Hedge Fund Activism and Their Long-Term Consequences: Unanswered Questions to Bebchuk, Brav and Jiang

13 Pages Posted: 17 Sep 2014

See all articles by Yvan Allaire

Yvan Allaire

Institute for Governance of Private and Public Organizations (IGOPP)

Francois Dauphin

Institute for Governance of Private and Public Organizations (IGOPP)

Date Written: August 18, 2014

Abstract

In our paper “Activist” hedge funds: creators of lasting wealth? What do the empirical studies really say?” (available here), we asked Lucian Bebchuk, Alon Brav and Wei Jiang questions of the sort that any referee/reviewer for a professional journal would raise about their paper The Long-Term Effects of Hedge Fund Activism. Their paper’s aim is to examine the empirical basis for “the long-standing claim that activist interventions are followed by declines in long-term operating performance”.

The reply we got from Professor Bebchuk was essentially that he had already answered all our questions in his reply to Wachtell Lipton “Don’t run away from the evidence” and that our paper was not academically rigorous because “it expresses an opposition to relying on empirical evidence”. He is wrong on both counts.

First, we must inform Bebchuk that we were once of the faith, believers in the power of statistical analysis to prove and disprove any and all assertions about social phenomena. We were, in short, empirical positivists who, like Bebchuk et al, asserted the superiority of statistical evidence and quantitative analysis over experience-based empirical knowledge and derided the “self-reported impressions of business leaders”.

After running hundreds, if not thousands, of multivariate analyses since my days at MIT, having taught for years doctoral seminars on multivariate analysis, I (Allaire) grew increasingly doubtful that the tool kit of multivariate analysis always provided a superior grasp of complex social phenomena.

The ease of use and the power of computer algorithms produced a surfeit of papers with exaggerated claims, which did not withstand the scrutiny of expert analysis or the passage of time.

Too often, today’s study and results are contradicted by tomorrow’s study. Results vary and swing in significance as a consequence of slight changes in the definition of sample and variables, in the structure of equations, in included/omitted variables, in ways of dealing with several statistical pathologies, and so on.

For instance and for the benefit of readers who are not specialists in esoteric statistical analysis, let’s examine briefly the issue of what causes deadly car accidents.

Several dozen statistical studies have been carried out to establish the correlates of deadly car accidents. Some find that speed limits do not have any statistically significant impact, other studies actually do; some find that seat-belt laws have an impact, others don’t; generally, studies agree on the negative role of alcohol consumption but in some studies, this variable is just barely significant; age of driver is sometimes a significant factor, sometimes not; sex of driver also; even use of cell phones while driving is sometimes a significant factor, in other studies, it is not.

To try to fully account for the multiple factors, some studies include up to 50 variables (time of accident, weather conditions, lighting conditions, road conditions, etc.). Of course, there is high likelihood of interactions (of the non-linear type) among variables (time of accident, weather conditions, speed, alcohol consumption for instance may well interact in complex fashion). But to include all potential interactions would consume large number of degrees of freedom and make interpretation of results very difficult.

Another type of empirical evidence comes from the police investigators who have examined hundreds of deadly accidents and developed a sophisticated understanding of the key contributing factors.

What should policy makers do? Rely on the conclusions, variable in time, contradictory across studies, of researchers far removed from actual deadly car accidents or should they listen to the empirical observations of investigators with years of experience in the field?

Now to our case. Bebchuk, Brav and Jiang claim to have conclusively shown that “activist interventions are followed by improved operating performance during the five-year period following the intervention”.

Their findings were broadcast widely, including in a Wall Street Journal op-ed by Professor Bebchuk (August 7th 2013).

In spite of the limited aim for their study (“whether the long-standing claim that activist interventions are followed by declines in long-term operating performance”), Bebchuk, Brav and Jiang get carried away and associate hedge fund intervention to the subsequent performance of companies long after the hedge funds have sold their shares.

One must examine closely the empirical basis for such claims of a quasi-causal relationship as one should for a study purporting to show that hedge funds do great harm.

Keywords: activism, hedge funds, long term consequences, Bebchuk, Brav and Jiang

Suggested Citation

Allaire, Yvan and Dauphin, Francois, Hedge Fund Activism and Their Long-Term Consequences: Unanswered Questions to Bebchuk, Brav and Jiang (August 18, 2014). Available at SSRN: https://ssrn.com/abstract=2496475 or http://dx.doi.org/10.2139/ssrn.2496475

Yvan Allaire (Contact Author)

Institute for Governance of Private and Public Organizations (IGOPP) ( email )

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514 439-9305 (Fax)

Francois Dauphin

Institute for Governance of Private and Public Organizations (IGOPP) ( email )

1000, de la Gauchetiere St. West, Suite 1410
Montreal, Quebec H3B 4W5
Canada
514-439-9301 (Phone)

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