members of other banks, and that a more developed ATM network raises the attraction of establishing account membership with a bank. 5. Hypotheses From the theoretical model in Section 4 in which a bank employs its surcharge level and ATM network as strategic variables to increase profitability either through the direct or indirect channels we can derive a number of testable hypotheses. Specifically, we test the following hypotheses with respect to surcharges, ATM network size and bank profitability: Total Effect Hypothesis 1: If foreign users are relatively price inelastic (direct effect) and/or switching is sufficiently strong to overcome any loss in revenue if foreign users are price elastic (indirect effect), then overall profitability will be increasing in surcharge levels: 12 () ( ) H1: ROE j f ( p j (0), j ) () ( ) ROAj g ( p j (0), j ) Note that we can also test an implication of the Massoud Bernhardt (2000b) Model – see Section 4 – that banks tend to over provide ATMs such that bank profitability (return) is decreasing in the size of a bank’s ATM network. An alternative hypothesis – believed by many bankers (see Dove (1999)) -- is that greater network size adds to the customer attraction to a bank and as a result the relationship between overall profitability (return) and network size is positive. Here we specify, a priori, a negative relationship between overall bank profitability and ne twork size in hypothesis 1, but recognize that the sign may be non-negative. Indirect Effect Hypothesis 2: While a finding that overall profits are positively linked to surcharges is consistent with the presence of both direct and indirect effects we wis h to investigate these two alternative channels more deeply. In particular, a two-step process is required for the indirect channel. Consequently, we propose to test H2 and H3: ( ) ( ) H2: y j (0) h( p j (0), j ) H2 tests the first step in the indirect channel, namely that higher surcharges ( p j (0) ) result in a lower proportion of foreign ATM users ( y j (0) ) since foreign users have an incentive to switch to becoming bank customers to avoid surcharges. Thus, the relationship between foreign usage proportion and bank surcharge levels is expected to be negative. A conventional 13 view is that greater network scope ( j ) will add to foreign customers use of the ATM network – a positive network size effect. That is, the relationship between y j (0) and j will be positive. However, if Massoud and Berhardt (2002a) are correct and banks over provide ATMs, then this relationship may be negative. Note a negative relationship between y j (0) and j would also be consistent with a switching effect. That is, the reduction in the proportion of foreigners using a (larger) bank’s ATMs could be the result of those customers switching to banks with larger ATM networks that offer consumers greater convenience. Thus, we hypothesize, a priori that a negative relationship exists between foreign usage proportion and network size, but recognize that the relationship maybe positive. Hypothesis 3: () () H3: Depositor growthj k ( p j (0), j ) ( ) ( ) Deposits j h( p (0), j ) j () () Loansj i( p j (0), j ) H3 reflects the second step in the indirect channel, namely that ATM users who switch to become bank account holders consume more bank products. Here we proxy fo r increased consumption of bank products by the dollar size of a bank’s deposits and loans. Such consumption would potentially add to a bank’s overall profitability. We also look at the link between surcharges and network size and a bank’s depositor growth. If the indirect channel is operational we would expect both surcharge level and ATM network size to have positive effects on depositor growth over the succeeding period, which is a precondition for them to expand their purchases of a bank’s products. 14 Direct Effect Hypothesis 4: () ( ) H4: ATM profitsj m( p j (0), j ) Hypothesis H4 seeks to test the direct effect. Specifically, if foreign customer demands were sufficiently price inelastic then raising surcharge levels would add to a bank’s profits from ATM provision. That is, there should be a positive relationship between ATM profitability and p j (0) the surcharge level. Similarly if (marginal) additions to a bank’s ATM network adds to its revenues and they exceed any additional costs, then greater network size should also increase bank profits. That is, ATM profitability should be positively associated with network size. However, to the extent that bank’s over provide ATM’s (as in Massoud and Bernhardt, 2002a and 2002b) then the relationship between ATM profitability (return) and ATM network size may be negative. Thus, we hypothesize, a priori a negative sign. The next section discusses the empirical methodology used to test these hypotheses and the empirical results. 6. Empirical Methodology and Results The Appendix to this paper provides a detailed description of data used in this study. As discussed there the empirical tests are based on underlying survey data generated by Dove Consulting of Boston in two reports on ATM deployment – the first in 1999 and the second in 2002. These data provide bank specific details by bank and year regarding surcharge levels, ATM network size, transactions per ATM, percent use of a bank’s ATM network by foreigners as well as other pertinent ATM related data. As a result our basic sample size covers 1996 – 2001 (six years). As discussed in the Appendix not every variable was measured each year and 15 the sample of banks differed over the 1999 and 2002 surveys. Nevertheless, we feel that this data set is sufficiently unique to allow us to examine the impact of ATM strategic variables (ATM surcharge and ATM network size) on bank profitability as well as to gain insights into the indirect and direct channels through which ATMs affect bank profitability. To gain insights into the indirect channel and to control for bank size, bank risk and market share we employ bank Call Report data and Federal Reserve generated bank market share data. With respect to the dependent variable data on bank depositor growth (percentage change in the number of depositors) and the dollar value of deposits and loan these were derived from Call Reports that most closely matched the dates of the Dove surveys. This was also true for the independent or control variables used: the bank’s capital – assets ratio (a measure of bank risk), bank assets (a measure of a bank’s size) and bank market share (a measure of local market competitive conditions). 10 An additional independent variable that we include is the number of transactions per ATM. This variable, taken from the Dove data set, includes both foreign as well as customer transactions at ATMs. This variable captures the “S” shaped growth curve in the number of ATMs from 1996 to 2002 described in detail by Dove (2002). By including this variable as an independent variable, we are able to capture the possible impact of the under/oversupply of ATMs on the dependent variables of interest. We also included in the tests a measure of geographic dispersion of a bank’s ATM network. Dove consulting divides the U.S. up into 7 regions and identifies whether a bank has ATMs in each region and outside U.S. (internationally). -- making 8 possible region in all. Since a bank has an endogenous choice to make regarding the number of regions it wishes to span with 10 The market share variable used in these tests was the percent of the banks deposits relative to total deposits in the State in wh ich the bank’s HQ is located. 16 its ATM network, it can use greater geographic or dispersion scope to attract new customers to the bank. 11 That is, geographic dispersion could be considered as an additional ATM strategic variable along with the level of bank surcharge and the size of a bank’s ATM network. The geographic dispersion variable takes a value between one and eight, where the value of the variable reflects the sum of the regions over which a bank locates its ATMs. The Appendix discusses in more detail the different regions identified in the Dove surveys. In testing hypotheses H1 to H4 we employ both fixed and random effect tests of the impact of the ATM strategic choice variables (ATM surcharge and number of ATMs) on the various outcomes of interest (profits, demand for other bank products etc...). We report both the fixed effect and random effect results, as well as reporting the Hausman test statistic to determine if the random effects model is appropriate for a given model. In all of our tests we report both contemporaneous results (i.e. where the dependent variable is measured in the same year as the independent variables) - which are labeled “Current” - and results when the dependent variable is one year ahead of the independent variables – which are labeled “Lead”. There are two reasons why we believe that the lead results offer a better test of the link between ATM strategic variables and bank profitability. First, the lead results capture causality in the relationship by focusing on how a change in the independent bank strategy variables (e.g. ATM surcharge) impacts the dependent bank outcome variables (e.g. return) one year later. Second, the lead equations also capture any likely institutional frictions, in that it may take a period of time for consumers to p rocess the fact that a bank has changed its ATM, pricing strategy and a further period of time to decide to switch to a new bank. 11 For example, by expanding a network out of reg ion a bank provides convenience for those customers who travel extensively and may persuade more foreigners to switch their accounts to the bank. 17 However, it is also possible that this switching decision may be made relatively quickly, which is why we also report the “current” equations. Results of the Effects on Total Profitability (H1) Tables 1a, 1b, 2a and 2b show, respectively, the effects of surcharge change and ATM network size on bank ROA and ROE. ATM network “size” is measured by the number of ATMs owned by the bank. As can be seen a striking result in all four tables is the positive and statistically significant impact of bank surcharge levels on bank profitability. As noted earlier, this positive total effect may be due to either a direct effect or an indirect effect -- reflecting customer switching. The impact of the number of ATMs is generally insignificant. This suggests little systematic linkage between the size of a bank’s ATM network and its ATM overall profitability. With respect to the other (control) variables no particular pattern is striking. Thus H1 is supported for bank surcharge levels, but rejects the hypothesis with respect to a negative linkage between ATM network size and overall bank profitability. Results for the Indirect Channel (H2 and H3) Tables 3a and 3b show the sensitivity of foreign (non-bank) ATM users to the level of the bank’s ATM surcharge. As can be seen in both Tables 3a and 3b, for both random and fixed effect models, surcharge is significantly negative. That is a higher surchar ge results in a lower foreign percentage usage, which is consistent with switching and supports H2 (it is also the first step in the indirect channel). With respect to ATM network size, the number of ATM’s is insignificant in both Tables 3a and 3b. Again, there is little overall pattern in the other control 18 variables. Overall, there is some evidence that is consistent with the first step in the indirect channel and thus with switching. Tables 4, 5a, 5b, 6a, and 6b seek to test the second step in the indirect channel (hypothesis H3), i.e., once a customer has switched do we see an expansion in customer demand for bank products? Table 4, analyses the percentage growth in bank depositors on a year-by- year basis. As can be seen for both the fixed and random effect models a high bank ATM surcharge is associated with a higher depositor growth rate in the succeeding year. Similarly the number of ATMs variable is significantly positive for both the fixed and random effects models, again this is consistent with the switching story and the indirect channel. The geographic dispersion variable is positive and significant in both the fixed and random affect models in Table 4. That is, banks with more extensive geographic networks engender greater depositor growth over the succeeding year. Because geographic dispersion of ATMs can be thought of as a bank strategic variable this is also consistent with the indirect channel and switching. Table’s 5a, 5b, 6a and 6b analyze the effects of bank surcharge level and ATM network size on specific bank products. For the dollar value of deposits and loans (5a and 6a), where a one year lead variable is used as the dependent variable, the bank ATM surcharge level is positive and statistically significantly related to deposits and loans. Furthermore, it also appears that increasing the number of ATMs (the second strategic variable) has a generally positive and statistically important effect on (next period’s) deposit and loan amounts. Geographic dispersion also has a significant and positive impact on the (next period) amount of deposits (6a). These results are consistent with the second step in the indirect channel, suggesting a potential customer relationship or switching effect linking ATM strategic variables and bank profitability. 19 As described above, we have a preference for the lead model tests (5a and 6a) over the current model tests (5b and 6b) due to of both econometric issues (the clarity of the causality relationship between strategy changes this year and outcome changes next year) as well as issues relating to institutional frictions (the lag in consumers becoming aware of bank strategic changes and the additional lag in acting on these changes to switch banks). It might be noted that the results in Tables 5b and 6b for the current models are less strong than the lead results (5a and 6a). Specificantly, general while surcharge has a positive sign it is statistically insignificant in the current regressions. The Direct Effect (H4) To test the direct effect of the strategic variables on bank profitability (hypothesis H4) we utilized the Dove consulting data to calculate the profitability of operations of “within branch” ATMs. This test was unable to include out-of-branch ATMs (and their profitability) since Dove did not collect these data. Moreover, only one year of data is available on ATM profitability and even then for just 33 banks. The results of the regression of bank ATM profits on our strategic and control variable is shown in Table 7. While both surcharge and the size of ATM network variables have positive signs, however, these variables are statistically insignificant. Nevertheless, while the evidence in Table 7 tends to reject the direct effect (and H4), the results may well reflect the limited sample size with which the tests were undertaken. 7. Summary and Conclusion This paper has modeled and tested the relationship between a bank’s use of strategic ATM variables – the foreign-user surcharge and its own network size – and a bank’s overall 20 profitability. An important aspect of the study was to differentiate the direct and indirect (or customer relationship) channels linking surcharge levels and network size to bank profitability. Using a unique data set provided by Dove Consulting, which contained both time-series as well as cross-sectional information on bank surcharges and other ATM related variables, it was found that there is evidence consistent with customer switching and thus the indirect channel. Specifically, higher surcharge levels were associated with greate r depositor growth, greater deposit amounts and greater loan amounts. In addition foreign ATM users seemed to be adverse to high surcharge levels, such that high surcharge levels may have induced foreign users to switch to becoming account holders of the high foreign surcharge bank. The evidence, in general, is consistent with presence of an indirect channel and switching. With respect to the direct channel, the data on ATM profitability that was available was very limited and what was available failed to support the hypothesis of a significant linkage between bank strategic ATM variables and ATM profitability. Clearly, this is one area that needs further research as more extensive databases on ATM profitability become available. 21 Table 1a: The Relationship Between ATM Strategic Variables and ROA (Lead), 1996-2001 Standard Standard Random Effects error Fixed Effects error Surcharge 0.173786*** 0.0454716 0.1518829** 0.061278 Number of ATMs 7.62E-06 0.0000372 -0.0000322 0.0000912 Geographic Dispersion 0.037714 0.0287631 0.1599676** 0.0780467 Transactions per ATM 5.87E-06 4.34E-06 -4.01E-06 0.0000141 Bank Capital Ratio 0.006841 0.0056544 -0.0008283 0.0185794 Bank Assets 3.20E-13 6.78E-13 3.58E-13 1.54E-12 Bank Market Share -0.00017 0.0010936 -0.0015881 0.0012486 Constant 0.335854*** 0.0973816 0.3172375 0.2256431 Sample Size 276 276 R 2 Within 0.09 0.11 R 2 Between 0.12 0.04 R 2 Overall 0.09 0.03 Hausman Test 2 9.54 (0.2161) Random effects is appropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value Source for all Tables: Dove (1999, 2002), Call Report and Source data. 22 Table 1b: The Relationship Between ATM Strategic Variables and ROA (Current), 1996 - 2001 Standard Standard Random Effects error Fixed Effects error Surcharge 0.101384** 0.040927 0.096822* 0.051368 Number of ATMs -6.17E-06 3.52E-05 -2.1E-05 7.72E-05 Geographic Dispersion -0.006 0.027335 -0.0752 0.065878 Transactions per ATM 5.86E-06 4.18E-06 9.06E-06 1.19E-05 Bank Capital Ratio 0.00092 0.005278 -0.04439*** 0.012913 Bank Assets 3.98E-13 6.33E-13 1.59E-12 1.30E-12 Bank Market Share 0.002601*** 0.000955 0.003011*** 0.00105 Constant 0.518622*** 0.089926 1.034202*** 0.168692 Sample Size 282 282 R 2 Within 0.056 0.12 R 2 Between 0.067 0.00 R 2 Overall 0.102 0.00 Hausman Test ( 2 ) 22.65(0.00) Random effects is inappropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 23 Table 2a: The Relationship Between ATM Strategic Variables and ROE (Lead) Standard Standard Random Effects error Fixed Effects error Surcharge 2.0642340*** 0.6466082 2.463823** 0.972484 Number of ATMs -0.0002266 0.0004920 -0.0013718 0.001447 Geographic Dispersion 0.1826976 0.3781347 1.643325 1.238605 Transactions per ATM 0.0000671 0.0000555 -0.0000657 0.000224 Bank Capital Ratio -0.2640739*** 0.0728048 -0.6417043** 0.294856 Bank Assets 8.32e-12 9.31E-12 2.25E-11 2.44E-11 Bank Market Share 0.0321767* 0.0169702 0.0141022 0.019815 Constant 7.5169910*** 1.3155360 9.389141*** 3.580964 Sample Size 276 276 R 2 Within 0.07 0.10 R 2 Between 0.18 0.13 R 2 Overall 0.17 0.12 Hausman Test 2 9.57 (0.2141) Random effects is appropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 24 Table 2b: The Relationship Between ATM Strategic Variables and ROE (Current), 1996 - 2001 Standard Standard Random Effects Error Fixed Effects Error Surcharge 1.487136** 0.610112 1.884333** 0.772716 Number of ATMs -0.00014 0.000498 -0.00062 0.001162 Geographic Dispersion 0.087227 0.38436 -0.85274 0.991 Transactions per ATM 9.09E-05 5.78E-05 0.000166 0.000179 Bank Capital Ratio -0.41068*** 0.073679 -1.64494*** 0.194244 Bank Assets 2.44E-12 9.11E-12 2.46E-11 1.96E-11 Bank Market Share 0.022404 0.014906 0.029696* 0.015797 Constant 9.563363*** 1.29026 21.63025*** 2.537614 Sample Size 282 282 R 2 Within 0.21 0.31 R 2 Between 0.16 0.13 R 2 Overall 0.16 0.13 Hausman Test 2 47.73(0.00) Random effects is inappropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 25 Table 3a: The Relationship Between ATM Strategic Variables and Foreign Percent ATM Usage (Lead), 1996 – 2001 Standard Standard Random Effects error Fixed Effects error Surcharge -6.06197** 2.893624 -8.36561* 5.04634 Number of ATMs -0.00413 0.003508 -0.01088 0.011228 Geographic Dispersion -0.16339 1.864571 -0.45271 5.560722 Transactions per ATM -0.00066*** 0.000267 -0.00092 0.001302 Bank Capital Ratio 26.6787 33.39713 225.3731** 111.3641 Bank Assets 4.88E-11 9.48E-11 1.33E-10 1.84E-10 Bank Market Share 0.010403 0.202422 1.635177 1.039176 Constant 44.24957*** 6.190163 22.43404 16.61529 Sample Size 120 120 R 2 Within 0.2667 0.4117 R 2 Between 0.0887 0.0114 R 2 Overall 0.1082 0.0184 Hausman Test 2 14.46 (0.0435) Random effects is inappropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 26 Table 3b: The Relationship Between ATM Strategic Variables and Foreign Percent ATM Usage (Current) 1996 – 2001 Standard Standard Random Effects error Fixed Effects error Surcharge -6.28685*** 2.133036 -6.92507** 2.935974 Number of ATMs -0.00096 0.00179 -0.00177 0.00523 Geographic Dispersion -0.07767 1.328582 -7.93143** 4.042646 Transactions per ATM -0.00059*** 0.00024 0.000442 0.000761 Bank Capital Ratio 0.06763 0.256811 -0.62671 1.150436 Bank Assets -4.40E-12 3.13E-11 8.05E-11 8.70E-11 Bank Market Share -0.17791 0.169284 -0.02708 0.486601 Constant 47.73202*** 4.691936 62.791.58*** 13.50732 Sample Size 182 182 R 2 Within 0.1112 0.1692 R 2 Between 0.1505 0.0002 R 2 Overall 0.1336 0.0026 Hausman Test 2 5.98(0.5424) Random effects is appropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 27 Table 4: The Relationship Between ATM Strategic Variables a time t and the Percentage Change in the Number of Bank Depositors (t to t + 1), 1996 - 2001 Standard Standard Random Effects error Fixed Effects error Surcharge 47.81289** 24.43226 50.3209* 26.13786 Number of ATMs 0.053089** 0.027212 0.099056** 0.038599 Geographic Dispersion 47.37285** 21.77648 111.5937*** 33.10758 Transactions per ATM 0.000697 0.003593 -0.00114 0.006007 Bank Capital Ratio -4.29506 4.656989 -4.04919 8.050552 Bank Assets -1.78E-09*** 4.67E-10 -3.07E-09*** 6.53E-10 Bank Market Share -0.87636* 0.499643 -1.33361** 0.528409 Constant -35.5029 70.2705 -166.273* 96.73478 Sample Size 268 268 R 2 Within 0.19 0.21 R 2 Between 0.00 0.00 R 2 Overall 0.01 0.00 Hausman Test 2 17.65(0.014) Random effects is inappropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 28 Table 5a: The Relationship Between ATM Strategic Variables and the Dollar Value of Bank Loans (Lead), 1996 – 2001 Standard Standard Random Effects error Fixed Effects error Surcharge 2.36E+09* 1.36E+09 6.73E+09** 2.80E+09 Number of ATMs 3113974*** 950782.7 2.35E+07*** 4162531 Geographic Dispersion 6.72E+08 6.80E+08 5.05E+09 3.57E+09 Transactions per ATM 40439.83 97145.84 196391.1 642715.6 Bank Capital Ratio -5.94E+07 1.29E+08 -2.06E+09** 8.46E+08 Bank Assets 0.5669262*** 0.022156 -0.0266869 0.070348 Bank Market Share 3.18E+07 4.90E+07 -2.08E+07 5.70E+07 Constant -2.68E+09 2.57E+09 2.11E+09 1.03E+10 Sample Size 278 278 R 2 Within 0.66 0.75 R 2 Between 0.99 0.47 R 2 Overall 0.90 0.59 Hausman Test 2 283.024(0.00) Random effects is inappropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 29 Table 5b: The Relationship Between ATM Strategic Variables and the Dollar Value of Bank Loans (Current), 1996 – 2001 Standard Standard Random Effects error Fixed Effects error Surcharge 3.86E+08 3.04E+08 3.30E+08 3.28E+08 Number of ATMs -68695.5 302670.3 -638005.8 493159.9 Geographic Dispersion -9.24E+08*** 2.38E+08 -2.86E+09*** 4.21E+08 Transactions per ATM -538.441 37747.33 81332.05 76027.49 Bank Capital Ratio 4.64E+07 4.65E+07 -3.94E+07 8.24E+07 Bank Assets 0.611503*** 0.005274 0.636024*** 0.00832 Bank Market Share 5911443 6561399 1.87E+07*** 6705126 Constant 4.36E+08 7.50E+08 4.04E+09*** 1.08E+09 Sample Size 282 278 R 2 Within 0.99 0.74 R 2 Between 0.99 0.46 R 2 Overall 0.99 0.58 Hausman Test 2 54.45(0.00) Random effects is inappropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 30 Table 6a: The Relationship Between ATM Strategic Variables and the Dollar Value of Bank Deposits (Lead), 1996 – 2001 Standard Standard Random Effects error Fixed Effects error Surcharge 1.62E+09 1.64E+09 4.98E+09* 2.64E+09 Number of ATMs 1.10E+07*** 1218081 1.09E+07*** 3933569 Geographic Dispersion -2.38E+09** 9.33E+08 7.42E+09** 3.37E+09 Transactions per ATM -3002.922 135721.9 91173.39 607362.8 Bank Capital Ratio -2.37E+08 1.78E+08 -1.65E+09** 8.00E+08 Bank Assets 0.3284854*** 0.023478 0.2584174*** 0.066479 Bank Market Share 2.75E+07 4.47E+07 -3.91E+07 5.38E+07 Constant 3.69E+09 3.28E+09 -2.18E+09 9.71E+09 Sample Size 278 278 R 2 Within 0.79 0.81 R 2 Between 0.89 0.72 R 2 Overall 0.89 0.73 Hausman Test 2 21.21(0.0035) Random effects is inappropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 31 Table 6b: The Relationship Between ATM Strategic Variables and the Dollar Value of Deposits (Current), 1996 – 2001 Standard Standard Random Effects error Fixed Effects error Surcharge -4.02E+08 4.74E+08 -2.36E+08 3.58E+08 Number of ATMs 1438626** 633301 -1646841*** 538092.9 Geographic Dispersion -2.07E+09*** 5.22E+08 -7.66E+08* 4.59E+08 Transactions per ATM -14072.13 89891.54 15841.49 82954.53 Bank Capital Ratio 7.39E+07 1.03E+08 1.79E+07 9.00E+07 Bank Assets 0.532291*** 0.010729 0.580527*** 0.009078 Bank Market Share 1.73E+07* 9669386 1.28E+07* 7316046 Constant 1.79E+09 1.70E+09 1.52E+09 1.18E+09 Sample Size 282 282 R 2 Within 0.99 0.99 R 2 Between 0.82 0.78 R 2 Overall 0.90 0.88 Hausman Test 2 0.00 (1.0) Random effects is appropriate estimator *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 32 Table 7: The Relationship Between ATM Strategic Variables and In-Branch ATM Profitability, 2001 Coefficient Standard error Surcharge 1370.984 983.3386 Number of ATMs -0.39663 0.627244 Geographic Dispersion -105.544 369.777 Transactions per ATM -0.25734 0.270495 Bank Capital Ratio -3.90388 125.0021 Bank Assets 1.01E-08 1.29E-08 Bank Market Share 36.58582 43.71877 Constant -816.889 2349.393 Sample Size 33 R2 0.22 F-test 0.99 *** Indicates p value of 1% ** Indicates p value of 5% * Indicates p value of 10% (.) Indicates p value 33 Appendix Data An important aspect of this paper lies in the uniqueness of the ATM data set employed in our tests. This data set was purchased from Dove Consulting Inc. and includes bank level data on a variety of variables that have not been previously used in the empirical ATM literature. In particular, the data includes a measure of the percentage of ATM users for different banks, who are foreigners – i.e., those who pay ATM surcharges. This variable – in conjunction with other data such as surcharge amount and ATM network size, allows us to test the hypotheses discussed in the paper. The Dove Survey data is used in conjunction with a variety of other publically available sources of bank level data, including Call Reports (Report of Condition and Income) taken from the Federal Reserve web site and Market Share data taken from SOURCE. The database provided by Dove Consulting is taken from two separate surveys of ATM providers – one taken in 1998 and the second in 2001(The Dove reports themselves were published in 1999 and 2002 respectively). In each case data were collected from each bank in the sample for the preceding three years generating a 6-year sample that spans 1996-2001. Unfortunately, the two surveys are not identical across the two time periods thus some data are available for only some of the time periods. For example, while each of the two Dove surveys asked respondents for information on a variety of variables for each of the proceeding three years, this was not the case for the foreign percentage variable. The first survey conducted during 1998 did ask for this data for each of the preceding 3 years, however the second survey only asked the respondents for this data for the final year of that survey i.e., 2001. In other words, for some of our empirical tests, which require the use of the foreign percentage variable, we use a data set made up of certain banks for each of 1996, 1997 and 1998 and different banks in 2001. 34 A further issue with our data concerns how the banks were asked to report their ATM surcharges over the preceding three years. In the case of both the 1998 and 2001 surveys, banks were asked to provide data on their ATM surcharges at the time of the survey. They were also asked to provide the date of the last change of the surcharge and how much that change was (in dollars and cents). This information is enough to create a partial historical record of surcharges charged by each bank. For example, if the date of the pervious surcharge change occurred prior to the three-year period covered by the survey, then we are able to use the value of the surcharge in the final year of the survey for all of the previous three years. Similarly, if the most recent surcharge change occurred during the preceding 3 years we are able to infer surcharges after that date. However, we would not be able to infer surcharges outside the three- year window of each data set. In cases where we are not able to infer the surcharge amount from the data, we do not use the data. One important variable employed is the measure of geographic dispersion of a bank’s ATM network. Dove divides the U.S. into 7 regions and identifies whether each bank (in each year) has an ATM in one of those regions plus whether ATMs are held internationally (making 8 regions). The 7 U.S. regions identified were New England, Mid-Atlantic, Southeast, South, Midwest, Mountain and Pacific (see Dove, 1999, p. 27). The geographic dispersion variable takes a value between one and eight, where the value of the variable reflects the sum of the regions where a bank locates its ATMs. For example, if geographic dispersion is equal to one, it indicates an ATM presence in only one region and if it is higher than one it indicates presence in more than one region. 35 References 1. Dove Consulting Group, 1999 ATM Deployer Study, Boston, 1999. 2. Dove Consulting Group, 2002 ATM Deployer Study, Boston, 2002. 3. Hannan, T.H., E.K. Kiser, R. Prager and J.J. McAndrews, “To Surcharge or Not to Surcharge: An Empirical Investigation of ATM Pricing,” mimeo 2002, Review of Economics and Statistics (forthcoming). 4. Massoud, N. and D. Bernhardt, “Rip-off ATM Surcharges” Rand Journal of Economics, Spring 2002, pp. 96-115. 5. Massoud, N. and D. Bernhardt,” Endogenous ATM Location and Pricing,” Working Paper, Dept. of Finance, School of Business, University of Alberta. 6. McAndrews, J.J., “A Model of ATM Pricing: Foreign Fees and Surcharges,” mimeo, Federal Reserve Bank of New York, 2002. 7. Prager, R., “ATM Network Mergers and the Creation of Market Power,” The Antitrust Bulletin, summer, 1999 pp. 349-363. 8. Prager, R., “The Effects of ATM Surcharges on Small Banking Organizations,” Review of Industrial Organization, 2001, pp. 161-173 9. Sienkiewicz, S., “The Evolution of EFT Networks from ATMs to New On- Line Debit Payment Products,” Discussion Paper: Payment Cards Center, Federal Reserve Bank of Philadelphia, April 2002. 10. Stavins, J., “ATM Fees: Does Bank Size Matter?” New England Economic Review, January/February 2000, pp. 13-24. 36