Prudence and Financial Self-Regulation in Credit Unions in Northern Ireland
John Forker
School of Management
University of Bath
Bath BA2 7AY
[email protected]
01225384618
Anne Marie Ward*
Department of Accounting
Ulster Business School
University of Ulster
Jordanstown
BT37 0QB
[email protected]
028 90366545
*Corresponding author: [email protected]
Acknowledgement: We are grateful for helpful comments received from Donal Mckillop and
when the paper was presented at UUJ and the University of Bath.
1
Prudence and Financial Self-Regulation in Credit Unions in Northern Ireland
Abstract
Credit unions in Northern Ireland are subject to a unique combination of statutory
oversight and self-regulation. This paper investigates the association between
prudential behaviour and the monitoring of accounting ratios by credit union trade
associations. We find that compliance with mandated capital reserve levels is
uniformly high regardless of the existence or extent of self-regulation. However,
after controlling for cross sectional differences in profitability, age, size, growth and
common bond type a positive relation exists between loan book quality and selfregulation. These findings have policy implications for the regulation of credit unions
in Northern Ireland particularly regarding potential regulatory cost savings from
reliance on self-regulation provided by trade associations.
Keywords: Self-regulation, prudence, loan book quality, credit unions, financial
ratios.
JEL classification:
2
Prudence and Financial Self-Regulation in Credit Unions in Northern Ireland
1. Introduction
Credit Unions in Northern Ireland represent a successful non-profit form of financial
institution that is self-supporting and grounded in the community. They have grown
significantly over the past two decades, with membership currently extending to
23.6% of the adult population in Northern Ireland (McKillop, Ward & Wilson, 2010). In
Northern Ireland, credit unions are regulated and supervised by the Registrar for
Companies, Credit unions and Industrial and Provident Societies, part of the
Department of Enterprise, Trade and Investment in Northern Ireland, under the terms
of the Credit Unions (NI) Order 1985 (and subsequent statutory amendments)
(McKillop, et al., 2010). Statutory regulation is restrictive and in particular, to protect
solvency, requires that credit unions maintain a minimum capital reserve level of
10% of total assets. Recommended best practice using financial ratios1 to promote
financial prudence is encouraged by the Registrar and in addition some trade
associations monitor financial ratios to improve loan book quality. In Northern Ireland
there are three trade associations. These are umbrella bodies that provide a voice
for the sector together with a variety of support services for their affiliated credit
union members. Two of the trade associations in Northern Ireland provide deposit
protection insurance and actively monitor their member’s financial activities. The
remainder of the credit union movement are unaffiliated to a trade association and
are subject only to statutory regulation. The variant regulatory environment is unique
to Northern Ireland and provides an opportunity to examine the association between
the existence and extent of self-regulation with mandated capital requirements and
with accounting ratio-based best practice recommendations on financial prudence
and loan book quality provided by the Registrar and the trade associations. This
3
study also contributes to the wider literature on financial institutions and the renewed
interest since the financial crisis on the themes of governance and risk (Wilson, Casu,
Girardone & Molyneux, 2010) and on differential capital adequacy and provisioning in
cooperative banking institutions (Iannotta, 2007).
Self-regulation in non-profit entities typically occurs when an industry level
body is created for the purpose of the industry. Reasons for the creation of such a
body may include resource maximisation, setting and ensuring compliance with
standards and protecting institutional rules and norms (Bies, 2010), The extent of
self-regulation provided by an industry level body is mooted to be associated with the
sophistication of public regulation with self-regulation creating regulation where it
does not exist, compensating for inadequate public regulation or complementing
adequate regulation (Young, 2000). A dearth of research into the effectiveness of
self-regulation and the potential benefits from participating in self-regulatory
organisations, such as trade associations, has been observed (Gugerty, Sidel &
Bies, 2010, p. 1036).
The study also has policy implications. HM Treasury (UK) is currently
undertaking a review of the regulation of credit unions in Northern Ireland (HM
Treasury, 2010). This review recommends that financial regulation should pass to
the Financial Services Authority (FSA). Anticipated benefits are that credit unions in
Northern Ireland are expected to expand their product range and access to the
Financial Services Compensation Scheme (FSCS) and the Financial Ombudsman
Service (FOS). However, the transfer of regulation will potentially increase costs of
compliance and may have adverse consequences for individual credit unions and for
umbrella trade associations. Many small-sized credit unions in Northern Ireland are
wholly dependent on volunteers for their labour requirements and the imposition of
4
compulsory quarterly filing requirements, as is required by the FSA, may lead to
volunteer burnout and credit union closure (McKillop, et al., 2010).
It may also
diminish the support and guidance provided by trade associations on issues relating
to financial management and prudence. A notable gap in the credit union literature
is consideration of the potential of self-regulation to serve as a cost effective
substitute for statutory oversight of financial prudence and loan book quality.
Our
investigation provides estimates of these benefits.
Using a sub-set of PEARLS that measure prudence and loan book quality for
the period 1996 to 2008, we find that compliance with the mandated minimum level
of capital reserves is high and, in general, capital reserve balances are independent
of trade association membership. However, credit unions subject to self-regulation
that actively monitors loan book quality are more prudent in providing for loan losses
relative to the minimum level recommended by the Registrar and have better quality
loan books. The policy implications of these findings are that self-regulation of
financial ratios promotes prudence and loan book quality in the absence of specific
legislation.
The paper is structured as follows. Section two describes, in an international
context, the institutional and regulatory characteristics of the credit union movement
in Northern Ireland and reviews the prior literature. The research design is presented
in section three, the data analysis and findings are presented in section four and
section five concludes.
2. Institutional background
Credit unions are self-help, co-operative, non-profit financial institutions that, in
Northern Ireland, provide simple savings and loans products to their membership2.
5
The credit union movement is a worldwide phenomenon with 49,330 credit unions in
existence in 97 countries. The movement has attracted 184 million members and
has amassed total assets of $1.35 trillion (WOCCU, 2009). Credit unions are
typically governed by a volunteer board of directors that are recruited from within
their membership (Ward & McKillop, 2005b). The membership is typically restricted
to persons who have a common interest, called a ‘common bond’ with each other.
This common bond is typically either employment related, geographical or through
an association. In principle, the common bond reduces information asymmetry
relating to credit making decisions enabling credit unions to provide loans based on
a person’s reputation (Ward & McKillop, 2005a).
The Credit Union (Northern Ireland) Order 1985 allows credit unions to charge up
to a maximum of 1% per month (12.68% effective annual rate) on outstanding loan
balances. Deshmukh, Greenbaum and Thakor (1982), Greinke (2005) and Brown &
Davis (2009) found that Australian credit unions varied the interest rate charged and
paid out on deposit accounts to achieve a profit target and this is the method used to
make changes to capital reserves. This policy does not occur in Northern Ireland
credit unions.
In the period to 2008, 176 of the 177 credit unions charged the
maximum loan interest amount allowed by legislation and credit unions in Northern
Ireland cannot offer deposit accounts. Therefore, their revenue is at its maximum
level with differential profitability being achieved by cost efficiencies.
2.1.
Public regulation
According to Ferguson and McKillop (1997) public regulation across countries
varies from being broadly similar to the regulation for-profit orientated financial
institutions in some countries where the movement is mature (US, Canada,
6
Australia) to being restrictive in other countries where the sector is less developed
(Britain, Northern Ireland, Poland). In the US credit unions are regulated by a
government department, the National Credit Union Administration (NCUA). In Great
Britain, an independent external body, the Financial Services Authority (FSA) has
regulated the credit union movement since 2002 (McKillop, et al., 2010). Though
credit union legislation is more restrictive in Great Britain relative to the US, similar
monitoring activities are prevalent. In both countries - credit unions have to file
quarterly returns and automated financial analysis of these returns is used to
highlight issues that require prompt attention.
In Northern Ireland the Registrar reviews credit union annual returns and audited
financial statements to determine if credit unions are complying with the relevant
legislation and also to determine if they are ‘financially sound’. The Registrar aims to
inspect credit unions every 18 months, though this is not mandatory (Bingham,
2009). In terms of prudence, the registrar has to ensure that credit unions maintain a
capital reserve balance of between 10% and 20% of their total assets. If this is not
the case, as is normal in emerging credit unions, then the legislation requires that the
credit union transfers at least 20% of their yearly surplus to capital reserves before a
dividend distribution can be made.
The Registrar also recommends that credit unions include a specific loan loss
provision to cover the potential loss from non-performing loans.
The guidance
suggests that a minimum provision for loan losses (calculated as 10% of net loans
that are overdue for between 10 and 18 weeks, 20% of net loans that are overdue
for between 19 and 26 weeks, 40% of net loans that are overdue for between 27 and
39 weeks, 60% of net loans that are overdue for between 40 and 52 weeks and
7
100% of net loans that are overdue for over 52 weeks) be made by the credit union.
Any provision in excess of this is a general provision.
2.2.
Self-regulation
Worldwide, trade associations differ in terms of their ethos, size, available
services and monitoring activities. Most trade associations provide guidance on good
financial practices with many promoting the use of ‘PEARLS ratio systems’. The
PEARLS system was created by WOCCU in 1990 and is promoted globally by
WOCCU affiliated trade associations. PEARLS is made up of 44 ratios (with
recommended target, or minimum outcomes) which are aimed at providing
information on six key financial areas including protection of members’ funds (P),
financial strength (E), asset quality (A), performance (return and cost levels) (R),
liquidity (L) and signs of growth (S).
Typically, trade associations do not get involved in monitoring the compliance
of their affiliated members with regulation. For example in the US and in New
Zealand the main trade associations, Credit Union National Association (CUNA) and
the New Zealand Association of Credit Unions do not monitor affiliated credit unions,
but assist credit unions with interpreting regulation and implementing systems that
will ensure that they comply with regulation. In Britain there are four trade
associations: the Association of British Credit Unions Limited (ABCUL), the Scottish
League of Credit Unions (SLCU), ACE Credit Union Services (ACECUS) and UK
Credit Unions (UKCU). None are involved in monitoring their affiliated members’
activities with respect to compliance with regulation or prudence. In Northern Ireland
the situation is different as monitoring is undertaken by two of the four trade
associations. The data panel we investigate represents information on 188 credit
8
unions, 104 are affiliated to the Irish League of Credit Unions (ILCU), 51 to the Ulster
Federation of Credit Unions (UFCU), 13 to the Tyrone Federation of Credit Unions, 6
to UK Credit Unions (UKCU), 3 class themselves as ‘Antigonish’ and the remaining
11 are independent.
Distinct differences in the level and sophistication of self-regulation exists
between the two main trade associations – the ILCU and the UFCU. The ILCU, an
all-Ireland trade association was formed in 1960. It has a dedicated monitoring
department with about 20 members of staff that audit credit unions. Their prudential
monitoring includes site visits and analysis of financial and other information that is
received quarterly from member credit unions. The analysis uses PEARLS; however,
in 1995 the ILCU has adapted the benchmark ratios to suit the movement in Ireland.
The ILCU use 26 of WOCCU’s suggested 44 ratios, though only 22 of these are
relevant for credit unions in Northern Ireland - due to the more restrictive legislation
within this jurisdiction limiting the investment and borrowing capabilities of credit
unions.
The PEARLS system is programmed to highlight credit unions that do not
meet minimum predefined target ratios. The ILCU provides feedback to its member
credit unions each quarter, highlighting areas that require attention.
In some
instances adverse financial ratios may trigger a field visit. Regardless, field visits
happen routinely (at least every two years) though will also take place if there is
concern about the credit union or if a credit union requires technical assistance. In
2009 field officers made 257 visits to credit unions across Ireland (Hewson, 2009).
The UFCU was formed in 1995, though many of the credit unions had been in
existence previously and were affiliated to the National Federation of Credit Unions,
a British trade association. The UFCU does not monitor the financial strength of its
9
member credit unions; however, it established a deposit insurance subsidiary and
this subsidiary monitors the member credit unions that pay deposit protection
insurance. The company has one part-time employee and is governed by the board
of the UFCU. Credit unions have to provide audited annual accounts to the deposit
insurance company. These are reviewed by the company to ensure compliance with
legislation and the Registrar’s recommendations as to the level of the provision for
loan losses. The company aims to undertake a site visit to review the financial
procedures of the credit unions that take deposit protection insurance every 18
months.
The savings protection subsidiary can remove old and appoint new
directors, where it is deemed that credit union is being mismanaged (Hannafin &
McKillop, 2007).
The Tyrone Federation of Credit Unions and UKCU do not provide any form of
self-regulation. The Antigonish credit unions also do not experience any form of selfregulation but their distinct moral ethos and compliant behaviour sets them apart
from the credit unions in the ‘independent’ category - educating members about
financial awareness and appropriate financial conduct is a core ethos (Coady, 1939).
The remaining credit unions are not affiliated to any trade association and operate
only under public supervision.
2.3.
Prior literature
Bies (2010 p. 1062) suggests that self-regulation in non-profit entities is ‘an
accountability response structured along a continuum of regulatory governance’. A
key feature of self-regulation is the formation by a central industry-level organisation
of best practice rules for operational conduct and ethical standards (Gunningham &
Rees, 1997). Bies (2010) identifies three types of self-regulation that are defined
10
according to the purpose that the self-regulation serves. These are complianceoriented self-regulation, adaptive self-regulation and professional self-regulation.
These are clearly defined by Bies in terms of their theoretical premise, source and
type of regulation system, motive of regulation, non-profit stance, basis for
participation and primary purpose. When we map the type of self-regulation being
provided by the two main trade associations in Northern Ireland across all the
predictors, we find overlap. None of the trade associations can be classified as
reflecting a single type of self-regulation. However, the focus of our study is on
whether the level of self-regulation as measured by the level and sophistication of
monitoring experienced by credit unions affects their mandated compliance
behaviour, prudence and loan book quality. To this end, we classify the trade
associations using Bies’ typology according to theoretical premise and type of selfregulatory monitoring system.
In compliance-oriented self-regulation the self-regulatory body creates
standards and procedures to identify and monitor their members’ behaviour and to
hold them to account for their actions. This form of self-regulation is contractuallybased, consistent with principal-agent relationships and is reflective of the monitoring
role adopted by the ILCU. The regulatory approach known as ‘adaptive selfregulation’ can be explained using resource dependence theory. It is assumed that
organisations seek resources that are necessary for their survival either as a
collective body (buying power) or from the networks created through the industry
level self-regulatory body (Pfeffer & Salancik, 1978). This form of self-regulation is
particularly evident when the UFCU’s monitoring activities are examined. Public
regulation was well established when the UFCU was formed, however deposit
protection insurance was not available. The UFCU established this resource for its
11
members. Monitoring activity arose to supplement the gap in public provision in
response to the perceived increase in risk associated with introducing deposit
protection insurance. Finally, professional self-regulation applies to both the ILCU
and UFCU and is associated with promoting or protecting the norms and values of a
particular non-profit sector (Bias, 2010).
Research on the impact of mandatory public regulation on the performance
and prudential behaviour (capital reserve levels) of banks is abundant (Repullo,
2004; Carletti, 2008; Inderst & Mueller, 2008). Some of this research has concluded
that a mandatory requirement to hold more capital does promote prudential
behaviour, typically by increasing the level of capital held (Keeley 1988; Berger,
1995; Jacques & Nigro, 1997; Ediz, Michael & Perraudin, 1998a, b; Aggarwal &
Jacques, 2001; Peura & Keppo, 2006).
Prior literature on capital reserve levels in credit unions suggests there is an
association between regulation and capital reserves levels with credit unions being
overcapitalised as a result (Jackson, 2007). A number of empirical studies have
considered the response of credit unions when minimum regulatory capital reserve
levels are introduced or strengthened (Deshmukh et al., 1982; Greinke, 2005; Hillier,
Hodgson, Stevenson-Clarke & Lhaopadchan, 2008; Brown & Davis, 2009; Goddard,
McKillop & Wilson, 2010). Though these studies do not examine self-regulation, all
found that credit unions alter their behaviour as a direct consequence of mandated
regulation.
Empirical research has yet to investigate the impact of different types of selfregulation on an entity’s prudential behaviour. Bushman and Piotroski (2006) in a
study covering 38 countries over the period 1992 to 2001, found evidence to suggest
that public regulation, measured as the sophistication of a country’s institutional
12
structure in respect of legal and political institutions, affects management behaviour
in for-profit entities with strong regulation leading to more conservative accounting
and reporting practices (Watts, 2003). To our knowledge, no previous studies have
examined the impact of the existence or extent of self-regulation on the prudential
behaviour of credit unions.
3. Research design
The credit union sector in Northern Ireland provides a unique opportunity to
investigate the association between the existence and extent of self-regulation and
mandated (legislative) and recommended (registrar and self-regulation) measures of
prudence and loan book quality. Drawing on the typology proposed by Bies (2010),
the existence and extent of self-regulation is proxied by trade association
membership.
In devising our empirical tests we classify regulation into the mandated level
of capital reserves and best practice guidance in the form of the Registrar’s
recommended level of loan loss provision and a further two PEARL ratios monitored
by the ILCU. These are loan losses written off less loan loss write backs in the
income statement and level of accumulated provision for loan losses in the
statement of financial position3. Prior literature finds that credit union behaviour is
associated with age, size, growth, performance (return on assets), common bond
type and year effects (Goddard & Wilson, 2005; Ward & McKillop, 2005a, b, c;
Greinke, 2005; Brown & Davis, 2009). Studies that examine the objective function of
credit unions have also suggested that capital reserve levels are associated with
credit union growth (Smith, 1988; Spencer, 1996). We control for these effects in our
model specifications.
13
Theory predicts that compliance will be stronger where self-regulation is
compliance-oriented (ILCU) compared to where the self-regulation is adaptive-based
(UFCU) and where there is no monitoring of financial prudence (Tyrone Federation,
UKCU or none). For the control variables the following relationships are predicted.
Older credit unions are more likely to comply - many emerging credit unions are loss
making in the initial years, or elect to allow their small surpluses to accumulate in an
unappropriated reserve for early years before starting to make transfers to general
reserves. More profitable credit unions are more likely to comply; credit unions with
bigger surpluses have a larger pool of funds available to enable them to meet the
competing demands on their surpluses (retentions, dividend and loan interest rebate
demands). A negative association is predicted with growth. Mandated capital
reserves are calculated using year-end total assets, whereas surpluses from the
utilisation of these assets, from which transfers to reserves are made, are generated
continuously throughout the year. Thus credit unions with high growth will have to
transfer a higher proportion of their yearly surplus, to maintain their capital reserve
levels, relative to a credit union with low growth.
Credit union size is measured using end of period total assets (also used by
Barron, West and Hannon, 1994; Goddard et al., 2008, 2010; Ward and McKillop,
2005a, b). Brown and Davis (2009) found a negative association between credit
union size and movements in mandated capital reserve levels in Australian credit
unions, hence, smaller credit unions are more likely to comply.
Expressed in the form of null hypotheses our first prediction is in respect of
compliance across credit union trade association membership with the mandated
requirements in respect of capital reserve levels:
14
H01 Ceteris paribus, there is no difference in the association between the
existence and extent of self-regulation and compliance with mandated levels
of capital reserves.
We test this hypothesis by applying univariate analysis and panel data
estimation techniques to control for unobserved effects that vary with time but are
constant across credit unions and those that are constant across time but vary
across credit unions. The hypothesis is tested by using the following multivariate
PROBIT model:
8
11
i 5
i 9
y*it  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
2008
  YEAR  u
l
i
l 1996
*
Where yi is coded 0 where Capital Reserves <= 10% and transfers to
reserves are < 20% of surpluses (non-compliers), otherwise 1 (compliers); lAGE =
log of age; lSIZE = log of total assetst; GROW = (Total Assetst-Total Assets t-1)/Total
Assetst-1; ROA = Surplus (Deficit)t /Total assetst; TAC (trade association type) is a set
of three dummy variables coded 1 for membership of ILCU; UFCU, Antigonish and
Other respectively; zero otherwise; CBOND (common bond type) is a set of three
dummy variables coded 1 for residential, employment and associational common
bond membership respectively; zero otherwise and YEAR is a set of dummies for the
13 years in the sample.
Continuous measures of prudence and loan book quality are utilised to further
investigate the contribution of self-regulation.
Credit unions that are subject to
compliance-oriented self-regulation (ILCU) are expected to exhibit stronger
adherence to recommended guidance in respect of levels of prudence and to have
better quality loan books compared to credit unions that are subject to adaptive-
15
it
based self-regulation (UFCU) and where there is no monitoring (Tyrone, UKCU or
Independent).
Age and profitability are expected to be positively associated with reserve
accumulation. Credit unions are required to transfer a minimum of 20% of yearly
surpluses to capital reserves until the minimum 10% threshold is achieved - young
credit unions require time to build up to such a level. Related to this, young credit
unions are under pressure to meet their statutory requirement in respect of capital
reserves, therefore are less likely to create prudential provisions. As reserves are
built from profits, more profitable credit unions are predicted to have higher levels of
reserves.
A negative association is expected between size, growth and reserve
accumulation. Whereas sufficient reserves are required to ensure that depositors’
funds are protected, that liquidity is maintained and funds are available for the
purchase of non-current assets in the future (Davis, 2001; Brown & Davis, 2009); it is
considered that holding reserves in excess of the minimum required level is
detrimental to current members (Hart & Moore, 1996) as it promotes free riding
activity and benefits future members (Emmons & Mueller, 1998). Indeed, Taylor
(1971) suggests that even the minimum 10% capital reserve level is too high and
damages member wealth.
A negative association is also expected between loan book quality and growth
as more conservative lending practices will result in lower growth, higher quality loan
balances and less write-offs.
Finally, credit unions with a tight common bond
(associational) are predicted to have better quality loan books relative to credit
unions with weaker common bonds (employment and residential) (Brown & Davis,
2009).
16
Expressed in the form of null hypothesis our second prediction is in respect of
the association between the existence and extent of self-regulation and prudence
and loan book quality.
H02 Ceteris paribus, there is no difference in the association between the
existence and extent of self-regulation and prudence and loan book quality.
Prudence and loan book quality is measured by four PEARLS 4 indicators.
Prudence is measured first, by the level of capital reserves and second by the
difference between the actual loan loss provision and the level recommended by the
Registrar.
Loan book quality is measured by net bad debt write offs and the
accumulated provision for loan losses.
The hypotheses are tested using OLS and panel regression analysis, where
standard errors are adjusted for heteroscedasticity and clustering within individual
credit unions:
Model 1
8
11
i 5
i 9
l 1996
8
11
2008
i 5
i 9
Cap Re sit  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
2008
  YEAR  u
l
i
it
Model 2
Abnprovit  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
  YEAR  u
l
i
l 1996
Model 3
8
11
i 5
i 9
Bdwoit  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
Model 4
17
2008
  YEAR  u
l
l 1996
i
it
it
8
11
i 5
i 9
Tbdprovit  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
2008
  YEAR  u
l
l 1996
Where the independent variables are Cap Re sit = Capital reservest/Total
assetst in Model 1; Abnprov = the abnormal loan loss provision measured as the
difference between actual and the Registrar’s recommended loan loss provision
scaled by total loans; Bdwo = (Loan book write-offs less loan book write-backs)t/total
loanst) and Tbdprov = provision for loan lossest/gross year-end loanst.
4. Data and findings
In Northern Ireland, in 2008, 176 credit unions filed returns disclosing an overall
membership of 431,303 with net assets of £968 million. This represents a
penetration rate of 23.6% of the relevant population (McKillop et al., 2010). The
database for this study was created from 2,276 annual returns from 188 credit
unions submitted to the Registrar in Northern Ireland over the period 1996 to 2008.
Included are credit unions which started up in the period (33) and those that ceased
operations (6)5.
4.1.
The dependent variables
Summary statistics on capital reserve levels (CapRes) for the population at the end
of each year are provided in Table 1 Panel A. The mean level of capital reserves in
1996 was 7.95% in 1996 and rose steadily each year to 11.52% in 2008. New
entrants typically do not transfer amounts to capital reserves in the earliest years of
their existence, hence the zero minimum balances.
18
i
it
INSERT TABLE 1 HERE
Financial prudence (Abnprov) is reported in Panel B6. Over the period of the
study the mean excess provision rises from 0.472% of the loan book in 1996 to
1.13% in 2008. The standard deviation for the whole period is 1.564 and the values
range from a minimum of -16.084 to a maximum of 15.87.
Loan book quality is tested using two ratios, a Net Write Off percentage (Bdwo)
(Panel C) and the accumulated loan loss provision (Tpdprov) (Panel D). The mean
net write-off for the period is 0.433%, rising from 0.295% in 1996 to 1.106% in 2008.
The range of values lies between a net write-back of loan losses of 32.65% to a net
write-off of 104.68%7.
4.2.
The explanatory variables
The overall return on assets for the 13 year period is 4.224% (Table 1, Panel E).
The yearly means ranged from a high of 5.04% in 1998 to a low of 3.588% in 2008.
Negative returns are recorded in most years with the lowest return on assets
reported in 2008 (-18.86%) and the highest (19.297) in 2002. Extreme positive and
negative returns typically occur in the founding years, or when credit unions are
running their operations down.
Size, reported in Table 1 Panel F, The size of credit unions within the population
varied greatly over the study period, with the smallest observation being total assets
of £0.007m in 1999 and the largest being £77.3m in 2008. The mean size for the
whole population is £3.48m. When total assets are analysed yearly a steady growth
pattern emerges. The mean asset size in 1996 is £1.661, growing to £5.493m by
2008.
19
Growth: On average credit unions grew at the rate of 15.91% per year over the
period 1996 to 2008 (Table 1, Panel G) though a distinct pattern is evident with
stronger growth in the earlier years (27.4% in 1996) falling progressively over the
period (5.7% in 2008). Credit union growth is restricted by their common bond. The
diminishing growth rates reflect the strong growth that is achieved by new entrants to
the sector who have growth capacity within their common bonds.
Age: The mean age of the panel is 22.81 years (Table 2).
The high standard
deviation (13.06) combined with the age range (One year old to 48 years old)
indicates much variation in this variable.
INSERT TABLE 2 HERE
Trade associations, not only differ in terms of the level of self-regulation that they
undertake, they also differ in respect of their underlying philosophy in respect of how
best to maximise membership benefits, in their age and by common bond type. As
reported in Table 2 this results in a distinctly different credit union membership
profile.
Examination of Table 2 reveals the majority of credit unions in Northern Ireland
have a common bond of residence (75%) with only two credit unions having a common bond
of employment.
Credit unions affiliated to the ILCU have the widest common bonds
(98% are registered as having a residential common bond).
They are also the
oldest, the largest, the most profitable and the most prudent - average reserves
exceed the regulatory minimum 10% level (mean value of 11.11%). ILCU registered
credit unions have the largest abnormal mean provision for loan losses (0.92% of
yearend loans outstanding). They write off on average 0.43% of their loan book (net)
per year.
When the abnormal provision is considered in conjunction with the
20
provision for loan losses, it can be concluded that ILCU credit unions have the least
risky and best quality loan book (lowest overall provision (2.74%), with the lowest
specific proportion and the highest general portion when compared to the other
categories in the sample.
Credit unions that are affiliated to the UFCU are the smallest, youngest and
have experienced high levels of growth (mean of 20.89%) in the sample period. A
high portion of UFCU affiliated credit unions are registered as having an
associational common bond (55%). They have lower reported capital reserve
balances (mean value is 7.9%) and lower abnormal provisions for loan losses
(0.31%) relative to the ILCU, though they have the largest reported provisions for
doubtful debts (3.85%). Their net loan write-offs are 0.25% and they report the
lowest mean surpluses (3.37%).
There are three Antigonish credit unions. Two use a residential common
bond, the other is associational. They have been in existence for 25.57 years, have
the lowest mean growth per year (7.25%) and have average total assets for the
sample period of £1.797m. They generate a return on assets of 4.46% and typically
have very low net write-offs (0.09%). In terms of prudence, they have the highest
capital balances (mean value of 12.42%) and report the lowest abnormal provision
for loan losses (0.05%). This means that most of their reported provision for loan
losses (3.35%) is specific in nature. There were no breaches of the regulatory capital
reserve requirements in any of the years examined.
Credit unions that make up the ‘Other’ category are on average 10.11 years in
existence and have the highest mean yearly growth (23.8%). They have mean total
assets of £1.355m and are typically profitable. Two thirds of the ‘Other’ category is
registered as having a common bond of association, 32% are residential and one is
21
employment based. They have the lowest reserve levels (average of 7.32%), the
highest write-offs (0.81%), an abnormal provision of 0.3% and a provision for loan
losses of 3.78%.
4.
Compliance
The dataset was interrogated to identify non-compliant observations. The
results are provided in Table 3. Observations with capital reserve levels of less than
10% that had not transferred a minimum of 20% of their yearly surplus to capital
reserves were coded as being non-compliant. The rate of non-compliance across all
credit unions was 7.9% (179 observations). The rate of non-compliance was higher
for UFCU affiliated credit unions (15.3%) and lowest for Antigonish credit unions with
100% compliance.
INSERT TABLE 4 HERE
Compliance data is also analysed by size, age, profitability and growth in
Table 4, Panel B). Compliers are on average larger, older and more profitable and
have lower rates of growth.
Pearson correlation coefficients, at the 1% level of
significance, for the independent variables and the four continuous dependent
variables respectively are reported in Table 4, Panels A to D. Prudence, measured
by levels of general reserves and abnormal bad debt provision rspectively, is
positively related at the 1% level of significance to size (0.395; 0.147), age (0.587;
0.223) and profitability (0.216; 0.080). The negative relationship between prudence
and growth (0.462; 0.151) however, indicates that the pursuit of growth can pose a
threat to capital adequacy in credit unions. The loan book correlations with size, age
and profitability are generally weaker. Size is negatively related to bad debts written
22
off (0.091) and profitability is negatively related to both bad debts written off (0.091)
and total provision for bad debts (0.119).
Loan book quality is, however as
negatively related to growth and to prudence (0.360; 0.361).
The correlations
between the independent variables are generally positive, except for the negative
correlations between growth, age and size. With the exception of the correlation
between age and size (0.812) these are also less than 0.38 and are not considered
to be problematic for multivariate analysis. The high positive association between
age and size is expected, even though the rate of increase declines with age8.
4.4
Multivariate analysis
The results of a random effects probit regression investigating compliance with
legislation in respect of capital reserves is provided in Table 5. The model excludes
37 observations for the Antigonish credit unions all of which complied.
INSERT TABLE 5 HERE
The coefficients on the control variables for age (0.770), size (-0.346), profitability
(0.236) and growth (-0.971) have the expected signs and are significant at 5%.
UFCU affiliated credit unions and Others have a lower likelihood of compliance
relative to ILCU affiliated credit unions, however, the difference is only significant at
the 10% level for UFCU affiliated credit unions. The finding of a significantly higher
probability of compliance for ILCU affiliated credit unions supports the prediction that
pro-active self-regulation of prudence has a positive incremental effect on
compliance with mandated capital reserve requirements.
23
To utilise the more precise measures of prudence and loan book quality
provided by continuous measures we proceed in Table 6 to apply regression
analysis. We first control for factors that differ across individual credit unions and
across time periods for all credit unions by estimating separate two-way fixed effects
regressions to explain the cross sectional variation in prudence and loan book quality
with respect to the control variables.
INSERT TABLE 6 HERE
There is no variation in trade association affiliation in Northern Ireland, thus the fixed
effects regression cannot test for differences in prudence and loan book quality
across trade association membership. We substitute continuous measures for the
dependent variables given by level of capital reserves ( Cap Re s , Model 1), the level
of abnormal loan loss provisions ( Abnprov ,Model 2), the net loan loss write-offs
(Bdwo, Model 3) and the level of the year end provision for loan losses (Tbdprov,
Model 4). The level of explanation is highest for mandated capital reserve levels
reported in Model 1 (R2 = 0.531) and the coefficients for age, size, profitability and
growth have the predicted signs and are significant at the 1% level. Apart from
1997, which is insignificantly different from 1996 base year, year effects
(untabulated) show a steady increase in the level of capital reserves, consistent with
the growing maturity of the credit union movement in Northern Ireland. The lowest
level of explanation, for abnormal provision, is reported for Model 2 (R2 = 0.042).
The control variables provide little explanation for the variation in abnormal
provisions where only size has the expected sign and is significant at the 5% level.
Profitability is negatively associated with abnormal provisioning at the 5% level, and
may reflect the possession of inside information by management on loan book
24
quality.
Year effects show a steady increase in the level of abnormal reserves
(untabulated). Clearly, factors other than size and profitability influence decisions
about abnormal provisions, but investigation of these is beyond the scope of this
paper and is left for further research.
Models 3 and 4 investigate loan book quality. The levels of explanation for
both models is satisfactory (R2s = 0.235 and 0.301 respectively). In Model 3, size,
growth and profitability have the predicated signs at the 1% level, The sign on
profitability differs from Model 1, though is consistent with Model 2.This may suggest
that credit unions with larger abnormal provisions have lower quality loan books
which generate less income. . Similar results are reported for accumulated loan loss
provisions in Model 4 where all control variables have the expected signs and are
significant at the 1% level.
To estimate if trade association membership impacts on prudence and loan
book quality measured using continuous dependent variables, we include the set of
trade association dummy variables. The Hausman test revealed that the results of
the Random effects regression may not be consistent as the individual credit union
effects were found to be correlated with the regressors. Therefore, as the next best
alternative, we carefully interpret OLS results where the standard errors are adjusted
for the effect of clustering within individual credit unions9. The results for the four
models are reported in Table 7.
INSERT TABLE 7 HERE
Model 1 provides a satisfactory level of explanation for the cross sectional
variation of capital reserves (R2 = 0.415) and the sign and significance of the control
variables are similar to those reported in the fixed effects regression. There is no
25
significant difference in the level of capital reserves across trade associations which
can be attributed to the effectiveness of the mandated requirement in delivering a
uniform level of prudence.
In Model 2 the level of abnormal provision differs significantly across trade
associations. Antigonish affiliated credit unions and unregulated credit unions (the
Other category) have significantly lower levels of abnormal provision relative to ILCU
affiliated credit unions.
Tests of differences across trade associations in loan book quality are
reported in Models 3 and 4. Higher levels of loan loss write offs in the income
statement reflect poorer loan book quality. Only ‘Other’ credit unions have lower
loan book quality (0.788, p = 0.006) relative to ILCU affiliated credit union which may
be attributed to the absence of self- regulation. In Model 4 we investigate the cross
sectional variation in accumulated loan loss provision, higher levels of which are
taken to indicate higher managerial expectation of loan losses. UFCU membership
(1.604, p = 0.032; 95% confidence interval: 0.139 to 3.06) and ‘Other’ (1.917, p =
0.011; 95% confidence interval: 0.449 to 3.338) have loan book quality that is
significantly lower than that for ILCU affiliated credit unions.
To summarise, a low incidence of non-compliance with mandated levels of
financial prudence targets is evident from regression analysis. When loan book
quality is examined, support emerges for the beneficial impact of self-regulation as
credit unions that are subject to lower levels of monitoring, or no self-regulation have
higher write offs and higher provisions for loan losses
5. Conclusion
26
Credit unions in Northern Ireland are currently subject to a unique mix of statutory
oversight and self-regulation. Compared to other jurisdictions legislation is strict and
in particular a minimum level of capital reserves is required to be held. Different
types of self-regulation are also prevalent in Northern Ireland. The founding trade
association, the ILCU, adopts a compliance-oriented role. They issue good practice
guidance to encourage prudential behaviour and compliance with statutory oversight
in the form of recommended ratio levels (PEARLS ratios) to their affiliated members
and monitor compliance with that guidance quarterly. The UFCU adopt an adaptive
style self-regulation through their deposit protection provider. These systems are
less sophisticated as those in operation in the ILCU. Credit unions that are not
affiliated to either the ILCU or the UFCU are not subject to any form of selfregulation. Consistent with Young (2000), trade association self-regulation in
Northern Ireland has played an important role in the historical development of the
regulatory framework for credit unions over the past 50 years, providing regulation
when public oversight was in its infancy, and supplementing legislation when it was
considered that there was insufficient financial guidance. However, the public
regulation of credit unions in Northern Ireland has remained static since the
implementation of the Credit Union (Northern Ireland) Order (1985)10. The current
legislation is restrictive and is considered to hinder the development of the sector in
Northern Ireland (HM Treasury, 2010) and as a consequence the UK Treasury set
up a taskforce to review public regulation and oversight.
One outcome of the review is that the UK Treasury is extending FSA
oversight to credit unions in Northern Ireland. This will enable credit unions in
Northern Ireland to provide more financial products and to have access to the FSCS.
This is a positive development as the rate of growth, measured as the change in total
27
assets, diminished steadily over the 13 year period. In addition, having access to the
FSCS will provide a safety net for those credit unions that do not have access to
deposit protection insurance.
In terms of the effectiveness of the current regulatory framework, we find little
incidence of non-compliance with statutory requirements, with 92.1% of all
observations complying with the statutory requirements. Investigation of the
difference between compliers and the small number of non-compliers identifies that
UFCU affiliated credit unions with adaptive style oversight were less likely to comply
relative to ILCU affiliated credit unions with compliance-based oversight and ‘others’
with no oversight.
An examination of prudence and loan book quality identifies that credit unions
that are subject to compliance-based self-regulatory monitoring of financial ratios
(the ILCU) have better quality loan books, with significantly lower net loan write offs
and provisions for loan losses. The implication of these findings for regulatory policy
is that, in the case of credit unions in Northern Ireland, there is an argument for
monitoring of PEARLS by trade associations and, specifically, for the recognition of
the main trade association, the ILCU, as a recognised supervisory body, that can
regulate their own members and report to the public regulator and for the adoption of
similar oversight by other trade associations. The potential regulatory savings will
reduce the burden of unnecessary monitoring on credit unions in Northern Ireland
and may provide scope for an improvement in monitoring activity of the ILCU, for
example, as it adapts in light of the transfer of regulation to the FSA. If the ILCU’s
monitoring role is ignored, this may weaken the trade associations’ standing and
cause credit unions to question the benefit being received from their affiliation fees.
If, as a result, the trade association has to downsize and curtail their activities, then a
28
powerful lobbying force for the sector will diminish, leaving credit unions at risk of
becoming Government policy tools, not independent co-operative financial
institutions that are strong enough to shape their own destiny.
Notes
1
Since 1990, the World Council of Credit Unions. has been promoting the use of a set of financial
ratios known as "PEARLS" to facilitate supervisory control of credit unions. PEARLS was
implemented by the Irish League of Credit Unions in 1985.
2
In other some other countries credit unions are much more sophisticated and can provide similar
services to banking institutions, for example in the US, Canada and Australia several credit unions
have converted to banks. (see Heinrich & Kashian, R. (2008) for a discussion of US demutualization
activity and Davis, K., (2007, 2005) for a discussion of Australian demutualization activity. The credit
union sector in these countries faces higher risks, relative to other countries that have not
experienced deregulation).
3
These three ratios are monitored by the ILCU using the PEARLS system.
4
Five of the 22 possible PEARLS ratios are included in our investigation, though we only report on
four as the results for one (total reserves to total assets) are similar to those reported for capital
reserve levels. The ratios that are not investigated include those that measure signs of growth (6),
the proportion of members who borrow (1), the proportion of assets on loan to members (1); rates of
return and cost management (6), the utilisation of assets (1). Finally two are not included in the
analysis due to data restrictions (one is on loan rescheduling the other a measure of solvency).
5
177 credit unions are currently registered, though the annual returns were only available for 176 in
2008.
6
In 130 instances data was not available in respect of the regulators recommended provision level,
resulting in a panel of 2,146 observations.
7
This large write-off occurred in 2008 in a credit union which had voluntarily decided to close. It was
no longer issuing loans. Its members were paying back their debts and were netting their share
accounts against their loan account resulting in a very low yearend loan balance and a
correspondingly high write off relative to the yearend loan balance.
8
We also test the robustness of the results by substituting lagged size for size. In addition, we re-ran
each of the multivariate models with size only, age only and then together (as reported). We find no
difference in the signs and significance of the results; therefore we only report the results for the latter
model.
9
In addition we estimated a between effects model and find that the reported signs and coefficients
are similar to those reported in OLS regression with standard errors adjusted for clustering.
29
10The
Deregulation (Northern Ireland) Order 1997; the Credit Union Deposits and Loans Order
(Northern Ireland), 2006 and the Credit Union (Limit on Membership) Order (Northern Ireland) 2006
relaxed the limits imposed in the 1985 order in respect of loan amounts, share capital holdings and
number of members, however, there were no other changes.
30
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38
Table 1
Descriptive statistics for Northern Ireland credit unions 1996 - 2008
Panel A: Capital reserves ( Cap Re s )
Year
Number
Mean (%)
Sd (%)
164
1996
7.951
3.853
168
1997
8.138
3.711
164
1998
8.693
3.641
177
1999
8.575
3.994
178
2000
9.486
3.865
181
2001
9.617
3.867
175
2002
9.707
3.827
174
2003
10.065
3.514
183
2004
10.212
3.558
176
2005
10.552
3.504
181
2006
11.087
3.571
179
2007
11.329
3.434
176
2008
11.517
3.404
2,276
Total
9.790
3.836
Capital reserves = general reservest/total assetst
Median (%)
8.564
8.518
9.252
9.403
10.072
10.059
10.016
10.093
10.186
10.335
10.607
10.686
10.785
10.079
Minimum (%)
Maximum (%)
0.000
0.000
0.169
0.000
0.000
0.000
0.000
1.421
0.193
0.677
1.182
1.822
2.635
0
19.528
17.870
16.602
18.433
22.200
23.098
22.952
22.804
21.909
21.391
20.805
20.746
24.447
24.447
Panel B: Deviation between actual and recommended provision for loan losses scaled by
total loans ( Abnprov )
Year
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Total
Number
150
156
148
167
170
174
166
167
167
167
173
173
168
2,146
Mean (%)
0.472
0.493
0.515
0.473
0.549
0.567
0.583
0.708
0.786
0.656
0.869
0.991
1.130
0.681
Sd (%)
Median (%)
1.071
1.028
1.000
1.017
1.185
0.901
1.159
1.202
1.471
1.173
1.943
2.161
3.120
1.564
0.001
0.002
0.013
0.052
0.111
0.152
0.160
0.295
0.270
0.210
0.341
0.546
0.550
0.172
Minimum (%)
Maximum (%)
-2.204
-0.921
-0.980
-4.903
-1.176
-0.327
-2.734
-1.912
-4.417
-2.852
-6.655
-10.169
-16.084
-16.084
Abnprov = (Actual provision - Regulators recommended provision)/Total loanst x 100
39
9.034
8.541
8.119
7.723
10.616
7.514
8.398
7.061
11.362
6.739
13.951
15.872
15.584
15.872
Panel C: Net Write Off Percentage (Bdwo)
Year
Number
Mean (%)
Sd (%)
161
0.295
0.720
1996
167
0.287
0.854
1997
163
0.354
0.972
1998
176
0.404
1.083
1999
177
0.343
0.746
2000
179
0.421
1.173
2001
171
0.455
1.134
2002
174
0.407
1.125
2003
183
0.408
1.421
2004
176
0.177
2.577
2005
181
0.470
0.950
2006
179
0.480
1.468
2007
176
1.106
7.967
2008
2,263
0.433
2.543
Total
Median (%)
0.000
0.000
0.000
0.006
0.011
0.004
0.163
0.072
0.049
0.129
0.107
0.157
0.226
0.054
Minimum (%)
Maximum (%)
-0.735
-0.952
-0.613
-0.552
-1.389
-2.075
-5.318
-3.724
-6.466
-32.655
-1.952
-6.183
-3.406
-32.655
5.015
8.444
10.772
10.614
4.819
10.043
6.729
11.623
11.139
2.533
6.933
9.887
104.682
104.682
Bad debts written off = Loan loss write offst less loan loss recoveriest/total loanst x 100
Panel D: Provision for loan losses (Tbdprov)
Year
Number
Mean (%)
Sd (%)
Median (%)
Minimum (%)
164
2.131
2.782
1.635
0
1996
168
2.353
3.372
1.583
0
1997
164
2.252
2.971
1.735
0
1998
177
2.417
2.914
1.865
0
1999
178
2.668
3.198
2.024
0
2000
181
2.928
3.170
2.072
0
2001
175
2.740
2.607
1.884
0
2002
174
3.288
3.152
2.367
0
2003
183
3.424
3.214
2.465
0
2004
176
3.769
3.198
2.757
0
2005
181
4.046
4.150
2.845
0
2006
179
4.029
3.979
2.906
0
2007
176
5.079
6.818
3.587
0
2008
2,276
3.179
3.747
2.197
0
Total
Loan loss provision = Provision for loan lossest/total loanst x 100
40
Maximum (%)
29.562
35.752
33.449
32.311
34.202
26.773
14.487
18.188
17.972
15.789
32.902
34.122
73.238
73.238
Panel E: Return on Assets
Year
Number
Mean (%)
Sd (%)
Median (%)
1996
164
4.294
2.376
1997
168
4.529
2.041
1998
164
5.047
1.487
1999
177
4.619
1.808
2000
178
4.777
1.592
2001
181
4.334
2.129
2002
175
4.110
1.924
2003
174
3.961
1.462
2004
183
3.856
1.440
2005
176
4.084
1.283
2006
181
3.785
1.686
2007
179
4.021
1.569
2008
176
3.588
2.325
Total
2,276
4.224
1.847
Return on Assets = Surplus (Deficit) /Total assetst
Panel F: Credit union size
Year
Number
Mean (£m)
164
1996
1.661
168
1997
1.910
164
1998
2.222
177
1999
2.329
178
2000
2.593
181
2001
2.897
175
2002
3.403
174
2003
3.840
183
2004
4.092
176
2005
4.566
181
2006
4.756
179
2007
5.148
176
2008
5.493
2,276
Total
3.480
Size = Total Assetst
Sd (£m)
Minimum (%)
Maximum (%)
4.742
4.953
5.199
4.875
4.990
4.611
4.142
3.929
4.020
4.081
3.967
4.105
3.860
4.404
-14.349
-5.161
-3.559
-5.449
-2.104
-11.497
-2.149
-5.530
-4.117
0.426
-8.773
-1.437
-18.856
-18.856
8.816
7.950
7.469
7.533
8.615
7.923
19.297
8.090
7.092
9.690
7.425
10.259
10.952
19.297
Median (£m)
Minimum (£m)
Maximum (£m)
0.738
0.867
1.028
1.032
1.175
1.244
1.462
1.610
1.676
2.064
2.030
2.194
2.458
1.408
0.016
0.008
0.029
0.007
0.016
0.022
0.026
0.026
0.030
0.031
0.034
0.045
0.043
0.007
31.000
38.300
43.300
45.000
48.300
53.300
59.000
63.100
66.700
69.300
71.700
74.700
77.300
77.300
3.321
3.932
4.492
4.697
5.135
5.701
6.567
7.142
7.511
8.032
8.323
8.821
9.218
6.781
41
Panel G: Credit union growth
Year
Number
Mean (%) Sd (%)
Median (%)
153
27.423
21.710
21.855
1996
164
26.755
28.864
18.904
1997
159
21.903
19.040
16.026
1998
164
18.396
13.452
14.495
1999
176
17.204
16.297
13.483
2000
177
17.525
16.148
14.451
2001
173
17.577
11.426
16.053
2002
166
16.912
27.311
13.142
2003
174
13.530
11.266
11.760
2004
176
10.515
11.672
8.816
2005
175
8.236
6.152
6.971
2006
178
8.119
4.713
7.660
2007
174
5.722
9.757
5.868
2008
2,209
15.911
17.778
12.432
Total
Growth = (Total Assetst-Total Assets t-1)/Total Assetst-1 x 100
42
Minimum (%)
-29.755
-18.168
-7.419
2.561
-4.081
-12.480
-11.766
-11.399
-26.687
-29.080
-4.858
-7.566
-86.753
-86.753
Maximum (%)
132.604
264.638
166.254
120.858
126.929
139.094
76.455
333.279
71.930
113.149
41.428
21.953
39.002
333.279
Table 2
Descriptive statistics on key ratios and trade association characteristics
ILCU
No. of CUs1.
Capital reserves (%)
No. of Obs (Years)
Mean
Standard dev
Median
Minimum
Maximum
Abnormal Provision (%)
No. of Obs (Years)
Mean
Standard dev
Median
Minimum
Maximum
Net write off (%)
No. of Obs (Years)
Mean
Standard dev
Median
Minimum
Maximum
Provision for bad debts (%)
No. of Obs (Years)
Mean
Standard dev
Median
Minimum
Maximum
Return on Assets (%)
No. of Obs. (Years)
Mean
Standard dev
Median
Minimum
Maximum
Size £m
No. of Obs (Years)
Mean (£’M)
Standard dev (£’M)
Median (£’M)
Minimum (£’M)
Maximum (£’M)
Growth (%)
No. of Obs. (Years)
Mean
Standard dev
Median
Minimum
Maximum
Age (years)
No. of Obs. (Years)
Mean
Standard dev
Median
Minimum
Maximum
Common bond
Residential
Employment
Associational
Total
104
UFCU
51
Antigonish
3
1,342
11.11%
2.35%
10.62%
2.39%
19.53%
580
7.90%
4.26%
7.24%
0.00%
24.45%
1,325
0.92%
1.30%
0.59%
-4.90%
10.61%
Other
Total
30
188
37
12.42%
3.23%
10.40%
10.00%
20.00%
317
7.32%
4.80%
7.45%
0.00%
20.24%
2,276
9.79%
3.84%
10.08%
0.00%
24.45%
492
0.31%
1.79%
0.00%
-10.17%
15.87%
29
0.05%
0.14%
0.00%
-0.24%
0.42%
300
0.30%
2.04%
0.00%
-16.08%
15.58%
2,146
0.68%
1.56%
0.17%
-16.08%
15.87%
1,337
0.43%
0.69%
0.28%
-2.08%
8.40%
575
0.25%
2.01%
0.00%
-32.66%
11.62%
37
0.09%
0.77%
0.02%
-3.06%
1.36%
314
0.81%
6.09%
0.00%
-1.75%
104.68%
2,263
0.43%
2.54%
0.05%
-32.66%
104.68%
1,342
2.74%
2.10%
2.20%
0.00%
15.11%
580
3.85%
4.95%
2.42%
0.00%
35.75%
37
3.36%
2.26%
2.90%
0.46%
8.18%
317
3.78%
5.96%
1.91%
0.00%
73.24%
2,276
3.18%
3.75%
2.20%
0.00%
73.24%
1,342
4.67%
1.22%
4.74%
-3.96%
8.61%
580
3.37%
2.32%
3.58%
-14.35%
19.30%
37
4.46%
1.63%
4.80%
-1.38%
6.49%
317
3.89%
2.40%
4.06%
-18.86%
8.61%
2,276
4.22%
1.85%
4.40%
-18.86%
19.30%
1,342
5.347
8.261
2.820
0.187
77.300
580
0.429
0.541
0.245
0.007
3.950
37
1.797
1.260
1.814
0.199
4.455
317
1.355
1.988
0.507
0.008
11.600
2,276
3.480
6.781
1.408
0.007
77.300
1,333
12.35%
6.76%
11.55%
-11.40%
83.43%
542
20.89%
23.71%
15.21%
-29.76%
264.64%
35
7.25%
9.40%
7.54%
-37.13%
24.51%
299
23.80%
30.55%
17.17%
-86.75%
333.28%
2,209
15.91%
17.78%
12.43%
-86.75%
333.28%
1,342
31.77 years
8.47 years
33 years
3 years
48 years
Number (%)
1,316(98%)
13 (1%)
13 (1%)
1,342 (100%)
580
8.83 years
4.42 years
9 years
1 year
21 years
Number (%)
260 (45%)
0 (0%)
320 (55%)
580 (100%)
37
25.57 years
4.54 years
26 years
18 years
35 years
Number (%)
25 (68%)
0 (0%)
12 (32%)
37 (100%)
317
10.11 years
4.85 years
10 years
1 year
21 years
Number (%)
98 (31%)
10 (3%)
209 (66%)
317 (100%)
2,276
22.81 years
13.06 years
26 years
1 year
48 years
Number (%)
1,699 (75%)
23 (1%)
554 (24%)
2,276 (100%)
43
1.
In 2009 the number of credit unions registered had fallen to 177 as some of the entities closed, or were
taken over by another credit union.
ILCU = Irish league of credit unions (comprehensive self-regulation); UFCU = Ulster federation of credit unions
(limited self-regulation); Antigonish (no self-regulation but strong ethical ethos); Other (no self-regulation).
CapRes = General reservest/Total assetst; Abnormal provision = (Actualt – Regulators recommended provision
for loan lossest)/Year end loans to memberst; Net write-off = (Loan loss write-offst – Write-offs from previous
years recoveredt)/Year end loans to memberst; ROA = Return on Assetst (Surplus (Deficit) /Total assetst); Size =
Total Assetst; Growth = (Total Assetst-Total Assets t-1)/Total Assetst-1.
44
Table 3
Comparison of the attributes of Northern Ireland credit unions that comply (1) with
legislation on capital reserves relative to non-compliers (0).
Panel A: Analysed by trade association
Total
ILCU
No.(%)
No.(%)
0
179(7.9%)
53(4%)
1
2,097(92.1%)
1,289(96%)
Total 2,276(100%)
1,342(100%)
UFCU
No.(%)
89(15.3%)
491(84.7%)
580(100%)
Antigonish
No.(%)
OTHER
No.(%)
37(11.7%)
280(88.3%)
317(100%)
0
37 (100%)
37(100%)
Panel B: Analysed by size, age, profitability and growth.
No. (%)
Age
Return on
Total Assets
(lAGE)
Assets (ROA)
0
179(7.9%)
£3,094,150
16.112
2.636%
1
2,097(92.1%)
£3,513,168
23.380
4.360%
Total 2,276(100%)
£3,480,214
22.808
4.224%
No.*
Growth
159
2,050
2,209
17.51%
13.59%
13.87%
Where: 1 = compliance (Capital reserve levels either exceed 10% or do not exceed 10% though
a minimum of 20% of surpluses have been retained in the year); and
0 = non-compliance (Capital reserves levels are below 10% and retentions from surpluses have
been less than the mandated 20%).
*Growth required total assets from the previous year (1995). This caused a loss of 67
observations where prior year data was not available.
45
Panel A
:Model 1
Table 4
Pair-wise correlations between continuous variables
Mandatory Capital Reserve Levels (CapRes)
CapRes
CapRes
lSIZE
lAGE
ROA1
GROW
Panel B:
Model 2
Abnprov
Panel D:
Model 4
1.000
0.812*
0.364*
-0.287*
lSIZE
1.000
0.147*
0.223*
0.080*
-0.151*
ROA1
1.000
0.270*
-0.478*
Growth
1.000
0.176*
1.000
lAGE
1.000
0.812*
0.307*
-0.287*
ROA2
1.000
0.231*
-0.478*
Growth
1.000
0.160*
1.0000
Self-Regulated - Bad debt Write Offs (Bdwo)
Bdwo
Bdwo
lSIZE
lAGE
ROA3
GROW
lAGE
Registrar and self-regulated – prudential provision (Abnprov)
Abnprov
lSIZE
lAGE
ROA2
GROW
Panel C:
Model 3
lSIZE
1.000
0.395*
0.587*
0.216*
-0.462*
lSIZE
1.000
0.005
0.050
-0.095*
-0.360*
lAGE
1.000
0.812*
0.370*
-0.287*
ROA3
1.000
0.291*
-0.478*
Growth
1.000
0.074*
1.000
Self-Regulated - Provision for Loan Loss level (Tbdprov)
Tbdprov
Tbdprov
1.000
lSIZE
-0.091*
lAGE
0.041
ROA2
-0.119*
GROW
-0.360*
*Significant at 1%
lSIZE
lAGE
1.000
0.812*
0.307*
-0.287*
ROA2
1.000
0.231*
-0.478*
Growth
1.000
0.160*
1.000
CapRes = Capital reservest/total assetst
Abnprov = Actual less the recommended loan book provision for loan losses t/total loanst
Bdwo = Loan loss write-offst less the loan loss write-backst/total loanst
Tbdprov = provision for loan lossest/ total loanst
lSIZE = log of total assets;
lAGE= log of age.
ROA1 = surplus (deficit)t/total assets;
ROA2 = surplus (deficit)t plus movement in the provision expensedt/total assets;
ROA3 = surplus (deficit)t plus loan loss write-offs t plus movement in the provision expensed t less the loan loss
write-backs t/total assetst;
GROW = (Total Assetst-Total Assets t-1)/Total Assetst-1
46
Table 5
Estimating the impact of trade association affiliation on compliance with
mandated levels of capital reserves
VARIABLES
Capital
reserves
Number of credit
unions
Observations
Constant
183
2,152
4.519***
(1.147)
0.770***
(0.234)
-0.346***
(0.100)
-0.971**
(0.409)
0.236***
(0.0354)
lAGE
lSIZE
GROW
ROA
Trade association
Antigonish
UFCU
-0.529*
(0.316)
-0.303
(0.329)
Other
Common bond
Employment
Associational
0.292
(0.239)
Yes
94.97
(p=0.000)
Year effects
Wald stat =
Standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
8
11
i 5
i 9
y*it  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
Dependent variables:
Compliance = 1 (Capital reserve levels either exceed 10% or do not exceed 10% though a minimum of 20% of
surpluses have been retained in the year); and
Non-compliance = 0 (Capital reserves levels are below 10% and retentions from surpluses have been less than
the mandated 20%).
Independent variables:
lAGE = log of age.
lSIZE = log of total assets;
ROA = surplus (deficit)t/total assets;
GROW = (Total Assetst-Total Assets t-1)/Total Assetst-1;
Trade association = a set of four dummy variables coded 1 for membership of ILCU; UFCU, Antigonish and
Other respectively; zero otherwise. The Antigonish credit unions are not included as they complied in all periods.
47
2008
  YEAR
l
l 1996
i
Common bond = a set of three dummy variables coded 1 for residential, employment and associational
respectively; zero otherwise. Credit unions with a common bond of employment are not included as they
complied in all periods.
Table 6
Two-way fixed effect regression model
Estimation of impact of age, size, growth and performance on prudence and loan book
quality of credit unions in Northern Ireland
(1)
(2)
(3)
(4)
Capital
Abnormal
Net write
Provision for
reserves
provision
offs
loan losses
Number of credit unions
188
187
188
188
Observations (years)
2,209
2,084
2,198
2,209
Constant
27.15***
6.420**
48.75***
30.74***
(2.567)
(2.515)
(3.851)
(3.805)
lAGE
5.767***
0.268
-0.560
2.148***
(0.246)
(0.220)
(0.363)
(0.362)
lSIZE
-2.621***
-0.486**
-3.295***
-2.309***
(0.219)
(0.208)
(0.331)
(0.327)
GROW
-1.621***
0.102
-10.23***
-7.664***
(0.370)
(0.383)
(0.547)
(0.538)
ROA1,1,2,3
0.274***
-0.0575**
-0.193***
-0.349***
(0.026)
(0.027)
(0.053)
(0.044)
Year effects
Yes
Yes
Yes
Yes
R-squared
0.531
0.042
0.235
0.301
Robust standard errors adjusted for clustering in parentheses
*** p<0.01, ** p<0.05, * p<0.1
VARIABLES
8
11
i 5
i 9
PEARLSit  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
2008
  YEAR  u
l
l 1996
Dependent variables (PEARLS):
Capital reserves = Capital reservest/total assetst
Abnormal provision = Actual less the recommended loan book provision for loan losses t/total loanst
Net write offs = Loan loss write-offst less the loan loss write-backst/total loanst
Provision for loan losses = provision for loan losses t/ total loanst
Independent variables:
lAGE= log of age.
lSIZE = log of total assets;
GROW = (Total Assetst-Total Assets t-1)/Total Assetst-1;
ROA1 = surplus (deficit)t/total assets;
ROA2 = surplus (deficit)t plus movement in the provision expensedt/total assets;
ROA3 = surplus (deficit)t plus loan loss write-offs t plus movement in the provision expensed t less the loan loss
write-backs t/total assetst.
48
i
it
Table 7
Regression analysis
Estimation of impact of age, size, growth, performance and trade association selfregulation on mandated and recommended prudential ratios
(1)
(2)
(3)
(4)
VARIABLES
Capital
Abnormal
Net write
Provision for
reserves
provision
offs
loan losses
Number of credit unions
188
188
188
188
Observations (years)
2,209
2,084
2,198
2,209
Constant
11.61***
0.735
4.325
9.027***
(2.328)
(0.832)
(3.763)
(3.381)
lAGE
2.232***
0.492**
-0.705
0.983
(0.521)
(0.207)
(0.699)
(0.663)
lSIZE
-0.705***
-0.140
0.0986
-0.570*
(0.195)
(0.088)
(0.089)
(0.311)
GROW
-7.510***
-0.270
-9.883
-10.52***
(1.106)
(0.375)
(7.152)
(3.661)
ROA1,1,2,3
0.497***
0.0893*
-0.199
0.0249
(0.087)
(0.052)
(0.204)
(0.181)
Trade associations
Antigonish
0.844
-0.999***
-0.639
-0.184
(1.461)
(0.153)
(0.566)
(1.115)
UFCU
-0.675
-0.370
-0.057
1.604**
(0.719)
(0.227)
(0.423)
(0.742)
Other
-1.033
-0.406**
0.788***
1.917**
(0.741)
(0.194)
(0.284)
(0.744)
Common Bond
Employment
0.087
-0.348
0.129
-1.455
(0.324)
(0.393)
(0.529)
(1.162)
Associational
-0.202
0.254
-0.638**
0.267
(0.591)
(0.198)
(0.249)
(0.705)
Year effects
Yes
Yes
Yes
Yes
R-squared
0.415
0.080
0.191
0.217
Robust standard errors adjusted for clustering in parentheses
*** p<0.01, ** p<0.05, * p<0.1
8
11
i 5
i 9
PEARLSit  a0  a1lAGEit  a2lSIZEit  a3 ROAit  a4GROWit    iTACi    iCBONDi 
2008
  YEAR  u
l
l 1996
Dependent variables (PEARLS):
Capital reserves = Capital reservest/total assetst
Abnormal provision = Actual less the recommended loan book provision for loan losses t/total loanst
Net write offs = Loan loss write-offst less the loan loss write-backst/total loanst
Provision for loan losses = provision for loan losses t/ total loanst
Independent variables:
lSIZE = log of total assets;
lAGE = log of age.
GROW = (Total Assetst-Total Assets t-1)/Total Assetst-1.
ROA1 = surplus (deficit)t/total assets;
ROA2 = surplus (deficit)t plus movement in the provision expensedt/total assets;
ROA3 = surplus (deficit)t plus loan loss write-offs t plus movement in the provision expensed t less the loan loss
write-backs t/total assetst.
Trade association = a set of four dummy variables coded 1 for membership of ILCU; UFCU, Antigonish and
Other respectively; zero otherwise.
Common bond = a set of three dummy variables coded 1 for residential, employment and associational
respectively; zero otherwise.
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it