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Erschienen in: Journal of Business Ethics 3/2021

20.12.2019 | Original Paper

Corporate Social Responsibility and Financial Fraud: The Moderating Effects of Governance and Religiosity

verfasst von: Xing Li, Jeong-Bon Kim, Haibin Wu, Yangxin Yu

Erschienen in: Journal of Business Ethics | Ausgabe 3/2021

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Abstract

This study investigates how managers in firms that have committed fraud strategically use socially responsible activities in coordination with their fraudulent financial reporting practices. Using propensity score matching to select control firms that have a similar probability of fraud in the pre-fraud benchmark period, we find that the corporate social responsibility (CSR) performance of fraudulent firms in the fraud-committing period is significantly higher compared with the CSR performance of non-fraudulent control firms during this period, and compared with that during their own pre-fraud benchmark periods. This higher CSR performance by fraudulent firms is achieved by means of investing in both stakeholder and third-party CSR categories and by improving in CSR strengths. Furthermore, the increase in CSR performance is more pronounced for fraudulent firms with a weak governance environment, and for firms located in high-religiosity states. Overall, our findings suggest that fraudulent firms strategically adjust their CSR performance to coordinate with their fraudulent financial activities.

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Fußnoten
1
While studies such as that of Kim et al. (2012) show that CSR-engaged firms are less likely to be subject to SEC enforcement actions, a positive relationship between fraud and CSR performance before the public discovery of fraud, if observed, would not necessarily be in conflict with these studies. Because regulatory enforcement actions by the SEC occur after the fraud is detected, whereas our study focuses on CSR performance during the period in which fraud is being committed. Furthermore, the lower likelihood of the SEC’s regulatory enforcement actions for CSR firms may be exactly due to these firms’ improvement in CSR during the fraud-committing period.
 
2
Audit Analytics data is only available to us up to 2014; thus, we supplement the years 2015–2016 using the Stanford Securities Class Action Clearinghouse database.
 
3
MSCI STATS is the successor to Kinder, Lydenberg & Domini (KLD), Innovest, and the Investor Responsibility Research Center (IRRC).
 
4
The coverage of the Audit Analytics Corporate and Legal database starts in 1960. However, there are fewer than 100 cases from 1960 to 1994. Consequently, after the sample selection process, all of our fraud cases are taken from the period from 1995 onwards.
 
5
A major advantage of using the Audit Analytics class action litigation database is that each fraud case has a start date (exposure begin date) and an end date (exposure end date), enabling us to accurately construct the fraud-committing period of each firm.
 
6
The ex ante probability of financial fraud is computed using the following procedure. First, we compute the predicted value using the estimated coefficients of Dechow et al. (2011): Predicted value = − 7.893 + 0.79 × rsst_acc + 2.518 × d_rec + 1.191 × d_inv + 1.979 ×  %soft_at + 0.171 × d_cs – 0.932 × d_roa + 1.029 × issue, where rsst_acc is total accruals; d_rec, d_inv, d_cs, and d_roa are changes in receivables, inventory, cash sales, and return on assets (ROA), respectively; %soft_at is the percentage of soft assets; and issue is a dummy variable that equals 1 if a firm issues equity or debt and 0 otherwise. Next, the ex ante predicted probability of financial fraud is computed as p(Fraud) = exp(Predicted_value)/[1 + exp(Predicted_value)].
 
7
For example, in 2010 data there are eight community strengths—charitable giving, innovative giving, support for housing, support for education, non-US charitable giving, volunteer program, community engagement, and other community strengths—and four community concerns—investment controversies, negative economic impact, tax disputes, and other community concerns.
 
8
For example, the maximum possible number of environmental concerns was six in the period from 1991 to 1998, increasing to seven in 1999.
 
9
For example, the community CSR score is defined as the number of community strengths divided by the maximum number of community strengths minus the number of community concerns divided by the maximum number of community concerns, and possible values range between − 1 and 1.
 
10
Our results are not affected if we define Leverage as the ratio of long-term debt (item 9) plus debt in current liabilities (item 34) to total assets.
 
11
The definition of these variables can be found in “Appendix 1”.
 
12
We also include the model-based measures of EM in our main regressions as additional control variables, and our results remain unchanged.
 
13
As a robustness check, we also investigate the association between corporate within-GAPP earnings management and CSR performance. The (untabulated) results show that corporate CSR performance is positively associated with its previous earnings management activities (both accrual-based and real earnings management).
 
14
The Bebchuk E-index is provided up to 2006; we thus construct the index for more recent years using the method proposed by Bebchuk et al. (2009).
 
15
Our results are not affected if we also include the interaction of Entrenchment with the Fraud and During dummies—that is, Fraud×Entrenchment and During×Entrenchment.
 
16
Our results are not affected by the inclusion of the interaction of Religiosity with the Fraud and During dummies—that is, Fraud×Religiosity and During×Religiosity.
 
17
Note that we define Fraud_Length as the logged number of months from the fraud start date to the fraud end date.
 
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Metadaten
Titel
Corporate Social Responsibility and Financial Fraud: The Moderating Effects of Governance and Religiosity
verfasst von
Xing Li
Jeong-Bon Kim
Haibin Wu
Yangxin Yu
Publikationsdatum
20.12.2019
Verlag
Springer Netherlands
Erschienen in
Journal of Business Ethics / Ausgabe 3/2021
Print ISSN: 0167-4544
Elektronische ISSN: 1573-0697
DOI
https://doi.org/10.1007/s10551-019-04378-3

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