Abstract
This study examines the influence of mood (‘affect’) on corporate philanthropic giving. Drawing on group emotions theory and affect-infused decision theory, we advance the argument that firms allocate greater resources to philanthropy when headquarters-based employees are in a more positive affective state. We also describe three boundary conditions in this relationship—executives’ embeddedness in the firm, executives’ latitude to engage in philanthropic giving, and the firm’s track record of corporate social irresponsibility. We test our arguments using a longitudinal dataset of philanthropic giving by U.S. firms. Our study contributes to the literature by shedding light on the role of affect in shaping the decision to allocate resources to corporate philanthropy.
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Notes
Findings from these studies are consistent with research in neurobiology (e.g., Lambert et al. 2002) showing that sunshine exposure triggers the release of a neurotransmitter—serotonin—which is associated with elevated emotional states and happiness.
An advantage of this approach is that experimental research on executives’ is challenged by their reluctance to submit themselves to psychological tests (c.f. Cycyota and Harrison 2006; Hambrick and Mason 1984). Therefore, scholars interested in how CEOs’ psychological states influence decision making have relied on observable stimuli—such as media praise or the death of an independent director (e.g., Shi et al. 2016), and link these stimuli to subsequent behavior.
Prior literature (e.g., Ashley and Faulk 2010; Porter and Kramer 2002) suggests that corporate philanthropic giving occurs through the year—rather than at one point in the year. For this reason, in our main analysis, we employ a measure that captures affect throughout the year—rather than at one point in the year. We reason that positive affect is primed for headquarters-based employees on days that are abnormally sunny. A common observation from the literature is that a positive deviation in the amount of daily sunlight primes positive daily affect (Goetzmann et al. 2015; Hirshleifer and Shumway 2003). This stream of research suggests that in years with a greater number of days that are abnormally sunny, positive affect is primed on a greater number of days (Zolotoy et al. 2019). Building on this literature, we reason that, in such years, affect is, on average, elevated.
Prior research suggests that positive and negative affect are orthogonal to one another rather than polar ends of a continuum (Rothbard and Wilk 2011; Watson et al. 1988) and have differing impacts on behavior and decision making (Koopman et al. 2016; Seo et al. 2010). Positive and negative affect also have differing primes. Said differently, prior literature does not suggest that there is likely to be a cancelation effect in years in which the area surrounding a firm’s headquarters has large number of abnormally sunny and abnormally cloudy days.
In contrast to ‘institutional’ CSR, ‘technical’ CSR (activities targeting primary stakeholders, e.g., corporate governance, product, and employee relations) are likely to be viewed as rational self-interest consistent with profit-maximizing motives (Godfrey et al. 2009).
7 We do not include the community category as it primarily captures philanthropic giving which is already captured by our dependent variable.
We corroborate that CSR strengths and CSR concerns exhibit strong positive correlation in our sample (p-value < 0.01).
As opposed to pooled fixed-effect estimator, panel fixed-effect estimator (also referred to as “within estimator”) does not saturate the model with firm-level dummies. Instead, it estimates the model using the dependent and explanatory variables mean-centered at firm level.
To further assess economic significance of positive affect at firms’ headquarters in shaping corporate philanthropic activities, we examined the out-of-sample explanatory power of Affect. In this analysis, we bisected our sample into two-subsamples: (1) estimation sub-sample, covering 2002–2007 period and (2) evaluation sub-sample, covering 2008–2012 period. Using data from the estimation sub-sample, we estimated our baseline model and used the obtained coefficients to construct forecasts of Philanthropy for the evaluation sub-sample (i.e., out-of-sample forecasts of Philanthropy). We followed similar approach to construct out-of-sample forecasts of Philanthropy based on the model with control variables only (i.e., model with Affect being excluded). We then compared the out-of-sample performance of these two models based on Root Mean Squared Error (RMSE) criterion. The (untabulated) results of this analysis suggest that accounting for Affect leads to 6% reduction in the RMSE of the model, further corroborating the role of affect in shaping corporate philanthropic giving.
Specifically, we first estimate the probability that a focal firm has a reputation for socially irresponsible behavior (i.e., probability that Social Irresponsibility dummy is equal to 1) conditional on firm’s attributes (control variables in our baseline model). We then use the estimates of the probit model to calculate an inverse Mills ratio and include it as an additional control in the model used to test Hypothesis 4.
We are grateful to Alan Muller for kindly sharing the corporate announcements and press releases related to Hurricane Katrina. From these announcements, we hand-collected data on Hurricane Katrina disaster relief donations.
In untabulated analysis, we estimated this model after controlling for both industry-and location-fixed effects with no material impact on our findings.
As our hypotheses are directional, inferences based on two-tailed tests provide a conservative estimate of the significance of our results.
In untabulated tests, we re-estimated our baseline model after excluding firms with zero top management team delta—i.e., with zero top management team compensation sensitivity to stock price (Core and Guay 2002). The results remain qualitatively unchanged.
Specifically, we excluded industries with the following two-digit Standard Industry Classification (SIC) codes: agriculture, forestry, and fishing (SIC codes 01–09), mining (SIC codes 12–13), railroad/water transportation (SIC codes 40 and 44), insurance (SIC code 63), hotels (SIC code 70), and amusement and recreation services (SIC code 79).
We note, however, that such possibility is remote: as the vast majority of firms in our sample have operations spread across multiple states (and for many of them, across multiple countries), local sunshine in the narrow (50 km) radius around firms’ headquarters should have little if any economic impact on firms’ performance. Relatedly, as we measure abnormal sunshine in the narrow radius surrounding firms’ headquarters, we do not expect our measure of affect to be correlated with state-wide economic and regulatory activity. Consistent with this notion, the results of untabulated analysis provide no evidence that state-level key economic indicators and statutory state-level corporate tax rates are significantly associated with Affect.
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Zolotoy, L., O’Sullivan, D., Seo, MG. et al. Mood and Ethical Decision Making: Positive Affect and Corporate Philanthropy. J Bus Ethics 171, 189–208 (2021). https://doi.org/10.1007/s10551-020-04432-5
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DOI: https://doi.org/10.1007/s10551-020-04432-5