Based on the panel data of Chinese listed companies spanning the period 1999-2015, this paper investigates the effects of Chairman’s cultural background characteristics on audit fees. The results show that Chairman’s cultural background characteristics significantly affect the company’s audit fees, the Chairman with the nomadic culture background compared with who with cultivation culture background tends to pay lower audit fees, and the relationship above is enhanced when the company’s Chairman and CEO is the same person. Furthermore, this paper finds that the bigger the board size, or the longer the Chairman’s tenure, the lower the audit fees the company whose Chairman has the nomadic culture background will pay.
The audit fees depend on the outcome of the final negotiation between the audit service provider and the company, which is subject to the bargaining power of both parties. The senior echelon theory believes that the executive characteristics influence the company’s choice of strategy, which further affect the company’s other behaviors (Hambrick and Mason, 1984) [
After Simunic (1980) [
This paper uses the panel data of China’s listed companies for 1999-2015 as the sample, and uses the native place of the Chairman to measure his or her cultural background. The results show that Chairman’s cultural background characteristics significantly affect the company’s audit fees, the Chairman with the nomadic culture background compared with those with cultivation culture background tend to pay lower audit fees, and the relationship above is enhanced when Chairman and CEO is the same person. Furthermore, the bigger the board size, the longer the Chairman’s tenure, the lower the audit fees paid by the company whose Chairman has the nomadic culture back-ground.
The main innovation of this paper is providing a new perspective to explain how audit fees are formed. The existing researches only suggest that the following aspects may affect audit fees. 1) The characteristics of company, including the size, debt ratio, return on assets, inventory to total assets ratio, loss, listing years, Ownership. 2) The characteristics of auditor’s office, including auditor reputation, audit tenure, audit opinion. 3) Personal characteristics of Chairman and CEO, including Chairman and CEO’s age, tenure, etc. Yet, there don’t exit discussions about how culture affect audit fees through the Chairman, this paper’s results show that culture do affect the behavior of company as well as audit fees, and the mechanism is that culture can affect the risk preference of the Chairman and affect the audit fees further. In addition, this paper is one of the earliest literatures in China to study the relationship between culture and company behaviors, which, of course, can expand the literatures in the field of culture and finance.
One of the ways in which culture affects corporate decision-making is to influence Chairman’s behavior and cognition and then to influence corporate decision-making. Studies have showed that individual decisions under different cultures have systematic differences (Ji et al., 2001) [
As the saying goes, “A side water and soil raises a side people”, different environments have created different personalities. Though different cultural elements form Chinese culture together, it cannot be ignored that there has been a parallel development of nomadic culture and farming culture in China since ancient times. Historically, nomadic culture and farming culture impact and blend with each other, but people from two cultures still maintain different patterns of behavior and behavior characteristics. Specifically, most of the nomadic people of our country live on the Qinghai Tibet Plateau, the northwest region and the Mongolia plateau, which have a bad natural environment. People there live by grazing and hunting, even go to wars owning to plundering materials and properties, power struggles between the tribes, etc. The cruelty of the natural environment, the unique way of life, and the continuous wars make the life of the nomadic people full of risk, as a result, the nomadic nations are more able to take risks and more of risk awareness. While, people in farming areas have cultivated land, unless there are large natural disasters and social unrest, they are generally able to be self-sufficient and live in peace and happiness. Therefore, people living in nomadic areas tend to take more risk than people in farming areas (Næss, 2003) [
Hypothesis 1: Chairman with nomadic cultural background will pay lower audit fees than Chairman with farming culture background.
Chairman and CEO duality generally exists in the listed companies at home and abroad. The influence of Chairman and CEO duality on the behavior of the company has not yet formed a more consistent conclusion. The agency theory holds that Chairman and CEO duality is not conducive to mitigating agency problems and also not conducive to the promotion of corporate value (Fama and Jensen, 1983; Hoitash, 2009) [
The hypothesis 2: Chairman and CEO duality will strengthen the negative relationship between the Chairman’s nomadic culture background and the audit fees.
The effectiveness of the board directly determines the extent of the board’s function, and the size of the board is one of the important factors that affect the effectiveness of the board. Jensen (1993) [
Hypothesis 3: the negative relationship between the nomadic cultural background of the Chairman and the audit fees will be enhanced in the larger scale of the board.
The research shows that Chairman’s characteristics can significantly affect the company’s decision-making. Chairman’s tenure is an important aspect of the chairman’s personal characteristics (Liu Yawei and Zhang Zhaoguo, 2016) [
Hypothesis 4: the longer the Chairman’s tenure is, the more negative the relationship between the chairman’s nomadic cultural background and the audit fees.
This is an empirical research, in which we use the regression model based on the least square method and data to test the 4 hypotheses suggested above. The empirical model and its variables introduced in detail in Section 3.2 and 3.3 of the paperare based on the exiting literatures about audit fees and have been well verified, and the data this paper uses are coming from databases and websites of finance and economics which are introduced in Section 3.1. To run the regression model and do the data analysis, this paper uses Stata as the software tool. Next, this paper will introduce the data sources and data filtering, variables definition, empirical model and the descriptive statistics of the data.
This paper uses the data of listed companies in Shanghai and Shenzhen Stock Exchange from 1999 to 2015 as the sample, the number of observations of which are 6958. When selecting the sample, the following companies were excluded: 1) Financial companies. 2) Companies that are categorized as ST, *ST in a certain year or continuous years. 3) Companies with abnormal indicators. The financial data and the Chairman’s native place data of Chinese listed companies all come from CSMAR Database, CCER Database and RSSET Database, as well as the major financial websites. CSMAR Database is developed by Shenzhen GTA Education Tech Ltd., its design concept, based on the Chinese corporations, draws lessons from the successful experiences of CRSP, Compustat, Thomson, etc. The database is the largest and most accurate financial and economic database in China. It is composed of 8 major series, namely, stocks, funds, bonds, financial derivatives, listed companies, economy, industry and high frequency data. CCER China Economic and financial Database is a research database launched by Sinofin Information Services cor., Ltd. and the National Development Research Institute of Peking University, and RESSET database is a data platform providing professional services for model testing and investment research, developed by experts coming from Tsinghua University and Peking University, more than 560 well-known domestic and foreign universities and research institutions have used RESSET Database products by 2016. The websites for each of the three databases are as follows: http://www.gtarsc.com, http://www.ccerdata.cn/Home/Login.aspx and http://www.resset.cn, repectively. Also, there are a few data coming from websites such as Sina finance and economics, Hexun Network, and their websites are http://finance.sina.com.cn and http://renwu.hexun.com.
This paper’s explained variable is audit fees. On the basis of the existing literature, such as Xing Liquan and Chen Hanwen (2013) [
According to the research of Simunic (1980) [
We use the following regression model to test the hypothesis 1 to hypothesis 4.
F e e i t = β 0 + β 1 Culture i t + β 2 Ownsh i t + β 3 Debt i t + β 4 Roa i t + β 5 Size i t + β 6 Csset i t + β 7 Loss i t + β 8 Listyear i t + β 9 Big 4 i t ( orbig 5 i t ) + β 10 Autenure i t + β 11 Autype i t + β 12 Age i t + β 13 Tenure i t + ∑ 14 30 Year + ∑ 31 40 I n d + ε i t (1)
In the regression model, β0 represents the constant, β1 − β40 represent the coefficients of Culture, and εit represents the residual.
Variables | Definition |
---|---|
Dependent variable | |
Fee | Natural log of year-end audit fees |
Independent variable | |
Culture | If Chairman belongs to nomadic culture areas, 1, otherwise, 0 |
Control variables | |
Duality | If Chairman and CEO is the same person, 1, otherwise, 0 |
Ownsh (ownersh) | If corporate belongs to state-owned business, 1, otherwise, 0 |
Debt | Year-end long-term debt/year-end total asset |
Roa | Net income/year-end total asset |
Size | Natural log of year-end total asset |
Casset | Year-end inventory/year-end total asset |
Loss | If net income less than 0, 1, otherwise, 1 |
Listyear | Natural log of listing time |
Big 4/big 5 | If accounting firm is big 4 or big 5, 1, otherwise, 0 |
Autenure | The duration of continuous audit of the accounting firm |
Autype | If audit opinion is standard audit opinion, 1, otherwise, 0 |
Age | Natural log of Chairman’s age |
Tenure | Natural log of Chairman’s tenure |
Variables | Min | Max | Mean | Med | Std |
---|---|---|---|---|---|
Fee | 9.210 | 17.520 | 13.380 | 13.310 | 0.676 |
Culture | 0.000 | 1.000 | 0.965 | 1.000 | 0.184 |
Duality | 0.000 | 1.000 | 0.191 | 0.000 | 0.393 |
Size | 17.920 | 27.550 | 21.940 | 21.750 | 1.258 |
Debt | 0.026 | 0.996 | 0.498 | 0.502 | 0.188 |
Roa | −0.691 | 0.496 | 0.037 | 0.035 | 0.053 |
Casset | 0.000 | 0.943 | 0.182 | 0.139 | 0.165 |
Loss | 0.000 | 1.000 | 0.078 | 0.000 | 0.269 |
Listyear | 0.511 | 3.219 | 2.185 | 2.335 | 0.617 |
Ownsh | 0.000 | 1.000 | 0.515 | 1.000 | 0.500 |
Big4/Big5 | 0.000 | 1.000 | 0.041 | 0.000 | 0.199 |
Autenure | 0.000 | 2.708 | 1.326 | 1.386 | 0.647 |
Age | 3.573 | 3.907 | 3.807 | 3.822 | 0.084 |
Tenure | −0.543 | 3.219 | 1.822 | 1.873 | 0.554 |
Autype | 0.000 | 1.000 | 0.968 | 1.000 | 0.176 |
control variables, such as company profitability and debt ratio, are similar to the statistical results of existing studies. For example, the asset liability ratio is 49.8%, close to 50%, and the total assets earnings rate is 3.75%, which indicates that the statistical results of the sample are reliable.
In
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Total sample | Total sample | No duality | Duality | |
Culture | −0.098** | −0.108*** | −0.063** | −0.296*** |
(−2.374) | (−3.958) | (−2.071) | (−4.248) | |
size | 0.384*** | 0.390*** | 0.355*** | |
(57.379) | (66.092) | (29.199) | ||
debt | −0.054* | −0.036 | −0.100 | |
(−1.648) | (−0.875) | (−1.400) | ||
roa | 0.061 | −0.046 | 0.277 | |
(0.513) | (−0.321) | (1.083) | ||
caset2 | −0.115*** | −0.111** | −0.200** | |
(−2.753) | (−2.311) | (−2.187) | ||
loss | 0.061*** | 0.051* | 0.087* | |
(2.709) | (1.947) | (1.793) | ||
listtime | −0.029*** | −0.040*** | −0.002 | |
(−2.704) | (−3.494) | (−0.106) | ||
ownership | −0.063*** | −0.069*** | −0.013 | |
(−5.600) | (−5.445) | (−0.453) | ||
Big4/big5 | 0.640*** | 0.593*** | 0.792*** | |
(17.634) | (20.504) | (12.895) | ||
audittenure | 0.011 | 0.017* | −0.022 | |
(1.400) | (1.853) | (−1.151) | ||
autype | −0.143*** | −0.156*** | −0.107* | |
(−5.593) | (−4.542) | (−1.946) | ||
age | 4.575 | 0.520 | 21.044 | |
(0.388) | (0.037) | (0.797) | ||
tenure | 0.007 | 0.000 | 0.042* | |
(0.659) | (0.014) | (1.770) | ||
Constant | 12.487*** | −11.336 | 3.215 | −76.300 |
(165.466) | (−0.269) | (0.059) | (−0.740) | |
Year | Yes | Yes | Yes | Yes |
Industry | Yes | Yes | Yes | Yes |
Adj.-R2 | 0.187 | 0.645 | 0.653 | 0.642 |
N | 7744 | 6958 | 5508 | 1304 |
Chi2 | 11.02*** |
Notes: Significance level at: *10, **5 and ***1 percent; numbers in parenthesis are t-statistics for t tests, Chi2-statistic for Chow test.
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Small board size | Big board size | Short tenure | Long tenure | |
Culture | −0.065* | −0.225*** | −0.039 | −0.188*** |
(−1.882) | (−4.894) | (−1.007) | (−4.981) | |
size | 0.373*** | 0.399*** | 0.383*** | 0.385*** |
(56.600) | (44.287) | (53.767) | (49.113) | |
debt | −0.052 | −0.092 | 0.002 | −0.144*** |
(−1.201) | (−1.539) | (0.043) | (−2.684) | |
roa | 0.310** | −0.358* | −0.062 | 0.176 |
(2.012) | (−1.744) | (−0.354) | (1.021) | |
caset2 | −0.085* | −0.164** | −0.199*** | −0.003 |
(−1.698) | (−2.088) | (−3.439) | (−0.043) | |
loss | 0.083*** | 0.031 | 0.021 | 0.117*** |
(2.841) | (0.832) | (0.674) | (3.513) | |
listtime | −0.032*** | −0.014 | −0.043*** | 0.013 |
(−2.620) | (−0.808) | (−3.488) | (0.648) | |
ownership | −0.061*** | −0.062*** | −0.064*** | −0.072*** |
(−4.291) | (−3.213) | (−4.016) | (−4.402) | |
Big4/big5 | 0.670*** | 0.599*** | 0.618*** | 0.664*** |
(18.874) | (15.379) | (17.078) | (17.968) | |
audittenure | 0.041*** | −0.035** | 0.016 | 0.002 |
(3.939) | (−2.566) | (1.491) | (0.156) | |
autype | −0.146*** | −0.144*** | −0.143*** | −0.144*** |
(−3.989) | (−2.969) | (−3.781) | (−3.175) | |
age | 21.416 | −24.793 | −13.816 | 30.582 |
(1.398) | (−1.199) | (−0.851) | (1.623) | |
tenure | −0.019 | 0.050*** | ||
(−1.472) | (2.885) | |||
Constant | −78.091 | 101.847 | 59.319 | −114.196 |
(−1.306) | (1.262) | (0.936) | (−1.553) | |
Year | Yes | Yes | Yes | Yes |
Industry | Yes | Yes | Yes | Yes |
Adj.−R2 | 0.630 | 0.681 | 0.645 | 0.640 |
N | 4422 | 2536 | 4040 | 2918 |
Chi2 | 8.27*** | 7.48*** |
Notes: Significance level at: *10, **5 and ***1 percent; numbers in parenthesis are t-statistics for t tests, Chi2-statistics for Chow tests.
behavior, so the negative relationship between the chairman’s nomadic cultural background and the audit fees is enhanced.
Considering the endogeneity of audit fees, the paper use one-year lagged audit fees to substitute audit fees of current period and do the robust tests,
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Total sample | Total sample | No duality | Duality | |
Culture | −0.101** | −0.128*** | −0.090*** | −0.334*** |
(−2.234) | (−4.041) | (−2.673) | (−3.927) | |
size | 0.373*** | 0.377*** | 0.357*** | |
(49.301) | (56.390) | (24.454) | ||
debt | −0.095** | −0.062 | −0.218** | |
(−2.421) | (−1.301) | (−2.456) | ||
roa | −0.139 | −0.274* | 0.213 | |
(−1.059) | (−1.667) | (0.683) | ||
caset 2 | −0.104** | −0.093* | −0.269** | |
(−2.216) | (−1.743) | (−2.391) | ||
loss | 0.060** | 0.047 | 0.113* | |
(2.380) | (1.594) | (1.889) | ||
listtime | −0.003 | −0.018 | 0.055* | |
(−0.195) | (−1.229) | (1.937) | ||
ownership | −0.043*** | −0.045*** | −0.008 | |
(−3.426) | (−3.185) | (−0.232) | ||
Big 4/big 5 | 0.607*** | 0.569*** | 0.751*** | |
(14.324) | (17.377) | (10.092) | ||
audittenure | 0.001 | 0.005 | −0.025 | |
(0.098) | (0.431) | (−1.096) | ||
autype | −0.130*** | −0.142*** | −0.067 | |
(−4.591) | (−3.510) | (−0.993) | ||
age | 17.135 | 12.796 | 41.755 | |
(1.234) | (0.798) | (1.281) | ||
tenure | 0.004 | 0.007 | 0.007 | |
(0.282) | (0.503) | (0.214) | ||
Constant | 13.411*** | −61.441 | −44.564 | −157.340 |
(355.596) | (−1.134) | (−0.712) | (−1.236) | |
Year | Yes | Yes | Yes | Yes |
Industry | Yes | Yes | Yes | Yes |
Adj.−R2 | 0.179 | 0.622 | 0.630 | 0.623 |
N | 6249 | 5530 | 4460 | 962 |
Chi2 | 7.86*** |
Notes: Significance level at: *10, **5 and ***1 percent; numbers in parenthesis are t-statistics for ttests, Chi2-statistics for Chow tests.
results of H3 and H4. We can find that the sign and significance of parameters have no change. Moreover, estimations of Culture are significantly different between the two groups, showing the robustness of the results. This paper also uses standard error of clustering robustness and replicate the robust tests, the results shown in
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Small board size | Big board size | Short tenure | Long tenure | |
Culture | −0.094** | −0.223*** | −0.054 | −0.202*** |
(−2.395) | (−4.295) | (−1.158) | (−4.963) | |
size | 0.358*** | 0.389*** | 0.367*** | 0.379*** |
(47.313) | (37.944) | (41.949) | (45.417) | |
debt | −0.082 | −0.156** | −0.033 | −0.178*** |
(−1.581) | (−2.253) | (−0.557) | (−3.056) | |
roa | 0.090 | −0.573** | −0.258 | −0.045 |
(0.501) | (−2.397) | (−1.163) | (−0.244) | |
caset2 | −0.090 | −0.111 | −0.211*** | 0.007 |
(−1.570) | (−1.245) | (−2.980) | (0.111) | |
loss | 0.061* | 0.049 | 0.019 | 0.112*** |
(1.828) | (1.163) | (0.489) | (3.117) | |
listtime | 0.002 | −0.000 | −0.028 | 0.033 |
(0.144) | (−0.003) | (−1.617) | (1.489) | |
ownership | −0.047*** | −0.032 | −0.047** | −0.046*** |
(−2.956) | (−1.468) | (−2.467) | (−2.662) | |
Big4/big5 | 0.642*** | 0.558*** | 0.603*** | 0.605*** |
(15.396) | (12.723) | (13.510) | (15.353) | |
audittenure | 0.033*** | −0.050*** | 0.012 | −0.013 |
(2.758) | (−3.253) | (0.893) | (−0.992) | |
autype | −0.128*** | −0.140** | −0.115** | −0.150*** |
(−2.946) | (−2.460) | (−2.405) | (−3.020) | |
age | 29.158 | −4.728 | −5.218 | 35.533* |
(1.615) | (−0.199) | (−0.257) | (1.763) | |
tenure | −0.019 | 0.040* | ||
(−1.237) | (1.893) | |||
Constant | −108.161 | 23.688 | 26.013 | −133.481* |
(−1.535) | (0.255) | (0.328) | (−1.696) | |
Year | Yes | Yes | Yes | Yes |
Industry | Yes | Yes | Yes | Yes |
Adj.−R2 | 0.599 | 0.670 | 0.626 | 0.617 |
N | 3509 | 2021 | 2821 | 2709 |
Chi2 | 3.88** | 5.37** |
Notes: Significance level at: *10, **5 and ***1 percent; numbers in parenthesis are t-statistics for t tests, Chi2-statistics for Chow tests.
Culture finance is a hot topic in the academic field, and western scholars have put forward the importance of culture to corporate behavior earlier (Kwok and
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Total sample | Total sample | No duality | Duality | |
Culture | −0.101 | −0.108* | −0.063 | −0.296** |
(−0.944) | (−1.877) | (−1.024) | (−2.549) | |
size | 0.384*** | 0.390*** | 0.355*** | |
(27.777) | (25.801) | (13.579) | ||
debt | −0.054 | −0.036 | −0.100 | |
(−0.868) | (−0.526) | (−0.787) | ||
roa | 0.061 | −0.046 | 0.277 | |
(0.324) | (−0.227) | (0.614) | ||
caset2 | −0.115 | −0.111 | −0.200 | |
(−1.402) | (−1.222) | (−1.284) | ||
loss | 0.061** | 0.051 | 0.087 | |
(2.148) | (1.574) | (1.467) | ||
listtime | −0.029 | −0.040* | −0.002 | |
(−1.330) | (−1.664) | (−0.060) | ||
ownership | −0.063*** | −0.069*** | −0.013 | |
(−2.602) | (−2.727) | (−0.262) | ||
Big4/big5 | 0.640*** | 0.593*** | 0.792*** | |
(9.525) | (8.527) | (5.004) | ||
audittenure | 0.011 | 0.017 | −0.022 | |
(0.868) | (1.178) | (−0.806) | ||
autype | −0.143*** | −0.156*** | −0.107* | |
(−4.147) | (−3.719) | (−1.688) | ||
age | 4.575 | 0.520 | 21.044 | |
(0.179) | (0.019) | (0.415) | ||
tenure | 0.007 | 0.000 | 0.042 | |
(0.350) | (0.008) | (0.988) | ||
Constant | 13.411*** | −12.536 | 3.215 | −76.300 |
(207.736) | (−0.126) | (0.029) | (−0.385) | |
Year | Yes | Yes | Yes | Yes |
Industry | Yes | Yes | Yes | Yes |
Adj.−R2 | 0.179 | 0.645 | 0.653 | 0.642 |
N | 6249 | 6958 | 5508 | 1304 |
Chi2 | 11.02 |
Notes: Significance level at: *10, **5 and ***1 percent; numbers in parenthesis are t-statistics for t tests, Chi2-statistics for Chow tests.
Tadesse, 2006, Chen et al., 2015). It is a significant financial decision of the company that how much to pay for the audit fees, although there exist literatures about the effects of executive background characteristics such as age, sex, tenure
Variables | (1) | (2) | (3) | (4) |
---|---|---|---|---|
Small board size | Big board size | Short tenure | Long tenure | |
Culture | −0.065 | −0.225*** | −0.039 | −0.188** |
(−0.896) | (−2.600) | (−0.687) | (−2.451) | |
size | 0.373*** | 0.399*** | 0.383*** | 0.385*** |
(22.213) | (18.402) | (23.162) | (22.190) | |
debt | −0.052 | −0.092 | 0.002 | −0.144 |
(−0.697) | (−0.909) | (0.028) | (−1.623) | |
roa | 0.310 | −0.358 | −0.062 | 0.176 |
(1.348) | (−1.211) | (−0.256) | (0.730) | |
caset2 | −0.085 | −0.164 | −0.199** | −0.003 |
(−0.852) | (−1.247) | (−2.101) | (−0.021) | |
loss | 0.083** | 0.031 | 0.021 | 0.117*** |
(2.543) | (0.630) | (0.638) | (2.820) | |
listtime | −0.032 | −0.014 | −0.043* | 0.013 |
(−1.225) | (−0.421) | (−1.916) | (0.345) | |
ownership | −0.061* | −0.062* | −0.064** | −0.072** |
(−1.953) | (−1.900) | (−2.366) | (−2.222) | |
Big 4/big 5 | 0.670*** | 0.599*** | 0.618*** | 0.664*** |
(6.775) | (6.868) | (6.318) | (10.258) | |
audittenure | 0.041** | −0.035* | 0.016 | 0.002 |
(2.404) | (−1.829) | (1.039) | (0.102) | |
autype | −0.146*** | −0.144** | −0.143*** | −0.144*** |
(−3.669) | (−2.284) | (−3.335) | (−3.096) | |
age | 21.416 | −24.793 | −13.816 | 30.582 |
(0.691) | (−0.627) | (−0.518) | (0.817) | |
tenure | −0.019 | 0.050 | ||
(−0.781) | (1.593) | |||
Constant | −78.091 | 101.847 | 59.319 | −114.196 |
(−0.645) | (0.659) | (0.570) | (−0.782) | |
Year | Yes | Yes | Yes | Yes |
Industry | Yes | Yes | Yes | Yes |
Adj.−R2 | 0.630 | 0.681 | 0.645 | 0.640 |
N | 4422 | 2536 | 4040 | 2918 |
Chi2 | 8.27*** | 7.48*** |
Notes: Significance level at: *10, **5 and ***1 percent; numbers in parenthesis are t-statistics for t tests, Chi2-statistics for Chow tests.
and heterogeneity of these on audit fees, few researches discuss how cultural background characteristics of Chairman affect audit fees. Western researches have studied how culture affects corporate financial decisions and corporate governance, but it is difficult to control the differences between national accounting standards, tax systems, bankruptcy laws and the implementation of laws.
This paper studies the influence of Chairman’s cultural background characteristics on the company’s audit fees by using the Chairman’s native place to measure the Chairman’s culture background, the results show that the Chairman’s cultural background characteristics significantly influence the audit fees, and compared to the Chairman coming from farming culture areas, the Chairman of the nomadic culture areas is only willing to pay lower audit fees. The main reason is that due to the influence of natural and social environment and other factors, people in nomadic culture areas will take more risks than people in farming culture areas, resulting in people coming from nomadic culture areas are more willing to take risks, and also more of risk awareness. This paper also finds that in the company of which the Chairman and CEO is the same person, the board size is bigger, the Chairman’s tenure is longer, the negative relationship between nomadic culture background and audit fees is more stronger. That is because it will strengthens the authority of the chairman and weaken the supervision of the board of directors if the Chairman and CEO is the same person, and the bigger board size will also weaken the supervision of the board of directors, and the chairman’s personal characteristics will also be more likely to be shown in the company’s decisions with longer tenure of Chairman.
Unavoidably, there are still some limitations of this paper. Due to difficulties in the acquisition of certain data, there are still some other factors we don’t consider, such as the other differences between culture areas, which may weaken the conclusions of this paper. Still, this is the direction of author’s follow-up research.
Hu, X.Q. (2018) Chairman’s Cultural Background Characteristics and Audit Fees: Based on Chinese Listed Companies. Open Journal of Accounting, 7, 107-124. https://doi.org/10.4236/ojacct.2018.72008