Abstract
We conjecture that corporate social responsibility (CSR) can be indicative of managerial ethics and integrity and examine whether equity investors and financial analysts consider CSR performance when they assess firms’ disclosures of actual and forecasted earnings. We find that only adverse CSR performance affects investors’ assessments of these disclosures. In contrast, we find that both positive and adverse CSR performance affect analysts’ forecast revisions in response to firms’ disclosures. We also find that firms with adverse CSR performance exhibit lower disclosure quality and earnings persistence, but do not find that firms with positive CSR performance exhibit higher levels of both measures. This asymmetric result is consistent with investors’, but not analysts’, assessments of the effect of CSR performance on corporate disclosures. Our results are robust to using a three-stage least squares approach to address endogeneity concerns and to a battery of robustness and sensitivity analyses. Overall, our findings suggest that investors and analysts consider CSR when assessing the information in earnings-related corporate disclosures.
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Notes
Business Social Responsibility is the largest organization in the US devoted to the promotion and development of corporate social responsibility among businesses and organizations.
We use the terms “equity investors” and “investors” interchangeably to refer to investors who invest in firms’ equity shares. We also use the term “financial analysts” and “analysts” interchangeably to refer to analysts who work for brokerages that provide research information on firms, including those listed on the stock exchanges.
Prior studies on the economic consequences of CSR include Waddock and Graves (1997), Roman et al. (1999), Orlitzky et al. (2003), Webb (2004), Kempf and Osthoff (2007), Surroca and Tribó (2008), Walls et al. (2012), Kim et al. (2012), Koh and Tong (2013), Servaes and Tamayo (2013), Khan et al. (2016), and Jeong et al. (2016).
In this regard, our study differs from prior studies (e.g., Roman et al. 1999; Waddock and Graves 1997) that examine the association between CSR performance and stock prices because our focus is on short-window price reactions to earnings-related disclosures and not on long-window stock price changes as a measure of firm performance.
Stock recommendations are based on categorical measures, such as “Sell,” “Hold,” and “Buy,” which are ordinal in nature. Earnings forecasts are based on analysts’ estimates of earnings per share, usually forecasted to the nearest cent. Hence, earnings forecasts provide a more detailed or finer measure of analysts’ reaction to new information. For example, a fine for environmental violations may decrease analysts’ earnings forecasts for the firm by a cent, but may leave analysts’ stock recommendation unchanged because the decrease of one cent is not significant enough to change the recommendation from, say, “Buy” to “Hold.”
Our study differs from these studies that rely on accounting-based measures of earnings management to examine whether CSR performance is indicative of managerial integrity and ethics (e.g., Kim et al. 2012; Koh and Tong 2013; Hoi et al. 2013). These studies can only address how CSR performance affects the reported accounting numbers, not how stakeholders respond to these reported accounting numbers. Our study attempts to fill this void in the extant literature by directly examining the effect of CSR performance on stakeholders’ reactions to the earnings numbers disclosed by firms.
Margolis and Walsh (2003) suggest that although most research evidence points to a positive association between CSR performance and financial performance, overall empirical evidence of this association is mixed. They examine 109 archival studies and find that 54 (7) report a positive (negative) effect of CSR performance on future firm performance, whereas 48 do not report a significant relation between the two factors.
Examining positive and adverse CSR performance separately is also consistent with the call by Mattingly and Berman (2006), who urge researchers to ensure that CSR strengths and weaknesses remain independent (i.e., are not combined) in a research design. Using factor analysis to identify latent constructs underpinning KLD ratings, Mattingly and Berman (2006) find that KLD’s strength and concern ratings do not exhibit convergent validity as they do not converge and load together on a single factor. Thus, they caution that using a net composite indicator of CSR performance is not a valid research a negative CSR performance is not simply the converse of positive CSR performance, or vice versa.
GAAP are financial reporting standards issued by the Financial Accounting Standards Board (FASB), which is the organization responsible for financial reporting standards in the USA.
Recently, the effectiveness of KLD ratings studies for measuring CSR performance has been questioned. However, Chatterji et al. (2009) confirm that KLD’s environmental concern ratings capture past environmental performance and are useful in predicting future environmental violations. Nonetheless, they find that the environmental strength ratings are less useful in predicting future environmental performance. Szwajkowski and Figlewicz (1999) find that KLD ratings are substantially valid measures of CSR performance. Mattingly and Berman (2006) describe the KLD dataset as the standard quantitative measurement of CSR performance.
Value-weighed abnormal returns (CAR) are based on market risk adjustment, which uses the value-weighted market portfolio as the benchmark. Size-adjusted abnormal returns (SAR) are based on a firm characteristic risk adjustment, which uses the value-weighted portfolio returns of firms of the same size as the benchmark portfolio. These two risk adjustment approaches are widely used in prior studies examining stock price reactions (e.g., see Grullon et al. 2002; Gleason and Lee 2003; Richardson et al. 2005; Cheung 2011; Ng et al. 2013; deHann et al. 2015). We do not rely on the Fama–French three- or four-factor model for risk adjustment because Ahern (2009) shows that abnormal return estimation using such models can produce statistical biases if the sample exhibits non-normal returns.
Ideally, the stock price used as the scaler should not be affected by any information in the management forecasts. Prior studies have used stock prices that range from 2 days prior forecast date to the beginning of the quarter in which the forecast is made (e.g., see Ng et al. 2013; Li and Zhang 2015). We use stock price 10 days before forecast date because Agapova and Madura (2011) find that information in management forecasts is leaked prior to the forecast dates and that the bulk of the leaked information occurs during the 10 days prior to the forecast dates. As a robustness check, we use the stock price 2 days before the forecast dates as the scaler and find that our results remain robust and our inferences unchanged.
The number of days between quarterly earnings announcements, including announcements of annual earnings in the fourth fiscal quarter, is about 90 calendar days apart (i.e., a calendar quarter). Thus, we use a 90-day window on both sides of an annual earnings announcement date to calculate analysts’ forecast revision (REV_EA). This will ensure that the prior consensus forecast is after the announcement of third fiscal quarter earnings, and the latter consensus forecast is before the announcement of first fiscal quarter earnings. On the one hand, using a window period longer than 90 days may not ensure that the calculated analysts’ forecast revision reflects only the news contained in the annual earnings announcement made in the fourth fiscal quarter. On the other hand, using a smaller window period of less than 90 days may unnecessarily reduce sample size. In our sample, we find that the average number of days between the annual earnings announcement date and the first updated consensus earnings forecast is 42.66 days. The average number of days between the annual earnings announcement date and the last updated consensus earnings forecast is 44.51 days.
Unlike earnings announcements, which are made only once every quarter and about 90 days between each announcement, managers may announce earnings forecasts more than once in a single quarter. Thus, following prior research (e.g., Hutton et al. 2012), we use a 30-day window period to calculate REV_MF. In our sample, we find that the average number of days between the management forecast date and the first updated consensus earnings forecast is 5.88. The average number of days between the management forecast date and the last updated consensus earnings forecast is 15.62.
Our study’s primary focus is whether CSR performance per se is indicative of managerial integrity and ethics, which in turn is indicative of disclosure quality and financial performance. Thus, the examination of our underlying assumptions about disclosure quality and earnings persistence is secondary. We note that if the assumptions hold, then including proxies of disclosure quality and earnings persistence in our empirical specifications will mechanically diminish the explanatory power of CSR performance for investors’ and analyst’ reactions. However, such an outcome does not invalidate the inference that CSR performance can be indicative of managerial integrity and ethics, which are factors that can influence disclosure quality and earnings persistence.
In their validation test, Chen et al. (2015) find that DQ is negatively (positively) associated with analysts’ forecast dispersion (accuracy), negatively associated with the information asymmetry component of bid-ask spreads, and negatively associated with the cost of capital.
The use of lagged earnings in Eq. (6) may raise concerns about bias and inefficient ordinary least squares (OLS) coefficient estimates for dynamic panel model. However, Nickell (1981) and Baltagi (2008) note that OLS coefficient estimates of a lagged dependent variable are biased mostly because of the correlations between firm fixed effects and the lagged dependent variable. In Eq. (6), we do not use firm fixed effects, only industry and year fixed effects. Moreover, we also adjust for inefficient estimates by calculating firm-clustered standard errors to account for firm-level serial correlations. Nonetheless, to address concerns about dynamic panel model, we employ the Arellano and Bond’s (1991) approach to estimate Eq. (6) as a robustness check. The results (untabulated) remain qualitatively similar to those reported in Table 6, and our inferences remain unchanged.
The results reported in Tables 5 and 6 are based on the largest sample in our study (based on the samples used in Table 3). When we restrict our analyses to the smaller samples that have analysts’ forecasts (based on the samples used in Table 4), we find similar results to those reported in Tables 5 and 6. Therefore, the asymmetric effect of CSR performance on firms’ actual disclosure quality and earnings persistence is not dependent on the specific samples used in our analyses.
In addition, we check the variance inflation factor (VIF) for estimated Eqs. (1)–(4). The VIFs for our test variables (i.e., CSRS × ESURP, CSRC × ESURP, CSRS × MFSURP, and CSRC × MFSURP) and the control variables are all below ten, except for the interacted terms of control variables LNSALES and INST with both ESURP and MFSURP. As such, we perform a robustness check by dropping LNSALES and INST completely from Eqs. (1)–(4) and re-estimate these equations. We find that the results remain qualitatively similar to those reported in Tables 3 and 4 of the paper, and we believe multicollinearity does not affect our overall results and inferences.
We caveat that our findings can neither speak to why investors and analysts view positive CSR performance differently, nor to the appropriateness of their differential reactions to earnings-related corporate disclosures. However, one possible explanation is that some analysts may issue optimistic earnings forecasts and stock recommendations to please managers so that they can gain better access to firm information and can build better relationship with the firms (e.g., see Ke and Yu 2006; Chen and Matsumoto 2006). Thus, it is possible that financial analysts may view and react to positive CSR performance differently from equity investors because they have a slightly different set of incentives and decision-making outcomes.
We combine the KLD’s employee and diversity dimensions and the community and human rights dimensions into two single stakeholder categories (employee and community). This is for the sake of brevity as the diversity dimension corresponds to CSR activities that primarily affect employees, whereas the human rights dimension corresponds to CSR activities that are associated with international labor rights and with relations between companies and indigenous people.
References
Agapova, A., & Madura, J. (2011). Information leakage prior to company issued guidance. Financial Management, 40, 623–646.
Ahern, K. R. (2009). Sample selection and event study estimation. Journal of Empirical Finance, 16(3), 466–482.
Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economics Studies, 58(2), 277–297.
Baltagi, B. H. (2008). Econometric analysis of panel data. West Sussex: Wiley.
Barth, M. E., & Hutton, A. P. (2004). Analyst earnings forecast revisions and the pricing of accruals. Review of Accounting Studies, 9(1), 59–96.
Bartov, E. & Li, Y. (2015). Corporate social responsibility and the market pricing of corporate earnings. Working Paper, New York: University and National University of Singapore.
Billings, B. K. (1999). Revisiting the relation between the default risk of debt and the earnings response coefficient. The Accounting Review, 74(4), 509–522.
Campbell, J. L. (2007). Why would corporations behave in socially responsible ways? An institutional theory of corporate social responsibility. Academy of Management Review, 32(3), 946–967.
Carroll, A. B. (1991). The pyramid of corporate social responsibility: Toward the moral management of organizational stakeholders. Business Horizons, 34(4), 39–48.
Chatterji, A. K., Levine, D. I., & Toffel, M. W. (2009). How well do social ratings actually measure corporate social responsibility? Journal of Economics & Management Strategy, 18(1), 125–169.
Chen, C., & Delmas, M. (2011). Measuring corporate social performance: An efficiency perspective. Production and Operations Management, 20(6), 789–804.
Chen, S., & Matsumoto, D. A. (2006). Favorable versus unfavorable recommendations: The impact on analyst access to management-provided information. Journal of Accounting Research, 44, 657–689.
Chen, S., Miao, B. I. N., & Shevlin, T. (2015). A new measure of disclosure quality: The level of disaggregation of accounting data in annual reports. Journal of Accounting Research, 53(5), 1017–1054.
Cheung, W. K. A. (2011). Do stock investors value corporate sustainability? Evidence from an event study. Journal of Business Ethics, 99, 145–165.
Collins, D. W., & Kothari, S. P. (1989). An analysis of intertemporal and cross-sectional determinants of earnings response coefficients. Journal of Accounting and Economics, 11(2–3), 143–181.
CSR Europe, Deloitte, & Euronext. (2003). Investing in responsible business: The 2003 survey of European fund managers, financial analysts and investor relations officers. Brussels: CSR Europe & Deloitte.
Davis, A. D., Guenther, L. K., & Williams, B. (2015). Do socially responsible firms pay more taxes? The Accounting Review, 91(1), 47–68.
Donaldson, T., & Preston, L. E. (1995). The stakeholder theory of the corporation: Concepts, evidence, and implications. The Academy of Management Review, 20(1), 65–91.
Ernst & Young. (2014). Let’s talk: Sustainability. A new point of view for business leaders. Retrieved from http://www.ey.com/Publication/vwLUAssets/EY_Lets_talk_sustainability_2014-04/$FILE/EY%20Let’s%20talk%20sustainability,%202014-04.pdf.
Gao, J., & Bansal, P. (2013). Instrumental and integrative logics in business sustainability. Journal of Business Ethics, 112(2), 241–255.
Gleason, C., & Lee, C. (2003). Analyst forecast revisions and market price discovery. The Accounting Review, 78(1), 193–225.
Godfrey, P. C. (2005). The relationship between corporate philanthropy and shareholder wealth: a risk management perspective. Academy of Management Review, 30, 777–798.
Godos-Díez, J., Fernández-Gago, R., & Martínez-Campillo, A. (2011). How Important Are CEOs to CSR practices? An analysis of the mediating effect of the perceived role of ethics and social responsibility. Journal of Business Ethics, 98(4), 531–548.
Grullon, G., Michaely, R., & Swaminathan, B. (2002). Are dividend changes a sign of firm maturity? Journal of Business, 75(3), 387–424.
Guiral, A., Moon, D., & Choi, H. (2014). Can excellence in corporate social performance improve investors’ financial assessments and credibility of managers’ forecasts? Asia-Pacific Journal of Financial Studies, 43(4), 530–555.
Hemingway, C. A., & Maclagan, P. W. (2004). Managers’ personal values as drivers of corporate social responsibility. Journal of Business Ethics, 50(1), 33–44.
Hoi, C. K., Wu, Q., & Zhang, H. (2013). Is corporate social responsibility (CSR) associated with tax avoidance? Evidence from irresponsible CSR activities. The Accounting Review, 88(6), 2025–2059.
Hong, B., Li, Z., & Minor, D. (2016). Corporate governance and executive compensation for corporate social responsibility. Journal of Business Ethics, 136(1), 199–213.
Hutton, A. P., Lee, L. F., & Shu, S. Z. (2012). Do managers always know better? The relative accuracy of management and analyst forecasts. Journal of Accounting Research, 50, 1217–1244.
Hutton, A. P., Miller, G. S., & Skinner, D. J. (2003). The role of supplementary statements with management earnings forecasts. Journal of Accounting Research, 41(5), 867–890.
Ioannou, I., & Serafeim, G. (2015). The impact of corporate social responsibility on investment recommendations: Analysts’ perceptions and shifting institutional logics. Strategic Management Journal, 36(7), 1053–1081.
Jayachandran, S., Kalaignanam, K., & Eilert, M. (2013). Product and environmental social performance: Varying effect on firm performance. Strategic Management Journal, 34, 1255–1264.
Jeong, K. H., Jeong, S. W., Lee, W. J., & Bae, S. H. (2016). Permanency of CSR activities and firm value. Journal of Business Ethics. https://doi.org/10.1007/s10551-016-3273-9.
Jones, T. M. (1995). Instrumental stakeholder theory: A synthesis of ethics and economics. The Academy of Management Review, 20(2), 404–437.
Ke, B., & Yu, Y. (2006). The Effect of issuing biased earnings forecasts on analysts’ access to management and survival. Journal of Accounting Research, 44(5), 965–999.
Kempf, A., & Osthoff, P. (2007). The effect of socially responsible investing on portfolio performance. European Financial Management, 13(5), 908–922.
Khan, M., Serafeim, G., & Yoon, A. (2016). Corporate sustainability: First evidence on materiality. The Accounting Review, 91(6), 1697–1724.
Kim, Y., Park, M. S., & Wier, B. (2012). Is earnings quality associated with corporate social responsibility? The Accounting Review, 87(3), 761–796.
Klein, A. (2002). Audit committee, board of director characteristics, and earnings management. Journal of Accounting and Economics, 33(3), 375–400.
Koh, K., & Tong, Y. H. (2013). The effects of clients’ controversial activities on audit pricing. Auditing Journal of Practice and Theory, 32(2), 67–96.
Kotchen, M. J., & Moon, J. J. (2012). Corporate social responsibility for irresponsibility. The B.E. Journal of Economic Analysis & Policy, 12(1), 1–21.
Kothari, S. P., & Sloan, R. G. (1992). Information in prices about future earnings: Implications for earnings response coefficients. Journal of Accounting and Economics, 15(2–3), 143–171.
Lacy, P., Cooper, T., Hayward, R., & Neuberger, L. (2010). A new era of sustainability: UN Global Compact-Accenture CEO Study study 2010. New York: UN Compact & Accenture.
Lange, D., & Washburn, N. T. (2012). Understanding attributions of corporate social irresponsibility. Academy of Management Review, 37(2), 300–326.
Lev, B., & Thiagarajan, S. R. (1993). Fundamental information analysis. Journal of Accounting Research, 31(2), 190–215.
Li, Y., & Zhang, L. (2015). Short selling pressure, stock price behavior, and management forecast precision: Evidence from a natural experiment. Journal of Accounting Research, 53, 79–117.
Lundholm, R., & Myers, L. A. (2002). Bring the future forward: The effect of disclosure on the returns-earnings relation. Journal of Accounting Research, 40(3), 809–839.
Luo, X., Wang, H., Raithel, S., & Zheng, Q. (2015). Corporate social performance, analyst stock recommendations, and firm future returns. Strategic Management Journal, 36(1), 123–136.
Margolis, J. D., & Walsh, J. P. (2003). Misery loves companies: Rethinking social initiatives by business. Administrative Science Quarterly, 48(2), 268–305.
Mattingly, J. E., & Berman, S. L. (2006). Measurement of corporate social action. Business and Society, 45(1), 20–46.
McWilliams, A., & Siegel, D. (2000). Corporate social responsibility and financial performance: correlation or misspecification? Strategic Management Journal, 21(5), 603–609.
McWilliams, A., Siegel, D. S., & Wright, P. M. (2006). Corporate social responsibility: Strategic implications. Journal of Management Studies, 43(1), 1–18.
Miao, B., & Tong, Y. H. (2011). Are dividends associated with the quality of earnings? Accounting Horizons, 25(1), 183–205.
Mishina, Y., Block, E. S., & Mannor, M. J. (2012). The path dependence of organizational reputation: how social judgment influences assessments of capability and character. Strategic Management Journal, 33, 459–477.
Mishra, S., & Modi, S. B. (2016). Corporate social responsibility and shareholder wealth: The role of marketing capability. Journal of Marketing, 80(1), 26–46.
Ng, J., Tuna, İ., & Verdi, R. (2013). Management forecast credibility and underreaction to news. Review of Accounting Studies, 18, 956.
Nickell, S. (1981). Biases in dynamic models with fixed effects. Econometrica, 49, 1417–1426.
Orlitzky, M., Schmidt, F. L., & Rynes, S. L. (2003). Corporate social and financial performance: A meta-analysis. Organization Studies, 24(3), 403–441.
Petersen, M. A. (2009). Estimating standard errors in finance panel data sets: Comparing approaches. Review of Financial Studies, 22(1), 435–480.
Petrovits, C. M. (2006). Corporate-sponsored foundations and earnings management. Journal of Accounting and Economics, 41(3), 335–362.
Phillips, R., Freeman, R. E., & Wicks, A. C. (2003). What stakeholder theory is not. Business Ethics Quarterly, 13(4), 479–502.
Ramnath, S., Rock, S., & Shane, P. (2008). The financial analyst forecasting literature: A taxonomy with suggestions for future research. International Journal of Forecasting, 24(1), 34–75.
Richardson, S., Sloan, R., Soliman, M., & Tuna, I. (2005). Accrual reliability, earnings persistence and stock prices. Journal of Accounting and Economics, 39, 437–485.
Roman, R. M., Hayibor, S., & Agle, B. R. (1999). The relationship between social and financial performance—repainting a portrait. Business and Society, 38(1), 109–125.
Schipper, K. (1991). Analysts’ forecasts. Accounting Horizons, 5, 105–131.
Servaes, H., & Tamayo, A. (2013). The impact of corporate social responsibility on firm value: The role of customer awareness. Management Science, 59(5), 1045–1061.
Shafer, W. E. (2015). Ethical climate, social responsibility, and earnings management. Journal of Business Ethics, 126(1), 43–60.
Skinner, D., & Soltes, E. (2011). What do dividends tell us about earnings quality? Review of Accounting Studies, 16(1), 1–28.
Surroca, J., & Tribó, J. A. (2008). Managerial entrenchment and corporate social performance. Journal of Business Finance and Accounting, 35(5–6), 748–789.
Szwajkowski, E., & Figlewicz, R. E. (1999). Evaluating corporate performance: A comparison of the fortune reputation survey and the socrates social rating database. Journal of Managerial Issues, 11(2), 137–154.
Valentine, S., & Fleischman, G. (2008). Professional ethical standards, corporate social responsibility, and the perceived role of ethics and social responsibility. Journal of Business Ethics, 82(3), 657–666.
Waddock, S. (2003). Myths and realities of social investing. Organization and Environment, 16(3), 369–380.
Waddock, S. A., & Graves, S. B. (1997). The corporate social performance—financial performance link. Strategic Management Journal, 18(4), 303–319.
Walls, J. L., Berrone, P., & Phan, P. H. (2012). Corporate governance and environmental performance: Is there really a link? Strategic Management Journal, 33(8), 885–913.
Warfield, T. D., Wild, J. J., & Wild, K. L. (1995). Managerial ownership, accounting choices, and informativeness of earnings. Journal of Accounting and Economics, 20(1), 61–91.
Webb, E. (2004). An examination of socially responsible firms’ board structure. Journal of Management and Governance, 8(3), 255–277.
Acknowledgements
We thank Senior Editor, Steven Dellaportas, and two anonymous reviewers for their invaluable comments and guidance. We also thank Shuping Chen, Bin Miao, and Terry Shevlin for kindly sharing the data on disclosure quality. We appreciate feedback from Azizul Islam, Sze Kee Koh, Issam Laguil, and conference participants at the 2015 Annual Meeting of the Accounting and Finance Association of Australia and New Zealand. We acknowledge our respective universities for financial support.
Funding
One of the authors has received a research grant from ASEAN CSR Network (ASEAN CSR Vision 2020 Small Grant Fund) for this study.
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Kevin Koh has received a research grant from ASEAN CSR Network (ASEAN CSR Vision 2020 Small Grant Fund). Audrey Hsu declares that she has no conflict of interest. Sophia Liu declares that she has no conflict of interest. Yen H. Tong declares that he has no conflict of interest.
Ethical Approval
This article does not contain any studies with human participants or animals performed by any of the authors.
Appendices
Appendix 1: KLD’s rating definitions
Dimension | Strengths | Concerns |
|---|---|---|
Community | Charitable giving | Investment controversies |
Innovative giving | Negative economic impact | |
Non-US charitable giving | Indigenous peoples relations | |
Support for housing | Tax disputes | |
Support for education | Other concerns | |
Indigenous peoples relations | ||
Volunteer programs | ||
Other strengths | ||
Diversity | CEO | Controversies |
Promotion | Non-representation | |
Board of directors | Other concerns | |
Work/life benefits | ||
Women and minority contracting | ||
Employment of the disabled | ||
Gay and lesbian policies | ||
Other strengths | ||
Employee relations | Union relations | Union relations |
No-layoff policy | Health and safety concerns | |
Cash profit sharing | Workforce reductions | |
Employee Involvement | Retirement benefits concerns | |
Retirement benefits strengths | Other concerns | |
Health and safety strengths | ||
Other strengths | ||
Environment | Beneficial products and services | Hazardous waste |
Pollution prevention | Regulatory problems | |
Recycling | Ozone-depleting chemicals | |
Clean energy | Substantial emissions | |
Communications | Agricultural chemicals | |
Property, plant, and equipment | Climate change | |
Management systems | Other concerns | |
Other strengths | ||
Human rights | Positive record in South Africa | South Africa |
Indigenous peoples relations strengths | Northern Ireland | |
Labor rights strengths | Burma concerns | |
Other strengths | Labor rights concerns | |
Indigenous peoples relations concerns | ||
Other concerns | ||
Product | Quality | Product safety |
R&D/innovation | Marketing/contracting concerns | |
Benefits to the economically disadvantaged | Antitrust | |
Other strengths | Other concerns |
Appendix 2: variable definitions
Variables from KLD dataset | |
CSRS | Total strengths in KLD’s six social rating categories: community, diversity, human rights, employee relations, environment, and product |
CSRC | Total concerns in KLD’s six social rating categories: community, diversity, human rights, employee relations, environment, and product |
CGOV | Total strengths minus total concerns in KLD’s corporate governance rating category in year t |
TConsumer | Total number of concerns in consumers dimension |
TEmployee | Total number of concerns in employees dimension |
TCommunity | Total number of concerns in community dimension |
TEnvironment | Total number of concerns in environment dimension |
DConsumer | Indicator variable set equal to 1 if at least one concern in the consumer dimension |
DEmployee | Indicator variable set equal to 1 if at least one concern in the employee dimension |
DCommunity | Indicator variable set equal to 1 if at least one concern in the community dimension |
DEnvironment | Indicator variable set equal to 1 if at least one concern in the environment dimension |
Variables from first Call/IBES | |
ESURP | Earnings surprise measured as earnings in year t minus the mean consensus forecast (from IBES) for firm i’s earnings before fiscal year end, scaled by the firm’s stock price at the end of the fiscal year |
MFSURP | Management forecast surprise measured as management annual earnings forecast (point or midpoint of range forecasts only) for year t minus the mean analysts’ consensus forecast for firm i’s earnings for year t, scaled by the firm’s stock price at 10 days before forecast date |
REV_EA | Analysts’ mean consensus earnings forecast for year t + 1 immediately after announcement of year t earnings minus the mean consensus earnings forecast for year t + 1 immediately before the earnings announcement of year t, scaled by the firm’s stock price at the end of the fiscal year t |
REV_MF | Analysts’ mean consensus earnings forecast immediately after the management forecast announcement minus the mean consensus earnings forecast immediately before the management forecast announcement, scaled by the firm’s stock price at 10 days before management forecast announcement date |
ANA | Natural logarithm of one plus the number of analysts following the firm over the year t |
Variables from compustat and other sources | |
CAR | Value-weighted cumulative abnormal (market-adjusted) returns, computed as the difference between the return for the firm and the return on the market portfolio cumulated over 3 days (− 1,1) surrounding annual earnings announcement or management forecast announcement |
SAR | Size-adjusted cumulative abnormal returns, computed as the difference between the return for the firm and the return on a firm’s size decile portfolio cumulated over 3 days (− 1,1) surrounding annual earnings announcement (management forecast announcement). Size portfolios are determined based on the decile assignment for all NYSE/AMEX/NASDAQ firms |
DQ | Disclosure quality score obtained from Chen et al. (2015) and based on a count of non-missing Compustat line items on both the balance sheet and income statements |
LOSS | Indicator variable that equals 1 if net income (NI) in year t is less than 0, and 0 otherwise |
LNSALES | Natural logarithm of firm i’s total sales (SALE) |
BM | The ratio of book to market value of equity calculated as book value of equity (CEQ) scaled by market value of equity (CSHO x PRCC_F) |
LEV | Proportion of long-term debt (DLTT) to total assets (AT) |
INST | Percent of firm i’s shares held by institutions in year t−1. If the data are missing, then set as 0 |
INTAN | Intangible intensity, ratio of intangible assets (INTAN) over total assets (AT) |
SPECIAL | Magnitude of special items (SPI) scaled by total assets (AT) |
SIZE | Natural logarithm of firm i’s total assets (AT) |
SEGMT | Number of business segments |
ROE | Pretax income (PI) scales by lagged equity (CEQ) |
ROESTD | Standard deviation of ROE over the current and previous 4 years |
ISSUE | Indicator variable that equals 1 if firm issued common shares exceeding 20% of market value within previous 4 years and 0 otherwise |
BIGN | Indicator that equals 1 if a firm engages a Big N audit firm and 0 otherwise |
EARN | Income before extraordinary items (IB) in scaled by total assets (AT) |
σEARN | Standard deviation of EARN over the current and previous 2 years |
DIV | Indicator variable that equals 1 if a firm has paid out dividends in year t and 0 otherwise (DVT > 0) |
CHGEARN | Changes in earnings measured as current income before extraordinary items minus lagged income before extraordinary items, scaled by total assets |
CHGCFO | Changes in cash flows from operations measured as current cash flows from operations (as per SFAS 95 adjusted for extraordinary items) minus lagged cash flows from operations, scaled by total assets |
CFO | Cash flows from operations (as per SFAS 95) adjusted for extraordinary items and scaled by total assets |
σEARN | Standard deviation of EARN over the current and previous 2 years |
σCFO | Standard deviation of CFO over the current and previous 2 years |
DSPECIAL | Indicator set to 1 if magnitude of special items (SPI) is greater than zero, 0 otherwise |
DFOREIGN | Indicator variable set to 1 if the firm engages in foreign operations based on nonzero pretax foreign income (PIFO—pretax income foreign), 0 otherwise |
INVREC | Sum of inventory (INVT) and accounts receivable (RECT) at the beginning of the year, scaled by total assets |
DMERGER | Indicator variable set to 1 if the firm is engaged in a merger or acquisition in the current year as denoted in Compustat footnote data (SALE_FN) and 0 otherwise |
IndDum | Industry dummies based on SIC classification |
YearDum | Calendar-year dummies |
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Hsu, A., Koh, K., Liu, S. et al. Corporate Social Responsibility and Corporate Disclosures: An Investigation of Investors’ and Analysts’ Perceptions. J Bus Ethics 158, 507–534 (2019). https://doi.org/10.1007/s10551-017-3767-0
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DOI: https://doi.org/10.1007/s10551-017-3767-0