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Executive Board Composition and Bank Risk Taking Allen, N. Berger, Thomas Kick, Klaus Schaeck Discussant: Dennis Veltrop (De Nederlandsche Bank/University.

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Presentation on theme: "Executive Board Composition and Bank Risk Taking Allen, N. Berger, Thomas Kick, Klaus Schaeck Discussant: Dennis Veltrop (De Nederlandsche Bank/University."— Presentation transcript:

1 Executive Board Composition and Bank Risk Taking Allen, N. Berger, Thomas Kick, Klaus Schaeck Discussant: Dennis Veltrop (De Nederlandsche Bank/University of Groningen) Corporate Governance of Financial Institutions Conference November

2 Summary of the paper Linking management board composition to bank risk taking. Essentially you argue that age, gender, and education of the management board affect variability of bank performance. You use data from German banks (two-tier structure) to test this.

3 What I like You try to open up the black box of the behavior of management teams in the banking industry. A very interesting topic with a large practical relevance. You are thorough in your analyses. In itself the difference-in-difference estimator that you use is a very interesting way to analyze the effect of board composition on performance.

4 Comments Literature Mechanisms Diversity Method

5 Literature You state that little attention has been given to socioeconomic composition of management boards (top management teams). – Upper echelon scholars (Hambrick and Mason, 1984, and onwards) have done exactly this. – Hundreds of papers on this topic in the field of management. So, why not use research from the field of management? There is SUBSTANTIAL overlap (e.g. papers published in strategic management journal, academy of management journal and so on).

6 Mechanisms You do not study nor convincingly argue why management board composition in terms gender, age, and education affect bank risk taking.

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8 8 Board characteristics Organizational Performance Profit per share, profit/sales ratio, development stock price, return on assets Size, Independence, gender, nationality age, experience, (educational) background “Black box” Board processes

9 Mechanisms H1: risk taking decreases in board age This is because younger individuals make more mistakes and are inexperienced. -I can argue the exact opposite backed up with literature that younger executives still have a career trajectory and therefore take LESS risk. So the reasoning has to be convincing. -Why not use tenure instead of age as an indicator of experience?

10 Mechanisms For gender and education you both hypothesize a negative and positive relationship. All in all I think there is a serious problem of spurious relationships.

11 Diversity – You do not study the effects of diversity. – You study the effects of the mean level of age, gender, and education. – That’s different.

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13 Operationalization You do not study age and education. – You study the effect of management board members holding a PhD, that’s different than education. – For age you construct the treatment group of banks that observe a decrease in average board age following mandatory retirement => consequently you do not compare age, but you compare whether a MB member has retired. That is different than studying the effects from age.

14 Analysis Your sample is reduced from observations to 6.440, 3.073, and for age, gender and education analyses respectively. Multiple changes: You consider one board change per bank, and you delete banks whose board change of any one type coincides with another board change. – What happens when two younger, female, PhD’s are appointed to the board in two subsequent years?

15 Difference in difference estimator You compare your ‘treatment group’ with the ‘control group’ to alleviate endogeneity concerns. Your treatment group contains the group with board changes and your control group contains the group without board changes. But the board change itself is not exogenous and is not randomly imposed.

16 Comments Not new, at least not how it is positioned now. Spurious relationships You do not study diversity Difference is difference estimator may suffer from endogeneity as well.


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