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The Nonlinear Associationbetween
Abnormal Audit Fees and Audit Quality:Evidence from Hong Kong
DBA Candidate : Alan S. K. Ho
DBA VIVA presentation 28th July 2008
Panel:
Chairman: Prof. Bin SRINIDHI
Supervisor: Prof. Jeong-Bon KIM
External Examiners:
Dr. Charles CHEN J P
Prof. FIRTH Michael Arthur
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Outline
1. Introduction2. Background3. Operationalisation4. Empirical procedures5. Results6. Conclusions7. Q&A
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1. Introduction
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The research questions
Do audit fees create economic bond between auditor and its client?
If so, how does this affect the audit quality?
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The research gapResults of prior studies are mixed and inconclusive. E.G., A survey on 25 most recent studies: 12 with no association, 2 with +ve association, 5 with -ve association, 6 with different associations in different divisions.
Why?Incorrect measure for economic bond (use size of fees and various fee ratios) - the concept of super profitsNonlinearity of abnormal fees – The effects of +ve and –ve abnormal fees are cancelling each other out.The measure of the consequence of lower audit quality (e.g. discretionary accruals) is not powerful enough.
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This study will ….Use positive abnormal audit fees (POSAAF) to measure the economic bond.Use accrual quality and C-Score to measure the audit quality.Demonstrate the nonlinear association between abnormal audit fees and audit quality.
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2. Background
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Audit quality & Independence
DeAngelo (1981a) defines audit quality as the market assessed joint probability that a given auditor will both discover a breach in the client’s financial statements and report such breach.
Competence
Independence
Audit Quality
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The Conceptual Model
Independence
Audit
Quality
Training and
Standards Earnings Quality
Economic Bond
Competence
Abnormal Audit Fees
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3. Operationalisation
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How should the economic bond be measured ?
DeAngelo (1981) suggests that Client-Specific Quasi Rent (CSQR) will create the economic bond. CSQR is the “super profits” arising from the client relationship.Therefore, large fees may not create an economic bond as long as they do not generate “super profits”.
Fees = Normal Fees + Abnormal Fees
Normal Fees = ƒ ( size, complexity, risk) [Simunic 1980]
The Positive Abnormal fees = “super profits”.
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Abnormal audit fees estimationTAF = NAF + AAF ………. (1)
TAF = α0 + α1 LNTA + α2 INVREC + α3 EMPLOY + α4 ISSUE+ α5 FOREIGN + α6 EXORD + α7 LOSS + α8 LEVE+ α9 ROA+ α10 CURRENT + α11 Big4+ α12 PB + α13 AUDITSPEC + Industry dummy + Yearend dummy +HSI dummy+ H share dummy + Red Chip dummy + Year dummy +ξ ………..(2)
Keys:
TAF = natural log of fees paid to auditors for their financial statement audits (i.e., audit fees) in million Hong Kong dollars; LNTA = natural log of total assets in million Hong Kong dollars; INVREC = inventory and receivables divided by total assets; EMPLOY = square root of the number of employees + 1; ISSUE = 1 if there is issue of equity or debt in the current year, 0 otherwise; FOREIGN = 1 if the firm pays any foreign income tax, 0 otherwise; EXORD = 1 if the firm reports any extraordinary gains or losses, 0 otherwise; LOSS =1 if the firm reported a loss during the year, 0 otherwise; LEVE = leverage (total liabilities divided by total assets); ROA = return on assets (income before extraordinary items divided by total assets); CURRENT = current assets divided by current liabilities; BIG4 = 1 if the auditor is one of Big 4, 0 otherwise; PB =Price to Book ratio; AUDITSPEC = 1 if the auditor is the largest market shares holder within the client industry, 0 otherwise; Industry dummies = the industry classification of Worldscope; Yearend dummy =1 if the financial year is ended in 31 December, 0 otherwise; HSI dummy =1 if the company is a composite stock of Hang Seng Index, 0 otherwise; H Share dummy =1 if the company is listed as a H share, 0 otherwise; Red Chip dummy =1 if the company is listed as Red Chip, 0 otherwise; Year dummy =Financial year of the company
(Sources: Carcello et al., 2002,, Chaney, Jeter, & Shivakumar, 2004, Choi et al., 2005, Choi et al., 2006, Craswell et al., 1995, DeFond, Francis & Wong, 2000, DeFond et al., 2002, Francis & Stokes, 1986, Gist, 1992, Gul, Chen, & Tsui, 2003, Gul, Srinidhi & Shieh, 2002, Gul & Tsui, 1998, Larker & Richardson, 2004, Pong & Whittington, 1994, Sankaraguruswamy & Whisenant, 2005, Seetharaman, Gul, & Lynn, 2002, Simunic, 1980, Tsui, Jaggi & Gul, 2001, Whisenant, Sankaraguruswamy, & Raghunandan, 2003.For detail specifications of their models please refer to Appendix 4)
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Dechow & Dichev (2002) accrual quality (“DDAQ”)
Accruals = Informative (private information signalling) + non-informative (earnings management).non-informative accruals (are less likely to be realized as future cash flows ) = poor earnings quality.Dechow and Dichev (2002) measure the accrual quality by the residuals (or its standard deviation) of the accruals and cash flows regression. The higher the value indicates lower accrual quality (i.e. lower EQ).
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Accrual quality estimationTCAj,t = b0 + b1 CFOj,t-1 +b2 CFOj,t + b3 CFOj,t+1 +b4 ChgRevj,t
+ b5 PPEj,t + ε j,t ……… (3)
Keys:
TCAj,t = For company j in year t, net income minus cashflow from operations
CFOj,t-1 = For company j in year t-1, cashflow from operations
CFOj,t = For company j in year t, cashflow from operations
CFOj,t+1 = For company j in year t+1, cashflow from operations
ChgRevj,t = For company j in year t, the change of revenue from period t-1 to t
PPEj,t = For company j in year t, the gross value of property, plant and equipment
Source: Dechow and Dichev, 2002
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C-Score and conditional conservatism
Conditional and unconditional conservatism – (Ball and Shivakumar, 2005) “Unconditional Conservatism” is effectively a “known”bias and has little effect on EQ Conditional conservatism is firm-year specific – (Ryan, 2006).Khan and Watts (2007) propose C-Score, a firm-year specific conservatism measure, which is a linear function of firm and year specific attributes which are leverage, firm size, and price to book ratio
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C-Score estimationa) Yearly λ coefficients estimationX j, t = β 1,t + β 2,t D j,t + R j,t (μ 1,t + μ 2,t Size + μ 3,t PB + μ 4,t Lev)
+ D j, t * R j,t (λ 1,t +λ 2,t Size +λ 3,t PB +λ 4,t Lev) + ε j,t ……… (4)
b) Firm year specific C-Score estimationC-Score j, t = λ 1,t +λ 2,t Size j,t +λ 3,t PB j,t +λ 4,t Lev j,t ……. (4A)
Keys:
X j, t = net income before extraordinary items, scaled by the beginning of year market value of equity
D j,t = 1 if R ≦ 0, zero otherwise
R j,t = Annual returns beginning from the fifth month after the fiscal year end
Size = Natural log of the end of year market value equity
PB = Price to book ratio
Lev = Total liabilities divided by beginning of year market value of equity
Source: Khan and Watts (2007)
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The Research Model
IndependenceAudit
QualityEconomic
Bond
Positive abnormal audit fees
(POSAAF)
Earnings Quality
Operational
Measures
Constructs
Accrual Quality and
Conservatism
Control Variables
Firm and Auditor
CharacteristicsIndependent
Variables
Dependent variable
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The HypothesesPositive Abnormal Audit Fees
H1 (null): The positive abnormal audit fees (POSAAF) do not have a relation with earnings management, ceteris paribus.H1 (alternative): The positive abnormal audit fees (POSAAF) have a positive relation with earnings management, ceteris paribus.H2 (null): The positive abnormal audit fees (POSAAF) do not have a relation with accounting conservatism, ceteris paribus.
Negative Abnormal Audit FeesH3 (null): The negative abnormal audit fees (NEGAAF) do not havea relation with earnings management, ceteris paribus.H3 (alternative): The negative abnormal audit fees (NEGAAF) havea negative relation with earnings management, ceteris paribus.H4 (null): The negative abnormal audit fees (NEGAAF) do not havea relation accounting conservatism, ceteris paribus.
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4. Empirical procedure
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Data and Sample
Based on the market capitalization as of 31 December 2006, the top 350 Hong Kong companies (the “sample”) are selected from the Worldscope database. The sample has a total market capitalization of HK$ 14.68 trillion which is 98.30% of the population market capitalization. The sample is roughly 38% of the population in terms of number of companies.Fy1996 – FY2006All data are Winsorized at top and bottom 1%
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Number of observations
890With Fees + DDAQ783With Fees + C-Score
1,776With C-Score2,076With DDAQ
1,129With abnormal audit fees metrics (Fees)
3,850Full panel (11 yr x 350 firms)
Number of observations
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Abnormal audit fees and DDAQ relation estimation
DDAQ j, t = α0 + α1 SIZEj,t + α2 OPCYCLEj,t +α3 SALESVj
+ α4 LOSSDUMMYj,t +α5 ABFeesj,t +ε .......... (5)
Keys:
DDAQj,t = Accrual quality, absolute value of the residual from equation (3) for company j on year t
ABFeesj,t = abnormal audit fee metrics, POSAAF and NEGAAF are residuals from equation (2) for company j on year t scaled by natural log of total audit fees
SIZEj,t = Natural log of the total assets of company j at the end of year t
OPCYCLEj,t = Sum of the account receivables days and inventory days of company j on year t
LOSSDUMMYj,t =1 if net income < 0, otherwise = 0 for company j on year t
SALESVj=Standard deviation of (sales/ total assets) from 1996 to 2006 of company j
Source: Dechow and Dichev (2002)
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Abnormal audit fees and DDAQ Section A
controlsSection BPOSAAF
Section CNEGAAF
Section DAAF
Variable Expsign
Coefficient(t value)
Coefficient(t value)
Coefficient(t value)
Coefficient(t value)
(Constant) N/A -3137.85 -4532.69 -3077.81 -3191.20(-19.37***) (-8.80***) (-10.35***) (-13.30***)
SIZE (-) 425.66 558.21 410.80 426.14(24.50***) (11.02***) (13.08***) (17.19***)
OPCYCLE (+) 0.01 -0.27 -0.02 -0.05(0.13) (-1.47) (-0.17) (-0.60)
SALESV (+) 397.36 78.82 290.39 214.19(3.46***) (0.33) (1.70*) (1.50)
LOSSDUMMY (+) 601.89 737.46 487.72 612.53(8.07***) (4.86***) (4.19***) (6.44***)
ABFees 623.65 26.83 56.93(3.79***) (0.86) (-1.52)
n 1638 428 462 890
Adj R2 0.2800 0.3040 0.3030 0.2930
Keys:
T statistics are in parentheses,
*** = 1% sig,
** = 5% sig,
* = 1% sig
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Abnormal audit fees and C-Score relation estimation
C-Scoret = α0 +α1 C-Scoret-1 + α2 DDAQt + α3 VORt + α4 Age +α5 Cyclet
+α6 ABFeest +ε
Sources: Khan and Watts (2007) and Chi et al. (2007)
Keys:
C-Scoret = C-Score of year t
C-Scoret-1 = C-Score of year t-1
DDAQt = Accrual quality measure of Dechow and Dichev of year t
VORt = Standard deviation of the firm level monthly return for year t
Age = Number of year that the firm is listed during the period 1996 to 2005.
Cyclet = Depreciation expenses at year t divided by the gross fixed assets at the beginning of the year
ABFeest = AAFt - Abnormal audit fees at year t; or
POSAAFt = Positive abnormal audit fees at year t; or
NEGAAFt = Negative abnormal audit fees at year t
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Abnormal audit fees and C-Score Variable
ExpSign
Section Acontrols
Section BPOSAAF
Section CNEGAAF
Section DAAF
Coeffieicent(t value)
Coeffieicent(t value)
Coeffieicent(t value)
Coeffieicent(t value)
(Constant) 0.505 0.441 0.106 0.294(2.144**) (0.843) (0.261) (0.914)
C-score t-1 (+) 0.045 0.165 0.032 0.098(3.735***) (4.303***) (0.952) (3.894***)
AQ t (-) 0.000 0.000 0.000 0.000(-7.517***) (-2.593***) (-3.6***) (-4.471***)
VOR t (+) -0.046 -0.053 -0.044 -0.055(-3.06***) (-1.373) (-1.118) (-1.989**)
Age (-) -0.011 -0.026 -0.005 -0.014(-0.47) (-0.504) (-0.128) (-0.429)
Cycle t (-) -1.901 -3.007 -0.494 -1.916(-1.805) (-1.415) (-0.205) (-1.22)
ABFees t 0.260 0.133 0.141(2.042**) (3.106***) (3.227***)
n 1563 374 409 783
Adj R2 0.069 0.128 0.075 0.095
Keys:
T statistics are in parentheses,
*** = 1% sig,
** = 5% sig,
* = 1% sig
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5. Results
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DDAQ results
POSAAF is negatively related to accrual quality (+ve with DDAQ)
NEGAAF and AAF have no significant relation with DDAQ
Srinidhi and Gul (2006) find no significant relation between unexpected audit fees (AAF) and accrual quality, using US data from 2000 to 2001- Similar results
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C-Score resultsBoth POSAAF and NEGAAF have positive relations with C-Score. And the coefficients of POSAAF is twice as NEGAAF nonlinearity.
Gul et al. (2002) using Hong Kong data from 1990 to 1997 find that total audit fee has a negative relation with conservatism. Repeat the test on total audit fees, the coefficient is -0.167 (t = - 4.897, p-value = 0.000) Similar resultsKrishnan (2004) using US data from 2000 to 2001 finds that greater conservatism for high-fee clients (POSAAF) than low-fee clients. Similar resultsJones et al. (2006) using US data from 2000 to 2004 find that firms who pay high unexpected fees (similar to POSAAF in this study) have higher conservatism in their financial statements. Similar results
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Nonlinearity
Yes
Yes
Nonlinearity
Coefficient of POSAAF is twice as NEGAAF
+VE+VEC-Score
Insig.+VE DDAQ
RemarksNEGAAFPOSAAF
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Hypotheses verification
Hypothesis Status Agree with Prediction?
H1 (null): The positive abnormal audit fees (POSAAF) do not have a relation with earnings management, ceteris paribus.
Rejected Yes
H1 (alternative): The positive abnormal audit fees (POSAAF) have a positive relation with earnings management, ceteris paribus.
Accepted Yes
H2 (null): The positive abnormal audit fees (POSAAF) do not have a relation with accounting conservatism, ceteris paribus.
Rejected Yes
H3 (null): The negative abnormal audit fees (NEGAAF) do not have a relation with earnings management, ceteris paribus.
Accepted No
H3 (alternative): The negative abnormal audit fees (NEGAAF) have a negative relation with earnings management, ceteris paribus.
Rejected No
H4 (null): The negative abnormal audit fees (NEGAAF) do not have a relation accounting conservatism, ceteris paribus.
Rejected Yes
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Additional TestsAutocorrelationLowballingSOX effectsC-Score on different groups of firmsDropping firms with marginal POSAAF and NEGAAFNonaudit fees and abnormal audit fees…… Results are substantially the same as the main test!
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6. Conclusions
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Concluding remarksThis study shows association between abnormal audit fees and audit quality and the nonlinearity of abnormal audit fee metrics. But we cannot infer POSAAF must cause lower audit quality. (Higher audit effort will also cause POSAAF).POSAAF may not be the only source of economic bond. It will be a challenge for researchers to find a more comprehensive model to capture factors affecting the economic bond.A funny paradox --- When the association of POSAAF and audit quality is more exposed, this will make such association weaker due to the shifting of channels of benefits delivery.
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Contributions of this studyi) Provide empirical evidence that earnings management is positively associated with POSAAF; ii) Provide empirical evidence that conservatism is positively associated with POSAAF; iii) Provide empirical evidence on the nonlinear nature of abnormal audit fees; iv) Provide additional evidence on the research on accounting conservatism using the latest measure of conservatism (C-Score); and v) Provide additional empirical evidence from Hong Kong on the research of audit quality.
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LimitationsAudit quality can be expressed in many contexts. Using accrual quality and conservatism as measures for audit quality may omit other important contexts.Although the accrual quality measure of Dechow and Dichev (2002)and the C-Score of Khan and Watts (2007) are well accepted as good measures, one cannot rule out the possibility of measurement errors.Even though the audit fee model of this study has an adjusted R2 of 0.733, there is still a possibility that important variables are omitted from the model. For example, nonaudit service fees, and various corporate governance variables are totally ignored from the measuring of abnormal audit fees. Hence, the POSAAF and NEGAAF may be estimated incorrectly. The model determining abnormal audit fees only takes in variables that relate to the supply of audit services and assuming all demand variables are uniform for all firms. It may not be appropriate to assume that the demand variables are uniform for all firms. The small sample size and the sampling method may create unknown bias in the results.
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7. Q&A
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Supporting slides
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What is independence ?“the conditional probability of reporting a discovered breach”(DeAngelo, 1981a);“the ability to resist client pressure” (Knapp, 1985);“an attitude/state of mind” (Moizer, 1994);“A function of character, with the attributes of integrity and trustworthiness“ (Magill and Previts, 1991);“An absence of interests that create un acceptable risk of bias” (AICPA, 1997); and“Freedom from those pressures and other factors that compromise, or can reasonably be expected to compromise, an auditor’s ability to make unbiased audit decision” (ISB, 2000)In summary, they all relate to Objectivity and Integrity(Dunmore and Falk, 2001)
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The performance of auditorsIn the US, the total audit fees for 5500 largest publicly listed firms in 2003 was US$ 3.4 billion which represents 0.04% of sales and 0.03% of the market capitalization of these firms, while outright audit failure is infrequent, far less than 1% annually (Francis,2004).
27% of bankruptcies are preceded by going concern audit reports and 47% of bankruptcies are preceded by unqualified audit reports. This indicates that 73% of the bankrupted companies are issued with ‘false negative’ reports (Carcello and Palmrose,1994).
During 1990 to 1994, 1003 going concern audit reports were issued while only 143 among these were finally bankrupted. This indicated that 85% of the going concern reports are ‘false positive’ (Francis and Krishnan, 2002)
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Interaction of abnormal fees metrics and audit quality
Demand of high audit effort
High audit fee
(POSAAF)High Audit Quality
Creation of Economic Bond
High audit fee
(POSAAF)Low Audit Quality
Low audit fee
(NEGAAF)Low Audit Quality
Demand of low audit effort
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Explanations for the positive relation between C-Score and POSAAF
First, it may be due to managerial bonding, which caused higher conservatism and demand of additional audit effort. Second, C-Score measures the asymmetric timeliness of responses to good and bad news. It does not indicate that a high level of conservatism is associated with high earnings quality. In fact, high level of conservatism is a sign of weak earnings quality (Schipper and Vincent, 2003) ! Third, one should not assume that opportunistic earnings management activities will always be making the financial statements less conservative.
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7 attributes of Earnings Quality (“EQ”) There are many definitions for EQ. Schipper and Vincent (2003) suggest EQ as the extent to which reported earnings faithfully represent the Hicksian income [1] . Since there is no uniform definition for EQ, there are numerous measures of it. At times some of these measures are contradictory. In order to get a better picture, it is advisable to look at a number of measures (Abdelghany, 2005).Francis et al. (2004) summarize 7 attributes for EQ. They are: accrual quality, persistence, predictability, smoothness, value relevancy, timeliness, and conservatism. The first 4 are accounting based attributes and the last 3 are market based attributes
[1] Hicksian income is defined as the amount that can be paid out from a firm during a period and leaving the firm equally well off at the beginning and the end of the period (Hicks 1939, 176).
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POSAAF estimationVariable Exp
signs Ceofficients t p-value
(Constant) N/A -2.988 -19.240 0.000LNTA (+) 0.399 21.652 0.000INVREC (+) 0.553 5.142 0.000EMPLOY (+) 0.004 11.761 0.000ISSUE (+) 0.028 0.646 0.518FOREIGN (+) 0.311 8.262 0.000EXORD (+) 0.115 3.429 0.001LOSS (+) 0.254 3.784 0.000LEVE (+) 0.198 1.937 0.053ROA (-) 0.002 1.000 0.317CURRENT (-) -0.021 -2.983 0.003Big4 (+) -0.052 -1.049 0.295PB (+) 0.013 2.171 0.030AUDITSPEC (+) 0.100 2.957 0.003Yearenddummy N/A -0.144 -3.801 0.000
n 1,129
Adjusted R2 0.733
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POSAAF and NEGAAF by year
Average POSAAF & NEGAAF by year
0.0000
0.2000
0.4000
0.6000
0.8000
1.0000
1.2000
1.4000
1.6000
1.8000
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
POSAAF NEGAAF
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Mean DDAQ by year
Mean DDAQ By year
0.00200.00400.00600.00800.00
1000.001200.001400.001600.001800.00
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Year
DD
AQ
Mean DDAQ
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Mean C-Score by yearMean C-Score by year
-1.50
-1.00
-0.50
0.00
0.50
1.00
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
Mean C-Score
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Additional test - Autocorrelation
NEGAAF coefficient t p-value Durbin-Watson
OLS 26.830 0.860 0.390 1.615Prais-Winsten 15.816 0.507 0.612 2.008
POSAAF coefficient t p-value Durbin-Watson
OLS 0.260 2.042 0.042 1.231Prais-Winsten 0.212 1.851 0.065 2.221
NEGAAF coefficient t p-value Durbin-Watson
OLS 0.133 3.106 0.002 1.240Prais-Winsten 0.132 3.095 0.002 1.999
AAF coefficient t p-value Durbin-Watson
OLS 0.141 3.227 0.001 1.135Prais-Winsten -0.001 -0.483 0.629 0.715
DDAQ
C-Score
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Additional test - LowballingFor DDAQ regressions
Coefficient t p-value n Adj R2
POSAAF 623.65 3.79 0.000 428 0.304POSAAF 3-year-mean 532.39 1.93 0.055 210 0.312
NEGAAF 26.83 0.86 0.390 462 0.303NEGAAF 3-year-mean 24.41 0.38 0.708 224 0.379
AAF 56.93 4.52 0.128 890 0.293AAF 3-year-mean 73.63 1.15 0.252 434 0.342
For C-Score regressions
POSAAF 0.26 2.04 0.042 374 0.128POSAAF 3-year-mean 0.49 3.22 0.002 195 0.263
NEGAAF 0.13 3.11 0.002 409 0.075NEGAAF 3-year-mean 0.14 1.81 0.072 224 0.125
AAF 0.14 3.23 0.001 783 0.095AAF 3-year-mean 0.17 2.57 0.011 419 0.165
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Additional test- SOX effectDDAQ
Coefficient t p-value n R2POSAAF pre-SOX 387.563 1.695 0.092 214 0.211POSAAF post-SOX 819.714 3.377 0.001 214 0.388POSAAF-Overall 623.649 3.789 0.000 428 0.304
NEGAAF pre-SOX 9.053 0.233 0.816 229 0.347NEGAAF post-SOX 51.624 1.037 0.301 233 0.305NEGAAF-Overall 26.832 0.860 0.390 462 0.303
C-ScoreCoefficient t p-value n R2
POSAAF pre-SOX 0.114 0.504 0.615 173 0.122POSAAF post-SOX 0.340 2.647 0.009 201 0.270POSAAF-Overall 0.260 2.042 0.042 374 0.128
NEGAAF pre-SOX 0.164 1.925 0.056 188 0.089NEGAAF post-SOX 0.098 2.412 0.017 221 0.129NEGAAF-Overall 0.133 3.106 0.002 409 0.075
pre-SOX = before 2003post-SOX = 2003 onwards
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Additional test - C-score comparison
Firm attributes n MeanC-Score t P-value
HSI 259 -0.7848Non-HSI 1665 0.3252 -13.980 0.000
PRC 459 0.0222non-PRC 1465 0.2239 -3.031 0.002
Big firms 663 -0.2230Small firms 1261 0.3855 -10.451 0.000
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Additional test – DDAQ and 90% abnormal audit fees metrics
DV=DDAQ Section APOSAAF
Section B90%
POSAAF
Section CNEGAAF
Section D90%
NEGAAF
Section EAAF
Section F90% AAF
Variable Expsign
Coefficient(t value)
Coefficient(t value)
Coefficient(t value)
Coefficient(t value)
Coefficient(t value)
Coefficient(t value)
(Constant) N/A -4532.69 -3443.81 -3077.81 -2595.15 -3191.20 -1968.90(-8.80***) (-7.67***) (-10.35***) (-9.33***) (-13.30***) (-11.26***)
SIZE (-) 558.21 433.51 410.80 355.37 426.14 277.32(11.02***) (9.38***) (13.08***) (11.62***) (17.19***) (14.59***)
OPCYCLE (+) -0.27 -0.17 -0.02 0.01 -0.05 0.02(-1.47) (-1.32) (-0.17) (0.16) (-0.60) (0.28)
SALESV (+) 78.82 60.22 290.39 200.60 214.19 158.26(0.33) (0.35) (1.70*) (1.38) (1.50) (1.72*)
LOSSDUMMY (+) 737.46 526.45 487.72 382.77 612.53 279.66(4.86***) (4.76***) (4.19***) (3.72***) (6.44***) (4.36***)
ABFees 623.65 467.86 26.83 19.96 56.93 36.24(3.79***) (3.75***) (0.86) (0.76) (-1.52) (1.54)
n 428 390 462 413 890 796
Adj R2 0.3040 0.2490 0.3030 0.2680 0.2930 0.2350key
*** 1 % significance** 5 % significance
* 10 % significancet statistics in parentheses
Version 1.0 DBA VIVA Presentation 28 July 2008 52
Additional test – C-Score and 90% abnormal audit fees metrics
DV=C-Score ExpSign
Section APOSAAF
Scetion B90%
POSAAF
Section CNEGAAF
Section D90%
NEGAAF
Section EAAF
Section F90% AAF
Coeffieicent(t value)
Coeffieicent(t value)
Coeffieicent(t value)
Coeffieicent(t value)
Coeffieicent(t value)
Coeffieicent(t value)
(Constant) 0.441 0.379 0.106 0.065 0.294 0.285(0.843) (0.762) (0.261) (0.148) (0.914) (0.896)
C-score t-1 (+) 0.165 0.218 0.032 0.046 0.098 0.111(4.303***) (5.443***) (0.952) (1.339) (3.894***) (4.269***)
DDAQ t (-) 0.000 0.000 0.000 0.000 0.000 0.000(-2.593***) (-1.147) (-3.6***) (-3.17***) (-4.471***) (-2.415**)
VOR t (+) -0.053 -0.016 -0.044 -0.045 -0.055 -0.025(-1.373) (-0.348) (-1.118) (-0.821) (-1.989**) (-0.683)
Age (-) -0.026 -0.026 -0.005 -0.005 -0.014 -0.017(-0.504) (-0.524) (-0.128) (-0.117) (-0.429) (-0.537)
Cycle t (-) -3.007 -2.152 -0.494 0.264 -1.916 -1.659(-1.415) (-0.942) (-0.205) (0.101) (-1.22) (-0.983)
ABFees t 0.260 0.229 0.133 0.139 0.141 0.137(2.042**) (1.869*) (3.106***) (3.153***) (3.227***) (3.189***)
n 374 340 409 367 783 699
Adj R2 0.128 0.111 0.075 0.063 0.095 0.056
key 1 % significance5 % significance10 % significance
27
Version 1.0 DBA VIVA Presentation 28 July 2008 53
Additional test - Nonaudit fees
Pearsoncorrelation ANF AAF POSANF POSAAF NEGANF NEGAAF
ANF 1-
AAF 0.0027 1(0.4891) -
POSANF 1.0000 0.4325 1(0.0000) (0.0013) -
POSAAF 0.3122 0.0714 0.7011 1(0.0121) (0.2542) (0.0003) -
NEGANF 0.9959 -0.0293 N/A 0.3467 1(0.0000) (0.4158) N/A (0.0259) -
NEGAAF 0.1422 0.2507 0.2560 N/A 0.2354 1(0.1623) (0.0069) (0.1034) N/A (0.1341) -
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