The Market for Professional Services in Indonesia - Wiley Online Library

International Journal of Auditing Int. J. Audit. 8: 153–164 (2004)

The Market for Professional Services in Indonesia Ilias G. Basioudis1 and Fifi Fifi2 1 2

University of Aston Giant Hypermarket, Singapore

This paper reports the results of a study which investigates the market for professional services in Indonesia, a country which has not been investigated in the by audit fee literature prior. A well-developed research model used in the prior literature has also been applied in this study, and the empirical findings suggest broad similarities in the pricing of professional services in Indonesia and other countries previously studied. In addition to extending the results of prior research to a country not previously studied, this paper examines whether the large auditors fee premium documented in other countries exists in Indonesia, especially after the major Asian financial crisis of 1997/98, since then almost all companies in this geographical area exercise tight budget controls. The results suggest that no audit fee premium is accrued to Indonesian Big 5 auditors, in contrast to the large audit firm fee premium documented in many other countries. Key words: Audit fees, Big 5 fee premium, Indonesia, market for professional services.

SUMMARY This paper examines the market for professional (audit) services in Indonesia. Data were collected from annual reports of 67 randomly selected companies listed in the Jakarta Stock Exchange for the 2000 financial year. This study uses data after the major Asian financial crisis in the late 1990s. Various proxies for client size, client complexity, client risk to fail, and a variable measuring the effect of Big 5 audit firms were examined as potential determinants of professional fees in Indonesia. A regression model similar to the one developed in the prior literature was developed. The model explains 60% of the

Correspondence to: Aston Business School, University of Aston, Birmingham B4 7ET, UK. Email: [email protected]

variability of professional fees. The study strongly confirms that most of the prior research findings are also applicable to the Indonesian market. The study also indicates an important difference between the professional fee market in Indonesia and other countries previously studied, that is there is no generalised fee premium accruing to Indonesian Big 5 audit firms.

INTRODUCTION This paper reports the results of a study which looks at the pricing of professional (audit) services in Indonesia, a country which has never been investigated in the prior audit fee literature. The current study contributes to a greater understanding of the market for audit services in that it examines the underpinning variables which explain the variability of professional fees in

ISSN 1090–6738 © Blackwell Publishing Ltd 2004. Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

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Indonesia. This study helps us understand the pricing of professional services in Indonesia, especially after the major Asian financial crisis in the late 1990s, where almost all companies in this geographical area have exercised tight budget controls since then. The similarity of audit fee determinants between Indonesia and other countries is investigated, and the extent to which the large auditors fee premium documented in other countries exists in Indonesia is also examined. This will extend our knowledge of accounting in Indonesia and allow assessment of the similarities and differences in the market for audit services in Indonesia and other countries. The remainder of the paper is divided into four further sections. The next section highlights the position of the accounting profession and the socio-economic environment in Indonesia. The third section presents a brief review of the previous research on the market for audit services. The fourth section describes the data and research methods. The empirical results and conclusions are set out in the remaining two sections respectively.

THE ACCOUNTING PROFESSION AND SOCIO-ECONOMIC ENVIRONMENT IN INDONESIA Indonesia was among the Asian countries which were hit hard by the Asian financial crisis in 1997/98. Before the crisis, Indonesia was classified as a vast developing country, a nation with the fourth largest population in the world, and rich with natural resources such as LNG, crude oil, and palm oil (Patrick, 2001). However, due to effects of the crisis, the Indonesian economy has suffered badly. Before the crisis in 1996, the inflation rate was 6.64%. However, it increased to 11.05% and 77.63% in 1997 and 1998 respectively (Corsetti et al., 1998). In addition, Indonesian economic growth was 8.2% in 1995 and 7.8% in 1996. It then dropped to 4.7% and -13% in 1997 and 1998 respectively (www.bi.go.id–Economic & International Monetary Indicator). The Indonesian currency, the Rupiah, depreciated by 567% in the period July 1997 to February 1998 (Yamazawa, 1998). Indonesia was a Dutch colony for centuries and was occupied by Japan during the Second World War. In 1945, Indonesia declared its independence and the Indonesian Institute of Accountants © Blackwell Publishing Ltd 2004

I. G. Basioudis and F. Fifi

was established in 1957. In the same year, all Indonesian companies were nationalised and as a result, all Dutch accounting firms closed their offices in Indonesia (Bachtiar, 2001). However, during the 1970s, most of the local accounting practices formed alliances with international accounting firms. Today, there are 156 accounting firms1 in Indonesia. Five Indonesian auditors are affiliated with the Big 5 audit firms and the rest are local or regional firms. These are: 1. Prasetio, Utomo & Co. affiliated with Andersen, 2. Hadi Sutanto & Rekan affiliated with PricewaterhouseCoopers, 3. Hanadi, Sarwoko & Sandjaja affiliated with Ernst & Young, 4. Sidharta & Sidharta affiliated with KPMG, 5. Hans Tuanakotta & Mustofa affiliated with Deloitte Touche & Tohmatsu. Indonesia has been greatly influenced by the developed Western countries. Foreign investors and international aid agencies, such as the World Bank and the IMF, have called on the Indonesian government to introduce tougher disclosure rules and harmonise accounting practice over the last two to three decades (Rosser, 1999). As a result, a number of economic reforms, accounting standards and corporate governance regulations have been introduced in Indonesia. These sometimes go even further than the Western regulations; for example, in September 2002 the Ministry of Finance in co-operation with the Indonesian Institute of Accountants issued a regulation concerned with the rotation of auditors (Decree No 423/KMK.06/2002). It specifies that accounting firms may not audit an organisation for more than five consecutive years and audit partners in that firm cannot sign the accounts of the client for more than three consecutive years. These rotation requirements in Indonesia are more onerous than the rotation requirements in most other jurisdictions throughout the world and exceed what is considered to be global best practice. The recent Sarbannes-Oxley Act in the US, for example, requires rotation of audit partners after five years but stops short of requiring rotations of audit firms. The Indonesian Minister of Industry and Trade (MIT) requires all companies to register their annual financial reports. The MIT requires all financial statements to be prepared in accordance with the Indonesian GAAP which is based on international and US accounting standards (Diga & Int. J. Audit. 8: 153–164 (2004)

The Market for Professional Services in Indonesia

Yunus, 1996). Similarly, the financial statements are audited in accordance with auditing standards established by the Indonesian Institute of Accountants, which are substantially similar to the generally accepted auditing standards in the United States. The predominant fiscal year-end in Indonesia is 31st December.

PREVIOUS RESEARCH It is rarely the case that a whole research literature can be traced to a single origin, but that distinction belongs to Simunic’s (1980) paper which was the first study to consider auditing from an industrial economics perspective. Since then, audit pricing research has extended Simunic’s original work both to consider different sizes of firm (for example, Francis & Stokes, 1986; Francis & Simon, 1987), and to different national settings, apart from the US market (Simunic, 1984; Wallace, 1984; Simon, 1985; Palmrose, 1984, 1986; Simon & Francis, 1988; Turpen, 1990; Ettredge & Greenberg, 1990; Gist, 1992; Pearson & Trompeter, 1994; Simon, 1997). Other countries audit markets examined are the Australian market (Francis, 1984; Francis & Stokes, 1986; Craswell et al., 1995), the Canadian market (Chung & Lindsay, 1988), the New Zealand market (Firth, 1985; Johnson et al., 1995), the Japanese market (Taylor, 1997), the Singaporean market (Low et al., 1990; Simon et al., 1992), the Hong Kong market (Simon et al., 1992; Gul, 1999; DeFond et al., 2000), the Indian market (Simon et al., 1986), the Pakistani market (Simon & Taylor, 1997), the Bangladeshi market (Karim & Moizer, 1996), the Bahraini market (Joshi & Al-Bastaki, 2000), the Irish market (Simon & Taylor, 2002), the Dutch market (Langendijk, 1997), and the UK audit market (Taylor & Baker, 1981; Taffler & Ramalinggam, 1982; Ramzy, 1988; Chan et al., 1993; Pong & Whittington, 1994; Ezzamel et al., 1996; Seetharaman et al., 2000; Ezzamel et al., 2002; Basioudis, 2002). One study (Haskins & Williams, 1988) has made a comparison between audit fees determinants across countries (i.e. Australia, New Zealand, Ireland, the United Kingdom and the United States) and across Big-Eight auditing firms, and more recently, three studies (Taylor & Simon, 1999; Fargher et al., 2001; Chung & Narasimhan, 2002) have used aggregating data from different countries to examine the ‘macro’ determinants of audit fees. Thus, similar cross-sectional methodologies, testing models and hypotheses have been used in © Blackwell Publishing Ltd 2004

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a number of alternative audit markets. In most of the above studies, cross-sectional multiple regression models are developed relating external fees to client and auditor firm characteristics. Auditor-related variables have been considered as important test variables, and include among others a variable representing either the name of the individual audit firm2 or the distinct group to which the firm belongs (usually Big 8 or 6 v. nonBig 8 or 6); client-related variables have often been merely regarded as control variables for audit effort, and include a client size variable (total assets or sales), client complexity variables (balance sheet ratios, number of subsidiaries, etc.), client risk variables (liquidity ratio, etc.), and other variables, for example, capturing audit production costs, such as provision of non-audit services, audit timing, geographical location, etc. In most of the above studies, therefore, similar dependent and independent variables are used and almost similar findings have been shown. However, the main focus of most of these studies was not to identify an exhaustive list of significant audit fee determinants as such, but rather to investigate whether there exists an audit firm size effect on audit fees, i.e., whether there are identifiable differences between fees charged by the Big 8 (or Big 6) firms and those charged by nonBig 8 (or Big 6), and hence, to draw conclusions with respect to price competition, product differentiation and economies of scale in the market for audit services.

Big 8 (or Big 6) audit fee premium There does not exist consensus as to the impact of different classes of auditor on differential audit fee pricing and as to whether the impact differs between the small and the large auditee market segment. Simunic (1980) found that the US audit market was generally competitive suggesting that price prevailed throughout the US market for the audits of publicly held companies, irrespective of the share of the market segment served by the large accounting firms. As in Simunic’s study, Firth (1985) also reported a non-significant auditor size effect in the New Zealand market for audit services (without partitioning into large and small auditees). However, other studies which tested for the existence of a Big 8 audit fee premium found significant results. In a study of 136 Australian companies, Francis (1984) found evidence that the Int. J. Audit. 8: 153–164 (2004)

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Big 8 firms charged 16.5% higher audit fees than non-Big 8 firms both in the large and small auditees market in Australia, consistent with a competitive audit market structure with product differentiation. Also, Chan et al. (1993) reported a significant Big 8 audit fee premium of 36.7% charged in both the small and the large company segments of the market for a sample of 280 UK auditees. Francis & Stokes (1986) analysis indicated that the Australian audit market is segmented by company size. In the large company segment of the market, no significant differences in audit fees between large and small audit firms were observed, suggesting that non-Big 8 diseconomies offset any Big 8 fee premiums. This result is consistent with Simunic (1980), but is in contrast with Johnson et al. (1995). For the small companies segment though, Francis & Stokes reported that Big 8 firms charged significantly (18.8%) higher audit fees than non-Big 8. This result is similar to Brinn et al. (1994) who found a significant Big 8 audit fee premium (28%) for independent unquoted companies in the UK (they compared their results with the relatively small quoted companies). Subsequent studies of the US audit market by Palmrose (1986) and Francis and Simon (1987) have also reported that the Big 8 firms were associated with higher audit fees with respect to smaller companies. In addition, Francis and Simon found a significant Big 8 audit fee premium existed with respect to both second tier national firms (29.7%) and local or regional firms (27.1%). Similar findings with regards to the second tier and local/regional firms are found in Basioudis (2002) study of the UK market. The above results are supportive for a competitive audit market with product differentiation to the Big 8 firms and diseconomies of scale to the non-Big 8 in the audits of large companies. However, another study has failed to provide evidence of Big 8 audit fee premium in medium-size UK auditees (Che-Ahmad & Houghton, 1996). In addition, more recent audit fee studies for non-US markets have also found that Big 6 audit firms earn an audit fee premium, for example Gul (1999) have shown a Big 6 firms audit fee premium between 29–39% in Hong Kong, DeFond et al. (2000) reported a 63% premium as well as an industry specialist premium in the same market, Craswell et al. (1995, 1996) found evidence that the Big 6 firms and industry specialists charge around 30% higher fees than non-Big 6 firms in Australia, © Blackwell Publishing Ltd 2004


Seetharaman et al. (2000) have shown a Big 6 firms audit fee premium ranged between 9.5% and 23.3% in the UK market, and a Big 6 audit fee premium of 18% in Bangladesh was found in Karim & Moizer (1996). No general audit fee premium accrued to Big 6 firms as a group but an Arthur Andersen audit fee premium in Norway was reported in Firth (1997); similarly, Big 6 firms received no audit fee premium but KPMG was found to earn a premium in the Netherlands (Langendijk, 1997). Finally, Simon & Taylor (2002) reported a 23.3% audit fee premium for Big 6 firms in Ireland which, after they performed further tests, it was found to apply only to Price Waterhouse and Coopers & Lybrand audit firms (their study took place before the merger of these two firms). In contrast, Basioudis & Ioannidou (2003) have found no evidence of a Big 5 fee premium in the Cypriot audit market. Taken together, it seems that monopoly pricing does not prevail in the audit markets, as no researchers’ findings appear to have advanced this suggestion. In other words, the empirical evidence indicates that the market for audit services is competitive, in the sense that it reveals that the audit fees charged by the Big 8 (or 6) accounting firms in the large auditee market segment have never been significantly and strictly higher, ceteris paribus, than the audit fees charged by the Big 8 accounting firms in the small auditee market segment. However, although there is a competitive audit market structure, there exists no consensus about the existence of product differentiation and scale (dis)economies. Most results point in the direction of product differentiation. Note that this lack of consensus does not necessarily derive from country-specific elements. Inconsistent evidence with regard to differential audit fee pricing by different classes of auditors was found within countries. For example, Simunic (1980) and Palmrose (1986) both examined US samples and reported such contradictory evidence; the same holds for Francis (1984) and Francis & Stokes (1986) with respect to Australian samples. One explanation, however, may be the average auditee size in the respective samples of small and large clients and/or different periods of data. The evidence reviewed in the preceding paragraphs enables us to explain some of the magnitude of the Big 8 (or 6) firms’ fee premiums ranged between 4% and 56% for different countries and periods. The existing literature suggests that there is a systematic difference between the fees Int. J. Audit. 8: 153–164 (2004)


charged by the Big 8 (or 6) as opposed to non-Big 8 (or 6) audit firms, especially in the small client segment. Researchers have classified auditors into two distinct groups, that is Big 6 (or Big 8, depending on when the studies were undertaken) and non-Big 6 (or Big 8) firms, and tested for the effect of differences in supplier concentration upon the audit prices.

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Generally, the audit fee results show that in the majority of the studies a general audit fee premium for Big 6 auditors as a group exists in the market for audit services. In addition, some other differences have been detected within the Big 6 firm group. For example, looking at Table 1, Price Waterhouse seemed to charge higher audit fees in the 1980s in the USA, Canada and New Zealand

Table 1: Summary of premiums or discounts as identified in various audit fee studies Study

Country

Big 6 (or 8) fee premium

Francis (1984) Francis & Stokes (1986) Craswell et al. (1995) Craswell et al. (1996) Craswell & Francis (1999) Karim & Moizer (1996) Chung & Lindsay (1988) Simon et al. (1992) Gul (1999) DeFond et al. (2000) Simon et al. (1986) Simon & Taylor (2002)

Australia Australia Australia Australia Australia Bangladesh Canada Hong Kong Hong Kong Hong Kong India Ireland

16.50% 18.80% 31% 30%

23%

Simon et al. (1992) Firth (1985) Firth (1997) Simon et al. (1992) Simon (1995)

Malaysia New Zealand Norway Singapore South Africa

None 4% None 26% None

Langendijk (1997) Chan et al. (1993) Brinn et al. (1994) Che-Ahmad & Houghton (1996) Ezzamel et al. (1996) Ezzamel et al. (2002) Davis et al. (1999) Seetharaman et al. (2000) Basioudis (2002) Palmrose (1986a) Francis & Simon (1987) Simon & Francis (1988) Turpen (1990) Balachandran & Simon (1993)

Netherlands UK UK UK UK UK UK UK UK USA USA USA USA USA

None 36.70% 28% None 23.40–32.7% 24.50–46.85% 5–18.9% 9.50–23.30% 10.20–15.40% 16.60% 24.6–29.6% 16.20% 55.70% None

Gist (1994) Simon (1997)

USA USA

5% 10.50–31%

18% None 31% 29–39% 63%

Other premiums (P) or discounts (D) None None Industry Specialist* (D) Industry Specialist (D) None None Price Waterhouse (P) None None Industry Specialist (D) None Price Waterhouse (P) Coopers & Lybrand (P) None Price Waterhouse (P) Arthur Andersen (P) None Deloitte Touche (P) Ernst & Young (P) KPMG (P) London office** (P) London office (P) None None None None not tested not tested None None None None Price Waterhouse (P) Deloitte Haskins & Sells (P) Peat Marwick (D) None Arthur Andersen (P), Arthur Young (P), Deloitte Haskins & Sells (P), Ernst & Whinney (P); Price Waterhouse (P)

*‘Industry specialist’ means that an auditor possesses the highest market share in a specific industry. **‘London office’ refers to a premium (P) or discount (D) earned by the those firms with London-based offices. © Blackwell Publishing Ltd 2004

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(Firth, 1985; Chung & Lindsay, 1988; Balachandran & Simon, 1993). Deloitte & Touche had fee premiums in South Africa and USA (Balachandran & Simon, 1993; Simon, 1995), Arthur Andersen in Norway (Firth, 1997), and so on. It is apparent from Table 1 that there is a lack of published research work into audit fees in China, South and Central America, other European Union countries such as France, Germany, Spain, Greece, etc., as well as in the newly developing Eastern European countries such as Poland, Romania, Czech Republic, Hungary, etc.

DATA AND RESEARCH METHODS Data were collected for the calendar year 2000 from the annual reports of a random sample of 283 Indonesian companies listed in the Jakarta Stock Exchange. One visit to the Jakarta Stock Exchange was made and the annual reports were collected by hand. The collection was hindered by whether the reports were available on that day as well as whether companies had filed their reports by that day. Also, the 67 companies final sample excludes 50 financial service companies because the audit fee model is not developed to reflect their activities. The final sample also excludes companies where their professional fees incorporate fees for other services. As a result, therefore, audit fees in this study are proxied by the professional service fees and they will be used to investigate the pricing of professional services in Indonesia. In addition to annual reports, Datastream financial database was also consulted. In this study, consistent with prior audit fee studies, a regression model of the audit fee function is utilised to determine the pricing of professional services in Indonesia. Typically, audit fee has been placed as a dependent variable to be explained by various characteristics of the client and auditor, such as client size and complexity, client risk to fail, and auditor size, tenure, specialisation,3 and so on. Similar to other studies, we proxy client size with the sales (SALES). Another measurable factor that is commonly tested and appears to be generally a significant explanatory variable in determining audit fees is client complexity. Increased client complexity and diversity may increase the requisite audit labour, knowledge and effort and, hence, the level of the audit fees. Complexity and diversity may also increase litigation costs as the inherent and business risks © Blackwell Publishing Ltd 2004


of the company increase. Client complexity variables control for such difficult audit areas as subsidiary companies, inventory, debtors and accounts receivable. The explanatory variables used in this study (as well as previous studies) are related to the number of subsidiaries (SUBS), and the total year-end debtors to total assets ratio (DEBTR). The larger the probability of business failure by the client, the greater the perceived risk of audit failure and, therefore, a possible increased audit effort and direct cost. The proportion of the company’s total assets represented by earnings before interest and taxes (EARN) and the type of audit opinion (AUDQN) variables are constructs of factors that measure the amount of auditee financial distress. Also, LTLBTA variable (longterm liabilities to total assets ratio) measures the level of gearing of the client company. It is a balance sheet measure of financial risk, and the higher the levels of gearing, the higher the audit fees charged due to the greater riskiness of such companies. Another client risk measure employed by this study is the current ratio (CR) which proxies for the level of the auditee liquidity. Acceptable level of this measure will determine the level of audit fees charged by the auditor. An apparently low CR may indicate an unhealthy company and, hence, the risk of audit failure is greater. Finally, the incidence of a loss in any of the past three financial periods (which in turn signals evidence of auditee financial distress and riskier operations) increases the risk of audit failure and also increases the posterior probability that the auditor will incur future losses because the auditee is bankrupt. Therefore, a LOSS variable was included in our audit fee model. One of the objectives of this study is to examine whether the large auditors fee premium documented in other countries exists in Indonesia. Therefore, we assume as other studies that Big 5 audit firms deliver a different level of audit quality or use different procedures than the non-Big 5 firms and, therefore, the fees charged by each group of firms may differ too. The audit fee models, that have utilised the variables above and successfully been used in developed as well as developing countries, have consistently been found to explain a considerable proportion of audit fees in prior literature. The regression model used in this study is of the following form: Int. J. Audit. 8: 153–164 (2004)


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Table 2: Descriptive Statistics (in Indonesian Rupiah)

SALES Ln(SALES) SUBS SUBS0.5 DEBTR Ln(DEBTR) EARN OPIN* LTLBTA CR Ln(CR) LOSS* BIG5* FEE LnFEE

N

Minimum Statistic

Maximum Statistic

Mean Statistic

Std. Deviation Statistic

Skewness Stat.

Kurtosis Stat.

67 67 67 67 67 67 67 67 67 67 67 67 67 67 67

4,394 8.388 0 0 6.19E-09 -18.900 -0.118

15,123,296 16.532 48 6.928 0.490 -0.714 0.385

14.399 0.292 6.252 1.157 7.943 -0.369 0.791

0.953 48.467 3.881

0.756 7.759 -0.262

-0.154 62.232 1.811

2.5 0.916

50,110 10.822

2,815,158 1.585 10.266 1.615 0.084 2.446 0.103 0.265 0.237 5.870 1.236 0.420 0.359 9,679 1.718

3.789 0.057 2.448 1.165 2.282 0.178 0.908

0.000 0.020 -3.922

1,276,323 12.820 6.940 2.091 0.081 -3.335 0.075 0.925 0.251 1.966 -0.182 0.776 0.851 5,613 7.462

2.858 -0.626

8.745 2.004

*For the dummy variables, the mean statistic value (multiplied by 100) shows the percentage of observations when the variable takes on a value of one.

Ln(FEE) = b1 + b 2 Ln(SALES) + b 3 SQRT(SUBS) + b 4 Ln(DEBTR ) + b 5EARN + b6 OPIN + b7 LTLBTA + b8 Ln(CR ) + b 9LOSS + b10 BIG5 + error where: Dependent Variable LnFEE = natural log of professional (audit) fees as disclosed in annual reports Explanatory (Control) Variables LnSALES = natural log of auditee’s sales = square root of auditee’s number of SUBS0.5 consolidated subsidiaries LnDEBTR = natural log of auditee’s total year-end debtors to total assets EARN = auditee’s total year-end earnings before interest and tax to total assets OPIN = audit qualification, coded 1 if auditee received an ‘unqualified report’, otherwise 0 LTLBTA = auditee’s ratio of long-term liabilities to total assets LnCR = natural log of auditee’s current ratio LOSS = coded 1 if auditee incurred a net loss in any of the past three years, otherwise 0 © Blackwell Publishing Ltd 2004

Experimental (Test) Variable BIG5 = coded 1 if the auditor is a ‘Big 5’ firm, otherwise 0 Table 2 provides important statistics about the shape of the data distribution for the variables of this study. It appears that the distributions of some of the continuous variables show high skewness and/or kurtosis values and, thus, data transformations are necessary to correct these violations and consequently the distributions to be improved (Hair et al., 1998). In prior research, two different empirical model specifications have been used. One is a natural log transformation of audit fee and the auditee size and risk measures, and also the square root transformation on the count of subsidiaries. The second is a scaling transformation achieved by dividing audit fee by the square root of the auditee size measure. However, both of these transformations are ad hoc, and are not based on any theories which may support the resulting regression relationships (Hair et al., 1998). Transforming variables by taking their natural logarithm, the resulting equation assumes a proportional relationship between the dependent and the independent variables. Scaling audit fee by the auditee size measure, the resulting equation assumes a relationship between the size measure and the other independent variables which may or may not exist. Int. J. Audit. 8: 153–164 (2004)

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Table 3: Regression results for the Indonesian companies (n = 67) Variable

(Constant) Ln(SALES) SQRT(SUBS) Ln(DEBTR) EARN OPIN LTLBTA Ln(CR) LOSS BIG5 Adjusted R square F-value (p-value)

Coefficient

-1.767 0.704 0.310 -0.334 2.6E-09 -0.522 -0.692 0.175 0.004 0.631 0.60 12.181 (