AUDIT QUALITY AND FINANCIAL REPORT DISCLOSURE. Philip D. Palmer 1, 2. Flinders Business School, Flinders University, Adelaide, Australia

Transcription

1 AUDIT QUALITY AND FINANCIAL REPORT DISCLOSURE Philip D. Palmer 1, 2 Flinders Business School, Flinders University, Adelaide, Australia JEL Classification: M41 Key Words: Auditor Quality, Mandatory Disclosure, Agency Theory, International Accounting Standards Flinders Business School Research Paper Series ISSN Philip D. Palmer, Flinders Business School, Flinders University, GPO Box 2100, Adelaide, South Australia, 5001, phone , fax , Philip.Palmer@flinders.edu.au. 2 The author would like to thank Carol Tilt for her helpful input, comments and feedback on this paper. 1

2 AUDIT QUALITY AND FINANCIAL REPORT DISCLOSURE ABSTRACT This study investigates the role of auditor quality in annual report disclosure. It is hypothesized that the extent and quality of annual report disclosure is related to the quality of the auditor, proxied by size. Due to risk to their reputation capital, in uncertain situations, auditors of higher quality will encourage greater and higher quality disclosures. The study is based on a cross-section of 150 Australian listed firms and uses the uncertainty surrounding the adoption of the International Financial Reporting Standards as an opportunity to examine this issue. The study provides evidence that companies audited by higher quality auditors have greater disclosure in terms of both extent and quality. 2

3 1. Introduction This study investigates whether companies, whose annual reports are audited by higher quality auditors, disclose more qualitative information and whether that disclosure is of better quality than those companies whose reports are audited by lower quality auditors. This research contributes to the broader question of how auditor quality impacts financial reporting quality and attempts increase our understanding of financial report disclosures. Prior disclosure studies have generally focused on whether an item is disclosed or not, or count the number of disclosure items as a proxy for audit quality. The current study extends previous research by investigating whether the information provided by companies audited by Big 4 auditors is not only quantitatively more, but of better quality in terms of informativeness, than those companies audited by non-big 4 auditors. The study focuses on disclosure made in compliance with AASB 1047, Disclosing the Impacts of Adopting Australian Equivalents to International Financial Reporting Standards. Treating audit quality as a dichotomous variable (Big 4/non-Big 4), the study tests the proposal that companies audited by Big 4 auditors disclose more information about the impact of adoption of Australian Equivalents of International Financial Reporting Standards (AIFRS) than those companies audited by non-big 4 auditors. This is due to the argument that larger auditors have more to lose by being seen to be associated with lower quality audits (Firth & Liau-Tan, 1998). Other variables, expected to be associated with disclosure levels, are controlled for in the study. The transition to AIFRS provides an excellent opportunity to examine the issue of auditor quality. Firstly, AASB 1047 disclosures have the advantage of being 3

4 discretely and easily identified and isolated in the notes of the annual report and thus the extent of disclosure can be directly measured. Although disclosure under AASB 1047 is mandatory, the amount of information released by each company is determined by the company and not prescribed by AASB The extent and quality of disclosure is therefore in effect voluntary. This interaction is recognised in other studies including Wallace et al. (1994) and Lang and Lundholm (1993, p. 246), who argue that while disclosure may be mandated by regulatory bodies, considerable latitude remains in determining what information is actually provided. Additionally, following the argument of Lee et al. (2006) who investigate auditor quality and initial public offerings (IPO), by examining attributes of mandatory disclosure factors associated with the extent and quality of disclosure which themselves may also be determinants of the decision to voluntarily provide such information are effectively controlled for. The transition to AIFRS has been of major significance to the financial reporting landscape in Australia. The adoption of AIFRS is a generational change (PricewaterhouseCoopers, 2004); bigger in disruption than the introduction of the goods and services tax in 2000 (Haswell & McKinnon, 2002). Of major concern to various stakeholders was the possibility of adverse share price reactions (Dodd and Sheehan, 2004). Additionally, changes to reported profit may mean a revision to loan covenants, dividends payments and profit incentive schemes (Pound, 2004). Jones and Higgins (2006) report that some companies are likely to have devoted considerable attention and resources to the adoption of AIFRS. Costs to companies in terms of time and resources in preparing for the change was highly significant (Ham, 2002) and in some cases in the tens of millions of dollars (Moullakis, 2004). Therefore there is 4

5 merit in examining disclosures made to comply with the requirements of AASB 1047 as these disclosures are significant in terms of impact on the company and interest to various stakeholders. Larger auditors, concerned to preserve their reputation, are hypothesised to have strongly encouraged their clients to provide comprehensive disclosure (Craswell & Taylor, 1992). The exploratory focus on the quality of disclosure is also important. The role of AASB 1047 is to provide users of financial reports with relevant and reliable information about the impacts of the changes in accounting policies resulting from adoption of AIFRS (AASB, 2004). Therefore it is not fundamentally the amount of disclosure that is important but the quality of that disclosure in terms of assisting users to understand the impact of the change. There must necessarily be, however, some interaction between these two constructs. The proceeds as follows: Section 2 provides the theoretical background to the study and develops the hypotheses. Section 3 outlines the research methods used to test the hypotheses. Section 4 reports the study s results. Section 5 concludes the study by discussing the implications of the research findings, the potential limitations of the study and considering future areas of research. 2. Prior literature and hypothesis development Agency costs are frequently cited as an explanation of why companies may disclose financial information (e.g. Chow & Wong-Boren, 1987; Hossain & Adams, 1995). Such disclosures assist principals to monitor the activities of their agents (Jensen & Meckling, 1976). The adoption of AIFRS has the potential to impact on the reported profits of Australian companies (Pound, 2004) and the majority of companies 5

6 surveyed by Jones and Higgins (2006) anticipated a negative impact from adoption of AIFRS and therefore potential negative impacts on share prices (Dodd & Sheehan, 2004). Further, where a negative impact on profitability was anticipated companies were found to place higher importance on the issues surrounding adoption and how they could communicate their continued underlying profitability to their shareholders (Jones & Higgins, 2006). As a means of keeping stakeholders informed of the likely impact of the adoption AIFRS the AASB released AASB The standard applied to annual and interim reporting periods ending on or after 30 June 2004 to first time adoption of AIFRS. AASB 1047 was of major significance as it required companies to disclose their level of preparedness leading up to the adoption of AIFRS, and what they consider the impacts of adoption to be. The objective of the standard was to ensure users of financial reports had information about the impact of adoption, as well as information concerning how companies were preparing for adoption. Auditing reduces the information asymmetries that exist between management and external stakeholders by allowing an independent external party to verify the validity of the financial statements (Becker et al., 1998). This external independent process is particularly important to corporate governance and the oversight of companies (Francis, 2004). External audits play a strong corporate governance role and are instrumental in supporting transparent financial reporting (Ashbaugh & Warfield, 2003). There was uncertainty regarding the impact on companies of the adoption of AIFRS. Financial reports play a critical role in investor decision making (Barton, 2005) and 6

7 companies had an incentive to communicate their intrinsic value by engaging a highquality auditor (Francis, 2004). Dunn and Mayhew (2004) provide evidence that firms select auditors as part of their disclosure strategy, suggesting the choice of an industry-specialist signals a firm s decision to provide high quality disclosures. Clarkson et al. (2003) find that disclosures made by companies in a similar uncertain situation (Year 2000 systems issue) are greater for clients of larger (the then Big 6) auditors. The relationship between audit firm size and audit quality is well established in the literature (Francis and Krishnan, 1999) with auditor size and quality likely to be strongly correlated (DeAngelo, 1981). Francis (2004, p. 353) argues that evidence from financial statements supports the argument that audits by bigger auditors are of higher quality and states that the collective evidence is strongly supportive that audits of large (Big 4) accounting firms are of higher quality. Francis (2004) suggests one of the reasons for this is that large international auditors have established brand name reputations and therefore have incentives to protect their reputation by providing high-quality audits. Auditors reputations may be at risk if they are associated with firms whose reporting practices are perceived as being of lower quality (DeAngleo, 1981). Auditors, concerned to preserve their reputation, will strongly encourage clients to provide comprehensive disclosure (Craswell and Taylor, 1992). Greater Year 2000 remediation program disclosure by clients of larger auditors is presented as evidence of conservative auditor behaviour by the larger auditors in a desire to maintain their reputation capital (Clarkson et al., 2003). 7

8 The most common proxy for audit quality is a dummy variable for Big 4/non-Big 4 auditor (Becker et al., 1998). This differentiation for audit quality is widely used in the literature (Becker et al., 1998; Francis & Krishnan, 1999; Lee et al., 2006) and is utilised in the current study as a measure of audit quality. Lee et al. (2006, p.183) state that there is an assumption that the quality of financial statement data is a joint function of management representations and the audit process. It has been suggested that the contents of annual reports are not only audited but also influenced by auditors (Wallace et al., 1994). The larger and better known the auditor, the greater influence they may be able to exercise (Firth, 1979). Thus, companies represented by the big international auditors are likely to provide more detail in their annual reports than companies that are not (Wallace et al., 1994). Many companies are expected to rely heavily on their auditors for advice regarding the adoption of AIFRS and the larger the firm the greater will be the involvement of the auditor (Jones & Higgins, 2006). Therefore it is expected that there will be a positive relationship between auditor size and the extent and quality of disclosure. H 1 : The clients of higher quality auditors disclose more AIFRS adoption information than clients of lower quality auditors. If the use of larger auditors can be an indication of higher quality audits and enhanced credibility and financial accounting disclosures (Bushman et al. 2004; Francis 2004) then it is reasonable to expect that not only will the extent of disclosure be greater, but that on average the quality of disclosure will be higer. In prior research on reporting and disclosure expressions such as adequate (Singhvi & Desai, 1971), comprehensiveness (Wallace et al., 1994) and depth (Naser et al., 2002) have been used to describe the quality of financial report disclosure. In most cases, 8

9 however, quality of disclosure was only used in the sense of measuring the number of items disclosed. Studies that investigate both the quantity and quality of disclosure base the measurement of quality on the depth of information; that is, on consideration of whether the disclosure improves a user s understanding of the financial statements (Wallace et al., 1994; Clarkon et al, 2003, Palmer, 2008, forthcoming). Quality is difficult to define and measure in financial accounting information and quality in relation to narrative accounting disclosures is complex, context-sensitive and subjective (Beattie et al., 2004, p. 229). The aspect of quality that is being investigated and measured in this study is the perceived informativeness of the disclosure. Further detail regarding the operationalising of this measure of a quality score is detailed in Section 3.2. H 2 : The clients of higher quality auditors have better quality disclosure of AIFRS adoption information than clients of lower quality auditors. 3. Research Design 3.1 Sample Selection The relevant population of the study is all companies listed on the Australian Stock Exchange (ASX) at 31 December 2004 with balance dates on or between 30 June 2004 and 31 December A final random sample of 150 companies was selected. 1 Table 1 presents a breakdown of the sample based on GICS sector 2, showing the broad cross-section of the companies included in the sample. 1 A minimum final sample size of 150 was desired for testing individual predictors in standard multiple regression (Tabachnick & Fidell, 2001). Trusts, companies without GICS classification or sector codes, with negative equity, using international accounting standards, suspended or delisted or not reporting between the dates covered by the requirements of AASB 1047 were not included in the sample. 2 GICS is a joint Standards and Poor s/morgan Stanley Capital International product which aims to standardise industry classifications and definitions (ASX, 2005). 9

10 INSERT TABLE 1 ABOUT HERE The disclosures made to comply with AASB 1047 are in narrative form in the notes accompanying companies financial reports, accessed from the Connect 4 Database. 3.2 Disclosure index The analysis in the current study considers the total extent of disclosures as well as the quality of disclosures; that is, inferences are drawn from what companies have disclosed in their notes. Thus, the unit of analysis for this study is sentences, which is the preferred unit of analysis if a meaning is to be inferred (Gray et al., 1995). The total number of sentences is used as the measure of the extent of disclosure concerning the adoption of AIFRS by each company in the study. Each sentence was given a qualitative score, based on the perceived informativeness of the information disclosed. Scores were awarded from 0 to 5 based on a scale where the greater the specificity of the information, the more useful it is deemed to be and therefore of greater quality. 3 After rating each sentence, the qualitative score for each company is then totalled. The rating scheme employed in this study is outlined in Table Empirical model INSERT TABLE 2 ABOUT HERE The hypotheses in the study, outlined in the previous section, are tested using the following models: DISCE = α + β 1 AUD + β 2 SIZE + β 3 PROF +β 4 LEV + ε DISCQ = α + β 1 AUD + β 2 SIZE + β 3 PROF +β 4 LEV + ε Where the extent of AIFRS adoption disclosure (DISCE) is measured by the number of sentences disclosed and the quality of disclosure (DISCQ) is the quality score measured using the index discussed above. 3 A similar (four point) scale is used by Clarkson et al. (2003) when considering companies voluntary disclosures concerning the year 2000 systems issue. Likewise a four point scale is used by Palmer (2008, forthcoming) considering determinants of certain aspects of AASB 1047 disclosures. 4 The coding rules and the coding of a sample of companies were reviewed by two independent accounting researchers. 10

11 A dummy variable (1,0) is used to proxy for audit quality (AUD) (e.g. Becker et al., 1998; Francis & Krishnan, 1999; Lee et al., 2006). Auditor is classified as being either a member of the Big 4 (Deloitte Touche Tohmatsu, Ernst & Young, PricewaterhouseCoopers, KPMG), or non-big 4. The control variables are explained in the following section. 3.5 Control variables Following Palmer, (2008, forthcoming) who considers factors associated with AIFRS disclosures, several measures which have been identified in the literature as determinants of disclosure are included in the study as control variables. Corporate size (SIZE) is consistently found to be significantly and positively related to the extent of disclosure (Lang & Lundholm, 1993; Clarkson et al., 2003). Jones and Higgins (2006) report that larger firms tend to have greater knowledge of the expected financial reporting impacts of adopting AIFRS. Larger companies are more likely to have the resources in place to prepare for an event such as the adoption of AIFRS (Ahmed & Nicholls, 1994; Hossain & Adams, 1995) and are likely to have a higher level of internal reporting (Owusu-Ansah, 1998). Additionally, larger companies are likely to come under more scrutiny from financial analysts (Hossain & Adams, 1995) and shareholders (Cooke, 1989) than smaller companies, leading to pressure for better disclosure. The current study adopts total assets as a measure of corporate size. 5 5 Size has also been measured as net sales (e.g. Cooke, 1989) and market capitalisation (e.g. Chow & Wong-Boren, 1987). 11

12 The profitability of a company (PROF) is also regularly included in disclosure studies and hypothesised to be positively associated with the extent of a company s disclosure (Inchausti, 1997; Owusu-Ansah, 1998). The majority of companies surveyed by Jones and Higgins (2006) anticipated a negative impact from adoption of AIFRS and therefore potential negative impacts on share prices (Dodd & Sheehan, 2004). Where a negative impact is anticipated companies are found to place higher importance on the issues surrounding adoption and how they can communicate their continued underlying profitability to their shareholders (Jones & Higgins, 2006). Therefore it is expected that more profitable companies will have a greater extent and quality of disclosure than less profitable firms. Return on Assets (e.g. Raffournier, 1995) is used as the measure of profitability in this study. Companies with a higher level of leverage (LEV) have been found disclose more information (Inchausti, 1997). Companies with a higher gearing level have a greater obligation to satisfy the informational needs of its long-term creditors (Wallace et al., 1994). The adoption of AIFRS has the potential to impact on the balance sheet (Goodwin & Ahmed, 2006) which may in turn impact debt covenants with consequences for stakeholders (Ormrod & Talor, 2004). Thus, it is expected that companies with greater levels of debt have a greater extent and quality of disclosure to explain possible changes to their balance sheets. Debt to Assets (e.g. Alsaeed, 2005) is the measure of leverage used in this study. 3.6 Statistical Tests Both univariate and multivariate methods are used to test the hypotheses developed above. Spearman s Rank Order correlation coefficients are used to investigate the relationship between the explanatory variables, while Mann-Whitney U tests are used 12

13 to examine the relationships between auditor size and the dependent variables. Kruskal-Wallis tests are conducted to test differences in the ranks of the auditors. The multivariate test used in this study is standard multiple regression. 4. Results 4.1 Descriptive Statistics Table 3 contains the descriptive statistics for the dependent variables (Part A), the non-categorical independent variables (Part B) and categorical independent variable (Part C) defined in the previous section. Interestingly, Panel B of Table 3 shows that the mean of extent and quality of disclosure is significantly higher for those companies audited by higher quality auditors. This relationship is further examined using univariate and multivariate tests. INSERT TABLE 3 ABOUT HERE The variables used in this study are either categorical or are non-normally distributed. Thus non-parametric univariate tests are employed. 4.2 Univariate Tests Correlation analysis is used to test the relationship between the dependent and independent variables. Table 4 shows the relevant Spearman s Rank Order correlation coefficients. INSERT TABLE 4 ABOUT HERE Cohen (1988) suggests that correlations of 0.10 to 0.29 are small, 0.30 to 0.49 are medium and 0.50 to 1.0 are large. As can be seen from the first column of the table the correlation coefficients between the extent of disclosure and the independent variables are significant at the indicated levels 6. Using Cohen s (1988) guidelines, the correlation between the extent of disclosure and auditor is large providing some 6 Probability values of or better are regarded as significant for the purpose of this study. 13

14 support for hypothesis 1, that companies audited by higher quality auditors disclose more information. Table 4 also contains the Spearman rank correlation coefficients for the dependent variable for the quality of disclosure and the independent variables included in this study. As can be seen from the second column of the table there is (using Cohen s (1988) guidelines) a large correlation between the quality of disclosure and auditor size, providing some support for hypothesis 2, that companies audited by higher quality auditors have better disclosures. All of the correlations shown in Table 4 between independent variables are significant at the level. There is a medium to large correlation between Assets and the other variables. Raffournier (1995, p. 275), commenting on the high correlation between size and the explanatory variables used in his study, notes that size probably captures most of other influences because of a high correlation with many variables. The existence of interaction between the independent variables indicates that multivariate analysis is required to account for such relationships. The relationship between the dependent variables and the categorical explanatory variable Auditor, is further investigated using the Mann-Whitney test. The results of the Mann-Whitney tests are presented in Table 5 INSERT TABLE 5 ABOUT HERE The results of the Mann-Whitney U test indicate that there is a statistically significant difference in both Extent and Quality of disclosure between companies audited by Big 4 auditors and those audited by others ; that is, the test provides evidence to 14

15 support hypotheses 1 and 2, that on average, companies audited by bigger auditors have higher Extent and Quality scores. Kruskal-Wallis tests were also conducted. The Kruskal-Wallis test is similar in nature to the Mann-Whitney U test, but allows comparison of scores on a continuous variable for more than two groups. Scores are converted to ranks and the mean rank for each group is compared. This test does not therefore rely on classification of audit firm as Big 4 or other. The separate audit firms and other category listed in Part C of Table 3 form the basis of the five samples used in this test. The results of the tests are shown in Table 6. INSERT TABLE 6 ABOUT HERE The significant test results indicate that for both dependent variables the null hypothesis of equal means is rejected, again providing support for hypotheses 1 and 2, indicating that the presence of an auditor effect on the extent and quality of disclosure is supported. An inspection of the mean ranks for the groups suggests that the bigger auditors have significantly higher extent scores (KPMG, Ernst & Young having the highest) than the other group. The overall result is similar for the quality score; however, while KPMG and Ernst & Young had similar extent scores, Ernst & Young s quality score is higher than that of KPMG. The results raise the possibility that while companies audited by bigger auditors may disclose more information, some of that information is not necessarily of better quality or improve a reader s understanding (Wallace et al., 1994). 4.3 Multivariate Tests Multiple regression analysis was used for multivariate testing of the hypotheses. Each of the dependent variables, DISCE and DISCQ, was regressed against the independent 15

16 variables of SIZE, LEV and PROF and the dummy variable AUD. The results of these regressions are reported in Table 7. INSERT TABLE 7 ABOUT HERE Extent The multiple regression model is highly significant (p 0.001) 7. The coefficient of determination (adjusted R 2 ) indicates that 27.5% of the variation in the dependent variable is explained by variation in the independent variables. The coefficient for AUD and SIZE are statistically significant (p and p 0.006). Of the two statistically significant variables, AUD (beta = 0.397) is making the strongest unique contribution to explaining the dependent variable, when the variance explained by all other variables in the model is controlled for (compared to SIZE with a beta of 0.211). The results provide evidence to support hypothesis 1, that companies audited by higher quality auditors disclose more information Quality The multiple regression model for DISCQ is also highly significant (p 0.001). The coefficient for AUD and SIZE are statistically significant (p and p 0.008). As with the extent of disclosure, AUD (beta = 0.385) is making the strongest unique contribution to explaining the dependent variable, when the variance explained by all other variables in the model is controlled for (compared to SIZE with a beta of 0.204). The results provide evidence to support hypothesis 2, that companies audited by higher quality auditors have disclosures of a higher quality. 5. Conclusions 7 Both regression models reported were tested for heteroscedasticity and multicolliniarity. Neither was found to be a significant factor affecting the reliability of the results. Tolerance Inflation Factors (VIF) are also reported in Table 6 with none being over 5 which Hair Jr. et al. (2003) suggest would be the maximum VIF value before multicollinearity becomes a factor. 16

17 The objective of this study was to examine the relationships between the use of a higher quality (Big 4) audit firm and the extent and quality of annual report disclosure made in compliance with AASB The results support the hypothesis that companies using a higher quality auditor will have more AIFRS adoption information than clients of lower quality auditors. The results are consistent with Clarkson et al. (2003) who examine the extent of Year 2000 disclosures. The present study also explores the quality of disclosure and finds that, consistent with the extent of disclosure, auditor quality is making the strongest contribution to the quality; that is, the auditor effect is consistent across both extent and quality. There is therefore, in relation to AIFRS disclosure, a relationship between the amount of disclosure a company makes and the quality of that disclosure: the more that was disclosed, the more the reader was assisted to understand the impact of adoption and the firm s level of preparedness. While there are many studies that measure the extent of disclosure this is one of the few studies that attempts to investigate disclosure quality in this way. The study is particularly important given the significance of the adoption of AIFRS and the uncertainty surrounding adoption. Size tends to dominate other variables in most disclosure studies investigating the relationship between levels of disclosure and corporate characteristics. The present study, however, conducted in an Australian setting and using the introduction of AIFRS as an opportunity for investigating disclosure, finds that in this case the size of a company s auditor is making the strongest contribution to the extent of disclosure. Audit quality is difficult to observe and investors often rely on auditor reputation to infer audit quality (Barton, 2005). As Chaney and Philipich (2002) observe, impaired auditor reputation has negative 17

18 consequences for the audit firm in terms of retaining and attracting clients. Thus given the uncertainty surrounding the adoption of AIFRS, auditors who are concerned with their reputation capital, have strongly encouraged their clients to provide comprehensive disclosure. One limitation of the study is the subjectivity of the creation of a disclosure index requiring the awarding of a quality score to each sentence as detailed in Section 3.2. The coding rules and the coding of a sample of companies were reviewed by two independent accounting researchers but given the limited investigation of quality in any real sense in prior literature, this part of the study is exploratory and therefore caution should be exercised in interpreting the results. A second possible limitation to the study is that companies may have disclosed impacts of the adoption of AIRFS outside of the annual report; for example, on their websites. It is possible that more detailed and higher quality disclosures may be provided in such locations. However, as Clarkson et al. (2003) argue, auditors are associated with the annual report disclosures and therefore are still likely to encourage comprehensive disclosure in the annual report. 18

19 REFERENCES Ahmed, K., and Nicholls, D., 1994, "The Impact of Non-Financial Company Characteristics on Mandatory Disclosure Compliance in Developing Countries: The Case of Bangladesh", The International Journal of Accounting, 29, Alsaeed, K., 2005, "The Association between Firm-Specific Characteristics and Disclosure: The Case of Saudi Arabia", Journal of American Academy of Business, Cambridge, vol. 7, no. 1, pp Asbaugh, H., and Warfield, T. D., 2003, Audits as a Corporate Governance Mechanism: Evidence from the German Market, Journal of International Accounting Research, 2, Australian Accounting Standards Board (AASB), 2004, AASB 1047, Disclosing the Impacts of Adopting Australian Equivalents to International Financial Reporting Standards, AASB, Melbourne. Australian Stock Exchange (ASX), 2005, What is GICS? [Online], available: [accessed 23 August 2005] Barton, J., 2005, Who Cares about Auditor Reputation?, Contemporary Accounting Research, 22, 3, Beattie, V., McInnes, B., and Fearnley, S., 2004, "A Methodology for Analysing and Evaluating Narratives in Annual Reports: A Comprehensive Descriptive Profile and Metrics for Disclosure Quality Attributes", Accounting Forum, 28, Becker, C.L., DeFond, M.L., Jiambalvo, J., Subramanyam, K.R., 1998, The Effect of Audit Quality on Earnings Management, Contemporary Accounting Research, 15, 1, 2-24 Bushman, R. M., Piotroski, J. D., and Smith, A. J., 2004, What Determines Corporate Transparency?, Journal of Accounting Research, 42, Chaney, P.K., and Philipich, K.L., 2002, Shredded Reputation: The cost of Audit Failure, Journal of Accounting Research, 40, 2, Chow, C.W., and Wong-Boren, A., 1987, "Voluntary Financial Disclosure by Mexican Corporations", The Accounting Review, 62, Clarkson, P.M., Ferguson, C. and Hall, J., 2003, Auditor Conservatism and Voluntary Disclosure: Evidence from the Year 2000 Systems Issue, Accounting and Finance, 43, Cohen, J.W., 1988, Statistical Power Analysis for the Behavioural Sciences, 2 ed., Lawrence Erlbaum Associates, Hillsdale, NJ. Cooke, T.E., 1989, "Disclosure in the Corporate Annual Reports of Swedish Companies", Accounting and Business Research, 19,

20 Craswell, A.T. and Taylor, S.L., 1992, Discretionary Disclosure of Reserves by Oil and Gas Companies: An Economic Analysis, Journal of Business Finance and Accounting, 19, 2, DeAngelo, L.E., 1981, Auditor Size and Audit Quality, Journal of Accounting and Economics, 3, 3, Dodd, C., and Sheehan, V., 2004, "On Your Mark, Get Set." Charter, vol. 75, no. 1, pp Dunn, K.A., and Mayhew, B.W., 2004, Audit Firm Industry Specialization and Client Disclosure Quality, Review of Accounting Studies, 9, 1, Firth, M., 1979, "The Impact of Size, Stock Market Listing and Auditors on Voluntary Disclosure in Corporate Annual Reports", Accounting and Business Research, 9, Firth, M. and Liau-Tan, K.L., 1998, Auditor Quality, Signaling, and the Valuation of Initial Public Offerings, Journal of Business Finance and Accounting, 25, Francis, J.R., 2004, What do we know about Audit Quality?, The British Accounting Review, 36, Francis, J.R. and Krishnan, J., 1999, Accounting Accruals and Auditor Reporting Conservatism, Contemporary Accounting Research, 16, 1, Goodwin, J., and Ahmed, K., 2006, The impact of international financial reporting standards: does size matter?, Managerial Auditing Journal, 21, Gray, R., Kouhy, R., and Lavers, S., 1995, "Methodological Themes: Constructing a Research Database of Social and Environmental Reporting by UK Companies", Accounting, Auditing & Accountability Journal, 8, Hair Jr., J.F., Babin, B., Money, A.H., and Samouel, P., 2003, Essentials of Business Research Methods, Wiley, USA. Ham, P., 2002, "Peace, Love and Accounting", CA Charter, vol. 73, no. 7, pp Haswell, S., and McKinnon, J., 2002, "IASB Standards for Australia by 2005: Catapult or Trojan Horse?" Australian Accounting Review, vol. 13, no. 1, pp Hossain, M., and Adams, M., 1995, "Voluntary Financial Disclosure by Australian Listed Companies", Australian Accounting Review, 5, Inchausti, B.G., 1997, "The Influence of Company Characterisitics and Accounting Regulation on Information Disclosed by Spanish Firms", The European Accounting Review, 6,

21 Jensen, M.C., and Meckling, W.H., 1976, "Theory of the Firm: Managerial Behaviour, Agency Costs and Ownership Structure", Journal of Financial Economics, Jones, S., and Higgins, A.D., 2006, Australia s Switch to International Financial Reporting Standards: A Perspective from Account Preparers, Accounting and Finance, 46, Lang, M., and Lundholm, R., 1993, "Cross-Sectional Determinants of Analyst Ratings of Corporate Disclosures", Journal of Accounting Research, vol. 31, no. 2, pp Lee, P.J., Taylor, S.J., Taylor, S.L., 2006, Auditor Conservatism and Audit Quality: Evidence from IPO Earnings Forecasts, International Journal of Auditing, 10, Maiden, M., 2002, Auditing the Auditors, The Age, 20 April 2002 [Online] available: [accessed 01 November 2005]. Moullakis, J., 2004, CBA sees volatility in new rules, The Australian Financial Review, 15 September, p. 56. Naser, K., Al-Khatib, K., and Karbhari, Y., 2002, "Empirical Evidence on the Depth of Corporate Information Disclosure in Developing Countries: The Case of Jordan", International Journal of Commerce and Management, 12, Ormrod, P., and Taylor, P., 2004, The Impact of the Change to International Accounting Standards on Debt Covenants: A UK Perspective, Accounting in Europe, 1, Owusu-Ansah, S., 1998, "The Impact of Corporate Attributes on the Extent of Mandatory Disclosure and Reporting by Listed Companies in Zimbabwe", The International Journal of Accounting, 33, Palmer, P.D., 2008, Disclosure of the Impacts of Adopting Australian Equivalents of IFRS, Accounting and Finance (forthcoming). Pound, G., 2004, "Smooth the Way", Charter, vol. 75, no. 4, pp PricewaterhouseCoopers (PWC), 2004, International Financial Reporting Standards. Ready to Take the Plunge? [Online], available: [accessed 8 June 2005]. Raffournier, B., 1995, "The Determinants of Voluntary Financial Disclosure by Swiss Listed Companies", The European Accounting Review, 4, Singhvi, S.S., and Desai, H.B., 1971, "An Empirical Analysis of the Quality of Corporate Financial Disclosure", The Accounting Review, 46,

22 Tabachnick, B., and Fidell, L., 2001, Using Multivariate Statistics, 4 ed., Allyn and Bacon, Boston. Wallace, R.S.O., Naser, K., and Mora, A., 1994, "The Relationship between the Comprehensiveness of Corporate Annual Reports and Firm Characteristics in Spain", Accounting and Business Research, 25,

23 Table 1: Sample by GCIS Industry Sector Sector Code Industry Sector Observations 10 Energy 9 15 Materials Industrials Consumer Discretionary Consumer Staples 6 35 Health Care Financials Information Technology Telecommunication Services 5 55 Utilities 2 Total Observations

24 Table 2: Coding Rules used as the basis for the qualitative score applied to each sentence of disclosure Rating Criteria Examples Rating 0 applies to non-specific, non-informative information 0 Indicates the sentence contains no real information about the adoption of AIFRS, and is not specific to the company The AASB is adopting IFRS for application to reporting periods beginning on or after 1/1/05 Rating 1 applies to general information on implementation of AIFRS only not specific standards 1 Indicates general information about the The adoption of A-IFRS will be first adoption of AIFRS in relation to the reflected in the consolidated entity's company, or indicates that the company has undertaken some action. Relates to financial statements for the half year ending general information only, not to the discussion of a specific standard. Ratings 2-5 apply in relation to specific standards 2 Applies where a sentence identifies issues specifically relevant to the company; for example, detailing the existing accounting policy or practice of the company, or detailing the accounting policy or practice under the new standard. However, no indication of the impact of the change in accounting policy or practice is mentioned in a sentence rated with a score of 2 3 Indicates disclosure of some impact on the company without necessarily specifying what that impact will be. This indicates that there will be some change in policy or practice that will impact on revenues, expenses, assets, liabilities and/or equity, but the extent of the impact has not yet been determined. Additionally sentences that stated there may be some impact were included in this rating. Under the Australian equivalent to IFRS 3 Business Combinations goodwill will no longer be able to be amortised but instead will be subject to annual impairment testing Certain assets and liabilities may not qualify for recognition under A-IFRS, and will need to be derecognised whereas other asset and liabilities not previously recognised may need to be recognised under A-IFRS For 4 or 5 the sentence must explicitly state that there will or will not be an impact 4 Applies where a sentence gives details The recognition of the share-based about the impact of adopting AIFRS and gives an indication of the nature and compensation expense will decrease the consolidated entity's profit in future direction of the impact. 5 Has the same criteria as 4, with the additional requirement that the dollar value of the expected change is provided. Sentences with scores of 4 or 5 then, give an indication of the direction of the change. Source: Adapted from Palmer (2008, forthcoming) The maximum deferred tax liability which may be required to be recorded in relation to this is approximately $20,445,

25 Table 3: Panel A: Descriptive statistics for the dependent variables extent and quality of disclosure and independent variables size, leverage, profitability, industry and auditor Part A: Dependent Variables Part B: Non-categorical Independent Variables Part C: Categorical Independent Variables DISCE DISCQ SIZE PROF LEV AUD Frequency Percent Valid Observations Deloitte Minimum PWC Maximum KPMG Mean EY Median Other Std Deviation Total Panel B: Descriptive statistics for companies engaging a Big 4 auditor Mean Median Big 4 Other Big 4 Other DISCE DISCQ SIZE PROF LEV DISCE = The number of sentences disclosed by a company. DISCQ = The quality score of the disclosures based on the coding rules outlined in Table 2. SIZE = Obtained from the annual report and used as a measure of the size of the company. PROF = Profit divided by assets. Obtained from the annual report and used as a measure of profitability. LEV = Total liabilities divided by total assets. Obtained from the annual report and used as a measure of leverage. AUD = a dummy variable (1 when a Big 4 auditor is used (Deloitte Touche Tohmatsu, Ernst & Young, PricewaterhouseCoopers, KPMG) ; 0 otherwise). 25

26 Table 4: Spearman s Rank Order correlation coefficients for the variables in the model. DISCE DISCQ SIZE AUD PROF LEV DISCE 1.00 DISCQ 1.00 SIZE ** ** 1.00 AUD ** ** ** 1.00 PROF * * ** ** 1.00 LEV ** ** ** * ** 1.00 * Significant at the level (1-tailed) ** Significant at the level (1-tailed) DISCE = Extent - The number of sentences disclosed by a company. DISCQ = Quality - The quality score of the disclosures based on the coding rules outlined in Table 2. SIZE = Assets - Obtained from the annual report and used as a measure of the size of the company. PROF = Return on Assets - Profit divided by assets. Obtained from the annual report and used as a measure of profitability. LEV = Debt to Assets - Total liabilities divided by total assets. Obtained from the annual report and used as a measure of leverage. AUD = a dummy variable (1 when a Big 4 auditor is used (Deloitte Touche Tohmatsu, Ernst & Young, PricewaterhouseCoopers, KPMG) ; 0 otherwise). 26

27 Table 5: Mann-Whitney Test Results Dependent Variable = DISCE n 1 n 2 U-statistic z-statistic Two-tailed Probability Big 4/Other Dependent Variable = DISCQ Big4/Other DISCE = Extent - The number of sentences disclosed by a company. DISCQ = Quality - The quality score of the disclosures based on the coding rules outlined in Table 2. 27

28 Table 6 Kruskal-Wallis Test Results Dependent Variable Auditor n Mean Rank DISCE Deloitte PWC KPMG EY Other Total 150 Kruskal-Wallis Test Statistic Probability Dependent Variable Auditor N Mean Rank DISCQ Deloitte PWC KPMG EY Other Total 150 Kruskal-Wallis Test Statistic Probability DISCE = Extent - The number of sentences disclosed by a company. DISCQ = Quality - The quality score of the disclosures based on the coding rules outlined in Table 2. 28

29 Table 7: Results of regression models of AIFRS adoption disclosure extent and quality for a sample of 150 Australian companies in 2005 Explanatory Variable Coefficient t-statistic Significance Variance Inflation Factor Part A: Dependent Variable = DISCE DISCE = α + β 1 AUD + β 2 SIZE + β 3 PROF +β 4 LEV + ε Constant AUD SIZE PROF LEV R 2 = 0.275; F = ; p = 0.000; n = 150 Part B: Dependent Variable = DISCQ DISCQ = α + β 1 AUD + β 2 SIZE + β 3 PROF +β 4 LEV + ε Constant AUD SIZE PROF LEV R 2 = 0.261; F = ; p = n = 150 DISCE = The number of sentences disclosed by a company. DISCQ = The quality score of the disclosures based on the coding rules outlined in Table 2. SIZE = Obtained from the annual report and used as a measure of the size of the company. PROF = Profit divided by assets. Obtained from the annual report and used as a measure of profitability. LEV = Total liabilities divided by total assets. Obtained from the annual report and used as a measure of leverage. AUD = a dummy variable (1 when a Big 4 auditor is used (Deloitte Touche Tohmatsu, Ernst & Young, PricewaterhouseCoopers, KPMG) ; 0 otherwise). 29