NEW ZEALAND BANK MERGERS AND EFFICIENCY GAINS

Paper presented at the 14th Annual Australasian Finance and Banking

Conference, Sydney, December 2001

Benjamin Liu

Department of Accounting and Finance

Monash University

Caulfield, Victoria

Australia

David Tripe1

Centre for Banking Studies

Massey University

Palmerston North

New Zealand

Abstract:

This paper uses accounting ratios and DEA (Data Envelopment Analysis) to explore

the efficiency impacts of 6 bank mergers in New Zealand between 1989 and 1998.

The paper is the first reported application of DEA to the New Zealand banking sector,

and its methodology is based around that used by Avkiran in his study published in

the Journal of Banking and Finance in 1999 [Avkiran (1999B)].

Consistent with earlier research, acquiring banks were found to be generally larger

than their targets, although they were not consistently more efficient. In a majority of

cases the merger led to an increase in efficiency, consistent with a trend observed for

the banking sector as a whole. No clear conclusions could be drawn on possible

public benefits from the mergers.

1 Corresponding author: Phone +64 6 350-5799 ext 2337, fax +64 6 350-5651, or E-mail D.W.Tripe@massey.ac.nz.

2

The wave of deregulation in financial markets over the last 20 years or so has caused

significant changes to the environment within which banks and financial institutions

operate. It has become much easier for new institutions to enter markets, but it has

also become much easier for existing institutions to merge with each other. New

Zealand has not been exempted from these trends. The deregulation process was

accelerated following the election of a Labour government in 1984, and by 1987 the

banking market had been opened up to allow the entry of new banks. In due course,

new and existing banks began to merge with each other, and since 1988 we have had

seven cases of mergers involving banks active in the retail market. These were:

• The acquisition of the Post Office Savings Bank (PostBank) from the New

Zealand government by the ANZ Banking Group (ANZ) in 1989;

• The acquisition of Westland Bank by ASB Bank in 1992;

• The acquisition of United Bank (United) by Countrywide Bank (Countrywide)

in 1992;

• The absorption of National Australia Bank (NZ) Ltd (NAB(NZ)) into the

Bank of New Zealand (BNZ) in 1992, following the (parent company)

National Australia Bank’s acquisition of the BNZ;

• The acquisition of the Rural Bank by the National Bank of New Zealand

(NBNZ) in 1992;

• The acquisition of Trust Bank New Zealand (TBNZ) by the Westpac Banking

Corporation (Westpac) in 1996, to form WestpacTrust; and

• The acquisition of Countrywide by the NBNZ in 1998.

A side effect of this has been that the New Zealand banking system is now more than

99% foreign-owned.

A variety of reasons have been advanced as to why banks merge. Some of the reasons

suggested are non-value-maximising for the firms involved, although in most cases,

mergers are justified on the basis that the new enlarged entity will be able to be more

efficient in its use of resources, and thus operate at lower cost, or achieve greater

3

revenues from the same cost base. In either case, the merged institution should be

able to increase returns to shareholders.2

This paper sets out to explore these propositions, that mergers allow banks to become

more efficient and reduce their operating costs or increase their revenues. In their

review of previous studies, Berger & Humphrey (1997) noted that there was no

evidence for such improvements, on average (p 195), but that should not stop us from

looking at this proposition against the background of the mergers amongst New

Zealand retail banks reported above.

The paper is structured as follows. We begin with a brief review of previous research,

with a particular focus on previous Australasian research, in the process of which we

identify the method used for this study. We then describe the data, and look at the

results obtained from the study. This allows a discussion of the relationships between

scale, efficiency and public benefits as observed in the New Zealand market. We

conclude by identifying a range of issues for further research.

Previous Research

Efficiency can be defined in terms of the extent to which a decision-making unit

(DMU), typically a business, can increase its outputs without increasing its inputs, or

reduce its inputs without reducing its outputs. A unit will be 100% efficient if there is

no scope for improvement in the ratio in which it converts inputs to outputs.

Efficiency can generally be grouped into scale efficiency, scope efficiency and X-

efficiency. Scale efficiency measures whether banks are operating with an efficient

level of outputs; scope efficiency measures whether banks are operating with an

efficient mix of outputs; and X-efficiency focuses on whether banks are operating

with an efficient mix of inputs.

Over the last two decades in particular, a number of studies on banking efficiency

have been conducted in the USA and elsewhere3. Most early studies focused on

2 For a more extensive review of the theoretical rationales for bank mergers, refer to Berger, Demsetz & Strahan (1999). 3 For a review of this research, refer to Berger & Humphrey (1997).

4

measurements of scale and scope efficiency. Most literature on scale efficiency in the

USA suggests that medium-sized banks are more scale efficient than either very large

or very small banks [Humphrey (1990)].

There has been little empirical research on bank efficiency in Australia since the small

number of banks makes it difficult to conduct econometric analysis.4 Valentine and

Williamson (1982), using a multiple product cost function estimation and data from

the 1970s, could not find conclusive evidence of scale efficiency. Research by

Walker (1998), using a multi-product translog function model and data from 1978 to

1990, showed stronger evidence of economies of scale for Australian banks.

The second type of bank efficiency is economies of scope, which arise from the

potential to use common production facilities to produce multiple products. Banks are

multiproduct firms simultaneously producing a variety of loans, deposits and

investments. Economies of scope exist when joint production of more than one type

of product or output is less costly than the sum of costs of production of these

products or outputs by specialist or separate firms.

More recently, bank efficiency studies have turned to x-efficiency, which represents

the ability of management to control costs and use resources to produce outputs, and

which links to differences in individual bank efficiency. X-efficiency covers the two

concepts of allocative and technical efficiency. Walker (1999) says, "technical

inefficiency occurs where there is an over-employment of inputs to produce a given

output and allocative inefficiency occurs when a better mix of inputs would produce

the same output at lower cost " (p 123).

For Australia, using a variant of the average residual method, Walker (1998) found

the National Australia Bank (NAB) to show best practice bank among the four majors

in the 1980s, while the Commonwealth Bank of Australia (CBA) was the least

efficient with an x-efficiency of 80%. Using 1990s data, he found the NAB to be, on

average, the lowest cost and the CBA the highest cost bank [Walker (1999)].

4 Rather more research has been undertaken on credit unions and other non-bank financial institutions, the numbers of which are rather greater, and which therefore provide more scope for statistical and econometric exploration.

5

All three types of bank efficiency concern inputs and outputs, but there is no

consensus on definitions of inputs and outputs. There are two general approaches to

viewing bank production: the production and the intermediation approaches. The

production approach sees banks as producers of loans and deposits accounts, using

labour, capital and other, as inputs. Outputs are measured as the number of each type

of account or service the bank handles. Costs comprise all operating expenses, which

are a function not only of the output levels and input prices, but also of the average

account size of each type of output [Mester (1987)].

Most studies have used the intermediation approach, which sees banks purchasing

labour, materials, and deposits funds to produce outputs of loans and investments.

Outputs are measured as the dollar value of the bank's earning assets; costs include

both interest and operating expense [Berger, Hanweck & Humphrey (1987)]. Mester

(1987) points out that, although the production approach allows the numbers of

accounts and their average size to have different effects on costs, the intermediation

approach has an advantage over the production approach because it includes the total

costs of banking and does not distinguish between a bank purchasing deposits from

other institutions or raising its own deposits.

Under the intermediation approach, the bank's outputs are found on the asset side of

the balance sheet and deposits are seen as inputs. Avkiran (1999A) suggests that

potential outputs include net interest income, non- interest income, commercial loans,

consumer loans, housing loans and investments. Potential inputs include interest

expense, non- interest expense, number of staff (full time equivalent), deposits, other

purchased capital, physical capital (fixed assets and equipment), demographics and

competition.

DEA and Other Frontier Analysis Approaches Although there is no consensus on the best method for measuring x-efficiency, the

most popular approach used for banks is frontier analysis. Berger and Humphrey

(1997) suggest that frontier analysis is essentially a sophisticated way to benchmark

the relative performance of production units and help managers to improve

6

managerial performance by identifying "best" and "worst practices" associated with

high and low measured efficiency (p 175).

At least five approaches have been used. The major measurement problem is

distinguishing variations in x-efficiency from random error [Bauer, Berger, Ferrier &

Humphrey (1998)]. Three major parametric frontier approaches include the stochastic

frontier (SFA), the distribution-free approach (DFA) and the thick frontier approach

(TFA). The stochastic frontier (SFA), sometimes referred to as the economic frontier

approach, specifies a functional form for costs, profits or production relationships

among inputs, outputs and environmental factors, and allows for random error. DFA

also specifies a functional form for the frontier, but separates inefficiency from

random error in a different way, and makes no strong assumptions about the specific

distribution of inefficiency or random error. TFA specifies a functional form and

assumes that deviations from predicted performance values with the highest and

lowest performance quartiles of observations represent random error. Berger and

Humphrey (1997) argue that "parametric frontier approaches commit the sin of

imposing a particular functional form (and associated behavioural assumptions) that

presupposes the shape of frontier…if the functional form is misspecified, measured

efficiency may be confounded with the specification error" (p.179).

Data envelopment analysis (DEA) and Free Disposal Hull (FDH) are non-parametric

approaches which put relatively little structure on specifications of best-practice

frontier. Bauer et al. (1998) state that an obvious benefit of DEA is that it does not

need the explicit specifications of a functional form and imposes very little structure

on the shape of the efficient frontier.

DEA gives a comparative ratio of weighted outputs to inputs for each DMU. The

relative score is normally expressed as a number between 0-100% or 0-1. A unit with

a score less than 100% or 1 is regarded as inefficient relative to other units in the

selected sample. This contrasts with the operation of parametric techniques, such as

Cobb-Douglas functions, which use statistical averages to construct a particular

measure of inefficiency, which may or may not be applicable to that unit's

composition.

7

DEA is particularly suited to working with limited sample size [Evanoff & Israilevich

(1991)], and is thus considered appropriate for use in New Zealand where there are

only 18 registered banks.

The major limitation of DEA is that it does not allow for random error or exceptional

performance, as recorded in DMUs’ accounting data: all deviations from the

estimated efficient frontier are thus identified as x-inefficiency. Exceptional events

unrelated to the fundamental economic performance of the DMU can cause its

apparent efficiency to be overstated, thus making other DMUs look comparatively

inefficient [Berger & Humphrey (1997), Bauer et al. (1998)].

The FDH approach is a special case of the DEA model. Since the FDH frontier is

either congruent with or interior to the DEA frontier, it will generate larger estimates

of the average efficiency than DEA [Berger & Humphrey (1997), p 177].

Evidence of Bank Mergers and Efficiency Gains

Efficiency gains through M&As are assumed to be made by banks changing their

input or output quantities in ways which can reduce costs, increase revenues, or

reduce risk to increase value for a given set of prices. Most studies have been

conducted in the USA, and have shown little evidence of cost savings. Studies by

Berger & Humphrey (1992) and Rhoades (1993) show that if the acquiring bank is

more efficient than its target, there are no efficiency gains from in-market mergers.

Some studies have found that, in a substantial proportion of M&As, a more efficient,

larger financial institution tends to take over a smaller, less efficient one [Berger &

Humphrey (1992), Pilloff & Santomero (1998)]. Another study of US banks found

acquiring banks to be more profitable and have smaller bad loan ratios than target

banks [Peristiani (1993) cited in Berger et al. (1999)]. European studies found that

larger, more efficient and more profitable banks tend to acquire smaller, less efficient

and less profitable banks [Vander Vennet (1997)]. Berger (1998) found that "on

average, bank mergers increase the profit efficiency relative to other banks, but have

little effect on cost efficiency. Efficiency is much more pronounced when the

participating banks are relatively inefficient ex ante, consistent with a hypothesis that

8

mergers may 'wake up' inefficient management or are used as an excuse to implement

unpleasant restructuring" (p. 79). Studies of US banking from the 1980s show average x-efficiency gains of 5% or less

from bank mergers and acquisitions [Berger and Humphrey (1992), Rhoades (1993),

DeYoung (1997) and Peristiani, (1997)]. Studies using early 1990s data are mixed.

Greenspan (1998) claims that there are no clear-cut findings that suggest bank

mergers uniformly lead to efficiency gains, but evidence suggests that there are

considerable differences in cost efficiencies within all bank size classes, implying

substantial potential for many banks to improve their efficiency, perhaps through

mergers.

Profit efficiency effects of M&As include scale, scope, product mix and x-efficiency

effects for both costs and revenues, and also include some diversification effects. A

recent Australian study (Avkiran, 1999b) measured relative efficiency gains for

Australian banks for the period of 1986-1995, using DEA and financial ratios. This

study used the intermediation approach and two DEA models; A and B, shown in

Table 1.

Table 1: DEA models regarding inputs and outputs (Avkiran, 1999b).

Model A Model B

Inputs Interest expense

Non-interest expense

Deposits

Staff numbers

Outputs Net interest income

Non-interest income

Net loans

Non-interest income

Avkiran studied four bank mergers and the whole banking industry, and reported that

acquiring banks were more efficient than target banks. He also found that acquiring

banks do not always maintain their pre-merger efficiency, but that, during the

deregulated period, overall efficiency, employees' productivity and return on assets

(ROA) improved. There was mixed evidence from the four cases on the extent to

which the benefits of efficiency gains from mergers were passed on to the public.

9

Most measurements of banking efficiency in New Zealand have been based on simple

accounting or financ ial ratios using a single input and output. This is the first study of

the efficiency of New Zealand banks to use a frontier analysis approach.

Research Design

Methodology

This study examines the efficiency and performance of the New Zealand banking

sector over the period 1987-1999. We use DEA and some key accounting efficiency

ratios: the operating efficiency (cost to income) ratio, operating expense/average total

assets, employees' productivity (operating income/average employee) and return on

assets (ROA). Non- interest expense is defined so as not to include tax expense or bad

and doubtful debt expense. Operating income is the net interest income plus non-

interest income. Total assets exclude goodwill.

Partly because of the unavailability of data necessary for use of the production

approach, this study uses the intermediation approach. Outputs are measured in

dollars. This study uses three DEA models, described as 1, 2 and 3, summarised in

Table 2.

Table 2 DEA models in this study

Model 1 (after 1990) Model 2 (after 1990) Model 3 (before 1990)

Inputs Interest expense

Non-interest expense

Interest expense

Non-interest expense

Interest expense

Non-interest expense

Outputs Net interest income

Non-interest income

Customer deposits

Net loans and advances

Operating income

Deposits

Loans and advances

Operating income

In each model, the input variables are interest and non- interest expense, which are

costs to generate incomes, reflecting the user cost approach (one part of the

intermediation approach) [Walker (1999)]. Bank non- interest expense comes mainly

from labour and infrastructure, and is used to generate non- interest income, included

in operating income. It is also used to receive customer deposits, make loans, and

monitor customers' borrowings. Model 2 uses the value-added approach (another part

10

of the intermediation approach), with a different set of outputs, operating income,

customer deposits, and net loans and advances, which together account for a large

proportion of banks’ operating costs.

This study uses the CCR model which assumes constant return to scale, meaning that

outputs change in direct proportion to the change in inputs, regardless of the size of

the DMU. We thus follow a common assumption in DEA analysis, that the DMU’s

scale of operations does not impact on its efficiency. 5 If a bank is found to be

inefficient, relative to the efficiency frontier, it can either minimise inputs, producing

its current level of output with fewer inputs, or maximise output, generating more

output with the same level of inputs.

Under the alternative, BCC, model with variable returns to scale, each unit is

compared only against other units of similar size, rather than against all other units.

This assumption of variable returns to scale is more suitable for a large sample

[Banxia Holdings Limited (1998)]: ".. a unit found to be inefficient has its efficiency

measured relative to other units in the data-set of a similar scale size only.” (p23).6

The proxy used to examine the extent to which efficiency gains of bank mergers are

passed on to the public is the change of market share of total customer deposits in the

two years following the merger (excluding the year when the merger was happening)

[Rhoades (1993), Avkiran (1999b)].

Sample and Data

Data are thus required for two years before and after the mergers, which occurred in

1989, 1992, 1996 and 1998. Annual bank data for the period from 1987 to 1999 have

been collected from KPMG New Zealand financial institutions performance surveys,

banks' disclosure statements since 1996 and banks' annual reports. Data for 2000 were

not yet available when this study was being undertaken.

5 Any actual economies of scale will thus be subsumed into measurements of x-efficiency. 6 Berg Forsund & Suominen (1993) also note that use of a variable returns to scale model may make larger banks appear to be efficient, just because they are large.

11

In analysing individual mergers, we exclude the year when the merger or acquisition

occurred as the accounting data can often be unhelpful. Some bank M&As occurred

before the end of the relative financial year, so that data include both the acquiring

and target bank, while others occurred after the financial year end, so that data are for

the acquiring bank only.

This study uses two data sets. One is limited to full service banks, which undertake

retail banking and wholesale banking; the other comprises a wider list of registered

banks in New Zealand. The full service banks have wide branch networks and make

loans to individual consumers and business, whereas other banks without branch

networks mainly focus on loans to corporate borrowers. The two types of bank thus

have different cost structures.

Sample selection is based on similarity of bank activities, and asset bases of close to

or more than $1 billion two years prior to and following the merger or acquisition.

Bankers Trust and Deutsche Bank (NZ) were excluded from the analysis because their

business activities were very different from other banks. Although ASB acquired

Westland Bank in 1992, this case is omitted because Westland Bank's assets were less

than $100 million prior to the merger. Other banks were omitted from the sample due

to small asset size or unavailability of data.

This study treats BNZ Finance Limited as an independent bank since 1990 when it

registered as a bank, even though its data is consolidated into BNZ's financial

statements. It enlarges the sample size and thus improves the discriminatory power of

the analysis.

Literature suggests that the products of inputs and outputs should be less than the

sample size for analysis to discriminate the inefficient DMUs, and the sample size in

this study is between 7 and 15 banks (See Table 3).

12

Table 3: Examples of small sample size in DEA literature

Researchers (Date) Sample size Inputs x outputs

This study (2000) 7-15 2x2=4 and 2x3=6

Avkiran (1999a and 1999b) 16-19 2x2=4

Oral and Yolalan (1990)* 20 5x4=20

Vassiloglou and Giokas (1990)* 20 4x4=16

Giokas (1991) 17 3x3=9

Hang and Jaska (1995)* 14 3x4=12

Yeh (1996) 7 3x3=9

( * cited in Avkiran, 1999b)

Research Analysis and Results

Efficiency Profiles of Banks Involved in Mergers and Acquisitions

Key aspects of the mergers reviewed in this study are summarised in Table 4 below.

Prior to their 1998 merger, Countrywide showed as being slightly more efficient that

the NBNZ on all three measures. The timing of this study did not allow inclusion of

year 2000 data. Westpac appeared more efficient than TBNZ pre-merger, with its

mean ratios of operating expense to average total assets and operating expense to

operating income better than those of the target bank.

Before its takeover of United, Countrywide was a little larger and significantly more

efficient. The major improvement in efficiency was in respect of employee

productivity. The NBNZ was much bigger than the Rural Bank, but in terms of three

key efficiency measures, Rural Bank was much more efficient than the NBNZ, which

gained significantly from the merger.

The BNZ was much larger than NAB(NZ). Before the acquisition, the acquiring

bank's cost to income ratio was far better than the target bank, while the other two

efficiency measures were similar.

13

The ANZ was significantly larger than PostBank. The merged bank's assets were

nearly the same as combined assets of the two banks before the merger. Through the

merger, ANZ achieved a small improvement in operating expense to average total

assets, but an obvious increase in operating expense to operating income.

Table 4: Mergers analysed.

Acquirer NBNZ Westpac Countrywide NBNZ BNZ ANZ

Acquiree Countrywide Trust

Bank

United Rural

Bank

NAB

(NZ)

Post

Bank

Year 1998 1996 1992 1992 1992 1989

Size before $18 B $13 B $1.8 B $7.4 B $18.9 B $6.7 B

Size after $29 B $27 B $4.7 B $14.7 B $19.1 B $10.4 B

Increase 61% 108% 161% 99% 1% 55%

Cost to

income

72.3% to

66.9%

61.4% to

58.2%

75.3% to

75.7%

75.9%

to

70.0%

84.1%

to

71.2%

64.3%

to

78.6%

Cost to

assets

2.52% to

1.84%

2.82% to

2.70%

3.55% to

3.20%

4.88%

to

3.05%

4.22%

to

3.88%

4.82%

to

4.31%

Employee

productivity

before

($000)

164 171 96 129 127 N/A

Employee

productivity

after($000)

237 186 162 162 179 130

In the six cases reviewed, acquiring banks were bigger than target banks, although not

in general more efficient, contrary to the findings of Avkiran (1999b) and others.

Except with the ANZ’s acquisition of PostBank, merged banks achieved most

efficiency gains by reducing employee numbers and closing branches. To understand

the efficiency changes properly, however, we cannot rely just on accounting

measures, but must use DEA.

14

DEA Analysis and Results

We first examine the correlation between the input and output variables, to assess

their suitability for use. Avkiran (1999A) suggests that a correlation coefficient higher

than 0.8 indicates reasonable relationships between variables for DEA analysis.

Under Model 1 (covering 1990-99), the lowest recorded value for correlation between

interest expense and net interest income was 0.86 in 1990, which is well within

acceptable limits. Model 2 measures banks' efficiency after 1990 while Model 3

measure it before. In 1993, the correlations between interest expense and net loans

and advances, and non- interest expense and net loans and advances were 0.84 and

0.88, but these figures are not so low as to invalidate the approach followed.

An initial test was undertaken with Frontier Analyst to examine the correlation

between the size of variables and efficiency. All the variables show a weak correlation

with efficiency, which implies an absence of significant returns to scale. This justifies

use of the CCR, constant returns to scale, model in preference to the BCC, variable

returns to scale, approach.

Table 5 shows DEA scores for two years before and after mergers or acquisitions

(excluding the merging year). Contrary to what would be expected from Avkiran

(1999b) and others, in three out of six cases the acquiring bank was less efficient than

the acquired bank. In four out of six cases, the acquisition caused an improvement in

efficiency for the acquiring bank.

Before the merger of NBNZ and Countrywide, the target bank, Countrywide, had

DEA scores of 100 for 1997 and 1996, but the acquiring bank, NBNZ, had DEA

scores of 77.5 and 76.0. The acquiring bank was less efficient than the target bank.

Before its acquisition of TBNZ, Westpac's DEA scores were higher. The merged

bank, WestpacTrust, showed efficiency improvements, consistent with the Australian

merger between Savings Bank of Tasmania and Tasmania Bank (Avkiran, 1999b), but

inconsistent with research reported by Berger and Humphrey (1992) and Rhoades

(1993).

15

Table 5 Relative efficiency scores (%) for two years prior to and following the

merger (excluding merger year), based on Models 1 and 3 and all banks.

Acquiring

bank

Pre-merger

efficiency

Acquired

bank

Pre-merger

efficiency

Post-merger

efficiency

NBNZ 76.77% Countrywide 100.00% 100.00%

Westpac 97.27% Trust Bank 95.75% 100.00%

BNZ 97.19% NAB (NZ) 47.04% 87.22%

NBNZ 98.95% Rural Bank 100.00% 87.50%

Countrywide 80.26% United Bank 60.69% 100.00%

ANZ 88.99% Post Bank 100.00% 90.66%

WestpacTrust’s improvements did not come from scale or scope economies, but from

rationalisation of branch networks. As Moore (1998) suggests, this merger was

supposed to achieve cost reduction because the costs of the combined bank after the

merger would be less than the sum of the individual banks' costs before, reflecting

rationalisation of branch networks, head offices and infrastructure. This is consistent

with a study by Berger (1998) on profit efficiency effects of bank mergers of the

1990s. He found that "on average, bank mergers increase profit efficiency relative to

other banks, but have little effect on cost efficiency. Efficiency is much more

pronounced when the participating banks are relatively inefficient ex ante, consistent

with a hypothesis that mergers may 'wake up' inefficient management or are used as

an excuse to implement unpleasant restructuring" (p 79).

BNZ was far more efficient than NAB(NZ). This accords with previous studies where

a more efficient, larger financial institution tends to take over a smaller, less efficient

one [Berger & Humphrey (1992), Pilloff and Santomero (1998), Vander Vennet

(1997), Avkiran (1999b)]. Following the merger, the BNZ experienced a decline in

efficiency, with a low profit in 1993 following the adoption of National Australia

Bank's accounting policies and procedures (KPMG, 1994). Write-back of previous

bad and doubtful debt provisions enhanced profits in 1994 and subsequent years.

16

Other mergers in 1992 were between the NBNZ and Rural Bank, and Countrywide

and United. The Rural Bank was slightly more efficient than the NBNZ. The merged

bank appeared to maintain its pre-merger efficiency for 1993, but had a sharp decline

in its DEA score for 1994. This may reflect an interest rate position, however, rather

than being an inefficiency effect of the merger [Staff (1995, 19 May)].

In the other case, Countrywide was bigger than United and appeared more efficient.

However, post-merger results contradict some previous studies, in that both net

interest income and non- interest income increased, pushing the bank to the efficiency

frontier with a DEA score of 100.

For the ANZ/PostBank case a lack of data forced us to use Model 3. Prior to the

merger, ANZ was much bigger than PostBank, although less efficient. Following the

merger the ANZ achieved a small efficiency gain.

Three out of the six cases support the hypothesis that acquiring banks are more

efficient than target banks, as opposed to three out of four cases in Australia (Avkiran,

1999b). For two years following mergers, four out of the six banks achieved

efficiency gains.

Analysis on Overall Operating Efficiency of the Bank Industry

We also consider the impact of these bank mergers and acquisitions on the New

Zealand banking sector as a whole. As Figure 1 shows, the operating efficiency and

cost to income ratios increased between 1987 and 1989. In both New Zealand and

Australia there was a period of very high interest rates, although the poor performance

in 1989 was due at least in part to significant bad debt problems for BNZ and NZI

Bank. Since 1990, both ratios have gradually decreased. This may be attributed to the

6 mergers since 1992, but there are other factors, such as increased technology use,

which may also have impacted.

Walker (1999) and Avkiran (1999b) found no evidence of scale efficiency for

Australian banks, and we have therefore looked at New Zealand banks with assets

over 0.5 billion in 1997. The four big banks were less efficient than small banks,

17

while retail banks, such as TSB, were less efficient than wholesale banks (based on

the ratio of operating expense to average total assets). A review of banks identified as

efficient in terms of their DEA scores, as shown in Tables 6 and 7, also fails to

convince us that scale is a necessary factor.7 Initial indications thus support the

Australian evidence rejecting the existence of scale economies.

Figure 1 Operating efficiency and operating expense to average total assets for the

New Zealand banking sector

Another indicator showing efficiency gains is the ratio of operating income to average

employees. There were significant gains, from 122 in 1989 to 228 in 1999. The

Australian banking sector showed a similar pattern for this period (Avkiran, 1999b).

Further evidence on efficiency gains can be found by evaluating profit performance,

as measured by ROA which dropped sharply at the beginning of the 1990s, but which

has increased since 1993. This result may be linked to the bank M&As.

Under both models, the number of banks classed as efficient tended to increase during

the 1990s, reflecting a trend in the mean DEA score. For all banks, this increased

from 81.3 in 1990 to 91.3 in 1995: for the full-service banks it increased from 81.8 in

1990 to 98.2 in 1995.

After 1996, DEA scores tended to decline slightly, although mean scores remained

higher for the full service banks than for the whole sample. This is believed to reflect

7 There are some differences between the banks identified as efficient by the two models, reflecting the different variables used.

0

1

2

3

4

5

6

7

87 88 89 90 91 92 93 94 95 96 97 98 99Year

Ope

ratin

g ex

pen

se/a

v.to

tal a

sset

s %

010

20

3040

5060

7080

90

Ope

ratin

g ex

pens

e/op

erat

ing

inco

me

%

Operatingexpense/av.totalassets %

Operatingexpense/operatingincome %

18

the effect of new entrant (foreign) banks dragging down the mean DEA scores. Since

1996, the industry mean DEA score has been between 85 and 90, which suggests

greater efficiency than has been reported for some other countries over the same time

period.

Table 6: Efficient banks in Model 1

Year Efficient banks

1999 BNZ Finance, Banque Nationale de Paris, Hong Kong Bank, ANZ,

WestpacTrust, NBNZ, TSB

1998 BNZ Finance, Hong Kong Bank, ANZ, WestpacTrust, TSB

1997 BNZ Finance, Countrywide, WestpacTrust, TSB

1996 BNZ Finance, ANZ, BNZ, Countrywide, TSB

1995 BNZ Finance, ASB, BNZ, Countrywide, Trust Bank, TSB

1994 BNZ Finance, ANZ, Countrywide

1993 BNZ Finance, Hong Kong Bank, ANZ, Countrywide, Westpac, TSB

1992 BNZ Finance, Hong Kong Bank, ANZ, BNZ, NBNZ, Westpac, TSB

1991 ANZ, NBNZ, TSB, Rural Bank

1990 ANZ, BNZ, Rural Bank

Table 7: Efficient banks in Model 2

Year Efficient banks

1999 BNZ Finance, AMP Bank, Hong Kong Bank, WestpacTrust, TSB

1998 BNZ Finance, AMP Bank, WestpacTrust, TSB

1997 BNZ Finance, TSB, ANZ, Rabobank

1996 BNZ Finance, ANZ, WestpacTrust, Hong Kong Bank, TSB

1995 BNZ Finance, ASB, Hong Kong Bank, Trust Bank, TSB

1994 BNZ Finance, Hong Kong Bank, ANZ, ASB

1993 BNZ Finance, ANZ, ASB, TSB

1992 BNZ Finance, ANZ, ASB, NBNZ

1991 BNZ Finance, NBNZ, United Bank, Rural Bank

1990 ANZ, ASB, Countrywide, Rural Bank, Trust Bank

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Public Benefits Associated with Efficiency Gains

As Rhoades [(1986), cited in Avkiran (1999b)] suggests, if the price of banking and

quality of services improve as a result of operating efficiency, the merged bank should

increase its market share. A positive correlation between change in market share and

change in overall operating efficiency would show that benefits of efficiency gains

were being passed on to the public.

Since we lacked industry-wide deposit data for 1990, 1991 and 2000, the

NBNZ/Countrywide, and ANZ/PostBank cases are excluded. Data for bank deposits

was obtained from KPMG's surveys. Results shown in Table 8 indicate a mixed but

generally positive relationship.

Table 8 Correlation between change in deposits and change in operating efficiency.

Year Sector Banks Percentage %

Change %

Operating Efficiency

Change %

Correlation

Westpac and Trust Bank 1996 72,354,198 19,494,700 0.2694 70.66 1997 76,255,812 20,955,800 0.2748 1.99 58.72 -16.90 Positive 1998 70,323,547 22,642,200 0.3220 17.16 57.69 -1.75 Positive

National Bank and Rural Bank 1992 49,796,244 9,549,000 0.1918 71.44 1993 49,102,705 10,909,000 0.2222 15.86 66.21 -7.32 Positive 1994 57,876,109 10,745,000 0.1857 -16.43 73.75 11.39 Positive

Countrywide and United Bank 1992 49,796,244 3,206,791 0.0644 106.79 1993 49,102,705 2,312,527 0.0471 -26.87 74.26 -30.46 Negative 1994 57,876,109 2,549,922 0.0441 -6.45 77.08 3.80 Positive

National Australia Bank (NZ) and BNZ 1992 49,796,244 17,462,502 0.3507 73.14 1993 49,102,705 14,001,606 0.2851 -18.69 76.23 4.22 Positive 1994 57,876,109 13,051,532 0.2255 -20.92 66.19 -13.17 Negative

Results in the Westpac/TBNZ, and NBNZ/Rural Bank cases appear to support the

assumption of a positive relationship, while in the Countrywide/United/1993, and

NAB(NZ)/BNZ/1994 cases they do not. In 1994, both deposits and operating

efficiency declined for the NBNZ, leaving the two variables with a positive

relationship.

20

Only WestpacTrust showed an increase in deposits for the two years after merger.

Deposits in BNZ and Countrywide actually declined sharply; the NBNZ had a big rise

for the first year after merger, but a little fall in the second year. A study by Avkiran

(1999b) also gave a mixed result for Australian banks. He points out that "the variable

change in share of deposits is not a good proxy measure of the extent to which

operating efficiency is passed on to the public" (p.1005). However, New Zealand

evidence on this issue was stronger than that in Australia.8 There is thus no clear

answer as to whether bank mergers or acquisitions bring benefits to the public.

Further study is required, perhaps using alternative variables to measure market share,

or looking for other ways to measure merger effects.

Conclusions and suggestions for further research

This study has used key accounting efficiency measures and three DEA models to

examine efficiency gains for individual banks involved in mergers or acquisitions, and

has attempted an introductory exploration of some of the costs and benefits associated

with New Zealand bank mergers and acquisitions since 1987.

On key accounting efficiency measures, acquiring banks were not consistently more

efficient than target banks, contrary to results of Avkiran (1999b) and others. Post-

merger, banks achieved most efficiency gains in employee productivity. Five out of

the six merged banks had efficiency gains based on the other ratios while ANZ only

achieved a slight improvement in operating expense to average total income.

Based on DEA analysis, only some banks were more efficient than their target banks

prior to mergers. Four banks had obvious efficiency gains post merger. There were

significant differences between the results reported under Models 1 and 2, which

shows the sensitivity of DEA analysis to variables used.

Annual mean DEA scores increased for the banking sector between 1990 and 1999.

This could provide evidence to support the hypothesis that efficiency gains are

associated with bank mergers and acquisitions in New Zealand, although other

8 There are, however, inclined to be problems and inconsistencies in what banks report as deposits. There is some exploration of this issue in Tripe (1999, December).

21

interpretations are possible, such as a greater emphasis by banks on efficiency and

cost reductions.

The four cases looked at indicated a mixed relationship, but generally support the

concept of a public benefit from efficiency gains. New Zealand evidence on this issue

was more supportive of a positive relationship than that in Australia.

Further studies on New Zealand bank efficiency may use modified DEA models

which could include risk factors, asset quality, the number of staff and branches, and

others as inputs and outputs, and may also need to collect more bank data for analysis

and comparisons. This study lacks some bank data for the late 1980s and for 2000,

and has only used annual data, whereas a larger data set might now be able to be

created from the quarterly data disclosed since the beginning of 1996. There may also

be merit in using approaches, other than DEA, while further studies might measure

technical and allocative efficiency separately.

Also, in view of the strong (ownership) relationship that exists between the New

Zealand and Australian banking sectors, it would be interesting to look at the

comparative efficiencies being achieved. This may be impacted by the trend now

being observed where banks’ New Zealand operations are being reduced to becoming

operations just like those in other Australian states.

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