Board declassifications and firm value: Have shareholders ...Emiliano M. Catan & Michael Klausner GCGC -June 2, 2018 0. Background •Over the past 15 years, several hundred publicly

Board declassifications and firm value: Have shareholders and boards really destroyed billions in value?

Emiliano M. Catan & Michael KlausnerGCGC - June 2, 2018

0

Background•Over the past 15 years, several hundred publicly-traded firms

destaggered their boards of directors (often in response to shareholder proposals).

2

Background

3

0.0

5.1

.15

.2.2

5.3

.35

.4.4

5.5

.55

.6.6

5

1995 2000 2005 2010 2015Year

Fraction of firms with Staggered Boards

6 5 46

2 31

13

23

30

36

31 32

20

42

29

39

42

31

16

010

2030

40

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Number of Board Declassifications

Background•Over the past 15 years, several hundred publicly-traded firms

destaggered their boards of directors (often in response to shareholder proposals).• The declassification wave has received overwhelming

support from shareholders in general, and from the big institutional investors in particular.

4

Background• Recent scholarly work (e.g., Cremers, Litov & Sepe (2017),

Cremers & Sepe (2016)) suggests that these declassifications led to economically significant drops in firm value.• On the basis of their empirical findings, Cremers & Sepe propose

1. Amending 14a-8 to make declassification proposals inadmissible.

2. Adopting a staggered board structure as a “quasi-mandatory” rule.

• But is that what the evidence really tells us?

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• If indeed the declassification wave was so harmful…• Directors should be blamed for being

ignorant/spineless.• It would raise fundamental questions about the

increasingly institution-centric corporate governance system adopted by the US over the past decades.

Why the answer matters…

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Caveat: spirit of the exercise• We do not necessarily…• endorse the use of Q as the best/single outcome variable to determine the

value implications of governance.• believe that the presence of staggered boards/the adoption of

declassifications is “exogenous”.• However, most of the recent debate on the effect of staggered boards

has done both.• The spirit of the exercise is to show that, even under the (heroic?)

assumptions that (i) destaggerings are plausibly “exogenous” and that (ii) Q is a good proxy for shareholder value, the results do not withstand closer scrutiny.

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Sample• Collected data on board structure over 1996-2015 for all firms ever in

S&P1500 (over 2200 firms, 28K firm-years, after excluding financials, utilities, firms with dual-class shares).• Matched with:• Compustat-CRSP for accounting data• CRSP for stock returns• Shark Repellent for precatory proposals

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Results 1

Firm FEYear FE “Years since Public” FE

6.5% of average Q

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(or around $350B in value)

0.0

5.1

.15

.2.2

5.3

.35

.4.4

5.5

.55

.6.6

5

1995 2000 2005 2010 2015Year

Fraction of firms with Staggered Boards

Potential source of concern

10


11


12

0.1

.2.3

.4

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

Year

Very Large Large Small

Fraction of firms with staggered boards targeted by SH proposals

1.5

22.

53

3.5

1995 2000 2005 2010 2015Year


Sample: firms that always had annual boardAverage value of Q


13

11.

52

2.5

33.

5

1995 2000 2005 2010 2015Year


Average value of Q


14

1.5

22.

53

3.5

1995 2000 2005 2010 2015Year

Very Large & Staggered Very Large & AnnualLarge & Staggered Large & AnnualSmall & Staggered Small & Annual

Average Value of Q

11.

52

2.5

33.

5

1995 2000 2005 2010 2015Year


Average value of Q


1 5

1.5

22.

53

3.5

1995 2000 2005 2010 2015Year


Average Value of Q1.

52

2.5

33.

5

1995 2000 2005 2010 2015Year


Average value of Q

~10% of the sample~20% of the sample~70% of the sample

If our conjecture is right…

•Naïve regression should suggest that most of the ostensible effect of declassifications is driven by the very large firms (and show substantial pre-treatment trends).• That statistical association between staggered boards

and Q should be attenuated in a regression that compares apples to apples.

1 7

Results 2 (naïve)

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Results 2 (naïve)

1 9

Sum=0.156p-value<.05(or 7% of firm value)

Sum=0.62p-value <.001(or 29% of firm value)$ 1 trillion!!!

-1-.5

0.5

1

-6-5-4-3-2-1 0 1 2 3 4 5 6Years around destaggering

Very Large Firms

-1-.5

0.5

1


Large Firms

-1-.5

0.5

1


Small Firms

Tobin's Q - Within-firm Dynamics Around Declassification

Lags & Leads (naïve)

20

Results 2 (apples-to-apples)

21

Results 2 (apples-to-apples)

22

Lags & Leads (apples-to-apples)

23

-1-.5

0.5

1


Very Large Firms

-1-.5

0.5

1


Large Firms

-1-.5

0.5

1


Small Firms

Tobin's Q - Within-firm Dynamics Around Declassification-1

-.50

.51


Very Large Firms

-1-.5

0.5

1


Large Firms

-1-.5

0.5

1


Small Firms

Tobin's Q - Within-firm Dynamics Around Declassification

Event study: management declassification proposals

• Event date: date of filing of proxy statement• Model: four factor

2 4

Event study: first precatory declassification proposal targeting firm• Event date: date of filing of proxy statement• Model: four factor

2 5

Robustness + Additional Details

• Results are robust:•More accurate construction of size-buckets by using

“stacked cohort approach” (Gormley & Matsa, RFS 2011)•NN-matching• Calendar-time portfolio analysis

2 6

Conclusion• The sky is probably not falling.•We should have some healthy skepticism about recent

claims suggesting that declassifications destroyed hundreds of billions of dollars in value.•Methodologically, scholars running panel regressions where Q is the outcome variable should be cautious about differential secular trends in stock prices.

Additional Materials

Do results depend on when the size buckets were formed?

• Cohort-based approach (Gormley & Matsa, RFS 2011)• For each year c, we could separately estimate the effect of

declassifications of firm value for firms that destaggered during c.• Treatment firms: firms that destaggered in year c• Control firm-years: firms that were part of the sample in c and c-1 and• Never switched board structure (all firm-year observations)• Switched board structure at some year c’>c (firm-year observations until c’-1)

• We sort treatment and control firms into size buckets according to their decile of market capitalization as of c-1• Call all those firm-year observations “cohort c”

2 9


• Although we could estimate one separate estimate reflecting the effect of declassifications for firms in cohort c, we want to aggregate all those estimates into one.• To do that, we form a database that ”stacks” the different cohorts,

and estimate

3 0

Not subindexed by c

Subindexed by c


31


32


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Another robustness check: N-N matching• For every firm that destaggered, we look (with replacement) for the

nearest neighbor that within the same 2-digit SIC industry that did not declassify in that year or any earlier year along the following dimensions:• Qt-1

• Qt-2

• Qt-3

• Qt-4

• Qt-5

• Market capt-1

• (R&D/Sales)t-1

• Firm age

• We follow both members of the matched pair between year -5 and year +5 surrounding the destaggering (or pseudo-destaggering).• If either firm drops out of the sample (or the control firm destaggers), the

matched pair is also dropped at that point in time. 3 4

Some examplesTreatment Matched control Cohort

RO B ERT H A LF IN T L IN C H EN RY (JA C K ) & A SSO C IAT ES 2 0 0 3

B R ISTO L-M Y E RS SQ U IB B CO SC H ER IN G -P LO U G H 2 0 0 3

CO C A -CO LA CO P E P SICO IN C 2 0 0 3

O M N ICO M G RO U P ELEC T RO N IC D ATA SYST EM S CO R P 2 0 0 3

G R EAT LA K ES C H EM IC A L CO R P FER RO CO R P 2 0 0 3

H A SB RO IN C K ID B R A N D S IN C 2 0 0 3

T EN ET H EA LT H C A R E CO R P H EA LT H SO U T H CO R P 2 0 0 3

P FIZE R IN C LILLY (ELI) & CO 2 0 0 3

R EEB O K IN T ER N AT IO N A L LT D A P TA RG RO U P IN C 2 0 0 3

D E LL T EC H N O LO G IES IN C N ETA P P IN C 2 0 0 3

M ID W AY G A M ES IN C A N SYS IN C 2 0 0 3

B ELLSO U T H CO R P D IR EC T V 2 0 0 4

D O W C H E M IC A L D U P O N T (E I) D E N E M O U RS 2 0 0 4

ED O CO R P C U B IC CO R P 2 0 0 4

FED EX CO R P SO U T H W EST A IR LIN ES 2 0 0 4

G ER B ER SC IEN T IF IC IN C M ILA C RO N IN C 2 0 0 4

STA RW O O D H O T E LS& R ESO RTS W R LD H ILTO N W O R LD W ID E H O LD IN G S 2 0 0 4

M E RC K & CO A B B O T T LA B O R ATO R IES 2 0 0 4

SA FE W AY IN C K RO G E R CO 2 0 0 4

AT & T IN C V ER IZO N CO M M U N IC AT IO N S IN C 2 0 0 43 5

NN-Matching

37

910

1112

Lagg

ed L

og(M

ktca

p) fo

r Tre

atm

ent fi

rms

7 8 9 10 11 12Lagged Log(Mktcap) for Control firms

3 8

910

1112

Lagg

ed L

og(M

ktca

p) fo

r Tre

atm

ent fi

rms

7 8 9 10 11 12Lagged Log(Mktcap) for Control firms

Pfizer & Eli Lilly


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Have management/SHs reacted to the recent findings?

40

82.93 82.7378.04 78.76

74.75 75.91 75.53 76.300

2040

6080

2010 2011 2012 2013 2014 2015 2016 2017

Percent of outstanding shares voting 'for'Management Proposals to Declassify

97.73 97.63 97.11 97.01 97.51 96.60 96.55 97.360

2040

6080

100

2010 2011 2012 2013 2014 2015 2016 2017

Percent of votes cast voting 'for'Management Proposals to Declassify

Puzzle: what is going on?

41

Did declassifications affect R&D-intensive firms more intensely?

4 2

1 if firm had R&D/Sales in top quartile as of 2002 (or the closest year available)

R&D Intensive

Low RD

Small

Large

VeryLarge X

R&D Intensive

Low RD

Small

Large

VeryLarge X

R&D Intensive

Low RD

Small

Large

VeryLarge X

Are these results also confounded by differential secular trends in value?

43

Are these results also confounded by differential secular trends in value?

44

Staggered boards & R&D intensity: comparing apples to apples

45

R&D Intensive

Low RD

Small

Large

VeryLarge X

R&D Intensive

Low RD

Small

Large

VeryLarge X

Documents

Board declassifications and firm value: Have shareholders ...Emiliano M. Catan & Michael Klausner GCGC -June 2, 2018 0. Background •Over the past 15 years, several hundred publicly