International Variation

International Variation in Bank AccountingInformation Content

Ronald Zhao and Yihong He

Department of Accounting, Monmouth University, West Long Branch, NJ 07764, USAe-mail: [email protected], [email protected]

Abstract

This study explores the cross-country impact of financial system and banking regulationson the information content of bank earnings and book value. Test results provideempirical evidence that financial system and banking regulations have a joint effect onthe association of equity price with earnings and book value components in Germany,France, the United Kingdom and United States. This effect is explainable by the objectivebank function, which shows that earnings of the period determine the terminal bookvalue, thus consistent with the clean surplus accounting approach. Cross-country varia-tion in bank accounting information content calls for caution in interpreting internationalbank financial and operating ratios.

1. Introduction

The accelerating globalization of the world economy and integration of

capital markets has led to a proliferation of research on the value

relevance of accounting information across countries, with a focus on

international diversity of earnings quality (e.g., Pope and Walker, 1999;

Ali and Hwang, 2000; Ball et al., 2000) and earnings management (e.g.,

Brown and Higgins, 2001; Bhattacharya et al., 2003; Leuz et al., 2003).

However, based exclusively on industrial/commercial firms, the extant

literature is not generalizable to financial institutions including commer-

cial banks, which differ significantly from industrial/commercial firms in

terms of operating characteristics and reporting requirements.

In contrast to the shortage of international accounting studies on

financial institutions, comparative works on bank efficiency and profit-

ability abound in economics and finance literature. For example, Berger

and Humphrey (1997) surveyed 130 studies that applied frontier effi-

ciency analysis to financial institutions in 21 countries, and found that

the various efficiency methods did not yield consistent results. We argue

that, to an extent, the mixed results are attributable to cross-country

The authors want to thank Professor Frederick D.S. Choi (the Editor) and two anonymousreviewers for their constructive comments and helpful suggestions.

Journal of International Financial Management and Accounting 19:3 2008

r 2008 Blackwell Publishing Ltd., 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

variation in bank accounting information content from which interna-

tional bank financial and operating ratios are derived. Hence, the need

for a paper to explore the international variation in bank accounting

information and ratio analysis.

Banking is a regulated industry owing to the important intermediary

role banks play in national financial systems. Each country has its own

regulations for bank capitalization, risk exposure and information

disclosure to address the three fundamental sources of systematic risks

for bank operations: interest risk, credit risk and liquidity risk (Stigum

and Branch, 1983). However, despite their national diversity, commercial

banks have a relatively simple and homogenous production function and

capital structure because they specialize in transforming deposits into

loans and investments, as compared with industrial/commercial firms

engaged in heterogeneous business activities. This production function

provides a feasible basis for identifying the impact of various institu-

tional factors on bank accounting information content.

Our study investigates the variation in bank accounting information

content for France, Germany, the United Kingdom and United States.

All the four countries are members of both the OECD and G-10 group,

characterized by a compatible level in economic development and

financial market sophistication.1 Nevertheless, significant differences

exist among their financial market structures and banking regulatory

regime. The United Kingdom and United States (France and Germany)

are examples of shareholder (creditor)-oriented financial systems, with

equity playing a significantly more (less) important role than bank loan

as a funding source for firms. Whether a country has a shareholder- or

creditor-oriented financial system is important because each type of

systems has dissimilar implications for dealing with potential asymmetric

information problems that arise between those providing the funds and

those receiving them. Furthermore, commercial banks have been per-

mitted a varying range of allowable activities in the four countries with

France (the United States) as the most deregulated (regulated) one in

terms of engaging in securities, insurance and real estate activities. The

motivation of the paper is to examine how the different sets of institu-

tional factors affect accounting information content across the four

countries, thereby leading to varying value relevance of international

bank accounting information and financial/operating ratios.

The next section reviews the balance sheet and income statement of

commercial banks and develops testable hypotheses. Section 3 describes

the test sample and reports empirical results. Section 4 concludes the paper.

International Variation in Bank Accounting Information Content 237

r 2008 Blackwell Publishing Ltd.

2. Hypotheses development

2.1 Financial Statements of Commercial Banks

Analysis of the financial statements of commercial banks involves

exposure to some accounts and ratios that are different from those of

industrial/commercial firms. The global financial system has experienced

several important changes over the past few decades. Simultaneous with

the transformation of the banking industry, the development of money

markets and mutual funds have created new possibilities for firms to

finance their investments and for investors to allocate their funds. These

changes directly or indirectly influenced the information content of bank

balance sheets and income statements, which are illustrated as follows:

(Figures 1 and 2)

One recent development in banking that had significant implications

for the evolution of balance sheet is the increase in importance of off-

balance-sheet activities. Some of the most common off-balance-sheet

activities are the provision of line of credit, the securitization and sale of

loans, and the trading of derivative instruments. Obviously, the changes

in the structure of the industry and in the composition of the balance

sheet will affect their ability to meet the capital adequacy requirements as

well as the sources of income for banks.

There are five main components of the income statement of commer-

cial banks. Interest income is the result of all interest and dividend earned

by banks on interest-bearing assets (such as loans and leases). Interest

expense is the result of all interest paid to depositors and other creditors

of the bank. Non-interest income includes fee income, gain on securities

transactions, and all other income not originated in interest payments.

Non-interest or Operating expense includes personnel compensation,

legal expenses, office occupancy and equipment expenses. Finally,

provision for loan losses is the amount charged as operating expenses

238 Ronald Zhao and Yihong He

Assets Liabilities

Deposits

Borrowed Funds

Others

Cash

Loans and Leases

Securities

Others Stockholders Equity

Figure 1. Balance sheet.


to provide an adequate reserve to cover anticipated losses in the loan

portfolio. These charges become part of the allowance for loan losses, a

deductive component from the asset on bank balance sheet, which is then

used to charge off loans after they become non-performing.

The institutional design of banking supervision has been emphasized

to eliminate moral hazard bias and strengthen market discipline in the

banking industry. The strategy of eliminating moral hazard consists in a

sharpening of capital requirements for banks and restriction with regard

to banking operations. In the context of the strategy to enlarge market

discipline in the banking system, an important issue relates to the

availability and quality of bank accounting information. To further

this objective, the International Accounting Standard Committee issued

IAS No. 30: Disclosure in the Financial Statement of Banks and Similar

Institutions (reformatted, 1994).

The quality of bank accounting information is essential in the working

of the market mechanism because market participants base their eco-

nomic decisions on the information. Quality information on capital

adequacy and earnings ability provide a more accurate picture of the risk

exposure and the financial cushion of the bank. As information moves

market prices, increased bank financial transparency complements reg-

ulatory supervision and promotes market discipline. We develop three

hypotheses to test market response to the value relevance of cross-

country bank accounting information.

2.2 Capital Requirements

The primary criterion in bank supervision involves capital adequacy

standards, for which the International Committee on Banking Supervision


Interest Income

Interest Expense

+Non-interest Income

Non-interest Expense

Provisions for Loan Losses

Others

Net Income

Figure 2. Income statement.


adopted the Basle Accord in 1988 and Basel Accord II in 2005. The Basle

Accords specify definitions of Tier 1 (core) capital (stockholders equity),

Tier 2 capital (additional components of capital), and a general frame-

work for assigning assets and off-balance sheet items to broad risk

categories to enable the calculation of risk-based capital ratio. A

minimum ratio of total capital (Tier 1 plus Tier 2) to risk-weighted

assets of 8 percent (of which at least 4 percent should be in the form of

core capital) was specified in 1992. Although the Basle Accords are

viewed by many as providing uniform minimum capital requirements, it

does not affect banks in each country equally because there are

differences in the items that may be included as components of capital

for purposes to fulfill the requirements. Table 1, panel A lists the

components of regulatory capital for meeting the capital requirement

in the four countries.

Failure to meet capital adequacy would increase banks cost of

capital, thus resulting in lower equity value. Bank managers can

increase regulatory capital through the combination of its components

(Moyer, 1990). Thus, differences in the composition of regulatory

capital constitute a major source of cross-country variation in the

information content of capital adequacy for commercial banks. The first

hypothesis is:

H1 : The association of market valuation with asset risk for capital

adequacy of commercial banks differ significantly between countries.

The following model can be used to test Hypothesis 1:

MVit a b1CCit b2RCit b3Di b4CCit Di b5RCit Di eit 1

where MVit5market value of bank is common equity at the end of year

t, CCit5 contributed capital of bank i at the end of year t, RCit5

reserved capital of bank i at the end of year t, Di5 system/country

dummy for bank i, CCit Di5 interaction of CCit and Di,RCit Di5 interaction of RCit and Di, eit5disturbance term.

Contributed capital (CC) consists of capital stock and additional paid-

in capital, which represent the legal capital requirement for an incorpo-

rated commercial bank and cannot be distributed to shareholders except

under liquidation. Reserved capital (RC) includes retained earnings,

other distributable and non-distributable reserves (e.g., unrealized secu-

rities gains/losses, fixed asset revaluation reserve), which reflect the




Table1.

Panel

A:components

ofcapitalformeetingthecapitalrequirem

ents(a)

France

Germany

UK

US

Perpetualpreferred

stock

No

Yes

Yes

Yes

Currentyearprofit(loss)

Yes

No

Yes

Yes

Goodwill

No

No

No

No

Other

intangible

assets

No

No

No

No

Undisclosedreserves

No

Yes,butlimits

N/A

No

Hybridcapitalinstruments

Yes,butnotprevalent

Yes,butlimits

Yes,butlimits

Yes,butlimits

Subordinatedterm

debt

Yes

Yes,butlimits

Yes,butlimits

Yes,butlimits

Lim

ited

life

redeemable

preferred

stock

Yes,butnotissued

No

Yes

Yes,butlimits

Fixed

asset

revaluationreserves

Yes

No

Yes,withcaution

No

Hidden

revaluationreserves

No

Yes,butlimits

N/A

No

Generalloanloss

reserves

Yes

Yes,butlimits

Yes,butlimits

Yes,butlimits

Investm

entin

other

financialinstitutions

Yes,butlimits

No

No

No

Panel

B:regulationsonbankoperatingactivities(a)

Permissible

BankingActivities:

France

Germany

UK

US

Securities

Unrestricted

Unrestricted

Unrestricted

Restricted

Insurance

Permitted

Restricted

Permitted

Restricted

Realestate

Permitted

Permitted

Unrestricted

Restricted

Investm

entin

nonfinancialfirm

sUnrestricted

Unrestricted

Unrestricted

Restricted

Nonfinancialfirm

investm

entin

commercialbanks

Unrestricted

Unrestricted

Unrestricted

Restricted

(a)BasedonBarthet

al.(1997).


additional components of bank capital. We expect both CC and RC to be

significant in relation to market value as proxies for Tier 1 and Tier 2

capital, respectively.

We run each model twice by using the dummy to discriminate between

shareholder- (D5 0) and creditor-oriented (D5 1) systems the first time,

and to distinguish among the four countries (D5 0 for the United States,

D5 1 for France, D5 2 for Germany, and D5 3 for the United King-

dom) the second time. In the first run, the interaction terms of CC Dand RC D will show the between-group difference of France andGermany (creditor-oriented system) from the United Kingdom and

United States (shareholder-oriented system) because equity plays sig-

nificantly different roles as funding source between the two groups. The

shareholder-oriented system reports book value of equity with higher

transparency, leading to a stronger association with market price. The

second run will further indicate the within-group difference between

countries within each system due to dissimilar banking regulation in

capital requirement (Table 1, panel A), which would affect the extent of

discretionary items in bank capital. For example, we expect the interac-

tion term of CC D and/or RC D for France to be more significantlydifferent than those for Germany relative to the United States (share-

holder-oriented system), though both France and Germany belong to the

creditor-oriented system. Within the shareholder-oriented system, the

CC D and/or RC D for the United Kingdom would also demon-strate significant difference between banks in the United Kingdom and

United States.

2.3 Income Smoothing

Managers in creditor-oriented markets are inclined to smooth earnings

to conform more closely to dividend and employee bonus policies and

requirements of tax authorities by increasing (decreasing) discretionary

accruals in good (bad) years (Ball et al., 2000). Income smoothing

involves the manipulation of the time profile of earnings to reduce the

fluctuations of publicly reported earnings in order to enhance investors

ability to predict future cash flows, while not necessarily increasing

reported earnings over the long run (Zhao and He, 2004). In particular,

bank management has strong incentives to smooth earnings in order to

maintain public confidence in the banking system. Income smoothing

could reduce banks bankruptcy risk as perceived by investors and

regulators. Moreover, the reduced bankruptcy risk may arguably lead



to a lower cost of capital, and therefore, a higher market valuation for

banks (Trueman et al., 1988). Income smoothing would also have a

beneficial effect on the evaluation of bank management performance by

providing an alternative for low-quality management to project an image

of high-quality management, contributing to their reputation capital

(Johnson, 1997). For instance, earnings stability is one of the criteria in

the CAMEL model used by US banking regulatory agencies for super-

vising bank performance.2

France, Germany, the United Kingdom and the United States differ in

permissible securities, insurance and real estate activities for banks

(Table 1, panel B), which generate non-interest (operating) revenues, as

opposed to interest revenues from traditional bank borrowing and

lending activities. National regulations on permissible bank activities

across countries would dominate the income smoothing behavior of

banks, and as a result, affect the quality of their earnings components. It

would require an optimal balance between market and regulatory

discipline to constrain both the kind and extent of risky activities in

which banks engage. The second hypothesis is developed as follows:

H2 : The association of market valuation with earnings components for

commercial banks differ significantly between countries.

We use a bank earnings decomposition model to test how the market

responds to interest, non-interest and other income components in the

four countries:

MVit a b1NIIit b2NNIIit b3ONIit b4Di b5NIIit Di b6NNIIit Di b7ONIit Di eit

2

where MVit5market value of bank is common equity at the end of year

t, NIIit5 net interest income for bank i in year t, NNIIit5 net noninterest

income for bank i in year t, ONIit5other net income for bank i in year t,

The dummy and interaction terms are as explained in Equation (1).

NII is the difference between interest income and interest expense,

while NNII is the difference between non-interest income and non-

interest expense. The variable ONI consists of other nonrecurring income

items such as foreign exchange income, exceptional items and other

provisions/reserves. NII and NNII are expected to have positive signs in

relation to market value because they provide primary recurring sources

of earnings for banks functioning as financial intermediaries. On the

other hand, ONI, which includes various types of provisions and other



nonrecurring earnings, would have weaker association with market value

especially if it is used as income smoothing tool. More stringent

regulations on banking operations increase the information content of

earnings components because they reduce managements choices of

discretionary accruals via various types of operating activities for income

smoothing by restricting banks permissible activities, thus leading to

higher earnings and earnings components quality.

As France, Germany and the United Kingdom allow for more

permissible bank activities than the United States, their banks are

more likely to have a greater scope for earnings management through

various accruals, therefore, weakening the association between banks

earnings and market valuation. Consequently, we expect a significantly

negative interaction of NII D and NNII D for the creditor-orientedsystem in the first run. In the second run, NII D and NNII D for thethree countries are also expected to be significantly different as compared

with the United States, though both the United Kingdom and United

States fall under the shareholder-oriented system. The interaction term of

ONI D would further reflect the relative extent to which it is used as anincome smoothing tool in each of the countries.

2.4 Equity Valuation

We separately examine the accounting implications of financial system

and banking regulations for book value and reported income of

commercial banks in the preceding sections. However, it is difficult to

isolate a banks demand for increasing earnings from its demand for

regulatory capital because earnings is also a source of capital. In this

section, we test the linear information dynamic between bank earnings

and book value components across the four countries.

Santomero (1984) modeled the financial intermediary role of a bank as

a microeconomic firm that attempts to maximize an objective function in

terminal wealth, and he generalized the optimization function as follows:

Maximize E VWt T a

Subject to WtT Wt1Pt11Pt2 . . . 1PtT b

PtT SigiAi SjdjLj CAiLj

=WtT1 PtT=WtT1 c



where V(n) is the objective function, where @V/@WX0 and@2V=@W2tT ; 0. Wt1T is the value of terminal wealth at the horizontime.Pt1T is the stochatic profit per unit of capital during period t1k, where04ko5T. pt1k is single period profit for period t1k. gi is the stochaticreturn on asset i. Ai is the asset category i, where 14i4n. dj is the stochasticcost for deposit j. Lj is the depository category j, where 14j4m. C(n) is theoperations cost function, where @C/@AiX0 for all i and @C/@LjX0 for all j.

Equation (a) is the general form of the objective function to be

maximized by the bank. In Equation (b), the general specification is

defined as a multi-period valuation problem. Equation (c) defines profit

per unit of capital invested by the owners. Solving (a), (b), and (c) results

in a joint decision of portfolio structure and leverage, which determines

the banks terminal wealth. Using reported earnings to proxy for pt1kand book value for Wt1k, this objective function conceptually agrees

with the clean surplus accounting approach to the linear information

dynamic between reported earnings and book value.

According to the clean surplus approach, the valuation of a firm equals

to its book value of equity, current profitability as measured by (abnor-

mal) earnings, and other information that affect the prediction of future

profitability (Feltham and Ohlson, 1995; Ohlson, 1995). This linear

information dynamic assumes that the value of a bank can be approxi-

mated by a function of forecasted earnings, book value and discount rate

over a finite horizon, if these forecasts are consistent with the clean surplus

relation. The clean surplus relation imposes two restrictions: first, discount

rates are constant across firms; and second, accounting conservatism is

constant across firms. These two conditions are more applicable to banks

than industrial/commercial firms because of the homogeneity in bank

production function and capital structure. Based on the clean surplus

approach, the third hypothesis tests the joint effect of financial system and

banking regulations on the variation in the linear information dynamic

framework for commercial banks across the four countries:

H3 : Financial system and banking regulations have a significant impact

on the linear information dynamics for commercial banks.

The empirical model is as follows:

MVit a b1CCit b2RCit b3NIIit b4NNIIit b5ONIit b6Di b7CCit Di b8RCit Di b9NIIit Di b10NNIIit Di b11ONIit Di eit

3



The definitions of the variables are the same as in Equations (1) and (2).

b1 and b2 are multiplicative parameters that relate book value tomarket value. If book value is equivalent to capitalized normal earnings,

then firm value is equivalent to the sum of capitalized normal earnings

and capitalized abnormal earnings, or simply capitalized earnings. b3, b4and 5 are earnings capitalization factors that take into account cross-country differences in risk, expected growth and other factors. In the

valuation framework of the clean surplus model, book value is assumed

to provide information on normal earnings, and abnormal earnings is

captured in the linear information dynamics between accounting earn-

ings and book value. More stringent banking regulations are expected to

have a positive impact on the linear information dynamic for commercial

banks because, holding everything else constant, current periods income

determines terminal wealth.

Recall that significant difference exists between France and Germany

(Germany, France and the United Kingdom) versus the United King-

dom and United States (the United States) in terms of capital require-

ment (earnings components) in H1 (H2). We expect significant difference

in the linear information dynamic, first between the shareholder- and

creditor-oriented systems, and then between the United Kingdom in

addition to France and Germany versus the United States, because the

variation in earnings quality would affect that of the capital components.

3. Empirical Tests

3.1 Data Description

The financial and market data were retrieved from Compustat Global

Financial Service File for the period of 1994 to 2004. The test data

contains a sample of commercial banks in each of the four countries with

SIC codes 60216022. Only banks with $100 million and above in total

assets are included in the test sample to control for size effect. Foreign

monetary units were translated into US dollar based on year-end

exchange rate. All variables were scaled by the square root of total

assets for the regression tests. The requirement of complete data set for

each observation results in 325 bank-year observations for France, 222

for Germany, 167 for the United Kingdom, and 822 for the United

States. Table 2 lists the descriptive statistics of variables. Year dummies

are added to each of the regression models to control for the variation in

economic environment during the examination period.



Scaling by the squared root of total assets makes it possible to

statistically compare market value, capital and earnings components

across the four countries. Market value is higher for the United Kingdom

and United States than France and Germany, reflecting that equity

markets play a more (less) significant role as a source of financing for

commercial banks in UK and US (France and Germany). Banks in the

four countries report positive interest margin (NII), reflecting the

improving business operating environment during the examination

period. Commercial banks in the United Kingdom post highest interest

income, followed by those in the United States and Germany. The

negative NNII is due to the deduction from non-interest revenue of

salary and benefits, a major operating expense incurred by commercial

banks. The last earnings component, ONI represents the scope of income

from other non-recurring activities, subject to cross-country bank

regulations.


Table 2. Descriptive Statistics of Model Variables

(Note) France Germany UK US

Market value (MV)Mean 6.5485 12.0083 39.5418 30.9732Standard deviation 10.3771 11.5378 37.5563 30.2702t-value (versus US) 20.575nnn 14.585nnn 2.680nnn

Contributed capital (CC)Mean 3.5403 6.0511 5.2445 4.2014Standard deviation 3.6918 5.0247 4.1929 5.8254t-value (versus US) 2.292nn 4.647nnn 2.662nnn

Reserved capital (RC)Mean 4.3479 3.0345 11.6244 7.8950Standard deviation 4.0168 3.9305 12.1004 8.3475t-value (versus US) 9.737nnn 12.398nnn 3.672nnn

Net interest income (NII)Mean 1.9813 2.4770 6.8290 4.7667Standard deviation 1.8438 2.2628 5.5222 4.1556t-value (versus US) 15.829nnn 10.893nnn 4.416nnn

Net noninterest income (NNII)Mean 0.6452 1.5458 2.9579 1.9143Standard deviation 1.4989 2.1514 2.7321 2.0520t-value (versus US) 11.533nnn 2.255nn 4.518nnn

Other net income (ONI)Mean 0.2001 0.1370 0.1953 0.0834Standard deviation 0.5630 0.5119 0.6745 0.4468t-value (versus US) 3.3nnn 1.399 4.938nnn

nn and nnnDenote statistical significance at level of 5% and 1%, respectively.NoteAll variables are scaled by square root of assets.t-value is calculated for France, Germany and UK, respectively, as compared with US.


3.2 Regression Results

The Model 1 regression results for the between- and within-group tests

are reported in panels A and B of Table 3, respectively. The high-

adjusted R2 for both tests indicates that the universal implementation of

the Basle Accord results in a significant association between market

valuation and equity capital for capital adequacy of commercial banks

across the four countries. Both the coefficients of CC and RC in panel A

(B) are positively significant for the shareholder-oriented system (the

US), showing the importance of Tier 1 and Tier 2 capital adequacy in the

market valuation of commercial banks in shareholder-oriented system

(the US). The greater weight of the coefficient estimate for RC, which


Table 3. Regression Model 1 Results

Panel A: system model

F-Value5 400.043 Significance5 .000 Adjusted R25 0.789Variable Coefficient SE t-statistic Significance

Constant 1.491 1.283 1.162 .245CC 1.575 0.076 20.633 .000RC 2.546 0.048 53.256 .000D 6.490 1.064 6.099 .000CC D 0.179 0.153 1.170 .242RC D 1.249 0.156 7.998 .000

D5 system dummy; 0 if shareholder-oriented, 1 if creditor-oriented.

Panel B: country model

F Value5 289.976 Significance5 .000 Adjusted R25 0.792Variables Coefficient SE t-statistic Significance

Constant 1.152 1.302 0.885 .376CC 1.582 0.079 20.145 .000RC 2.628 0.056 47.135 .000D1 7.845 1.325 5.919 .000D2 3.465 1.533 2.261 .024D3 0.229 1.764 0.130 .897CC D1 0.377 0.222 1.697 .090CC D2 0.339 0.210 1.612 .107CC D3 0.100 0.308 0.323 .746RC D1 1.137 0.204 5.585 .000RC D2 1.236 0.260 4.750 .000RC D3 0.223 0.117 1.903 .057

Dependent variable: market value of equity; CC5 contributed capital; RC5 reserved capital.D5 country dummy; D15 1 if France; D25 1 if Germany; D35 1 if the UK.All variables are scaled by square root of assets.


constitutes retained earnings and other reserves, represents future growth

prospect for commercial banks in shareholder-oriented system (the US).

In panel A, the coefficient for CC D is negative but not significant,and that for RC D is negative and also significant. This result indicatesthat there is (no) significant difference in the composition of Tier 2 (1)

capital between the shareholder- and creditor-oriented systems. This

significant difference in RC is explainable by their different capital

adequacy requirements. Commercial banks in France and Germany

have greater flexibility to include fixed asset revaluation reserves, invest-

ment in other financial institutions, undisclosed reserves and hidden

revaluation reserves as asset composition for meeting Tier 2 capital

adequacy (Table 1, panel A). Consequently, the markets respond to these

assets, which carry higher uncertainty and less predictable value, more as

capital management tool rather than economic benefit.

Test results in Panel B further show that within the shareholder-

oriented system, the RC D for the United Kingdom is significantlydifferent from that of the United States, because commercial banks in the

United Kingdom, like France, report a higher level of RC than those in

the United States as they are allowed to include more items for

regulatory capital (Table 1, Panel A), and this dissimilarity in banking

regulation leads to significant difference in information content of capital

adequacy between banks in the United Kingdom and the United States.

Taken together, these results first corroborate the literature that legal

system has a primary effect on the properties of accounting numbers of

firms (e.g., Ball et al., 2000). Second, they provide further evidence that

banking regulations also plays a significant role in the value relevance for

the components of bank capital for meeting capital requirements. The

empirical findings support H1.

It is of interest to note that the regression results of Model 1 are

opposite to those of comparative studies based on industrial/commercial

firms, which usually report greater weight for book value of firms in

creditors- than in shareholders-oriented countries. Assuming the same

degree of market efficiency and motivations for reporting opportunism,

shareholders-oriented system and more stringent banking regulations

lead to closer scrutiny of commercial banks net asset components. The

information content of regulatory capital components for US banks

significantly improve on those for UK and French banks.

Table 4 presents the regression results for Model 2. Panel A shows that

all the three earnings components for banks under shareholder-oriented

systems are significantly positive in relation to market value. NII is the



result of interest-related activities, such as lending and borrowing, which

are considered to be traditional business activities for financial inter-

mediaries, and historically net interest margin has been the major source

of commercial banks profit. As a result of intensified competition

triggered by deregulation of the financial markets, NNII, which is related

to investment and service activities, has become an increasingly impor-

tant source of income for commercial banks (Edwards and Mishkin,

1995). Furthermore, as NNII also includes loan loss provision, and bank




F Value5 449.569 Significance5 .000 Adjusted R25 0.827Variable Coefficient SE t-statistic Significance

Constant 4.362 1.145 3.811 .000NII 9.100 0.138 65.900 .000NNII 8.400 0.276 30.436 .000ONI 1.732 0.747 2.307 .021D 3.560 0.950 3.747 .000NII D 3.074 0.393 7.824 .000NNII D 5.008 0.482 10.393 .000ONI D 1.385 1.216 1.139 .255

D5 system dummy; 0 if shareholder-oriented, 1 if creditor-oriented.



Constant 4.764 1.132 4.209 .000NII 9.416 0.149 63.044 .000NNII 9.551 0.297 32.168 .000ONI 0.137 0.920 0.149 .882D1 5.721 1.144 5.002 .000D2 2.208 1.296 1.705 .088D3 4.922 1.529 3.220 .001NII D1 3.320 0.495 6.712 .000NII D2 3.336 0.568 5.871 .000NII D3 2.018 0.343 5.879 .000NNII D1 4.928 0.614 8.031 .000NNII D2 6.425 0.651 9.868 .000NNII D3 5.890 0.716 8.230 .000ONI D1 3.535 1.483 2.384 .017ONI D2 2.255 1.829 1.233 .218ONI D3 2.205 1.754 1.257 .209

Dependent variable: market value of equity; NII5net interest income; NNII5 net noninterestincome; ONI5other net income.D5 country dummy; D15 1 if France; D25 1 if Germany; D35 1 if the UK.All variables are scaled by square root of assets.


managers are found to use loan loss provision to signal improvement in

future cash flow prospects (Wahlen, 1994). ONI, which includes mostly

foreign currency transactions for US banks, also has a positive sign.3 The

interaction terms NII D, NNII D are significantly negative, suggest-ing that these two major earnings components are less value relevant

under creditor-oriented system. ONI D, which include more reservesand provisions for creditor-oriented banks, are insignificant.

The interaction coefficients of NII D and NNII D in the countrymodel (Panel B) demonstrate significant difference in the value relevance

in NNI and NNII between France, Germany and the United Kingdom

versus the United States. This difference is attributable to two causes.

First, commercial banks in the three countries are allowed to be engaged

in a wider range of activities than in the United States (Table 1, Panel B),

but the information content of income from each individual source is lost

in the aggregate NII and NNII. Second, more diverse banking activities

also provide ampler scope for the use of accounting accruals in earnings

management, thus diluting the information content of earnings compo-

nents. The NII and NNII for France and Germany are expected to be

significantly different from those of the United States because of the joint

effect of differences in reporting requirements and permissible banking

activities. The value relevance of NII and NNII differs between the

United Kingdom and United States, both of which belong to the

shareholder-oriented system, for two possible reasons. First, Ball et al.

(2000) found the earnings quality of UK (commercial/industrial) firms

inferior to that of their US counterparts. The combination of more

flexible accounting standards plus fewer operating restrictions is likely to

provide commercial banks in UK with more latitude for earning

management. An alternative explanation is that commercial banks in

the United Kingdom are supplemented by a variety of other financial

institutions, such as building societies, mutual or cooperative banks,

rural/agricultural banks, etc. The Competition and Credit Control Act

(1971) has blurred the market segmentation between commercial banks

and these institutions in the United Kingdom. The exclusion of these de

facto banking institutions from the data set would have probably

amplified the variability of the United Kingdom sample.

In contrast to the negative sign for NII D and NNII D, ONI Dis (significantly) positive for (France) Germany and the United King-

dom. Judging by the greatest magnitude of the coefficient, it can be

interpreted that French banks make a more extensive use of ONI as a

tool to manage earnings than in the other three countries. The significant



difference in ONI (NII and NNII) between France and the United States

(the United Kingdom and United States) again provide strong evidence

of the effect of banking regulation on earnings quality in addition to

reporting system (H2).

Table 5 provides the regression result of Model 3, which test the linear

information dynamic between capital and earnings compositions (H3).

Both the system and country test results have the highest adjusted R2

among all the three models, indicating that the clean surplus model

captures the linear information dynamic missing in Models 1 and 2.

A comparison of the test results of Model 3 with those of Models 1

and 2 for all the similar items reflect that the value relevance of book

value and earnings depends on whether they are assessed separately

(Models 1 and 2) or in a linear information dynamic frame (Model 3).

We first compare Models 2 and 3 for earnings components. NII D,NNII D and ONI D are identical at both the system and countrylevels between Models 2 and 3, except for that ONI D for France is(not) significant in Model 2 (3). A comparison of Models 1 and 3 for

capital composition reveals that CC D is insignificantly negative at thesystem level in Model 1, however, it becomes significantly positive in

Model 3. This change occurs because in Model 1, the value relevance of

book value is estimated without reference to earnings as a source of

capital; but in Model 3, it also reflects the linear information dynamic

between book value and earnings. At the country level, the most

noticeable distinction is that while RC D is significantly different forFrance, Germany and the United Kingdom in Model 1, it becomes

insignificant in Model 3. Such changes arise because the capital and

earnings components are segregated in Model 3, but in Model 1 the

earnings is part of capital components as being contained into RC. By

combining the three models together, we can discern the value relevance

of book value (earnings) in a clearer perspective by holding earnings

(book value) constant. In the context of commercial banks, the test

results of Model 3 can also be interpreted as the joint effects of share-

holder- versus creditor-oriented system (which affects book value) and

banking regulations (which affect earnings components) on the proper-

ties of accounting information contents.4

In summary, a comparison of all the three models sheds light on the

joint effect of shareholder- versus creditor-oriented system and banking

regulations on the accounting information content of commercial banks.

Models 1 and 2 demonstrate that book value and earnings components

have higher value relevance in shareholder-oriented countries where







Constant 1.957 1.101 1.777 .076CC 0.800 0.093 8.585 .000RC 1.020 0.093 10.996 .000NII 6.571 0.255 25.724 .000NNII 7.461 0.278 26.848 .000ONI 2.364 0.722 3.275 .001D 5.196 0.920 5.649 .000CC D 0.375 0.180 2.073 .038RC D 0.989 0.093 10.583 .000NII D 2.405 0.494 4.868 .000NNII D 4.070 0.467 8.717 .000ONI D 0.970 1.159 .836 .403

D5System dummy; 0 if shareholder-oriented, 1 if creditor-oriented.



Constant 3.888 0.591 2.052 .040CC 0.782 0.105 7.473 .000RC 0.936 0.117 7.992 .000NII 6.632 0.359 18.459 .000NNII 7.946 0.353 22.504 .000ONI 1.280 0.913 1.401 .161D1 7.330 1.164 6.298 .000D2 3.723 1.310 2.843 .005D3 3.746 1.556 2.407 .016CC D1 0.264 0.227 1.163 .245CC D2 0.286 0.318 .902 .367CC D3 0.606 0.330 1.837 .066RC D1 0.359 0.311 1.154 .249RC D2 0.018 0.292 .063 .950RC D3 0.034 0.203 .167 .868NII D1 3.298 0.995 3.316 .001NII D2 4.350 0.999 4.354 .000NII D3 1.534 0.622 2.466 .014NNII D1 4.563 0.815 5.598 .000NNII D2 5.971 0.717 8.329 .000NNII D3 5.234 0.740 7.070 .000ONI D1 1.351 1.541 .877 .381ONI D2 0.684 1.788 .383 .702ONI D3 0.219 1.731 .126 .899

Dependent variable: market value of equity; CC5 contributed capital; RC5 reserved capital;NII5net interest income; NNII5net noninterest income; ONI5other net income.D5Country dummy; D15 1 if France; D25 1 if Germany; D35 1 if the UK.All variables are scaled by square root of assets.


banking regulations are also stricter. The test results of Model 3 show

that bank accounting information in shareholder-oriented countries are

more sensitive to linear information dynamic between book value and

earnings components than in creditor-oriented countries. For example,

both the book value and earnings components are more positive for UK

than for French and German banks in Models 1 and 2; however, the

negative implication of earnings components for book value is only

discernible for the United Kingdom in Model 3.

3.3 Ratio Analysis

Accounting ratios are commonly used as measurement of firm perfor-

mance. In evaluating the financial health and operating results of a firm,

the quality of its earnings is of particular importance to analysts. Banks

attempt to effectively manage the trade-off between risk and returns in

order to improve the overall return on equity, and their performance

(income) is determined by their efficiency to earn more on their assets

(loans and investments) than they pay interest to depositors through the

financial intermediary function. However, just as variations in the

application of GAAPs may hamper comparability and reduce quality

of earnings for domestic firms, international differences would further

affect the value relevance of analytical ratios for assessing commercial

banks performance across countries. Table 6 presents the descriptive

statistics of several typical bank financial and operating ratios for

France, Germany, the United Kingdom and United States.

Table 7 reports the results of two sets of univariant regression, the first

(second) set regresses each of the bank financial and operating ratios on

net income (market value). The net income based results displays the

statistical differences of the ratios across the four countries. These

differences result from banks cost function (Rose and Walken, 1986)


Table 6. Descriptive Statistics of Ratios

Mean of France Germany UK US

Capital ratio 0.0919 0.0527 0.0890 0.0854Loan-to-deposit ratio 2.2976 0.8385 1.8165 0.8796Return on assets 0.0091 0.0005 0.0143 0.0127Net interest margin 0.0273 0.0147 0.0514 0.0412Noninterest expense to assets 0.0379 0.0302 0.0491 0.0341Noninterest income to total income 0.2785 0.1553 0.2941 0.2388



Table7.UnivariantAnalysisofRatios

Variable

Net

Income

Market

Value

Coeffi

cient

SE

t-stat

Significance

R2

Coeffi

cient

SE

t-stat

Significance

R2

Capitalratio

0.440

0.032

3.97

.000

.303

0.763

0.231

9.29

.000

.616

D

10.166

0.033

1.71

.086

0.091

0.240

1.27

.202

D

20.457

0.034

6.34

.000

0.164

0.244

3.06

.002

D

30.044

0.036

0.68

.496

0.017

0.260

0.36

.716

Loan-to-deposit

0.357

0.003

0.49

.621

.051

0.883

0.032

1.26

.205

.117

D

10.318

0.003

0.48

.626

0.794

0.032

1.26

.207

D

20.121

0.005

1.59

.111

0.195

0.049

2.65

.008

D

30.053

0.003

0.15

.875

0.581

0.032

1.78

.075

Return

onassets

1.623

0.915

17.38

.000

.626

D

10.299

0.957

5.38

.000

D

21.14

0.937

15.75

.000

D

30.095

1.100

2.65

.008

Interest

Margin

0.297

0.062

3.47

.001

.261

0.514

0.477

7.65

.000

.547

D

10.329

0.070

5.53

.000

0.393

0.536

8.43

.000

D

20.109

0.199

2.08

.037

0.035

1.52

0.85

.392

D

30.001

0.066

0.017

.986

0.039

0.505

0.60

.545

NIE

A0.325

0.040

3.04

.002

.296

0.812

0.221

13.53

.000

.769

D

10.256

0.042

3.49

.000

0.203

0.233

4.93

.000

D

20.190

0.042

2.40

.016

0.227

0.230

5.13

.000

D

30.114

0.046

2.10

.036

0.032

0.254

1.05

.291

NIITI

0.090

0.005

2.33

.020

.120

0.227

0.043

6.70

.000

.327

D

10.353

0.008

6.91

.000

0.444

0.068

9.94

.000

D

20.003

0.009

0.075

.940

0.199

0.076

6.22

.000

D

30.155

0.011

2.99

.003

0.071

0.094

1.56

.117

Dependentvariables:net

incomeandmarket

value,

scaledbysquare

rootofassets,respectively.

NIE

A:noninterest

expense

toassets.

NIITI:noninterest

incometo

totalincome.

D5Countrydummy;D

151ifFrance;D

25

1ifGermany;D

35

1iftheUK.


and do not reflect the impact of cross-country institutional factors on

their information content. The interaction terms of these ratios with

country dummies indicate the differences in banks cost function across

the four countries. These differences are not derived from the introduc-

tion of the country classification in the analysis. In contrast, the

significant interactions terms in the second set of market value based

results demonstrate how institutional differences across countries affect

the markets interpretation of the ratios.

The differences between the two sets of univariant tests illustrate how

financial system and banking regulations influence the markets assess-

ment of bank performance through ratio analysis. For example, the

mean capital ratio for France (the United States) is 0.0919 (0.0854)

(Table 6). The significance level of the net income (market value) based

interaction term of capital ratio with France is 0.086 (0.202) (Table 7). A

comparison of the paired results suggests that the markets are indifferent

to the ratio between France and the United States despite their significant

statistical difference. The markets indifference is attributable to the fact

that French banks have more components of capital for meeting the

capital requirements, therefore, reducing the value relevance of the

variable. Another example is the paired results for the loan-to-deposit

ratio. The means for loan-to-deposit ratio for Germany and the United

Kingdom are 0.8385 and 1.8165, respectively, compared with 0.8796 for

the United States (Table 6). While the interaction coefficients of loan-to-

deposit for Germany and the United Kingdom are not significant in the

net income-based regression, both become significant in market value-

based regression, implying that the markets distinguish between the

ratios of Germany and the United Kingdom versus that of the United

States in making pricing decision because the ratio has significantly

different information content in terms of loan portfolio composition and

deposit types across the countries.

Table 8 lists the results of two sets of multiple regression results for

all the ratios combined, with the first (second) set using net income

(market value) as dependent variable. Besides the difference between

the coefficient estimates of the independent variables, the intercept

dummies for France and Germany, which are insignificant in the net

income based model, become highly significant in the market value based

model. This change in significance implies that, while there is no

significant difference in banks cost function between France and

Germany, the markets take banks national identities into account

when interpreting their ratios.




Table8.Multiple

RegressionResultsofRatios

Variable

Net

Income

Market

Value

Coeffi

cient

SE

t-stat

Significance

Coeffi

cient

SE

t-stat

Significnce

Constant

0.007

0.004

1.80

.072

0.058

0.020

2.92

.003

D1

0.017

0.004

2.31

.818

0.200

0.022

4.88

.000

D2

0.141

0.006

1.49

.134

0.238

0.031

4.71

.000

D3

0.025

0.005

0.372

.710

0.041

0.026

1.11

.264

Capitalratio

0.289

0.029

2.90

.004

0.103

0.159

1.81

.070

D

10.026

0.033

0.270

.787

0.075

0.182

1.38

.166

D

21.27

0.035

17.07

.000

0.026

0.204

0.58

.562

D

30.033

0.035

0.523

.601

0.028

0.201

0.77

.442

Loan-to-deposit

0.463

0.002

0.873

.383

1.614

0.013

5.73

.000

D

10.393

0.002

0.821

.412

1.484

0.013

5.83

.000

D

20.215

0.004

3.44

.001

0.169

0.022

5.08

.000

D

30.203

0.002

0.817

.414

0.749

0.013

5.66

.000

Return

onassets

1.476

0.733

19.72

.000

D

10.662

0.795

14.37

.000

D

21.041

0.749

17.94

.000

D

30.322

1.20

8.20

.000

Interest

margin

0.288

0.072

2.91

.004

0.097

0.400

1.71

.086

D

10.040

0.087

0.542

.588

0.068

0.477

1.63

.102

D

20.045

0.172

0.995

.320

0.139

0.899

5.78

.000

D

30.068

0.105

0.517

.605

0.387

0.582

5.22

.000

NIE

A0.175

0.067

0.974

.330

0.441

0.351

4.61

.000

D

10.276

0.072

2.21

.027

0.305

0.376

4.59

.000

D

20.848

0.070

6.39

.000

0.008

0.371

0.11

.910

D

30.050

0.111

0.385

.701

0.196

0.577

2.84

.004

NIITI

0.130

0.007

2.37

.018

0.029

0.039

0.94

.345

D

10.108

0.009

1.81

.070

0.019

0.049

0.57

.564

D

20.374

0.012

7.75

.000

0.050

0.064

1.86

.063



Table8.(C

ontinued.)

Variable

Net

Income

Market

Value

Coeffi

cient

SE

t-stat

Significance

Coeffi

cient

SE

t-stat

Significnce

D

30.022

0.015

0.302

.763

0.026

0.081

0.67

.502

FValue

74.46

374.13

Significance

0.000

0.000

Adjusted

R2

0.525

0.868

Dependentvariables:net

incomeandmarket

value,

scaledbysquare

rootofassets,respectively.

NIE

A:noninterest

expense

toassets.

NIITA:noninterest

incometo

totalincome.

D5countrydummy;D

151ifFrance;D

251ifGermany;D

351iftheUK.


The (lack of) significance of the intercept as well as slope dummies

further illustrate the impact of international difference on the value

relevance of accounting ratios as (missing) captured in the (net income)

market value based model. The adjusted R2 for the net income (market

value) based model is 0.525 (0.868). The considerable increase in the

adjusted R2 for the market value based model provides strong evidence

that markets make significant adjustments for cross-country variations in

accounting ratio analysis, and these adjustments substantially enhances

their value relevance.

4. Conclusion

Previous literature has studied the value relevance of accounting earnings

and book value in relation to managerial discretion based on industrial/

commercial firms. This study investigates how financial system and

banking regulations affect international bank accounting information.

Test results provide empirical evidence that the joint effects of financial

system and banking regulations account for, to a significant degree,

international variation in the information content of bank earnings and

book value across France, Germany, the United Kingdom and United

States. Capital requirements have an impact on the association between

book value components and market valuation. Regulations on bank

operating activities are found to have a significant effect on the associa-

tion of equity price with earnings components. The joint effect of

financial system and banking regulations on the linear information

dynamic for commercial banks is explainable by the objective bank

function model, which shows that earnings of the period determines the

terminal book value, thus consistent with the clean surplus approach. An

understanding of the impact of cross-country institutional difference on

the information content of accounting variables also increases the value

relevance of analytical ratios in comparing bank performance in an

international context.

Notes

1. The central bank governors of the Group of 10 countries established the BasleCommittee on Banking Supervision.2. The acronym CAMEL stands for capital adequacy, asset quality, management

competence, earnings stability and liquidity.3. UK banks have more items in ONI. However, as there are more US than UK banks

in the sample, the test results may be weighted toward US banks.



4. The difference between book value (CC1RC) in Models 1 and 3 can also bestatistically tested. It is (not) statistically different from 1 in Model 1 (3) in accordance tothe theoretical constraints of the clean surplus approach.

References

Ali, A. and L. Hwang, Country-Specific Factors Related to Financial Reporting and theValue Relevance of Accounting Data, Journal of Accounting Research 38 (2000), pp.121.

Ball, R., S. Kothari and A. Robin, The Effect of International Institutional Factors onProperties of Accounting Earnings, Journal of Accounting and Economics 29 (2000),pp. 152.

Barth, J.R., D.E. Nolle and T.N. Rice Commercial Banking Structure, Regulation, andPerformance: An International Comparison, Economic Working Paper 97-6, Office ofthe Comptroller of the Currency, 1997.

Berger, A.N. and D.B. Humphrey, Efficiency of Financial Institutions: internationalSurvey and Directions for Future Research, European Journal of Operational Research98 (1997), pp. 175212.

Bhattacharya, U., H. Daouk andM. Welker, The World Price of Earnings Opacity, TheAccounting Review 78 (2003), pp. 641679.

Brown, L.D. and H.N. Higgins, Managing Earnings Surprises in the US versus 12 OtherCountries, Journal of Accounting and Public Policy 20 (2001), pp. 373398.

Edwards, F. and F. Mishkin The Decline of Traditional Banking: Implications forFinancial Stability and Regulatory Policy, Economic Policy Review, Federal ReserveBank of New York, July, 1995, pp. 2745.

Feltham, G.A. and J.A. Ohlson, Valuation and Clean Surplus Accounting for Operatingand Financial Activities, Contemporary Accounting Research 11 (1995), pp. 689731.

Johnson, S.A., The Effect of Bank Reputation on the Value of Bank Loan Agreements,Journal of Accounting Auditing and Finance 12 (1997), pp. 83100.

Leuz, C., D. Nanda and P.D. Wysocki, Investor Protection and Earnings Management:an International Comparison, Journal of Financial Economics 69 (2003), pp. 505527.

Moyer, S., Capital Adequacy Ratio Regulations and Accounting Choices in CommercialBanks, Journal of Accounting and Economics 13 (1990), pp. 123154.

Ohlson, J.A., Earnings, Book Value, and Dividends in Security Valuation, Contem-porary Accounting Research 11 (1995), pp. 661687.

Pope, P. and M. Walker, International Differences in the Timeliness, Conservatism, andClassification of Earnings, Journal of Accounting Research 37 (1999), pp. 5387.

Rose, J.T. and J.D. Walken Statistical Cost Accounting Models in Banking: AReexamination and an Application, Staff Study 150, Board of Governors of theFederal Reserve System, 1986.

Santomero, A.M., Modeling the Banking Firm, Journal of Money, Credit and Banking 4(1984), pp. 576602.

Stigum, M. and R. Branch Jr., Managing Bank Assets and Liabilities: Strategies for RiskControl and Profit (Homewood, IL: Dow-Jones Irwin, 1983).

Trueman, B., S. Titman and P. Newman, An Explanation for Accounting IncomeSmoothing: discussion, Journal of Accounting Research 26 (1988), pp. 127143.

Wahlen, J.M., The Nature of Information in Commercial Bank Loan Loss Disclosures,The Accounting Review 69 (1994), pp. 455478.

Zhao, R. and Y. He, The Impact of SFAS No. 114 on the Linear Information Dynamicfor Commercial Banks, Review of Quantitative Finance and Accounting 23 (2004), pp.313328.



International Variation

Documents

Transcript of International Variation