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Internal control material weakness, analysts’ accuracy and bias, and brokerage reputation

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Abstract

The main purpose of this paper is to examine the impact of internal control material weaknesses (ICMW hereafter) on sell side analysts. We find that ICMW reporting firms have less accurate analyst forecasts relative to non-reporting firms when the reported ICMWs belong to the Pervasive type. ICMW reporting firms have more optimistically biased analyst forecasts compared than non-reporting firms. The optimistic bias exists only in the forecasts issued by the analysts affiliated with less-highly-reputable brokerage houses. The differences in accuracy and bias between ICMW and non-ICMW firms disappear when ICMW disclosing firms stop disclosing ICMWs. Collectively, our results suggest that the weaknesses in internal control increases forecasting errors and upward bias for financial analysts. However, a good brokerage reputation can curb the optimistic bias.

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Notes

  1. Key points of Section 302 include: (1) The signing officers must certify that they are responsible for establishing and maintaining internal control and have designed such internal controls to ensure that material information relating to the registrants and its consolidated subsidiaries is made known to such officers by others within those entities, particularly during the period in which the periodic reports are being prepared. (2) The officers must “have evaluated the effectiveness of the registrant’ internal controls as of a date within 90 days prior to the report and have presented in the report their conclusions about the effectiveness of their internal controls based on their evaluation as of that date.

  2. Key points of Section 404 include: (1) Management is required to produce an internal control report as part of each annual Exchange Act report. (2) The report must affirm the responsibility of management for establishing and maintaining an adequate internal control structure and procedures for financial reporting. (3) The report must also contain an assessment, as of the end of the most recent fiscal year of the registrant, of the effectiveness of the internal control structure and procedures of the issuer for financial reporting. (4) External auditors are required to issue an opinion on whether effective internal control over financial reporting was maintained in all material respects by management. This is in addition to the financial statement opinion regarding the accuracy of the financial statements.

  3. For example, Donald J. Peters, a portfolio manager at T. Rowe Price Group, says: "The accounting reforms [of SOX] have been a win. It is [now] much easier for financial statement users to have a view of the true economics" of a company (Wall Street Journal, January 29th, 2007).

  4. A recent working paper by Kim et al. (2009) confirms our results. They find that internal control quality is inversely associated with analysts’ error and forecast dispersion.

  5. For example, Dyntek Inc. disclosed the following deficiencies in their 2004, 10-K: The material weaknesses that we have identified relate to the fact that our overall financial reporting structure and current staffing levels are not sufficient to support the complexity of our financial reporting requirements. We have experienced employee turnover in our accounting department including the position of Chief Financial Officer. As a result, we have experienced difficulty with respect to our ability to record, process and summarize all of the information that we need to close our books and records on a timely basis and deliver our reports to the Securities and Exchange Commission within the time frames required under the Commission's rules.”

  6. For example, Westmoreland Coal Inc. disclosed the following deficiencies in their 2005, 10-K: “The company’s policies and procedures regarding coal sales contracts with its customers did not provide for a sufficiently detailed, periodic management review of the accounting for payments received. This material weakness resulted in a material overstatement of coal revenues and an overstatement of amortization of capitalized asset retirement costs”. Moody’s suggests that these types of material weaknesses are “auditable,” and thus do not represent as serious a concern regarding the reliability of the financial statements.

  7. The detailed classification of Pervasive and Contained ICMWs is provided in “Appendix 1”.

  8. The conclusions of this paper remain the same if we classify G2 firms as firms disclosing only Pervasive ICMWs.

  9. Our sample period starts after the introduction of Regulation Fair Disclosure (Reg. FD). The goal of Reg. FD is to prohibit management from selectively disclosing private information to analysts. However, as pointed out by recent research (see for example, Ke and Yu 2006; Kanagaretnam et al. 2004), there is no empirical evidence of management relations incentive weakening after Reg. FD. In the post-Reg. FD period, there are other incentives for analysts to please management, such as to gain favored participation in conference calls (Libby et al. 2008; Mayew 2008). Anecdotal evidence also shows that Reg. FD does not prevent a company from more subtle forms of retaliations against analysts who issue negative research reports (Solomon and Frank 2003).

  10. Note that our hypothesis is still valid if the forecasts have been made before the disclosure of ICMWs. Doyle et al. (2007a) argue that Sarbanes–Oxley has led to the disclosure of ICMWs that might have existed for some time. Indeed, they find that accrual quality has been lower for ICMW firms relative to non-ICMW firms even in the periods prior to the disclosure of ICMWs.

  11. Brown et al. (2009) document stock market responds to an analyst’s recommendation change and the difference between the analyst’s recommendation and the consensus recommendation. The market’s reaction is strongly influenced by the analyst’s reputation.

  12. It could be argued that our sample might miss some firms which have ICMWs but choose not to disclose them. However, discovery and disclosure of material weaknesses are mandatory according to 2004 SEC FAQ #11. We, therefore, use the disclosure of ICMW as a proxy for the existence of ICMW.

  13. We thank Sarah McVay for making the data available on her website (http://pages.stern.nyu.edu/~smcvay/research/Index.html).

  14. If a firm in our final sample reports internal material weaknesses in multiple years, the firm will show up in our sample multiple times. We have 599 distinct firms showing up once in our final sample and 64 firms showing up twice in our sample. The conclusions of this paper remain the same if we exclude these 64 firms from our analyses.

  15. Note that the ACCURACY is defined so that larger errors correspond to a lower level of accuracy.

  16. As a sensitivity test, we calculate ACCURACY and BIAS using the simple average of the measures across the 6 or 12 monthly reporting periods on the IBES before the company’s fiscal year end. In other words, we choose all median forecasts across the six or twelve monthly reporting periods on IBES before the company’s fiscal year end, and then average the median forecasts to create our ACCURACY and BIAS variables. The results are similar to what we report in this paper (not tabulated). When we use forecasts from the prior year instead of the current year, we also get similar results (not tabulated).

  17. Note that the differences in the earnings quality could also be the consequences of the existence of ICMWs. By controlling for absolute abnormal accruals, we may over-control the impact of ICMWs. But it will bias against us finding any results.

  18. Fan and Yeh (2006) find that forecasting error is a negative function of firm size.

  19. The results are similar if we use value-weighted market adjusted cumulative returns.

  20. We thank an anonymous referee for pointing this out to us.

  21. When we use forecasts from the prior year instead of the current year, we also get similar results (not tabulated).

  22. We exclude earnings volatility (EPSVOL) variable because the variable is significantly correlated with SKEW variable. In a sensitivity test, we replace SKEW by EPSVOL, the results are similar to what we report in the paper.

  23. See Shiller (1997) on anchoring behavior of financial analysts.

  24. For firms that disclose ICMWs for multiple years, the last year in which ICMWs are disclosed for the firms in our sample period is used.

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Acknowledgments

Li Xu gratefully acknowledges the financial support from Southern Illinois University at Carbondale. Alex P. Tang gratefully acknowledges that this research is supported in part by a summer research grant from the School of Business and Management at the Morgan State University. We appreciate the comments from two anonymous referees and the editor, Cheng-Few Lee. We also appreciate the research assistance of Jui-Chin Chang. All errors are our own.

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Authors and Affiliations

  1. School of Accountancy, Southern Illinois University Carbondale, 1025 Lincoln Drive, Carbondale, IL, 62901, USA

    Li Xu

  2. Department of Accounting and Finance, Morgan State University, Baltimore, MD, 21251, USA

    Alex P. Tang

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  1. Li Xu
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Correspondence to Li Xu.

Appendices

Appendix 1: Material weakness classification examples

1.1 G1: Contained material weaknesses

  1. 1.

    Account-specific

E.g., “U.S. Cellular did not maintain effective controls over the completeness, accuracy, presentation and disclosure of its accounting for income taxes.”(U.S. Cellular Inc., 2004 10-K report)

  1. 2.

    Period-end reporting/accounting policies

E.g., “–a lack of an ongoing formal self-assessment process related to internal control over financial reporting.” (Ivanhoe energy Inc., 2004 10-K report)

  1. 3.

    Revenue recognition

E.g., “The Company’s policies and procedures regarding coal sales contracts with its customers did not provide for a sufficiently detailed, periodic management review of the accounting for payments received. This material weakness resulted in a material overstatement of coal revenues and an overstatement of amortization of capitalized asset retirement costs.” (Westmoreland Coal Co., 2005 10-K report)

  1. 4.

    Account reconciliation

E.g., “The Company did not maintain effective controls over reconciliations of certain financial statement accounts.” (SIRVA Inc., 2004 10-K report)

1.2 G2: Pervasive material weaknesses

  1. 1.

    Segregation of duties

E.g., “Inadequate segregation of duties was noted with respect to the revenue, expenditure and payroll processes as numerous incompatible tasks are performed by the same accounting personnel.” (Versant Co., 2004 10-K report).

  1. 2.

    Subsidiary-specific

E.g., “We have reported to the SEC that one of our foreign subsidiaries operating in Nigeria made improper payments of approximately $2.4 million to an entity owned by a Nigerian national who held himself out as a tax consultant when in fact he was an employee of a local tax authority. The payments were made to obtain favorable tax treatment and clearly violated our Code of Business Conduct and our internal control procedures.” (Halliburton Co., 2002 10-K report)

  1. 3.

    Senior management

E.g., “management did not set a culture that extended the necessary rigor and commitment to internal control over financial reporting.” (SIRVA Inc, 2004 10-K report)

  1. 4.

    Technology issues

E.g., “There are weaknesses in the Company’s information technology (“IT”) controls which makes the Company’s financial data vulnerable to error or fraud; a lack of documentation regarding the roles and responsibilities of the IT function; lack of security management and monitoring and inadequate segregation of duties involving IT functions.” (Earthshell Co., 2005 10-K report)

  1. 5.

    Training and personnel:

E.g., “The Company lacks personnel with adequate expertise in accounting for income taxes in accordance with U.S. GAAP.” (Westmoreland Coal Co., 2005 10-K report)

Appendix 2: Variable definitions

 

Variables

Definition and data source

NUMBER

NUM

The number of analysts who make the forecasts in calculating the last median earnings

Natural logarithm of the number of analysts who make the forecasts in calculating the last median earnings

SKEW

The skewness of the earnings, calculated as the mean-median difference of price-scaled earnings from the prior five years (minimum of four years)

SPECIAL

An indicator variable equal to one if special items (Compustat # 17) are not equal to zero, zero otherwise

RET

Is the equally weighted market adjusted cumulative return over the past three years

DA

The absolute value of abnormal total accruals. The calculation of DA is estimated using the modified Jones model of Larcker, Richardson and Tuna (2007)

LOSS

An indicator variable equal to one if earnings are negative, zero otherwise

ECHG

Is the change in earnings (Compustat #18), calculated as the change in earnings over the previous year scaled by the previous year’s earnings

NECHG

Is equal to one if ECHG is negative and zero otherwise

ABSECHG

The absolute change in earnings (Compustat #18), calculated as the absolute value of the change in earnings over the previous year scaled by the previous year’s earnings

EPSVOL

The standard deviation of earnings before extraordinary items (Compustat #18) estimated using data from the prior 5 years (minimum of 4 years)

BM

The natural logarithm of book value (Compustat # 60) to the market (Compustat # 25* Compustat #199) of the firms

ROA

The ratio of return to asset, calculated as earnings before extraordinary items (Compustat #18) scaled by average total assets (Compustat # 6)

LEV

The ratio of debt (Compustat # 34 + Compustat # 9) to averaged total assets (Compustat # 6)

MV

Natural logarithm of the market value of equity (Compustat #199*#25)

FOREIGN

An indicator variable equal to one if foreign currency translation (COMPUSTAT Data Item #150) is not zero, zero otherwise

G1

An indicator variable that equals one if a firm discloses only Contained ICMWs in year t, and zero otherwise

G2

An indicator variable equal to one if a firm discloses Pervasive ICMWs in year t, and zero otherwise

ICMW

An indicator variable equal to one if the firm has disclosed internal control material weakness in year t, and zero otherwise

STALE

The days between the date of fiscal year end and the date of the last annual forecast issued (before the fiscal year end) by an analyst

ADJSTALE

The median value of the STALE variable for a firm per fiscal year

AGE

The number of years that a firm has been the CRSP database

BROKERAGE REPUTATION

The Institutional Investors’ ranking of brokerage houses is used to proxy for brokerage reputation: a brokerage is considered to be of high reputation if it is consistently (at least for three prior years) ranked among the “Leaders” by Institutional Investors during the sample period. The following twelve brokers are identified as highly reputable: Bear, Stearns & Co; CS First Boston; Goldman Sachs; Lehman Brothers; Donaldson, Lufkin & Jenrette; J.P. Morgan Securities; Merrill Lynch; Morgan Stanley & Co; Paine Webber; Prudential Securities; Salomon Brothers; Smith Barney. The other brokerages are classified as less-highly-reputable

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Xu, L., Tang, A.P. Internal control material weakness, analysts’ accuracy and bias, and brokerage reputation. Rev Quant Finan Acc 39, 27–53 (2012). https://doi.org/10.1007/s11156-011-0243-2

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