I have long held reservations about corporate governance research that hinges on event studies. (An event study is “an analysis of whether there was a statistically significant reaction in financial markets to past occurrences of a given type of event that is hypothesized to affect public firms’ market values.†An example of the sort of study that makes me a bit nervous is the study of derivative lawsuits done by Professors Fischel and Bradley in their 1986 paper titled “The Role of Liability Rules and the Derivative Suit in Corporate Law.â€) I have been leery of sharing my views regarding event studies, however, because it seems that most folks in my area of the academy have no similar reservations. Discretion being the better part of valor, I would prefer not to be viewed as standing alone off in left field. After spending some time a few afternoons ago chatting about my concerns with my mathematician friend John Armstrong, however, I am emboldened to share my thoughts here.
In a nutshell, I worry that event studies as traditionally conducted in the context of corporate governance undervalue the long term implications of and cumulative effects of various events. I worry that, relying on event studies, we might be quick to undervalue activity that does not immediately generate a market reaction but that, in the bigger picture, lays the foundation for achieving a meaningful goal.Â
For purposes of discussion here, let us use an event study designed as follows: A researcher wants to know what impact, if any, an institutional shareholder announcing its intention to withhold its affirmative vote on a slate of directors at an annual meeting has on the market. In the typical event study, the researcher would look at the stock price of the stock of the company at issue on the day before the institutional shareholder’s announcement and the researcher would look at the stock price the day after. If the stock price moved only minimally (in a way that was not “abnormal†for the market), the researcher would conclude that the institutional shareholder’s announcement did not matter to the market. If the researcher were being thorough, I suppose the researcher might also look at how many shareholders at the next annual meeting, a week hence, actually withheld their votes. If the number withholding was not abnormal, I imagine the researcher would believe his view of the irrelevance of the institutional investor’s pronouncement confirmed.
But what troubles me is that this ignores the long view. Stay with me: Assume that, 11 months after the above-mentioned institutional investor airs its concerns, an article appears in the WSJ reporting that the much-loved, long-serving CEO of the company at issue was arrested for drunk driving. Assume that, the day after the drunk driving announcement, the stock price of the company at issue dropped 20%. A researcher with an event study affinity might say that the drunk driving announcement moved the market. But what of the notion that the announcement PLUS the recall of the institutional investor’s concerns actually cumulatively moved the market? How do event studies account for time lag? How do event studies account for the accumulation of information? Surely just the announcement that the CEO was arrested for drunk driving should not, in and of itself, move the market. But I can easily imagine situations where that might just be the straw that broke the camel’s back, so to speak. Yet your typical event study would not account for that, would it? Moreover, what if, at the annual meeting several weeks later, an abnormal number of investors withheld their votes for the nominated panel of directors? Would we attribute that to the drunk driving instance? I cannot imagine we would. Yet would our scholarly memories be long enough to remember to attribute it to the institutional investor’s disavow of faith a year prior?
To be clear: I much admire the scholars in our field who are aggressively using all research tools, event studies and otherwise. I share my unease with event studies for what it is worth, which might be nothing. (My hope, however, is that a useful exchange of ideas will occur here.)
