1. Introduction Hypothesys and Methodology Results Conclusion
The Network Centrality of In‡uential Bankers:
a new Capital Structure Determinant
João Mergulhão (Universidade Nova de Lisboa)
João Amaro de Matos (Universidade Nova de Lisboa)
Miguel Ferreira (Universidade Nova de Lisboa, European Corporate
Governance Institute)
Pedro Matos(University Southern California)
January 16, 2010
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2. Introduction Hypothesys and Methodology Results Conclusion
The paper in one slide
The presence of bankers-directors on the board and capital
structure
In‡uential bankers and capital structure
Social Network Analysis to measure in‡uence
Role of Bankers in information transmission mechanism
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3. Introduction Hypothesys and Methodology Results Conclusion
Outline
Introduction
Bankers and information asymmetry
Social Networks and information asymmetry
Social Networks and …nancial markets
Hypothesys and Methodology
Network construction and centrality measures
Estimation
Results
Summary
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4. Introduction Hypothesys and Methodology Results Conclusion
Introduction
Bankers and Information Asymmetry
Banks as delegated monitors [Schumpeter (1939) and
Diamond (1984)]
More e¤ective monitoring mechanism then loan covenants
[Williamson (1998), Krozner and Strahan (2001)]
Banker-directors provide …nancial expertise [Mace (1971),
Lorsh and MacIver (1989)]
Lower costs of funds [James (1987), Berger and Udell (1995);
Fama (1985), Leland and Pyle (1997), Kracaw and Zenner
(1998), Kroszner and Strahan (2001)]
Positive correlation between the …rm’ capital structure and
s
the presence of banker-directors [Byrd and Myzruchi (2005),
Ciammarra (2006)]
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5. Introduction Hypothesys and Methodology Results Conclusion
Network Centrality
Social Networks and Information Asymmetry
Social relationships may prevent market failure
[Podolny (1994)]
Social networks screen and select relevant information
[Burt (1997)]
Social networks lower information-gathering costs
[Nahapiet and Ghosal (1998)]
Creation and maintenance of information ‡ows increases
information set [Nohria (1992)]
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6. Introduction Hypothesys and Methodology Results Conclusion
Network Centrality
Social Networks in Financial Markets
Politically connected boards add value to …rms [Goldman,
Rocholl and So (2009)]
Social ties and venture capital [Shane and Cable (2002)]
Similar corporate investment decisions [Fracassi (2008)]
Fund managers portfolio decisions [Cohen, Frazzini and
Malloy (2009)]
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7. Introduction Hypothesys and Methodology Results Conclusion
Bankers in‡uence and capital structure
Hypothesis 1 The presence of a banker on the board increases the
leverage of a …rm
Hypothesis 2 The more in‡uential a banker-director, the higher
the leverage of a …rm
Hypothesis 3 The higher the level of information asymmetry, the
bigger the impact of the presence (or in‡uence) of a banker on the
leverage of a …rm
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8. Introduction Hypothesys and Methodology Results Conclusion
Constructing the network
Board of Directors Data
BoardEx Reports
historical linkages between boards of di¤erent …rms
Information ‡ows between individuals
Construction of a new network
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9. Introduction Hypothesys and Methodology Results Conclusion
Constructing the network
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10. Introduction Hypothesys and Methodology Results Conclusion
Constructing the network
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11. Introduction Hypothesys and Methodology Results Conclusion
Constructing the network
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12. Introduction Hypothesys and Methodology Results Conclusion
Measuring In‡uence
Centrality Measures
Degree
Closeness
Betweeness
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13. Introduction Hypothesys and Methodology Results Conclusion
Measuring In‡uence
Measuring In‡uence: back to the …rm dimension
Aggregate the centrality measures to the …rm level.
Bankers-directors: for each …rm, the corresponding centrality
measure is the maximum value of the banker-director in the board.
If there is no banker-director, the centrality measure is 0.
1 Firm is covered by Boardex and has no banker seated on the
board
2 Firm is not covered by Boardex
We will assume that if we have information on the board size,
then that …rm is covered by Boardex.
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14. Introduction Hypothesys and Methodology Results Conclusion
Financial Data
Merging …nancial and social network data
Financial data
Datastream, Compustat
Final sample
US …rms Listed in WorldScope
from 2001 to 2006
all variables are winsorized at 1% level.
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15. Introduction Hypothesys and Methodology Results Conclusion
Financial Data
Estimation
LRt +1,i = β0 + β1 Sizet,i + β2 Pro…tabilityt,i + β3 Asset Tangibilityt,i
+ β4 Asset Speci…cityt,i + β5 Growth Opportunitiest,i
+δBankert,i
+γ1 Industry Dummiest,i + γ2 Year Dummiest
Total debt
LRt +1 : Leverage ratio= Maket capitalization
Size : log (sales)
Tangible Assets
Asset Tangibility : Total Assets
R&D expenses
Asset Speci…city: Total Sales
Pro…tability: Return on Assets
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16. Introduction Hypothesys and Methodology Results Conclusion
Financial Data
Estimation
LRt +1,i = β0 + β1 Sizet,i + β2 Pro…tabilityt,i + β3 Asset_Tangibilityt,i
+ β4 Asset_Speci…cityt,i + β5 Growth_Opportunitiest,i
+δBankert,i
+γ1 Industry_Dummiest,i + γ2 Year_Dummiest
Banker
the presence of banker on the board (hypothesis 1)
centrality measures (hypothesis 2)
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17. Introduction Hypothesys and Methodology Results Conclusion
Financial Data
Estimation
LRt +1,i = β0 + β1 Sizet,i + β2 Pro…tabilityt,i + β3 Asset_Tangibilityt,i
+ β4 Asset_Speci…cityt,i + β5 Growth_Opportunitiest,i
+δ1 Bankert,i + δ2 Bankert,i Opacityt,i
+γ1 Industry_Dummiest,i + γ2 Year_Dummiest
Opacity (hypothesys 3) :
Size
Tangibility
Rating
S&P500
Illiquidity: Amihud’ (2002)Illiquidity measure
s
Accruals quality: Dechow and Dichev (2002)
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18. Introduction Hypothesys and Methodology Results Conclusion
Financial Data
Endogeneity
Board composition and capital structure are simultaneously
chosen
OLS fails with endogenous regressors.
IV is not a solution for endogenous binary regressors (Imbens
and Angrist 1994, Angrist, Imbens and Rubens 1996)
Solution: Average Treatment E¤ects
Instruments: Board size, Size, Leverage, Market to Book, Asset
Tangibility
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19. Introduction Hypothesys and Methodology Results Conclusion
Results
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20. Introduction Hypothesys and Methodology Results Conclusion
Results
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21. Introduction Hypothesys and Methodology Results Conclusion
Results
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22. Introduction Hypothesys and Methodology Results Conclusion
Conclusion
We study relation between the presence of bankers on boards
and capital structure.
Presence of bankers in the board increases the leverage ratio
E¤ect is magni…ed by the in‡uence of the banker
E¤ect of banker’ social infuence on the leverage ratio
s
increases with …rm’ opacity
s
role of bankers on the information transmission mechanism.
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