Good Companies
The Macro Impact of Short-Termism
Stephen Terry
Econometrica, September 2023, Pages 1881-1912
Abstract:
R&D investment reduces current profits, so short-term pressure to hit profit targets may distort R&D. In the data, firms just meeting Wall Street forecasts have lower R&D growth and subsequent innovation, while managers just missing receive lower pay. But short-termist distortions might not quantitatively matter if aggregation or equilibrium dampen their impact. So I build and estimate a quantitative endogenous growth model in which short-termism arises naturally as discipline on conflicted managers and boosts firm value by about 1%. But short-termism reduces R&D, and the social return to R&D is higher than the private return due to standard channels including knowledge spillovers and imperfect competition. So at the macro level, short-termist distortions slow growth by 5 basis points yearly and lower social welfare by about 1%.
Corporate Social Responsibility and Voting over Public Goods
Andrew Samwick & Sophie Wang
NBER Working Paper, August 2023
Abstract:
This paper analyzes the impact of corporate social responsibility (CSR) on the total provision of public goods in a framework in which consumers who may make such voluntary contributions to public goods via CSR are also voters who decide on the level of taxes to finance publicly provided public goods. The main result indicates that, relative to an economy in which all public goods are publicly financed, the introduction of CSR lowers the total amount of public goods, as voters rationally anticipate that higher CSR will partially offset the consequences of lower public funding. The results offer a cautionary tale about the promotion of CSR in an economy with heterogeneous preferences for the public good.
Do Nice Guys Finish Last? Prosociality in the CEO Labor Market
Daniel Keum & Nandil Bhatia
Columbia University Working Paper, August 2023
Abstract:
Prosocial CEOs increase employee motivation but are often slower to implement layoffs. We present a model of CEO-firm matching wherein negative industry shocks that require downsizing asymmetrically reduce the match quality for prosocial CEOs and drive turnover. We find that prosocial CEOs are more likely to be dismissed and replaced with less prosocial successors during periods of intensifying import competition. Prosocial CEOs who are retained receive greater bonus-based pay relative to less prosocial CEOs, consistent with increased financial incentives to engage in downsizing. Our findings highlight a novel selection channel (i.e., increased dismissal) and treatment channel (i.e., increased bonus pay) that decrease CEO prosociality during industry downturns. We also highlight that foreign competition affected not only the firm's economic activities but also the CEO's psychological characteristics.
CEO reputation and shareholder voting
Thomas David, Alberta Di Giuli & Arthur Romec
Journal of Corporate Finance, December 2023
Abstract:
This paper examines the influence of CEO reputation on corporate proxy voting. Relying on prestigious business awards (through which the CEO is elevated to superstar status) as salient shocks to CEO reputation, we find that shareholders in aggregate, and mutual funds in particular, are more likely to vote with management (i.e., against shareholder proposals) when the CEO is a superstar. We use a battery of matching procedures to mitigate the concern that these results are driven by selection. We further show that shareholder proposals, especially contested ones and those with positive ISS recommendations, are significantly more likely to fail when the CEO is a superstar. Our results suggest that investors are sensitive to the external appraisal conveyed by the superstar status and prefer not to oppose management.
Sharing Names and Sharing Information: Incidental Similarities between CEOs and Analysts Can Lead to Favoritism in Information Disclosure
Omri Even-Tov et al.
University of California Working Paper, June 2023
Abstract:
When two people coincidentally have something in common (such as a name or birthday), they tend to like each other more and are thus more likely to offer help and comply with requests. This dynamic can have important legal and ethical consequences whenever these incidental similarities give rise to unfair favoritism. In a large-scale, longitudinal natural experiment, covering nearly 200,000 annual earnings forecasts over more than 25 years, we show that when a CEO and a securities analyst happen to share a first name, the analyst's forecast is more accurate. We offer evidence that name matching improves forecast accuracy due to CEOs privately, selectively sharing important information with name-matched analysts. This effect holds above and beyond the effects of gender- and ethnicity-matching. Additionally, we show that this effect is especially pronounced among CEO-analyst pairs who share an especially uncommon first name. Our research thus demonstrates how incidental similarities can give way to special treatment. Whereas most investigations of the effects of similarity consider only one-shot interactions, we use a longitudinal dataset to show that the effect of name matching diminishes over time with more interactions between CEOs and analysts. We also point to the findings of an experiment suggesting that favoritism born of sharing a name may evade straightforward regulation in part due to people's perception that name similarity would exert little influence on them. Taken together, our work offers insight into when private disclosures are likely to be made. Our results suggest that the effectiveness of regulatory policies can be significantly impacted by psychological factors shaping the context in which they are implemented.
Is your surname remunerative? Surname favorability and CEO compensation
Jay Heon Jung, Sonya Lim & Jongwon Park
Journal of Corporate Finance, December 2023
Abstract:
We find that CEOs with more favorable surnames receive significantly higher compensation. The estimated effect of surname favorability is unique and incremental to the documented effects of various firm, board, and CEO characteristics. CEOs with French or German surnames receive significantly lower compensation after the French and German governments' opposition to the Iraq war. Surname favorability is not associated with corporate investments, disclosure policies, or firm performances. The results are more pronounced for professional (i.e., non-founder) or short-tenured CEOs and for firms with lower institutional ownership. Surname favorability reduces the likelihood of forced CEO turnover following poor stock performance but is not associated with a CEO's self-serving behaviors. Our results suggest that the effect of surname favorability is attributable to inefficient contracting by the board of directors. Our findings have implications for corporate stakeholders who have committed to the efficient contracting of CEO compensations.
The tangled webs we weave: Examining the effects of CEO deception on analyst recommendations
Steven Hyde et al.
Strategic Management Journal, forthcoming
Abstract:
Organizations are punished by analysts and investors when material deceit by their CEO is uncovered. However, few studies examine analysts' responses to deceptive CEOs before their deceit is publicly known. We use machine learning (ML) models to operationalize the likelihood of CEO deception as well as analysts' suspicion of CEO deception on earnings calls. Controlling for analysts' suspicion of deception, we show that analysts are prone to assigning superior recommendations to deceptive CEOs, particularly those deemed as All-Star analysts. We find that the benefits of CEO deception are lower for habitual deceivers, pointing to diminishing returns of deception. This study contributes to corporate governance research by enhancing our understanding of analysts' reactions to CEO deception prior to public exposure of any fraud or misconduct.
From Transcripts to Insights: Uncovering Corporate Risks Using Generative AI
Alex Kim, Maximilian Muhn & Valeri Nikolaev
University of Chicago Working Paper, October 2023
Abstract:
We explore the value of generative AI tools, such as ChatGPT, in helping investors uncover dimensions of corporate risk. We develop and validate firm-level measures of risk exposure to political, climate, and AI-related risks. Using the GPT 3.5 model to generate risk summaries and assessments from the context provided by earnings call transcripts, we show that GPT-based measures possess significant information content and outperform the existing risk measures in predicting (abnormal) firm-level volatility and firms' choices such as investment and innovation. Importantly, information in risk assessments dominates that in risk summaries, establishing the value of general AI knowledge. We also find that generative AI is effective at detecting emerging risks, such as AI risk, which has soared in recent quarters. Our measures perform well both within and outside the GPT's training window and are priced in equity markets. Taken together, an AI-based approach to risk measurement provides useful insights to users of corporate disclosures at a low cost.