Auditors' Perception on Non-Articulation in Financial Statements

Do Auditors Perceive Non-articulation between Financial Statements as a Source of Audit Risk Daniel W. Collins (University of Iowa) Hong Xie (University of Kentucky) Kai Zhu (Shanghai University of Finance and Economics) 1

Research Question Background Bahnson et al. (1996) and Hribar and Collins (2002) document the prevalence of non-articulation, i.e., Changes in noncash C.A. and in C.L. accounts on comparative B/S their corresponding changes on the statement of cash flows Non-articulation amounts (NARTA) = changes in noncash C.A. and in C.L. accounts on comparative B/S their corresponding changes on the statement of cash flows 2

Research Questions continued Why does non-articulation arise? Unusual transactions that are non-operating but affect operating accounts (hereafter, non-articulation transactions or events) Case 1: Delphi Corp (Mulford and Comiskey 2005, p. 142) (1) a non-articulation transaction arranging for GE Capital to pay off its $287 million A/P (2) OCF is artificially inflated by $287 million (3) a positiveNARTA of $287 million Case 1(a): Delphi Corp - hypothetical (1) a non-articulation transaction transferring a piece of land to pay off its $287 million A/P (2) OCF is artificially inflated by $287 million (3) a positiveNARTA of $287 million An otherwise financing (Case 1) or investing (Case 1(a)) cash inflows are classified as operating cash inflows, thereby inflating OCF 3

Research Questions continued Why does non-articulation arise? Case 2: Lesco (1) a non-articulation transaction selling most of its accounts receivable to GE Capital (2) OCF is artificially deflated because Lesco reported the proceeds as financing cash flows (3) a negativeNARTA up to the amount of A/R factored McAfee was sued and identified in a SEC AAER for multiple counts of frauds during 1989-2000, which fraudulently inflated the company s revenues To conceal the buildup of A/R that have little chance to be collected, McAfee sold approximately $261 million A/R to banks for cash during 1998-2000 McAfee s sum of absolute NARTA during 1998-2000 is $73.429 million, about 28% of the A/R sold McAfee s attempt to conceal its frauds leaves a trail (non- articulation) that is captured by NARTA 4

Research Questions continued Why does non-articulation arise? Case 3: Apple (1) a non-articulation transaction employee stock options accounting per SFAS 123 or APB 25 engenders NARTA because the tax benefit reduces Income Taxes Payable on B/S but is credited to APIC (Additional Paid-in Capital) (2) OCF is artificially inflated because most firms report the tax benefit as part of OCF. Unlike other components of OCF, the tax benefit is unlikely to recur (Siegel 2006; Hribar and Nichols 2007) (3) a positiveNARTA equal to the tax benefit Apple was sued and identified in a SEC AAER for misreporting in 2001 and 2002 related to backdating of stock options awarded to Steve Jobs Apple s tax benefit from stock option exercise in 2002 = $28 million and its NARTA = $15 million (using current accounts only) or $25 million (using current accounts + noncurrent accounts shown in the operating section of Apple s SCF) Apple s backdating results in non-articulation and thus can be captured by NARTA 5

Research Questions continued What s the punch line? As long as a cash flow management technique results in non-articulation, that cash flow management technique can be captured by NARTA NARTA appears to be a nature measure of the amount of managed OCF 6

Research Question continued Do auditors perceive non- articulation as a source of audit risk? 7

Literature and Hypothesis 1. Non-articulation between financial statements Drtina and Largay (1985) many events lead to non-articulation, including the changes in the reporting entity (i.e., M&A and divestiture) Huefner et al. (1989) foreign currency translation gains or losses lead to non- articulation Bahnson et al. (1996) 75% of their large sample of Compustat firms report non-articulated changes between comparative B/S and statement of cash flows (SCF). 8

Literature and Hypothesis continued 1. Non-articulation between financial statements Hribar and Collins (2002) accruals estimated using the B/S approach (ACCbs) accruals estimated using the SCF approach (ACCcf), when a non-articulation event is present. Recall: non-articulation events are non- operating transactions that affect operating accounts We define NARTA = ACCbs ACCcf Hribar and Collins (2002) find that NARTA is predictably large in magnitude when there are M&As, divestitures, or foreign currency translations 9

Literature and Hypothesis continued 1. Non-articulation between financial statements The literature up to this point shows: 1) Non-articulation is wide spread 2) Non-articulation is caused by non-articulation events or transactions 3) NARTA is particularly large in magnitude when major non-articulation events (i.e., M&A, divestiture, and foreign currency translations) are present, although NARTA is still present when none of the three major non-articulation events is present However, the literature up to this point does not investigate whether NARTA contains useful information 10

Literature and Hypothesis continued 1. Non-articulation between financial statements Gong et al. (2014) are the first to conjecture based on anecdotal evidence similar to Cases 1, 2, and 3 discussed earlier: 1) Managers can use non-articulation events to manage (inflate or deflate) OCF 2) NARTA resulting from the non-articulation events captures managed portion of OCF Their findings support the above insights NARTA captures managed portion of OCF and |NARTA| contains useful information about a firm s risk. 11

Literature and Hypothesis continued 2. Audit risk and auditor decisions The audit risk model: Audit risk = Inherent risk Control risk Detection risk Prediction of the audit risk model: when auditors perceive an increase in inherent risk or control risk, they must try to reduce detection risk by doing more substantive testing increase audit fees to compensate for more effort and risk 12

Literature and Hypothesis continued 2.1 A large volume of studies support the prediction of the audit risk model Gul and Tsui (1998) - firms of low growth with high free cash flows are more likely to engage in non-value-maximizing activities auditors perceive higher audit risk for these firms charge higher fees Bedard and Johnstone (2004) - auditors plan increased effort and billing rates for clients with earnings manipulation risk Hanlon et al. (2012) - larger absolute BTD indicates high earnings management and low reporting quality auditors charge higher fees for firms with larger absolute BTD 13

Literature and Hypothesis continued 2.1 A large volume of studies support the prediction of the audit risk model Hogan and Wilkins (2008) - firms with internal control weakness have high control risk auditors charge higher fees for firms with internal control weakness 14

Literature and Hypothesis continued 2.2 Auditors can also mitigate increased audit risk by issuing a modified or going- concern audit opinion Carcello and Palmrose (1994) - MAOs issued prior to bankruptcy reduce both the incidence and magnitude of litigation if bankruptcy subsequently occurs Francis and Krishnan (1999) larger absolute accruals pose higher audit risk auditors lower the threshold for issuing MAOs Kaplan and Williams (2013) issuing going- concern opinions reduces auditor litigation probability 15

Literature and Hypothesis continued 3. Hypotheses To summarize, prior literature suggests the following: NARTA captures the managed portion of OCF Firms with larger absolute NARTA are more likely to be involved in cash flow management activities lower financial reporting quality Hypothesis 1: A firm s financial reporting quality is negatively associated with absolute NARTA. 16

Literature and Hypothesis continued 3. Hypotheses Prior literature also suggests the following: Auditors respond to an increase in perceived audit risk by charging higheraudit fees and issuing MAOs or going-concern audit opinions Hypothesis 2a: Audit fees that a firm pays are positively associated with absolute NARTA. Hypothesis 2b: The probability for a firm to receive a modified or going-concern audit opinion is positively associated with absolute NARTA 17

Research Design Measurement of non-articulation amounts ACCbs= ( CA CASH) ( CL STDEBT) DEP (1) ACCcf = (CHGARcf + CHGINVcf+ CHGAPcf + CHGTAXcf+ CHGOTHcf) DEPcf (2) |NARTA| = |ACCbs ACCcf| (3) 18

Research Design continued Absolute NARTA and Reporting Quality 1)SEC AAERS as a proxy for reporting Quality following Armstrong et al. (2013) AAER= a0 + a1|NARTA| + a2MKTCAP + a3BM + a4LEV + a5ROA + a6AGE + a7RETURN + a8STDRET + a9CAPEXP + a10INTANG + a11SGRW + a12RECINV + Industry dummies + (4) a1 > 0 is consistent with H1 19

Research Design continued Absolute NARTA and Reporting Quality 2)Accruals quality as a proxy for reporting Quality following Butler et al. (2004) AQ= c0 + c1|NARTA| + c2MKTCAP + c3BM + c4LEV + c5LagROA + c6LagROA2 + c7CRATIO + c8BigN + Industry dummies + (6) c1 > 0 is consistent with H1 20

Research Design continued Absolute NARTA and Auditor Decisions 1)Audit fees following DeFond et al. (2002) AUDFEE= d0 + d1|NARTA| + d2SIZE + d3BigN + d4ROA + d5RETURN + d7STDRET + d8LEV + d9SPE + d10RECINV + d11INSTN + d12BM + d13SEG + d14REPLAG + d15FINANCE + d16SGRW + d17FIRST2YRS + Industry dummies + (7) d1 > 0 is consistent with H2a 21

Research Design continued Absolute NARTA and Reporting Quality 2)MAOs or GC following DeFond et al. (2002) MAO or GC= e0 + e1|NARTA| + e2BKRPTZ + e3SIZE + e4AGE + e5RETURN + e7STDRET + e8LEV + e9CLEV + e10LagLOSS + e11BigN + e12ROA + e13INVESTM + e14RECINV + e15SGRW + Industry dummies + (8) e1 > 0 is consistent with H2b 22

Research Design continued Sample selection Base sample Accruals quality sample Audit fees and going-concern sample 23

Findings Table 4 Probit regression of AAERs on |NARTA| Variable Intercept |NARTA| MKTCAP BM LEV ROA AGE RETURN Other controls Industry dummies N Pseudo R2 AAER Without MNAE -5.738*** (-20.48) 1.312*** (3.003) 0.159*** (7.233) 0.167*** (3.131) -0.240* (-1.756) 0.254* (1.732) -0.228*** (-4.814) -0.009 (-0.287) Included Included 42,348 0.0923 Expected Sign + + + + Full Sample -6.574*** (-23.14) 0.680** (2.510) 0.173*** (8.254) 0.081* (1.677) -0.297*** (-3.364) 0.239* (1.823) -0.147*** (-4.261) -0.043* (-1.647) Included Included 75,452 0.0870 With MNAE -6.786*** (-18.09) 0.171 (0.398) 0.189*** (8.266) -0.014 (-0.222) -0.378** (-2.233) 0.230 (1.451) -0.085* (-1.867) -0.072** (-2.102) Included Included 31,032 0.0846 24

Findings Table 5 OLS regression of AQ on |NARTA| Variable Intercept |NARTA| MKTCAP BM LEV LagROA LagROA2 CRATIO Other controls Industry dummies N Adj. R2 AQ Expected Sign + Full Sample 0.089*** (22.47) 0.146*** (16.08) -0.007*** (-25.09) -0.011*** (-9.906) -0.025*** (-14.17) -0.031*** (-6.339) 0.022*** (3.810) -0.001*** (-4.964) Included Included 54,200 0.370 Without MNAE 0.082*** (15.31) 0.181*** (14.76) -0.007*** (-31.06) -0.011*** (-10.48) -0.023*** (-10.30) -0.036*** (-6.998) 0.015*** (2.870) -0.001*** (-3.755) Included Included 29,398 0.379 With MNAE 0.094*** (216.7) 0.115*** (11.85) -0.006*** (-24.28) -0.011*** (-8.113) -0.026*** (-10.93) -0.025*** (-3.940) 0.032*** (3.651) -0.001*** (-3.347) Included Included 24,802 0.342 25

Findings Table 6 OLS regression of Audit fees on |NARTA| Variable Intercept |NARTA| SIZE BigN ROA RETURN STDRET LEV Other controls Industry dummies N Adj. R2 AUDFEE Without MNAE -6.016 (0.000) 0.641*** (5.117) 0.553*** (30.62) 0.071 (0.970) -0.555*** (-7.707) -0.045 (-1.207) -4.056 (-1.615) -0.277*** (-4.688) Included Included 15,010 0.682 Expected Sign + + + + + Full Sample -6.239 (0.000) 0.532*** (4.095) 0.598*** (41.08) 0.030 (0.405) -0.586*** (-7.297) -0.043 (-1.115) -4.674 (-1.590) -0.294*** (-6.603) Included Included 27,784 0.732 With MNAE -6.343*** (-31.30) 0.078 (0.376) 0.606*** (39.90) -0.022 (-0.265) -0.587*** (-5.614) -0.048 (-1.162) -5.338 (-1.520) -0.307*** (-5.694) Included Included 12,774 0.735 26

Findings Table 7 Probit regression of MAOs on |NARTA| Variable Intercept |NARTA| BKRPTZ SIZE AGE RETURN STDRET LEV Other controls Industry dummies N Pseudo R2 MAO Without MNAE -2.097*** (-5.300) 1.511*** (6.289) 0.275*** (4.113) 0.096*** (4.618) 0.132*** (4.284) -0.013 (-0.361) -0.231 (-0.110) 0.083 (0.791) Included Included 43,636 0.0506 Expected Sign + + + + Full Sample -2.026*** (-7.596) 1.199*** (6.832) 0.202*** (3.124) 0.105*** (5.600) 0.145*** (5.103) -0.004 (-0.127) -0.618 (-0.245) 0.160 (1.603) Included Included 76,938 0.0518 With MNAE -1.878*** (-4.602) 0.764*** (4.283) 0.104 (0.830) 0.100*** (5.388) 0.160*** (5.204) 0.006 (0.170) -1.186 (-0.364) 0.258** (2.046) Included Included 33,302 0.0487 27

Findings Table 8 Probit regression of AAERs on |NARTA| Variable Intercept |NARTA| BKRPTZ SIZE AGE RETURN STDRET LEV Other controls Industry dummies N Pseudo R2 GC Expected Sign + + + + Full Sample -1.959*** (-7.599) 1.239*** (3.665) 0.050 (0.312) -0.150*** (-5.370) 0.119** (2.534) -0.278*** (-5.536) 12.049*** (8.399) 0.721*** (3.708) Included control 27,784 0.412 Without MNAE -1.710*** (-6.794) 1.121** (2.242) 0.128 (0.773) -0.184*** (-6.453) 0.087 (1.637) -0.300*** (-4.506) 11.033*** (7.200) 0.591*** (3.128) Included control 14,992 0.417 With MNAE -2.257*** (-6.190) 1.355** (2.329) -0.110 (-0.385) -0.123*** (-3.470) 0.150** (2.340) -0.253*** (-2.843) 13.628*** (7.016) 1.020*** (2.756) Included control 12,698 0.417 28

Conclusion Absolute NARTA is positively associated with the probability of a firm receiving AAERS. Absolute NARTA is negatively associated with accruals quality. Auditors charge higher audit fees for firms with larger absolute NARTA. Auditors are more likely to issue MAOs or going- concern for firms with larger absolute NARTA. Larger absolute NARTA indicates lower financial reporting quality Auditors charge higher audit fees and/or issue MAOs to compensate for higher audit risk stemming from cash flow management as captured by NARTA. 29

Future Research Relation between absolute NARTA and properties of analyst earnings forecasts and cash flow forecasts. Relation between absolute NARTA and the cost of equity capital. 30

The End Thank You! 31