- Email: [email protected]
Fair value and economic consequences of financial restatements
Finance Research Letters xxx (xxxx) xxx–xxx
Contents lists available at ScienceDirect
Finance Research Letters journal homepage: www.elsevier.com/locate/frl
Fair value and economic consequences of financial restatements Hua-Wei Solomon Huanga, Zhi-Yuan Andy Fengb, Angie Abdel Zaherc,
⁎
a
National Cheng Kung University, Tainan, Taiwan National Sun Yat-sen University, Kaohsiung, Taiwan c American University In Cairo, New Cairo, Egypt b
ARTICLE INFO
ABSTRACT
Keywords: SFAS No. 157 Financial restatements Market reactions Financial crisis
This study finds that negative market reactions to restatement announcements are more severe when firms disclose higher ratios of Level 3 fair values. In addition, this negative association is stronger during financial crisis periods, showing that market investors prefer conservative fair values.
1. Introduction Statement of Financial Accounting Standards No. 157, Fair Value Measurements (SFAS No. 157) outlined three levels of fair value measurements for financial assets and liabilities.1 Among the three levels, Level 3 (1) inputs are clearly subject to more (less) serious information asymmetry problems between managers and users of financial statements. Thus, corporate managers are likely to utilize managerial discretion over the inputs used to measure fair values that could induce opportunistic activities, and in turn impair financial reporting fairness. This is supported by empirical evidence provided by Lin et al. (2017) who finds that “…firms with higher ratios of Level 3 fair value assets to total assets are more likely to subsequently restate their financial statements…that use of less reliable (Level 3) fair value measurements may reduce financial reporting quality (p. 01)”. This study extends Lin et al. (2017) and further investigates the effect of fair value accounting on the market reaction of financial restatements to observe how market participants respond to restatement announcements associated with firms that report Level 3 fair values. Since Level 3 fair values may contain serious measurement errors and induce managerial manipulation, this paper predicts the market will penalize firms with restatements having higher Level 3 fair values. We also examine the sensitivity of the market during and after the crisis period. This study contributes to the literature in several ways. First, it provides relevant evidence that Level 3 measurements are vulnerable to subjective manipulation, thus suggesting that additional supporting disclosures are required. Such disclosures can prevent managers from misleading the users of financial statements. Second, investors and financial analysts can use Level 3 fair values as financial risk indicators when making investment decisions. This provides incremental information for investors to value the companies and avoid fraudulent financial reporting. Finally, because some board members, especially the audit committee directors, have the authority and responsibility to remediate internal control weaknesses and select/appoint/dismiss the incumbent auditor of We thank the participants in the International Conference of Innovation and Management 2018 in Fukuoka, Japan, and Workshops at National Cheng Kung University for their helpful comments on this paper. ⁎ Corresponding author. E-mail address: [email protected] (A.A. Zaher). 1 Level 1 includes observable inputs from quoted market prices in active markets for identical assets or liabilities. Level 2 consists of observable inputs from quoted market prices in active markets for similar assets or liabilities, quoted market prices for identical or similar assets or liabilities in inactive markets, and other market-corroborated inputs. Level 3 represents unobservable, firm-generated inputs. https://doi.org/10.1016/j.frl.2019.07.017 Received 24 January 2019; Received in revised form 31 May 2019; Accepted 27 July 2019 1544-6123/ © 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Hua-Wei Solomon Huang, Zhi-Yuan Andy Feng and Angie Abdel Zaher, Finance Research Letters, https://doi.org/10.1016/j.frl.2019.07.017
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the company, corporate boards may strengthen their governance and select better auditors by hiring high quality directors in order to develop more reliable Level 3 fair values. 2. Literature and hypothesis development 2.1. Literature There is a research stream examining market reaction to restatement announcements (e.g., Dechow et al., 1996; Palmrose et al., 2004; Files et al., 2009; Nguyen and Puri, 2014). Regulators and market investors view restatement announcements as bad news because they are usually related to weak internal controls and earnings manipulation. Prior literature consistently showed negative market reactions to restatement announcements. Palmrose et al. (2004) and Nguyen and Puri (2014) found significant negative abnormal returns two days after restatement announcements for 403 restatement announcements released from 1995 to 1999. Files et al. (2009) found negative market reactions to all locations where restatements are disclosed (i.e., in a headline, with a headline on a different subject, or in a footnote to operating results). The enactment of the Sarbanes–Oxley Act (SOX) in 2002 has improved investor perceptions regarding the reliability and timeliness of financial disclosures provided by restated firms. Hranaiova and Byers (2007) compared restatement announcements in the pre- and post-SOX periods and found that the average negative (positive) cumulative abnormal return is lower by 71 (33) percent post-SOX. Furthermore, the market is less sensitive when this information is disclosed obscurely (Files et al., 2009). However, few papers focused specifically on the impact of Level 3 fair values on restatement announcements. 2.2. Hypothesis development Cannon and Bedard (2017) indicated that fair values “…have high estimation uncertainty, high subjectivity, significant/complex assumptions, and multiple valuation techniques”. Lin et al. (2017) found that firms with higher Level 3 fair values are more likely to report financial restatements. As an extension, this study explores incremental effects of Level 3 fair values on market reactions to restatement announcements. Because Level 3 fair values are more easily manipulated by managers engaging in opportunistic activities, including intentional financial statement frauds, market investors may have stronger reactions to firms reporting higher Level 3 fair values. Hence, the following hypothesis is proposed: H. The negative market reaction to financial restatement will be higher for firms reporting higher Level 3 fair values. 3. Data and method Firstly, we identify 2837 restatement firm-year observations with fair value data in Compustat during the years 2008–2017.2 Our sample overlaps with the 2008 financial crisis period, considered to be the worst period since the Great Depression which simulated instability around the globe. Among the 2837 restatements, 1344, 99, and 1394 restatements were initiated by management (47.4%), SEC (3.5%), and auditors (49.1%), respectively. Building on Palmrose et al. (2004) and Files et al. (2009), the following OLS regression model is expended to investigate the market reaction to restatement announcements when firms disclose different levels of fair values.
CAR = + 1 FRAUD + 2 AUD _LETTER + 3 SEC _INVEST + 4 CORE _ACC+ 5 CHANGE _NI _TA + 6 YEARS _RES + 7 SIZE + 8 ICW + 9 ACCRUALS + 10 ROA+ 11 EVENT + 12 INSIDER% + 13 BLOCKHO% + 14 PRIOR _RETURN + 15 17 FVA _VARS+ Year + Industry +
(1)
where: CAR = Cumulative abnormal market returns (CAR) during a period of time. Two event windows of three-days (−1 to +1) and six days (−1 to +5) around the restatement FRAUD = 1 if fraud-related restatements are reported on AuditAnalytics, 0 otherwise AUD_LETTER = 1 if restatements are attributed to auditors SEC_INVEST = 1 if restatements are attributed to SEC investigations announcements are used.3 CORE_ACC = 1 if core accounts are affected by the restatement CHANGE_NI_TA = change in net income over total assets affected by the restatements YEARS_RES = number of years restated SIZE = natural logarithm of total assets ICW = 1 if the company reports material internal control weakness in the SOX 404 report 2 Level 3 fair value data became available after (including) 2008. Our test period overlaps with the financial crisis because the effect of Level 3 fair values on restatements may be especially profound when the sluggish economy exacerbates the liquidity of certain financial instruments. 3 The two windows are very conventional. One trading day before the event day is used to measure the effect due to potential information leakage of this disclosure. One trading day or five trading days after the event day is used to measure the effect of this disclosure in one day or one week.
2
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Table 1 Descriptive data of restatements (N = 732).
Mean Median Mean Median
CAR (−1, +1)
CAR (−1, +5)
FVA1_TA
FVA2_TA
FVA3_TA
FRAUD
AUD_LETTER
SEC_INVEST
CORE_ACC
PRIOR_RETURN
−1.11% −0.31% CHANGE_NI_TA −0.03% 0.00%
−0.99% −0.29% YEARS_RES 2.29 1.95
0.06 0.00 SIZE 21.07 21.01
0.07 0.00 ICW 0.15 0.00
0.01 0.00 ACCRUALS −0.46 −0.04
0.02 0.00 ROA −0.04 0.01
0.47 0.00 EVENT 0.16 0.00
0.04 0.00 INSIDER% 2.68% 0.00%
0.34 0.00 BLOCKHO% 33.46% 33.76%
3.98% 1.67%
ACCRUALS = discretionary accruals (Kothari et al., 2005) ROA = return on assets EVENT = 1 if there is any significant event or litigation case against the company during the period of event days, otherwise 0 (Wall Street Journal and Stanford Law School Database) INSIDER% = percentage of stock held by all directors on the board based on BoardEX BLOCKHO% = percentage of stock held by block-holders on Corporate Library PRIOR_RETURN = Changes in stock price over 120 days prior to the restatement announcement (Palmrose et al., 2004) FVA_VARS represents the proportions of level 1, 2, and 3 fair value assets held by the company, including: FVAx_TA = Level x fair values of financial assets divided by total assets Similar to Palmrose et al. (2004), we control for firm complexity using SIZE, for firm performance using ROA, for recent stock performance using PRIOR_RETURN, and for signals of restatement from outside parties using AUD_LETTER and SEC_INVEST. We also control for FRAUD due to the increased threat of litigation. Materiality of restatement is controlled using CORE_ACC, CHANGE_NI_TA, and YEARS_RES (Palmrose et al., 2004). Both the impact of internal control strength (ICW) and earnings management (ACCRUALS) are included. We use INSIDER% and BLOCKHO% to control for the influence of insiders and block holders. Finally, we include year and industry dummy variables to control for year and industry fixed effects. After deleting observations with missing financial data in the BoardEX/Corporate Library (1112) and matching with CRSP/ EVENTUS (993), our sample size is reduced to 732 observations. Table 1 provides the descriptive statistics. The mean CAR using both windows is significantly negative, consistent with previous studies (Palmrose et al., 2004). Also, the mean values of FVA1_TA, FVA2_TA, and FVA3_TA are 0.06, 0.07, and 0.01, respectively, which are close to the values of FVA1_TA, FVA2_TA, and FVA3_TA (0.09, 0.07, and 0.02), respectively, reported in Lin et al. (2017). Likewise, the average values of SIZE, ICW, ACCRUALS, and ROA are 21.07, 0.15, −0.46, and −0.04, respectively, which are similar as those reported in Lin et al. (2017). Finally, there are 16% sample firms with events and 47% or 4% restatements attributed by auditors or SEC, respectively. The mean (median) ratio of Table 2 Regression of CAR, restatements, and fair values. Variables
Sign
(−1, +1) CAR Coefficient
Constant FVA1_TA FVA2_TA FVA3_TA FRAUD AUD_LETTER SEC_INVEST CORE_ACC CHANGE_NI_TA YEARS_RES SIZE ICW ACCRUALS ROA EVENT INSIDER% BLOCKHO% PRIOR_RETURN Year Industry R2 N Coefficient comparisons FVA1_TA=FVA2_TA FVA1_TA=FVA3_TA FVA2_TA=FVA3_TA
? + + – – – – – + – ? – – + – ? ? +
0.0146 0.0428 0.0267 −0.1837 −0.0076 −0.0121 0.0128 0.0052 0.0727 −0.0038 0.0009 −0.0214 −0.0004 0.0061 −0.0283 −0.0050 −0.0293 −0.0001 Yes Yes 16.51% 732 p-value 0.23 20.38 15.92
F-stat
p-value 0.815 0.024 0.304 0.000 0.739 0.073 0.436 0.449 0.460 0.070 0.689 0.018 0.682 0.631 0.001 0.897 0.461 0.979
F-stat 0.630 <0.0001 <0.0001
3
(−1, +5) CAR Coefficient 0.0160 0.0870 0.0147 −0.2329 −0.0026 −0.0171 0.0376 0.0044 −0.0596 −0.0025 0.0009 −0.0336 −0.0004 −0.0050 −0.0386 −0.0028 −0.0193 0.0055 Yes Yes 16.00% 732 p-value 3.01 26.33 14.29
p-value 0.837 0.000 0.649 0.000 0.926 0.041 0.065 0.600 0.626 0.345 0.753 0.003 0.750 0.752 0.000 0.953 0.697 0.329
0.084 <0.0001 0.0002
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Table 3 Impact of financial crisis. Variables
Sign
(−1, +1) CAR Coefficient
FVA1_TA FVA2_TA FVA3_TA Crisis FVA1_TA × Crisis FVA2_TA × Crisis FVA3_TA × Crisis Control Year Industry
+ + – –
0.0229 0.0140 −0.0666 −0.0287 0.0192 0.0485 −0.2637 Yes Yes Yes
R2 N
p-value 0.533 0.613 0.275 0.280 0.644 0.380 0.005
17.70% 732
(−1, +5) CAR Coefficient 0.0536 0.0103 −0.0326 −0.0210 0.0421 −0.0117 −0.4620 Yes Yes Yes
p-value 0.237 0.764 0.666 0.523 0.412 0.864 0.000
18.10% 732
PRIOR_RETURN is 3.98 (1.67)%, showing positive trends for stock prices before the event date windows. Table 2 reports the OLS regression results. Multicollinearity should not be an issue since all VIFs are less than 10.0. Firstly, the coefficients of FVA1_TA on CAR (−1, +1) and CAR (−1, +5) are both positive and significant (p-value < 0.050 and < 0.010), showing that negative market reactions to the restatements of high values of Level 1 assets are less than the restatements of low values of Level 1 assets because those firms should have less information asymmetry between managers and financial statement users. Next, FVA3_TA is significantly negative in both test windows (at p-value < 0.010). This finding shows that, in general, Level 3 fair values increase the negative abnormal returns around the restatement announcements. Market participants appear to penalize firms reporting Level 3 fair values. We compare the slope coefficients for Level 1, Level 2, and Level 3 fair values. The coefficients of Level 3 fair values are significantly lower (p-values < 0.100 for both windows). As for the control variables, AUD_LETTER and ICW are negatively associated with CAR, indicating that restatements attributed to auditors and poor internal controls result in more negative market responses. In addition, YEARS_RES and EVENT also show significantly negative impacts (Palmrose et al., 2004). In the additional analyses, we investigate whether the stock market reactions to restatements are different during the crises and non-crises periods. We define the crisis dummy coded as 1 if the observations fall within 2008 to 2010, and otherwise 0, and then interact this crisis dummy with FVA1_TA, FVA2_TA, and FVA3_TA, respectively. In Table 3, the interaction items FVA3_TA × Crisis for the two event windows are both negative and significant (p-values < 0.010). This indicates that the negative market reactions to restatements with high Level 3 fair values are stronger during the crises period, showing that the market investors prefer conservative fair values during the financial crisis. 4. Conclusion This study analyzes the effect of Level 3 value disclosures on market reaction. We find that restated firms experience a significantly negative stock price reaction. Our results also indicate that the use of less reliable fair values such as Level 3 values is likely to result in restatements, which triggers further damage to stock prices. These findings are of importance to regulators, investors, and auditors in the US. Such Level 3 disclosures are a determinant behind firm restatements and play a key part in how the market reacts. Limitations of our study include potential biases since our sample eliminated some observations due to missing BoardEX/ Corporate Library/CRSP/EVENTUS data. Further, we acknowledge that there may still be uncaptured effects of missing confounding events. Acknowledgment Hua-Wei Huang gratefully acknowledges the National Science Council, Taiwan, ROC, for support of this work under contract (NSC 100-2410-H-006-102). Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.frl.2019.07.017. References Cannon, N.H., Bedard, J.C., 2017. Auditing challenging fair value measurements: evidence from the field. Account. Rev. 92 (4), 81–114. Dechow, P.M., Sloan, R.G., Sweeney, A.P., 1996. Causes and consequences of earnings manipulation: an analysis of firms subject to enforcement actions by the SEC. Contempor. Account. Res. 13, 1–36. Files, R., Swanson, E.P., Tse, S., 2009. Stealth disclosure of accounting restatements. Account. Rev. 84 (5), 1495–1521. Hranaiova, J., Byers, S.L., 2007. Changes in market responses to financial statement restatement announcements in the Sarbanes-Oxley Era. . Available at SSRN:
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https://www.ssrn.com/abstract=1319354. Kothari, S.P., Leone, A.J., Wasley, C.E., 2005. Performance matched discretionary accrual measures. J. Account. Econ. 39 (1), 163–197. Lin, Y.H., Lin, S., Fornaro, J.M., Huang, H.W., 2017. Fair value measurement and accounting restatements. Adv. Account. 38, 30–45. Nguyen, D., Puri, T.N., 2014. Information asymmetry and accounting restatement: NYSE-AMEX and NASDAQ evidence. Rev. Quant. Finance Account 43, 211–244. Palmrose, Z.V., Richardson, V.J., Scholz, S., 2004. Determinants of market reactions to restatement announcements. J. Account. Econ. 37 (1), 59–89.
5
Contents lists available at ScienceDirect
Finance Research Letters journal homepage: www.elsevier.com/locate/frl
Fair value and economic consequences of financial restatements Hua-Wei Solomon Huanga, Zhi-Yuan Andy Fengb, Angie Abdel Zaherc,
⁎
a
National Cheng Kung University, Tainan, Taiwan National Sun Yat-sen University, Kaohsiung, Taiwan c American University In Cairo, New Cairo, Egypt b
ARTICLE INFO
ABSTRACT
Keywords: SFAS No. 157 Financial restatements Market reactions Financial crisis
This study finds that negative market reactions to restatement announcements are more severe when firms disclose higher ratios of Level 3 fair values. In addition, this negative association is stronger during financial crisis periods, showing that market investors prefer conservative fair values.
1. Introduction Statement of Financial Accounting Standards No. 157, Fair Value Measurements (SFAS No. 157) outlined three levels of fair value measurements for financial assets and liabilities.1 Among the three levels, Level 3 (1) inputs are clearly subject to more (less) serious information asymmetry problems between managers and users of financial statements. Thus, corporate managers are likely to utilize managerial discretion over the inputs used to measure fair values that could induce opportunistic activities, and in turn impair financial reporting fairness. This is supported by empirical evidence provided by Lin et al. (2017) who finds that “…firms with higher ratios of Level 3 fair value assets to total assets are more likely to subsequently restate their financial statements…that use of less reliable (Level 3) fair value measurements may reduce financial reporting quality (p. 01)”. This study extends Lin et al. (2017) and further investigates the effect of fair value accounting on the market reaction of financial restatements to observe how market participants respond to restatement announcements associated with firms that report Level 3 fair values. Since Level 3 fair values may contain serious measurement errors and induce managerial manipulation, this paper predicts the market will penalize firms with restatements having higher Level 3 fair values. We also examine the sensitivity of the market during and after the crisis period. This study contributes to the literature in several ways. First, it provides relevant evidence that Level 3 measurements are vulnerable to subjective manipulation, thus suggesting that additional supporting disclosures are required. Such disclosures can prevent managers from misleading the users of financial statements. Second, investors and financial analysts can use Level 3 fair values as financial risk indicators when making investment decisions. This provides incremental information for investors to value the companies and avoid fraudulent financial reporting. Finally, because some board members, especially the audit committee directors, have the authority and responsibility to remediate internal control weaknesses and select/appoint/dismiss the incumbent auditor of We thank the participants in the International Conference of Innovation and Management 2018 in Fukuoka, Japan, and Workshops at National Cheng Kung University for their helpful comments on this paper. ⁎ Corresponding author. E-mail address: [email protected] (A.A. Zaher). 1 Level 1 includes observable inputs from quoted market prices in active markets for identical assets or liabilities. Level 2 consists of observable inputs from quoted market prices in active markets for similar assets or liabilities, quoted market prices for identical or similar assets or liabilities in inactive markets, and other market-corroborated inputs. Level 3 represents unobservable, firm-generated inputs. https://doi.org/10.1016/j.frl.2019.07.017 Received 24 January 2019; Received in revised form 31 May 2019; Accepted 27 July 2019 1544-6123/ © 2019 Elsevier Inc. All rights reserved.
Please cite this article as: Hua-Wei Solomon Huang, Zhi-Yuan Andy Feng and Angie Abdel Zaher, Finance Research Letters, https://doi.org/10.1016/j.frl.2019.07.017
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the company, corporate boards may strengthen their governance and select better auditors by hiring high quality directors in order to develop more reliable Level 3 fair values. 2. Literature and hypothesis development 2.1. Literature There is a research stream examining market reaction to restatement announcements (e.g., Dechow et al., 1996; Palmrose et al., 2004; Files et al., 2009; Nguyen and Puri, 2014). Regulators and market investors view restatement announcements as bad news because they are usually related to weak internal controls and earnings manipulation. Prior literature consistently showed negative market reactions to restatement announcements. Palmrose et al. (2004) and Nguyen and Puri (2014) found significant negative abnormal returns two days after restatement announcements for 403 restatement announcements released from 1995 to 1999. Files et al. (2009) found negative market reactions to all locations where restatements are disclosed (i.e., in a headline, with a headline on a different subject, or in a footnote to operating results). The enactment of the Sarbanes–Oxley Act (SOX) in 2002 has improved investor perceptions regarding the reliability and timeliness of financial disclosures provided by restated firms. Hranaiova and Byers (2007) compared restatement announcements in the pre- and post-SOX periods and found that the average negative (positive) cumulative abnormal return is lower by 71 (33) percent post-SOX. Furthermore, the market is less sensitive when this information is disclosed obscurely (Files et al., 2009). However, few papers focused specifically on the impact of Level 3 fair values on restatement announcements. 2.2. Hypothesis development Cannon and Bedard (2017) indicated that fair values “…have high estimation uncertainty, high subjectivity, significant/complex assumptions, and multiple valuation techniques”. Lin et al. (2017) found that firms with higher Level 3 fair values are more likely to report financial restatements. As an extension, this study explores incremental effects of Level 3 fair values on market reactions to restatement announcements. Because Level 3 fair values are more easily manipulated by managers engaging in opportunistic activities, including intentional financial statement frauds, market investors may have stronger reactions to firms reporting higher Level 3 fair values. Hence, the following hypothesis is proposed: H. The negative market reaction to financial restatement will be higher for firms reporting higher Level 3 fair values. 3. Data and method Firstly, we identify 2837 restatement firm-year observations with fair value data in Compustat during the years 2008–2017.2 Our sample overlaps with the 2008 financial crisis period, considered to be the worst period since the Great Depression which simulated instability around the globe. Among the 2837 restatements, 1344, 99, and 1394 restatements were initiated by management (47.4%), SEC (3.5%), and auditors (49.1%), respectively. Building on Palmrose et al. (2004) and Files et al. (2009), the following OLS regression model is expended to investigate the market reaction to restatement announcements when firms disclose different levels of fair values.
CAR = + 1 FRAUD + 2 AUD _LETTER + 3 SEC _INVEST + 4 CORE _ACC+ 5 CHANGE _NI _TA + 6 YEARS _RES + 7 SIZE + 8 ICW + 9 ACCRUALS + 10 ROA+ 11 EVENT + 12 INSIDER% + 13 BLOCKHO% + 14 PRIOR _RETURN + 15 17 FVA _VARS+ Year + Industry +
(1)
where: CAR = Cumulative abnormal market returns (CAR) during a period of time. Two event windows of three-days (−1 to +1) and six days (−1 to +5) around the restatement FRAUD = 1 if fraud-related restatements are reported on AuditAnalytics, 0 otherwise AUD_LETTER = 1 if restatements are attributed to auditors SEC_INVEST = 1 if restatements are attributed to SEC investigations announcements are used.3 CORE_ACC = 1 if core accounts are affected by the restatement CHANGE_NI_TA = change in net income over total assets affected by the restatements YEARS_RES = number of years restated SIZE = natural logarithm of total assets ICW = 1 if the company reports material internal control weakness in the SOX 404 report 2 Level 3 fair value data became available after (including) 2008. Our test period overlaps with the financial crisis because the effect of Level 3 fair values on restatements may be especially profound when the sluggish economy exacerbates the liquidity of certain financial instruments. 3 The two windows are very conventional. One trading day before the event day is used to measure the effect due to potential information leakage of this disclosure. One trading day or five trading days after the event day is used to measure the effect of this disclosure in one day or one week.
2
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Table 1 Descriptive data of restatements (N = 732).
Mean Median Mean Median
CAR (−1, +1)
CAR (−1, +5)
FVA1_TA
FVA2_TA
FVA3_TA
FRAUD
AUD_LETTER
SEC_INVEST
CORE_ACC
PRIOR_RETURN
−1.11% −0.31% CHANGE_NI_TA −0.03% 0.00%
−0.99% −0.29% YEARS_RES 2.29 1.95
0.06 0.00 SIZE 21.07 21.01
0.07 0.00 ICW 0.15 0.00
0.01 0.00 ACCRUALS −0.46 −0.04
0.02 0.00 ROA −0.04 0.01
0.47 0.00 EVENT 0.16 0.00
0.04 0.00 INSIDER% 2.68% 0.00%
0.34 0.00 BLOCKHO% 33.46% 33.76%
3.98% 1.67%
ACCRUALS = discretionary accruals (Kothari et al., 2005) ROA = return on assets EVENT = 1 if there is any significant event or litigation case against the company during the period of event days, otherwise 0 (Wall Street Journal and Stanford Law School Database) INSIDER% = percentage of stock held by all directors on the board based on BoardEX BLOCKHO% = percentage of stock held by block-holders on Corporate Library PRIOR_RETURN = Changes in stock price over 120 days prior to the restatement announcement (Palmrose et al., 2004) FVA_VARS represents the proportions of level 1, 2, and 3 fair value assets held by the company, including: FVAx_TA = Level x fair values of financial assets divided by total assets Similar to Palmrose et al. (2004), we control for firm complexity using SIZE, for firm performance using ROA, for recent stock performance using PRIOR_RETURN, and for signals of restatement from outside parties using AUD_LETTER and SEC_INVEST. We also control for FRAUD due to the increased threat of litigation. Materiality of restatement is controlled using CORE_ACC, CHANGE_NI_TA, and YEARS_RES (Palmrose et al., 2004). Both the impact of internal control strength (ICW) and earnings management (ACCRUALS) are included. We use INSIDER% and BLOCKHO% to control for the influence of insiders and block holders. Finally, we include year and industry dummy variables to control for year and industry fixed effects. After deleting observations with missing financial data in the BoardEX/Corporate Library (1112) and matching with CRSP/ EVENTUS (993), our sample size is reduced to 732 observations. Table 1 provides the descriptive statistics. The mean CAR using both windows is significantly negative, consistent with previous studies (Palmrose et al., 2004). Also, the mean values of FVA1_TA, FVA2_TA, and FVA3_TA are 0.06, 0.07, and 0.01, respectively, which are close to the values of FVA1_TA, FVA2_TA, and FVA3_TA (0.09, 0.07, and 0.02), respectively, reported in Lin et al. (2017). Likewise, the average values of SIZE, ICW, ACCRUALS, and ROA are 21.07, 0.15, −0.46, and −0.04, respectively, which are similar as those reported in Lin et al. (2017). Finally, there are 16% sample firms with events and 47% or 4% restatements attributed by auditors or SEC, respectively. The mean (median) ratio of Table 2 Regression of CAR, restatements, and fair values. Variables
Sign
(−1, +1) CAR Coefficient
Constant FVA1_TA FVA2_TA FVA3_TA FRAUD AUD_LETTER SEC_INVEST CORE_ACC CHANGE_NI_TA YEARS_RES SIZE ICW ACCRUALS ROA EVENT INSIDER% BLOCKHO% PRIOR_RETURN Year Industry R2 N Coefficient comparisons FVA1_TA=FVA2_TA FVA1_TA=FVA3_TA FVA2_TA=FVA3_TA
? + + – – – – – + – ? – – + – ? ? +
0.0146 0.0428 0.0267 −0.1837 −0.0076 −0.0121 0.0128 0.0052 0.0727 −0.0038 0.0009 −0.0214 −0.0004 0.0061 −0.0283 −0.0050 −0.0293 −0.0001 Yes Yes 16.51% 732 p-value 0.23 20.38 15.92
F-stat
p-value 0.815 0.024 0.304 0.000 0.739 0.073 0.436 0.449 0.460 0.070 0.689 0.018 0.682 0.631 0.001 0.897 0.461 0.979
F-stat 0.630 <0.0001 <0.0001
3
(−1, +5) CAR Coefficient 0.0160 0.0870 0.0147 −0.2329 −0.0026 −0.0171 0.0376 0.0044 −0.0596 −0.0025 0.0009 −0.0336 −0.0004 −0.0050 −0.0386 −0.0028 −0.0193 0.0055 Yes Yes 16.00% 732 p-value 3.01 26.33 14.29
p-value 0.837 0.000 0.649 0.000 0.926 0.041 0.065 0.600 0.626 0.345 0.753 0.003 0.750 0.752 0.000 0.953 0.697 0.329
0.084 <0.0001 0.0002
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Table 3 Impact of financial crisis. Variables
Sign
(−1, +1) CAR Coefficient
FVA1_TA FVA2_TA FVA3_TA Crisis FVA1_TA × Crisis FVA2_TA × Crisis FVA3_TA × Crisis Control Year Industry
+ + – –
0.0229 0.0140 −0.0666 −0.0287 0.0192 0.0485 −0.2637 Yes Yes Yes
R2 N
p-value 0.533 0.613 0.275 0.280 0.644 0.380 0.005
17.70% 732
(−1, +5) CAR Coefficient 0.0536 0.0103 −0.0326 −0.0210 0.0421 −0.0117 −0.4620 Yes Yes Yes
p-value 0.237 0.764 0.666 0.523 0.412 0.864 0.000
18.10% 732
PRIOR_RETURN is 3.98 (1.67)%, showing positive trends for stock prices before the event date windows. Table 2 reports the OLS regression results. Multicollinearity should not be an issue since all VIFs are less than 10.0. Firstly, the coefficients of FVA1_TA on CAR (−1, +1) and CAR (−1, +5) are both positive and significant (p-value < 0.050 and < 0.010), showing that negative market reactions to the restatements of high values of Level 1 assets are less than the restatements of low values of Level 1 assets because those firms should have less information asymmetry between managers and financial statement users. Next, FVA3_TA is significantly negative in both test windows (at p-value < 0.010). This finding shows that, in general, Level 3 fair values increase the negative abnormal returns around the restatement announcements. Market participants appear to penalize firms reporting Level 3 fair values. We compare the slope coefficients for Level 1, Level 2, and Level 3 fair values. The coefficients of Level 3 fair values are significantly lower (p-values < 0.100 for both windows). As for the control variables, AUD_LETTER and ICW are negatively associated with CAR, indicating that restatements attributed to auditors and poor internal controls result in more negative market responses. In addition, YEARS_RES and EVENT also show significantly negative impacts (Palmrose et al., 2004). In the additional analyses, we investigate whether the stock market reactions to restatements are different during the crises and non-crises periods. We define the crisis dummy coded as 1 if the observations fall within 2008 to 2010, and otherwise 0, and then interact this crisis dummy with FVA1_TA, FVA2_TA, and FVA3_TA, respectively. In Table 3, the interaction items FVA3_TA × Crisis for the two event windows are both negative and significant (p-values < 0.010). This indicates that the negative market reactions to restatements with high Level 3 fair values are stronger during the crises period, showing that the market investors prefer conservative fair values during the financial crisis. 4. Conclusion This study analyzes the effect of Level 3 value disclosures on market reaction. We find that restated firms experience a significantly negative stock price reaction. Our results also indicate that the use of less reliable fair values such as Level 3 values is likely to result in restatements, which triggers further damage to stock prices. These findings are of importance to regulators, investors, and auditors in the US. Such Level 3 disclosures are a determinant behind firm restatements and play a key part in how the market reacts. Limitations of our study include potential biases since our sample eliminated some observations due to missing BoardEX/ Corporate Library/CRSP/EVENTUS data. Further, we acknowledge that there may still be uncaptured effects of missing confounding events. Acknowledgment Hua-Wei Huang gratefully acknowledges the National Science Council, Taiwan, ROC, for support of this work under contract (NSC 100-2410-H-006-102). Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.frl.2019.07.017. References Cannon, N.H., Bedard, J.C., 2017. Auditing challenging fair value measurements: evidence from the field. Account. Rev. 92 (4), 81–114. Dechow, P.M., Sloan, R.G., Sweeney, A.P., 1996. Causes and consequences of earnings manipulation: an analysis of firms subject to enforcement actions by the SEC. Contempor. Account. Res. 13, 1–36. Files, R., Swanson, E.P., Tse, S., 2009. Stealth disclosure of accounting restatements. Account. Rev. 84 (5), 1495–1521. Hranaiova, J., Byers, S.L., 2007. Changes in market responses to financial statement restatement announcements in the Sarbanes-Oxley Era. . Available at SSRN:
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