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Earnings Management, Auditor Changes and Ethics: Evidence from Companies Missing Earnings Expectations

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Abstract

Companies’ earnings are arguably their most important financial disclosure, and corporate tactics to manage earnings can be directly constrained by audit procedures. In this article, we examine whether there is a link between companies’ earnings performance and changes in the accounting firm they choose to audit their financial statements. We find that when companies’ reported earnings just miss analysts’ expectations, they are more likely to change their auditor. Consistent with an opportunistic auditor switch, we also find that these companies have lower levels of earnings quality after the change. Our results concentrate on companies with more incentive or ability to act opportunistically, including those with negative market reactions to earnings, higher levels of accruals flexibility, and weaker corporate governance. Our study advances research into the public’s interest by providing evidence of suspect auditor changes that increase auditors’ ethical conflict to maintain independence and objectivity.

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Data Availability

Data are available from public sources identified in the text.

Notes

  1. When examining metrics of financial performance, it is difficult to rule out an alternative explanation that auditor changes are driven by significant performance issues (DeFond & Subramanyam, 1998). In addition to controlling for company characteristics, we focus on companies near the earnings expectation benchmark to help us substantially reduce this concern.

  2. Detailed statements are available at https://www.sec.gov/news/statement/munter-statement-assessing-materiality-030922.

  3. Specifically, a U.S. Senate (1976) report documents the concern of possible opinion shopping of accountants. In the late 1980s, new amendments to the S-K, 8-K and 14-A disclosure requirements were made to address potential opinion shopping situations (SEC, 1988). Also, the SEC’s proposal of mandatory auditor rotation issued in August 2011 (PCAOB, 2011) was abandoned after receiving criticism that prescribed rules would increase auditor competition and stimulate clients’ opinion shopping behavior.

  4. In a sample spanning from 1993 to 1996, only 26.3 percent of firms provided auditor–client realignment reasons aside from those required by mandatory disclosure rules. Hackenbrack & Hogan, (2002) document that 43.7 percent of their sample from 1991 to 1997 report reasons for auditor changes. Chang et al., (2010)’s sample spans from 2002 to 2006 and they find that only 22 percent of their observations disclose auditor change reasons, whether voluntarily or mandatorily.

  5. Opinion shopping is first observed and documented using data from other countries such as China and the United Kingdom (e.g., Chen et al., 2016; Lennox, 2000).

  6. Managers can walk down analysts’ forecasts by providing downward-biased earnings guidance (e.g., Burgstahler & Eames, 2006; Matsumoto, 2002), exclude some specific items from non-GAAP earnings (e.g., Doyle et al., 2013), or manipulate earnings through income shifting (Barua et al., 2010), real earnings activities (e.g., Burgstahler & Eames, 2006; Graham et al., 2005), or accounting accruals (e.g., Dhaliwal et al., 2004; Gupta et al., 2016; Payne & Robb, 2000) to meet or beat analysts’ forecasts.

  7. Under Staff Accounting Bulletin (SAB) No. 99 issued by the U.S. Securities and Exchange Commission (SEC), even a small quantitative misstatement could be qualitatively material to investors when it hides managements’ failure to meet analysts’ forecasts (SEC 1999).

  8. Limited studies suggest auditors may not be fully incentivized to constrain earnings management behavior. Libby & Kinney, (2000) find that auditors are likely to make concessions on subjective matters. Brown-Liburd et al., (2013) provide evidence that auditors are insensitive to accounting decisions impacting market expectations.

  9. Some companies that meet or far exceed earnings expectations may not perceive their auditor to be a constraint since they have met expectations and are less likely to employ accrual earnings management tactics because they do not require them. In addition, companies that miss expectations by a large margin may lack the ability to employ such tactics since the costs of earnings management increase as the missed amount increases (Burgstahler & Eames 2006). In our additional analyses we test a restricted sample of only just miss and just meet companies and find our results hold.

  10. Although I/B/E/S does not cover all Compustat companies, it includes over 80 percent of the total assets and profits of the Compustat population (Davis et al., 2007) and is considered representative.

  11. Consistent with prior research (Bhojraj et al., 2009; Dhaliwal et al., 2004; Frankel et al., 2002; Gupta et al., 2016), we use summary forecasts as our earnings benchmark because most companies use them in their press releases to evaluate performance and they are visible to the market.

  12. We use a GEE model because it allows us to account for various types of autocorrelation (Gardiner et al., 2009). The Huber sandwich style estimator of variance is used to account for heteroscedasticity. Taken together, the standard errors produced are HAC (heteroscedasticity-autocorrelation consistent).

  13. As described in model (1), we measure all the control variables as of year t.

  14. We obtain these measures using data from BoardEx and Thomson Reuters. Shareholders rights (G-Index) developed by Gompers et al., (2003) is used as a sixth measure in the DeFond et al., (2005) index but is not sufficiently available for our sample period.

  15. Standard errors are clustered by year.

  16. Beginning with our full sample of 19,210 company-year observations from Table 1, our sample is reduced to 18,098 due to data availability to estimate the variables of model (2).

  17. Control variable estimates are in line with our expectations. We observe a smaller magnitude of discretionary accruals (DA) for larger or older companies (SIZE and AGE), companies with higher book to market ratios (BTM), companies with higher institutional ownership (INT_OWN), and companies that record lower accruals in the past year (LAG_ACC). Companies with more sales growth (SALES_G), companies that report a loss (LOSS), and companies that are important to their auditor (IMP) report higher DA.

  18. According to Benford’s Law, if a firm does not manipulate earnings, then the occurrences of the first digits of numbers (e.g., 1–9) of their financial statement line items should follow a certain distribution. FSD, simply put, captures the divergence of a firm’s financial statement from such expected distribution (Amiram et al., 2015).

  19. We refrain from controlling for these variables in our main results as they significantly reduce sample size.

  20. Our first stage determinant variables include return on assets, leverage, firm size, market-to-book ratio, the log audit fees, operating cash flows, Altman-z score, auditor tenure, institutional investor ownership, prior period meeting or beating earnings expectations, BigN auditor, the log of firm age, research and development expenses, positive seasonal change in earnings, the log of firms’ shares outstanding, labor intensity, the number of previous four quarters with negative earnings, the number of days between the fiscal year end and the earnings announcement, if the firm is in a litigation industry, macro-economic growth, and if the firm is included in the S&P 500 index (e.g., Filzen & Peterson, 2015; Huang et al., 2017).

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Correspondence to Eric Lohwasser.

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Appendix: variable definitions

Appendix: variable definitions

Variables

Definition

AC_SIZE

The number of audit committee members divided by the number of directors

AC_IND

An indicator variable coded 1 if all audit committee members are independent, and 0 otherwise

ACC

Net income less operating cash flows, net of cash flows for discontinued operations scaled by lagged total assets

ACC_FLEX

The ratio of net operating assets to sales at the beginning of the year, scaled by industry-year median

ACQ

Cash flows for acquisitions scaled by average total assets

AGE

The natural log of firm age

ALTMAN

Altman is calculated as:\(\begin{aligned} AltmanZ = & 3.3 \times \frac{{Net\, Income}}{{Total\, Assets}} + 0.99 \times \frac{{Sales}}{{Total\, Assets}} \\ & + 0.6 \times \frac{{Market\, Value}}{{Total\, Liabilities}} + 1.2 \times \frac{{Curent\, Assets}}{{Total\, Assets}} \\ & + 1.4 \times \frac{{Retained\, Earnings}}{{Total\, Assets}} \\ \end{aligned}\)

AUD_CHG

An indicator variable coded 1 if the client changes its auditor within one year of the earnings announcement date, and 0 otherwise

BD_IND

An indicator variable coded 1 if 60% or more of the directors are independent, and 0 otherwise (Consistent with DeFond et al., (2005))

BD_SIZE

The number of directors on the board

BTM

The ratio of the book value to its market value of equity

CASH

Cash and cash equivalents scaled by lagged total assets

CAR

Accumulated market-adjusted stock returns for the (− 1, 1) window around the earnings announcement date

CEOCFO_CHG

An indicator variable coded 1 if the company changed their CEO and/or CFO

DA

The absolute value of performance-matched discretionary accruals. Discretionary accruals are estimated as the residuals from the Jones (1991) model and performance adjusted based on the return on assets (Kothari et al., (2005)

DOWN

An indicator variable coded 1 if the client switches from a BigN auditor to a non-BigN auditor, and 0 otherwise

FEE

The natural log of total audit fees

FSD

Financial statement divergence is calculated as: \({\sum }_{1}^{9}(|AFi-EFi|)/9*100,\) where i = 1, 2, 3…9, and AF (EF) is the actual (expected) frequency of the first digit i from the financial statement items. If an item is smaller than one, then the next non-zero value after the decimal will be used as the first digit

GC

An indicator variable coded 1 if the company received a going-concern opinion, and 0 otherwise

GOV

Modified corporate governance index used in DeFond et al. (2005)

HERF

Herfindahl index capturing the variation in the number of audit firms present in a given market, as well as the distribution of audit fees across those firms. The sum of the squared audit fee market shares of all auditors in an MSA

IMP

The importance of the client to the auditor measured as the percentage of total audit fee revenue collected from the auditor’s client portfolio

INV_AR

Inventory plus receivables divided by total assets

ISSUE

The sum of debt or equity issued during the past three years scaled by total assets

JUST_MISS

An indicator variable coded 1 if actual earnings per share minus consensus analysts’ forecasted earnings per share falls within the range of [− 0.01, 0], and 0 otherwise

LAG_ACC

Total accruals in the prior year scaled by total assets

LEVERAGE

Total short-term and long-term debt scaled by total assets

LOSS

An indicator variable coded 1 if the company reported a loss, and 0 otherwise

MEET_OR_BEAT

An indicator variable coded 1 if earnings per share minus consensus analysts’ forecasted earnings per is greater than or equal to zero, and 0 otherwise

PSEUDO_MISS_FIRM

A pseudo just miss variable produced through random firm assignment using the quantity of just miss observations within the same industry-year

PSEUDO_MISS_IND

A pseudo just miss variable produced through random year assignment using the quantity of just miss observations within the same firm

RESTATE

An indicator variable coded 1 if the client announced a restatement during the prior-year to current-year earnings announcement date range, and 0 otherwise

RESTRUCTURE

An indicator variable coded 1 if restructuring costs are present, and zero otherwise

ROA

Net income before extraordinary items divided by total assets

SALE_G

Percentage change in sales from the prior year

SD_CASH

Volatility of cash flows calculated as the standard deviation of the operating cash flows in the last five years

SIZE

The natural log of total assets

TENURE

An indicator variable coded 1 if the current auditor has audited the company for more than five years, and 0 otherwise

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Lohwasser, E., Zhou, Y. Earnings Management, Auditor Changes and Ethics: Evidence from Companies Missing Earnings Expectations. J Bus Ethics 191, 551–570 (2024). https://doi.org/10.1007/s10551-023-05453-6

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