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Expert advice in the presence of conflicts of interest: the case of star-crossed acquisitions

Abstract

Expert advice is presumed to be more valuable, but, when the expert has a conflict of interest, overcoming that conflict is difficult. We examine the performance of acquirers who hire an adviser that employs an expert—a star analyst—who covers the target and show that such “star-crossed” acquirers fare worse than other acquirers along multiple dimensions, including lower announcement returns and higher subsequent goodwill impairments. We consider various explanations for these outcomes, and the evidence strongly points toward star-crossed acquirers being unable to mitigate their advisers’ conflict of interest. Surprisingly, our analysis suggests that star-crossed managers are uninformed ex-ante about the low quality of the deals. Finally, we posit that a star-crossed adviser’s advantage increases with the opacity of the target firm’s accounting. Consistent with this, we find that, in star-crossed deals only, acquirer announcement returns decrease with target opacity.

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Notes

  1. For example, Kelly and Ljungqvist (2012), Loh and Stulz (2011), Mola and Guidolin (2009), and Irvine et al. (2007). Additionally, Cliff and Denis (2004), Krigman et al. (2001), and Clarke et al. (2007) examine star analysts in a mergers and acquisitions context.

  2. Although Global Analysts Research Settlements (GARS) resulted in restrictions to mitigate the influence of investment banking divisions over analysts, the settlement allowed interactions between analysts and investment bankers to discuss the merits of a transaction, industry trends, or the adequacy of disclosures. There are mandated limitations on the interactions, such as a requirement that counsel “chaperones” the meetings. (See the settlement for further details at https://www.sec.gov/litigation/litreleases/finaljudgadda.pdf.) Moreover, GARS did not explicitly prohibit discussions between analysts and issuers. Even so, research analysts are prohibited from soliciting business from companies. (See question 19 at https://www.sec.gov/divisions/marketreg/mr-noaction/grs110204.htm.)

  3. For either hypothesis, the star analyst’s level of direct involvement is irrelevant. All that is required is that the acquirer assumes that the opinion of the investment banking division is consistent with that of the star analyst.

  4. See Akdoğu (2011), Bhagat et al. (2005), Jovanovic and Braguinsky (2004), and Wang (2018).

  5. Strictly speaking, they frame it in opposite terms: that acquirer returns increase with target financial accounting quality.

  6. For example, Bradley et al. (2020) show that analysts that have overlapping career paths with executives in the firm they cover make more accurate earnings predictions. Green et al. (2014) show that analyst recommendations have more impact when the analyst’s firm has more conference-hosting relations with the firm they cover.

  7. In unreported results, we run a related test by limiting the sample to deals in which targets had star-analyst coverage. Again, the coefficient on Star-Crossed remains negative and significant.

  8. Within the top tercile of deals, the covariates are generally balanced across star-crossed and other deals. There are no significant differences in acquirer size, leverage, cash flow, and levels of institutional ownership. The main differences are that targets are larger and have more star analyst coverage in star-crossed bids, which is expected, as stars are attracted to larger firms.

  9. We thank an anonymous referee for the suggestion.

  10. We run several additional robustness checks. First, we include acquirer adviser bank fixed effects to test whether the results are due to certain banks being correlated with lower-quality deals (Bao and Edmans 2011) Second, to check whether Star-Crossed status simply proxies for targets with high levels of attention, we include the number of news articles about the target over the year prior to the deal announcement. In unreported results, the coefficient on star-crossed remains negative and significant in both tests.

  11. For completeness, we also estimate the model using a full information maximum likelihood approach, following Lokshin and Sajaia’s (2004), and find similar results.

  12. Inclusion of the Lee and So (2017) abnormal analyst coverage measure reduces our sample by roughly 200 observations, including 12 star-crossed observations. We re-run the tests excluding their measure and find quantitatively similar results.

  13. In robustness analysis, we also control for the information effects of the presence of a star analyst by restricting the sample. We eliminate targets that do not have star analyst coverage from a star working for a top 10 investment bank. This ensures that bidders could have chosen an adviser with a star following the target. We find qualitatively similar results in switching regressions with this subsample.

  14. We use an alternative instrument, the change in the number of star analysts covering the target, to provide further identification of the relation between returns and star-crossed deals. The change in stars on the target between two years and one year before the announcement of an acquisition is positively, significantly related to the probability of a star-crossed deal at the 1% level. While the change in stars is arguably a greater shock to the probability of forming a star-crossed deal, we believe the number of stars provides more exogenous variation, as star analysts initiate coverage well in advance of any potential deal on average.

  15. We also use a two-stage least-squares model to correct for the endogenous selection of investment banks with star analysts who cover the target firm. We find similar results overall as well as evidence of the relevance of our instrument. With an F-statistic of over 50, all typical Stock and Yogo (2005) critical values are met, providing strong evidence that the instrument relates to the choice of star-crossed deals.

  16. To be clear, research has identified methodological and endogeneity considerations that raise questions about the connection between competition and acquisition prices (Boone and Harold Mulherin 2008; Moeller et al. 2004). Even so, given our empirical setting, we believe that the possibility that competition affects prices in star-crossed deals should be investigated. We thank an anonymous referee for pointing us in this direction.

  17. In untabulated results, we test alternative measures of target premium: offer price versus 1) target share price 10 weeks prior to announcement, 2) maximum target share price within 52 weeks prior to announcement, and 3) minimum target share price within 52 weeks prior to announcement. Across all three alternatives, we find no evidence of higher target premia for star-crossed deals.

  18. Separately, we categorize deals in which the star-crossed acquirer adviser has a star analyst covering the target and a star analyst covering the acquirer as dual-star-crossed. In this case, the target analyst and the acquirer analyst could be the same person, so the super-star-crossed observations are a subset of dual-star-crossed observations. When we compare the mean announcement CAR of the dual-star-crossed sample to all other star-crossed deals, we again find the difference in average announcement CARs is statistically insignificant.

  19. Unfortunately, the cumulative evidence does not offer clear insights on the exact nature of the decision-making. On the one hand, the acquirer may defer to the star-crossed adviser in selecting a target, and the adviser strategically may select a firm that their star analyst covers to increase the probability of deal completion. On the other hand, the acquirer may also select the target first, and the star-crossed adviser may increase the likelihood that a low-quality deal receives board and shareholders’ approval. A priori, both scenarios are plausible, and both lead to deal underperformance.

  20. In unreported results, we test whether star-crossed CEOs receive differentially greater changes to their post-acquisition compensation. Multivariate analyses, controlling for acquirer, target, and deal characteristics, do not indicate that hiring a star-crossed bank yields higher increases in compensation relative to all other acquiring CEOs’ increases. The interpretation here is that, while acquisitions may on average be associated with increases in the CEO’s compensation, star-crossed CEOs do not receive even greater increases in compensation.

  21. Results are robust to using a three-year window for turnover.

  22. Some deals have multiple advisers, some of which may be star-crossed and some of which may not be. If any adviser is star-crossed, the star-crossed deal indicator variable equals 1.

  23. With a transparent (i.e., not opaque) target, the bidding manager has more agency to make an informed decision independent of the star-crossed adviser’s recommendation. Similarly, with a nonstar-crossed adviser, the bidding manager may be reluctant to take on an opaque target, given the relationship between target information asymmetry and acquirer announcement returns.

  24. If the target is transparent, an informed manager cannot sell the board on the deal with or without a star-crossed adviser, since transparency means the board will know the deal quality in advance. If the target is opaque, a nonstar-crossed adviser may lack the credentials to persuade the board to take on the deal. Accordingly, the empire-building manager should want an opaque target for which he or she can hire a star-crossed adviser, since this is the path of least resistance for gaining approval for an acquisition.

  25. We refer the reader to these papers for precise definitions.

  26. For robustness, we use several alternative measures of target opacity from the earnings management literature. Specifically, we follow Roychowdhury (2006) in looking for manipulations with real earnings by taking “abnormal” measures of the following: cash flow scaled by assets, cost of goods sold scaled by assets, inventory change scaled by assets, production costs scaled by assets, and discretionary expenses scaled by assets. Abnormal is defined as the residual from Roychowdhury’s (2006) models of these variables. Our unreported results are generally consistent with our reported results using accruals, although in a minority of specifications the interaction variable is insignificant.

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Acknowledgments

We thank conference participants from the Conference of Empirical Legal Studies Europe, Quantlaw, FMA 2018, the Manne Forum at George Mason Law School, and the Mid-Atlantic Faculty Forum, NBLSC as well as seminar participants at University of Oklahoma, American University, University of Washington, Tel Aviv University, University of Adelaide, and University of Melbourne. We are grateful for comments from Vladimir Atanasov, Brant Christensen, Janya Golubeva, Avner Kalay, Bin Li, Hamed Mahmudi, William Megginson, and Micah Officer.

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Correspondence to Jordan B. Neyland.

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Aharoni, G., Lim, B., Litov, L.P. et al. Expert advice in the presence of conflicts of interest: the case of star-crossed acquisitions. Rev Account Stud (2022). https://doi.org/10.1007/s11142-022-09679-z

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Keywords

  • Analyst coverage
  • Star analysts
  • M&A
  • Goodwill
  • Acquisition advisers

JEL classifications

  • G24
  • G34
  • K22
  • M41