To test the hypotheses H1 a – H1 d, the expanded audit fees model is used, which is primarily based on the standard audit fees model of Hay, Knechel and Wong (2006). The expanded audit fees model excludes the internal control variable from the set of control variables to avoid a small sample size outcome, and it includes several additional variables, which are the variables of interest of this study—namely, corporate citizenship variables (CC1YR, 2YR, 3YR), foreign operation (FOREIGN), premium city (PREM_CITY), auditor geographic dispersion (AUD_ GEODISP) and corporate social responsibility (CSR) controls (ENV_STR, ENV_CON, EMP_STR and ENV_CON). In the absence of publicly available data for the number of subsidiary, FOREIGNt indicator is used to proxy for the firm’s complexity associated with multinationals. The expanded audit fees model is as follows: ]^#_66.= `a + `;"";+,,c+,,d+,,. + `c]^'#.+ `dJ)_()HSI.+ `e]Gf.+ `g]Jh. + `i)H#.+ `jk&#. + `m)G$')n".+ `o_H)GJp?.+ `;aqJp4. + `;;#ns_"%#?pG. + `;c()Gk_"J'I. + `;d]^?#$_66. + `;e]^#ns'G?n)G.+ `;g#ns_pGHsJ$(.+ `;i)G$'#'G. + `;jp_"H?"G)?.+ `;m$t#ns]#p.+ `;oqn$I_$G#$H?. + `caJ?fkJ]]$.+ `c;G?f_$'). + `ccG?fuv*.+ `cdGk(_$'). + `ceGk(_"H?.+ ∑J?s.+ ∑IG#). + w. (4)
Where LnAFeet is the natural logarithm of audit fees and the dependent variable. CC1YR, 2YR, 3YR is the corporate citizenship and the independent variable. Corporate citizenship is measured by a firms’ performance in relation to tax fairness (H1 a), wage unfairness (H1 b) and philanthropy (H1 c and H1 d) (as discussed in Sections 4.1.1–4.1.3). All corporate citizenship variables are measured as one-year (annual) performance, except for the tax fairness, which extends to two- and three-year cumulative average performance to be consistent with prior tax literature, which usually uses a cumulative average measure. The discussion on control variables are provided in the following section.
3.3.2.1 Control Variables
Evidence from prior audit research shows that audit fees are more likely to be correlated with three types of audit supply factor: firm-related, auditor and audit engagement characteristics (Hay, Knechel and Wong 2006). Control variables from the firm-related characteristics usually include the risk related to the firm’s size, LnTAt, which is measured as the natural logarithm of the total assets (AT, Compustat#94), the firm’s inherent risk level, IR_PROXYt, which is proxied by the combination of total inventory (INV, Compustat#423) and total receivables (RECT, Compustat#709) divided to total assets (AT, Compustat#94). Financial risk ratios are measured using the leverage ratio and liquidity ratio, LEVt and LIQt. LEVt is computed by dividing the total liabilities (LT, Compustat#527) to the total assets (AT, Compustat#94), and LIQt is computed by dividing the total current assets (ACT, Compustat#49) over the total current liabilities (LCT, Compustat#499). The firm’s profitability rate, ROAt, is measured by ROA, which is computed by dividing the net income (NI, Compustat#553) to total assets (AT, Compustat#94). Restructuring activities are proxied by the merger and acquisition, M&At, which is equal to 1 if the firm engages in merger and acquisition activities and 0 otherwise. Restructuring activities is also measured using year-to-year changes in total assets, RESTRUCt (AT, Compustat#94). Foreign operation, FOREIGNt, which serves as a proxy for complexity17 or multinational is equal to 1 if the firm has pre-tax income foreign and 0 if the firm has not reported any pre-tax foreign income (PIFO, Compustat#620).
The variables, which represent auditors’ characteristics, include auditor reputation, BIG4t, which is assessed by the extent of the auditor’s market size divided by the auditor’s audit fees to total audit fees (AUDIT_FEES, Audit Analytics#5). Auditor change, AUD_CHANGEt, is equal to 1 if the firm’s prior auditor is not the same as its current auditor for the period t (AUDIT_FKEY, Audit Analytics#1). Auditor’s premium city, PREM_CITYt, is equal to 1 if the auditor’s city (AUDIT_CITY, Audit Analytics#9) is located in one of the top six expensive cities in the US. This list of cities is determined from five-year average results for US cities that top the cost-of-living list on the NUMBEO webpage. The inverse Mills ratio, INVMILLSt, serves as a control for the BIG4t selection bias. The INVMILLSt is estimated using the probit regression, which regresses the probability of the audit firm being a BIG4t against the firm’s leverage ratio, ROA and asset turnover. Asset turnover is computed by dividing the total sales (SALE, Compustat#749) over the total assets (AT, Compustat#94).
The control variables classified as audit engagement characteristics include the natural logarithm of non-audit fees ratio, LnNASFeet, which is computed by dividing non-audit fees (NON_AUDIT_FEES, Audit Analytics#6) over audit fees (AUDIT_FEES, Audit Analytics#5). Audit tenure, LnAUD_TENUREt, is measured as the natural logarithm of audit tenure for a specific auditor identified by the auditor’s key (AUDIT_FKEY, Audit Analytics#1). Auditor geographic dispersion, AUD_GEODISP, is equal to 1 if the firm engages an auditor from a similar state (AUDIT_STATE, Audit Analytics#10). The indication of high-risk clients is proxied by audit restatement and the going concern opinion. The restatement, RESTATEt, equals 1 if the firm’s financial reporting is being restated, and 0 otherwise (RESTATEMENT, Audit Analytics#14). Going concern opinion, G_CONCERNt, equals 1 if the firm receives a going concern opinion, and 0 otherwise (GOING CONCERN, Audit Analytics#8). The conflict or difficulty associated with the issuance of audited financial statements is proxied by the audit report lag, SqAUD_LAGt, which is measured as the square root of differences between the date the financial year ended (FISCAL_YEAR_ENDED, Audit Analytics#4) and the signature date of the audited financial statements (SIG_DATE_OF_OP_S, Audit Analytics#7). Audit peak season, BUSY_SEASONt, is identified from firms that have a financial year-end between November and January (FISCAL_YEAR_ENDED, Audit Analytics#4). In addition, the variables include industry, INDt, and year fixed effects, YEARt, in the audit fees model.