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Review of Quantitative Finance and Accounting

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29-07-2016 | Original Research

A comprehensive and quantitative internal control index: construction, validation, and impact

Authors: Hanwen Chen, Wang Dong, Hongling Han, Nan Zhou

Published in: Review of Quantitative Finance and Accounting | Issue 2/2017

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Abstract

We use a new method to better measure internal control quality. Specifically, we construct an internal control index for all public firms in China, because the lack of internal control regulations during our sample period presents an interesting setting, in which the diversity of internal control quality is preserved. Two distinctive features set our index apart from the information currently available under SOX 404 in the U.S. First, it comprehensively evaluates a firm’s internal control, based on the COSO framework. Second, it quantitatively measures a firm’s internal control, using the analytic hierarchy process designed for analyzing complex decisions. We proceed to validate our index by confirming the known relation between internal control quality and earnings management. Further, we theorize that our internal control index has a positive impact on the earnings response coefficient, and find that better internal control indeed makes financial reporting more credible to investors.

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An accelerated filer—a public firm with an equity market capitalization of more than $75 million—must comply with SOX Section 404 for its first fiscal year ending on or after November 15, 2004. A non-accelerated filer must comply with SOX 404(a) for its first fiscal year ending on or after December 15, 2007, but is exempt from complying with SOX 404(b) under Section 989G of the Dodd-Frank Act.

Based on mathematics and psychology, AHP was developed by Thomas L. Saaty in the 1970s and has been extensively used in a wide range of decision situations in fields such as government, business, industry, healthcare, and education. Vaidya and Kumar (2006) and Subramanian and Ramanathan (2012) review the applications of AHP in different settings. Subramanian and Ramanathan (2012, p. 235–236) also provide a primer on how to apply the AHP methodology in their Appendix 1. A number of AHP software packages and Excel templates are commercially available. For example, Saaty's consulting company gives access to its AHP software at http://www.superdecisions.com/.

In the same release, SEC also cites the Guidance on Assessing Control published by the Canadian Institute of Chartered Accountants (“CoCo”) and the report published by the Institute of Chartered Accountants in England & Wales Internal Control: Guidance for Directors on the Combined Code (known as the Turnbull Report) as examples of other suitable frameworks that issuers could choose in evaluating internal control effectiveness. SEC encourages companies to examine and select a framework that may be useful in their own circumstances; SEC also encourages the further development of existing and alternative frameworks.

The first three categories are contained in the 1992 original COSO report and the fourth category “safe guarding of assets” is added in the 1994 COSO addendum to the Reporting to External Parties volume of the COSO report. While specifically including “safeguarding of assets” in its ICFR definition, SEC (2003) acknowledges in Release No. 33-8238 that its ICFR definition only “encompasses the subset of internal controls addressed in the COSO Report that pertains to financial reporting objectives” and “does not encompass the elements of the COSO Report definition that relate to effectiveness and efficiency of a company's operations and a company's compliance with applicable laws and regulations.” To overcome this limitation, we follow the COSO framework to also consider “effectiveness and efficiency of operations” and “compliance with applicable laws and regulations”.

Following Wang et al. (2008) and Chen et al. (2010), we examine all firms listed on the Shanghai Stock Exchange and on the Shenzhen Stock Exchange. Note that we exclude firms listed on the Entrepreneurship Section of the Shenzhen Stock Exchange, because the Entrepreneurship Section was introduced in 2009.

Please see Kothari (2001) for a review of the ERC literature.

Dechow et al. (2010) classify earnings quality proxies into three categories: (1) properties of earnings that include earnings persistence and accruals; earnings smoothness; asymmetric timeliness and timely loss recognition; (2) investor responsiveness to earnings that includes the earnings response coefficient (ERC) or the R square from the earnings-returns model; and (3) external indicators of earnings misstatements included in Accounting and Auditing Enforcement Releases (AAERs), restatements, and internal control procedure deficiencies.

The original letter with the seal and on the official letterhead is available upon request.

Reported by the official Xinhua News Agency on March 15, 2006.

We do not include firms in the Entrepreneurship Section of the Shenzhen Stock Exchange, because the Entrepreneurship Section was introduced by the Shenzhen Stock Exchange in 2009.

ST stands for “special treatment”. When a public firm has abnormal financial or other conditions that make it hard for investors to assess its business prospects, the security exchanges will apply special treatments to this firm’s stock transactions, including (1) adding “ST” to the ticker symbol, and (2) limiting the daily stock price appreciation or depreciation to no more than 5 %.

We obtain very similar results, when we measure discretionary accruals with either the Jones Model (Jones 1991) or the performance-matched Jones Model (Kothari et al. 2005).

We use the logarithmic transformation of market value (MV) and later firm age (AGE), because the distributions for these two variables are skewed. Please see the univariate statistics for these two variables in Table 2.

Since the firm’s true value $\tilde{\mu }$ can be viewed as the net present value of all future cash flows (Teo and Wong 1993), $\frac{1}{{{\text{p}}_{\mu } }}$ is related to the uncertainty of the firm’s future cash flows (Francis and Ke 2006).

We further test alternative ERC model specifications in the literature. Following Park and Pincus (2001) and Balsam et al. (2003), we only include the interactive terms in the model; following Chan et al. (2012), we include the interactive terms and the main effect of our internal control index in the model. Our results for both specifications are very similar to the results based on Eq. (2) and reported in Table 5.

We use the three-day market-adjusted cumulative abnormal returns to be consistent with our measurement of long-term cumulative abnormal returns. Our results remain unchanged, when we use the three-day market-model adjusted cumulative abnormal returns, covering the day before, the day of, and the day after a firm’s earnings announcement. We estimate market model parameters with daily stock returns over the 250-trading-day estimation window ending twenty days before the earnings announcement. We require firms to have positive trading volumes for at least 100 days during this estimation window and eliminate those firms that fail to meet this requirement.

These CAR_L numbers are consistent with the one-year long-window CAR numbers reported for the pre-SOX 404 year in Chen et al. (2013, p. 72).

YAAHP is software for AHP, available for download from the website of Beijing Xinshengyun Software Co. (http://www.foreology.com/product/yaahp.html). Many other AHP software packages and Excel templates are commercially available. For example, Saaty's consulting company gives access to its AHP software at http://www.superdecisions.com/.

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Title: A comprehensive and quantitative internal control index: construction, validation, and impact
Authors: Hanwen Chen
Wang Dong
Hongling Han
Nan Zhou
Publication date: 29-07-2016
Publisher: Springer US
Published in: Review of Quantitative Finance and Accounting / Issue 2/2017
Print ISSN: 0924-865X
Electronic ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-016-0593-x

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