Abstract
We investigate the effectiveness of corporate social responsibility (CSR) disclosure in protecting corporate reputation following financial restatements. As expected under legitimacy theory, firms can signal their legitimacy via nonfinancial disclosure after the negative effects of financial restatements. Our results show that restating firms make substantial improvements to overall CSR disclosure quality by changing their standalone reports to a more conservative tone, increasing readability and report length, even though they strategically disclose less forward-looking and sustainability-related content. Such improvements are more pronounced in restating firms with prior low-quality CSR disclosure. Moreover, restating firms with CSR disclosure have smaller forecast errors than non-CSR disclosers, yet the change in CSR disclosure after restatements does not further improve analyst forecast accuracy. Finally, we find that compared with nondisclosers, restating firms with CSR disclosure suffer smaller firm value losses. Overall, the evidence supports the view that consistent CSR reporting alleviates reputational damage and plays an insurance-like or value protection role during crisis periods.
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Notes
A survey of 388 mainstream fund managers and financial analysts initiated by Deloitte, CSR Europe, and EuroNext (2003) shows 79% of respondents indicating that CSR activities’ positive impact on firm value in the long-term, and about half of them indicating that they take CSR information into account.
Griffin (2003) reported that analyst revision occurs in the month of a restatement announcement and can last up to six months following the restatement.
A product-harm crisis is a well-publicized instance of defective or dangerous products following the definition of Dawar and Pillutla (2000).
Most firms in the sample publish periodical CSR reports (usually annually), and the frequency of CSR reporting remains largely unchanged during the financial restatement period. However, three firms (Nordstrom Inc, ManpowerGroup and CF Industries Holding Inc) started to issue CSR reports after the financial restatement. Exclusion of these restating CSR firms does not change our results.
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There is an evolving trend towards integrated reporting. However, mainstream CSR reporters still provide standalone CSR reports. A 2018 report released by the Sustainable Investments Institute (Si2) and IIRC Institute finds that a total of 395 firms among the S&P 500 (78%) issue CSR reports for the most recent reporting period, while a minority of the S&P 500 references a recognized integrated reporting framework (35 firms citing SASB and 4 firms citing IIRC). Nevertheless, we checked sample firms that publish standalone CSR reports and find that none of them adopt integrated reporting during the event window. Some CSR reporters adopted integrated reporting many years after the restatement, for example, TransAlta Corporation had a restatement in 2005 and began to issue integrated reports from 2015, which goes beyond the investigation period.
In untabulated analysis, we compare CSR-related content in standalone CSR reports to corresponding content in annual reports (or 10-Ks) for restating firms and find that firms disclose this information mostly in the Chairman’s Letter, Business Overview, and Management’s Discussion & Analysis. Standalone CSR reports are longer in length (55.6 versus 2.5 pages) and cover more general issues (9.5 versus 2.1 issues) compared to annual reports or 10-Ks. Standalone reports also divulge more details about CSR activities (27.3 specific issues on average). One example is Avery Dennison which used 10 pages to disclose its environmental efforts in 2010 CSR report, showing how it reduced environmental footprint, managed energy consumption and greenhouse emissions, reduced waste, reduced water consumption, obtained environmental certifications, achieved sustainability in its supply chain and sources responsibly. In its 2010 annual report, there was only half a page of a section titled “Environmental Matters” showing the environmental liability figures.
Some firms publish CSR reports biennially or every three years. If that is the case, we retain the CSR reports published five years before and after a financial restatement (year t − 5 to t + 5).
We checked to ensure that there is no confounding event such as change in dividend rate, M&A announcement and executive turnover in the month of the restatement announcement for both treatment and control firms, which might interfere with firms’ disclosure behavior.
Among treatment firms, there are 51 restatements due to accounting rule application failure, one restatement due to financial fraud and irregularities, four restatements due to clerical errors, and three restatements due to other significant issues. This represents 86.4% of Treatment Group (51 out of 59 restatements). Among control firms, there are 69 restatements due to accounting rule application failure, one restatement due to clerical errors, and eight restatements due to other significant issues noted. Similarly, this represents 88.5% of Control group 2 (69 out of 78 restatements).
The Pearson correlation coefficient between DSCORE and KLD strengths (KLDSTR) is 0.37 at the 1% significance level while the coefficient of DSCORE and KLD concerns (KLDCON) is − 0.07 and insignificant. This is consistent with a firm’s CSR disclosure being positively related with its CSR performance (Clarkson et al. 2008; Lyon and Maxwell 2011), yet there is a potential disconnect between voluntary CSR disclosure and third-party CSR performance ratings (Cho et al. 2013; Shane and Spicer 1983). The third-party CSR performance ratings, such as KLD indices, affect the decision-making of investors, managers, and other parties. For instance, Lee (2017) reported a positive association between CSR proxied by KLD and management forecast accuracy.
Financial disclosure quality is measured by absolute value of discretionary accruals (ADA) from the Modified Jones model (Dechow et al. 1995). A high level of ADA indicates greater financial opacity. We expect a positive coefficient on ADA, as financially opaque firms are more likely to be associated with forecast errors.
For control variables, the CSR group outperforms the non-CSR group in CSR performance with a higher KLDSTR of 4.91 and a lower KLDCON of 1.80. Compared with non-CSR firms, restating CSR firms have slightly better financial disclosure quality (0.44 compared to 0.45 of non-CSR firms), attract more financial analysts, have longer forecast horizon, are larger in size, experience less losses and less volatile earnings, and are more profitable on average.
To ensure that forecast is only affected by the restatement announcement, we keep the last forecast EPS prior to a restatement and the first forecast EPS after the restatement for all following analysts of a firm in a given year. The analyst forecast EPS refers to current-year forecast EPS, that is, forecast made in year t for earnings in year t (the restatement year).
In untabulated analysis, we use the CSR measure from Muslu et al. (2019) as an alternative to DSCORE and similar results are obtained.
The difference of 0.39 in the Column 1 is calculated as the difference of coefficients \(({\alpha }_{LHDS}-{\alpha }_{HHDS})\)= (–0.96) – (–1.35) = 0.39. The difference is not statistically significant.
In untabulated analysis, we control for corporate governance-related factors using institutional ownership and our main inferences remain largely unchanged.
Because our sample period covers the subsequent four years after a financial restatement (year t + 1 to t + 4), we also run the regression models with two-year-ahead ROA (F2ROA), three-year-ahead ROA (F3ROA), and four-year-ahead ROA (F4ROA). The untabulated results show that CSR and DSCORE are significantly positively associated with all forward-looking ROA measures.
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Acknowledgements
We are grateful to the Section Editor Professor Omrane Guedhami and three anonymous reviewers for their constructive comments and suggestions on earlier versions of this paper. We thank the participants at the 2018 AFAANZ Doctoral Symposium and seminar participants at Renmin University of China, Guangdong University of Foreign Studies, and Curtin University for their feedback. Lu Zhang has received a scholarship from China Scholarship Council and other financial support from The University of Western Australia.
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Appendices
Appendix 1: Variable Definitions
CSR disclosure score | |
RATIO_OPT | Optimism ratio is defined as the number of financial positive words divided by total number of words in a CSR report. The financial positive word list is obtained from Loughran and McDonald (2016)’s Master Dictionary (https://sraf.nd.edu/textual-analysis/resources/) |
RATIO_PES | Pessimism ratio is defined as the number of financial negative words divided by total number of words in a CSR report. The financial negative word list is obtained from Loughran and McDonald (2016)’s Master Dictionary (https://sraf.nd.edu/textual-analysis/resources/) |
SMOG | SMOG denotes the Smog index, it is a measure of readability based on the number of years of formal education a reader with average intelligence needed to understand the report text. It is calculated as 1.043 × [(number of polysyllables) × (30/(number of sentences))]1/2 + 3.1291. Polysyllables are words with more than three syllables |
RESWORDS | RESWORDS is a measure of a CSR report’s length after considering two orthogonal components the natural logarithm of the total number of words (WORDS) and the readability (SMOG). RESWORDS is calculated as the residual from the regression \(WORDS=\alpha +\beta \times SMOG+\varepsilon \), including the fixed year and industry effects |
RATIO_NUM | The ratio of numerical content is calculated using the number of Arabic numerals and numerical words divided by the total number of words in a CSR report. The numerical words are the same as defined in Muslu et al. (2019) |
RATIO_HOR | The ratio of horizon content is calculated using the number of future years and horizon words divided by the total number of words in a CSR report. The horizon words include both short-horizon and long-horizon words, which are the same as defined in Muslu et al. (2019) |
RARIO_SUS | The ratio of sustainability-related content is calculated using the number of sustainability words divided by the total number of words in a CSR report. The sustainability words are “all-natural,” “healthy,” “clean,” “safe,” “community,” “energy-efficient,” etc. A full sustainability word list is provided upon request |
DSCORE | DSCORE is a sum of decile ranks (a scale of 0.1 to 1) of RATIO_OPT, RATIO_PES, RATIO_NUM, RATIO_HOR, RATIO_SUS, and the inverse decile ranks of RATIO_OPT and SMOG |
LHDS | An indicator variable that equals 1 if a firm’s DSCORE is lower than the median of the sample, and 0 otherwise |
HHDS | An indicator variable that equals 1 if a firm’s DSCORE is larger than the median of the sample, and 0 otherwise |
Variables in the main regressions | |
Dependent variable(s) | |
POSTDAY | POSTDAY is defined as the average days of the first post-restatement EPS forecast from all following analysts of a firm |
FE0 | FE0 is current-year analyst forecast error for current-year earnings, calculated as the average absolute difference between analyst forecast and actual earnings per share (EPS), multiplied by 100 then divided by the stock price at the beginning of the year |
FE1 | FE1 is current-year analyst forecast error for one-year ahead earnings, calculated as the average absolute difference between analyst earnings’ forecast and actual earnings per share (EPS), multiplied by 100 then divided by the stock price at the beginning of the year |
FE2 | FE2 is current-year analyst forecast error for two-year ahead earnings, calculated as the average absolute difference between analyst earnings’ forecast and actual earnings per share (EPS), multiplied by 100 then divided by the stock price at the beginning of the fiscal year |
TOBINQ | TOBINQ is a measure of firm value, calculated as the market value of common equity plus preferred stock plus total debt divided by the book value of total assets. Specifically, TOBINQ = (PRCC_F × CSHO + PSTK + DLC + DLTT)/ AT, where PRCC_F is the fiscal year-end stock price, CSHO is number of shares outstanding, PSTK is the book value of preferred stock, DLC is debt in current labilities, DLTT is long-term debt, and AT is total asset |
FNTOBINQ | FNTOBINQ is TOBINQ at year t + n. n = 1,2,3,4 stand for one-year ahead, two-year ahead, three-year ahead and four-year ahead TOBINQ, respectively |
DISPER | DISPER denotes analyst forecast dispersion, calculated as the standard deviation of analyst forecasts for current-year earnings divided by the year-end stock price |
F1ROA | F1ROA is one-year ahead return on asset (ROA). ROA is defined as net income divided by lagged total assets |
Independent variables | |
RES | An indicator variable that equals 1 if a firm engages in a financial restatement, and 0 otherwise |
CSR | An indicator variable that equals 1 if a restating firm issues a CSR report, and 0 otherwise |
POST | An indicator variable that equals 1 if in the post-restatement period, and 0 otherwise |
KLDSTR | KLD strength score is a sum of CSR strengths from six categories, namely community, employee relations, environment, human rights, product and diversity |
KLDCON | KLD concern score is a sum of CSR concerns from six categories, namely community, employee relations, environment, human rights, product and diversity |
CSRAUD | An indicator variable that equals 1 if a firm’s CSR report is assured by an external auditor, and 0 otherwise |
ADA | ADA is a measure of firm-level financial disclosure quality, which is the absolute discretionary accruals calculated from the modified Jones (1991) model based on Dechow et al. (1995) |
SIZE | SIZE is the natural logarithm of total equity, calculated as common shares outstanding CSHO multiplied by year-end stock price PRCC_F |
LEV | Leverage is calculated as long-term debt divided by total assets |
LNAF | LNAF is the natural logarithm of total number of analysts following a firm in a fiscal year |
FHORIZON | FHORIZON is the forecast horizon, defined as the median number of days between earnings announcement date and analyst forecast date |
LOSS | An indicator variable that equals 1 if a firm reports a loss in a given year, and 0 otherwise |
ROAVOL | ROAVOL measures earnings volatility, defined as the time-series standard deviation of previous five years’ ROA. At least three nonmissing annual observations are required for calculation |
RD | Research and development expenditures divided by total sales |
CAPX | Capital expenditures divided by total assets |
LNSA | LNSA is the natural logarithm of total sales |
ROA | ROA is defined as net income divided by lagged total assets |
MTB | Market-to-book ratio, calculated as common shares outstanding CSHO multiplied by year-end stock price PRCC_F divided by total equity CEQ |
IMR | IMR is an inverse Mills ratio used to control for a restating firm’s decision of issuing a CSR report. IMR is calculated from the first-stage probit model shown in Appendix 4 |
Variables in robustness tests | |
DJSI | An indicator variable that equals 1 if a firm is included in the Dow Jones Sustainability World Index (1999–2017) in a given year, and 0 otherwise |
AGE | Natural logarithm of the number of years since a firm first appeared in CompuStat |
MKTSHARE | A firm’s fraction of sales in its Fama and French 48 Industry |
Appendix 2: Propensity Score Matching (PSM) Estimation Procedure (Control Group 1)
Panel A: Logit Regression Estimates
P (restatement = 1) | ||
|---|---|---|
Coefficient | Pr >|z| | |
SIZE | 0.32*** | 0.00 |
Year FE | Yes | |
Industry FE | Yes | |
Pseudo R2 | 0.1720 | |
N | 133,746 | |
Panel B: Test of Effectiveness
Variables | Mean | t-test | Diff. (treated–control) | |||
|---|---|---|---|---|---|---|
Treated | Control | t | P >|t| | |||
SIZE | Pre-match | 8.79 | 4.86 | 20.00 | 0.00 | 3.93*** |
Post-match | 8.47 | 8.41 | 0.30 | 0.77 | 0.06 | |
Panel C: Kernel Density Plots
.
Appendix 2 presents the results of matching nonrestating firms with CSR reports (Control Group 1) to restating firms with CSR reports (Treatment Group) by year, industry, stock exchange, and firm size based on the nearest propensity score.
***, **, * indicate statistical significance at the 1, 5, or 10% levels, respectively.
Appendix 3: Propensity Score Matching (PSM) Estimation Procedure (Control Group 2)
Panel A: Logit Regression Estimates
P (CSR = 1) | ||
|---|---|---|
Coefficient | Pr >|z| | |
SIZE | 0.86*** | 0.00 |
Year FE | Yes | |
Industry FE | Yes | |
Pseudo R2 | 0.2097 | |
N | 3,968 | |
Panel B: Test of Effectiveness
Variables | Mean | t-test | Diff. (treated–control) | |||
|---|---|---|---|---|---|---|
Treated | Control | t | P >|t| | |||
SIZE | Pre-match | 9.12 | 6.37 | 11.84 | 0.00 | 2.75*** |
Post-match | 9.12 | 8.10 | 4.01 | 0.00 | 1.02*** | |
Panel C: Kernel Density Plots
Appendix 3 presents the results of matching restating firms with no CSR report (Control Group 2) to restating firms with CSR reports (Treatment Group) by year, industry, stock exchange, and firm size based on the nearest propensity score.
***, **, * indicate statistical significance at the 1, 5, or 10% levels, respectively.
Appendix 4: First-Stage Probit Model of a CSR Report Issuance Decision
P (CSR = 1) | ||
|---|---|---|
Coefficient | z-stat | |
DJSI | 2.65*** | 5.53 |
AGE | 0.03 | 0.18 |
ROA | 1.65 | 1.02 |
LEV | 3.28*** | 4.10 |
RD | 0.49 | 0.22 |
CAPX | − 4.89 | − 1.05 |
MKTSHARE | − 43.90*** | − 6.38 |
SIZE | 1.11*** | 6.14 |
ROAVOL | − 8.04*** | − 3.50 |
ADA | 0.00 | 0.02 |
LNAF | − 0.64** | − 2.99 |
Year FE | Yes | |
Industry FE | Yes | |
Pseudo R2 | 0.4972 | |
N | 445 | |
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Zhang, L., Shan, Y.G. & Chang, M. Can CSR Disclosure Protect Firm Reputation During Financial Restatements?. J Bus Ethics 173, 157–184 (2021). https://doi.org/10.1007/s10551-020-04527-z
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DOI: https://doi.org/10.1007/s10551-020-04527-z