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Applied Financial Economics Letters
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The future of credit unions in the United States:
evidence from quantitative extrapolations
Kostantinos Nikolopoulos a; Michael C. Handrinos b
aDepartment of Economics, University of Peloponnese, Tripolis 22100, Greece
bDepartment of Applied Social Science, Faculty of Arts and Social Sciences,
Lancaster University, Lancaster LA1 4YD, United Kingdom
Online Publication Date: 01 May 2008
To cite this Article: Nikolopoulos, Kostantinos and Handrinos, Michael C. (2008) 'The
future of credit unions in the United States: evidence from quantitative extrapolations
', Applied Financial Economics Letters, 4:3, 177 - 182
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Applied Financial Economics Letters, 2008, 4, 177–182
The future of credit unions in the
United States: evidence from
quantitative extrapolations
y
Kostantinos Nikolopoulos
a,
* and Michael C. Handrinos
b
a
Department of Economics, University of Peloponnese, Tripolis 22100,
Greece
b
Department of Applied Social Science, Faculty of Arts and Social Sciences,
Lancaster University, Lancaster LA1 4YD, United Kingdom
Credit Unions (CUs) are financial co-operatives owned and controlled by
their members; in the United States they operate both on state as well as on
a national level and are in direct competition with retail high-street banks.
In this study we use published data for six key financial figures from ten
states in the US and present short to mid-term extrapolations. An Expert
Forecasting Support System, selecting via a competition among classic
extrapolative techniques, has been employed in order to prepare one-year
as well as five-years ahead forecasts. The results surface significant
statistical evidence of: (a) merging across CUs, and (b) blooming of all key
financial figures.
I. Introduction
Credit Unions (CUs) are financial co-operatives
owned and controlled by their members. In most
countries they serve the ones who cannot get access to
credit from retail banks due to bad credit history or
low credit scoring. In the United States CUs do play a
significant role in the economy; In the state of
California, only one in five residents trust his/her
savings to such institutions. Since those organizations
are in direct competition with retail banks, short- to
mid-term extrapolations are essential in order to
visualize the CUs’ evolution.
Time series methods have been proven very
successful for extrapolating trends (Makridakis
et al., 1998). Exponential Smoothing approaches
have been consistently performed significantly well
in terms of out-of-sample forecasting accuracy
(Makridakis et al., 1982; Makridakis et al., 1993;
Makridakis and Hibon, 2000). In this study we use
published data acquired by permission from Callahan
and Associates Inc. for ten states in USA: Alabama,
Alaska, Arizona, Arkansas, California, Colorado,
Connecticut, Delaware, District of Columbia (DC)
and Florida. Six key figures for each state are
examined: number of CU, number of Members, Total
Assets, Total Shares, Total Loans and Total Capital.
An expert software, selecting via a competition
among classic extrapolative techniques as exponential
smoothing, moving averages, etc., is employed in
order to provide one-year and 5-year ahead forecasts
for the selected times series.
II. Credit Unions
A credit union is a mutual financial co-operative
which provides convenient and accessible savings and
*Corresponding author. E-mail: kostas.nikolopolous@mbs.ac.uk
y
An earlier version of this paper was presented in MIC’06 – Management International Conference 2006, 23–25 November
2006, Portoroz
˘, Slovenia.
Applied Financial Economics Letters ISSN 1744–6546 print/ISSN 1744–6554 online ß2008 Taylor & Francis 177
http://www.tandf.co.uk/journals
DOI: 10.1080/17446540701704349
Downloaded By: [The University of Manchester] At: 22:18 28 April 2008
loans to its members; it is a democratically owned
co-operative society which is built on membership
and on the principles of equity (Albee and Gamage,
1996). It is owned, operated and controlled by the
members, a group of people who share a ‘common
bond’ of, for instance, employment, profession,
locality, religion or ethnic group. It uses members’
savings to provide loans at reasonable rates of
interest. Credit unions rely heavily on volunteer
commitment; they can help foster community spirit
and play an educational role in money management
(National Consumer Council, 1994). Hermann
Schulze-Delitzsch and Friedrich Wilhelm Raiffeisen
created the first true CU in Germany in 1852 and
1864. In 1849, Raiffeisen founded a credit society in
Flammersfeld, but it depended on the charity of
wealthy men for its support. In 1864, Raiffeisen
organized a new credit union along principles still
fundamental today (CUNA, 2006).
Credit Unions’ foundation are small pre-cooperative
groups who federate together to form the ‘union’. This
union is not controlled or owned by nonborrowers. It
challenges conventional ‘banking for the poor’ in
which institutions are built by professionals who by
and large lead a life very different from the poor
borrowers who they seek to serve. Credit unions are an
important mechanism through which people them-
selves can own and control resources (Albee and
Gamage, 1996).
Credit unions are financial co-operatives which are
open to people wishing to save and lend on the basis
of a common bond. There are threads which unite
CUs worldwide, but the details of how any given
union functions is determined locally. Credit unions
most often operate without the bureaucracy and
institutional apparatus of centralized and hierarchical
organizations such as banks. Worldwide there are an
estimated 136 million individual members of CUs in
90 countries, where it is estimated that their impact
reaches an average of four additional household
members for each CU member. Thus, they have an
effective outreach of 680 million persons (WOCCU,
2004).
Key elements of the CU movement, and their
difference from retail banks, include:
.Decentralized development
.Saving is promoted before loans are issued to
members
.A common bond between members is emphasized
.Common ownership by the members is promoted
Various studies have indicated that the vast
majority of people joined their credit union specifi-
cally to gain access to the services it offered,
particularly as they had found it difficult to gain
access to them through retail providers. In particular,
people liked the combination of saving and credit
that both encouraged them to put money aside and
also amplified their borrowing power. Around half,
however, had drawn a distinction between saving and
borrowing at the time they joined their credit union,
and had been attracted primarily by one or the other
(Whyley et al., 2000). It is important to note,
however, that whatever people’s initial motivation
for joining the credit union, the majority made full
use of the services on offer once they had become
members.
Especially in the applied Economics literature, CUs
was a theme that had been revisited many times in the
last three decades starting with the Ryland studies in
the 70s (Taylor, 1972, 1979) and following with a
series of more sporadic studies in the 80s and 90s
(Kebede and Jolly, 2001; Jefferson and Spencer, 1998;
Worthington, 1998; McKillop et al., 1995; Bundt and
Keating, 1988; Kohers and Mullis, 1988; Smith,
1986); in fact in many regions, CUs seem to be an
attractive alternative to high street banks as they
provide a different type of access to credit (Handrinos
et al., 2007) – and as such they attract the interest
of the academia across the globe – UK, USA,
New Zeeland – in the recent years (Glass and
McKillop, 2006; Sibbald and McAlevey, 2003)
III. Credit Unions in the US
The CU industry in the US, since the 1977 change of
legislation of the financial services industry, has been
affected by a number of forces such as innovation,
technology, deregulation and competition. Due to the
complex interplay of these forces various types of
financial intermediaries with similar functions have
been created but, at the same time, a separate and
distinct legal and regulatory structure remains
(Kaushik and Lopez, 1994). The CU industry has
been affected by all these changes as this deregulation
was accompanied by the introduction of a less
restrictive interpretation of the common bond require-
ment for membership, which created new opportu-
nities for growth and merger (Goddard et al., 2002).
This relaxation of the previously restrictive
common bond requirements has inevitably brought
CUs into closer competition with other financial
institutions, especially retail banks. Thus, one could
well argue that they act as mini-banks as they operate
in a more market-oriented approach than they do in
some other parts of the world by offering a range of
products and services that are similar to that of retail
178 K. Nikolopoulos and M. C. Handrinos
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banks. They are a success story in the movement’s
history as they have grown significantly in recent
years. With more than 8880 CUs now serving
86.5 million members the CU industry continues to
attract shareholders/depositors because of its gener-
ally lower cost services and higher returns on savings
(Boldin et al., 1998). This represents a penetration of
the economically active population of over 50%
making CUs a strong player in the US financial
services’ market. Average membership per union
stands at 9741 almost nine and a half times that of
Britain and double that of Ireland (Callahan and
Associates, 2005, 2006). In February 2006, the
average membership number in British CUs was
814 538 in a total number of 779 CUs and
£900 million in assets (Goth et al., 2006).
Nevertheless, despite their small number, the credit
union movement is now the fastest-growing, fully
mutual co-operative sector in Britain (Jones, 1999).
IV. Data and Forecasts
Annual data for five consecutive years from 2001 to
2005 has been collected from the published database
of Callahan and Associates Inc. for the following
10 states in the US:
.Alabama, Alaska, Arizona, Arkansas, California,
Colorado, Connecticut, Delaware, District of
Columbia, Florida
These 10 datasets are the first part of a larger
dataset with data for all 50 states in the US. The
analysis of the whole dataset will be the subject of a
future study where regional differences will also be
investigated. For each of those states six time series
were constructed, analysed and extrapolated for the
following six key figures for each state, respectively:
.Number of Credit Unions, Number of Members,
Total Assets, Total Shares, Total Loans, Total
Capital
In total sixty time series were analysed and a
projection for up to 5 years ahead has been prepared.
For each individual series the best method was
selected via a forecasting competition over available
data (2001-2005) among three exponential smoothing
methods: Simple Exponential Smoothing, Holt
Linear Trend Exponential Smoothing and Damped
Trend Exponential Smoothing (Makridakis et al.,
1998).
Box Jenkins or decomposition methods have not
been tested due to the lack of sufficient number of
observation for each individual series, that is only
five data points in total (Makridakis et al., 1998). In
the majority of the cases Holt – Linear Trend
Exponential Smoothing method is selected by the
expert method.
The forecasts for all ten states (aggregate) are
presented in Table 1. For all states the same pattern
from 2006 to 2010 can be seen:
.The number of CUs will be decreasing annually
with an average of 3.6% for the next 5 years;
.The number of members will be increasing
annually with an average of 1.3% for the next
5 years;
.Total assets will be increasing annually with an
average of 5% for the next 5 years;
.Total shares will be increasing annually with an
average of 4.8% for the next 5 years;
.Total loans will be increasing annually with an
average of 8.4% for the next 5 years;
.Total capital will be increasing annually with an
average of 5.6% for the next 5 years.
The case of California is of great interest as 20%
of the population trust CUs for savings and
access to credit (this stands for more than 10 million
people – that is more than the population of
many European countries). Figure 1 shows the
decrease of CUs in the state of California while
Fig. 2 shows the increase of total capital. Table 2
shows the detailed 5-years ahead forecasts for the
state of California.
Table 1. Annual forecasts for aggregate data from 10 states
Figure\Year 2006 2007 2008 2009 2010
Number of CUs 1163 1123 1085 1043 1004
Number of members 6597.377 6690.281 6783.184 6876.087 6968.991
Total assets 53 263.860 55 883.507 58 503.153 61122.802 63 742.446
Total shares 46 219.316 48 386.023 50 552.729 52719.435 54 886.142
Total loans 34 398.735 37 184.133 39 969.529 42754.927 45 540.324
Total capital 6140.120 6486.214 6832.310 7178.406 7524.501
The future of credit unions in the United States: evidence from quantitative extrapolations 179
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Fig. 2. Total capital for the state of California
Fig. 1. Number of credit unions for the state of California
Table 2. Annual forecasts for the state of California
Figure\Year 2006 2007 2008 2009 2010
Number of CUs 551 535 520 504 489
Number of members 9917.451 10 065.147 10 212.843 10 360.539 10 508.236
Total assets 113 979.768 120 747.944 127 516.120 134 284.304 141 052.480
Total shares 97 498.280 102 882.760 108 267.232 113 651.712 119 036.192
Total loans 78.342.384 87 064.552 95 786.720 104 508.888 113 231.048
Total capital 12 564.713 13 355.891 14 147.069 14 938.247 15 729.425
180 K. Nikolopoulos and M. C. Handrinos
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V. Conclusions and Future Research
Two key conclusions are highlighted from the current
research:
.Merging As the total number of CUs will be
decreasing annually with an average of 3.6%
while all the other key figures are steadily
increasing, we speculate that major merges are
about to happen in the following years.
Therefore, industry consolidation is a trend
that will continue to prevail.
.Blooming of all key financial figures All the key
financial figures increase on an average of more
than 5% per year. Thus there is a strong
potential for CUs in the US in terms of market
penetration and growth.
As these projections have been made using time
series models, the assumption that the environmental
variables will remain constant has to be made. Thus it
is a necessity that the financial environment, competi-
tion, legislation etc., have to remain constant for
the next 5 years. If these variables do not remain
constant then econometric models should be
employed in order to take account for these major
environmental changes that could potentially
happen in the future. Such major changes could be
embedded as dummy variables in an econometric
model.
Future research should focus on:
.The inclusion in the study of all 50 US states;
.The geographical analysis via a Geographic
Information System in order to identify any
regional differences either intra-state or across
states;
.The analysis of data from other countries
in order to see if these US trends can be
generalized on a global scale. An analysis
of the UK CU movement would be of great
value as it appears that it is on a very high
growth rate thus making it a good area for
research;
.An analysis between the different kinds of
CUs (employee-based, community-based etc.)
and the different patterns of their growth and
expansion.
Acknowledgements
The authors would like to thank C. Filson and
S. Patterson from Callahan and Associates, Inc.
(http://www.creditunions.com) for allowing us to use
the organization’s data in our analysis.
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