Determinants of Audit Fees in China - Essay Example

?Empirical Analysis of Determinants of Audit Fees in China Table of Contents 4. Analysis 3 4 Introduction 3 4.2 Descriptive Statistics of whole sample 3 4.3 Descriptive Statistics of sub-sample 5 4.4 Correlation Analysis of whole sample 8 4.5 Correlation Analysis of sub-sample 9 4.6 Regression Analysis of the whole sample 13 4.6 Regression Analysis of the Sub Sample 14 4.7 Interpretation 16 Reference List 18 4. Analysis 4.1 Introduction This section deals with the findings and analysis of the collected data. The analysis is based on descriptive, correlation and regression analysis of the data that has been collected by using various databases. The data like financial characteristics of the listed companies, audit fees, audit opinion and auditors are collected from the CSMAR database. However, financial information about some of the listed companies was missing for which the Chinese database RESSET was used as the supplementary source. Apart from this, annual report of some of the companies was also checked. The data that are considered for the study are of 2011. For the analysis of the collected data SPSS, statistical software has been used. The first section is based on the analysis of the whole data set that comprises of data of the listed companies of both Shenzhen and Shanghai. The second section analyses the data of the two cities separately. 4.2 Descriptive Statistics of whole sample The Table 1 given below shows the statistics for the audit fees with respect to the other variables. As the table shows that the minimum audit fees is ?1.00 million, whereas the maximum is ?3.51 million. This reveals that there is a huge difference between the audit fees of the two cities. However, the average audit fees in these two cities are ?3.51 million. This huge difference can be due to the factors like characteristics of the area and financial position of the company, which are located at the various places of the two cities. The total assets of the companies refer to the total client size of the organization. The minimum total assets of the companies are 7.89 and the maximum total assets of the company are 11.70. The average total assets held by the companies participating in the study are 9.50. The inventory ratio of the companies is also hypotheses to be one of the important factors. The minimum inventory ratio is 0 while the maximum is .94. The average inventory ratio is 0.18. The inventory ratio depicts a huge difference between the maximum and minimum levels. Some of the organizations are seen to have no inventories at all while some other companies are having a high level of inventory with them. This ratio helps in determining the fact whether the organization is making optimum utilization of resources. Therefore, a high inventory ratio is not good for the organization (Barthwal, 2007; Anupindi et al., 2008). Accounts receivables is the claim that is paid in cash and in exchange for the product and services that are provided by the company. The position of accounts receivable in comparison to the total assets of the firm is shown by the accounts receivable ratio. It signifies the complexity of the organization (Jiambalvo, 2009; 2007; Weil, 2012). The table 1 shows that the accounts receivable ratio ranges between the minimum value of 00 and the maximum value of 0.60. The average account receivable ratio is 0.93. The intangibles ratio of the firm is another factor, which is considered to affect the auditor’s fees. When the intangible assets are compared to the total asset, it is seen that the ratio is at a minimum level of 00 and the maximum level of 0.67. The average intangible ratio is 0.05. This reveals that some of the companies do not have any type of intangible assets while some others have. The current ratio is another factor that may affect the audit fees. The current ratio is calculated by dividing the current assets by the current liabilities (Lasher, 2013; Pratt, 2010; Gibson, 2012). The minimum current ratio is 0.11 and the maximum is 204.74. This signifies that there exists a huge difference in the level of current assets when compared to current liabilities. Audit fee is hypothised to be dependent on the audit opinion, allotment, big 4, area and list, which are represented either as 0 or 1. The average value of audit opinion is 0.032, which signifies that the about 3.2 percent of the audit provided un-standardized and unqualified opinions to the organizations. The mean value of big 4 reveals that 3.5 percent of the audits done are by the big four audit firms, which shows that they are not having a monopoly power over the market of China. The mean value of Return on Equity (ROE) reveals that on an average about 5.5 percent of the organizations have their ROE between 6 to 7 percent. On the other hand the mean value of list signifies that on an average about 8.3 percent of the companies have their ROE between 0 to 2 percent. Table 1: Descriptive Statistics of the whole sample N Minimum Maximum Mean Std. Deviation Log audit fees 1487 1.00 3.51 1.8000 .24786 Log total assets 1487 7.89 11.70 9.5034 .50980 Inventory ratio 1487 .00 .94 .1842 .16503 Account receivable ratio 1487 .00 .60 .0938 .09357 Intangible ratio 1487 .00 .67 .0495 .06278 Audit ratio 1487 .00 1.00 .0323 .17680 Big4 1487 .00 1.00 .0350 .18376 Allotment 1487 .00 1.00 .0558 .22965 Area 1487 .00 1.00 .5205 .49975 Current ratio 1487 .11 204.74 2.6575 8.00353 List 1487 .00 1.00 .0841 .27757 Valid N (listwise) 1487 4.3 Descriptive Statistics of sub-sample The descriptive statistics of the two cities namely Shenzhen and Shanghai (Table 2 and 3) are considered separately in order to get a clear understanding regarding the determinants of audit fee of the two cities. The minimum audit fee of Shenzhen is ?1.18 million, while that in Shanghai is ? 1.00 million. This reveals a significant difference between the minimum audit fees of the both cities. On the other hand, the maximum audit fee of Shenzhen is ?2.85 million and that of Shanghai is ? 3.51 million. However, no such huge difference is observed between the average audit fees of both the two cities. The maximum, minimum and the average amount of total assets held by the two cities are almost equal. The minimum total assets of Shenzhen are 7.89 while that of Shanghai is 7.94. On the other hand, the maximum log value of the total assets of Shenzhen and Shanghai is 11.15 and 11.70 respectively. Again, the average log total asset is 9.37 for Shenzhen and 9.64 for Shanghai. For inventory ratio, the minimum of both the cities are at zero and the maximum is 0.94 for Shenzhen and 0.90 for Shanghai. This signifies that though the two cities are not having a huge difference between their maximum and average inventory ratio but the companies in Shanghai are seen to utilize their resources in a much efficient manner than that of Shenzhen. The minimum accounts receivable ratio of both the cities are same but there lies difference in the figures of the maximum accounts receivable ratio; for Shenzhen it is 0.60, whereas that of Shanghai is 0.44. The average for that of Shenzhen and Shanghai are 0.10 and 0.08 respectively. This signifies that the companies located in Shenzhen are having higher amount of accounts receivable as compared to the income of the organization. Apart from this, the descriptive statistics also signifies that the intangibles assets in the organizations of Shanghai are much higher in amount as compared to the total assets. The figures of current ratio signify that the organizations that are located in Shenzhen are having much higher amount current assets as compared to the current liabilities. The other independent variables like audit option, list, allotment and big four are showing a minimum and maximum value of 0 and 1 respectively. The average value of audit option shows that 2.2 percent of the firms in Shenzhen and 4.3 percent of the firms in Shanghai receive unprofessional and un-standardized recommendations from the audit firms. Again audit of 2.2 percent of the firms in Shenzhen and 4.9 percent of the firms in Shanghai are done by the big four audit firms. The average value of allotment and list reveals that the return on equity of about 6.3 percent firms in Shenzhen is between 6 to 7 percent and about 7.4 percent of the firms has less than 2 percent ROE. On the other hand, for Shanghai it is 4.7 percent of the firms are between 6 to 7 percent and about 9.4 percent of the firm has their ROE less than 2 percent. Table 2: Descriptive Statistics of Shenzhen N Minimum Maximum Mean Std. Deviation Audit fees 774 1.18 2.85 1.7460 .21009 Total assets 774 7.89 11.15 9.3766 .45978 Inventory ratio 774 .00 .94 .1776 .15590 Account receivable ratio 774 .00 .60 .1061 .09759 Intangible ratio 774 .00 .55 .0471 .05052 Audit option 774 .00 1.00 .0220 .14666 Big 4 774 .00 1.00 .0220 .14666 Allotment 774 .00 1.00 .0633 .24367 Area 774 1.00 1.00 1.0000 .00000 Current ratio 774 .11 204.74 3.5820 10.93223 List 774 .00 1.00 .0749 .26346 Valid N (listwise) 774 Table 3: Descriptive Statistics of Shanghai N Minimum Maximum Mean Std. Deviation Audit fees 713 1.00 3.51 1.8585 .27150 Total assets 713 7.94 11.70 9.6410 .52580 Inventory ratio 713 .00 .90 .1914 .17424 Account receivable ratio 713 .00 .44 .0805 .08712 Intangible ratio 713 .00 .67 .0520 .07378 Audit option 713 .00 1.00 .0435 .20407 Big 4 713 .00 1.00 .0491 .21620 Allotment 713 .00 1.00 .0477 .21325 Area 713 .00 .00 .0000 .00000 Current ratio 713 .13 11.93 1.6539 1.41427 List 713 .00 1.00 .0940 .29199 Valid N (listwise) 713 4.4 Correlation Analysis of whole sample The table 4 given below shows that the Log audit fee is having a significant relationship with log total assets, inventory ratio, accounts receivable ratio, audit ratio, big four, area, current ratio and list since the value of 2 tailed significance is less than 0.05. The log audit fee is very strongly correlated with log total assets as the value of Pearson correlation is 0.707. The value of Pearson correlation indicates that the correlation between inventory ratio and log audit fee is very weak. Again the log audit fee is negatively correlated with the independent variables like accounts receivable ratio, audit ratio, allotment, area, current ratio and list due to the negative value of the Pearson correlation. The log audit fee is moderately correlated with the auditing done by the big 4 firms. However, the findings after conducting the correlation analysis suggests that the study has failed to find any significant relationship of log audit fee with intangible ratio and allotment. Table 4: Correlation Matrix of whole sample Correlations Log audit fees Log total assets Inventory ratio Account receivable ratio Intangible ratio Audit ratio Big 4 Allotment Area Current ratio List Log audit fees Pearson Correlation 1 .707** .085** -.086** -.022 -.082** .370** -.009 -.227** -.084** -.070** Sig. (2-tailed) .000 .001 .001 .398 .002 .000 .741 .000 .001 .007 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Log total assets Pearson Correlation .707** 1 .145** -.181** -.092** -.166** .248** .003 -.259** -.098** -.060* Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .914 .000 .000 .020 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Inventory ratio Pearson Correlation .085** .145** 1 -.100** -.238** -.038 -.028 .003 -.042 -.066* -.011 Sig. (2-tailed) .001 .000 .000 .000 .142 .274 .918 .109 .011 .681 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Account receivable ratio Pearson Correlation -.086** -.181** -.100** 1 -.116** -.008 .023 -.010 .137** -.021 -.014 Sig. (2-tailed) .001 .000 .000 .000 .750 .380 .694 .000 .418 .585 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Intangible ratio Pearson Correlation -.022 -.092** -.238** -.116** 1 .137** .005 .024 -.038 -.063* .000 Sig. (2-tailed) .398 .000 .000 .000 .000 .843 .355 .138 .014 .985 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Audit ratio Pearson Correlation -.082** -.166** -.038 -.008 .137** 1 -.035 -.044 -.061* -.030 -.014 Sig. (2-tailed) .002 .000 .142 .750 .000 .180 .087 .019 .241 .584 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Big 4 Pearson Correlation .370** .248** -.028 .023 .005 -.035 1 .018 -.074** -.029 -.018 Sig. (2-tailed) .000 .000 .274 .380 .843 .180 .500 .004 .263 .486 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Allotment Pearson Correlation -.009 .003 .003 -.010 .024 -.044 .018 1 .034 .000 -.074** Sig. (2-tailed) .741 .914 .918 .694 .355 .087 .500 .190 .986 .004 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Area Pearson Correlation -.227** -.259** -.042 .137** -.038 -.061* -.074** .034 1 .120** -.034 Sig. (2-tailed) .000 .000 .109 .000 .138 .019 .004 .190 .000 .187 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 Current ratio Pearson Correlation -.084** -.098** -.066* -.021 -.063* -.030 -.029 .000 .120** 1 .037 Sig. (2-tailed) .001 .000 .011 .418 .014 .241 .263 .986 .000 .158 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 List Pearson Correlation -.070** -.060* -.011 -.014 .000 -.014 -.018 -.074** -.034 .037 1 Sig. (2-tailed) .007 .020 .681 .585 .985 .584 .486 .004 .187 .158 N 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 1487 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). 4.5 Correlation Analysis of sub-sample For better understanding, the correlation analysis of the two cities was considered separately. The correlation matrix of Shenzhen reveals that total assets, inventory ratio, accounts receivable ratio, intangible ratio, big four and current ratio has significant relationship with the log audit fees. The log total assets of the firm have a strong correlation with the log audit fees. The independent variables like accounts receivable ratio, intangible ratio, current ratio has a negative correlation with the log audit fees. The value of Pearson correlation depicts that inventory ratio is weakly related to the audit fee. On the other hand, the big four is moderately correlated with the audit fees. However, the study fails to find any significant relationship between log audit fees and audit option, allotment and list in case of organizations in Shenzhen. Table 5: Correlation matrix of Shenzhen Correlations Audit fees Total assets Inventory ratio Account receivable ratio Intangible ratio Audit option Big 4 Allotment Area Current ratio List Audit fees Pearson Correlation 1 .621** .165** -.095** -.098** -.049 .305** -.025 .b -.075* -.036 Sig. (2-tailed) .000 .000 .008 .006 .171 .000 .493 . .036 .317 N 774 774 774 774 774 774 774 774 774 774 774 Total assets Pearson Correlation .621** 1 .235** -.197** -.197** -.140** .139** -.008 .b -.082* -.064 Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .814 . .022 .076 N 774 774 774 774 774 774 774 774 774 774 774 Inventory ratio Pearson Correlation .165** .235** 1 -.119** -.220** -.018 -.048 -.046 .b -.096** .014 Sig. (2-tailed) .000 .000 .001 .000 .627 .187 .197 . .007 .695 N 774 774 774 774 774 774 774 774 774 774 774 Account receivable ratio Pearson Correlation -.095** -.197** -.119** 1 -.078* .010 -.016 -.010 .b -.054 -.011 Sig. (2-tailed) .008 .000 .001 .030 .790 .662 .786 . .130 .754 N 774 774 774 774 774 774 774 774 774 774 774 Intangible ratio Pearson Correlation -.098** -.197** -.220** -.078* 1 .173** -.002 .036 .b -.083* .014 Sig. (2-tailed) .006 .000 .000 .030 .000 .956 .321 . .021 .694 N 774 774 774 774 774 774 774 774 774 774 774 Audit option Pearson Correlation -.049 -.140** -.018 .010 .173** 1 -.022 -.039 .b -.024 .024 Sig. (2-tailed) .171 .000 .627 .790 .000 .533 .279 . .497 .499 N 774 774 774 774 774 774 774 774 774 774 774 Big 4 Pearson Correlation .305** .139** -.048 -.016 -.002 -.022 1 .070 .b -.027 -.009 Sig. (2-tailed) .000 .000 .187 .662 .956 .533 .053 . .445 .799 N 774 774 774 774 774 774 774 774 774 774 774 Allotment Pearson Correlation -.025 -.008 -.046 -.010 .036 -.039 .070 1 .b -.002 -.074* Sig. (2-tailed) .493 .814 .197 .786 .321 .279 .053 . .947 .040 N 774 774 774 774 774 774 774 774 774 774 774 Area Pearson Correlation .b .b .b .b .b .b .b .b .b .b .b Sig. (2-tailed) . . . . . . . . . . N 774 774 774 774 774 774 774 774 774 774 774 Current ratio Pearson Correlation -.075* -.082* -.096** -.054 -.083* -.024 -.027 -.002 .b 1 .063 Sig. (2-tailed) .036 .022 .007 .130 .021 .497 .445 .947 . .078 N 774 774 774 774 774 774 774 774 774 774 774 List Pearson Correlation -.036 -.064 .014 -.011 .014 .024 -.009 -.074* .b .063 1 Sig. (2-tailed) .317 .076 .695 .754 .694 .499 .799 .040 . .078 N 774 774 774 774 774 774 774 774 774 774 774 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). b. Cannot be computed because at least one of the variables is constant. The correlation matrix of Shanghai shown in table 6 depicts that audit fees has significant relationship with total assets, audit option, big four, current ratio and list. The value of the Pearson correlations shows that there is a strong correlation between total assets and log audit fees. The log total audit fee has a negative correlation with audit option, current ratio and list. On the other hand, log audit fees have a moderate correlation with the big four audit firms. Table 6: Correlation matrix of Shanghai Correlations Audit fees Total assets Inventory ratio Account receivable ratio Intangible ratio Audit option Big 4 Allotment Area Current ratio List Audit fees Pearson Correlation 1 .742** .012 -.024 .007 -.128** .398** .022 .b -.122** -.114** Sig. (2-tailed) .000 .753 .523 .855 .001 .000 .560 . .001 .002 N 713 713 713 713 713 713 713 713 713 713 713 Total assets Pearson Correlation .742** 1 .057 -.107** -.047 -.222** .304** .035 .b -.166** -.078* Sig. (2-tailed) .000 .127 .004 .209 .000 .000 .358 . .000 .036 N 713 713 713 713 713 713 713 713 713 713 713 Inventory ratio Pearson Correlation .012 .057 1 -.071 -.257** -.057 -.022 .060 .b .039 -.035 Sig. (2-tailed) .753 .127 .059 .000 .126 .566 .108 . .297 .349 N 713 713 713 713 713 713 713 713 713 713 713 Account receivable ratio Pearson Correlation -.024 -.107** -.071 1 -.146** -.008 .076* -.022 .b .036 -.008 Sig. (2-tailed) .523 .004 .059 .000 .826 .044 .551 . .338 .836 N 713 713 713 713 713 713 713 713 713 713 713 Intangible ratio Pearson Correlation .007 -.047 -.257** -.146** 1 .116** .004 .018 .b -.115** -.013 Sig. (2-tailed) .855 .209 .000 .000 .002 .905 .629 . .002 .738 N 713 713 713 713 713 713 713 713 713 713 713 Audit option Pearson Correlation -.128** -.222** -.057 -.008 .116** 1 -.048 -.048 .b -.089* -.045 Sig. (2-tailed) .001 .000 .126 .826 .002 .196 .203 . .018 .229 N 713 713 713 713 713 713 713 713 713 713 713 Big4 Pearson Correlation .398** .304** -.022 .076* .004 -.048 1 -.020 .b -.046 -.029 Sig. (2-tailed) .000 .000 .566 .044 .905 .196 .587 . .220 .445 N 713 713 713 713 713 713 713 713 713 713 713 Allotment Pearson Correlation .022 .035 .060 -.022 .018 -.048 -.020 1 .b -.023 -.072 Sig. (2-tailed) .560 .358 .108 .551 .629 .203 .587 . .538 .054 N 713 713 713 713 713 713 713 713 713 713 713 Area Pearson Correlation .b .b .b .b .b .b .b .b .b .b .b Sig. (2-tailed) . . . . . . . . . . N 713 713 713 713 713 713 713 713 713 713 713 Current ratio Pearson Correlation -.122** -.166** .039 .036 -.115** -.089* -.046 -.023 .b 1 -.023 Sig. (2-tailed) .001 .000 .297 .338 .002 .018 .220 .538 . .535 N 713 713 713 713 713 713 713 713 713 713 713 List Pearson Correlation -.114** -.078* -.035 -.008 -.013 -.045 -.029 -.072 .b -.023 1 Sig. (2-tailed) .002 .036 .349 .836 .738 .229 .445 .054 . .535 N 713 713 713 713 713 713 713 713 713 713 713 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). b. Cannot be computed because at least one of the variables is constant. 4.6 Regression Analysis of the whole sample The regression analysis between the dependent and the independent variables for the whole sample shows that the dependent variable is 54.7 percent affected by the independent variables, since the value of R square as shown in table 7 is .547. According to the values shown in table 8 it can be concluded that log total assets, accounts receivables ratio, intangible ratio, big four and area are significant predictors of the value of dependent variables that is audit fees. Table 7 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .739a .547 .544 .16745 a. Predictors: (Constant), List, Intangibleratio, Big4, Currentratio, Allotment, Accountrecievableratio, Auditratio, Area, Inventoryratio, Logtotalassets Table 8 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -1.255 .093 -13.468 .000 Log total assets .320 .010 .658 33.522 .000 Inventory ratio .010 .028 .007 .380 .704 Account receivable ratio .103 .048 .039 2.136 .033 Intangible ratio .152 .073 .039 2.080 .038 Audit ratio .036 .025 .026 1.423 .155 Big4 .274 .025 .203 11.156 .000 Allotment -.015 .019 -.014 -.794 .428 Area -.022 .009 -.043 -2.352 .019 Current ratio -8.124E-005 .001 -.003 -.147 .883 List -.025 .016 -.028 -1.589 .112 a. Dependent Variable: Logauditfees 4.6 Regression Analysis of the Sub Sample The regression analysis of the sub samples showed in table 9 and 11 shows that for Shenzhen the dependent variable is affected by the independent variables by 43.9 percent; on the other hand in case of Shanghai, the dependent variable is affected 59.1 percent by the independent variables. The table 10 and 12 depicts that in case of Shenzhen total assets and big four firms is a significant predictor of audit fees whereas in case of Shanghai total assets, big four audit firms and list are significant predictor of audit fees. Table 9: Model summary of Shenzhen Model R R Square Adjusted R Square Std. Error of the Estimate 1 .663a .439 .433 .15825 a. Predictors: (Constant), List, Big4, Intangibleratio, Accountrecievableratio, Allotment, Currentratio, Auditoption, Inventoryratio, totalassets Table 10: Regression analysis of organizations in Shenzhen Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -.825 .128 -6.429 .000 totalassets .271 .013 .594 20.133 .000 Inventoryratio .059 .039 .044 1.510 .131 Accountrecievableratio .068 .061 .032 1.130 .259 Intangibleratio .106 .120 .026 .882 .378 Auditoption .048 .040 .034 1.215 .225 Big4 .326 .039 .227 8.257 .000 Allotment -.028 .024 -.033 -1.198 .231 Currentratio .000 .001 -.012 -.417 .677 List .001 .022 .001 .032 .974 a. Dependent Variable: Auditfees Table 11: Model summary of Shanghai Model R R Square Adjusted R Square Std. Error of the Estimate 1 .769a .591 .585 .17480 a. Predictors: (Constant), List, Accountrecievableratio, Currentratio, Allotment, Big4, Inventoryratio, Auditoption, Intangibleratio, totalassets Table 12: Regression analysis of organizations in Shanghai Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -1.637 .137 -11.936 .000 totalassets .360 .014 .697 25.963 .000 Inventoryratio -.018 .039 -.012 -.464 .643 Accountrecievableratio .129 .078 .041 1.664 .097 Intangibleratio .142 .094 .039 1.507 .132 Auditoption .039 .033 .029 1.152 .250 Big4 .229 .032 .182 7.145 .000 Allotment .000 .031 .000 .011 .991 Currentratio .001 .005 .006 .259 .796 List -.048 .023 -.052 -2.125 .034 a. Dependent Variable: Auditfees 4.7 Interpretation The overall analysis of the data set shows that the overall size of the organization has a positive and strong correlation with the audit fees. Hence, first hypothesis is accepted. Inventory ratio is revealing a positive significant relationship with audit fees, hence the alternative hypothesis in accepted and H2 is rejected. There is negative relationship between accounts receivables ratio and audit fees; thus, H3 is rejected. In case of the fourth hypothesis the study has failed to get any significant relationship between intangible ratio and audit fees, so nothing conclusive can be said. Non-standard unqualified audit opinions are negatively related to audit fees, so the fifth hypothesis is also rejected. In case of auditing done by big four audit firms, the audit fees is seen to be positively and moderately related. Hence, H6 accepted. The ROE between 0 to 2 percent is seen to negative relationship with audit fees, while ROE between 6 to 7 percent provides no significant relationship. Therefore, H7 is accepted. Again current ratio is seen to share a negative relationship with audit fees, which signifies that H9 is rejected. Again the audit fee is seen to vary according to location and area is a significant predictor of the dependent variable, so H8 is accepted. Reference List Anupindi, R., Chopra, S., Deshmukh, S.D., Mieghem, J.A.V. and Zemel, E., 2008. Managing business process flows: Principles of operations management. 2nd Ed. New Delhi: Pearson Education India. Barthwal, R.R., 2007. Industrial economics: An introductory text book. New Delhi: New Age International. Gibson, C.H., 2012. Financial reporting and analysis. 13th Ed. Connecticut: Cengage Learning. Jiambalvo, J., 2007. Managerial accounting. New Jersey: John Wiley & Sons. Jiambalvo, J., 2009. Managerial accounting. New Jersey: John Wiley & Sons. Lasher, W.R., 2013. Practical financial management. Connecticut: Cengage Learning. Pratt, J., 2010. Financial accounting in an economic context. New Jersey: John Wiley & Sons. Weil, R.L., 2012. Financial accounting: An introduction to concepts, methods and uses. 14th Ed. Connecticut: Cengage Learning. Read More