Loan loss provision and bank capital management changes under Basel Accord

Zhou Yunxia

Ph.D CandidateFinance and Accounting Department

NUS Business School

March, 2007

Abstract

This paper empirically examines how new capital adequacy regulation under Basel Accord change management manipulation mechanisms of the U.S. banking industry after 1991. I find strong evidence that bank firms are more likely to decrease loan loss provision to manipulate regulatory capital upward when Tier I capital is low, instead of increasing as they did before Basel Accord. On the contrary, they push loan loss provision upward when Tier II capital falls short of threshold, and when loan loss reserve to risk-weighted total assets ratio is at low level. This is the first paper investigate features of both major capital components and their associated capital management incentives separately. The cross-sectional variations of identified new manipulation mechanisms are directly examined as well, as a function of three factors—size, non-audit service purchase level and its variability. Consistent with literature evidences in other industries, high level of non-audit service fees encourage bank firms to involve in capital management more. However, non-audit service purchase of consistent frequency and magnitude (low variability) suppresses manipulation actions. Furthermore, capital management is more prevail in firms of small size (low total assets). All of these evidences provide directional references to improve regulators’ supervision and monitoring efficiency under the Basel Capital Accord.

Key words: Basel Accord; Capital Management; Loan Loss Provision; Non-Audit Service

JEL classification: C80 G10 M41 M42

Email: g0201925@nus.edu.sg. I gratefully acknowledge and thank the comments from my supervisor Professor Michael Shih Sheng-Hua and his dedicated guidance. I also highly appreciate helpful suggestions and comments from my dissertation committee: Edmund K eung and Anand Srinivasan. All errors are mine.

1. Introduction

This paper examines the impact of Basel Capital Accord on managerial manipulation of

United States banks. Previous research so far has only focused on the marginal transition effect of

different capital regulation environments before and after Basel implementation. This paper’s

interest is to provide much more direct and complete evidences of how bank firm managers react

in response to specific capital policy changes in the Basel Accord regime, and to identify capital

manipulation mechanisms changes associated with each major capital components(Tier I and Tier

II capital specifically), and their cross-sectional variations.

Basel Accord is mainly about regulatory capital framework. Capital adequacy ratio is the key

component of this framework and it is defined as percentage of a bank's capital to its highly

standardized risk-weighted assets. Cost of falling short of minimum threshold of capital adequacy

ratio is very substantial. Specifically, banks could be subject to sanctions, termination of federal

insurance or stringent restriction on additional loan deposit and investment. This gives bank

management strong capital management incentives to inflate capital adequacy ratios (see Moyer,

1990; Beatty et al, 1995; Kim and Kross, 1998; Ahmed et al, 1999).Without doubt, it is of

paramount importance to detect their manipulation actions to facilitate more efficient supervision

and monitory of banks and maintain health financial system. However, Moyer (1990) and Beatty

et al (1995) can not provide much information since they only investigate banks’ behavior before

the Basel change in 1988. Although Kim and Kross (1998) and Ahmed et al (1999) studies are

related to capital adequacy policy changes in the new regime, they focus only on the marginal

transition effect of capital regulation regime shift. Given the importance of capital manipulation

detection and inadequacy of literature evidence on that, this paper tried to provide complete

evidence of new capital manipulation mechanisms associated with each Basel capital regulation

changes, and their cross-sectional variations. In addition, this paper takes non-audit service into

consideration, which is a potentially important economic determinant of manipulation incentives

not incorporated in prior capital research works.

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This paper investigates the bank firms’ capital management via loan loss provision 1.Loan loss

provision is a relatively large accrual in banking sector and used as a popular performance

manipulation vehicle. According to Statement of Financial Accounting Standards (SFAS) No.5,

managers can execute judgment in selecting amount and decide timing of loan loss provision.

Furthermore, bank managers have private information of loan portfolios, which are very costly to

be obtained by outside auditors and regulators. Therefore, their discretion on loan loss provisions

can not be easily verified or detected. Moyer (1990) and Beatty et al. (1995) report that bank

firms use loan loss provisions to reduce expected regulatory costs associated with violating

capital requirements.

Prior to 1988, loan loss provision has positive impact on bank firm’s regulatory capitals. Total

regulatory capital before Basel Accord is mainly divided into two parts: primary capital and

supplementary capital. Primary capital consists of two key elements: equity capital and disclosed

reserves (including common stocks, retained earnings, loan loss reserve, perpetual preference

shares and mandatory convertible debt). They are wholly visible in the published accounts and

common to judgments of capital adequacy of all countries’ banking systems. As critical indicator

of profit margins and capacity to compete, they reflect both the quality and level of capital

resources maintained by a bank. Supplementary capital is largely consisting of reserves, general

provisions, hybrid instrument and subordinate term debt. Banks by mandatory must maintain both

primary and total capital ratios above certain minimum requirement levels, in particular, primary

capital ratio must exceed 5.5% and total capital ratio over 6%. The net effect of loan loss

provision on primary capital is the tax shield of loan loss provision since it decreases retained

earnings and increase loan loss reserve, which are two important compositions of primary capital

(see Appendix A for detailed explanation of ratio computation). Therefore, banks with low capital

1 The capital –raising target could also be reached via the security gains and losses, loan charge-offs, capital notes, common stock, preferred stock, and dividends.

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ratios would like to manipulate capital ratios upward via inflation of loan loss provisions (see

Moyer, 1990; Beatty et al, 1995; Kim and Kross, 1998; Ahmed et al, 1999).

U.S banks adopted Basel Capital Accord in 1991. This new capital requirement system

changes the composition and computation of capital adequacy ratios to incorporate underlying

risks that banks face. In particular, loan loss reserve is removed from primary capital and it is

renamed as Tier I capital (mainly equity capital and published reserves from post-tax retained

earnings). Tier II capital is basically the secondary capital under the old regime, however, loan

loss reserve is added with an upper limit of 1.25% of risk-weighted assets. Furthermore, it brings

up the total capital ratio minimum level from of 6% to 8 %( 8% at the end of 1992; from 1988 to

December, 1990, minimum total capital ratio is 7.25%) to be “well –capitalized”. These changes

substantially alter the association between regulatory capitals and loan loss provision, leading us

to make new predictions on bank management behaviors.

Using a sample of 1609 bank holding firm-year observations that file Y-9C reports with the

Federal Reserve from year 2000 to 2005, new capital management evidences in response to

regulation changes under Basel Accord are identified and explained. First, bank managers would

like to reduce loan loss provision (instead of increase as they did prior to 1988) to preserve Tier I

capital ratio. As loan loss reserve is no longer included in Tier I capital, the overall effect of loan

loss provision would be reduction of retained earnings only, that is, there is a positive association

between loan loss provision and Tier I capital since Basel Accord ( see Appendix B for further

explanation). This is totally different from Moyer (1990) and Beatty et al. (1995) which

document a negative relationship under old capital requirement regime. However, the results are

supported by Kim and Kross (1998) and Ahemad et al (1999). Although they did not provide

direct evidences, they find out that banks have lower loan loss provision ever since 1991 relative

to the old regime. Second, opposite to Tier I capital, loan loss provision is negatively related to

Tier II capital. That is, bank firms would engage in capital management via increasing loan loss

provision, and this incentive is particularly strong when loan loss reserve to risk-weighted assets

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ratio is at low level. Under Basel Accord, loan loss reserve is shift from Tier I capital to Tier II

capital. Different from Tier I capital, one unit increase of loan loss provision increases Tier II

capital by the same magnitude. Basel Accord gives bank mangers a new option to reach total

capital requirement level besides Tier I capital since total capital is the sum of Tier I and Tier II

capital. Furthermore, loan loss reserve qualified to be included in Tier II capital is up to 1.25% of

risk-weighted assets. The upper bound definition gives banks with low loan loss reserve stronger

incentive to increase loan loss provision to enjoy the maximum benefit. Bank firms with high

level of loan loss reserve usually have large capital, facing weaker capital management

incentives.

Loan loss provisions are also used for earnings management purpose (Greenawalt and Sinkey,

1988; Beatty et al., 1995; Collins et al, 1995).This earnings management incentive is reexamined

to see if it holds in a more recent time period after controlling significant capital regulatory

changes. Results show a positive relation between loan loss provision and earnings before loan

loss provision and tax (EBTP).This is consistent with prior papers since loan loss provision works

as a pure expense in the profit and loss statement to decrease taxable income. In the old regime,

loan loss provision has opposite effect on earnings and capitals (Although loan loss provision

increase primary capital, doing so would decrease taxable income). Different from that, Basel

Accord makes earnings and capital management incentive consistent, reducing loan loss

provision not only help to maintain Tier I regulatory capital, but also increase taxable income and

smooth reported earnings.

Besides investigation of new capital management mechanisms induced by Basel capital

adequacy rules changes, the cross-sectional variations of the mechanisms as a function of three

factors are also examined, namely, size effect, non-audit service purchase magnitude and its

variability. With respect to size, firms of small total assets are more likely to engage in capital

manipulations via loan loss provision. Higher litigation risk and reputation cost of large firms

constrain big firms’ discretionary actions. Compare to their large counterpart, small banks’

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performance are more volatile while facing the same level of earnings and capital benchmark, and

the strong earnings smooth demand give them high manipulation incentives. Their less

sophisticated internal control systems and incompetent internal auditors also encourage them to

do so.

With respect to non-audit service, consistent with literature evidences in other industries, high

level of non-audit service purchases encourages bank firms to exercise more discretion on

earnings and capitals. Surprisingly, contradictory to the prevailing “economic bond” theory

(providing rents to auditors by non-audit service purchase strengthens the economic bond

between auditee and auditors, which encourage firms to engage in manipulations), I find that

low variability of non-audit service purchase suppress manipulation actions, that is, firms

purchased non-audit services with consistent recurrence frequency and magnitude are less likely

to manipulate performance. This could be the result of Sarbanes-Oxley Act and SEC (2000)2

implementation. Auditor independence becomes a big concern of researchers and regulators, and

quite lots of intervention come out after 2000.Continuous non-audit service purchase does not

only pose more litigation risk to auditors, keep providing rent to auditors give investors

perception of impaired independence and low reporting quality to trigger negative market

reaction to bank firms as a consequence.

The prevail of non-audit service in the same period of Basel Accord implementation motivate

this paper to empirically investigate its impact on bank firms’ manipulation behavior via loan loss

provision after controlling the capital adequacy rules changes. Regulators including the Federal

Reserve are very interested in external audits of institutions it supervises and take auditor’s

opinion as a crucial reference to facilitate their supervision and monitoring. Banks with total

assets of $500 million or more are required by statute to have an external auditor. The benefit

2 After implementation of Sarbanes-Oxley Act, SEC filed “Final Rule: Revision of the Commission's Auditor Independence Requirements” (the “rule”) [File No. S7-13-00] in November 2000, requires firms, starting from February 5, 2001, to disclose non-audit service fees beside audit fees. Detailed definition and contents of non-audit service are described in Audit and Non-Audit Services Pre-Approval Policy.

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derived from an external audit, however, is contingent upon the auditor's competence and

objectivity. It is widely evidenced that non-audit service is associated with observable difference

in earnings quality and reporting proxies, and has adverse effect on earnings quality in many

industries (see DeAngelo 1981; Beck et al. 1988; Magee and Tseng 1990; Francis and Ke, 2001;

Frankel et al 2002; DeFond et al. 2002; Ashbaugh et al, 2003). However, the literature leaves

banking industry untouched. Loan loss provision as a widely used measure for financial reporting

quality in banking industry enables this paper to empirically investigate the association between

non-audit fee and discretion of bank management. However, this paper does not attempt to

investigate whether auditor independence is factually impaired. This stand-alone marginal

analysis can not tell us much about that without comprehensive investigation of detailed

institutional settings and specific audit contracting incentives. Evidence of factual impairments is

very limited in literature due to the fact that auditor independence is not readily observable with

real data, therefore advanced and rigorous models which can probe subjective issues are needed.

Thus I regard this part only as a direct test of association between non-audit service and loan loss

provision. However, the results do provide directional reference to regulators and researchers for

further examinations in auditor independence issues.

This paper contributes to the literature of both capital adequacy regulatory system and loan

loss provision in several ways. First, it identified and explained positive association between loan

loss provision and Tier I capital under Basel Accord. This is a new finding in capital management

literature. Moreover, different from conflicting incentives related to loan loss provision on

capitals and earnings, new capital rules enable bank firms to maintain regulatory capital and

smooth reported earnings at the same time via reducing loan loss provision. Second, Tier II

capital and loan loss reserve ratio are directly examined and the associated management

mechanisms are excavated. These two factors are very important as they are related to major

capital rules changes in Basel Accord and influence bank management choice substantially.

However, they are not examined before. All the above findings enrich our knowledge of the

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effectiveness of Basel Accord and correspondent management behaviors in the new capital

regime. Third, the statistical association between non-audit service and loan loss provision is

analyzed. This is the first time non-audit service issue is investigated in banking industry.

Moreover, different from studies in other industries, the impact of non-audit service purchase

variety is examined as well beside the popular magnitude measure. This provides a new angle for

further experiments on auditor independence issue, especially the effectiveness of SEC rules on

non-audit service disclosure requirements. In a word, findings in this paper shed some lights on

the mechanism and extent of bank management behavior under new Basel capital rules and their

cross-sectional variations, trying to provide valuable reference to regulators for higher monitoring

and supervision oversight efficiency.

Basel Committee on Banking Supervision keeps revising capital rules over years. Besides an

amendment incorporated market risks in 1996, they issued an agreed text and a comprehensive

version of Basel II Framework in June 2004 and July 2006 respectively. Basel II intends to apply

more forward-looking approach to encourage banks to identify the market, credit and operation

risks they may face in the future to facilitate better capital supervision. However, the fundamental

elements of the 1988 Accord are intact. Therefore, results of this paper are still applicable to

banks today.

The next section presents detailed hypothesis tested in this paper, followed by experimental

model design in section 3. Sample and data description are presented in section 4, and results are

discussed in section 5. Section 6 contains closing remarks.

2. Hypotheses Development

This section begins with a discussion on the association between loan loss provision and

banks’ manipulative behaviors. And next, I develop hypotheses on specific capital and earnings

management in the new Basel capital adequacy regime. Finally, I discuss cross-sectional

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variations of management incentives as a function of three factors, size effect, non-audit service

purchase magnitude and its variability.

2.1 Bank manipulation and loan loss provision

Bank loan loss provision is very sensitive to capital and earnings manipulation incentives.

First of all, it is closely related to regulatory capital measures. Loan loss provision is a very

important proxy for default risk, reflecting increase of expected future loan losses level in the

current period. Loan portfolios are typically 10-15 times larger than equity in banking industry,

thus default risk has critical impact on banks’ market valuations, and so does loan loss provision.

More importantly, as a relatively large accrual for commercial banks, loan loss provision has

substantial influence on capital adequacy ratio via loan loss reserve. Capital adequacy ratio is a

very important proxy for bank healthiness and it is defined as percentage of a bank's regulatory

capital to its highly standardized assets. No matter it is before or after the Basel Accord, loan loss

reserve is included in regulatory capitals. In the old regime, it is a paramount component of

primary capital; under the Basel framework, although there is an upper limit, loan loss provision

is still qualified to be included in Tier II capital. Loan loss provision is closely associated to

regulatory capital through its mechanical link to loan loss reserve, one unit increase of loan loss

provision technically increase loan loss reserve by the same magnitude.

Banks must maintain capital ratios above certain minimum required level, for example,

primary capital ratio exceed 5.5% and total capital ratio above 6% in the old capital regime before

Basel Accord. Cost of falling below capital adequacy requirement could be substantial. Moyer

(1990) point out that “because regulators are empowered to restrict bank operations, a bank with

capitals that regulators consider to be inadequate incurs greater regulatory costs than a bank with

adequate capital.” Specifically speaking, banks could be subject to sanctions, termination of

federal insurance or stringent restriction on additional loan deposit and investment, and banks’

growth perspective could be constrained as a consequence. This tremendous cost of capital

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inadequacy gives bank managers high incentive to manipulate capital ratios upward when it falls

short of target level. Because of the inherent association between capital ratio and loan loss

provision mentioned above, loan loss provision is used a popular capital management tool (see

Moyer, 1990; Beatty et al, 1995; Kim and Kross, 1998; Ahmed, Takeda and Thomas, 1999).

Moyer (1990) and Beatty et al. (1995) both document a negative relationship between capital

ratio and loan loss provisions, indicating that banks with low capital ratios would like to

manipulate capital ratios upward via inflating loan loss provision. Both of these two studies

investigate banks’ behavior in the old capital regulation regime when loan loss reserve was still

included in primary capital. One unit increase of loan loss provision decreases retained earnings

by (1-t) unit, t is the tax rate, it increase loan loss reserve by one unit at the same time. The net

effect of loan loss provision on primary capital is to increase it by one unit time t. Basel capital

adequacy framework shift loan loss reserve from primary capital to Tier II capital, and the

management incentives should be changed accordingly.

Besides regulatory capital, loan loss provision is sensitive to bank earnings. Taxable net

income of bank firms can generally be increased by interest income, service revenues, securities

gains and losses, and reduced by interest expense, operating costs, loan loss provision, and

income tax expense. It is difficult for bank managers to significantly change interest income or

expense, service revenues or operating costs during financial periods, neither adjusts them at

year-end. Loan loss provision is the only income component that can be revisable interim and

adjustable at year-end. According to Statement of Financial Accounting Standards (SFAS) No.5,

managers can execute judgment in selecting amount and decide timing of loan loss provision.

This special feature makes it a natural choice of bank managers’ earnings discretion. $1 reduction

in loan loss provision can successfully increase net income after tax by $1* (1-t), t is the tax rate.

This mechanism is reflected in positive relation between loan loss provisions and earnings (before

loan loss provisions) in many prior empirical studies (see Greenawalt and Sinkey, 1988; Beatty et

al., 1995; Collins et al, 1995).

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Loan loss provision is not only sensitive to capital and earnings measures, it is also highly

manageable. First, bank managers’ judgments and discretion are necessary in estimating the loan

loss provision each period, and can not possibly be removed or replaced. Second, they have their

own private information regarding default risk inherent in loan portfolio which are not accessible

or can not be obtained without high cost by outsiders, thus investors and regulators can hardly

verify the validity of the managers’ loan loss provision decision. In other words, loan loss

provision can be used as a manipulation vehicle by bank management to reach their desired

results and without much detection risk within short period.

2.2 Capital management

Capital adequacy framework begins a new regime in 1988. Before that, each nation has its own

regulatory policies and capital rules to regulate banks and depository institutions. Basel

Committee on Banking Supervision introduced a new capital measurement system for the

purpose of international convergence of capital measures and capital standards in 1988, which is

commonly referred as Basel Capital Accord. United States started to implement Basel Accord in

1991 through issuance of Federal Deposit Insurance Corporation Improvement Act of 19913 and

it is supervised by Board of Governors of the Federal Reserve System (FRB), Office of the

Comptroller of the Currency (OCC) and Federal Deposit Insurance Corporation (FDIC). This

new capital system seeks to improve existing rules by aligning regulatory capital requirements

more closely to the underlying risks that banks face, and incorporates assets risk weights and off-

balance activities into consideration4.More importantly, it changes the composition and

3 Federal Deposit Insurance Corporation Improvement Act of 1991 started the implementation of new capital adequacy framework in 1991,and 1990 is a transitional year, banks in U.S can choose to conform to the old system or to the new one.4 1988 Basel Accord is mainly designed to assessing capital in relation to credit risk. Supervision institutions are trying to deal with other risks, for example, interest rate risk, operation risk and investment risk in further development of Basel Accord. Furthermore, the relative strength of capital also depends on the quality of a bank’s assets and off-balance sheet exposure. Therefore, risk-weighted assets are designed to be in the denominator of capital ratios. In order to be simple and easy to implement, the framework of weights are designed in a broad-brush basis, only five weights are used, 0, 10, 20, 50 and 100%.

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computation of capital ratios. In particular, total capital is divides into Tier I capital and Tier II

capital. Tier I capital represents shareholders' funds in a bank, that is, their share of the bank's

assets after all debts have been repaid to creditors. Basically it is defined as sum of shareholder’s

equity, non-cumulative perpetual preference stock and minority interests. Different from primary

capital composition prior to 1991, loan loss reserve is removed from Tier I capital. Instead, it

counts an important component of Tier II capital. Under the new regime, Tier II capital is defined

as a sum of loan loss reserve (up to 1.25% of risk-weighted assets), preference shares, hybrid

capital instrument, subordinate term debt and perpetual debt. The minimum capital requirement

level is changed as well. In the 1991 new capital regulation framework, banks must at least

maintain 4% of Tier I capital ratio and 8% of total capital ratio to be “well –capitalized”, instead

of the primary capital ratio exceed 5.5% and total capital ratio over 6% requirement in the old

regime. These capital ratios are reviewed regularly on the Call Report or Thrift Financial Report.

Moreover, bank firms are required to do “Capital Adequacy Quantitative Disclosures” on a

consolidated basis, that is, to disclose total and Tier I capital ratios not only for the top bank

group, but for significant bank subsidiaries as well(stand alone or sub-consolidated depending on

how the framework is applied).

It is worth investigating how bank managers adjust their manipulation mechanisms in response

to the above policy changes under Basel Accord. First, the relationship between loan loss

provision and Tier I capital is different that of primary capital. Loan loss provision decreases Tier

I capital (instead of increasing primary capital in the old regime) since 1991. As loan loss reserve

is no longer included in Tier I capital, the overall effect of $1 loan loss provision increase would

be reduction of retained earnings by $1 (1-t). This leads us to predict a positive relationship

between loan loss provisions and Tier I capital, that is, bank managers would like to preserve Tier

I capital by reducing loan loss provision when regulatory capital level is low. This is totally

different from Moyer (1990) and Beatty et al (1995) which document a negative relationship

under the old capital requirement regime. However, it is partially supported by indirect evidences

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from Kim and Kross(1998) and Ahemad et al (1999). They find that although loan loss provision

still have positive effect on capitals, banks with low capital ratios have lower loan loss provisions

after Basel capital requirement implemented.

Second, Basel rules give bank managers a new option for total capital management, Tier II

capital. Beside 4% of Tier I capital ratio, banks are required to meet the minimum 8% level of

total capital threshold. Total capital is sum of Tier I and Tier II capital. Under Basel capital

regulation system, although removed from Tier I capital, loan loss reserve still counts as an

important part of Tier II capital5. Due to the mechanical link between loan loss provision and loan

loss reserve, one unit increase of loan loss provision increases Tier II capital at the same

magnitude. Firms with low Tier II capitals can still reach total capital requirement via inflating

loan loss provisions, therefore a negative relation between loan loss provision and Tier II capital

is expected. Benefit of this manipulation would be maximized if a bank’s loan loss reserve level

is low. It is required in the Basel Accord that the amount of: loan loss reserve qualified to be

included in Tier II capital is limited up to 1.25% of risk-weighted assets. Firms with loan loss

reserve below this upper bound are more likely to engage in Tier II capital management. On the

contrary, firms with high loan loss reserve generally have high capital; therefore their capital

management incentives are reduced.

The above hypotheses are summarized and stated in alternative forms as follows:

H1.a: Tier I capital and loan loss provision (as a fraction of average total loan) are positively associated in Basel capital regime.

H1.b: Tier II capital and loan loss provision (as a fraction of average total loan) are negatively associated in Basel capital regime.

H1.c: Loan loss reserve to risk-adjusted assets ratio and loan loss provision (as a fraction of average total loan) are negatively associated in Basel Capital regime.

5 Basel Capital Accord 1998 April version:”General provisions or general loan-loss reserves are created against the possibility of losses not yet identified. Where they do not reflect a known deterioration in the valuation of particular assets, these reserves qualify for inclusion in tier 2 capital. Where, however, provisions or reserves have been created against identified losses or in respect of an identified deterioration in the value of any asset or group of subsets of assets, …….should therefore not be included in the capital base”

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2.3 Earnings management

Loan loss provision is sensitive to bank earnings measure and highly manageable. As

mentioned, loan loss provision is the only income component that can be revisable interim and

adjustable at year-end. According to Statement of Financial Accounting Standards (SFAS) No.5,

managers can execute judgment in selecting amount and decide timing of loan loss provision.

Furthermore, outsider auditors and regulators have difficulty to obtain and examine the private

information of loan portfolios bank managers have, thus bank managers’ loan loss provision

decision can not be easily verified or justified. This special feature makes it a natural choice of

bank managers’ earnings discretion. Different from capital management context, loan loss

provision purely works as an expense to decrease taxable income in profit and loss statement. $1

reduction in loan loss provision can successfully increase net income after tax by $1* (1-t), t is

the tax rate. Bank firms therefore would smooth reporting earnings via exercising discretion on

the magnitude and timing of loan loss provision. Both Greenawalt and Sinkey (1988) and Collins

et al. (1995) find positive relation between loan loss provision and reported earnings, implying

that firms with poor real earnings performance generally record less loan loss provision to inflate

reported earnings.

I expect to observe a significant positive relation between real earning and loan loss

provision. Firms with lower the real earnings are more likely to decrease loan loss provision.

Besides the mechanical negative impact of loan loss provision on earnings, new Basel capital

rules strengthen the above manipulation incentive. Under the Basel capital framework, earnings

management incentive becomes consistent with capital incentive, that is, firms can manipulation

earnings upward without worrying capital decrease as they did in the old regime. Earning before

loan loss provision and tax (EBTP) is used as real earning proxy. In addition, in order to test

whether bank firms have different management incentives under low earnings or complete loss

circumstances, an alternative variable, LOSS, is used. It represents negative earnings before loan

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loss provision and tax. Firms with pure loss have strong incentive to manipulate their earnings

across above the zero benchmark. Hypothesis related to earnings manipulation could be described

as:

H2: Earnings before loan loss provision and tax (or loss) and loan loss provision are positively associated in Basel capital regime.

2.4 Non-audit service purchase level and its variability

Non-audit service purchase prevails in the same period of Basel Accord implementation, and

this motivate this paper to empirically investigate its impact on bank firms’ manipulation

behavior via loan loss provision after controlling the capital adequacy rules changes. According

to SEC reports, non-audit service purchase substantially increased since the 1990s. During 1990s,

proportion of corporations purchased non-audit service increased significantly, from 25% in 1991

to 96% in 2000. Non-audit service fee typically makes up to 51% more than auditor service fee

(see Abbott et al. 2003). Auditor independence received the highest attention it ever had from the

public investors and researchers since then. Quite many papers have been done to investigate the

impact of non-audit service provision on financial reporting quality and auditor independence.

The results, however, are quite mixed (Exhibit 2). Some research find negative association

between non-audit service provision and discretionary performance measures, that is, the more

non-audit service a firm purchased, the lower financial reporting quality it has. This is mainly

explained by two schools of theories. First, agency theory characterizes auditor bias as deliberate.

It is believed that provision of non-audit service from auditors to auditees generates substantial

revenue besides regular audit service and aligns the two parties closely. This economic bond

increases auditor’s incentive to acquiesce to client pressure, including deliberately allowing

earnings management, which seriously impairs auditor objectivity, and affect the quality and

credibility of the financial information as a consequence (Simunic 1984; Beck et al. 1988a).

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Second, in contrast to agency theory, behavioral literature suggests that psychological heuristics

may unconsciously lead auditors to biased judgments (see Beeler and Hunton, 2001). Some

studies find no association between non-audit service fee and discretionary accrual. They believe

that auditors are unlikely to jeopardize their reputation to attain clients since it takes many years

and tremendous effort to build reputation in the market (see Arrun˜ada 1999). In view of

increasing public concern of auditor independence and inconsistent literature research results,

SEC issued Final Rule of Revision of the Commission's Auditor Independence Requirements (the

“rule”) [File No. S7-13-00] (Exhibit 1) in November 2000. This rule requires firms, starting from

February 5, 2001, to disclose all detailed audit fees information in recent years. To date, the

effectiveness of the rules is not examined empirically.

No matter what auditors’ incentives are, no factual evidence of auditor independence

impairment or effectiveness of SEC non-audit fee disclosure regulations can be accurately

obtained when they are studied in isolation with specific industrial context and comprehensive

audit contracting. Banking industry in the new Basel regime provides us a good experimental

environment on this research topic. First of all, capital and earnings management incentives and

relevant manipulation mechanisms can be clearly identified and tested. Second, loan loss

provision is banking industry context better satisfies two critical criteria which make it a good

accrual measure in manipulation detection models. Although it is still a controversial question

whether the generally accepted accounting principle (GAAP) is violated for firms heavily

purchase non-audit service, literature papers do provide evidences that non-audit service is

associated with observable difference in earnings quality proxies (see DeAngelo 1981; Beck et al.

1988; Magee and Tseng 1990; Francis and Ke, 2001; Frankel et al 2002; DeFond et al. 2002;

Ashbaugh et al, 2003). Loan loss provision is one widely used measure for capital and earnings

quality in banking context and very sensitive to hypothesized discretionary behaviors, which is

discussed in the beginning of this section. An empirically association between non-audit service

fee and loan loss provision is expected. Second, nondiscretionary components of loan loss

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provision is readily developed, as researchers can rely on generally accepted accounting

principles (GAAP) to understand what fundamentals should be reflected in the account in absence

of management manipulation, which enables researchers to make a reasonably accurate prediction

about the frequency of earnings realization not caused by its nondiscretionary components

(Scholes et al 1990).The through understanding of specific manipulation mechanisms and better

experimental design enable us to find evidences on these important issues with less bias. More

importantly, non-audit service has never been studied in banking industry context before, thus the

research in this paper can enrich our industry-specific knowledge on this topic. Same as other

industries, follow agency theory, we hypothesize that non-audit service purchase can increase

firms’ management incentives, that is ,bank firms purchased high level of non-audit service are

more likely to engage in capital or earnings management compare to the firms with less non-audit

service purchase.

Besides absolute non-audit service purchase magnitude, variability of non-audit service

purchase is also expected to affect bank management behaviors. Variability refers to variance of

both purchase frequency and magnitude here. In recent years not only more companies purchase

non-audit service from incumbent auditors, frequency and magnitude of non-audit service

demand also vary vastly across different companies; even for the same firm, frequency and

magnitude of purchase could be largely volatile from year to year. As variability could be an

important proxy for the tightness of economic bond between auditors and bank firms,

manipulation incentives should be hugely different between firms who consume non-audit service

regularly and consistently and those who only purchase sparsely. However, I do not have clear

prior prediction of the direction of the association between non-audit service purchase variability

and banks management behavior. There are two possibilities. First, consistent non-audit service

provision may encourage bank firms for more manipulation engagement. Beck et al (1988) find

that economic bond between auditor and clients are much stronger when non-audit service

revenue is recurring, and can be explained by auditors’ high start-up and switching cost. In the

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study of relation between agency incentive and non-audit service purchase, Parkash and Venable

(1993) find that auditee’s purchase of recurring non-audit service is highly influenced by agency

incentives and recurred services are perceived as steady annuity of auditors. On the other hand,

regular purchase may constrain management actions. Since year 2001, auditor independence has

been a big public consideration and the expected monitoring value of audit is assumed lowered by

the market. Furthermore, market reacts very negatively to firms with high non-audit fee whenever

they “perceive “it a representation of low audit quality (JERE .R, 2006). As a result, many

legislative interventions come out aimed at restricting non-audit service supply. Continuous and

consistent non-audit service provision would not only pose high litigation risk to auditors because

of potential independence impairment, regularly providing rents to incumbent auditors can also

intrigue negative stock market reaction to auditees due to the perceived dishonesty or low quality

of their financial reporting . Firm-specific standard deviation of non-audit service fee over sample

period is used as a proxy for non-audit service purchase variability6, the lower standard deviation

is, the more consistent non-audit service purchase behaviors is.

The hypotheses related to non-audit service purchase level and its variability is summarized in

the alternative form as follows:

H3.a: Bank firms with high level of non-audit service purchase are likely to have: 1) more negative association between loan loss provision and Tier I capital; 2) more positive association between loan loss provision and Tier II capital; 3)more negative association between loan loss provision and earnings than firms with less non- audit service purchase

H3.b: Bank firms with low variability of non-audit service purchase are more(less) likely to have 1)negative association between loan loss provision and Tier I capital; 2) positive association between loan loss provision and Tier II capital; 3)negative association between loan loss provision and earnings

6 Although the SEC (2003) prohibit registrants from purchasing financial information systems design and implementation services and internal audit outsourcing from incumbent auditor, this does not affect data consistency over sample period. Registrants may still purchase many types of non-audit services, including tax compliance and consulting, employee plan audits, consulting on accounting matters, merger and acquisition consulting, and consulting on new debt and equity issues.

- 17 -

2.5 Size matters

It is also important and meaningful to investigate size effect under Basel Accord. Firms of

different sizes have different capital and earnings management incentives. Manipulation

behaviors of large firms are widely documented in prior papers (see Rangan, 1998; Myers and

Skinner, 2000).This could be explained by higher pressure they face to meet or beat analysts'

expectations since market punishes them more severely for loss or falling below expectations

than small firms( Barton and Simko, 2002). On the other hand, large-size firms’ manipulation

incentives could be constrained by huge reputation cost and litigation risk. Being caught of

manipulation would substantially diminish their years of effort to establish their credibility and

reputation social responsibility and high quality of financial information in business community.

Their litigation risk is much higher than small firms as well (see Bonner et al, 1998; Kellogg,

1984; Lys and Watts, 1994; Stice, 1991). Besides reputation and litigation constraints, great

bargaining power they possess can lower their manipulation incentives. Bishop (1996) argues that

large banks could continually violate capital adequacy requirements without provoking regulatory

intervention (“too big to fail” hypothesis).

Similarly, current literature has opposing views on manipulations incentives of small bank

firms as well. First of all, small firms’ performances are more volatile than their large size

counterparts, thus they have higher manipulation demand to achieve smooth performance. Due to

small production scale and lack of diversification, small firm usually suffer a larger degree of loss

for the same level of adverse change in external market environment than large firms do. Besides,

low audit efficiency and lack of necessary information induce extra difficulty for manipulation

detection. Usually small banks have less sophisticated internal control systems and less

competent internal auditors than large-size bank firms. On the other hand, small bank firms may

subject to stricter oversight by federal regulators and market investors, suggesting discretionary

behaviors are less likely. Based on above analysis, I do not have clear prior directional prediction

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of size impact on capital or earnings management incentives after 1991.The hypothesis stated in

alternative form as:

H4: Bank firms of small total assets are more(less) likely to have: 1) negative association between loan loss provision and Tier I capital; 2) positive association between loan loss provision and Tier II capital; 3) negative association between loan loss provision and earnings than large-size bank firms

3. Model Design and Specification Management manipulations are widely found and documented in the highly regulated banking

industry. However, different from other industries, banks management does not have many

private contract incentives, for example, bonus plans, debt agreements, cost of capital and other

contracts. Smith and Watts (1986) report only 67% of banks have accounting-based bonus plans,

while the percentage is as high as 91% in other unregulated industries, and cost of capital does

not impact accounting choices much neither. Based on a sample of commercial banks, Moyer

(1988) finds no association between accounting adjustments and dividend covenants. All the

empirical evidence indicate private contracts incentives possibly do not influence bank manager’s

accounting choices as much as they do in other industries, which makes the manipulation

detection modeling more straightforward and efficient. The most recognized manipulation

incentives in banking industry are regulatory capital and earnings (see Greenawalt and Sinkey,

1988; Moyer, 1990; Beatty et al., 1995; Collins et al, 1995). Capital managements are driven by

capital adequacy requirements, which set frameworks on how banks and depository institutions

must handle their capitals. Basically it requires the ratios of regulatory capital to highly

standardized assets to be maintained above certain minimum level. Bank firms also face pressures

from investors and regulatory institutions about their profit numbers and balance sheet

appearance. Punishment of falling short of either regulatory capital or earnings targets can be

very detrimental to the growth perspective of bank firms. The substantial cost induces

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management incentives, and both capital and earnings manipulation can be achieved via

discretionary loan loss provision.

Basic experimental model is designed based on above discussion. First, for the capital

management incentive, Tier I capital and Tier II capital proxy are used (T1C, T2C).In the old

capital regime setting, Tier II capital is not related loan loss provision. Basel capital rules shift

loan loss reserve from Tier I capital to Tier II capital, by which Tier II capital becomes a new

option of capital management under Basel Accord. Tier I capital is still related to loan loss

provision, but it has totally different management mechanism from Tier II capital. Tier I and Tier

II capital are therefore studied separately. Second, earnings manipulation incentive is represented

by one real earning proxy--earnings before taxes and loan loss provision deflated by total assets

(EBTP). If bank firms smooth earnings via loan loss provision, we expect to observe a positive

relationship between loan loss provision and EBTP. In addition, in order to examine whether

bank managers behavior differently when banks perform poorly or when there is a pure loss

incurred, another variable is used. Negative earning before taxes and loan loss provision (LOSS)

is added to capture the difference. Fourth, although loan loss reserve is included in Tier II capital

under the new regime, it is limited up to 1.25% of risk-weighted assets. This encourages banks

with low loan loss reserve levels to involve in capital management. The benefit of manipulation

for banks with loan loss reserve exceed the upper bound is not maximized, and usually, banks

with large amount of loan loss reserve have high capital level. The ratio of loan loss reserve

before loan loss provision of current year to risk-weighted assets (LLR) is used to capture the

significant impact of loan loss reserve level on capital manipulation.

(1) Where T1C Ratio of Tier I capital before loan loss provision to risk-weighted total assets T2C Ratio of Tier II capital before loan loss provision to risk-weighted total assets LLR Ratio of Loan Loss Reserve loan loss provision to risk-weighted total assets EBTP Earnings before taxes and loan loss provision/average total assets

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LOSS Negative earnings before taxes and loan loss provision/average total assets LEVERAG Ratio of total liability to average total assets

Besides above basic incentive variables, two more additional variables are included. First,

prior studies show that discretionary accruals are generally associated with leverage level (see

DeFond and Jiambalvo 1994; DeAngelo et al. 1994; Becker et al. 1998).Although the findings are

based on samples from industries other than banking, it is worthwhile to examine the relationship

between leverage level and loan loss provision since leverage is also an important performance

indictors for banks. To achieve this, total liability to total asset ratio (LEVERAGE) is included in

the regression. Second, the different impact of Big-5 and non Big-5 auditors on bank

management behaviors is considered as well. Becker et al (1998) and Francis et al (1999)

conclude that Big-5 auditing firms usually report lower level of discretionary accruals than non-

Big 5 firms while they report higher level of total accruals. Gore et al. (2001) also directly claim

that non-Big 5 auditors allow more earnings management, and they do not find any significant

statistical association between several manipulation proxies and fees charged by their Big-5

counterparts. The conservative behavior of Big-5 firms could possibly be explained by high

litigation risk and adverse reputation effect they may face. Big auditors with substantial number

of clients have “more to lose” if their reputation is ruined by helping or failing to report detected

misbehaviors in a particular clients financial records (see DeAngelo, 1981; Reynolds and Francis,

2000). BigFive, a dummy variable which equals one if the auditor is one of the big five auditors,

is used to test whether it is still true in the banking industry that Big 5 auditors are generally

related to higher financial reporting qualities. This is a very interesting issue to investigate,

because among all industries, only banking has extra capital targets to reach besides the popular

earnings benchmarks. Furthermore, Tier I capital (the primary component of total capital) and

earnings management incentive become consistent starting from the Basel Accord, and this, gives

bank managers more incentive to “bribe” auditors by providing” bigger rent”. In other words,

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although Big 5 auditors have “more to lose” by hiding detected misbehaviors, they have “more to

gain” in the banking industry at the same time.

One common way to “bribe” auditors is non-audit service purchase. The impact of both the

level (HNAF) and variety (VAR) of non-audit purchase on bank management manipulation

mechanisms are tested as conditional variables, as they are defined in the hypothesis section.

Moreover, size effect (SIZE) is also examined. These variables are added into the basic

regression model as formula (2) demonstrated (uses HNAF as an illustration), to reflect the cross-

sectional variations of banks’ earnings and capital manipulations as a function of the above three

variables. As stated in the hypothesis development part, I expect firms purchase higher level of

non-audit service to be more likely to manipulate their earnings and capital ratios upward to their

desired level, compared to those firms with less non-audit service purchase. However, I do not

have clear prior prediction of the impact of non-audit service purchase variability and size effect.

(2)

Same as Kim and Kross(1998) and Ahemad et al (1999), Tier I capital and Tier II capital are

capitals after adjustment. All capital data download from databases are only the capital reported

by the bank manager after possible loan loss provision manipulation, adjustment is needed in

order to avoid mechanical link between dependent variable and capitals. However, our

adjustments are made in different ways. I start from reported capitals in Y9-C report

(Consolidated Financial Statements for Bank Holding Companies—FR Y-9C) instead of the

capital ratios as they did. Adjusted Tier I capital ratio= [reported Tier I capital (BHCK8274) + (1-

T)* LLP (BHCK 4230)]/total risk-weighted assets (item 62), and adjusted Tier II capital ratio=

[reported Tier II capital (BHCK 8275)-LLR (BHCK5310)]/total risk-weighted assets (item 62), T

is the tax rate. There are two things to be clarified about the capital ratios computation. First thing

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is about the tax rate. Y9-C does not report the tax rate for each firm in each specific fiscal year,

only the total tax expense is presented. For the purpose of calculation, I follow Kim and Kross

(1998) and assume a universal tax rate of 34%. To get more accurate results, I plan to use item 8

(income before tax and extraordinary items) and item 9(applicable income tax) in the income

statement to calculate the yearly tax rate for each firm. However, I expect the result to be similar.

Second, according to Basel Accord, bank firms can choose to deduct the amount LLR exceeding

1.25% of risk –weighted assets from denominator when calculate Tier I capital or Tier II capital

ratio. The denominator reported in Y9-C is actually the total risk-weighted assets (item 62) after

possible LLR adjustments. That is, denominators are also need to be adjusted if a bank’s LLR is

larger than 1.25% of risk-weighted assets after possible LLP discretion and the firm chooses to

use this to reduce denominator in order to inflate capital ratios. However, after careful scrutiny in

the test sample, I find LLR before loan loss provision in this sample are mostly lower than the

upper limit, specifically, the mean is 1.1% and median is 0.09% of risk-weighted assets.

DLLP in the above two regressions is discretionary loan loss provisions. Compare to financial

reporting quality proxies in other non-banking industries, loan loss provision better satisfies two

critical criteria which make it a good measure of manipulation behaviors. First, it is very sensitive

to hypothesized discretionary behaviors, in particular, earnings and capital managements which

are discussed in section two. Second, nondiscretionary components of loan loss provision are

readily developed in banking context. As researchers can rely on generally accepted accounting

principles (GAAP) to understand what fundamentals should be reflected in the accounts in

absence of management manipulation, they can make a reasonably accurate prediction about loan

loss provision realizations which are not caused by its nondiscretionary components. These non-

discretionary loan loss provision components should reflect sound credit risk assessment and loan

portfolio valuation. Based on this, I follow Beatty et al (2002) to regress loan loss provision on a

series of loan portfolio characteristics variables identified under GAAP:

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(3)

The size effect, region effect and specific function of loans are controlled in the regression. I pool

across all bank-years with available data, and the regression residuals are used as discretionary

loan loss provision (DLLP), the proxy for financial information quality in our sample.

4. Sample and Data Description

I use 1609 bank holding firm-year observations over the period of 2001-2005. Each firm has at

least four years data. All firms are with the SIC code 6021 and 6022, and have December 31

Fiscal year-end. Bank firms with Merger and Acquisitions activities over the sample period are

removed since these events increase expected demands for both audit and consulting services.

Gunther and Moore (2003) investigated regulator mandated revisions instances in loan loss

provisions and found out that only six in their study involve banks with over $500 million in total

assets. Bank firms in our sample all have total assets over $500 million so that the loan loss

provision determination and analysis by the management are tacitly allowed by regulators.

Besides, to be included in the sample, banks firms must have complete data from following data

sources as well:

CFRB of FRBC7 : loan portfolio variables needed for loan loss provision regression

for banking holding firms

7 Federal Reserve Bank website of Chicago

- 24 -

LOSS =

= LASSET = LLR =

LOANR =

LOANC =

LOAND =

LOANA =

LOANI =

LOANF =

loan loss provision deflated by the average of beginning and ending total loans;Change in nonperforming loans deflated by the average of beginning and ending total loans;natural log of total asset;loan loss reserve deflated by the total loans at the beginning of the year;loans secured by real estate deflated by total loans;commercial and industrial loans deflated by total loans;loans to depository institutions deflated by total loans;loans to finance agricultural production deflated by total loans;loans to individuals deflated by total loans;loans to foreign government deflated by total loans

EDGAR8: DEF 14A proxy statement for auditor fee matrix data and 10-k for non-

performing loan data

Compuastat: all other control variables

According to SEC rule (2000), Section II.C.5, firms are required to disclose audit service fee,

financial information system design and implementation fees (IS in short) 9 and “All other fees”

(Exhibit 1). Sum of IS fee and all other fees are considered as non-audit service fee. Descriptive

statistics in Table 1 indicate that average (median) non-audit fee ratio is 29.27 %( 26.31%), much

lower than those of audit service fee ratio of 70.73 %%( 73.69%). This is different from extant

literature findings, which show that the proportion of non-audit service makes up more than 50%

of total fee since late 1990s.This maybe is caused by stringent regulatory and monitoring systems

specific to the banking industry. Panel B of Table 1 shows that, three components of non-audit

service are evenly distributed, that is, average amount of audit-related fee, tax service fee and all

other fee is around 10% of total fee respectively. This is also different from other industries.

Generally, some non-audit service are less recurring than other single engagement, for example,

merger and acquisition service and consulting on new debt and equity issues, and some are more

recurring, for example, audit-related service, and tax service. Especially in recent years, more

firms purchase a high portion of tax service as non-audit service, aiming to save tax expenses via

lower taxable earnings. Table 2 reports descriptive statistics comparison of fees composition

between Big5 auditors and non-Big5 auditors (All fees are in thousands of dollars). Total number

of observations is 828 for Big5 firms and 781 for non-Big5 firms. Therefore, our results will not

be biased by sample construction bias. The average total fee charged by the Big4 auditors is

2083.18 thousands, much higher than that charged by non-Big5 auditors (167.18 thousands).

Possible explanation would be that big-five firms charge fee premiums for non-audit service as

8 EDGAR: SEC Filings and Forms9 Required by Sarbanes-Oxley Act of 2002(July 30, 2002), audit firms are prohibited from providing services such as financial information system implementation and design, internal auditing, and a number of other services

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well as audit service based on their recognized industry specializations, high audit quality and

general brand name. Non-audit fee ratio of non-Big5 firms (28.45%) is slightly lower than that of

Big-five firms (30.04%), but the magnitude of difference is not significant. However, they are far

larger than the previous level (10%) reported by SEC (2000)10. The substantial increase of non-

audit service as an important revenue source of auditor firms poses threats to auditor

independence.

Table 3 presents time-series analysis of audit fees and ratios from year 2001 to year 2005. The

median data of full sample, Big-Five firm sample and Non-Big-Five firm sample are reported in

Panel A, B and C respectively. Generally, non-audit service fee ratio decreases over the years

from 2001 to 2005, and the decrease becomes substantial starting from 2003. I suspect this is not

caused by the effect of SEC 2000 detailed audit fee disclosure rule, as evidenced by significant

relations between non-audit service fee and discretionary loan loss provision in results part. On

the contrary, it may due to huge increase of audit fee caused by the Sarbanes-Oxley Act of 2002.

SOA expanded SEC 2000 rule and requires companies to include any fees for services performed

to fulfill the accountant’s responsibility under GAAS in the “audit fees” category, instead of just

the fees paid for audits and quarterly reviews. Besides that, SOA removed quite many services

from “non-audit service” category, for example, financial information system implementation and

design, and a number of other services. Therefore our time-series results remind researchers to

interpret the non-audit service fee ratio decrease with caution. It may not necessary due to the

effectiveness of SEC 2000 rule although I can not fully exclude its influence.

Loan is a major asset of banks. The total loan to total asset ratio in our sample has a mean

(median) of 66.28 %( 67.45%). Untabulated table shows that mean (median) ratio of loan loss

provision to average total loan is 0.39 %(0.29%), and mean (median) ratio of loan loss provision

to earnings before loan loss provision and tax is as high as 15.85 %(11.05%). Thus, loan loss

10 In SEC (2000) report, the 1999 data shows that non-audit fee is only 10% of total fee, and only 75% of firms purchase non-audit service.

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provision is a substantially important accrual for banks. Table 4 presents descriptive statistics of

regression variables for 1609 bank holding firm-year observations from year 2001 to year 2005.

All bank firms file Y-9C reports with the Federal Reserve and disclose audit data in EDGER. On

average, the reported Tier I capital before loan loss provision is 12.429%, much higher than the

minimum 4% level required under the 1991 new capital regulation. This suggests that bank firms

in our sample are well-capitalized. The means of Tier II capital and loan loss reserve ratios are

1.260% and 1.10%respectivley. Moreover, mean ratio of earnings before tax and loan loss

provision to total asset (EBTP) is 6.9% and the mean return on asset (ROA) is 1.1%. These

magnitudes are consistent with what documented in prior studies in literature.

5. Empirical Results

Table 5 presents evidences of new earnings and capital management mechanisms of bank

firms under Basel Accord. Consistent with the basic hypothesis that loan loss provision decreases

Tier I capital under the new regime instead of increasing as it does before 1991, I find a

significantly positive coefficient of TIC(0.0003, two-tailed p- vale 0.00). That is, firms with low

Tier I capital would like to decrease loan loss provision to reach capital adequacy requirement.

This finding is different from Ahemad et al (1999), which find a negative coefficient on Tier I

capital (CAPB, pg12).I think this discrepancy is caused by sample difference. Ahemad et al

(1999)‘s sample period is from 1986 to 1995, which covers both regimes before and after Basel

Accord. However, the interaction term CAPB*REG (REG equals one if the data is from the new

capital regime) is significantly positive, verified the results in this paper in an indirect manner.

Furthermore, Kim and Kross(1998) use a test sample similar to Ahemad et al (1999) with sample

period of 1985 to 1992, they do find that banks with low capital ratios have a lower loan loss

provision under Basel Accord regime. Although many papers investigated the impact of capital

adequacy regulation changes, this paper is the first one using all-new-regime data to provide

direct bank manipulations mechanism evidences under Basel Accord.

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Basel Accord changes have impact on Tier II capital as well. Under the new regime, loan loss

reserve is shift from Tier I capital to Tier II capital, that is, one unit increase of loan loss

provision can increase the Tier II capital by one unit. This new regulation manifests itself by a

significant negative coefficient of T2C (-0.0002, two-tailed p-value, 0.00) in table 5. Therefore,

different from loan loss provision’s negative effect on Tier I capital, firms are more likely to

manipulate loan loss provision upward when Tier II capital is at low level. However, loan loss

reserve in Tier II capital is restricted to an upper bound. Under Basel Accord, loan loss reserve

includable in Tier I capital must be lower than 1.25% of risk-weighted total assets. Therefore,

banks with loan loss reserve under that threshold would have more capital management incentive

than firms with high loan loss reserve. LLR variable, ratio of loan loss reserve before loan loss

provision at year end is used to capture different manipulation mechanisms for firms with

different loan loss reserve level. The result is consistent with the above hypothesis. Specifically,

LLR has a negative coefficient, and significant at 5%level (-0.0102, two-tailed p-value, 0.00).

Consistent with literature evidence, earning management behavior also manifests itself by a

significant positive coefficient of EBTP (0.0003, two-tailed p-value, 0.01), suggesting that firms

with poor earnings performance prefer to decrease loan loss provision. This could be easily

explained since loan loss provision works as a pure expense in the income statement to decrease

the taxable income under Basel Accord. The variable LOSS, however, does not have explanatory

power. It could be mostly likely due to the specific banking industry context of this paper. Under

common circumstances, banks firms are less likely to have negative earnings than firms in other

industries. After carefully examination of the sample data, I indeed find very few firms with loss.

Coefficient of Big five is significantly negative (-0.0004, two-tailed p-value, 0.02), indicating that

litigation risk and adverse reputation effect cause the conservative behavior of Big-5 firms. Large

auditors with substantial number of clients have “more to lose” if reputation is ruined by helping

or failing to report detected misbehaviors in a particular clients financial records (see DeAngelo,

1981; Reynolds and Francis, 2000).Furthermore, different from prior studies (see DeFond and

- 28 -

Jiambalvo 1994; DeAngelo et al. 1994; Becker et al. 1998), I do not find significant association

between leverage level and loan loss provision.

Table 6 presents evidences of cross-sectional variation of banks’ manipulation behaviors in

particular, as a function of high non-audit service purchase. As we know, many literature works

provide evidences that non-audit service is associated with observable difference in earnings

quality proxies (see DeAngelo 1981; Beck et al. 1988; Magee and Tseng 1990; Francis and Ke,

2001; Frankel et al 2002; DeFond et al. 2002; Ashbaugh et al, 2003), while loan loss provision is

one widely used measure for financial reporting quality in banking industry. This motivate this

paper to investigation the empirical association between non-audit service and loan loss

provision, conditional on different loan loss provision management incentives. HNAF, a dummy

variable which equals one if the Non-audit fee to total fee ratio is above the median level is used.

Table 6 shows that T1C *HNAF is significantly positive (0.0002, two-tailed p-value 0.00), and

T2C *HNAF is negative, significant at 5% level (-0.0003, two-tailed p-value 0.04).The

interaction terms have the same signs as those of TIC and T2C, indicating that high non-audit

service fee strengthen the capital management incentives. In a word, high level of non-audit

service purchase give bank firms more incentive to do manipulations to reach desired results, in

the expected direction. However, LLR* HNAF and EBTP* HNAF are not significant.

Besides non-audit service fee level, the variability of non-audit service purchase is also

expected to reflect the economic bonding between auditors and bank firms. Firms purchase non-

audit service in large amount consistently must have different manipulation incentives from those

firms who purchase little in magnitude or those who purchase sparsely. Thus it is another aspect

needed to be take into account when study banks’ manipulation behaviors under Basel Accord.

Table 7 presents the impact of non-audit service fee variability on the association between banks

managers’ manipulation incentives and loan loss provision (LLP). Two different measures (VAR)

are used to capture the nature of non-audit service fee variability in terms of both magnitude and

frequency. In model (1), VAR is defined as a dummy variable, equal to 1 if the standard deviation

- 29 -

of a firm’s non-audit service fee is below the sample median; in model (2), as an alternative

measure for robustness check purpose, it is defined by standard deviation rank, equal to 1 if the

standard deviation of the non-audit service fee ratio is in the highest rank deciles, and 10 if it is in

the lowest rank deciles in the sample. The coefficients of T1C* VAR and EBTP*VAR under both

models are significant negative at 5%level, while T2C* VAR coefficients are positive and

statistically significant; all are opposite to the signs in the basic model. This suggests that firms

purchase non-audit services consistently are less likely to manipulate capital and earnings upward

via loan loss provision adjustments than those firms who purchased sparsely. This could be

possibly due to high litigation risk and negative market reaction caused by continuous non-audit

service purchase. The sample period in this paper starts from 2001, the year when auditor

independence became a big consideration and many legislative interventions come out aiming to

restrict non-audit service supply. Consistent and regular non-audit service provision poses more

litigation risk to auditors when it is perceived as a symbol of impaired independence. Furthermore

the expected monitoring value of audit is assumed lowered by the market; therefore, continuous

providing rents to incumbent auditors via non-audit service purchase can also result in perception

of dishonesty or low quality of financial reporting of auditees. As a result, market reacts very

negatively, whenever they “perceive “low audit quality (JERE .R, 2006).

Size effect on banks’ manipulation behavior under Basel Accord in 1991 is investigated in

table 8. SIZE is a dummy variable, equals to 1 if total asset of a bank firm is below the sample

median level, and 0 otherwise. Size effect on Tier 1 capital and Tier 2 capital are both significant,

and in the expected direction. Coefficient of interaction term T1C *SIZE is positive (0.0004, two-

tailed p-value 0.00), indicating that small firms have stronger association between Tier I Capital

and discretionary loan loss provision. Size has reinforcing effect on Tier II capital as well,

showing a significantly negative coefficient of the interaction term T2C *SIZE (-0.0013, two-

tailed p-value 0.00). All these evidences indicate that, compare to large-size firms, small firms

have stronger capital management incentives via loan loss provision manipulation. Stinson (1993)

- 30 -

and Bishop (1996) bring up a ‘too big to fail’ hypothesis, arguing that regulators are reluctant to

intervene in the operations of large banks. Therefore, cost of falling short of capital adequacy

requirement is low and big firms do not bother to manipulate. Besides these, large-size firms’

manipulation incentives could be constrained by huge reputation cost and litigation risk, as

Kellogg (1984), Stice( 1991) and Bonner et al(1998) find out. On the other hand, this could be

explained by the fact that small-size firms have more manipulation incentives by nature. First,

their performances are far more volatile compared to large firms. Small firms face same earnings

stress and capital requirement pressures from both market and regulatory institutions as large

firms do, however, their performance suffer a larger degree of variability for the same level of

external market factor change. Therefore, small firms have high manipulation demand to achieve

performance smoothing. Secondly, small banks have less sophisticated internal control systems

and less competent internal auditors than large-size bank firms. Lack of necessary private

information and low efficiency increase the difficulties of manipulation detection, which

encourage bank firms to manipulate earnings and capitals to the desired level. Greeenawalt and

Sinkey(1988) document that small regional firms are more likely to engage in earning

management. However, this paper does not find similar evidence.

As robustness check, the impact of interaction between HNAF and VAR, HNAF and SIZE

are investigated in table 9 and table 10 respectively. Table 9 presents the impact of both level and

consistency of non-audit service purchase on bank firms’ manipulation incentives via loan loss

provision (LLP) under Basel Accord. Similar to results in table 7, coefficient of

EBTP*HNAF*VAR is significantly negative (-0.0009, two-tailed p-value 0.01). That is, probably

due to high litigation and detection risk, and negative market reaction caused by perceived low

quality financial reporting, firms purchase non-audit service consistently and regularly are less

likely to manipulate earnings than those firms who purchased irregularly. Another variable

significant under HNAF and VAR interaction is loan loss reserve. However, coefficient of

LLR*HNAF*VAR is significantly negative (-0.0617, two-tailed p-value 0.00), suggesting that

- 31 -

non-audit service purchase level dominant the effect here, high level and high frequency of non-

audit service purchase give bank firms more incentive to manipulate loan loss reserve upward via

loan loss provision. The impact of interaction between HNAF and SIZE is examined in table 10 11.

Although T1C*HNAF*SIZE is not significant, it has the sign consistent with results in table 8.

T2C*HNAF*SIZE is negative and significant at 5% level (-0.0008, two-tailed p-value 0.00),

indicating that, compare to large size firms with same level of non-audit service fee, small firms

are more likely to manipulate loan loss provision upward to reach the capital requirement target

when Tier II capital is low. Firms have discretion to choose auditors and decide the timing and

magnitude of non-audit service purchase themselves. This self –selection system reflect a lot

about the association between non-audit service purchase and agency incentives, that is, different

management incentives motivate and decide non-audit service purchase amount. Consistent with

what discussed in hypothesis development part, small firms has higher manipulation demand than

their counterpart of larger scale, therefore, they deliberately choose to purchase high level of non-

audit service.

6. Conclusion

This paper empirically investigate new capital and earnings management mechanisms under

Basel Accord in US banking industry, and its cross-sectional variations as a functions of both

level and variability of non-audit service purchase, and total assets.

Overall, I find evidence that: (i) Tier I capital is positively related to loan loss provision, that

is, bank firms would like to manipulate capital ratios up by decrease loan loss provision when

Tier I capital is low. This is different from literature papers which document a negative

association. The discrepancy is caused by capital adequacy requirement change under Basel

Accord since 1991. Loan loss reserve is no longer a component of Tier I capital and loan loss

11 LOSS*HNAF*SIZE variable is deleted from the regression analysis by the statistic software since the variables are constants or have missing correlations

- 32 -

provision purely has negative impact on it as a deduction to retained earnings. Moreover, loan

loss provision is negatively related to Tier II capital and loan loss reserve to risk-weighted total

assets ratio. Bank firms are more likely to increase loan loss provision to manipulate Tier II

capital upward, and this incentive is especially stronger when loan loss reserve is at low level. All

these findings enhance our understanding of capital management mechanisms under Basel

Accord. (ii) In addition, consistent with prior literature, loan loss provision decreases income

before tax, thus firms would like to decrease loan loss provisions for earnings management

purpose. (iii) Compared to large bank firms, small firms have stronger capital management

incentive via loan loss provision.( iv) Same as the evidences from other industries, high level of

non-audit service purchase give bank firms more incentive of earnings and capital management

However, regular and consistent non-audit service purchase suppress bank firms’ manipulation

actions. This is because continuous providing rent to auditors does not only increase detection

possibility and pose high litigation risk to auditors, perception of impaired honesty and low

financial reporting quality by the investors also triggers negative market reaction to bank firms.

The primary focus of this paper is the capital management and loan loss provision under the

new capital regime after 1991 and its cross-sectional variations related to size and non-audit

service properties. It does not discuss whether the auditor independence is impaired. This stand-

alone marginal analysis can not tell us much about that in isolation with comprehensive

institutional settings and audit contracting incentives investigation. Evidence of factual

impairments is very limited in the literature due to the unobservability of auditor independence.

Advanced and rigorous models which can probe subjective issues are needed. However, the

documented evidences of association between non-audit service and loan loss provision in this

paper do provide directional references for further auditor independence research in this specific

banking industry. Furthermore, this paper enriches the literature in both non-audit service and

loan loss provision, and can facilitate well-informed policy making by regulators to improve

regulators’ supervision and monitoring processes. Limitation of this paper is that these industry-

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specific evidences may have difficulty to be generalized to other industries since banking industry

has lots of unique features which are substantially different from others.

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Exhibit 1: The “rule” and the “policy”

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The exhibit reports major regulatory requirement related to non-audit service after year 2000. After implementation of Sarbanes-Oxley Act, SEC filed “Final Rule: Revision of the Commission's Auditor Independence Requirements” (the “rule”) [File No. S7-13-00] in November 2000, requiring firms, starting from February 5, 2001, to disclose: 1) audit fees; 2) IS fees; 3) audit-related fees; 4) tax fees; and 5) all other fees. They are described in Audit and Non-Audit Services Pre-Approval Policy (the “policy”) as follows:

Audit services include the annual financial statement audit (including required quarterly

reviews), subsidiary audits, and other procedures required to be performed by the

independent auditor to be able to form an opinion on the Company's consolidated

financial statements. These other procedures include information systems and procedural

reviews and testing performed in order to understand and place reliance on the systems of

internal control, and consultations relating to the audit or quarterly review. Audit services

also include the attestation engagement for the independent auditor's report on

management's report on internal controls for financial reporting, when required.

IS services include financial information system design and implementation.

Audit-related services include, among others, due diligence services pertaining to

potential business acquisitions/dispositions; accounting consultations related to

accounting, financial reporting or disclosure matters not classified as "Audit services";

assistance with understanding and implementing new accounting and financial reporting

guidance from rulemaking authorities; financial audits of employee benefit plans; agreed-

upon or expanded audit procedures related to accounting and/or billing records required

to respond to or comply with financial, accounting or regulatory reporting matters; and

assistance with internal control reporting requirements.

Tax services include tax compliance, tax planning and tax advice

All Other services include permissible non-audit services12 that are routine and recurring

services, would not impair the independence of the auditor and are consistent with the

SEC's rules on auditor independence

Exhibit 2: Non-audit service research literature evidence

The exhibit presents a brief summary of mixed results of the association between non-audit service provision and auditor independence in the literature. Basically the literature reveals three

12 Prohibited Non-Audit Services in SEC filed Final Rule include: bookkeeping or other services related to the accounting records or financial statements of the audit client; financial information systems design and implementation; appraisal or valuation services and fairness opinions; actuarial services; internal audit services; management functions; human resources; broker-dealer, investment adviser or investment banking services; legal service; expert services unrelated to the audit

- 38 -

types of relation: positive, negative and no association. Most papers find no empirical evidence that non-audit service provision impair auditor independence.

Relation between Non-Audit Service and Earnings Quality

Prior Papers Number

Positive Association Dee et al.(2002)Ferguson et al.(2003) Frankel et al.(2002)

3

--only for income-decreasing accruals

Ashbaugh et al.(2003)1

--only for smallest firm groups Chung and Kalllapur (2003)

1

--only for non-big five firms Gore et al.(2001)

1

--only for firms with poor corporate governance

Larcker and Richardson (2004)1

Negative Association Antle et al.(2002)Firth (2002)SharmaandSidhu (2001)

3

No Association Pringle Buchman (1996)Bajaj et al. (2003)Chung and Kalllapur (2003)Craswell (1999)Craswell et al.(2002)DeFond et al. (2002)Kinney et al.(2003) Krishnan (2003)Li et al.(2003) Raghunandan et al.(2003) Ruddock et al.(2003)Larcker and Richardson.(2004)

12

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Table 1: Descriptive Statistics of Auditor Fees Disclosed in Proxy Statements in Banking Holdings Companies (2001-2005)

This table reports descriptive statistics of auditor fees disclosed in proxy statement for 1609 bank holding firm-year observations from year 2001 to year 2005.Panel A presents the distribution of mandatory disclosure by SEC 2000, Section II. The components Non-Audit fee in Panel A are described in Panel B: audit-related fee, tax fee, the financial information system design and implementation fee (IS) and all other Advisory fee. All other advisory service is general consulting service, and information technology consulting for systems not associated with the financial statements. Please refer to Exhibit 1 for fee variables definition. All fees are in thousands of dollars.

  Standard First ThirdVariable Mean Deviation Quartile Median Quartile Minimum Maximum

Panel A: Mandatory Disclosure of Fee DataAudit 665.20 2916.91 75.50 135.20 345.40 0.07 55000.00Audit/Total 70.73% 18.32% 59.94% 73.69% 84.37% 6.36% 100.00%

NonAudit 487.96 2521.77 22.00 49.47 131.18 0.00 58700.00NonAudit/Total 29.27% 18.32% 15.63% 26.31% 40.06% 0.00% 93.64%

IS 1.00 37.20 0.00 0.00 0.00 0.00 1491.00IS/Total 0.07% 1.41% 0.00% 0.00% 0.00% 0.00% 43.60%

Total Fees 1153.17 5030.73 110.59 202.96 521.18 0.09 74200.00

Panel B: Voluntary Disclosure of Fee DataAudit-Related 215.89 878.19 10.64 23.50 62.73 0.00 9900.00Audit-Related/Total 9.50% 11.15% 0.00% 6.30% 14.20% 0.00% 72.37%

Tax 271.25 1393.00 9.00 20.78 66.75 0.00 15300.00Tax/Total 10.10% 10.91% 0.00% 7.56% 14.31% 0.00% 74.77%

All Other 240.74 1767.31 6.22 23.79 73.40 0.00 35300.00All Other/Total 9.59% 16.88% 0.00% 0.05% 12.25% 0.00% 93.64%

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Table 2: Descriptive statistics of fees disclosed by Big-Five and Non-Big Five auditors in banking holdings companies (2001-2005)

The table reports descriptive statistics of auditor fees disclosed by Big-Five and Non-Big-Five auditors respectively from year 2001 to year 2005.In particular, the Big-Five Auditors are Arthur Andersen (AA), Deloitee & Touché(D&T), Ernst & Young(E&Y), KPMG(KPMG), and PricewaterhouseCoopers(PWC). The auditors included in the category of " Non-Big Five Auditors " with observations exceed 50 are as follows: Beard Miller Company LLP,Crowe Chizek and Company LLC,Dixon Hughes PLLC,Moss Adams LLP and Yount, Hyde & Barbour P.C. All fees are in thousands of dollars.

               Panel A: Big-Four Auditors, Fees are divided by Total Auditor Fees

Standard First ThirdVariable Mean Deviation Quartile Median Quartile Minimum Maximum

Total Fees 2083.18 6884.56 206.04 466.23 1023.65 41.00 74200.00Audit/Total 69.96% 20.22% 58.34% 73.68% 85.86% 6.36% 100.00%NonAudit/Total 30.04% 20.22% 14.14% 26.32% 41.66% 0.00% 93.64%IS/Total 0.08% 1.62% 0.00% 0.00% 0.00% 0.00% 43.60%Audit-Related/Total 9.04% 11.03% 0.00% 5.40% 13.44% 0.00% 72.37%Tax/Total 11.48% 13.23% 0.00% 7.46% 17.77% 0.00% 74.77%All Other/Total 9.44% 17.99% 0.00% 0.00% 9.97% 0.00% 93.64%

Panel B: Non- Big-Four Auditors, Fees are divided by Total Auditor Fees

Standard First ThirdVariable Mean Deviation Quartile Median Quartile Minimum Maximum

Total Fees 167.18 170.90 81.57 119.17 191.15 0.09 2049.08Audit/Total 71.55% 16.05% 61.91% 73.79% 83.69% 15.57% 100.00%NonAudit/Total 28.45% 16.05% 16.31% 26.21% 38.09% 0.00% 84.43%IS/Total 0.07% 1.16% 0.00% 0.00% 0.00% 0.00% 26.77%Audit-Related/Total 9.99% 11.26% 0.00% 7.20% 15.37% 0.00% 67.86%Tax/Total 8.64% 7.45% 3.27% 7.61% 12.24% 0.00% 43.44%All Other/Total 9.75% 15.63% 0.00% 0.85% 13.40% 0.00% 81.58%

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Table 3: Time-series analysis of audit and Non-audit fees and ratios of bank holding firms (2001-2005)

This table presents the median of audit fee, non-audit fee, total fee, audit ratio and non-audit ratio for 1609 bank holding firm-year observations from year 2001 to year 2005. Panel A.B and Panel C report the medians of full sample, Big-Five sample and Non-Big-Five sample respectively. All fees are in thousands of dollars.

Year Audit fee NonAudit Fee Total Fees Audit ratio NonAudit RatioPanel A: Full Sample

2001 98.90 58.00 171.00 62.72% 37.28%2002 100.00 52.02 159.45 67.43% 32.57%2003 116.35 47.21 176.09 71.31% 28.69%2004 208.12 45.29 269.65 79.85% 20.15%2005 215.00 46.90 290.50 81.65% 18.35%

Panel B: Big-Five Sample2001 188.00 131.41 308.03 58.43% 41.57%2002 205.00 110.00 320.06 65.26% 34.74%2003 256.13 98.97 332.98 71.24% 28.76%2004 519.17 102.79 608.78 82.69% 17.31%2005 529.30 90.25 647.00 83.96% 16.04%

Panel C: Non-Big-Five Sample2001 62.67 35.46 102.54 66.79% 33.21%2002 71.80 32.01 107.29 68.74% 31.26%2003 72.55 31.00 107.50 70.52% 29.48%2004 100.41 31.95 135.64 77.20% 22.80%2005 118.58 33.30 158.59 79.49% 20.51%

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Table 4: Descriptive statistics of major regression variables (2001-2005)

This table reports descriptive statistics of major regression variables for 1609 bank holding firm-year observations from year 2001 to year 2005. All bank firms file Y-9C reports with the Federal Reserve and disclose audit data in EDGER. Total assets (TA) of bank firms at year end, is dollar amount in millions.

Variable Mean STD Min 25% Median 75% Max DLLP 0.000 0.003 -0.018 -0.002 0.000 0.001 0.049NAF 0.293 0.183 0.000 0.156 0.263 0.401 0.936TIC 12.429 3.350 5.386 10.488 11.826 13.484 46.401T2C 1.260 1.020 -4.314 0.753 0.969 1.296 9.849LLR 0.011 0.035 -0.024 0.007 0.009 0.011 0.895EBTP 0.069 0.767 -14.041 0.000 0.091 0.190 19.745LEVERAGE 1.036 2.388 0.017 0.897 0.908 0.919 49.928LN(TA) 14.200 1.575 12.040 13.118 13.728 14.893 21.125STD(NAF) 0.129 0.070 0.000 0.075 0.118 0.178 0.363ROA 0.011 0.004 -0.021 0.009 0.011 0.013 0.047

Variable Definitions

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DLLPNAF

T1CT2CLLREBTP LEVERAGLN(TA) STD(NAF)ROA

Discretionary loan loss provisions from Beatty et al (2002) model Non-audit service fee to total fee ratio, non-audit service fee is the sum of audit-related fee, tax fees, other advisory fees, IS and all other fees Ratio of Tier I capital before loan loss provision to risk-weighted total assetsRatio of Tier II capital before loan loss provision to risk-weighted total assetsRatio of Loan Loss Reserve before loan loss provision to risk-weighted total assets Earnings before taxes and loan loss provision/average total assetsRatio of total liability to average total assetsNatural log of total assets at year endStandard deviation of non-audit service fee ratio for each bank firmNet income divided by average total asset

Table 5: Evidence of new capital and earnings management mechanisms under Basel Accord (2001-2005) Dependent variable= DLLP, N=1, 609

This table presents evidences of new earnings and capital management behaviors of bank firms via loan loss provision under Basel Accord. The dependent variable is discretionary loan loss provision. Results show, instead of the positive effect in the old capital requirement regime, loan loss provision has negative impact on Tier I capital. This suggests that firms would like to lower loan loss provision to increase Tier I capital. Firms are more likely to increase loan loss provision when Tier II capital, and this incentive is much strong when loan loss reserve is at low level. Consistent with literature evidence, the coefficient between loan loss provision and earnings is positive since loan loss provision works as a pure expense to decrease income before tax.

Basic Model:

Independent Variable Coefficient Estimates Two Tailed p -value

(Constant) -0.0006 0.02

T1C 0.0003 0.00

T2C -0.0002 0.00

LLR -0.0102 0.00

EBTP 0.0003 0.01

LOSS -0.0018 0.47

Big Five -0.0004 0.02

LEVERAGE 0.0000 0.55R-square 2.91%

Adjusted R-square 2.48%

Variable Definitions

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DLLP T1C T2C LLR EBTP LOSS

Big5 LEVERAG

Discretionary loan loss provisions from Beatty et al (2002) model Ratio of Tier I capital before loan loss provision to risk-weighted total assetsRatio of Tier II capital before loan loss provision to risk-weighted total assetsRatio of Loan Loss Reserve before loan loss provision to risk-weighted total assets Earnings before taxes and loan loss provision/average total assetsNegative earnings before taxes and loan loss provision/average total assetsDummy variable, equal to 1 if the auditor firm is one of the big five auditorsRatio of total liability to average total assets

Table 6: Interaction between Non-audit service provision and Banks’ manipulation behaviors under Basel Accord (2001-2005) Dependent variable= DLLP, N=1, 609

This table presents the variations of bank firms’ manipulation behaviors via loan loss provision, within the context of high level of non-audit service purchase. Results show that large amount of non-audit service purchase encourage bank firm managements to involve in manipulation actions. That is, providing rents to auditors strengthen the economic bond between bank firms and auditors, as a result, reinforce the association between capitals and loan loss provisions. Model:

Independent Variable Coefficient Estimates Two Tailed p -value

(Constant) -0.0005 0.10

T1C 0.0002 0.07

T2C -0.0001 0.14

LLR -0.0142 0.00

EBTP 0.0002 0.41

LOSS -0.0028 0.41

T1C *HNAF 0.0002 0.00

T2C *HNAF -0.0003 0.04

LLR* HNAF 0.0050 0.38

EBTP*HNAF 0.0002 0.48

LOSS*HNAF 0.0023 0.64

Big Five -0.0004 0.04

LEVERAGE 0.0000 0.57

R-square 3.88%

Adjusted R-square 3.16%

Variable Definitions

- 45 -

T1C T2C LLR EBTP LOSS

HNAF

Big5 LEVERAG

Ratio of Tier I capital before loan loss provision to risk-weighted total assetsRatio of Tier II capital before loan loss provision to risk-weighted total assetsRatio of Loan Loss Reserve before loan loss provision to risk-weighted total assets Earnings before taxes and loan loss provision/average total assetsNegative earnings before taxes and loan loss provision/average total assetsDummy variable which equals one if the Non-audit fee to total fee ratio is above the median level.Dummy variable, equal to 1 if the auditor firm is one of the big five auditorsRatio of total liability to average total assets

Table 7: Impact of Variability of non-audit service purchase on banks’ manipulation actions under Basel Accord (2001-2005) Dependent variable= DLLP, N=1, 609

The table presents impacts of non-audit service purchase variability on the association between banks managers’ manipulation incentives and loan loss provision (LLP). Two different measures (VAR) are used to capture the non-audit service variability property. In model (1), VAR is defined as a dummy variable, equal to 1 if the standard deviation of a firm’s non-audit service fee is lower than the sample median level; in model (2), as an alternative measure, it is defines by the standard deviation rank, equal to 1 if the standard deviation of the non-audit service fee ratio is in the highest rank deciles, and 10 if it is in the lowest rank deciles in the sample. Tier 1* VAR, Tier 2* VAR and EBTP*VAR are significant at 5%level, however, their signs are opposite to Tier 1, Tier 2 and EBTP. Regular and consistent non-audit service purchases suppress the manipulations of bank firms in the expected direction. This could be explained by the fact that continuous providing rents to auditors would not only increase detection probability and pose higher litigation risk to auditors, perception of impaired honesty and low quality of financial reporting also would trigger negative market reaction to bank firms. The two-tailed p-values are stated in italic.

Model:

Independent Variables Model(1) Model(2)

(Constant) 0.0001 0.00040.74 0.21

T1C 0.0003 0.00030.01 0.01

T2C -0.0005 -0.00090.00 0.00

LLR -0.0090 -0.00720.00 0.04

EBTP 0.0006 0.00080.00 0.00

LOSS -0.0009 0.01060.78 0.78

T1C *VAR -0.0002 -0.00010.01 0.00

T2C *VAR 0.0005 0.00010.00 0.00

LLR*VAR -0.0063 -0.00110.25 0.17

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EBTP*VAR -0.0006 -0.00010.01 0.02

LOSS*VAR -0.0017 -0.00510.72 0.74

Big Five -0.0004 -0.00040.01 0.02

LEVERAGE 0.0000 0.00000.50 0.45

R-square 4.48% 5.11%Adjusted R-square 3.76% 4.40%

Variable Definitions

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T1C T2C LLR EBTP LOSS

RECUR (1)

RECUR (2)

Big5 LEVERAG

Ratio of Tier I capital before loan loss provision to risk-weighted total assetsRatio of Tier II capital before loan loss provision to risk-weighted total assetsRatio of Loan Loss Reserve before loan loss provision to risk-weighted total assets Earnings before taxes and loan loss provision/average total assetsNegative earnings before taxes and loan loss provision/average total assetsDummy variable, equal to 1 if the standard deviation of a firm’s non-audit service fee is lower than the sample median levelAn alternative measure of non-audit service purchase variability, proxied by the standard deviation rank, equal to 1 if the standard deviation of the non-audit service fee ratio is the highest rankDummy variable, equal to 1 if the auditor firm is one of the big five auditorsRatio of total liability to average total assets

Table 8: Size effect on Banks’ Manipulation behavior under Basel Accord in 1991 (2001-2005) Dependent variable= DLLP, N=1, 609

This table presents evidences of impact of banks firms’ size (total assets) on the relation between regulatory capital and discretionary loan loss provision under Basel Accord 1991. Size effect is captured by a SIZE dummy variable, which equals to 1 if total asset of a bank firm is below the median level of this sample and 0 otherwise. The result shows size effect on Tier I and Tier II capital are significant. That is, compare to large size bank firms, small firms are more likely to do capital management. This is could be explained that large-size firms’ manipulation incentives are constrained by huge reputation cost and litigation risk (Kellogg, 1984; Stice, 1991; Bonner et al, 1998).Furthermore, small firms have more manipulation demand result from their volatile performance, and inefficiency internal control system encourage them to do so.

Model:

13

Independent Variable Coefficient Estimates Two Tailed p -value

(Constant) 0.0002 0.38

T1C 0.0000 0.86

T2C 0.0000 0.70

LLR -0.0085 0.01

EBTP 0.0005 0.00

LOSS -0.0023 0.34

T1C *SIZE 0.0004 0.00

T2C *SIZE -0.0013 0.00

LLR* SIZE -0.0053 0.29

EBTP*SIZE -0.0003 0.15

Big Five -0.0005 0.00

LEVERAGE 0.0000 0.93

R-square 7.55%

Adjusted R-square 6.91%

13 LOSS*SIZE variable is deleted from the regression analysis by the statistic software since the variables are constants or have missing correlations

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Table 9: Impact of Interaction between HNAF and RCUR on bank management incentives through LLP under Basel Accord (2001-2005) Dependent variable= DLLP, N=1, 609

The table presents impact of interaction between high non-audit service purchase level and its variability on bank firms’ manipulation incentives through loan loss provision under Basel Accord. HNAF is defined in table 6. VAR is a dummy variable, equal to 1 if the standard deviation of a firm’s non-audit service fee is below sample median. The coefficient of EBTP*HNAF*VAR is significantly negative. That is, probably due to high litigation and detection risk, and negative market reaction caused by perceived low quality financial reporting, firms purchase non-audit service in large amount consistently and regularly are less likely to manipulate earnings than those firms who purchased irregularly. However, LLR%*HNAF*VAR is significantly negative, suggesting that non-audit service purchase level dominant the effect here, high level and high frequency of non-audit service purchase give bank firms more incentive to manipulate loan loss reserve upward via loan loss provision.

Independent Variable Coefficient Estimates Two Tailed p -value

(Constant) -0.0004 0.16

T1C 0.0002 0.09

T2C -0.0001 0.18

LLR -0.0143 0.00

EBTP 0.0002 0.40

LOSS -0.0028 0.41

T1C *HNAF 0.0003 0.00

T2C *HNAF -0.0002 0.08

LLR*HNAF 0.0070 0.22

EBTP*HNAF 0.0004 0.15

LOSS*HNAF 0.0017 0.72

T1C *HNAF*VAR 0.0001 0.28

T2C *HNAF*VAR -0.0001 0.81

LLR*HNAF*VAR -0.0617 0.00

EBTP*HNAF*VAR -0.0009 0.01

Big Five -0.0004 0.02

LEVERAGE 0.0000 0.66

R-square 5.37%

Adjusted R-square 4.41%

* LOSS*HNAF*VAR variable is deleted from the regression analysis by the statistic software since the variables are constants or have missing correlations

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Table 10: Impact of the Interaction between HNAF and SIZE on bank management mechanisms under Basel Accord (2001-2005) Dependent variable= DLLP, N=1, 609

The table presents evidences of how the interaction between high level of non-audit service purchase and total assets of bank firms influence manipulation incentives through loan loss provision after 1991. HNAF and SIZE are defined in previous tables. Although T1C*HNAF*SIZE is not significant, it has the sign consistent with the results in table 8. T2C*HNAF*SIZE is negative and significant at 5% level, indicating that, compare to large size firms, small firms are more likely to choose to purchase high level of non-audit service and based on that they manipulate loan loss provision upward to reach the capital requirement target when Tier II capital is low.

Independent Variable Coefficient Estimates Two Tailed p -value (Constant) -0.0004 0.17

T1C 0.0002 0.07

T2C -0.0001 0.14

LLR -0.0143 0.00

EBTP 0.0002 0.38

LOSS -0.0028 0.42

T1C *HNAF 0.0003 0.00

T2C *HNAF -0.0002 0.03

LLR*HNAF 0.0072 0.22

EBTP*HNAF 0.0003 0.35

LOSS*HNAF 0.0018 0.71

T1C *HNAF*SIZE 0.0001 0.59

T2C *HNAF*SIZE -0.0008 0.00

LLR* HNAF*SIZE -0.0113 0.12

EBTP*HNAF*SIZE -0.0003 0.27

Big Five -0.0005 0.00

LEVERAGE 0.0000 0.82

R-square 5.11%

Adjusted R-square 4.16%

* LOSS*HNAF*SIZE variable is deleted from the regression analysis by the statistic software since the variables are constants or have missing correlations

Appendix A. How to calculate Capital Adequacy Ratios

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LLR: Loan Loss Reserve; GRWA: Gross Risk-Weighted Assets

Step1: Compute Tier I Capital

(a) Permanent shareholders’ equity: Fully-paid ordinary shares/common stock (CS) Perpetual non-cumulative preference shares (PS) (b) Disclosed reserves: Retained earnings (RE) Mandatory convertible debt (CD) Legal reserves (LR) Other surplus (OS)

Deduction from Tier I capital: Goodwill

Step2: Compute Tier II Capital

(a) Undisclosed reserves(UR)(b) Asset revaluation reserves (AR)(c) Loan-loss reserves (LLR)(d) Hybrid capital instruments (CI)(e) Subordinated term debt (TD)

Restrictions of Tier II capital:(i) The total of Tier II capital is limited to a maximum of 100% of the total of Tier I capital;(ii) Subordinated term debt is limited to a maximum of 50% of Tier I capital;(iii) Loan loss reserve included in Tier II capital is limited to a maximum of 1.25 percentages points of risk-weighted assets;(iv) Asset revaluation reserves which take the form of latent gains on unrealized securities is subject to a discount of 55%.

Step3: Compute Total Capital

Total Capital= Tier I capital+ Tier II capital- Deductions

Deductions from Total capital:(a) Investments in subsidiaries engaged in banking and financial activities which are not consolidated

in national systems, to prevent the multiple uses of the same capital resources in different parts of the group.

(b) Investments in the capital of other banks and financial institutions, to avoid the cross-holdings of bank capital designed artificially to inflate bank capital positions.

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Step4: Compute Risk –Weighted Assets (RWA)

RWA is calculated by multiply relevant risk-weights to the value of both on-balance sheet items and off-balance sheet items.

On-Balance Sheet ItemsRisk CategoriesThe framework of weights has been designed in a very simple way and only five weights are used: 0, 10, 20, 50 and 100% .For example:

Balance Sheet Risk Assets Risk WeightCash, Claims on central governments and central banks or claims , Federal balances, Treasury securities 0%General obligation municipal bonds, claims on multilateral development banks, or cash items in process of collection 20%Loans fully secured by mortgage on residential property , or Revenue municipal bonds 50%All other loans and investments, premises and equipment 100%

Off-Balance Sheet ItemsIn the Basel Accord, all off-balance-sheet activity is taken into account in the capital adequacy framework. All categories of off-balance-sheet engagements are converted to credit risk equivalents by multiplying a credit conversion factor, the resulting amounts then being weighted according to the nature of the equivalent on-balance sheet counterparty. Credit conversion ratios are derived from the estimated size and likely occurrence of the credit exposure, as well as the relative degree of credit risk as identified in the Committee’s paper "The management of banks’ off-balance sheet exposures: a supervisory perspective" issued in March 1986.

Off-Balance Sheet Items Credit Conversion Ratio

Other loan commitments with an original maturity of up to one year ,or which can be unconditionally cancelled at anytime 0%Short-term self-liquidating trade-related contingencies, eg, commercial letter of credit 20%Transaction-related contingent items, note issuance facilities and revolving underwriting facilities 50%Direct credit substitute, sale and repurchase agreements, asset sales with recourse, Forward asset purchases, forward deposits and partly-paid shares and securities

100%

Total Risk –Weighted Assets (RWA) =Adjusted On-Balance Sheet Items + Adjusted Off-Balance Sheet ItemsAppendix B. The net effect of Basel Accord Changes on Tier I and Tier II capital

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I. Primary capital and Tier I capital

Primary Capital before 1988 Basel Accord

Primary capital consists of:a) Fully-paid ordinary shares/common stock( CS)b) Perpetual non-cumulative preference shares(PS)c) Retained earnings(RE)d) Loan Loss Reserve( LLR)e) Mandatory convertible debt(CD)f) Legal reserves(LR)g) Other surplus(OS)

LLP is related to LLR and RE. ,that is , one unit increase of LLP increase LLR by one unit .However, in the income statement LLP decrease the RE by (1-t) unit, t is the

tax rate. Therefore, the net effect of LLP on primary capital is the tax shield of LLP,

, in one word, LLP increase primary capital before the Basel Accord.

Tier I Capital after 1988 Basel Accord

LLR is removed from the numerator of Tier I capital, therefore the net effect of LLP is

1) When LLR<1.25%GRWA, net effect of LLP is , LLP has negative effect

on Tier I capital ratio

2) When the LLR > 1.25% GRWA, the net effect of LLP is:

Take the differentiate of the above formula respect to LLP, to make it looks simple, take b= -1and all the other variables in the denominator as c, then

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-(1-t)*LLP is the numerator , and(b*LLP+c) is the denominator, the condition need to make LLP has negative effect is :

Assume the tax rate t=34%, we only need the denominator >1.5 times numerator so that LLP has negative effect on Tier I capital even when LLR is larger than 1.25% of risk-weighted assets. And this criterion can be fully satisfied in most banks.

Therefore LLP decrease Tier I capital ratio after Basel Accord in stead of increasing before 1988.

II. Secondary Capital and Tier II capital

Secondary capital after 1988 Basel Accord

Secondary capital before Basel Accord consists of:(a) Undisclosed reserves(UR)(b) Asset revaluation reserves (AR)(c) Hybrid capital instruments (CI)(d) Subordinated term debt (TD)

Tier II Capital after 1988 Basel Accord

The loan loss reserve (LLR) is shifted from Primary capital before 1988 to Tier II capital under Basel Adequacy Accord, however, LLR qualifies to be included in Tier II capital is limited to 1.25% of Gross Risk-Weighted Assets (GRWA)

The net effect of LLP on Tier II capital is:

That is, LLP has positive net effect on Tier II capital under the Basel Adequacy Accord.

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