Efect of Change in Compensation

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Master Thesis I

Effects of Changes in Executive Compensation

In the Light of the Financial Crisis


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Abstract

Executive compensation is one of the most widely discussed topics since the latest economic

turmoil. Shortly after the S&P 500 decreased by almost 50 percent in fall 2008, 70 percent of the

200 largest corporations in the United States reported changes in compensation packages for

their executives. This study gives the reader an empirical insight into the stock market reaction

following the announcement of these changes. Applying the event study methodology weanalyzed 69 corporations and the corresponding stock price movements around the

announcement date. The results show that the market does not react significantly on the

announcement of changes in executive compensation. Shareholders do not seem to perceive

these adjustments as fundamental and do not seem to expect an additional increase in the firms

future value following the change. Nevertheless the study identifies that a decrease in short-term

incentives is perceived as negative by the market. This reaction is oppositional to the public

discussion which suggests that short-term incentives should be limited. The paper provides an

indebt analysis of the difference in market reaction following short- and long-term incentive

changes. Furthermore the results substantiate that companies with a poor past performance and

profitability react stronger upon the announcement of changes in executive compensation.

Keywords: Executive Compensation, Short-term Incentive, Long-term Incentive, Market

Reaction, Financial Crises, Agency Problems, Shareholder, Stakeholder, Event Study

Tutor: Hossein Asgharian, Professor, Department of Economics, Lund University, Sweden

Acknowledgements:


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Table of Content

Glossary ........................................................................................................................................... I

Tables .............................................................................................................................................. II

Exhibits ......................................................................................................................................... III

1 Introduction ............................................................................................................................. 1

1.1 Background ...................................................................................................................... 1

1.2 Research Question ............................................................................................................ 2

1.3 Study Outline.................................................................................................................... 3

2 Theoretical Framework............................................................................................................ 4

2.1 Efficient Market Hypothesis and Abnormal Returns ....................................................... 4

2.2 Agency Theory and Signaling .......................................................................................... 5

2.3 Compensation ................................................................................................................... 6

2.4 SEC Disclosure Rule ........................................................................................................ 9

2.5 Previous Research .......................................................................................................... 10

3 Methodology .......................................................................................................................... 12

3.1 Data Sample ................................................................................................................... 12

3.2 Event Study Design ........................................................................................................ 17

3.3

Measuring Normal Returns ............................................................................................ 19

3.4 Measuring Abnormal Returns ........................................................................................ 20

3.5 Test of Significance ........................................................................................................ 22

3.6 Cross-sectional Analysis ................................................................................................ 26

4 Empirical Results ................................................................................................................... 27

4.1 Hypothesis 1 ................................................................................................................... 27

4.2 Hypothesis 2 ................................................................................................................... 28

4.3 Hypothesis 3 ................................................................................................................... 31

5 Evaluation .............................................................................................................................. 34

5.1 Hypothesis 1 ................................................................................................................... 34

5 2 H th i 2 37


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Glossary

APT Arbitrage Pricing Theory

AR Abnormal Return

CAPM Capital Asset Pricing Model

CAR Cumulative Abnormal ReturnsCAR Average Cumulative of Abnormal ReturnsCEO Chief Executive Officer

CF Cash Flow

CIC Change-in-Control

DEF 14A SEC Proxy Statement

EBIT Earnings before Income and Taxes

EBITA Earnings before Income and Taxes and Amortisation

EPS Earnings per Share

ESOPs Employee Stock Ownership Plans

IID Identical and Independently Distributed

L Length

LLC Limited Liability Company

LTI Long-Term IncentivesNEO Named Executive Officers

NI Net Income

OI Operating Income

OLS Ordinary Least Squares

PRE 14A SEC Preliminary Proxy Statement

S&P 500 Index of the 500 largest corporations by market capitalisation in the United States

SARs Stock Appreciation RightsSERP Supplemental Executive Retirement Program

SEC U.S. Securities and Exchange Commission

STI Short-Term Incentives

T Time


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Tables

Table 1: Compensation ................................................................................................................... 7

Table 2: Changes in STI Performance Measures .......................................................................... 13

Table 3: Changes in LTI Mix........................................................................................................ 14

Table 4: Changes in LTI Performance Measures ......................................................................... 14

Table 5: Event Windows ............................................................................................................... 18

Table 6: Major Changes ................................................................................................................ 27

Table 7: Long-Term Incentive Changes ....................................................................................... 29

Table 8: Short-Term Incentive Changes ....................................................................................... 30

Table 9: Differences in Abnormal Returns ................................................................................... 31

Table 10: Results Cross Sectional Analysis Performance ............................................................ 32

Table 11: Results Cross Sectional Analysis Profitability ............................................................. 33


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Exhibits

Exhibit 1: Industry Breakdown ..................................................................................................... 16

Exhibit 2: Time Line Event Study ................................................................................................ 17

Exhibit 3: Major Changes CAR [-20;+20] ................................................................................... 34

Exhibit 4: Major Changes CAR [-20;+20] excluding Outliers ..................................................... 34

Exhibit 5: STI Changes CAR [-20;+20] ....................................................................................... 37

Exhibit 6: LTI Changes CAR [-20;+20] excluding Outliers ........................................................ 37


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1 Introduction

1.1 Background

In the presidential election 2008 Barack Obama stated ...Its about changing a system where

bad behaviour is rewarded so that we can hold CEOs accountable, and make sure they're acting

in a way that's good for their company, good for our economy, and good for America, not just

good for themselves1addressing the increased focus on executive compensation.

During the last decade two major financial crisis: the burst of the internet bubble in 2000 and the

Subprime Crisis in 2008 have triggered public corporate scandals, bankruptcies and the

destruction of shareholder wealth worldwide.2 Fuelled by these events a governmental and public

debate arose, questioning the high levels of executive compensation and to which extend the

structural changes in compensation design had enforced excessive risk taking. Looking back, the

remarkable increase in CEO pay levels has been mainly due to the generous use of stock option

grants and bonuses. In 2010, the value of option packages received in 2008 and 2009 has been

multiplied due to the recovery of the stock market. The option package of Alan Mulally, CEO of

the distressed Ford Motor company has currently a market value of USD 50 million, a ten times

increase.3 Even with required holding periods of numerous years the stock options granted

during the financial turmoil in 2008/2009 will most likely lead to a high future payout for most

executives.

Today, the majority of public companies are characterized by separation of ownership and

control. Named executive officers (NEO) are assigned to act in the best interest of owners and

work towards maximizing shareholder value. However, it is most likely the case that the


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performance plans.4 The study Executive Compensation, Trends for 2009 by James F. Reda &

Associates was discussed at the World Economic Forum in Switzerland, Davos in 2009. It

showed that 70 percent of the top 200 firms in the S&P 500 reported changes in executive

compensation in 2009.5 The results of the study demonstrate a shift away from long-term

incentives towards more emphasises on short-term performance targets. According to James F.

Reda the trend in 2009 was to focus more on short-term incentives. This trend is counterintuitive

since a focus on long-term value creation is most beneficial for the company and the

shareholders, and ultimately for the economy as a whole.6

1.2 Research Question

The purpose of our study is to observe how the recent changes in executive compensation affect

the stock price of the firm after the financial crises. The majority of event studies in this field of

research date back to the 1980s and 1990s. Recent studies in the area only investigate in the

relationship between CEO ownership and stock market performance.7 However they do not

consider if the changes in compensation lead to abnormal returns. Our paper shall fill the

research gap by focusing on the analysis of the market reactions upon compensation changes. It

is our intended purpose to discover if the level of abnormal return is more significant for

companies with a greater loss in performance and profitability compared to companies that

performed reasonably well during the financial crisis. Furthermore this paper examines if there

are differences in market reactions depending on whether the nature of the change in executivecompensation are concerned with long-term incentives (LTI) or short-term incentives (STI).


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In essence we propose the following research questions:

i) Does the market react to the announcements of changes to executive compensation plans in the

light of the financial crisis?

ii) Do STI or LTI changes cause differences in market reaction?

iii) Does past performance and profitability of the firm influence the magnitude of the reaction to

changes?

1.3 Study Outline

To substantiate our study and research questions, this paper first presents a discussion of the

underlying theory. The theoretical framework contains a review of the efficient market

hypothesis as basis for the existence of abnormal returns. Subsequently, we describe the

importance of agency theory and market signalling by firms to investors. In order to provide the

basis for later discussions we define different compensation components such as long and short-

term incentive plans. This also includes an outline of the historic development and the motives

behind compensation. Furthermore, an overview of other findings and research in the area will

later give a comparable perspective on our findings and conclusions. The chapter on

methodology describes how the event study is performed, including the choice of the data

sample, subsamples and the study design. By applying a cross-sectional analysis we investigate

if the market reaction is influenced by profitability or performances of the firm. The empirical

results are discussed and evaluated with regards to the hypotheses and underlying theory.

Further, we critically review the applied methodology and results of this study. A conclusion and

suggestions for further research are provided at the end of this paper.


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2 Theoretical Framework

2.1 Efficient Market Hypothesis and Abnormal Returns

The efficient market hypothesis states that in an efficient market the true rational value of a

security is fully reflected in its price, i.e. the security is fairly priced. All accessible data which

reveals value relevant information will be instantly reflect in the share price. Therefore it

becomes impossible for investors to generate abnormal returns and to outperform the market

based on their own evaluations. According to the theory three conditions must be met. First, the

market is free of transaction costs or taxes. Second, all investors have simultaneously access to

information. And third all investors agree on the informations impact on the securitys price. In

reality, frictionless markets which fulfil all these conditions do hardly exist. Nevertheless, a

market can still be efficient as long as an adequate number of market participants have free

access to available information and the majority is able to interpret their implications rationally.8

In 1970 Eugene B. Fama classified three types of market efficiencies in order to test for the fairly

general term market efficiency:

(i) The weak form of market efficiency assumes that security prices today reflect all relevant

historical information and only unanticipated events and news will lead to changes in the stock

price. As a result the security price today plus a random error term, i.e. the impact of the

unforeseen information disclosure, can be viewed as best estimator for tomorrows stock price. A

technical analysis of previous stock price movements will therefore not lead to abnormal

returns.9

(ii) The semi-strong form of market efficiency assumes that in addition to historical information

all publicly available information such as earnings announcements or stock splits is reflected in


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price. Given that the semi-strong form holds, neither the technical nor fundamental security

analysis leads to returns above the market because collecting information is not valuable.10

(iii) The strong form of market efficiency states that not only historical and publicly available

information but also private information such as insider knowledge is reflected in market prices.

If the market is strongly efficient active security selection on average would yield no excess

returns for the investor.11

Thus, given that the market is semi-strong efficient the impact of information releases can be

measured applying the event study methodology.

2.2 Agency Theory and Signaling

Agency theory states that in the case in which one or more individuals (principals) appoint

another group of individuals (agents) and delegate decision-making competence, conflicts of

interest will arise if both parties are utility maximizer. The most common example for this

circumstance is the so called separation of ownership and control in companies with diffuse

ownership.

Shareholders hire managers to act in their best interest and to maximize shareholder value. 12 In

large cooperations all investors are atomistic. With diffuse ownership no shareholder possesses

a large enough amount of shares to establish an incentive to manage or monitor the firms

activities. Therefore managerial positions are delegated to non-owners. This creates advantages

and disadvantages for the shareholders. On the one hand, managerial executives have the

expertise and the time to manage the company more effectively than owners. Hereby the

cooperation fulfils the function in an economy to pool two factors of production, i.e. capital and


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risk differentiates. Principals and agents do not share the same risk attitude.14 Investors are

perceived as risk-neutral towards the firm, because they are able to diversify their risk on the

market. The managers main income source and wealth depends on the one firm alone. Therefore

the manager will acquire a risk-averse attitude which might lead to increased conglomerate

building activities that decrease the overall business risk. In addition there is a tendency that the

firm will be left under-levered to lower the financial risk and decrease the risk of bankruptcy.15

Other identified problems are information asymmetries. The management has more information

about the company, capital structure and possible challenges than the investors. In terms of moral

hazard, the agent may lack effort and does not fulfil what was agreed upon. It also is difficult for

the shareholder to assess if executives have the skills and the talent as they promised when

employed. This selection problem is defined as adverse selection when the manager

misrepresented his actual ability to serve the position.16 Typical other agency conflicts arise

when managers excessively consume perquisites for personal benefits; manipulate earnings or

dividends to increase their bonuses or emphasis short-term payoffs.17

To address these problems owners implement monitoring, out-come based compensation

contracts and other incentive devices such managerial equity investments, i.e. shares or stock

options. Compensation packages shall inline the interest of the shareholders with the interest of

management and lower the cost caused by agency problems.18

2.3 Compensation

Most executive compensation plans consists of two components: (i) a fixed base salary and (ii) a

variable element which formally links managerial compensation to the firms performance. The

later can be classified into two components: short-term incentives (STI) and long-term incentives


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management for sustainable, long-term value creation. Severance payments, e.g. insurance and

retirement benefits are additionally included in most executive compensation plans.19

Table 1: Compensation

Short-term Long-term

Accounting-based Annual bonus Performance shares

Long-term performance plan

Market-based Restricted stock

Stock options

Stock appreciation rights

Phantom shares

A fixed salary payment guarantees management a certain monetary amount because it is not

directly linked to the performance of the company. In the past decade there has been a

continuous shift away from fixed salary towards variable elements to mitigate agency problems

between management and shareholders. However, with increasing uncertainty in compensation

plans, risk averse and undiversified executives will only accept performance-based compensation

if the total value is substantially higher than the value of the foregone cash salary.20 As a result,

companies have to weigh the benefits of aligning management and shareholder interests against

higher overall compensation costs when designing the compensation packages.21

Short-term incentives, i.e. cash bonuses, are linked to individual or corporate performance duringa fixed period of time, usually one fiscal year. Performance targets are quantified by

income/profit measures and earnings per share.22 In most cases there are fixed thresholds for

each performance measure which have to be met to be eligible for the bonus payment. The main

Source: following Gaver/Gaver (1997), p. 4


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executive compensation packages incorporate long-term incentives to mitigate agency problems

and encourage sustainable growth and value creation for shareholders. 23

There are two types of long-term incentives: First, the accounting-based incentives under which

management performance is measured based on operating results and second, the market-based

incentives which are linked directly to the development of the share price. Accounting-based

incentives, such as performance shares, are awarded according to the fulfilment of predetermined

operating targets. In order to enforce the focus on long-term value creation, management is often

required to stay within the company for several years after receiving performance shares.

However, equally to other accounting-based incentives, performance shares bear the risk of

manipulated financial results to met performance targets.24

Market-based incentives are directly linked to the development of the future share price. This

includes stocks, stock options, stock appreciation rights (SARs) and phantom shares. Executives,

who are turned into owners by receiving stocks as part of their compensation, have an incentive

to shift their interest towards shareholder value creation. Too high stock ownership on the other

hand might introduce risk-averse behaviour. The executives wealth is less diversified as the

wealth of shareholders and closely tied to the well being of the company. This might motivate

the executive to avoid investment opportunities that are risky, but profitable for the majority of

shareholders.25

The bull market in the 1990s triggered the widespread use of stock option plans for executives

and employees. The average value of granted options packages increased from nearly zero in

1970 to about USD 6 million in 2005.26 According to the Washington Post, Stephen J. Helmsley

the CEO of UnitedHealth Group, one of Americas largest health insurance companies, gained

USD 98.6 million by exercising his options in 2009.27 Typically companies use so-called fixed


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period in which the option is not exercisable. Under these conditions options are an important

tool to align management interests with those of shareholders. The monetary benefits of

executives are directly linked to the creation of long-term shareholder value, i.e. the higher the

stock price the more valuable the option becomes.28

Despite the (theoretical) benefits of including options in compensation packages there has been

increasing criticism in the past years. The dilutive nature of stock option plans has caused

growing concern among institutional investors. Investors fear that future earnings per share will

be reduced if the outstanding options are exercised.29 A possible solution is the use of stock

appreciation rights (SARs) instead. Thereby, management has the right to receive a cash

payment if the stock price of the company increases over a predetermined period. This holds the

advantage that compensation is tied to long-term value creation while at the same time risk-

averse behaviour and shareholder dilution is reduced. 30

2.4 SEC Disclosure Rule

In the past years investors showed a growing interest in detailed and understandable information

about executive compensation. As a result the SEC announced the adoption of a revised rule

regarding executive and directors compensation disclosure in July 2006. The goal was to provide

more indebt information to the shareholders and include disclosure regulations about stock and

stock option ownership. This should improve the quality, comparability and usefulness of the

proxy statements, annual reports and registration statements. Prior to the change in regulation

companies were able to keep the information about executive pay confidential or inform only

selectively about the actual rewards. Now, the investors are informed about the total amount of

compensation packages for each named executive officer, director and financial officer. A


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precisely notified about the compensation programs, plans and practices including the timing of

option grants, excise prices and underlying stock prices on the grant date.31 In addition the

investor will be provided with information about the outstanding equity interests and awards as

well as retirement and post-employment plans. However, critics have commented negatively on

the latest reporting standards. They argue that it is still too confusing for the investor to identify

the true amount of executive compensation pay. Grands are spread over a long period making

the annual option awards look relatively small compared to the actual amount. According to the

rules from 2006, the summary executive compensation table only included the annual accounted

compensation expenses for each executive. This caused two concerns, first, option awards are

distributed over several years depending on when they had been vested. This leads to the

possibility for companies to assign tremendous option packages already at the start ofemployment without disclosing this information as such. Second, accounting options each year

can lead to negative values when share prices decreased. Therefore the entire balance of the

compensation package might turn out to amount to zero as if executives have worked without

receiving any salary.32 In the future, the SEC plans to lower the level of confusion by enforcing

even more transparent disclosure rules. Auditors will have to confirm the estimated value ofoption grants. In the light of the financial crises the changes planned for 2010 shall additionally

include a discussion about compensation policies which aim to decrease risk taking and large

loss attitudes.33

2.5 Previous Research

The results of earlier studies investigating the shareholder wealth effects of incentive based

compensation in the US market, found a positive market reaction.Larcker (1983) was the first to

apply the event-study methodology to investigate the market reaction of the adoption of


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The observed time periods varied between a rather long event window beginning with the board

meeting date and ending with the day following the SEC stamp date, to a short event window of

one day following the proxy statement. Kumar/Sopariwala (1992) found that long-term

performance plans have a significantly positive impact on reducing agency problems and suggest

that growth and profitability of the firm will enhance. The studies of Tehranian/Waegelein

(1985), Waegelein (1988) and Battistel/King (1995) examined the market reaction with regards

to the adoption of short-term performance plans i.e. bonus plans with annual performance

targets. Their findings are not consistent. Tehranian/Waegelein (1985) and Waegelein (1988)

detect significantly positive reactions whereas Battistel/King (1995) results do not indicate an

abnormal return following the announcements. However this inconsistency may be the result of

differences in study design.34

Tehranian/Waegelein (1985) used monthly returns to calculate theabnormal return. This increases the risk of conflicting events such as earnings announcement in

the observation period which can lead to biased responses. Another reason for differences in the

findings might be the lack of power of the significance test in the study ofBattistel/King (1995).

DeFusco/Johnson/Zorn (1990),Morgan/Poulsen (2000) andMartin/Thomas (2005) focus on the

effect on shareholder wealth in the case of option plans. The earlier studies of

DeFusco/Johnson/Zorn (1990) and Morgan/Poulsen (2000) find a significantly positive return

around the proxy date. The results ofMartin/Thomas (2005) however, find a significant negative

reaction to the adoption of stock option plans. The differences in their findings can be explained

by the increased use of highly dilutive stock option plans; leading to extremely high executive

compensation levels which altered the market perception.35

Two studies by Lambert/Larcker (1985) and Gordon/Pound (1990) investigated the effects of

compensation changes which might be associated with take over activities surrounding the firm.

In their study Lambert/Larcker (1985) tested the market reaction to the adoption of golden


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addition, the adoption of golden parachutes might be perceived as a signal of increasing

probability of a takeover.36Gordon/Pound (1990) focused on Employee Stock Ownership Plans

(ESOPs) which potentially hinder hostile takeover activities. They found a positive market

reaction in the case of a no-takeover situation. However, in the case of takeover pressure they

observed a significantly negative abnormal return since the adoption of ESOPs under these

circumstances reduces potential shareholder wealth.37

3 Methodology

3.1 Data Sample

The foundational data for this study was provided by the US based company James F. Reda &

Associates. It comprises of the 200 largest S&P 500 companies - by market capitalization. Out of

the 200 companies of interest 191 reported to the SEC in 2009. 134 firms filed forward looking

changes in executive compensation as a part of their annual proxy filings.38

The changes in executive compensation are specified as minor and major changes. Hereby minor

changes are adjustments in the base salary e.g. a decrease, increase or freeze. Major changes on

the other hand are alterations concerning short- and long-term incentive plans as well as changes

in severance, retirement and perquisite programs.

Changes with regards to STI plans include adjustments to the weights of the performance

measures as well as general modifications to the STI plan, i.e. changes to the target bonus

opportunities or the introduction of mid-performance goals. James F. Reda & Associates

identified that 25 percent of the companies announced STI changes for 2009 As a result of the


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performance measures such as EPS, NI, EBIT/EBIDA, pre-tax profit and OI. At the same time

seven companies decreased the weights of performance measures taking into account capital

efficiency e.g. ROE or ROC.39 Table 2 displays a detailed overview of the STI changes in

performance measures.

Table 2: Changes in STI Performance Measures

Performance Criteria Type

Changes to Weight or Emphasis

No. of reportedincreases

No. of reporteddecreases

Netchanges

Profit: EPS, NI, EBIT/EBITDA, OI, pretax profit 13 3 10

Cash Flow: Cash Flow, cash flow growth 7 2 5

Non-Financial: Strategic goals, individual goals,liquidity, market share, overall performance of thecompany, team incentive

9 7 2

Revenue: Revenue, revenue growth 2 3 -1

Capital Efficiency: ROE, ROC, RONIC, RONA,EVA

1 7 -6

TOTAL 32 22 10

20 percent of the companies announced general modifications to their STI plan e.g. changes to

the pay for performance curve and the target bonus opportunities. Adjustments included cuts in

the payout level as well as an increased difficulty to reach target payout levels.40

Changes to the LTI plan take into account changes in the performance measures and

performance period, adjustments to the components of the LTI plan as well as a reduction of LTI

grants. 39 percent of the companies disclosed changes to their LTI plan. In terms of performance

Source: Reda (2009), p. 8


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towards restricted shares and unites.41 Please find a detailed overview of changes to the LTI mix

below in Table 3.

Table 3: Changes in LTI Mix

Type of Plan


No. of reported

increases

No. of reported

decreases

Net changes

Restricted Shares and Units 13 9 4

Performance Shares and Units 13 14 -1

Stock Options and SARs 6 16 -10

TOTAL

32 39 -7

14 percent of the companies announced other changes to their LTI plans such as a reduction of

LTI grants, cancellation of the LTI cash component or adjustments to the length of the

performance period.42

Table 4: Changes in LTI Performance Measures

Performance Criteria Type


No. of reportedincreases

No. of reporteddecreases

Netchanges

Capital Efficiency: ROE, ROC, RONIC,RONA, EVA

5 0 5

Cash Flow: Free cash Flow, operating cashflow

2 0 2

Total Shareholder Return: Stock priceappreciation plus dividends (relative andabsolute)

6 4 2

Source: Reda (2009), p. 11


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Benefits and perquisites include basic benefits, supplemental executive retirement program

(SERP), personal use of the aircraft, financial counselling, and other benefit plans. 15 percent of

the companies disclosed to take changes in benefits, perquisites and severance.43

The study of James F. Reda & Associates draws the conclusion that as a result of the financial

crisis and the ongoing difficult economic environment companies have changed their focus to

STI rather than LTI. Short-term performance measures are shifting away from capital efficiency

towards profit measures and CF while long-term performance measures emphasis capital

efficiency, CF and total shareholder return. The post-crisis development contradicts the

traditional theory which states that LTI plans are most beneficial to shareholder and

stakeholders.44

We choose to only consider the effects of major changes on the stock price because we assumed

to see stronger effects compared to minor changes. We agree with the categorisation of James F.

Reda & Associates and follow their example. According to the study of James F. Reda &

Associates, 108 companies announced major changes in their 2009 proxy filings. To obtain

unbiased results we defined selection criteria which the 108 companies had to meet in order to be

included in our final sample. Since this study investigates the effect of executive compensation

changes in the light of financial crisis we only included companies which filled their annual

proxy statements during the period January 1, 2009 and before July 28, 2009. In addition to the

restriction regarding time we imposed the so called clean proxy and clean event window

constraint. Most annual proxy statements typically contain routine voting items e.g. the

election of the board of directors and the approval of selected auditors.45 However, in addition to

these items there might be other voting items such as share repurchases which have a potential

influence on the market reaction. Applying the event study methodology we base our results on

the abnormal returns observed in the event window Therefore it is necessary to ensure that the


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eliminate the presence of interferi

long event window of [-20;+20].

After the filtering of the original d

major changes in our final sam

announcements of STI or LTI ch

reported only changes to their STI

The final sample data is categoriz

code. Please view Exhibit 1 below

Exhibit 1: Industry Breakdown

Please find a detailed list of all incl

12%1

199%

20%

9%

6%1%

7%

Source: own

g information releases completely especially i

ata we included an overall of 69 companies w

ple. To evaluate whether the market reacts

nges we then divided the sample further. S

and 17 focuses solely on adjusting their LTI pr

ed into seven industrial sectors based on the

for a detailed overview.

uded companies in the Appendix 1.

%

7%

Consumer Discretionary

Consumer Staples

Energy

Financials

Health Care

Industrials

in the relatively

hich announced

differently to

ven companies

ogram.

companies SIC


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3.2 Event Study Design

The purpose of an event study is to measure the effect of economic events on the value of a

firm.46 Applying the event study methodology we measure the effects of changes in executive

compensation on the value of a firm. Under the assumption that markets are efficient and rational

the event will have an immediate impact on the share price of the firm.

In order to determine the impact of compensation changes the date of interest is the day at which

executive compensation changes are disclosed with the SEC. Therefore we determine the event

date as the announcement date when the annual proxy is filed at the SEC. Older studies

suggested that finding the event date could be difficult because in the past companies announced

changes throughout various occasions. This could have been the SEC stamp date, board

meetings, the filing of the proxy statement or the date when shareholders vote in favour of a

compensation plan. However, already Bhagat/Brickley (1985) found that most of the

announcements were made at the SEC stamp date47. Later studies e.g. ofMartin/Thomas(2003)

used specifically the SEC filing date of the DEF 14A form or the date of the pre-filing PRE

14A.48 Following those recent approaches we will use the filing of the annual proxy or pre-proxy

as event date (=0).

The time horizon of this study is divided into two time frames as illustrated in Exhibit 2 below,

the estimation window (=T0+1 to =T1) or control window and the event window (=T1+1 to

=T2). The length of the estimation window is defined as L1 = T1- T0 and respectively L2= T2-

T1for the event window.

Exhibit 2: Time Line Event Study


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In the estimation period prior to the event window a sufficiently large number of daily data is

captured in order to define the normal returns which are realized without the impact of the event.

Non-overlapping estimation and event windows ensure that the event does not influence the

estimation of the expected return. In our study we included 252 trading days prior to the event

window to capture past performance.

Generally, the event window is not restricted to the announcement date but rather expanded to a

multi-day period around the event date. This enables us to capture effects which might occur

before the actual announcement date due to information leakage or as a lagged market reaction.

The standardized short-term event window is defined as 3 trading days, the announcement date

minus/plus one trading day. This three day event window captures the effect of an event which

has been disclosed prior or after the stock market opened.49 We decided to distinguish between

ten different event windows to evaluate the market reactions as precisely as possible. For a

detailed overview please see table 5 below. However, the widening of event windows introduces

a trade-off between capturing lagged effects and the possible biased results due to new

information reaching the market.

Table 5: Event Windows

Event Windows

[-1;+1] Captures effect of event

[-20;0] Captures effect of pre-event information leakage

[-10;0] Captures effect of possible information leakage

[-5;0] Captures effect of possible information leakage

[-5;+5] Captures effect of pre-event information leakage as well as lagged post-event effects




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3.3 Measuring Normal Returns

A variety of models are used in past research to estimate the normal returns. These can be

differentiated by means of statistical models and economic models. The input for the statistical

models is purely based on statistics, whereby the economic models are based on economic

theory. The most common statistical models are the constant mean return model, the market

model and the multi-factor model. Economic models include the Capital Asset Pricing Model

(CAPM) and the Arbitrage Pricing Theory APT.50

We decided that the market return model is the most suitable for our purposes. The multi-factor

model was disregarded because it has been examined that additional factors do not increase the

explanatory power of the model but rather make the model overly complex. The same is true for

the APT model. Further, we do not use the CAPM model for our study because the implied

theoretical restrictions may result in misleading findings.51 The market return model is also

superior over the constant return model because ...by removing the portion of return related to

variations in the market return, the variance of the abnormal returns is reduced...52 Generally

one can say the higher the R2 of the market model the more the variance component is reduced.

We obtained an average R2 for all 69 companies of 0.6123 and respectively for the subsamples

LTI and STI changes, 0.5867 and 0.6371. Please view Appendix 4 for a detailed overview of the

obtained R2 values. Given the fairly high R2 values of the market model our decision is further

supported by the majority of past studies which also have employed the market model. It is the

most often used model in event studies.53

The underlying assumption for modelling normal returns with the market model is that the

relationship between market return and the return of the securities is stable. All returns are

assumed to be jointly multivariate normal and identical and independently distributed (IID)

54


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industries we used corresponding industry indices instead of the somewhat more general S&P

500 index to improve the results of the model. The industry classification is based on the

corresponding SIC code of the company. All data was obtained using Thomson Reuters

Datastream.

The market model to estimate the expected return of stocki is:

0

= Stock return

= Market returnThe expected normal returns as defined as:

| where the estimated parameters and are obtained by running an ordinary least squares(OLS) regression on the daily data of stock returns and market returns in the estimationwindow.55

3.4 Measuring Abnormal Returns

Having estimated the normal returns we then are able to calculate the abnormal return in the

event window. The abnormal return describes the impact of the event on the market value of the

security. It is the actual ex post return of the security over the event window minus the normal


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The abnormal return for one security i is defined as

where is the actual return in the event window at day t and is theexpected return as predicted by the normal performance model parameters and the market

return.57

Calculating the abnormal return in the event window gives us

~ 0,

In order to gain an overall picture and to draw overall conclusions we aggregate the abnormal

returns through time and across securities. This way we are able to estimate if the change in

executive compensation has a general impact on the stock price of the firm. Cumulating the

abnormal returns is also important for testing the significance which is of little explanatory

power if only tested for one single security.

The cumulative abnormal return (CARi) for security i is the sum of all abnormal returns

throughout the event window .

Under the null-hypotheses the cumulative abnormal returns are normally distributed with a zero

conditional mean and conditional variance.


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abnormal returns through time and securities are simply calculated as average of the individual

CARis.

The average of the cumulative abnormal return is:

1

~ 0 ,3.5 Test of Significance

Statistical significance can be tested in form of parametric or non-parametric significance tests.

The results of parametric tests are based on the underlying assumption that the abnormal returns

follow a predetermined distribution, e.g. the assumption of student-distribution for the t-test.

Non-parametric test such as the rank or sign test do not require a specific distribution of

abnormal returns. Previous research on daily data has shown that the parametric t-test is adequate

to explain the significance of results while parametric methods are not.59 Therefore we view the

applied t-tests as sufficient to test our results, especially after adjusting for freak values.

To test for both, significantly positive and negative abnormal returns we conducted a two-sided

test under the null hypotheses:

: 0 : 0and respectively:

0 0


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1

on the obtained s and sIn order to assess the null hypotheses the obtained t-values are then compared to the critical t-value ./ with L1 2 degree of freedom. Under the assumption of a t-distribution with 2degrees of freedom the critical values at the 5 percent significant level are +/- 1.96 and

respectively +/-2.576 at the 1 percent significant level. The null hypothesis is rejected if the

obtained t-value is smaller or larger than the critical t-value at the given significance level.60

./ ./The variance estimation applied in the basic t-test has two potential drawbacks. First it follows

the underlying assumption that the market variations in the event period are equal to the

variations during the estimation period. Second, it does not take into account the number of

observations in the estimation period.61

These drawbacks are addressed when including a more advanced variance estimator in the

significance test. The estimated variance adjusts for the length of the estimation window as wellas for changes in the market variance between the estimation and event period.

In order to test the significance the cumulative abnormal return for company i


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with

and the average cumulative abnormal return over the corresponding event window . ~ 0,1with

1 are standardized. The standardized aggregates then form the basis for the test statistic and are

compared to the critical t-values with L1 2 degree of freedom.

So far the applied tests have focused on the null hypotheses that the event has no effect on the

behaviour of asset returns. Under this somewhat strict assumption event introduced variations in

the mean or variance will lead to the rejection of the null hypotheses. However, since we want to

concentrate on the mean effect while taking into account the likelihood of a change in variance,

it is necessary to construct a test which allows for changing variances. By avoiding any reliance

on past returns in estimating the variance of CARs, event introduced changes of the variance are

allowed for.62 This leads to an enhanced variance estimator by eliminating biased variance

estimates from the estimation period.63


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as described above the aggregated average abnormal returns are then standardized using the

estimated variance and tested by comparing the results to the critical t-value.To test whether there are significant differences in abnormal returns after the announcement of

LTI and STI changes we constructed a two sided test under the null hypothesis:

: : Subsequently will be referred to as. and as.The test needs to take into account the small size of the data sample since only 14 companies

(excluding outliers) announced merely LTI changes and seven companies respectively adjusted

their short-term incentives.64 Under the condition that both samples have the same variance and

normally distributed abnormal returns we can apply the following test statistic with N1+N2-2

degree of freedom:

~ 1 1 1 1 2

where s is the estimated common standard deviation of the sample.

In order for this test to be valid it is necessary to check whether the two data samples have the

same variance or if there are significant deviations.65 Therefore we test for differences in sample

variances under the following test statistic:


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3.6 Cross-sectional Analysis

Applying cross-sectional analysis we test if firm specific characteristics other than the

announcement of the changes in executive compensation have an influence on the abnormal

returns. Possible firm specific characteristics might be the past performance, profitably of the

firm, company size or exposure to the macro-economic environment.

The cumulative abnormal returns are regressed against the specific firm characteristic. OLS can

be applied by assuming that the expected disturbance term of the characteristics equals zero and

that disturbance terms are cross-sectionally uncorrelated and homoskedastic.

The regression equation is defined as66

where Y = Vector of CARi

X = Vector of characteristics = Vector of coefficients = Vector of disturbance terms

The significance of the coefficient is tested by the following test-statistic:

under the null hypothesis that 0 , the characteristics have no influence on the abnormalreturns. 67


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4 Empirical Results

4.1 Hypothesis 1

Hypothesis 1 tests if the market reacts to major changes in executive compensation plans.

According to the null hypothesis the announcement of those changes should not have an effect

on the stock price of the firm. Therefore the null hypothesis is 0. A t-statisticexceeding 1.96 leads to the rejection of the null hypothesis, indicating a significant abnormalreturn at a 5 percent significance level.

Table 6 shows the obtained average cumulative abnormal returns in the ten investigated event

windows. For each event window we do observe average cumulative abnormal returns. In the 20

days window prior to the announcement amounted to 3.69 percent. The graduallydecreased in the event windows towards the event date. For the standard event window [-1;+1]

days the average cumulative abnormal return amounted to -0.75 percent.

Table 6: Major Changes

EventWindow t-stat1 t-stat2 t-stat3 excl.Outliers t-stat1 t-stat2 t-stat3[-1;+1] -0,75% -0,7239 -0,7664 0,0428 -0,59% -1,0144 -1,1484 -1,1398

[-20;0] 3,69% 1,3074 1,3500 0,1351 1,85% 1,1600 1,1397 1,1311

[-10;0] 3,13% 1,5636 1,5793 0,1230 1,88% 1,6559* 1,2701 1,2606

[-5;0] 0,90% 0,6158 0,8728 0,0667 0,50% 0,6076 0,6280 0,6233

[-20;+20] 3,41% 0,8368 1,4326 0,1937 3,06% 1,3239 1,3126 1,3027

[-10;+10] 2,95% 1,0472 1,5695 0,1483 2,44% 1,5257 1,3655 1,3553

[-5;+5] 0 80% 0 3981 0 6281 0 0879 0 34% 0 3021 0 3239 0 3215


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The significance test results for each are included in Table 6. None of the obtainedaverage cumulative abnormal returns in the original sample is significant at a 95 percentconfidence level. To further test the robustness of the results we excluded outliers which could

induce possible biases. In order to detect outlier values we plotted the daily abnormal returns

across the sample. Please view Appendix 4. Based on this visual analysis we concluded to reduce

the data sample by two companies whose abnormal returns showed extreme deviations from themean. In addition to the visual analysis, we computed the mean of the and added three timesthe standard deviation which resulted in a non-outlier interval of 14 percent abnormal return.68All values outside the interval are treated as freak values and therefore are excluded. This

approach led to the same results as from our visual analysis and confirmed to remove the two

datasets outside the interval. The average cumulative abnormal returns excluding outliers and thecorresponding significance tests are additionally shown in Table 6. Generally the test-statistic

has improved after adjusting for freak values. The 10;0 value is significant at a tenpercent level indicating a positive significant abnormal return in the ten days prior to the

announcement. All other event windows show no significance.

4.2 Hypothesis 2

Hypothesis 2 tests if short-term incentive changes and long-term incentive changes cause

differences in market reaction. Under the null hypothesis the nature of the changes has no

influence on the market reaction. In other words, the impact of LTI and STI changes on the stock

price should have the same magnitude and size.

Table 7 shows the cumulative average abnormal returns of the long-term incentive changes as

well as the t-statistics For each of the ten event windows we do obtain a cumulative abnormal


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plotted abnormal returns. Additionally, we calculated a non-outlier interval of 9.7 percent to -6.3

percent. Both methods led to the conclusion that three out of the 17 datasets showed freak values.

By excluding the data we obtained an improved t-statistic. The average cumulative abnormal

return after adjusting for outliers shows significance at the 90 percent confidence level in the [-

1;+1] event window. Even after the adjustment for freak values all other event windows did not

indicate an impact.

Table 7: Long-Term Incentive Changes

EventWindow t-stat1 t-stat2 t-stat3 excl.Outliers t-stat1 t-stat2 t-stat3

[-1;+1] -0,48% -0,3421 -0,3217 0,0310 1,39% 0,9758 1,8496* 1,7823*

[-20;0] -0,68% -0,1766 -0,2216 0,1012 -2,05% -0,5257 -0,8355 -0,8051

[-10;0] 1,11% 0,4065 0,4109 0,0932 0,24% 0,0860 0,1055 0,1016

[-5;0] -1,89% -0,9489 -0,9039 0,0699 -1,71% -0,8450 -1,0098 -0,9730

[-20;+20] 1,97% 0,3554 0,3702 0,1974 -2,78% -0,4925 -0,5807 -0,5595

[-10;+10] 4,44% 1,1592 0,9897 0,1399 0,33% 0,0852 0,0980 0,0944

[-5;+5] -1,33% -0,4872 -0,4216 0,0861 -2,01% -0,7263 -0,9637 -0,9286

[0;+5] 0,83% 0,4169 0,4018 0,0545 0,39% 0,1920 0,2943 0,2836

[0;+10] 3,33% 1,2256 1,3458 0,0703 0,09% 0,0338 0,0550 0,0530

[0;+20] 2,65% 0,6913 0,8589 0,1163 -0,73% -0,1870 -0,2583 -0,2489

1advanced variance approach

2

cross sectional variance approach3basic approach

*significance at the 10% level


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five days after the event date. For this event window we reject the null hypothesis. All other

event windows do not indicate a significant reaction at the five or ten percent significance level.

For these windows we cannot reject the null hypothesis.

Table 8: Short-Term Incentive Changes

Event Window

t-stat

1t-stat

2t-stat

3

[-1;+1] -2,20% -1,2340 -1,1592 -1,0732

[-20;0] -6,58% -1,3479 -1,0370 -0,9601

[-10;0] -4,12% -1,1871 -0,9740 -0,9017

[-5;0] -1,64% -0,6466 -0,5532 -0,5121

[-20;+20] -5,01% -0,7096 -0,8830 -0,8175[-10;+10] -1,94% -0,3969 -0,5569 -0,5156

[-5;+5] -2,51% -0,7227 -0,9545 -0,8837

[0;+5] -1,92% -0,7556 -2,5774*** -2,3862**

[0;+10] 1,13% 0,3259 0,8707 0,8061

[0;+20] 0,52% 0,1060 0,2670 0,2472

1advanced variance approach

2cross sectional variance approach

3basic approach

** significance at the 5% level

***significance at the 1% level

Furthermore, we tested the significance of the difference in the average cumulative abnormal

returns of long-term incentive changes and short-term incentive changes. For both subsamples

the variances was located in the non-rejection interval, i.e. the variances are the same and


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Table 9: Differences in Abnormal Returns

Event Window excl. OutliersLTI changes N excl. Outliers

STI changes N t-stat

[-1;+1] 1,39% 14 -2,20% 7 3,4015***

[-20;0] -2,05% 14 -6,58% 7 1,5677

[-10;0] 0,24% 14 -4,12% 7 2,1214**

[-5;0] -1,71% 14 -1,64% 7 -0,0481

[-20;+20] -2,78% 14 -5,01% 7 0,5342

[-10;+10] 0,33% 14 -1,94% 7 0,7856

[-5;+5] -2,01% 14 -2,51% 7 0,2407

[0;+5] 0,39% 14 -1,92% 7 1,5359

[0;+10] 0,09% 14 1,13% 7 -0,5050[0;+20] -0,73% 14 0,52% 7 -0,4316


*** significance at the 1% level

According to our results we reject the null hypothesis for two of the analyzed event windows.

Short-term incentive changes and long-term incentive changes cause a significant difference in

market reaction in the standardized event window [-1;+1] as well as for the [-10;0] event

window. We cannot reject the null hypotheses for the other event windows.

4.3 Hypothesis 3

The third hypothesis investigates whether the past performance and profitability of the firm has

an influence on the magnitude of the abnormal returns. For this purpose we test the cross-


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Variations in past performance range from 81 percent decrease in stock price to a 24 percent

increase. Overall, 65 companies reported a negative performance and for 15 datasets the market

value declined by more than 50 percent during the period of observation.

Table 10 displays the obtained OLS coefficients as well as the corresponding t-statistics. The

regression coefficients up to 10 and 20 days after the announcement showed significance at a one

percent significance level. Furthermore the results indicate significance at a five percent

significance level for the obtained coefficients in the period 10 and 20 days prior to the event

date.

Table 10: Results Cross Sectional Analysis Performance

Event Window Coefficient t-stat1

[-1;+1] -0,0487 -1,0847

[-20;0] 0,2442 1,9761**

[-10;0] 0,1827 2,0395**

[-5;0] -0,0168 -0,3491

[-20;+20] -0,1040 -0,9446

[-10;+10] 0,0041 0,0470

[-5;+5] -0,0405 -0,6881

[0;+5] -0,0197 -0,4976

[0;+10] -0,1747 -3,4698***

[0;+20] -0,3442 -4,0163***


*** significance at the 1% level


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31.12.2008. The EPS for each company range from zero to $15.89 per share. Two of the 69

companies allocated a profit above $15 to each outstanding share while for five of the firms the

EPS was zero. 59 companies achieved an EPS not greater than $5 per share.

Table 11: Results Cross Sectional Analysis Profitability

Event Window Coefficient t-stat1

[-1;+1] -0,0024 -0,7581

[-20;0] -0,0144 -1,6159

[-10;0] -0,0065 -0,9960

[-5;0] -0,0058 -1,7069*

[-20;+20] -0,0089 -1,1307[-10;+10] -0,0046 -0,7377

[-5;+5] -0,0060 -1,4296

[0;+5] -0,0038 -1,3392

[0;+10] -0,0016 -0,4148

[0;+20] 0,0020 0,2904

* significance at the 10% level

Table 11 displays the results from the OLS regression. None of the results are significant at a 95

percent confidence level. Five days before the event window the profitability coefficient

indicates a weak influence on the magnitude of abnormal returns. The t-value for the event

window [0;-5] demonstrates weak significance at a 10 percent level. We can reject the null

hypothesis for this event window.


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5 Evaluation

5.1 Hypothesis 1

The average cumulative abnormal returns through time and security are illustrated in Exhibit 3

and excluding outliers in Exhibit 4. When comparing both graphs the bias introduced by freak

values is visible. The plotted 20;20 including the freak values exhibits a high degreeof fluctuation and randomness. After excluding the outliers the graph looks noticeably smoother.Exhibit 3: Major Changes CAR [-20;+20]

Exhibit 4: Major Changes CAR [-20;+20] excluding Outliers

-2,5%

-2,0%

-1,5%

-1,0%

-0,5%

0,0%

0,5%

1,0%

1,5%

2,0%

2,5%

T-20 T-18 T-14 T-12 T-10 T-8 T-8 T-6 T-4 T-2 0 T+2 T+4 T+6 T+8 T+10T+12T+14T+16T+18T+20

1,5%

2,0%


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Although none of the average cumulative abnormal returns are significant at the five percent

level Exhibit 4 indicates that changes of executive compensation cause an undefined market

reaction prior to the announcement. Six days before the event the increase to a peak pointof 1.43 percent and gradually decreases to -0.25 percent at the actual event date. As presented in

Table 6 the

in the ten day event window prior to the announcement is significant at a 90

percent confidence level. An intensified analysis of this event window shows a high increase ofthe average cumulative abnormal returns eight to one day before the announcement date. Please

view Exhibit 4 for graphical illustration. Therefore we decided to perform an additional test for

the event window [-8;-1]. We found the value of 2.31 percent to be significance at a 95percent confidence level. We can reject the null hypothesis for the event window [-8;-1]. The

market reacts positively eight to one day before the announcement of compensation changes.

This impact might be explained by an information leakage on the market. Another possibility

could be that the firms announce changes in executive compensation before the actual filing at

the SEC.

However we find it most unlikely that the information of a change in executive compensation

would have an impact on abnormal returns eight days before the actual announcement with a

peak point 6 days before the announcement. Especially, considering the wider time frame of the

significant event window one must keep in mind the introduced trade-off between capturing the

lagged effect and possible new information release. Therefore we cannot disregard the possibility

that other information releases have had an impact on the abnormal returns. An assessment of

this additional information is outside of the scope of this study. We assume that the reaction isnot due to the announcement of changes in compensation.

There are several possible explanations of why the stock prices do not demonstrate a significant

i h f j h i i


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announcement. In this case, no significant abnormal return can be measured because it hasalready been incorporated long before the firm publicly announced the change. An approach to

further study the problem of anticipated changes would be to group the data according to their

different level of anticipation and then test the significance of the abnormal returns group wise.69

Furthermore the market may perceive the implementation of the latest compensation changes as

a relatively minor change that will not noticeably alter management incentives.70 Compensation

incentives are only one instrument to diminish agency problems. Studies that found significant

abnormal returns after the implementation of performance packages were initiated in the 1980s

and 1990s. Since then, the burst of the internet bubbles and the latest financial crisis lead to

increased monitoring of the firms management. Shareholders are able to enforce monitoring

through the board of directors and increasing shareholder activism.71 In addition, management is

disciplined by outside control mechanism such competition in managerial labour markets as well

as the increasing public attention towards mismanagement.72 Under these monitoring

mechanisms, agency problems are decreased and the compensational incentives may not be as

important to inline management interests with the interest of shareholders as it was in the past.

In the end, the weak market reaction to adjustments in executive pay might also be simply due to

the fact that the market does not recognise the changes made. The enforced disclosure

requirements of the SEC have increased transparency in executive compensation filings.

However, many critics still view the information given by the firms as deceptive. Companies still

have the possibility to hide major option packages and the compensation reports might not be

sufficient enough to understand the pay package design fully.


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5.2 Hypothesis 2

In Exhibit 5 and 6 the cumulative abnormal return of short-term and long-term incentive changes

are visualised. Although the results from the estimation seem absolutely random Graphs 5 and 6

show an inverse reaction in cumulative abnormal returns in the three days following the

announcement. After the event date, the cumulative average abnormal returns for STI changes

decrease and increase for LTI changes.

Exhibit 5: STI Changes CAR [-20;+20]

Exhibit 6: LTI Changes CAR [-20;+20] excluding Outliers

-3%

-2%

-1%

0%

1%

2%

3%

4%

1%

2%

3%

4%


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To further analyze this inverse effect we decided to test one additional event window [0;+3] forboth subsamples. Following changes in STI we obtained a negative average cumulative

abnormal return of -3.19 percent which is significant at the one percent level for both the basic t-

test and the cross-sectional approach. By shorting the event window we were able to receive a

stronger significance. The results indicate that the market perceives changes in STI measures as

negative. Testing the [0;+3] event window for an impact of LTI changes we observe a non-significant positive average cumulative abnormal return of 0.35 percent.

In both cases the announced changes implied a decrease in either the long-term or short-term

management incentives. Taking into account the nature of the change the results might indicate

that currently the market favours short-term incentive schemes. Post-crisis, investors seem to

have a tendency to perceive STI as more important and making a quick recovery of share prices

their first priority. This contradicts the theory which implies that short-term incentives are

perceived as less beneficial for shareholders as well as former studies stating that the market

reacts positive on the initiation of long-term performance incentive programs.

5.3 Hypothesis 3

Under Hypothesis 3 we tested the influence of the past performance and profitability on the

magnitude of abnormal returns. The obtained OLS coefficients for past performance in the

[0;+10] and [0;+20] event windows are highly significant at a one percent level. This supports

our hypothesis that there is a relationship between the past performance of the company and theobserved market reaction. Seven out of the ten obtained coefficients are negative, indicating an

inverse relationship between the two variables. Firms with a negative past performance show a

greater abnormal return compared to firms with a positive past performance. Shareholders of


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the [0;-5] event window the coefficients for profitability are weakly significant at a 10 percentlevel. For this event window we reject the null hypothesis. The profitability has a weak impact

on the magnitude of abnormal returns. The result indicates a tendency that shareholders

acknowledge the adjustment of executive compensation for a company with lower profitability

more than if the firm had performed well.

Shareholders seem to recognize the fact that firms with higher profitability and a better

performance are less exposed to agency problems. The interests of managers of profitable and

well performing firms are assumed to be more in-lined with the goal to maximise the firms

value for shareholder. Therefore a change in the executive compensation package for firms with

a poor performance and poor profitability might be perceived as more positive by the market.

Shareholders assume that agency problems will be decreased.

6 Critical Discussion

Weaknesses in the design or the methodology will affect the results and the validity of the

conclusion drawn from the study. Therefore it is important to address potential flaws in terms of

specific characteristics of the data samples, applied models and testing procedures which could

cause the results to be biased.

The sample selection and the narrow timeframe of the study might lead to a potential bias of the

results. All 69 companies are US based and listed in the S&P 500 index.

The time focus of the study falls within a period shortly after one of the most severe global

financial crisis. During 2008 the S&P 500 experienced a drop of almost 50 percent in value


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through time and across securities is no correlation between the individual sample s.Based on this assumption the variance of the average aggregated abnormal returns can beestimated disregarding the covariance between individual s.73 However, thisassumption only holds if there are no overlapping event windows, i.e. event clustering. In the

case of clustering the covariance may not be zero which will reduce the power of significance

test, leading to biased results.

There are two ways to account for clustering in the sample data: (1) The portfolio approach, in

which the abnormal returns are aggregated into a portfolio and then analysed and (2) the security

by security approach which tests for the significance of abnormal returns individually without

aggregation across securities. We decided to use the security by security approach because it fits

the characteristics of the data sample best. Due to marginal variations in the actual

announcement date, the portfolio approach would have led to a high number of portfolios which

still would be influenced by clustering. The result of the significance test security by security did

not show any contradicting results in comparison to the aggregated results which are presented

earlier in this study. Nevertheless, one must be aware of the reduced power of the applied

significance test.

The obtained abnormal returns depend on the selection of the Normal Performance Model to

calculate the normal returns. As discussed in methodology we choose to apply the market model

because it is the most commonly used in previous event studies and has shown good results.

However, in the case of non-synchronous trading there is a risk of biased beta values when

applying the market model.74 We do not assess this as problematic because the data sample

consists entirely of S&P 500 stocks which are assumed to be traded actively. Therefore we

expect this approach to generate reliable results especially taking into consideration the high R 2

l th t bt i d Th lt f thi t d i ht h i d if li d diff t


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as past performance and profitability, should be included in the Normal Performance Model.However, we did not use the statistical approach in form of a multi-factor model although after

the cross-sectional analysis we are aware that other factors have an influence. By narrowing

down our sample with regards to size (by market capitalisation) and industry index in our model,

we decreased variance by a large part. Although the multi-factor model decreases the variance of

the abnormal returns even further, the marginal explanatory power of the extra factors is

perceived as small.75 We do not believe that including more factors to the model would have

changed the test results significantly. In the light of the financial crises a great variety of

additional significant factors may have an influence that can hardly be capture by a model.

A variety of test approaches can be used to test the significance of the results from the

regression. As recommended in previous literature we decided to focus on parametric approaches

to test the significance of the abnormal returns. In addition to the basic t-test we applied two

more advanced test method allowing for event introduced variance changes as well as changes

in variance between the estimation and event period. In order to test the robustness of the results

we excluded companies with outlier values. Nevertheless, the results have to be interpreted with

cautions since the smaller sample size reduces the power of the tests noticeably.

7 Conclusion

Since the latest economic turmoil, executive compensation is one of the most discussed topics by

the public, media and politicians. Earlier studies have shown that the implementation of long-

term executive compensation packages has been perceived as positive by the markets. However,analyzing changes in payment plans we do observe different results.

When testing the market reaction on major changes in executive compensation we are able to


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the possibility that the reaction of the stock market could be anticipated long time before theannouncement. Furthermore in this extraordinary economic environment other factors which are

outside the scope of this study could lead to biased result.

Excessive short-term incentives schemes have been in the center of public discussion, too.

Although, we did not receive valid results when testing if the announcement of executive

compensation leads to abnormal returns, we nevertheless tested if short-term incentives have a

different impact on the abnormal returns compared to long-term incentives. Our study shows that

a difference exists. We measured a significant abnormal return following the announcement of

changes to short-term incentives. Shareholders perceive a decrease in short-term incentives

negatively. This contradicts the public discussion favoring a decrease in annual bonus payments.

It also opposes the theory and former studies that an emphasis on long-term incentive programs

is more beneficial for shareholders. In light of the financial crises it seems that shareholders are

more interested in a quick recovery of the stock prices instead of long-term value creation.

Furthermore, our study shows that investors react more favorably to announced changes if the

company performed poorly in the past. If performance and profitability was a reason of concern

earlier than this factor influenced the abnormal returns additionally. Since the stock price shows

the expectation of investors and the abnormal return is higher when economic performance was

poor, one may conclude that the investor has a marginally higher expectation on the future

development of poor performers.

Taking into consideration all possible factors which have an influence on the market, especially

in times of economic turmoil, the markets reaction to executive compensation changes seem

hard to capture. Therefore we cannot disregard the possibility that many other economic factors

outside the scope of this study have an impact on abnormal returns. We suggest repeating this


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Appendix

Appendix 1: Overview of Companies with Major Changes

Company Name Symbol IndustryProxy Filing

DateAnnual

Meeting Date

3M CO MMM Industrials 25-03-2009 12-05-2009

ALLSTATE CORP ALL Financials 01-04-2009 19-05-2009

ALTRIA GROUP INC MO Consumer Staples 09-04-2009 19-05-2009

AMERICAN EXPRESS CO AXP Financials 10-03-2009 27-04-2009

AMGEN INC AMGN Health Care 09-03-2009 06-05-2009

BANK OF NEW YORK MELLON BK Financials 10-03-2009 14-04-2009

BRISTOL-MYERS SQUIBB CO BMY Health Care 23-03-2009 05-05-2009

CBS CORP CBS Consumer Discretionary 24-04-2009 09-06-2009

CENTERPOINT ENERGY INC CNP Utilities 13-03-2009 23-04-2009

CIGNA CORP CI Health Care 19-03-2009 22-04-2009

CITIGROUP INC C Financials 16-03-2009 21-04-2009

COVENTRY HEALTH CARE INC CVH Health Care 10-04-2009 21-05-2009

CSX CORP CSX Industrials 24-03-2009 06-05-2009

CUMMINS INC CMI Industrials 01-04-2009 12-05-2009

DANAHER CORP DHR Industrials 20-03-2009 05-05-2009

DEAN FOODS CO DF Consumer Staples 15-04-2009 21-05-2009

DEERE & CO DE Industrials 15-01-2009 25-02-2009

DEVON ENERGY CORP DVN Energy 24-04-2009 03-06-2009

DIRECTV GROUP INC DTV Consumer Discretionary 20-04-2009 02-06-2009

DOMINION RESOURCES INC D Utilities 20-03-2009 05-05-2009

DONNELLEY (R R) & SONS CO RRD Industrials 15-04-2009 21-05-2009

DU PONT (E I) DE NEMOURS DD Materials 20-03-2009 29-04-2009

EMC CORP/MA EMC Information Technology 06-03-2009 06-05-2009

FIRSTENERGY CORP FE Utilities 01-04-2009 19-05-2009

GAP INC GPS Consumer Discretionary 07-04-2009 19-05-2009

GOODYEAR TIRE & RUBBER CO GT Consumer Discretionary 27-02-2009 07-04-2009

GOOGLE INC GOOG Information Technology 24-03-2009 07-05-2009

HOME DEPOT INC HD Consumer Discretionary 30 03 2009 28 05 2009


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Company Name Symbol IndustryProxy Filing

DateAnnual

Meeting Date

KOHL'S CORP KSS Consumer Discretionary 27-03-2009 14-05-2009

KROGER CO KR Consumer Staples 15-05-2009 25-06-2009

LOWE'S COMPANIES INC LOW Consumer Discretionary 24-03-2009 29-05-2009

MARSH & MCLENNAN COS MMC Financials 02-04-2009 21-05-2009

MCKESSON CORP MCK Health Care 15-06-2009 22-07-2009

METLIFE INC MET Financials 31-03-2009 28-04-2009

MORGAN STANLEY MS Financials 20-03-2009 29-04-2009

MURPHY OIL CORP MUR Energy 27-03-2009 13-05-2009

NORTHROP GRUMMAN CORP NOC Industrials 17-04-2009 20-05-2009

NUCOR CORP NUE Materials 25-03-2009 14-05-2009

PACCAR INC PCAR Industrials 12-03-2009 28-04-2009

PG&E CORP PCG Utilities 01-04-2009 13-05-2009

PPG INDUSTRIES INC PPG Materials 06-03-2009 16-04-2009

PROGRESSIVE CORP-OHIO PGR Financials 13-03-2009 24-04-2009

PRUDENTIAL FINANCIAL INC PRU Financials 20-03-2009 12-05-2009

QUALCOMM INC QCOM Information Technology 13-01-2009 03-03-2009

SAFEWAY INC SWY Consumer Staples 27-03-2009 13-05-2009

SCHLUMBERGER LTD SLB Energy 06-02-2009 08-04-2009

SPRINT NEXTEL CORP STelecommuni

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