M I R M U H I B U L I S L A M

AUDIT COMMITTEE EFFECTIVENESS AND FINANCIAL REPORTING QUALITY

BACKGROUND AND MOTIVATION

• Jeon, Choi and Park, 2004 and Wild, 1994: Korean Companies - Level of significance was low between the ACE and FRQ; and

US Companies- Strong relationship between the ACE and FRQ.

• Klein (2002)- Companies (US) with AC strong on independence had significantly lower amount of abnormal accruals than others.

• Xie, Davidson and DaDalt (2003)- Better FRQ in companies (US) that had majority of corporate experienced as well as independent directors.

• Two similar empirical research in Australia :Davidson et. al. (2005)- inverse relationship between the percentage of non-executive directors and the suspected amount of earnings management.

Baxter, P (2007)- Significant difference between the FRQ of a company before and after the establishment of audit committee, however any subsequent improvement or change in the AC seemed to not have any major impact on FRQ.

RESEARCH QUESTIONS AND OBJECTIVES

• RQ: Is there an association between audit committee effectiveness and financial reporting quality in the Australian publicly listed firms ?• Australian listed firms is positively or negatively associated and to what

extent.

• Corporate governance activists that structural and operational composition factors influence an ACE. Prior literature (Beasley and Salterio, 2001; Van der Zahn and Tower, 2004) five major components underlying the ACE was determined.

• MSQ : Is there an association between key audit committee effectiveness (i.e. (a) AC independence (b) independent AC members financial expertise (c) independent audit committee members tenure (d) the size of the AC (e) AC diligence) and financial reporting quality in the Australian publicly listed firms?

(see: ASX Corporate Governance Council, 2007, 2003; KPMG, 1999; Blue Ribbon Committee, 1999; Price Waterhouse, 1993; Cadbury Committee, 1992)

LITERATURE REVIEW

• DeZoort et. al. (2002):

“An effective audit committee has qualified members with

the authority and resources to protect stakeholder interests by

ensuring reliable financial reporting, internal controls, and risk

management through its conscientious oversight efforts.”

• The operational composition:

(1) Authority (responsibilities, influence); (2) Diligence

(incentive, number of meetings, perseverance).

• The structural composition-

(3) Resources (size, access to management, internal and external auditor) (4) Composition (integrity, objectivity,

expertise, experience, independence).

Board of Director

Management

(Agents)

Shareholders

(Principal)

Audit

Committee

Agency

Problem

Responsible for

managing top

management

Delegates

Financial

Reporting

Oversight

Independence

Expertise

Size

Tenure

Diligence

AUDIT COMMITTEE EFFECTIVENESS

HYPOTHESES

• Audit Committee Independence

H1: Australian publicly listed firms with a majority of

independent directors on the audit committee are more likely

to have higher levels of financial reporting quality.

• Audit Committee Financial Expertise

H2: Australian publicly listed firms with audit committees

comprising members with financial expertise are more likely to

have higher levels of financial reporting quality.

• Audit Committee Size

H3: Australian publicly listed firms with larger audit committee size are more likely to have higher levels of financial reporting

quality.

HYPOTHESES

• Audit Committee Tenure

H4: Australian publicly listed firms with audit committees

comprising members with prior audit committee experience

are more likely to have higher levels of financial reporting

quality.

• Audit Committee Diligence

H5: Australian publicly listed firms with more diligence audit

committees (i.e. meet more frequently) are more likely to

have higher levels of financial reporting quality.

CONCEPTUAL SCHEMA

SAMPLE SELECTION

• The analysis involves data of one calendar year period (Jan 2008 – Dec 2000). • Selected data is considering the fact 2008 as a pre global financial

crisis

• The initial sample comprised of 110 random Australian publicly listed firms registered with the ASX as at Jan 1 2008.• FinAnalysis or DatAnalysis (Aspect Huntley on-line repositories) has

been utilized to identify the firms. Consistent with prior research financial and banking industries firms was excluded (Ball et. al. 2000; Goodwin, 2003).

• From the resulting sample pool, 93 firms is selected for which all the data is available.

• Data of ACE has been collected analyzing the Annual Reports.

RESEARCH METHODOLOGY:MODIFIED JONES MODEL

• TAi,t/Ai,t-1 = αi[1/Ai,t-1] + β1i[ΔREVi,t - ΔRECi,t /Ai,t-1] +

β2i[PPEit/Ai,t-1] + εi,t

• Ai,t-1 = Total assets in year t - 1 for firm i;

• ΔREVi,t = Revenues in year t less revenues in year t - 1 for firm i;

• ΔRECi,t = Net receivables in year t less net receivables in year t -

1 for firm i;

• PPEi,t = Gross property, plant and equipment in year t for firm i;

• εi,t = Error term in year t for firm i.

• TAi,t is a dependent variable, and all other variable put into the equation are independent. Some variable such as αi,

εi,t are firm specific variable

RESEARCH METHODOLOGY:MULTIPLE REGRESSION MODEL

• DACjt = β0 + β1Ind_ACEjt + β2 Expt_ACEjt + β3 Siz_ACEjt + β4

Ten_ACEjt + β5 Dil_ACEjt + β6Bod_SIZEjt + β7MTBjt + β8LnBVTAjt + β9LEVERAGE + Ɛt

• Dependent variable (DV) is the Discretionary Accruals (DACjt)

which is a proxy to measure financial reporting quality.

• Independent variables (IV) or inputs are determinants of the

ACE: independence (Ind_ACEjt), financial expertise

(Expt_ACEjt), size (Siz_ACEjt), Tenure (Ten_ACEjt) and Diligence

(Dil_ACEjt).

• Control variable (CV) are: Board Size (Bod_SIZE), market to

book ratio (MTB); natural logarithm of book value of total

assets(LnBVTA), leverage (LEV).

• Ɛ is the error term for that time period.

FINDINGS AND DISCUSSIONS

• Frequency Table

Expt_Acc_AC

Frequency Percent Valid Percent Cumulative Percent

Valid0 46 49.5 49.5 49.5

1 47 50.5 50.5 100.0

Total 93 100.0 100.0

Dil_AC

Frequency Percent Valid Percent Cumulative Percent

Valid 0 50 53.8 53.8 53.8

1 43 46.2 46.2 100.0

Total 93 100.0 100.0

FINDINGS AND DISCUSSIONS

• Descriptive Statistics

Size_AC Ind_AC_per AC_Ten Bod_Size MTB LnBVTA LEV

NValid 93 93 93 93 93 93 93

Missing 0 0 0 0 0 0 0

Mean 3.02 .6219 6.16091 5.43 2.7957 18.1398255 2.57280

Median 3.00 .6667 5.30639 5.00 1.7400 17.9247766 1.87000

Mode 3 1.00 1.370a 3 .00 13.20117a 1.040

Std. Deviation .921 .38806 4.035975 2.214 3.45763 2.35192525 3.992350

Variance .847 .151 16.289 4.900 11.955 5.532 15.939

Minimum 1 .00 .779 3 -5.49 13.20117 -.990

Maximum 6 1.00 22.037 12 17.87 23.42657 36.490

a. Multiple modes exist. The smallest value is shown

FINDINGS AND DISCUSSIONS

• Regression Analysis

• a. Predictors: (Constant), LEV, Size_AC, AC_Ten, Ind_AC_per, Dil_AC, MTB, Expt_Acc_AC, Bod_Size, LnBVTA

• b. Dependent variable: Unstandardized_DAC

Model Summary

Model R

R

Square

Adjusted

R Square

Std. Error

of the

Estimate

Change Statistics

R Square

Change

F

Change df1 df2

Sig. F

Change

1 .335a .112 .016 .30870811 .112 1.164 9 83 .329

Regression Analysis

Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1

(Constant) .202 .363 .557 .579

Size_AC -.010 .038 -.029 -.256 .799

Ind_AC_per .197 .110 .245 1.783 .078

AC_Ten -.001 .008 -.010 -.100 .921

Expt_Acc_AC -.129 .082 -.209 -1.570 .120

Dil_AC .067 .072 .108 .934 .353

Bod_Size .001 .024 .009 .050 .960

MTB -.021 .010 -.239 -2.080 .041

LnBVTA -.012 .024 -.092 -.515 .608

LEV .008 .009 .099 .863 .391

a. Dependent Variable: Unstandardized_DAC

FINDINGS AND DISCUSSIONS

• Correlation

• *. Correlation is significant at the 0.05 level (2-tailed).

• **. Correlation is significant at the 0.01 level (2-tailed).

Correlations

Size_

AC

Ind_AC

_per

AC_Te

n

Expt_Acc_

AC

Dil_A

C

Bod_

Size MTB

LnBV

TA LEV

Unstandardized_DAC

Pearson

Correlation

-.016 .145 -.029 -.089 .057 .033 -.187 -.003 .059

Sig. (2-tailed) .878 .167 .780 .394 .588 .754 .073 .977 .574

Sum of

Squares and

Cross-products

-.426 1.606 -3.391 -1.286 .816 2.085 -

18.4

88

-.205 6.747

Covariance -.005 .017 -.037 -.014 .009 .023 -.201 -.002 .073

N 93 93 93 93 93 93 93 93 93

LIMITATIONS

• Data collection is limited to 110 ASX limited companies and of one year.

• The data for the variable to measure the ACE will be extracted from the annual reports in order to test the hypotheses, thus it limits the extent and type of data that can be collected.

• Few specific attributes is considered to examine the ACE whereas ACE is a multi-dimensional paradigm; and complete information about the AC work is not possible to derive.

SIGNIFICANCE

• This study established association between the ACE and

the FRQ thus it can be deduced the agency conflicts

can be resolved by presence of an ACE.

• Research methodology involves 5 determinants of the

ACE. Prior studies generally used combination of two or

three aforementioned determinants.

• Each of the determinant is separately tested as well which

determined the level of influence of each determinant.

• Can be used practically for CG purpose by the board of

directors in decision making purpose considering the

trends identified and implemented to improve the FRQ.

REFERENCE LIST

ASX Corporate Governance Council (2003), Principles of Good Corporate Governance and Best Practice

Recommendations, ASX Corporate Governance Council, Sydney.

ASX Corporate Governance Council (2007), Corporate Governance Principles and Recommendations, 2nd

ed., ASX Corporate Governance Council, Sydney.

Ball, R., Kothari, S. P., and Robin, A.(2000). The effect of institutional factors on properties of accounting

earnings. Journal of Accounting and Economics.

Blue Ribbon Committee (1999), “Report and recommendations of the blue ribbon committee on improving

the effectiveness of corporate audit committees”, The Business Lawyer, Vol. 54 No. 2, pp. 1067-95.

Cadbury Committee 1992, Report of The Committee on the Financial Aspects of Corporate Governance.

DeZoort, F. T, Dana R. Hermanson, Deborah S. Archambeault, and Scott A. Reed. "Audit Committee

Effectiveness: A Synthesis of the Empirical Audit Committee Literature." [In English]. Journal of

Accounting Literature 21 (2002): 38-75.

Goodwin, J. (2003). The relationship between the audit committee and the internal audit function: Evidence

from Australia and New Zealand. International Journal of Auditing.

Jeon, K., Choi, J. and Park, J. 2004, 'The relationship between new audit committee establishment and

earnings management', Korean Accounting Review, vol. 29, no. 1, pp. 143-178

Klein, A. 2002b, 'Economic determinants of audit committee independence', The Accounting Review, vol. 77,

no. 2, pp. 435-452.

KPMG, 1999. Shaping the Audit Committee Agenda, KPMG, Montvale, NJ.

Price Waterhouse 1993, Improving Audit Committee Performance: What Works Best. Institute of Internal

Auditors Research Foundation, Altamonte Springs.

Wild, J. 1994, 'The audit committee and earnings quality', Journal of Accounting Auditing and Finance, vol.

22, no. 1, pp. 247-276.

Xie, B., Davidson, W. and DaDalt, P. 2003, 'Earnings management and corporate governance: the role of the

board and the audit committee', Journal of Corporate Finance, vol. 9, no. 3, pp. 295-316

REFERENCE LIST

THE END

QUEST ION AND ANSWERS???