Quantifying equilibrium network externalities in the ACH banking industry

• Author: Gautam Gowrisankaran,Daniel A. Ackerberg
• Published date: 01 September 2006
• Date: 01 September 2006
• DOI: http://doi.org/10.1111/j.1756-2171.2006.tb00040.x

mss # Ackerberg & Gowrisankaran; art. # 13; RAND Journal of Economics vol. 37(3)

RAND Journal of Economics

Vol.37, No. 3, Autumn 2006

pp. 738–761

Quantifying equilibrium network

externalities in the ACH banking industry

Daniel A. Ackerberg∗

and

Gautam Gowrisankaran∗∗

We seek to determine the causes and magnitudes of network externalities for the automated

clearing house (ACH) electronicpayments system. We construct an equilibrium model of customer

and bank adoption of ACH. Westructurally estimate the parameters of the model using an indirect

inference procedure and panel data. The parameters are identified from exogenous variation in

the adoption decisions of banks based outside the network and other factors. We find that most

of the impediment to ACH adoption is from large customer fixed costs of adoption. Policies to

provide moderate subsidies to customers and larger subsidies to banks for ACH adoption could

increase welfare significantly.

1. Introduction

Our goal is to estimate the size and importance of network externalities for the automated

clearing house (ACH) banking industry using an equilibrium model of ACH usage and adoption.

ACH is an electronic payment mechanism developed by the U.S. Federal Reserve and used by

banks and customers. It is essentially an electronic alternative to paper checks, typically used for

recurring transactions such as direct deposit paychecks and automated utility bill payments. Since

banks on both sides of a transaction must adopt ACH for an ACH transaction to occur, ACH is a

two-sided market.

As a two-sided market, ACH is characterized by network effects.A bank will be more likely

to adopt ACH as other banks adopt because it will be able to originate more transactions with

ACH, thus justifying the fixed costs of adoption. The importance of the network effect depends

on the incremental profits to the bank from each ACH transaction relative to the fixed cost

of adoption. Because banks most likely cannot compensate each other for ACH adoption, these

network effects are network externalitiesand typically cause underutilization of the network good.

The underutilization is particularly relevant for ACH—inan age when computers and technology

have become prevalent, many more payments are performed with checks than with ACH.

∗University of California Los Angeles; ackerber@econ.ucla.edu.

∗∗ Washington Universityin St. Louis; gowrisankaran@wustl.edu.

We acknowledgefunding from the NET Institute and the National Science Foundation (Grant No. SES-0318170),

and we thank the Editor, two anonymous referees, Steve Berry, Liran Einav, Jinyong Hahn, Fumiko Hayashi, Brian

McManus, Andrea Moro, Joanna Stavins, Klaas van’t Veld, Bill Vogt,and seminar participants at numerous institutions

for helpful comments. We also thank Anita Todd for editorial assistance.

738 Copyright ©2006, RAND.

mss # Ackerberg & Gowrisankaran; art. # 13; RAND Journal of Economics vol. 37(3)

ACKERBERG AND GOWRISANKARAN / 739

Network effects may also exist at the level of the banks’ ACH customers, which include

employers, utility companies, and small businesses. These customers must also bear a fixed cost

of adoption (e.g., updating their disbursement systems) and similarly may be more likely to

adopt ACH if more of the customers with whom they transact also adopt. In contrast to banks,

while it is clear that customers must adopt ACH to originate transactions, the extent to which

a customer receiving an ACH transaction must actively adopt ACH is unknown. Starting direct

deposit payroll, for example, takes very little effort on the part of the employee, the recipient in

this case. This extent to which receiving customers must adopt, along with the magnitudes of

customer and bank fixed costs of adoption and the customer and bank incremental benefits from

ACH transactions, will all affect equilibrium adoption and may play a role in the low observed

rates of adoption.

To understand the causes and extent of the network externalities, we specify a simple static

two-sided market model of ACH technology adoption in local markets. Each market contains

a set of banks, each with a given set of customers. Each customer must make a fixed number

of transactions to other customers using either checks or ACH. While all banks and customers

accept checks, some may not have adopted ACH. Some banks are locally based, while others are

branches of big banks based outside the network. Local banks decide whether to adopt ACH based

on whether the variable profits from ACH transactions conditional on adoption are greater than

the fixed costs of adoption; the decisions of nonlocal banks are made exogenously and are known

to the local banks. Following bank adoption, customers at banks that have adopted ACH choose

whether or not to adopt ACH. We model two types of transactions: one-way transactions, which

are passively accepted by the receiving customers, and two-way transactions, which require the

receiving customers to adopt ACH actively.

The implications of the model depend on parameters that specify bank and customer costs

and benefits, the proportion of two-way transactions, and other details including scales and time

trends. We structurally estimate these parameters by applying an indirect inference estimator (a

variant of the method of simulated moments) to bank-level panel data on ACH adoption and

the number of ACH transactions. The idea of the estimator is to simulate data from the model

(which requires solving for the equilibrium of the model conditional on structural parameters

and unobservables) to find the parameters for which the simulated data most closely match the

observed data.

This work builds on a recent literature on empirically estimating the extent of network

effects for differentindustries (see Goolsbee and Klenow, 2002; Gowrisankaran and Stavins, 2004;

Ohashi, 2003; Park, 2003; and Rysman, 2004a, 2004b, among others). Network externalitiesimply

an interdependence of preferences, leading to simultaneity in equilibrium adoption decisions.

This makes identification of the network externalities potentially difficult. These articles have all

tried to find evidence of network effects by estimating correlations among usage decisions or by

estimating reaction functions with techniques such as instrumental variables. Our work differs

from this literature in that we fully specify an equilibrium model of interactions among banks

and their customers, and we estimate the structural parameters of our model by computing and

matching equilibrium predictions of the model to data.1

Our use of a fully specified structural model has a number of advantages. Relative to exam-

ining correlation among usage decisions (e.g., Gowrisankaran and Stavins, 2004), our structural

model also allows us to estimate the magnitudes of the network effects, rather than just being

able to test for their presence. In addition, we are able to allow for time-varying local shocks that

otherwise might be incorrectly interpreted as network effects. Also, the methods that we develop

here are novel and contribute to the literature on structural estimation of network games with

potential multiple equilibria.

In comparison to articles that structurally estimate reaction functions using linear or log-

1A related literature considers the empirical implications of social-interaction models (see Brock and Durlauf,

2001). One article in this literature (Topa, 2001) also identifies structural parameters from the steady state of the system,

although not in the context of an underlying profit-maximizing model of decision making.

© RAND 2006.