Darryl Laws

   I chose this particular article to review because the topic aligns with my dissertation research topic; What causes irrational human behavior in mergers and acquisitions and to what economic extent does these behaviors impact the premium price paid / sold for the acquisition?  The author’s two independent variables that are relative to my research question are: CEO overconfidence and CEO hubris. Furthermore, their article fits the academic paper selection criteria because it uses a binary logistic regression method as the main empirical methodology to look at the impact on the dependant variable, the premium price paid for acquiring companies. 

Introduction. The biggest challenge for the analysis of CEO overconfidence is; “How to construct a plausible measure of overconfidence?” Biased beliefs naturally defy direct and precise measurement (Malmendier and Tate, 2004). Malmendier and Tate’s (2004) previous work proposes two approaches to measurement; 1) the first is a revealed beliefs argument. They infer CEOs’ beliefs about the future performance of the company from their personal portfolio of stock options transactions, (incentive compensation), 2) the second approach captures how outsiders, the public and press, perceive the CEO. They classify CEOs as overconfident based on their portrayal in the press. This measure was proposed by Malmendier and Tate in 2005, builds on the perception of outsiders. The authors conducted a study of Forbes 500 companies which was comprised of their collecting data on how the press portrays each of the CEOs during a sample period 1980 to 1994. They search articles referring to the CEOs in The New York Times, Business Week, Financial Times, The Economist and The Wall Street Journal. For each CEO and sample year, they recorded the number of articles containing the words confident or confidence; the number of articles containing the words optimistic or optimism; and the number of articles containing the words ‘reliable’, cautious, conservative, practical, frugal, or steady. Then they hand-checked the terms that were used to describe the CEO in question describing the CEO as not confident or not optimistic. They then constructed an indicator, TOTAL dummy, equal to 1 if a CEO is more often described as confident and optimistic or as reliable, cautious, conservative, practical, frugal, or steady. They found that This alternative indicator of CEO confidence is significantly positively correlated with their portfolio measures.

Darryl Laws

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Darryl Laws

  Their model is binary because there are two kinds of variation that they use to identify the effect of overconfidence on acquisitiveness, cross-sectional and within-company variation. Malmendier and Tate (2008) solve their regression equation using three estimation procedures: 1) a logit regression, makes use of both types of variation, 2) a logit regression with random effects, also makes use of both types of variation but, it explicitly models the effect of the firm, rather than the CEO, on acquisitiveness. I noted that if the estimated effects of overconfidence in the logit equation are due to company effects, they should expect to see a decline in their estimates if they include random effects. The remainder of their solution uses a logit regression with fixed effects. This regression equation makes use only of the second type of variation, the effect of overconfidence on acquisitiveness using only variation between overconfident and rational CEOs within a particular firm. Fo...
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