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What Good Does Doing Good do? The Effect of Bond Rating Analysts’ Corporate Bias on Investor Reactions to Changes in Social Responsibility

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Abstract

In this study, we explore how investors reconcile information on firms’ social responsibility with analysts’ assessments of future firm risk in the pricing of long-term bonds. We ask whether investors pay attention to small strides toward and/or small slips away from socially responsible behavior, arguing that analysts’ corporate bias toward gains and against losses influences investor reactions to corporate social responsibility. We hypothesize that analysts notice and reward improvements in social responsibility, yet excuse lapses. We find support for this hypothesis, using a unique dataset of long-term bonds that combines lagged measures of firm-level financial and social performance with bond-specific data pertaining to risk of default and pricing. The empirically robust asymmetry in investor responses to small but often cumulative increases versus decreases in corporate social responsibility reveals an under-examined root cause of longer-term, larger-scale distortions in financial market returns regarding corporate social performance. Our findings elaborate earlier behavioral research on how corporate bias influences analysts’ short-term assessments of economic risk, by theorizing why this corporate bias may influence long-term assessments of social risk. Our work also motivates more critical scrutiny of the role analysts play in revising the future risk of today’s social action versus inaction.

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Notes

  1. In the short-term, firms face risks such as manufacturing challenges, supply shortages, labor disruptions, and price increases, each of which are made predictable from repetition. These short-term risks manifest in the present and the near future when environments greatly resemble the past. Short-term risks can usually be predicted using conventional measures that take into account a firm’s historical risk, such as beta, a measure of a firm’s historical systematic risk (Balabanis et al. 1998; McGuire et al. 1988) and sigma, a measure of its historical total risk (Aupperle et al. 1985; Herremans et al. 1993).

  2. In practice, analysts often assign the same default risk to short-term and long-term bonds—if they expect the same risk factors to impact both equally. However, the assessment process calls for a separate evaluation of the risk facts associated with each bond, and we expect that at least some social actions or inactions may weigh more heavily in the future than in the present.

  3. Because we are measuring incremental changes with a limited range of performance, in what is seen to be a relatively stable context (corporate bonds), we expect that the relationship will approach linearity. However, since other authors have found a nonlinear relationship between CSR changes and financial performance measures in settings with more variation (see, for example, Brammer and Millington 2008; Barnett and Salomon 2012), we subject our linearity assumption to a post hoc test in the results section.

  4. As a reviewer noted, investors may attend to multiple sources of data about bond risk. Specific to our argument investors have access to multiple third party ratings with different models and therefore different biases. We examine this boundary condition empirically using the case of S&P (an issuer-pays model of credit rating) and EJR (an investor-pays model of credit rating). Our results show that when specific parallels are being drawn between two different ratings of the same bond using the same risk measurement framework, the corporate bias is no longer present. This argument has also received support in the broader corporate bias literature where the robust effects of a credit agency disappeared once an agency with a competing model began evaluating the same bonds (Xia 2014), arguably because investors compared and contrasted the two ratings when making their decisions.

  5. The hypothesized mediation mechanism only applies to firms whose credit risk is explicitly rated by third parties. A comparison of rated and nonrated firms, while helpful in principle to discern the effect size of the mediation effect, is problematic in our case because rated firms and their rated bonds differ significantly on many underlying characteristics from the firms and bonds analysts do not rate. We do however examine differences among rated firms by testing the effects of two competing models (issuer-pays and investor-pays), and are able to show that the mediation effect holds only for the specific case of issuer-pays models as we hypothesize. We also show that this mediation effect is turned off when investors have access to direct comparisons between competing models. This pattern of results is consistent with our core argument of when and why corporate bias may influence the corporate social responsibility–performance relationship.

  6. Some suggested that Moody’s ratings may have been more susceptible to the financial crisis. However, we found the same high convergent validity with other credit-rating agencies one year after our analyses (i.e., in June 2009, the average inter-item correlation .92; standardized alpha .97). This reassured us that our results were not driven by our choice of Moody’s data as our primary source of credit analyst risk ratings.

  7. Our design relies on a real-time natural experiment. During the same window of our study, all firms reported changes in their social responsibility - some did more, others less. Credit analysts rewarded some of these firms by reducing their default risk, and penalized others by increasing their default risk. Because the social expectations are the same, and we control for alternative explanations ranging from traditional economic performance to good governance arguments, our design includes the counter-factual, affording greater confidence in comparing the two hypothesized effects.

  8. EJR (and S&P) uses 10 major gradations (AAA, AA, A, BBB, BB, B, CCC, CC, C, D), which when qualified as positive or negative extend to a total of 22 minor gradations. Moody’s uses 9 major gradations (Aaa, Aa, A, Baa, Ba, B, Caa, Ca, C; qualifiers of (1), (2), and (3) on Aa–Caa extends the Moody’s scale to 21 minor gradations.

  9. In practice, analysts often assign the same default risk to short-term and long-term bonds if they expect the same risk factors to impact both equally. However, the assessment process calls for a separate evaluation of the risk facts associated with each bond, and we expect that at least some social actions or inactions may weigh more heavily in the future than in the present.

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Authors and Affiliations

  1. Richard Ivey School of Business, Western University, 1255 Western Road, London, ON, N6G 0N1, Canada

    Oana Branzei

  2. Faculty of Business Administration, University of New Brunswick, 350 Tilley Hall, 9 MacAulay Lane, Fredericton, NB, E3B 5A3, Canada

    Jeff Frooman

  3. DeGroote School of Business, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada

    Brent Mcknight

  4. Schulich School of Business, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada

    Charlene Zietsma

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  1. Oana Branzei
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Correspondence to Brent Mcknight.

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Branzei, O., Frooman, J., Mcknight, B. et al. What Good Does Doing Good do? The Effect of Bond Rating Analysts’ Corporate Bias on Investor Reactions to Changes in Social Responsibility. J Bus Ethics 148, 183–203 (2018). https://doi.org/10.1007/s10551-016-3357-6

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