examining the relationship between organizational risk attributes hedging

Examining the Relationship between Organizational Risk Attributes of U.S. Defense

Companies and Corporate Hedging

Dissertation

Submitted to Northcentral University

Graduate Faculty of the School of Business and Technology Management in Partial Fulfillment of the

Requirements for the Degree of

DOCTOR OF BUSINESS ADMINISTRATION

by

CHARLIE SHAO

Prescott Valley, Arizona September 2012

UMI Number: 3534186

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Charlie Shao

APPROVAL PAGE

Examining the Relationship between Organizational Risk Attributes of U.S. Defense

Companies and Corporate Hedging

by

Charlie Shao

Approved by:

Chair: Steven Munkeby, D.M U/-T/ao\a.

Date

Member: Roy Nafarrete, D.M.

Member: Becky Takeda-Tinker, Ph.D.

Certified by:

School Dean: A. Lee Smith, Ph.D. vi /W/?-

Date

Abstract

Corporate hedging had become a vital activity for success of United States (U.S.) defense

firms. As a result of corporate hedging in foreign exchange and currency risk

management, U.S. defense companies were exposed recently to financial risks resulting

in millions of dollars of lost profits. While research has shown organizational risk

attributes may be indicators of corporate hedging activities, the relationship between

organizational risk attributes and corporate hedging practices in U.S. defense industry has

not been studied. To ensure the success of corporate hedging, managers in the U.S.

defense companies need to be attentive to the organizational determinants that might

influence corporate hedging decisions. The purpose of this study was to examine the

relationship between the risk attributes of U.S. defense companies and corporate hedging

in foreign exchange and currency risk management. A linear regression model was

utilized to estimate the relationship between seven risk attributes and corporate hedging

for a random sample of 55 U.S. defense companies that were faced with foreign exchange

and currency risk exposures. Evidence indicated financial distress was not statistically

significant correlated with corporate hedging, t(53) = 1.18,/? > .05; tax benefits were

statistically significant and positively correlated with corporate hedging, t(53) = 6.64, p

< .05; underinvestment problems were positively correlated with corporate hedging, /(53)

= 2.44, p < .05; managerial incentives were not statistically significant correlated with

corporate hedging, /(53) = -1.92, p > .05; scale economies were statistically significant

and positively correlated with corporate hedging, r(53) = 4.54, p < .05; level of foreign

involvement was not statistically significant correlated with corporate hedging, f(53) =

1.45, p > .05; and revenues derived from U.S. government contracts were negatively

iv

correlated with corporate hedging, /(53) = -2.39, p < .05. Findings of this research

suggest tax benefits, underinvestment problems, scale economies, and revenues derived

from U.S. government contracts are important determinants of corporate hedging for U.S.

defense companies. Further research in assessment of the relationship between

organizational risk attributes of U.S. defense companies and corporate hedging is

recommended.

v

Acknowledgements

There is no way I could have written this dissertation manuscript without my

support team. I would like to take this opportunity to express my profound gratitude to

all who helped me complete this research study. Their comments and suggestions were

inestimably contributed to the success of the study. I am particularly grateful to my

committee chair, Dr. Steven Munkeby, who made specific comments and suggestions

that led to significant improvements of the study. The consistent counsel and guidance

provided by Dr. Munkeby have been invaluable. I would like to thank my committee

members, Dr. Roy Nafarrete and Dr. Becky Takeda-Tinker, for their wisdom and advices

as well. I also owe a word of appreciation to Dr. Bob Goldwasser, Dr. Catherine

Crocker, Dr. Emil Berendt, Dr. Carrie Williams, and Dr. John Caruso for their

encouragement and knowledge in my pursuit of this academic journey.

I would like to give a special thanks to the establishment of an employee scholar

program at United Technologies Corporation (UTC) and Computer Sciences Corporation

(CSC). I have been encouraged to develop additional skills and engage in lifelong

learning from the program. In particular, my thanks go out to my former and current

managers, Aksel Sidem, Barbara Nickels, and Daniel Hamernick, for their support of my

academic study along the way.

Most naturally, I want to say thanks to my wife Jenny and sons Jason and Tyler,

who gave me the time and quiet I needed to work and do research for the study. Without

their constant support and patience, the completion of this study would not have been

possible. I also appreciate my brother, Dr. Ruijin Shao, to let me learn from his

vi

knowledge and experience. As always, I would like to thank my parents and parents-in-

law for their love and prayers for me on the journey.

vii

Table of Contents

List of Tables x

List of Figures xi

Chapter 1: Introduction 1 Background 2 Problem Statement 4 Purpose of the Study 4 Theoretical Framework 6 Research Questions 11 Hypotheses 12 Nature of the Study 14 Significance of the Study 17 Definitions 18 Summary 24

Chapter 2: Literature Review 26 Overview 28 Financial Distress 33 Tax Benefits 37 Underinvestment Problems 43 Managerial Incentives 46 Scale Economies 53 Level of Foreign Involvement 56 Other Factors 59 Corporate Hedging in Foreign Exchange and Currency Risk Management 78 Summary 85

Chapter 3: Research Method 87 Research Design and Methods 88 Participants 91 Research Instruments 93 Operational Definition of Variables 101 Data Collection, Processing, and Analysis 104 Methodological Assumptions, Delimitations, and Limitations 117 Ethical Assurances 118 Summary 120

Chapter 4: Findings 122 Results 123 Evaluation of Findings 147 Summary 153

Chapter 5: Implications, Recommendations, and Conclusions 155

viii

Implications 156 Recommendations 167 Conclusions 169

References 174

Appendixes 194 AppendixA: Random Sampling Procedure 195 Appendix B: Determination of Sample Size with a Priori Power Analysis 196 Appendix C: Permission to Use the Diagram of Evaluating Secondary Data 199 Appendix D: Residual Plots for the Independent Variables 200 Appendix E: Normal Probability Plots of Residuals for the Dependent Variable ....204 Appendix F: Approval Letter for the Research Study from the University's IRB ...208

ix

List of Tables

Table 1 Summary of Independent Variable, Description and Data Type 102 Table 2 General Guidelines for Interpreting the Calculated Value of Durbin-Watson Statistics (d) 113 Table 3 Frequencies and Percentages of Corporate Hedging in Foreign Exchange and Currency Risk Management Markets 124 Table 4 Frequencies and Percentages for Financial Distress 125 Table 5 Frequencies and Percentages for Tax Benefits 126 Table 6 Frequencies and Percentages for Underinvestment Problems 127 Table 7 Frequencies and Percentages for Managerial Incentives 128 Table 8 Frequencies and Percentages for Scale Economies 129 Table 9 Frequencies and Percentages for Level of Foreign Involvement 130 Table 10 Frequencies and Percentages for Revenues Derivedfrom U.S. Government Contracts 131 Table 11 Descriptive Statistics of the Risk Attributes of U.S. Defense Companies and Corporate Hedging in Foreign Exchange and Currency Risk Management Markets.... 132 Table 12 The Calculated Value of Durbin-Watson Statistic (d) for Independent Variables in the Analyzed Data Sets 135 Table 13 Results of Testing the Significance of the Linear Relationship between Financial Distress and Corporate Hedging (n = 55) 137 Table 14 Results of Testing the Significance of the Linear Relationship between Tax Benefits and Corporate Hedging (n = 55) 138 Table 15 Results of Testing the Significance of the Linear Relationship between Underinvestment Problems and Corporate Hedging (n = 55) 140 Table 16 Results of Testing the Significance of the Linear Relationship between Managerial Incentives and Corporate Hedging (n = 55) 141 Table 17 Results of Testing the Significance of the Linear Relationship between Scale Economics and Corporate Hedging (n = 55) 143 Table 18 Results of Testing the Significance of the Linear Relationship between Level of Foreign Involvement and Corporate Hedging (n = 55) 144 Table 19 Results of Testing the Significance of the Linear Relationship between Revenues Derived from U.S. Government Contracts and Corporate Hedging (n = 55) 146

x

List of Figures

Figure 1. Tax benefits in corporate hedging 38 Figure 2. Evaluating secondary data 107

xi

1

Chapter 1: Introduction

With growing globalization and the global economic and financial crisis

beginning in 2008, the increased volatility of the financial markets has given rise to

increased financial risks faced by United States (U.S.) defense companies such as

Lockheed Martin Corporation and the Boeing Company (The Boeing Company, 2009;

Chance & Brooks, 2007; Gregory, 2010; Lockheed Martin Corporation, 2009). The

management of financial risks has become paramount for the survival of U.S. defense

companies in volatile financial markets (The Boeing Company, 2009; Chance & Brooks,

2007; Lockheed Martin Corporation, 2009; Whaley, 2006). In 2009, a survey from the

International Swaps and Derivatives Association (ISDA) indicated increased corporate

usage of financial derivatives. Representatives of more than 94% of the top 500 global

companies use derivative instruments to manage and hedge financial risks more

effectively (ISDA, 2009). As a means of reducing financial risk, corporate hedging with

derivatives is an integral part of corporate risk management among leading companies

worldwide (Chance & Brooks, 2007).

An introduction to the problem resulting from corporate hedging in risk

management is provided in this chapter. Background information is presented regarding

the importance of the problem caused by corporate hedging. The problem and the

purpose of the study are presented, followed by a discussion of the theoretical framework

of the study. Research questions and hypotheses are defined, and the nature and

significance of the study are described. Finally, definitions of key terms for the study are

given, followed by a summary of the chapter.

2

Background

A derivative is a financial instrument whose value is derived iBrom the value of

another underlying asset (Chance & Brooks, 2007; Hull, 2006; Stulz, 2003). The

derivatives used by representatives of a company to hedge financial risk include forward

contracts, future contracts, option, and swap (Hancock-Weise, 2011; Hull, 2006; Whaley,

2006). In general, corporate hedging with derivatives is defined as "a component of a

more general process called risk management, the alignment of the actual level of risk

with the desired level of risk" (Chance & Brooks, 2007, p. 355). There is a demonstrated

need for corporate hedging in foreign exchange and currency risk management (Eiteman,

Stonehill, & Moffett, 2007; Homaifar, 2004; Nguyen & Faff, 2010). Such evidence

points to the fact that companies benefit from corporate hedging (Froot, Scharfstein, &

Stein, 1993; Graham & Smith, 1999; Jensen & Meckling, 1976; Morellec & Smith, 2007;

Smith & Stulz, 1985; Shapiro, 2005). Corporate hedging with derivatives can be

designed to create a wide range of cash flows because derivatives are cheap and flexible

(Hancock-Weise, 2011; Nguyen & Faff, 2010; Whaley, 2006).

As documented in the annual financial reports, company representatives in the

U.S. defense industry perform corporate hedging in risk management on a regular basis

(The Boeing Company, 2009; Lockheed Martin Corporation, 2009). Corporate hedging

is important to ensure that U.S. defense companies gain reliable, timely, and affordable

access to materials needed to produce defense products and to protect the value of the

assets of a company against appreciation or depreciation in foreign currencies (The

Boeing Company, 2009; Eiteman et al., 2007; Stulz, 2003; Lockheed Martin Corporation,

2009; Watts, 2008). However, company representatives are reluctant to hedge against a

3

foreign exchange and its currency risks because corporate hedging may introduce risks

such as a buildup of a derivative position, which is an uncertainty in terms of the hedge

performance, counterparty risks, and possible high hedging costs (Chance & Brooks,

2007; Gregory, 2010; Hancock-Weise, 2011; Stulz, 2003; Whaley, 2006). Uncertainties

regarding global currency may result in increased costs and reduced profits for U.S.

defense companies while limiting the desire of representatives of these companies to

conduct business with foreign markets (The Boeing Company, 2009; Eiteman et al.,

2007; Homaifar, 2004; Lockheed Martin Corporation, 2009).

Researchers (e.g., Artez & Bartram, 2010; Stulz, 2003) have suggested a range of

theoretical determinants that might influence corporate hedging decisions at the

organizational level. The main explanations of corporate hedging focus on risk

management as a means to lessen the possibility of financial distress (Smith & Stulz,

1985), reduce expected taxes (Graham & Smith, 1999; Smith & Stulz, 1985), avoid

underinvestment (Froot et al., 1993), and maximize managers' own self-interest (Jensen &

Meckling, 1976; Shapiro, 2005; Stulz, 2003). However, the determinants of corporate

hedging in foreign exchange and currency risk management can differ across different

industry sectors and companies with different characteristics (Adam, Dasgupta, &

Titman, 2007; Bartram, Brown, & Fehle, 2009; Lei, 2006; Papaioannou, 2006; Reynolds,

Bhabra, & Boyle, 2009; Rogers, 2002). To improve the efficiency of corporate hedging

in risk management, managers in the U.S. defense companies need to be attentive to the

organizational determinants that might affect corporate hedge policies (Artez & Bartram,

2010; Stulz, 2003).

4

Problem Statement

The problem addressed in this study was that, as a result of corporate hedging

practices in foreign exchange and currency risk management markets, U.S. defense

companies are exposed to financial risks leading to a potential loss of millions of dollars

of profit (The Boeing Company, 2009; Chance & Brooks, 2007; Eiteman et al., 2007;

Gregory, 2010; Lockheed Martin Corporation, 2009; Stulz, 2003). As a U.S. government

contractor, the Boeing Company reported net losses of $92 and $101 million, in 2007 and

2008 respectively, associated with corporate hedging transactions (The Boeing Company,

2009). Derivatives used for defense contracts, with notional foreign exchange and

currency values of $1.9 billion in 2008 and $1.4 billion in 2009, were designated as

hedging instruments (Lockheed Martin Corporation, 2009). Although corporate hedging

in risk management is receiving increasing attention in the U.S. defense industry, whether

organizational risk factors relate to corporate hedging for U.S. defense companies is

unknown (Artez & Bartram, 2010). To ensure that company managers succeed in

performing corporate hedging in risk management, a need exists for empirical assessment

regarding the relationship between the risk attributes of U.S. defense companies and

corporate hedging (Artez & Bartram, 2010; Petersen & Thiagarajan, 2000; Stulz, 2003).

The relationship between the risk attributes of U.S. defense companies and corporate

hedging practices in foreign exchange and currency risk management markets has not

been examined in previous literature.

Purpose of the Study

The purpose of this quantitative correlational study was to examine the


5

in foreign exchange and currency risk management markets. A secondary data analysis

was used. The independent variables of the risk attributes of U.S. defense companies

were defined as financial distress, underinvestment problems, tax benefits, managerial

incentives, scale economies, level of foreign involvement, and revenues from U.S.

government contracts (Allayannis & Ofek, 2001; Bartram et al., 2009; Dolde & Mishra,

2007; Froot et al., 1993; Jensen & Meckling, 1976; Jorion, 1990; Smith & Stulz, 1985;

Stulz, 2003). The dependent variable was defined as corporate hedging in foreign

exchange and currency risk management markets. The population for the study consisted

of 194 U.S. defense companies in the National Automated Accounting Research System

(NAARS) database (American Institute of Certified Public Accountants, 2005). All 194

defense companies that conducted defense-related business from 2000 to 2010 in the U.S.

qualified for inclusion in the study. A random sample for the study was drawn from the

list of 194 U.S. defense companies. From this population, a sample size of 55 U.S.

defense companies was used to ensure statistical significance. All financial data were

collected from the annual financial report on Form 10-K and the annual proxy statement,

filed in the electronic data gathering and retrieval (EDGAR) database system of the U.S.

Securities and Exchange Commission (Securities and Exchange Commission [SEC],

2012). With the passage of the Sarbanes-Oxley Act of2002, corporate executives must

certify the financial statements are faithful representations of the financial positions and

results of operations of the company (Whittington & Pany, 2004). Because of the

improved disclosure requirements for the business and financial information of a

company, more empirical studies have been based on the use of the data contained in the

annual financial reports (Apostolou & Apostolou, 2008; Bartram et al., 2009; Carter,

6

Rogers, & Simkins, 2006; Hsu, Ko, Wu, Cheng, & Chen, 2009; Judge, 2006; Nguyen,

Mensah, & Faff, 2007; Ramirez, 2007; Reynolds et al., 2009; Schiozer & Saito, 2009;

Spano, 2008; SprCic, 2007).

Theoretical Framework

The underlying theoretical framework supporting this study is composed of

corporate hedging theories and empirical studies. To discuss the rationale for engaging in

corporate hedging and what the effects of corporate hedging can be, the two most

prevalent theories used by representatives of nonfinancial companies are shareholder

value maximization theory and managerial utility maximization theory. Empirical

research on corporate hedging in foreign exchange and currency risk management for

nonfinancial companies is relatively recent, and the results of the empirical studies are

varied (Allayannis & Weston, 2001; Bartram et al., 2009; Berkman, Bradbury, Hancockc,

& Innes, 2002; Brown, 2001; Carter et al., 2006; Davies, Eckberg, & Marshall, 2006;

Dolde & Mishra, 2007; Fabling & Grimes, 2008; Graham & Rogers, 2002; Hagelin,

2003; Judge, 2006; Kapitsinas, 2008; Lei, 2006; Luiz & Junior, 2011; Marsden &

Prevost, 2005; Menon & Viswanathan, 2005; Nguyen & Faff, 2003; Reynolds & Boyle,

2005; Schiozer & Saito, 2009; Spano, 2008). The current study was designed to confirm

whether the corporate hedging theories and the findings from empirical studies are

applicable to corporate hedging practices in the U.S. defense industry.

According to the shareholder value maximization theory, the exploitation of

inefficiencies in the perfect capital market is based on the assumption that corporate

hedging can add value by reducing various costs involved with future cash flows and

alleviating problems associated with these costs. Furthermore, financially distressed

7

companies face costs of default on debt obligations and costs of filing for bankruptcy

(Smith & Stulz, 1985). One of the most important benefits in effective risk management

is to reduce the costs associated with financial distress (Stulz, 2003). Given these costs,

company representatives have incentives to reduce the probability of financial distress.

When companies are subject to a progressive tax system, corporate hedging can reduce

expected tax liabilities (Graham & Smith, 1999; Smith & Stulz, 1985). As such, a greater

convexity in the tax functiorj will lead to a greater likelihood of corporate hedging.

Furthermore, when external financing is more costly to companies than are internally

generated funds, company representatives may tend to use derivative instruments (Froot

et al., 1993). In particular, the company representatives can hedge cash flows to avoid a

shortfall in internal funds so that costly external financing from the capital markets may

be prevented (Froot et al., 1993).

The primary theoretical alternative to the shareholder value maximization as a

corporate hedging theory is managerial utility maximization. From the perspective of the

managerial utility maximization theory, corporate hedging can have different effects on

shareholder value. Corporate hedging decisions may be the result of the aversion of

company managers to financial risks because, unlike shareholders, the company

managers have disproportionately large investments in the company, which cannot easily

diversify their risks (Morellec & Smith, 2007). When the objectives of shareholders and

company managers diverge, the managers can behave in their own self-interest rather

than in the best interests of the shareholders (Jenson & Meckling, 1976). Therefore,

company managers may seek to maximize their own self-interest and have incentives to

hedge their own private wealth at the expense of the shareholders (Jensen & Meckling,

8

1976; Shapiro, 2005; Stulz, 2003). To ensure that company managers act to maximize

shareholder value and not just to advance their own private wealth, managerial

compensation policy can be designed to give the company managers incentives to select

corporate hedging that increase shareholder value (Jenson & Meckling, 1976; Shapiro,

2005; Stulz, 2003). Company managers may also be interested in protecting the

profitability of a company through corporate hedging in risk management because of a

possible change in corporate asset value (Shapiro, 2005).

In addition to the theoretical determinants of corporate hedging, some additional

factors are associated with the use of derivative instruments in company risk

management. These additional factors include scale economies (Allayannis & Ofek,

2001; Nance, Smith, & Smithson, 1993), firm value (Carter et al., 2006; Jin & Jorion,

2006), level of foreign involvement (Howton & Perfect, 1998; Menon & Viswanathan,

2005), foreign debt (Judge, 2009; Nguyen & Faff, 2006), asymmetric information

(Breeden & Viswanathan, 1996; DeMarzo & Duffie, 1991), board characteristics

(Borokhovich, Brunarski, Crutchley, & Simkins, 2004; Prevost, 2005), industry-specific

characteristics (Rogers, 2002; Schiozer & Saito, 2009), country-specific characteristics

(Lei, 2006; Marsden & Prevost, 2005), and accounting reporting methods (Sapra, 2002;

Supanvanij & Strauss, 2010).

Large companies are more likely to hedge than are small companies because the

large companies may have better access to external financing in capital markets

(Allayannis & Ofek, 2001). Smaller companies have been advised to hedge more than

larger ones because the smaller companies are likely to have a greater informational

asymmetric problem (Nance et al., 1993). Corporate hedging and firm value were

9

positively related in the U.S. airline industry (Carter et al., 2006). In contrast, corporate

hedging did not affect market values of companies in the U.S. oil and gas industry (Jin &

Jorion, 2006). Corporate hedging activities were significantly and positively related to

the extent of foreign involvement by U.S. multinational corporations (Menon &

Viswanathan, 2005). However, the relationship between the level of foreign involvement

and corporate hedging with currency derivatives was not strongly supported in another

study (Howton & Perfect, 1998). Corporate hedging was significantly related to the

existence of foreign debt in one study (Judge, 2009), but in a different study, the use of

foreign debt was found to be irrelevant to corporate hedging in foreign exchange and

currency risk management (Nguyen & Faff, 2006).

Corporate hedging decisions can be explained by the reputation of company

managers (Breeden & Viswanathan, 1996; Demarzo & Duffie, 1991). Board

composition was not related to the use of derivative instruments (Marsden & Prevost,

2005). Board size and the presence of corporate executives on the board were not found

to be determinants of corporate hedging (Borokhovich et al., 2004). Because regulated

industries operated in more stable environments (Smith & Watts, 1992), representatives

of companies in regulated industries used corporate hedging less than did representatives

of companies in unregulated industries (Rogers, 2002). Furthermore, company

representatives in regulated industries were less likely to use currency derivatives for

corporate hedging (Schiozer & Saito, 2009). Financial market developments, legal

environment, and macroeconomic characteristics of the country were considered to be

possible reasons for differences in corporate hedging practices (Lei, 2006; Marsden &

Prevost, 2005). Derivative reporting transparency is a significant determinant of

10

corporate hedging (Supanvanij & Strauss, 2010). Furthermore, increased reporting of

transparency resulting from the FAS 133 standard may induce company representatives

to take an excessive speculative position (Sapra, 2002).

From a theoretical perspective, companies benefit from corporate hedging in

foreign exchange and currency risk management because of shareholder value

maximization and managerial utility maximization (Froot et al., 1993; Graham & Smith,

1999; Jensen & Meckling, 1976; Morellec & Smith, 2007; Smith & Stulz, 1985; Shapiro,

2005). The theoretical framework presented in the study underscores the premise that

U.S. defense companies may benefit from corporate hedging in foreign exchange and

currency risk management. Recently, corporate hedging theories have been empirically

tested to examine if nonfinancial companies benefit from corporate hedging in foreign

exchange and currency risk management (Allayannis & Weston, 2001; Bartram et al.,

2009; Berkman et al., 2002; Brown, 2001; Carter et al., 2006; Davies, Eckberg, &

Marshall, 2006; Dolde & Mishra, 2007; Fabling & Grimes, 2008; Graham & Rogers,

2002; Hagelin, 2003; Judge, 2006; Kapitsinas, 2008; Lei, 2006; Luiz & Junior, 2011;

Marsden & Prevost, 2005; Menon & Viswanathan, 2005; Nguyen & Faff, 2003;

Reynolds & Boyle, 2005; Schiozer & Saito, 2009; Spano, 2008). However, the

conflicting findings from prior empirical studies remain because the conclusions from the

prior empirical studies are largely sample specific, and the measurement of the

determinants for corporate hedging is not consistent (Artez & Bartram, 2010; Nguyen &

Faff, 2010; Stulz, 2003).

Although the existing empirical studies on corporate hedging in foreign exchange

risk management by nonfinancial companies are diverse, in a recent review of the

11

literature, a gap in research studies on the relationship between the risk attributes of U.S.

defense companies and corporate hedging was identified. Therefore, additional research

to assess the relationship between the risk attributes of U.S. defense companies and

corporate hedging in foreign exchange and currency risk management markets is

warranted. Furthermore, an evaluation of the corporate hedging theories in light of the

findings from empirical studies was enabled by the current study. As such, the study can

be used to extend the body of knowledge on corporate hedging at an organizational level.

Research Questions

To broaden a view of corporate hedging in the U.S. defense industry with

discussions of risk management for a specific financial exposure to U.S. defense

companies, the following research questions directed the focus of the study:

Ql. To what extent, if any, is financial distress related to corporate hedging in

foreign exchange and currency risk management markets for U.S. defense companies?

Q2. To what extent, if any, are tax benefits related to corporate hedging in


Q3. To what extent, if any, are underinvestment problems related to corporate

hedging in foreign exchange and currency risk management markets for U.S. defense

companies?

Q4. To what extent, if any, are managerial incentives related to corporate


companies?

Q5. To what extent, if any, are scale economies related to corporate hedging in


12

Q6. To what extent, if any, is level of foreign involvement related to corporate


companies?

Q7. To what extent, if any, are revenues from U.S. government contracts related

to corporate hedging in foreign exchange and currency risk management markets for U.S.

defense companies?

Hypotheses

Based on the research questions and literature review presented in Chapter 2,

seven hypotheses about the relationship between the risk attributes of U.S. defense

companies and corporate hedging in foreign exchange and currency risk management

markets were developed for the study.

Hl0. Financial distress, as measured with debt ratio, is not correlated to corporate

hedging in foreign exchange and currency risk management markets, as measured with

notional value of derivatives, for U.S. defense companies.

Hla. Financial distress, as measured with debt ratio, is correlated to corporate



H2o. Tax benefits, as measured with income tax credit range, are not correlated to

corporate hedging in foreign exchange and currency risk management markets, as

measured with notional value of derivatives, for U.S. defense companies.

H2„. Tax benefits, as measured with income tax credit range, are correlated to



13

H3o. Underinvestment problems, as measured with research and development

(R&D) spending, are not correlated to corporate hedging in foreign exchange and

currency risk management markets, as measured with notional value of derivatives, for

U.S. defense companies.

H3a. Underinvestment problems, as measured with R&D spending, are correlated

to corporate hedging in foreign exchange and currency risk management markets, as


H4o. Managerial incentives, as measured with presence of corporate executives'

stock shares, are not correlated to corporate hedging in foreign exchange and currency

risk management markets, as measured with notional value of derivatives, for U.S.

defense companies.

H4„. Managerial incentives, as measured with presence of corporate executives'

stock shares, are correlated to corporate hedging in foreign exchange and currency risk

management markets, as measured with notional value of derivatives, for U.S. defense

companies.

H5o- Scale economies, as measured with firm size, are not correlated to corporate



H5a. Scale economies, as measured with firm size, are correlated to corporate



14

H6o. Level of foreign involvement, as measured with foreign sale ratio, is not

correlated to corporate hedging in foreign exchange and currency risk management

markets, as measured with notional value of derivatives, for U.S. defense companies.

H6a. Level of foreign involvement, as measured with foreign sale ratio, is



H70. Revenues derived from U.S. government contracts, as measured with sales

to U.S. government, are not correlated to corporate hedging in foreign exchange and



H7a. Revenues derived from U.S. government contracts, as measured with sales

to U.S. government, are correlated to corporate hedging in foreign exchange and currency


defense companies.

Nature of the Study

The purpose of this quantitative correlational study was to examine the


in foreign exchange and currency risk management markets. The design of the study was

based on an analysis of secondary source. The quantitative correlational study was

theoretically informed by related literature on corporate hedging. A positivistic view was

used to develop a focus on theory testing, wherein corporate hedging theories were first

adopted as the framework for developing and testing hypotheses in the research context

(Trochim & Donnelly, 2008). Therefore, a deductive orientation of the study was

15

emphasized in the study (Trochim & Donnelly, 2008). Given the nature of the research

purpose, the research questions, and the adequate availability of previous empirical

studies to formulate hypothesized relationships for examination, the research design for

the study was a quantitative correlational design.

The population for the study consisted of 194 U.S. defense companies listed in the

NAARS database (American Institute of Certified Public Accountants, 2005). All 194

defense companies that conducted defense-related business from 2000 to 2010 in the U.S.

qualified for inclusion in the study. From this population, 55 U.S. defense companies

were randomly selected to ensure statistical significance. Seven constructed independent

variables were defined to represent the risk attributes of U.S. defense companies: (a)

financial distress, (b) underinvestment problems, (c) tax benefits, (d) managerial

incentives, (e) scale economies, (f) level of foreign involvement, and (g) revenues from

U.S. government contracts. The instruments to measure the independent variables were

debt ratio, income tax credit range, R&D spending, presence of corporate executives'

(CEO) stock shares, firm size, foreign sale ratio, and sales to U.S. government. The

constructed dependent variable for the study was defined as corporate hedging in foreign

exchange and currency risk management markets. Corporate hedging was measured as

the notional value of derivatives. All data were collected from the annual financial report

on Form 10-K and the annual proxy statement in the EDGAR database system of the

SEC.

In prior empirical studies, the outcome of corporate hedging decisions was

considered to be a linear function of the independent variables, which are proxies of the

determinants of corporate hedging (Allayannis & Weston, 2001; Berrospide,

16

Purnanandam, & Raj an, 2007; Carter et al., 2006; Hagelin, 2003; Jin & Jorion, 2006;

Judge, 2006; Khediri, 2010; Lei, 2006; Nguyen et al., 2007; Nguyen & Faff, 2010;

Spano, 2008; SprCic, 2007). In the current study, the relationship between each

independent variable and the dependent variable was measured as a bivariate linear

regression, with corporate hedging in foreign exchange and currency risk management

markets as the dependent variable and a U.S. defense company-specific risk attribute as

the independent variable. Bivariate linear regression analyses were performed to address

the research questions for the study. Parametric methods to test the hypotheses were used

because the normality, independence of errors, and equal variance assumptions for

performing a bivariate linear regression were met (Allen, 2004, Weiers, 2002).

Parametric linear regressions were used in prior empirical studies to determine similar

relationships (Carter et al., 2006; Hagelin, 2003; Hsu et al., 2009; Jin & Jorion, 2006;

Judge, 2006; Khediri, 2010; Lei, 2006; Nguyen et al., 2007; Nguyen & Faff, 2010;

Reynolds, Bhabra, & Boyle, 2009; Spano, 2008; SprCic, 2007). The following steps were

taken for conducting hypothesis testing to address the research questions in the study:

state the hypothesis to be tested, analyze the assumptions of underlying linear regression,

select test statistic used for measures of association, and define decision criterion to either

accept or reject the hypothesis (Allen, 2004; Lind, Marchal, & Mason, 2005; Zikmund,

2003). To support the interpretation associated with correlation in bivariate linear

regression analysis, the coefficient of determination and sign of regression coefficients

indicated the strength and direction of the association between the risk attributes of U.S.

defense companies and corporate hedging in foreign exchange and currency risk

management markets.

17

Significance of the Study

To compete in global markets as well as competitive and regulated environments,

U.S. defense companies are exposed to financial risks resulting in a potential loss of

millions of dollars of profits as a result of corporate hedging practices in foreign

exchange and currency risk management (The Boeing Company, 2009; Chance &

Brooks, 2007; Eiteman et al., 2007; Gregory, 2010; Lockheed Martin Corporation, 2009;

Stulz, 2003). Identifying and measuring the determinants for corporate hedging becomes

a critical battle for company managers in U.S. defense companies. If the relationship

between the risk attributes of U.S. defense companies and corporate hedging in foreign

exchange and currency risk management markets is conclusively demonstrated, the study

may provide useful insight for corporate hedging to company managers in the U.S.

defense industry, and may help to improve the effectiveness of strategic thinking and

decision-making for corporate hedging by U.S. defense companies in foreign exchange

and currency risk management markets.

The contribution of this study to the literature regarding corporate hedging is

significant given that U.S. defense companies potentially lose millions of dollars of

profits as a result of corporate hedging practices in foreign exchange and currency risk

management. In addition, no prior research studies have been conducted on corporate

hedging in risk management in terms of the risk attributes of U.S. defense companies.

Therefore, research designed to examine the relationship between the risk attributes of

U.S. defense companies and corporate hedging in foreign exchange and currency risk

management markets is merited. The current study was applied to add to the

understanding of the determinants of corporate hedging in foreign exchange and currency

18

risk management at the organizational level. Furthermore, the results of the study have

the potential to trigger further research into this relationship.

Definitions

Agency costs. Agency costs are "costs caused by management's ability to pursue

its own interests at the expense of the firm's shareholders" (Stulz, 2003, p. 645).

Bankruptcy costs. Bankruptcy costs are "the costs incurred as a result of a

bankruptcy filing" (Stulz, 2003, p. 645).

Counterparty risks. Counterparty risks are "the risk that a counterparty fails to

deliver the promised payoff, either because of being financially unable to do so or for

other reasons" (Stulz, 2003, p. 647).

Convex function. According to Jensen's inequality (Azar, 2008), iff(x) is a

convex function and x is a random variable with nonzero variance, the expectation of the

transform of a random variable x by a convex function is larger than the transform of the

expectation of x, that is, E(/(x)) >y(E(x)) (Azar, 2008). A tax function for a given

company is a convex function (Smith & Stulz, 1985).

Convexity. A convexity is "a curve above a straight line connecting two end

points" (Harvey, n.d., p. 376). This curve is used to describe characteristics of a tax

function for a given company.

Corporate Hedging. Corporate hedging is "a component of a more general

process called risk management, the alignment of the actual level of risk with the desired

level of risk" in a company (Chance & Brooks, 2007, p. 355).

19

Currency risk. Currency risk is "the risk that currency exchange rates may

change adversely for a business that has exposure to foreign currency" (Stephens, 2001,

P- 8).

Default. Default is the failure to make interest and principal payments as agreed

to in a debt agreement based on the terms and at the designated time set (Penman, 2007).

Derivative. A derivative is "an instrument whose price depends on, or is derived

from, the price of another asset" (Hull, 2006, p. 747).

Economic risk. Economic risk is

The risk to the firm's present value of future operating cash flows from exchange

rate movements. In essence, economic risk concerns the effect of exchange rate

changes on revenues (domestic sales and exports) and operating expenses (cost of

domestic inputs and imports). Economic risk is usually applied to the present

value of future cash flow operations of a firm's parent company and foreign

subsidiaries. (Papaioannou, 2006, p. 131)

Empirical study. An empirical study is "a study using available market data and

observation to draw conclusion" (Hancock-Weise, 2011, p. 471).

Exchange rate. An exchange rate is "the rate at which a unit of one currency is

exchanged for another" (Whaley, 2006, p. 877).

Fair Value of Derivatives. Fair value of derivatives is recorded at market value

on the balance sheet, either an asset or liabilities (Penman, 2007).

Financial Accounting Standard No. 133 (FAS 133). FAS 133 is an accounting

standard that requires derivatives are reflected on the balance sheet at fair market value

20

for U.S. companies (Ramirez, 2007). FAS 133 was issued by the Financial Accounting

Standards Board (FASB).

Financial distress. Financial distress is "a low cash-flow state of the firm in

which it incurs deadweight losses without being insolvent" (Purnanandam, 2007, p. 706).

Financial leverage. Financial leverage is the degree to which a company funds

business operation and investment by debts (Chance & Brooks, 2007).

Financial risk. Financial risk is "the risk associated with changes in such factors

as interest rates, stock prices, commodity prices, and exchange rate" (Chance & Brooks,

2007, p. 627).

Foreign debt. Foreign debt is the debt denominated in foreign currency (Aabo,

2006).

Foreign exchange risk. Foreign exchange risk is

The likelihood that an unexpected change in exchange rates will alter the home

currency value of foreign currency cash payments expected from a foreign source.

Also, the likelihood that an unexpected change home currency needed to repay a

debt denominated in a foreign currency. (Eiteman et al., 2007, p. EM-37)

Foreign involvement. Foreign involvement ranges from simple import or export

activity to more complicated decisions including integrated global sourcing, production,

and competition (Eiteman et al., 2007).

Foreign tax credit. Foreign tax credit is "the amount by which a domestic firm

may reduce (credit) domestic income taxes for income tax payments to a foreign

government" (Eiteman et al., 2007, p. EM-37).

21

Form 10-K. Form 10-K is a report required by the U.S. SEC, in which a

comprehensive overview of a company's business and financial condition, including

audited financial statements, is provided (Penman, 2007).

Forward contract. Forward contract is "one party agrees to buy the underlying

from another party at maturity of the contract and pay for it then a price agreed upon

when the contract is originated with no cash changing hands before maturity" (Stulz,

2003, p. 648).

Future contract Future contract is "a contract traded on an exchange enabling

one party to buy for future delivery and another to sell for future delivery with gains and

losses settled daily" (Stulz, 2003, p. 649).

Hedge. Hedge is "a transaction in which an investor seeks to protect a position or

anticipated position in the spot market by using an opposite position in derivatives"

(Chance & Brooks, 2007, p. 628).

Hedge accounting. Hedge accounting is

A form of accounting for derivatives transactions in which certain transactions,

qualifying as hedges, are accounted for in such a manner that the gains or losses

from hedges are, to an extent, limited by specified rules, combined with gains and

losses from transactions they are designed to hedge, so as to minimize the impact

on reported earnings. (Chance & Brooks, 2007, p. 628-629)

Hedging costs. Hedging costs are "costs of putting on a hedge; examples include

transaction costs, monitoring costs, and design costs" (Stulz, 2003, p. 649).

22

Information asymmetry. When one party to a transaction has more or superior

knowledge and information, the other party does not. This informational disparity is

referred as information asymmetry (DaDalt, Gary, & Nam, 2002).

International Accounting Standard No. 39 (IAS 39). IAS 39 is an international

accounting standard that requires derivatives are reflected on the balance sheet at fair

market value for corporations (Ramirez, 2007). IAS 39 was issued by the International

Accounting Standard Board (IASB).

Managerial incentives. Managerial incentives are the variation in company

managers' total equity holdings as a result of increases in stock prices (Core, Guay, &

Larcker, 2003).

Marginal tax rate. Marginal tax rate is "the highest rate at which income is

taxed" (Penman, 2007, p. 313). In the U.S., "the marginal tax rate is usually the

maximum statutory tax rate for federal and state taxes combined" (Penman, 2007, p.

314).

Net operating loss (NOL) carryback. NOL carryback is an accounting

technique that applies the current year's net operating losses to past years' profits in order

to reduce tax liability (Penman, 2007)

NOL carryforward. NOL carryforward is an accounting technique that applies

the current year's net operating losses to future years' profits in order to reduce tax

liability (Penman, 2007).

Notional value of derivatives. Notional value of derivatives is "the quantity of

the underlying used to determine the payoff of the derivative" (Stulz, 2003, p. 650).

23

Option. Option is "a contract granting the right to buy or sell an asset, currency,

or futures at a fixed price for a specific time period" (Chance & Brooks, 2007, p. 633).

Progressive tax function. A progressive tax function is a convex function that

indicates marginal tax rates are increasing in taxable income, in which "the tax on the

average of two possible outcomes is less than the average of the tax reckoned on each

outcome individually" (Brennan, 2010, p. 2).

Risk aversion. Risk aversion is "the characteristic referring to an investor who

dislike risk and will not assume more risk without an additional return" (Chance &

Brooks, 2007, p. 636).

Risk management. Risk management is "the practice of identifying the risk

level a firm desires, identifying the risk level it currently has, and using derivative or

another financial instruments to adjust the actual risk level to the desired risk level"

(Chance & Brooks, 2007, p. 636).

Scale economies. Scale economies "constitute the relationship between the size

of a firm (or plant) and its costs of production in the broadest sense" (Stigler, 1983, p.

67).

Swap. Swap is "an agreement to exchange cash flows in the future according to a

prearranged formula" (Hull, 2006, p. 757).

Tax benefit. Tax benefit is an allowable deduction on a taxpayer's tax liability

(Penman, 2007).

Transaction risk. Transaction risk is

Cash flow risk and deals with the effect of exchange rate moves on transactional

account exposure related to receivables (export contracts), payables (import

24

contracts) or repatriation of dividends. An exchange rate change in the currency

of denomination of any such contract will result in a direct transaction exchange

rate risk to the firm. (Papaioannou, 2006, p. 131)

Translation risk. Translation risk is "balance sheet exchange rate risk and

relates exchange rate moves to the valuation of a foreign subsidiary and, in turn, to the

consolidation of a foreign subsidiary to the parent company's balance sheet"

(Papaioannou, 2006, p. 131).

Underinvestment problem. Underinvestment problem is characterized by "the

instances wherein companies are unable to fund profitable investments projects due to the

lack of adequate financing" (Salvary, 2005, p. 89).

Summary

The U.S. defense companies are exposed to financial risks resulting in millions of

dollars of lost profits as a result of corporate hedging practices in foreign exchange and

currency risk management markets. The purpose of this quantitative correlational study

was to examine the relationship between the risk attributes of U.S. defense companies

and corporate hedging in foreign exchange and currency risk management markets. The

seven constructed independent variables for the study were defined as (a) financial

distress, (b) underinvestment problems, (c) tax benefits, (d) managerial incentives, (e)

scale economies, (f) level of foreign involvement, and (g) revenues from U.S.

government contracts. The constructed dependent variable for the study was defined as

corporate hedging in foreign exchange and currency risk management markets. A

correlational design was used. The instruments to measure the independent variables

were debt ratio, income tax credit range, R&D spending, presence of corporate

25

executives' stock shares, firm size, foreign sale ratio, and sales to U.S. government. The

instrument for the dependent variable was the notional value of derivatives. The outcome

of the study was a contribution to the understanding of corporate hedging for the U.S.

defense companies and may be employed to help improve the effectiveness of strategic

thinking and decision-making for corporate hedging among U.S. defense companies in

foreign exchange and currency risk management markets. The need and purpose for the

study was established within this chapter; the theoretical framework, research questions,

hypotheses, research methods, nature of the study, and significance were summarized;

and definitions of key terms were provided.

26

Chapter 2: Literature Review

Company managers in the U.S. defense industry perform corporate hedging in

risk management on a regular basis, as documented in the annual financial reports (The

Boeing Company, 2009; Lockheed Martin Corporation, 2009). The problem addressed

within the study was that U.S. defense companies are exposed to financial risks resulting

in millions of dollars of lost profits as a result of corporate hedging practices in foreign

exchange and currency risk management markets (The Boeing Company, 2009; Chance

& Brooks, 2007; Eiteman et al., 2007; Gregory, 2010; Lockheed Martin Corporation,

2009; Stulz, 2003). Although the theoretical consideration and empirical evidence

indicated a range of factors that might influence corporate hedging, the relationship


exchange and currency risk management is not clear. The quantitative correlational study

was used to examine the relationship between the risk attributes of U.S. defense


markets.

The literature search on corporate hedging in foreign exchange and currency risk

management was a significant step in the research process for the study. Since whether a

particular source would be cited in the literature review for the study was unknown, a

complete record of all of the bibliographic information from sources was developed for

the study. Search strategies for the study were to locate books that are currently accepted

reference texts in corporate hedging and find out who has cited the books in recent years

and to search original (seminal) journal papers and identify who has cited the papers in

recent years. Once information related to corporate hedging in foreign exchange and

27

currency risk management was located, the following step was to summarize the

information into a coherent literature review section for the study. To identify which

sources were applicable to the study and in what context sources were related to the

subject of the study, Booth, Colomb, and Williams (1995) suggested to become familiar

with the geography of the source, locate the point of the argument, identify key sub-

points, identify key themes, and skim paragraphs. Finally, literature material relevant to

corporate hedging in foreign exchange and currency risk management were focused

without spending time on the literature material that was at best only marginally related.

Most of references cited in the study are from books and peer-reviewed journals.

To assess the relationship between risk attributes and corporate hedging using

derivative instruments is a complex task (Artez & Bartram, 2010; Nguyen & Faff, 2010).

To measure the theoretical risk attributes as determinants of corporate hedging in foreign

exchange and currency risk management is difficult (Nguyen & Faff, 2010; Stulz, 2003).

The determinants of corporate hedging in foreign exchange and currency risk

management can differ across different industry sectors and companies with different

characteristics (Adam et al., 2007; Bartram et al., 2009; Lei, 2006; Papaioannou, 2006;

Rogers, 2002). Therefore, the theoretical discussions, the information from prior

empirical evidence, and the discussion of specific characteristics of the U.S. defense

industry were a theoretical framework upon which the study was built on.

In this chapter, the literature review begins with the importance of identifying

determinants of corporate hedging in risk management followed by the theoretical and

empirical research on corporate hedging in risk management pertaining to the constructs

for the study. In the literature review, theoretical discussions relevant to these constructs

28

are organized into sections to create a context for comprehension of the theoretical

rationale of corporate hedging and to help readers understand the study. In the final

review of literature, specific information and studies on corporate hedging in foreign

exchange and currency risk management are highlighted and followed by a summary of

the chapter.

Overview

Corporate hedging is the process that is used to reduce risk of loss against

negative outcomes within the capital market (Chance & Brooks, 2007). Corporate

hedging policy is a controversial subject in risk management (Stulz, 2003). By

facilitating the access of U.S. companies to international capital markets and enabling

U.S. companies to lower the cost of funds while diversifying the funding sources,

corporate hedging improves the position of U.S. companies in an expanding, competitive,

and global economy (Eiteman et al., 2007). However, the dramatic growth of corporate

hedging activities in risk management coupled with the derivatives-related losses has

resulted in millions of dollars of lost profits in U.S. companies (The Boeing Company,

2009; Chance & Brooks, 2007; Eiteman et al., 2007; Gregory, 2010; Lockheed Martin

Corporation, 2009; Stulz, 2003). The recent economic and financial crisis has further

accentuated the importance of understanding the incentives of corporate hedging

practices for U.S. companies. Identifying corporate hedging becomes an essential

component of corporate hedging strategy in risk management (Artez & Bartram, 2010;

Petersen & Thiagarajan, 2000; Stulz, 2003).

Theoretical and empirical researchers of corporate hedging in risk management

have focused on the question of what factors are used to justify corporate hedging

29

decisions when companies hedge a given risk (Artez & Bartram, 2010; Petersen &

Thiagarajan, 2000; Stulz, 2003). Viewed from a finance theory developed by Modigliani

and Miller (1958), corporate hedging policy is irrelevant in shareholder value creation.

However, characterized by corporate hedging theories, companies have incentives to

hedge (Artez & Bartram, 2010; Stulz, 2003). In the absence of capital market

perfections, the Modigliani and Miller (1958) framework does not hold (Eiteman et al.,

2007). Therefore, research studies, based on corporate hedging theories, were developed

to empirically test various factors to explain corporate hedging behavior in risk

management (Artez & Bartram, 2010; Stulz 2003). Despite extensive empirical research

studies in corporate hedging, the actual determinants of corporate hedging at the

organizational level remain uncertain (Artez & Bartram, 2010; Nguyen & Faff, 2010;

Stulz, 2003).

According to the Modigliani and Miller (1958) framework, perfect capital market

assumptions are no taxes, no transaction costs, no symmetric information between

company managers and shareholders, rational investors and markets, no costs of

bankruptcy, and aligned interests between company managers and shareholders. Under

these assumptions, corporate financing policy cannot be attributed to the shareholder

value creation because shareholders manage their own financial risks by holding well-

diversified portfolios (Modigliani & Miller, 1958). Corporate hedging policy is a

component of corporate financing policy because financial claims using derivative

instruments against a firm are involved (Stulz, 2003). Therefore, the Modigliani and

Miller (1958) framework can be extended to the application of corporate hedging

(Stiglitz, 1974). Under the perfect capital market assumptions defined by Modigliani and

Miller (1958), corporate hedging in foreign exchange and currency risk management is

irrelevant in value creation (Stiglitz, 1974). However, since the capital market is

imperfect, corporate hedging does matter in foreign exchange and currency risk

management (Artez & Bartram, 2010; Stulz 2003). Corporate hedging theories, based on

shareholder value maximization and managerial utility maximization, are utilized to

explain the reasons companies may require corporate hedging in a real financial world.

From the shareholder maximization theory, corporate hedging can be used to

reduce the various costs involved with future cash flows including costs of financial

distress, external financing, taxes, and underinvestment costs (Froot et al., 1993; Graham

& Smith, 1999; Smith & Stulz, 1985). First, corporate hedging can reduce the expected

transaction costs of financial distress by reducing the probability of incurring these costs

(Smith & Stulz, 1985). Second, since corporate tax expenses are a progressive tax

function to the taxable income of a company, corporate hedging can reduce the variability

of taxable income and the expected value of taxes (Graham & Smith, 1999; Smith &

Stulz, 1985). Third, corporate hedging ensures companies have sufficient internal funds

that enable the companies to mitigate unnecessary fluctuations in either investment

spending or costly external financing (Froot et al., 1993).

The primary theoretical alternative to the shareholder value maximization as a

corporate hedging theory is managerial utility maximization. From the managerial utility

maximization theory, company managers may seek to maximize their own self-interest at

the expense of shareholders because the company managers understand better than the

shareholders if the company's objectives the shareholders consider important can be met

(Jensen & Meckling, 1976). Furthermore, the company managers have the capability to

31

behave in their own self-interest rather than in the best interests of the shareholders

(Jensen & Meckling, 1976). Stulz (2003) indicated company managers have an incentive

to hedge their own wealth, which is aligned with the job performance at the expense of

the shareholders. Jensen and Meckling (1976) suggested the managerial compensation

policy can be "designed to give the manager incentives to select and implement actions

that increase shareholder wealth" (p. 226). Company managers may be interested in

protecting the company's profitability through corporate hedging in risk management

because of a possible change in corporate asset value (Shapiro, 2005). In addition,

company managers may have different risk preferences. The company managers are

essentially willing to consider risk-free prospects in financial decisions (Morellec &

Smith, 2007; Shapiro, 2005). Therefore, the company managers may be likely to be risk-

averse under uncertainty (Morellec & Smith, 2007; Shapiro, 2005).

Other possible justifications explore additional factors not well explained by the

corporate hedging theories. Jorion (1990) found the degree of foreign exchange and

currency risk exposure varies directly with the degree of foreign involvement and the

fluctuations of foreign exchange rate. Corporate hedging with financial derivatives was

found by Brown (2001) to depend on accounting reporting methods and foreign exchange

volatility. Judge (2006) indicated the level of foreign debt and foreign currency sales are

related to corporate hedging decisions.

According to Allayannis and Ofek (2001), large companies are more likely to

hedge than small companies. Market values of companies for derivative users are higher

than for non-users (Allayannis & Ofek, 2001). However, it was posited by Nance et al.

(1993) that smaller companies should hedge more than larger ones. Dolde and Mishra

(2007) argued the extent of information asymmetry about exposures of financial risks

between company managers and shareholders influences the likelihood of corporate

hedging. Firm value and corporate hedging have been reported to be significantly related

(Kapitsinas, 2008). Changes in reporting corporate hedging activities were documented

by Supanvanij and Strauss (2010) as having influenced the relationship between

executive compensation packages and use of financial derivatives. Furthermore, Adam,

Dasgupta, and Titman (2007) stated corporate hedging in financial risks depends on

industry-specific characteristics. Corporate governance mechanisms were demonstrated

by Lei (2006) and Marsden and Prevost (2005) as having an impact on the use of

financial derivatives in risk management. Finally, Bartram et al. (2009) and Marsden and

Prevost (2005) substantiated the legal support involvement in corporate hedging

decisions.

In summary, the theoretical area of interest for the study is determinants of

corporate hedging in risk management. Corporate hedging theories and empirical studies

of additional risk factors associated with corporate hedging are the foundation of the

study of the organizational determinants of hedging (Stulz 2003). The existing corporate

hedging literature indicated a range of factors that might influence corporate hedging

decisions in risk management (Artez & Bartram, 2010; Stulz 2003). If these factors do

matter in corporate hedging decisions, and if company managers could determine which

factors are critical to corporate hedging, the reduction of risks associated with corporate

hedging practices would be significant (Nguyen & Faff, 2010; Stulz, 2003).

Two main classes of theoretical explanations of why company managers engage

in corporate hedging practices are shareholder value maximization and managerial utility

33

maximization. Empirical studies have been applied in the exploration of additional

factors associated with corporate hedging in risk management, such as scale economies,

firm value, information asymmetry, level of foreign involvement, foreign debt, industry-

specific characteristics, country-specific characteristics, and account reporting methods

(Artez & Bartram, 2010; Stulz, 2003). Among the various company-specific factors

associated with corporate hedging in foreign exchange and currency risk management,

emphasis has been placed on financial distress, tax benefits, underinvestment problems,

managerial incentives, scale economies, and level of foreign involvement (Allayannis &

Ofek, 2001; Stulz, 2003). In spite of the fact that the theoretical and empirical evidence

on these company-specific determinants of corporate hedging are available, much

controversy remains about the effects of these company-specific determinants on

corporate hedging (Artez & Bartram, 2010; Nguyen & Faff, 2010; Stulz, 2003). In this

chapter, each of the company-specific determinants on corporate hedging in foreign

exchange and currency risk management will be presented with special reference to

corporate hedging in the U.S. defense industry, which applies to the study.

Financial Distress

Financial distress can impose significant costs on a company (Andrede & Kaplan,

1998; Korteweg, 2006). Companies that are significantly exposed to the exchange rate

fluctuations would derive benefits from corporate hedging because corporate hedging

reduces the costs of financial distress such as default and bankruptcy costs (Smith &

Stulz, 1985). Shareholders will be interested in corporate hedging to reduce the

probability of financial distress (Stulz, 2003). The costs of financial distress include not

only litigation expenses such as lawyer's and court fees and direct bankruptcy costs

(Andrede & Kaplan, 1998; Warner, 1977; Weiss, 1990), but less quantifiable effects of

financial trouble such as damage to the company's reputation, the loss of key employees

and customers, and the loss of value from foregone investment opportunities (Andrede &

Kaplan, 1998; Korteweg, 2006).

Warner (1977) and Weiss (1990) estimated the direct costs of litigation fees and

bankruptcy to be about 3 to 5% of total firm value at the time of financial distress.

However, a far greater consequence is the costs stemming from customers who are

reluctant to buy from a distressed company, high-quality employees who leave, company

managers who are distracted from running the business because of financing distress, and

potential investment opportunities that are missed because of insufficient capital funds

(Andrede & Kaplan, 1998; Korteweg, 2006). Andrede and Kaplan (1998) found the total

loss in firm value attributable to financial distress in the range of 10 to 23% of pre-

distress firm value. Korteweg (2006) stated the costs of financial distress are 31% of firm

value on average across industries if companies are at bankruptcy and the equity of a

company is zero. Since financial distress is costly to a company, a company has an

incentive to hedge the exposure of financial risks by reducing the costs of financial

distress. As such, "firms with a high probability of default and/or high financial distress

costs should be more likely to engage in corporate hedging" (Artez & Bartram, 2010, p.

348).

The magnitude of the costs of financial distress can be defined by the size and

exposure of a company's financial leverage (Geczy, Minton, & Schrand, 1997). A

company's financial leverage is the degree to which a company funds business operation

and investment by debts (Chance & Brooks, 2007). As payments of debts and interest

35

constitute obligations the debtholders are legally entitled to, debts put pressure on the

company. A distressed company more likely experiences difficulties of the payments of

debts and interest (Smith & Stulz, 1985). If the company does not meet the financial

obligations in time, financial distress occurs, followed by default and bankruptcy.

Therefore, the higher levered company with debts might have a strong incentive to hedge

(Geczy et al., 1997; Smith & Stulz, 1985).

Graham and Rogers (2002) illustrated companies with higher financial leverage in

long-term debt will typically hedge with foreign currency derivatives. Corporate hedging

may increase debt capacity and the present value of the tax benefits (Graham & Rogers,

2002). However, a large amount of debt may also increase the degree of financial

distress and probability of default and bankruptcy, which in turn may increase the

incentive for companies to hedge (Graham & Rogers, 2002). Nguyen and Faff (2003)

analyzed a sample of469 Australian nonfinancial companies and confirmed companies

with debts in the capital structure are more likely to hedge foreign currency risk

exposure. From a sample of 493 U.S. nonfinancial companies with sales exceeding $1

billion, Dolde and Mishra (2007) supported a strong positive relationship between

financial leverage and use of derivative instruments exists at the corporate level in

foreign exchange and currency risk management. Spano (2008) collected annual

financial data from 443 nonfinancial companies in United Kingdom and affirmed the

higher levered companies intend to hedge. The findings from these empirical studies are

consistent with Smith and Stulz's (1985) theory.

However, empirical results on costs of financial distress and corporate hedging

are varied. A large number of recent empirical studies confirmed financial leverage is

36

significantly positive related to corporate hedging (Bartram et al., 2009; Berkman, 2002;

Berrospide et al., 2007; Dolde & Mishra, 2007; Graham & Rogers, 2002; Haushalter,

2000; Lei, 2006; Nguyen & Faff, 2003; Reynolds et al., 2009; Schiozer & Saito, 2009;

Spand, 2008). In contrast, Allayannis and Ofek (2001) suggested the relationship

between financial leverage and corporate hedging is positively insignificant. Davies et al.

(2006) and SprCic (2007) indicated no evidence is found to support financial leverage is

an explanatory factor for corporate hedging. Hagelin (2003) and Hagelin, Holmen,

Knopf, and Pramborg (2007) stated financial leverage is negatively associated with

corporate hedging. Judge (2006) further acknowledged financial leverage with the level

of debt is not a good measure for costs of financial distress.

According to the Standard & Poor's industry survey for aerospace and defense

industries, a 30-year average debt ratio is about 60% in the defense industry, and the debt

ratio is widely varied among U.S. defense companies (Tortoriello, 2011). The U.S.

defense companies with foreign subsidiaries or U.S. defense companies that hold foreign

debts or foreign currencies are more susceptible to financial distress because of high

financial leverage. As a result, financial leverage may vary directly with corporate

hedging in U.S. defense industry.

Financial distress is one of the key elements in shareholder value maximization

theory used to explain corporate hedging (Smith & Stulz, 1985). Both theoretically and

empirically, financial distress can impose significant costs on a company (Andrede &

Kaplan, 1998; Korteweg, 2006; Warner, 1977; Weiss, 1990). Companies that face

greater risk of financial distress with the implicit and explicit costs contained may benefit

from corporate hedging (Artez & Bartram, 2010). Through corporate hedging, reduction

37

in the probability of financial distress will result in improvement of a company's ability

to increase financial leverage (Graham & Rogers, 2002). However, high financial

leverage increases the degree of financial distress and probability of default and

bankruptcy, which in turn increases the incentive for companies to hedge (Smith & Stulz,

1985).

Despite the theoretical analysis of financial distress, empirical results on the

relationship between costs of financial distress and corporate hedging are not without

ambiguity. Highly levered U.S. companies are more susceptible to financial distress.

Therefore, financial leverage in U.S. defense companies may be directly related to

corporate hedging decisions in foreign exchange and currency risk management (Geczy

et al. 1997; Graham & Rogers, 2002; Smith & Stulz, 1985).

While high debt capacity for a company increases, a degree of financial distress

and probability of default and bankruptcy increases (Graham & Rogers, 2002). Debts

also have tax advantages because the interest payments are made from pre-tax earnings

(Penman, 2007; Smith & Stulz, 1985). As such, the question exists whether tax benefits

are related to corporate hedging decisions in risk management situations.

Tax Benefits

A progressive tax is convex (Smith & Stulz, 1985). The principle of progressivity

is reflected in much of the U.S. tax system (Graham & Smith, 1999; Smith & Stulz,

1985). Corporate marginal tax rates vary as a convex function of the level of taxable

income in the U.S. (Graham & Smith, 1999; Smith & Stulz, 1985). Companies pay a

higher corporate marginal tax rate at higher levels of total taxable income. Therefore, the

U.S. tax system has significant convexity (Graham & Smith, 1999; Smith & Stulz, 1985).

38

Companies face nonlinear tax schedules in which varying corporate marginal tax

rates introduce a company-specific source of risk. The issue of nonlinear taxation is

commonly referred to as the tax convexity problem (Smith & Stulz, 1985). When a

company's tax liabilities increase more than proportionally with the level of expected

taxable income, the demand for corporate hedging may increase (Smith & Stulz, 1985)

because corporate hedging can stabilize the level of expected taxable income, and thus

lower corporate marginal tax rates. The benefits of corporate hedging are illustrated in

Figure 1. The minimum and maximum limits of pre-tax income of a company are

denoted with Xi or XH, respectively. The possible pre-tax incomes are ordered from

Y(X„)

Y'(Xo)

u Y(Xo)

XL

Pre-Tax Income

Figure 1. Tax benefits in corporate hedging.

39

state Xl to state Xh- The possible post-tax incomes of a company are given a convex

solid line, which exhibits progressive tax liabilities. According to Jensen's inequality

(Azar, 2008), the convex transformation of a mean is less than or equal to the mean after

convex transformation. If a company's tax liabilities are a convex function of the pre-tax

income, the expected tax liabilities will be smaller at the average pre-tax income level Xo

than what the tax liabilities will be if the company has increases and decreases in pre-tax

income around the average income level Xo (Gagnon, Khoury, & Landry, 2010; Smith &

Stulz, 1985). As such, the expected post-tax income at the average pre-tax income level

X0 will be higher (Gagnon et al., 2010; Smith & Stulz, 1985). Therefore, stabilizing pre

tax income through corporate hedging is beneficial to the company (Smith & Stulz,

1985).

The theoretical analysis of the impact of tax convexity on corporate hedging was

provided by Smith and Stulz (1985). For a given company, the convexity of progressive

tax function depends upon the schedule of marginal tax rates, but also upon a number of

tax preference items such as NOL carrybacks, NOL carryforwards, investment tax

credits, and foreign tax credits (Smith & Stulz, 1985). The corporate income tax in the

U.S. provides only limited tax relief to companies that report a net operating loss

(Penman, 2007). Companies that have paid positive taxes during the three years prior to

the loss year may carry back the net operating loss and receive a tax refund (Graham &

Rogers, 2002; Smith & Stulz, 1985). The total of the tax refund cannot exceed the total

tax payments in the three years (Penman, 2007). If a company exhausts the net operating

loss carrybacks, the company may carry the net operating loss forward to corporate

income for 20 future years (Penman, 2007). However, the NOL carryforwards can only

40

be applied if pre-tax earnings are positive (Penman, 2007). If a company faces lower

earnings prospects for the near future, the present discounted tax benefits associated with

accumulated NOL carryforwards positively vary with pre-tax earnings due to the time

value of money (money in hand today is worth more than money that is expected to be

received in the future) and possible time limits on the use of NOL carryforwards (Graham

& Smith, 1999; Penman, 2007; Smith & Stulz, 1985). A similar reasoning applies for

any other tax preference items that can only be counted against positive earnings and

have a time limitation on the use of any other tax preference items such as investment tax

credits and foreign tax credits. To increase the probability of taking advantage of tax

preference items, companies with more tax preference items have benefits to intensify

corporate hedging activities (Graham & Smith, 1999; Smith & Stulz, 1985). Therefore, a

more significant convexity of progressive tax function will lead to a likelihood of

corporate hedging (Graham & Smith, 1999; Smith & Stulz, 1985).

Graham and Smith (1999) provided the empirical evidence on the potential tax

benefits to companies from corporate hedging by looking at the tax structures of U.S.

companies. Graham and Smith (1999) estimated about 50% of all U.S. companies face

convex tax functions where corporate tax rates increase with corporate taxable income.

Graham and Smith (1999) evaluated the potential tax savings to the U.S. companies and

concluded tax savings are substantial for 20% of the U.S. companies with convex tax

rates. In some cases, the tax savings amounted to more than 40% of the overall tax

liability. In agreement, Gagnon et al. (2010) indicated the potential tax savings through

corporate hedging is significant. The potential tax savings resulting from NOL

carryforwards were 16.5 to 33% of the tax liabilities to Canadian nonfinancial companies

41

(Gagnon et al., 2010). Furthermore, Berrospide, Purnanandam, and Rajan (2007) studied

167 Brazilian nonfinancial companies and found the companies hedge to increase debt

capacity, and therefore higher tax benefits. The findings from these empirical studies are

consistent with the expectations of Smith and Stulz (1985).

However, empirical evidence on the relationship between tax benefits and

corporate hedging is mixed. Berrospide et al. (2007), Gagnon et al. (2010), Graham and

Smith (1999), and Lin and Smith (2007) confirmed tax convexity and corporate hedging

are positively and significantly related while Spano (2008) found the relationship

between tax convexity and corporate hedging is positively weak. In contrast, Benson and

Oliver (2004), Carter et al. (2006), Jalilvand (2009), Ramlall (2009), and Sprdic (2007)

suggested tax convexity is not associated with corporate hedging. Knopf, Nam, and

Thornton (2002) indicated tax convexity is insignificantly and negatively related to

corporate hedging activities. Graham and Rogers (2002) and Purnanandam (2007)

concluded companies with higher tax convexity hedge less than others.

In theory, U.S. defense companies pay a 35% marginal tax rate on the profits the

U.S. defense companies earn (Graham & Rogers, 2002; Penman, 2007). Tax benefits

received by U.S. defense companies were documented in the annual financial reports

such as R&D tax credits (The Boeing Company, 2009; Lockheed Martin Corporation,

2009). However, whether a convexity of progressive tax function relates to corporate

hedging for U.S. defense companies is unknown.

The development of tax benefits in shareholder value maximization theory has

attracted as much scholarly attention as has the theoretical and empirical relationship

between tax benefits and corporate hedging in risk management (Graham & Smith, 1999;

42

Smith & Stulz, 1985). At a theoretical level, companies benefit from corporate hedging

due to tax incentives (Graham & Smith, 1999; Smith & Stulz, 1985). When a company's

tax liabilities increase more than proportionally with the level of expected taxable

income, corporate hedging can stabilize the level of expected taxable income (Graham &

Smith, 1999; Smith & Stulz, 1985) and lower corporate marginal tax rates. Furthermore,

Smith and Stulz (1985) indicated for a given company, the convexity of progressive tax

function depends upon the schedule of marginal tax rates, but also upon a number of tax

preference items including NOL carrybacks, NOL carryforwards, investment tax credits,

and foreign tax credits (Smith & Stulz, 1985).

The theoretical tax incentives on corporate hedging are partly supported by

empirical testing. Empirical evidence on the relationship between tax benefits and

corporate hedging is inconclusive. Given the conflicting results of empirical testing,

whether the relationship between tax benefits and corporate hedging for U.S. defense

companies exists is not clear.

With decreases in costs of financial distress and increases in tax benefits through

corporate hedging, funds can be effectively committed to R&D investment projects for

companies with abundant growth opportunities (Froot et al., 1993). Furthermore, costly

external financing for these R&D investment projects can be avoided (Froot et al., 1993).

For company managers to ensure companies are financed at the lowest possible costs,

providing an answer to a question of whether underinvestment problems are associated

with corporate hedging decisions becomes important in risk management (Froot et al.,

1993; Stulz, 2003).

43

Underinvestment Problems

A company's growth opportunities affect investment decisions (Eiteman et al.,

2007; Stulz, 2003). Because a company's growth opportunities require sizable outlays of

funds that commit a company to a given course of action (Eiteman et al., 2007; Froot et

al., 1993), a company with abundant growth opportunities may have underinvestment

problems to the extent the positive net present value (NPV) investments in growth

opportunities available are not chosen (Eiteman et al., 2007; Froot et al., 1993; Stulz,

2003). Therefore, guarding against underinvestment problems becomes an important

reason to hedge (Froot et al., 1993; Stulz, 2003).

Underinvestment problems, as described by Froot et al. (1993), are important to a

company with high R&D investment opportunities for reasons. First, faced with R&D

investment opportunities, company managers often raise capital through both internal

funds and external financing. When external financing costs more than internal funds,

and investment spending is cut because internally generated cash flows are not sufficient

to finance the R&D investment opportunities, corporate hedging can reduce the

variability of the internal funds to make sure the company has sufficient internal funds

required by the R&D investment opportunities, and thus the costs of underinvestment

are reduced (Froot et al., 1993). Next, company value is related to the anticipated future

cash flows. Foreign exchange rate movements can reduce the future cash flows and

lower a company's ability to invest in other profitable R&D projects (Graham & Rogers,

2000). Finally, R&D investment expenditure is used to indicate the intensity of R&D

investment opportunities within a company. Because of the uncertainty of the payoff

from R&D investment expenditures, the value of the R&D investment opportunities are

44

unlikely to be fully recognized in bankruptcy (Froot et al., 1993). Therefore, to alleviate

underinvestment problems, companies with high investment opportunities should

increase corporate hedging (Froot et al., 1993).

Carter et al. (2006) investigated jet fuel and hedging policies in the U.S. airline

industry and found capital expenditures exhibit a positive relationship with the amount of

corporate hedging. Graham and Rogers (2000) analyzed 531 companies' financial data

in annual reports and found corporate hedging with derivatives is positively related to

measures of the company's investment opportunity represented by R&D expenditures.

Graham and Rogers' (2000) empirical results showed the use of derivative instruments is

driven by the need to avoid potential underinvestment problems. By sampling 364

nonfinancial companies from 34 countries, Lei's (2006) empirical evidence indicated the

companies with high investment opportunities hedge more with derivative instruments.

Hsu et al. (2009) studied 624 nonfinancial companies in Taiwan and confirmed

companies with more growth investment opportunities will use more derivative

instruments for corporate hedging. These empirical results are consistent with the

predictions of Froot et al. (1993).

However, empirical studies on relationship between underinvestment problems

and corporate hedging have produced mixed results. Carter et al. (2006), Crabb (2006),

Graham and Rogers (2000), Hsu et al. (2009), Lei (2006), Mseddi and Abid (2010),

Sprdic (2007), and Schiozer and Saito (2009) reported a significantly positive relationship

between investment opportunities and corporate hedging while Spano's (2008) results

were mixed. However, Purnanandam (2007) pointed out a positive relationship between

R&D investment expenditure and corporate hedging was not supported. Bartram et al.

45

(2009), Dolde and Mishra (2007), Geczy et al. (1997), and Lin and Smith (2007)

suggested a significantly negative relationship between investment opportunities and

corporate hedging.

R&D investment opportunities have been pointed out as a major engine of growth

in the U.S. defense industry (The Boeing Company, 2009; Lockheed Martin Corporation,

2009; Watts, 2008). Significant amounts of funds in R&D for U.S. government programs

and weapon systems have been spent within U.S. defense companies (Arnold, Harmon,

Tyson, Fasana, & Wait, 2009; Tortoriello, 2011). The U.S. defense companies with

R&D investment opportunities have greater potential for future profitability and sales

growth (Froot et al., 1993). However, R&D investment expenditure in U.S. defense

companies may be limited due to the foreign exchange and currency risk (The Boeing

Company, 2009; Lockheed Martin Corporation, 2009). Therefore, underinvestment

problems described by Froot et al. (1993) are critical to U.S. defense companies with

more investment opportunities. Nevertheless, whether underinvestment problems are

positively associated with corporate hedging in the U.S. defense industry is unclear.

In order to reduce underinvestment problems, investment opportunities related to

corporate hedging have been subjected to intense theoretical and empirical investigation

(Froot et al., 1993; Stulz, 2003). In theory, investment opportunities of a company

demand for sufficient cash flows, and the cash flows impact of a company's investment

decision matters (Froot et al., 1993). All growth companies with low levels of internally

generated funds may be vulnerable to underinvestment problems (Eiteman et al., 2007;

Froot et al., 1993; Stulz, 2003). To alleviate underinvestment problems, companies with

R&D investment opportunities will hedge to reduce the variability of the internal funds so

46

the companies have adequate internal funds to finance the R&D investment opportunities

(Froot et al., 1993).

The empirical support for the linkage between underinvestment problems and

corporate hedging is documented. However, different conclusions concerning this

relationship are made in the empirical testing. Although the reduction of

underinvestment problems is important to U.S. defense companies with abundant

investment opportunities (The Boeing Company, 2009; Froot et al., 1993; Lockheed

Martin Corporation, 2009), further documentation of the relationship between

underinvestment problems and corporate hedging in U.S. defense industry is lacking.

Since growth companies with low levels of internally generated funds may be

subjected to underinvestment problems (Eiteman et al., 2007; Froot et al., 1993; Stulz,

2003), high growth opportunities may exacerbate conflicts between company managers

and shareholders due to the wider latitude company managers have in investment

decisions (Jensen & Meckling, 1976; Shapiro, 2005). These investment decisions are

especially difficult for shareholders to monitor (Shapiro, 2005). As such, managerial

incentives may relate to corporate hedging in risk management for growth companies

through reduction of the agency costs of the company manager-shareholder relationship

(Jensen & Meckling, 1976; Smith & Stulz, 1985; Tufano, 1996).

Managerial Incentives

The conflicts of interest in the company manager-shareholder relationship can

predict strategic managerial behaviors of company managers (Jensen & Meckling, 1976;

Shapiro, 2005). Jensen and Meckling (1976) defined an agency relationship as "a

contract under which one or more persons-the principal(s)-engage another person-the

47

agent-to perform some service on their behalf that involves delegating some decision

making authority to the agent" (p. 378). Within a mutually agreed-upon contractual

relationship, a principal will delegate some or all of the decision-making power to an

agent. For instance, shareholders (principals) grant the decision-making power to

managers (agents) of a company. The decision-making power is acknowledged in the

belief the agent can effectively take the responsibilities due to the agent's specialized and

professional expertise (Jensen & Meckling, 1976; Shapiro, 2005). Within the mutually

agreed-upon contractual relationship, compensation incentives for the agent, distribution

of responsibilities, appropriation of corporate ownership rights, and information systems

monitoring the agents' behaviors are defined (Jensen & Meckling, 1976; Shapiro, 2005).

When shareholders (principals) employ company managers (agents) to act on the

shareholders' behalf, the prosperity of the shareholders is affected by the decisions of the

company managers (Jensen & Meckling, 1976; Shapiro, 2005). Potential conflicts of

interest may arise, which result from the divergence of the company's objectives between

shareholders and company managers (Jensen & Meckling, 1976; Shapiro, 2005). Such

conflicts of interest between shareholders and company managers do not lead to

maximization of shareholders' value. As such, the potential conflicts of interest in the

company manager-shareholder relationship must always be considered in corporate

hedging behavior analysis (Jensen & Meckling, 1976; Smith & Stulz, 1985; Tufano,

1996). As stated by Lambert (2001), the impact of the conflicts of interest between

shareholders and company managers should be examined because of differential risk

preferences of company managers and shareholders, the delegation of decision-making

48

power from shareholders to company managers, and allocation of resources by company

managers for their own benefits.

Shareholders are considered to be risk-neutral in the preference of risk

management for financial decisions since the shareholders can efficiently diversify the

shareholdings of many different securities from several collective companies (Morellec &

Smith, 2007). In contrast, risk-averse company managers have limited ability to

capitalize the employment status and to diversify the financial risks for the private wealth

because the company managers' compensation incentives and employment status are

inevitably attached to the company (Shapiro, 2005; Stulz, 2003). As a result, the

company managers are essentially willing to consider risk-free prospects in corporate

hedging decisions (Morellec & Smith, 2007; Shapiro, 2005; Stulz, 2003) so that

exposures of the company managers' private wealth are reduced.

Because of the delegation of decision-making power from shareholders to

company managers, the possibility of the divergence of company objectives between

shareholders and company managers is created (Jensen & Meckling, 1976; Shapiro,

2005). Larger companies and the more diverse shareholders will indicate the divergence

of company objectives between shareholders and company managers more likely exists

(Jensen & Meckling, 1976; Shapiro, 2005). Company managers may seek to maximize

their own self-interest and have incentives to hedge their private wealth at the expense of

the shareholders (Jensen & Meckling, 1976; Shapiro, 2005; Stulz, 2003).

From an organizational perspective, company managers might not adequately

support the interests of shareholders due to moral hazard (Jensen & Meckling, 1976;

Shapiro, 2005). Moral hazard is defined as the tendency among agents to abuse the

49

resource allocation authorities delegated to them through the agency contract to

maximize their own welfare and establish their positions within the company (e.g.,

acquisition decisions and luxury spending) even if these actions lead to de-optimizing the

best interests of principals (Heath, 2009). To reduce the moral hazard from an

organizational perspective, shareholders (principals) have to oversee company managers'

(agents') actions and reward the company managers when the company's objectives the

shareholders consider important are met (Eisenhardt, 1989; Jensen & Meckling, 1976;

Shapiro, 2005; Smith & Stulz, 1985; Tufano, 1996).

To prevent company managers to act in advancing their own private wealth at the

expense of the shareholders, managerial compensation policy must be designed and

aimed at inducing company managers to act in the best interest of shareholders by

maximizing the value of the company (Coles, Daniel, & Naveen, 2004; Jensen &

Meckling, 1976; Perry & Zenner, 2000; Smith & Stulz, 1985; Tufano, 1996). By making

managerial compensation policy a convex function of company performance,

shareholders can discourage "managers from devoting excessive resources to hedging"

(Smith & Stulz, 1985, p. 401). Higher levels of such managerial compensation policy

should ultimately lead to higher company performance (Jensen & Meckling, 1976).

Therefore, including stock and option holdings, elements in managerial compensation

policy may "better align the interests of managers and shareholders" (Lei, 2006, p. 21)

and mitigate the tendency for risk-averse company managers to hedge (Smith & Stulz,

1985; Tufano, 1996).

The use of stock and option holdings in managerial compensation policy is

generally one of the most effective means of aligning the interests of company managers

50

and shareholders because the stock and option holdings are seen as an increase of

managerial ownership (Coles et al., 2004; Perry & Zenner, 2000; Smith & Stulz, 1985).

Such stock and option holdings give company managers the right to buy company stock

at a fixed price in the future. When the market value of the company increases, the value

of the stock and option holdings also increases (Eiteman et al., 2007). Company

managers can exercise the stock and option holdings to make more profits. As a result,

the company managers are motivated to improve the company's financial performance

for increase of firm value (Jensen & Meckling, 1976; Smith & Stulz, 1985).

At the same time, incorporating stock and option holdings into managerial

compensation policy may also have the desired effect of motivating company managers

to invest in higher risk investment opportunities than would be possible otherwise

(Rogers, 2002; Smith & Stulz, 1985). The reason is shareholders receive the benefits of

positive stock price developments when the shareholders have a call-option like provision

on the company's assets (Merton, 1974). According to option theory, the shareholders

will be interested in the upside and the volatility, since the volatility increases the value

of the option (Chance & Brooks, 2007). Therefore, when company managers act in the

interest of the shareholders to choose investment opportunities with different levels of

risks, the company managers have incentives to choose investment opportunities with

high risks (Rogers, 2002; Smith & Stulz, 1985).

Although the managerial utility maximization theory provides a useful theoretical

foundation for the study of the role of managerial compensation incentives in corporate

hedging, empirical studies on the relationship between managerial incentives and

corporate hedging have produced conflicting results. Managerial compensation has been

51

applied to explain corporate hedging, and increases in executive stock holdings and

corporate hedging have been reported to be positively and significantly related

(Gonzalez, Bua, Lopez, & Santomil, 2010; Marsden & Prevost, 2005; Purnanandam,

2007; Rogers, 2002; Sprdic, 2007; Supanvanij & Strauss, 2010). Lei (2006) asserted,

"The link between managerial incentives and corporate hedging in strongly governed

companies is insignificant" (p. 21). The sensitivity of the company managers' stock and

option holdings to a stock price of a company is positively related to corporate hedging

activities (Knopf et al., 2002). In agreement, Graham and Rogers (2000) affirmed

managerial stock and option holdings are positively related to corporate hedging

activities. Interestingly, Tufano (1996) and Wang and Fan (2011) found evidence

supporting corporate hedging increases with managerial stock holdings and decreases

with managerial option holdings. However, a significantly positive link between

managerial option holdings and corporate hedging exists in foreign exchange and

currency risk management (Boubaker, Mefteh, & Shaikh, 2010; Hagelin, 2003; Hagelin

et al., 2007; Haushalter, 2000).

Conversely, Adam, Fernando, and Salas (2008) and Kapitsinas (2008) stated no

evidence was found to support company managers' engagement in corporate hedging for

their own benefits. Adam et al. (2008) argued managerial stock and option holdings are

negatively related to corporate hedging in the U.S. gold mining industry. Evidence was

supplied by Dolde and Mishra (2007) and Smith and Stulz (1985) to support managerial

option holdings and corporate hedging are negatively related. Similarly, Jalilvand

(2009), Reynolds and Boyle (2005), and Spano (2008) claimed managerial ownership

does not directly affect the likelihood of corporate hedging. In conclusion, no evidence

52

has indicated shareholders benefit from corporate hedging practices (Brown, Crabb, &

Haushalter, 2006). Further evidence was cited by Kruse (1991) to support the concept

that employees might be willing to accept greater variability in the managerial

compensation in exchange for more stable employment, which indicates job security is an

important factor in managerial utility maximization. Among U.S. defense companies, the

prevalence of managerial incentives incorporating managerial stock and option holdings

exists (The Boeing Company, 2009; Lockheed Martin Corporation, 2009). Therefore, the

managerial incentives and corporate hedging might be related in the U.S. defense

industry (Graham & Rogers, 2000; Marsden & Prevost, 2005; Tufano, 1996).

The important thought of managerial utility maximization theory is managerial

incentives are the key determinant of corporate hedging (Jensen & Meckling, 1976; Stulz,

2003). Due to the divergence of company objectives between shareholders and company

managers in a company (Jensen & Meckling, 1976; Shapiro, 2005), potential conflicts of

interest arise. Such conflicts of interest between company managers and shareholders

can predict managerial behaviors of company managers (Jensen & Meckling, 1976;

Shapiro, 2005). The conflicts of interest between shareholders and company managers

will not lead to maximization of shareholders' value (Jensen & Meckling, 1976). In

addition, company managers may seek to maximize their own self-interest and have

incentives to hedge their private wealth on the expense of the shareholders (Jensen &

Meckling, 1976; Shapiro, 2005; Stulz, 2003). The important method of aligning

company managers and shareholder interests regarding value maximization is with an

appropriately structured managerial compensation package including stock and option

holdings (Jensen & Meckling, 1976; Smith & Stulz, 1985; Tufano, 1996).

53

Although the managerial utility maximization theory provides a theoretical

explanation for the study of the role of managerial compensation incentives in corporate

hedging (Jensen & Meckling, 1976; Shapiro, 2005; Smith & Stulz, 1985; Tufano, 1996),

no clear answers are available in the empirical texts. Even though there is lack of

conclusive evidence, managerial incentives and corporate hedging may be related in the

U.S. defense industry because among U.S. defense companies, the prevalence of

managerial incentives incorporating managerial stock and option holdings is reflected in

a company's annual financial reports (The Boeing Company, 2009; Lockheed Martin

Corporation, 2009).

Shareholder value maximization and managerial utility maximization theories

may be applied to explain corporate hedging decisions within the imperfect capital

markets in which companies operate (Froot et al., 1993; Graham & Smith, 1999; Jensen

& Meckling, 1976; Smith & Stulz, 1985; Shapiro, 2005). At the same time, other lines of

reasoning on corporate hedging behaviors have received considerable attention in the

literature and provoked vigorous debate (Artez & Bartram, 2010; Stulz, 2003). The

question of whether scale economies matter for corporate hedging in risk management is

significant (Allayannis & Ofek, 2001).

Scale Economies

Scale economies represented by firm size are related to the magnitude of financial

losses (Shih, Samad-Khan, & Medapa, 2000). Corporate hedging can be used to reduce

risk of loss against negative outcomes in the imperfect capital markets (Chance &

Brooks, 2007). Empirical studies show scales economies and corporate hedging in risk

management are related (Allayannis & Ofek, 2001; Bartram et al., 2009; Berrospide et

54

al., 2007; Hagelin et al., 2007; Reynolds et al., 2009; Schiozer & Saito, 2009; Spand,

2008; Smith & Stulz, 1985). However, competing arguments for either a positive or

negative relationship between firm size and corporate hedging exist, and will be viewed

in light of each of the following dimensions.

Large companies are more likely to hedge than small companies because the large

companies may have better access to external financing in capital markets (Allayannis &

Ofek, 2001). First, corporate hedging with sophisticated derivative instruments has high

fixed costs such as initial set-up costs, ongoing consulting costs, and costs of monitoring

and operating corporate hedging strategies. Only large companies are able to bear the

high fixed costs (Allayannis & Ofek, 2001). Second, large companies are more

internationally oriented and exposed to the foreign exchange and currency risk than small

companies, and thus have a greater need to hedge (Jong, Ligterink, & Macrae, 2006).

Third, large companies often have expert staff to identify and analyze possible financial

loss exposures (Eugene & Houston, 2009). Therefore, the large companies are at a

distinct advantage in corporate hedging for mitigation of financial risks (Allayannis &

Ofek, 2001; Jong et al., 2006).

Although large companies may be more likely to hedge than small companies,

smaller companies might have a greater likelihood of financial distress and face more

severe financial constraints (Nance et al., 1993; Smith & Stulz, 1985), which in turn may

increase the small companies' likelihood to hedge. According to Nance et al. (1993) and

Smith and Stulz (1985), smaller companies are also subject to costly external financing

because the smaller companies are likely to have a greater informational asymmetry

problem (Nance et al., 1993) and the costs of corporate hedging are proportional to firm

55

size (Smith & Stulz, 1985). These valid arguments support the hypothesis that corporate

hedging should be more prevalent among small companies.

Empirical evidence indicating the effect of firm size on corporate hedging is not

without controversy. In most empirical studies, the positive relationship between firm

size and corporate hedging supports the hypothesis that corporate hedging exhibits

scale economies (Bartram et al., 2009; Berrospide et al., 2007; Carter et al., 2006; Davies

et al., 2006; Guay & Kothari, 2003; Hagelin et al., 2007; Haushalter, 2000; Hsu et al.,

2009; Jong et al., 2006; Judge, 2006; Klimczak, 2008; Lei, 2006; Mseddi & Abid, 2010;

Nguyen et al., 2007; Purnanandam, 2007; Reynolds et al., 2009; Schiozer & Saito, 2009;

Spand, 2008). However, Adam et al. (2008) and Reynolds et al. (2009) concluded

corporate hedging with derivative use is essentially driven by the small companies.

Similarly, Gagnon et al. (2010) indicated small and medium-sized companies are more

likely to hedge than large companies in the Canadian context. However, Dolde and

Mishra (2007) and SprCic (2007) argued no evidence is found to support firm size is a

determinant for corporate hedging. As such, whether there is a relationship between firm

size and corporate hedging for U.S. defense companies is uncertain.

The compelling theoretical explanations of a relationship between firm size and

corporate hedging differ (Allayannis & Ofek, 2001; Nance et al., 1993; Smith & Stulz,

1985). The positive relationship between firm size and corporate hedging indicated large

companies are more likely to hedge because the large companies have better access to

external financing in capital markets (Allayannis & Ofek, 2001). On the other hand,

small companies have a greater incentive to hedge because small companies are also

faced with greater information asymmetries and high costs of corporate hedging (Nance

56

et al., 1993; Smith & Stulz, 1985), which are likely to make external financing more

expensive for smaller companies, and therefore corporate hedging is more likely.

The U.S. defense industry base includes small, medium, and large private

enterprises for U.S. defense related contracts (Watts, 2008). The conflicting theoretical

predictions about the effect of firm size on corporate hedging have not been resolved.

Therefore, firm size effect on corporate hedging for U.S. defense companies is uncertain.

Also noted is the issue that global operations of small and large companies are expanding

(Eiteman et al., 2007; Pope, 2002). Due to an unexpected change in the exchange rate,

the impact of these companies on corporate hedging in risk management has made the

companies' foreign involvement a topic of significant interest. As a result, the level of

foreign involvement and its relationship to corporate hedging in risk management has

become a major issue in foreign exchange and currency risk management (Jorion, 1990).

Level of Foreign Involvement

The U.S. defense companies have recognized substantial foreign exchange and

currency risk as a constant financial risk to business operations because changes in

exchange rates drive changes in cash flows, and ultimately the value of U.S. defense

companies (Allayannis & Ofek, 2001; The Boeing Company, 2009; Jorion, 1990;

Lockheed Martin Corporation, 2009). The exposures to foreign exchange and currency

risk are influenced by a company's foreign involvement such as the level of foreign sales

and the extent of foreign subsidiaries (Jorion, 1990). Companies are more exposed to

foreign exchange and currency risk from foreign sales, foreign income, and foreign

assets. Corporate hedging can lessen the foreign exchange and currency risk (Chance &

Brooks, 2007; Stulz, 2003). Since the magnitude and significance of a company's

57

foreign exchange and currency risk exposures are measured by the level of foreign

involvement, at the corporate level, companies with the greater level of foreign

involvement have greater benefits from corporate hedging (Jorion, 1990). Therefore,

these companies are typically known to hedge a greater proportion of the exposures to the

foreign exchange and currency risk (Allayannis & Ofek, 2001; Jorion, 1990).

By examining the relationship between determinants of corporate hedging and the

use of foreign currency derivatives in a sample of U.S. nonfinancial companies,

Allayannis and Olek (2001) reported the use of corporate hedging instruments reduced

the exposure to the foreign exchange and currency risk, and confirmed foreign sales were

significantly and positively correlated with the corporate hedging decisions. Using

survey data from 441 nonfinancial companies in the United Kingdom, Judge (2006)

found companies with higher foreign sales were more likely to hedge foreign exchange

and currency risk. Menon and Viswanathan (2005) examined how U.S. multinational

corporations used foreign exchange derivatives from 1995 to 2000 and affirmed a

significantly positive relationship between the extent of foreign involvement by U.S.

multinational corporations and corporate hedging activities. By analyzing 81 companies

from nine industry sectors categorized by the Oslo Stock Exchange, Davies et al. (2006)

reported the extent of international operations is a significant determinant of corporate

hedging. The empirical evidence from these studies is consistent with Jorion's (1990)

proposition.

However, the outcome of empirical studies in view of the level of foreign

involvement and corporate hedging is not conclusive. Allayannis and Ofek (2001),

Bartram et al. (2009), Clark and Mefteh (2011), Dolde and Mishra (2007), Davies et al.

58

(2006), Jong et al. (2006), Jorion (1990), Judge (2006), Menon and Viswanathan (2005),

and Pantzalis, Betty, and Laux (2001) found the level of foreign involvement and

corporate hedging are positively related. In contrast, Howton and Perfect (1998)

indicated the relationship between the level of foreign involvement and corporate

hedging with currency derivatives is not supported in a random sample of 461 U.S.

nonfinancial companies. The level of foreign involvement was indicated by Nguyen and

Faff (2006) and Nydahl (1999) as being negatively related to corporate hedging.

Evidence indicating derivative instruments for corporate hedging have a significant and

negative relationship with the existence of foreign assets was provided by Judge (2009).

By analyzing 102 U.S. oil and gas companies, Wang and Fan (2011) concluded the extent

of international operations is negatively related to corporate hedging.

The level of foreign involvement in U.S. defense companies is high. The U.S.

defense industry is responsible for 7% of exports and is the largest net exporting industry

to the U.S. economy in 2010 (Deloitte Development LLC, 2012). According to the

Defense Security Cooperation Agency (DSCA), the U.S. defense companies sold more

than $30 billion in weapons systems and other defense products to the allies of the U.S. in

2010 (Murray, 2010). However, no previous studies have been conducted to assess the

relationship between the level of foreign involvement for U.S. defense companies and

corporate hedging.

The level of foreign involvement, a key measure to the magnitude and

significance of a company's foreign exchange and currency risk exposures, is considered

in corporate hedging decisions (Allayannis & Ofek, 2001; Jorion, 1990). At the

corporate level, companies with a greater level of foreign involvement have greater

59

benefits from corporate hedging (Jorion, 1990) and typically hedge a greater proportion

of the exposures to foreign exchange and currency risk (Allayannis & Ofek, 2001).

However, the outcome of empirical studies addressing the level of foreign involvement

and corporate hedging is not clear. Although the level of foreign involvement in the U.S.

defense companies is high, the question of whether a relationship exists between the level

of foreign involvement for U.S. defense companies and corporate hedging remains

unanswered.

The six key determinants of corporate hedging discussed previously may

influence corporate hedging decisions in risk management within the imperfect capital

markets (Allayannis & Ofek, 2001; Froot et al., 1993; Graham & Smith, 1999; Jensen &

Meckling, 1976; Jorion, 1990; Nance et al., 1993; Smith & Stulz, 1985; Shapiro, 2005;

Stulz, 2003). Other theoretical extensions justifying corporate hedging with derivatives

at the organizational level have been developed in recent studies. Additional corporate

hedging factors in risk management include firm value (Allayannis & Ofek, 2001),

foreign debt (Kelohaiju & Niskanen, 2001), asymmetric information (Breeden &

Viswanathan, 1996; DeMarzo & Duffie, 1991; Raposo, 1997; Tufano, 1996), board

characteristics (Whidbee & Wohar, 1999), industry-specific characteristics (Jorion,

1991), country-specific characteristics (Gebhardt, 1999), and accounting reporting

methods (Melumad, Weyns, & Ziv, 1999; Sapra, 2002). The key empirical studies of the

exploration of each of the additional factors are cited and discussed below. A review of

critical findings from these empirical studies is emphasized.

Other Factors

Firm value. Company managers should make all decisions so as "to increase the

60

total long run market value of the company. Total value of the sum of the value of all

financial claims on the company including equity, debt, preferred stock, and warrants"

(Jensen, 2001, p. 298). In an imperfect capital market, corporate hedging is a means to

increase firm value to the benefit of shareholders (Jensen, 2001; Jensen & Meckling,

1976; Shapiro, 2005). Therefore, maximization of firm value is a primary motive for

corporate hedging in risk management (Allayannis & Ofek, 2001).

The findings of empirical evidence indicating the relationship between firm value

and corporate hedging are debatable. Bartram et al. (2009), Berrospide et al. (2007), and

Kapitsinas (2008) supported the impact of corporate hedging on firm value is significant.

Evidence supporting both corporate hedging and firm value are positively related in the

U.S. airline industry was provided by Carter et al. (2006). A large cross section of 442

nonfinancial companies was examined by Graham and Rogers (2002), and they

concluded corporate hedging with currency derivatives increases firm value by 1.1%.

Firm value increases when transaction risk is hedged with currency derivatives, according

to Hagelin (2003).

In contrast, Guay and Kothari (2003) demonstrated corporate hedging has a

positively insignificant affect on firm value. It was concluded by Nguyen and Faff

(2006) that firm value was not related to corporate hedging in 428 Austrian nonfinancial

companies. Corporate hedging decisions were determined to have no impact on company

valuations in 250 French nonfinancial companies (Khediri, 2010). Jin and Jorion (2006)

indicated corporate hedging did not affect companies' market values in the U.S. oil and

gas industry. Lastly, Spr5ic (2007) suggested the primary reasons for corporate hedging,

61

such as the reduction of taxes and costs of financial distress, were not supported in

foreign exchange and currency risk management practices.

As Allayannis and Ofek (2001) indicated, corporate hedging may be positively

related to an increase in firm value for U.S. defense companies. However, the mix of

empirical results from previous studies does not indicate whether the existing corporate

hedging theories apply to U.S. defense companies. Furthermore, an estimate of firm

value is provided by the market capitalization of the company's equity and debt (Koller,

Goedhart, & Wessels, 2005). The market value of assets and debts is difficult to

estimate, which may lead to inaccurate findings. Therefore, firm value, as a determinant

of corporate hedging, was not included in the study.

Foreign debt. Financial derivatives are not the only corporate hedging

instruments. Foreign debt can act as an important alternative of corporate hedging

instruments for companies whose cash flow is more sensitive to exchange rate

fluctuations (Aabo, 2006; Allayannis, Brown, & Klapper, 2003; Judge, 2009; Kelohaiju

& Niskanen, 2001). If companies have liabilities in the same currency as the assets, the

amount of foreign currency translation is reduced, and the overall effect of exchange rate

volatility on cash flow and earnings is reduced (Allayannis et al., 2003). Therefore,

companies with more foreign debts may relate to higher corporate hedging activities in

reduction of exposures to foreign exchange and currency risk (Aabo, 2006; Allayannis et

al., 2003; Gonzalez et al., 2010; Judge, 2009; Kelohaiju & Niskanen, 2001).

The companies that select foreign debt as a corporate hedging instrument could be

exporters (Judge, 2009), companies with foreign subsidiaries, or companies that hold

foreign currency debt (Kelohaiju & Niskanen, 2001). The main reasons for companies to

62

select foreign debt as a corporate hedging instrument are when foreign debt is cheaper

than domestic debt (Allayannis et al., 2003; Berrospide et al., 2007; Gonzalez et al.,

2010; Kelohaiju & Niskanen, 2001), companies with liabilities destined to repaying the

principal and interest of the foreign debt would be compensated by income in the foreign

currency generated by foreign operations (Gonzalez et al., 2010; Judge, 2009), and

companies with revenue in foreign currency might issue debt denominated in foreign

currency to avoid mismatches in the balance sheets (Judge, 2009; Kelohaiju & Niskanen,

2001).

Berrospide et al. (2007) indicated companies using corporate hedging in foreign

exchange and currency risk management have significantly higher proportions of foreign

debt. Aabo (2006) analyzed the determinants of foreign debt compared to derivative

instruments for corporate hedging in foreign exchange and currency risk. Aabo showed

the importance of foreign debt in corporate hedging is positively related to the exposures

to foreign exchange and currency risk. Allayannis and Ofek (2001) asserted American

exporters with higher foreign exchange and currency risk exposure are more likely to use

foreign debt in corporate hedging. Using a sample of nonfinancial companies traded on

the U.S. exchanges in the four most developed Latin American countries, Schiozer and

Saito (2009) reported the size of currency derivative portfolios held by a company is

positively influenced by foreign debt.

Judge (2009) illustrated the likelihood of using derivative instruments and the

existence of foreign debts is significantly and positively related. Judge further suggested

foreign debt is a complementary rather than a competing strategy to hedge the exposures

to foreign exchange and currency risk. Gathering a sample of Finnish nonfinancial

63

companies, Kelohaiju and Niskanen (2001) found companies raise foreign debt in order

to hedge the exposure to foreign exchange and currency risk. Kelohaiju and Niskanen

detected larger companies have better access to international financial markets, and thus,

companies typically use foreign debt for corporate hedging. Using a data set of East

Asian nonfinancial companies, Allayannis et al. (2003) indicated direct costs of debt

issuance are an important factor of corporate hedging using foreign debt. Gonzalez et al.

(2010) suggested company managers are more inclined to hedge using foreign debt

because of managerial risk aversion. Clark and Judge (2009) analyzed the joint use of

derivative instruments and foreign debt to test the hypothesis that corporate hedging

reduces the costs of financial distress. However, empirical results on the relationship

between foreign debt and corporate hedging are not stable. Nguyen and Faff (2006)

detected no relationship between the use of foreign debt and the exposures to foreign

exchange and currency risk. Evidence was supplied by Schiozer and Saito (2009) to

support the use of currency derivative are not influenced by the level of foreign debt.

With globalization, the trend of U.S. defense companies is to extend the

international operations that enhance economic competitiveness (Arnold et al., 2009). As

such, U.S. defense companies are increasingly exposed to the foreign exchange and

currency risk. However, whether foreign debt is used to hedge the foreign exchange and

currency risk exposure in the U.S. defense industry is unknown. Because direct data

indicating whether foreign debt is used in corporate hedging for U.S. defense companies

is not available, foreign debt, as a determinant of corporate hedging, was excluded in the

study.

64

Asymmetric information. Asymmetric information signifies a situation in which

one party involved in a transaction with another has more or superior knowledge and

information than the other (DaDalt et al., 2002; Hillairet, & Jiao, 2010). In an imperfect

capital market, prohibitive dissemination, expense, and competitive safeguarding of

proprietary information prevent companies from delivering sufficient data to shareholders

to manage their portions of the exposures to foreign exchange and currency risk

(DeMarzo & Duffie, 1991; Dolde & Mishra, 2007). As such, company managers would

have superior information regarding the foreign exchange and currency risk that could be

hedged. If a company's volatile earnings are provided, shareholders cannot tell whether the

fluctuations of earnings are due to the foreign exchange and currency risk that could be

hedged or whether the variability is caused by managerial incompetence (DaDalt et al.,

2002). Under these circumstances, company managers could decide to hedge. Evidence

indicating asymmetric information is an important determinant for corporate hedging in

foreign exchange and currency risk management was provided by Dolde and Mishra

(2007).

A different explanation of corporate hedging behaviors, based on asymmetric

information, was presented by Breeden and Viswanathan (1996) and DeMarzo and

Duffie (1995) who focused on managers' reputations. Breeden and Viswanathan and

DeMarzo and Duffie argued company managers may prefer to engage in risk

management activities to communicate their skills to the labor market. Both teams of

researchers found younger executives and company managers with shorter tenures have

less developed reputations than older or longer-tenured company managers (Breeden &

Viswanathan, 1996; DeMarzo & Duffie, 1991). Therefore, young executives and

65

company managers with shorter tenures are more willing to embrace risk management.

Although an executive's age and the extent of risk management activity are not related,

Tufano (1996) argued companies whose executives have fewer years in the current job

are more likely to engage in higher risk management activities. Tufano confirmed young

executives are more willing to engage in risk management activities than are their older

colleagues. Therefore, the results are consistent with Breeden and Viswanathan's (1996)

and DeMarzo and Duffie's (1995) theory.

Raposo (1997) addressed the interaction between the disclosure of corporate

hedging positions and company manager's hedging strategies. Assuming the risk

exposure of the company is not known, the disclosure of corporate hedging positions is

not desirable (Raposo, 1997). Disclosing the value of derivative instruments for corporate

hedging can destroy company manager's incentive to hedge because corporate hedging

can reveal more information about the company manager's ability, and thereby make the

future compensation more risky (Raposo, 1997). However, if profits from corporate

hedging are aggregated with other revenues, company managers will be encouraged to

hedge to reduce the volatility of earnings, and thus reduce the employment risk (Raposo,

1997).

The empirical evidence needed to support the relationship between asymmetric

information and corporate hedging is limited. Human resource information of U.S.

defense companies is not publicly available. As a result, asymmetric information as a

determinant of corporate hedging was not included in the study.

Board characteristics. Another potential determinant of corporate hedging,

based on the conflicts of interest argument in an agency relationship, is the board

66

characteristics (Borokhovich et al., 2004; Marsden & Prevost, 2005; Whidbee & Wohar,

1999). Corporate statutes describing the affairs of the company are managed by or under

the direction of a board of directors (Fama & Jensen, 1983). Shareholders contribute

capital and retain ownership interests. Company managers make decisions regarding

corporate operations, including strategic planning, risk management, and financial

reporting. The board is composed largely of independent directors, who oversee

company managers' performance on the behalf of the shareholders. The board monitors

such performance and intervenes to remedy deficient management operations (Fama &

Jensen, 1983). Through the risk oversight role, independent directors evaluate the risk

management policies and procedures designed and implemented by corporate executives

and ensure company managers' actions are consistent with the corporate strategy and risk

plan (Fama & Jensen, 1983). Therefore, the board characteristics such as board

independence, board size, board composition, and directors' characteristics may influence

corporate hedging practices at the organizational level in risk management (Borokhovich

et al., 2004; Marsden & Prevost, 2005; Whidbee & Wohar, 1999).

Empirical studies supported the relationship between board characteristics and

corporate hedging (Borokhovich et al., 2004; Marsden & Prevost, 2005; Triki, 2005;

Whidbee & Wohar, 1999). Whidbee and Wohar (1999) explored the relationship

between use of derivative instruments and the board independence, which is measured by

the proportion of outside directors within the board. Whidbee and Wohar (1999)

suggested corporate hedging activities are influenced by outside directors' presence at

low levels of insiders' share holdings only. Company managers who own a small

fraction of the company's share holdings are more likely to be disciplined if the company

67

managers' performance is poor (Whidbee & Wohar, 1999). To minimize the financial

risk of the private wealth, the company managers will be encouraged to hedge more.

Borokhovich et al. (2004) found corporate hedging activities cannot be explained

by the board size and the presence of corporate executives on the board. Dionne and

Triki (2005) suggested the financial education of the board and the audit committee

impact corporate hedging practices. An examination of the relationship between board

composition and use of derivative instruments was conducted by Marsden and Prevost

(2005), and they concluded the board composition does not systematically affect the

decisions to use derivative instruments.

While recent studies indicating board characteristics influence corporate hedging

have been documented, the results of empirical testing are not conclusively supported.

Research on the board characteristics, as a determinant of corporate hedging, is still

developing. Since board of directors' data in the U.S. defense industry is limited, the

board characteristics were not examined for the study.

Industry-specific characteristics. Foreign exchange and currency risk

exposures are largely determined at the industry level (Marston, 2001). Recent empirical

studies supported a hypothesized relationship between corporate hedging and industry-

specific characteristics, which are not directly related to the corporate hedging theories.

To understand if the industry-specific characteristics are related to corporate hedging in

foreign exchange and currency risk management is important for the following reasons.

First, to meet competitive challenges from international trading partners, the

optimization of target specific industries is needed (Westphal, 1990). The importance of

foreign exchange and currency risk management and its impact on the industries has been

68

a topic of significant interest in the optimization (Eiteman et al., 2007; Homaifar, 2004).

If foreign exchange and currency risk exposures differ systematically between industries,

industry-level corporate hedging in foreign exchange and currency risk management

would be more relevant to company managers in these industries. Second, according to

the corporate hedging hypothesis, effective corporate hedging eliminates foreign

exchange and currency risk premium in industry returns (Jorion, 1991). If foreign

exchange and currency risk is priced at the stock market level, and currency and stock

markets are imperfectly integrated, corporate hedging can reduce industry cost of capital

by eliminating the foreign exchange and currency risk premium (Jorion, 1991). Third,

foreign exchange and currency risk is economically more important for U.S. industries

(Bartram et al., 2009; Francis, Hason, & Hunter, 2008). Corporate hedging in industry-

level foreign exchange and currency risk management adds to the discussion U.S.

investors can obtain benefits of international diversification for their investment

portfolios (Errunza et al., 1999). Therefore, industry-specific characteristics may

influence corporate hedging decisions at the organizational level (Jorion, 1991).

Empirical results representing industry-specific characteristics and corporate

hedging are not consistent. Adam et al. (2007) stated, "Industry characteristics, such as

on the number of firms in the industry, the elasticity of demand, the convexity of

production costs, and the relative market shares of each firm" (p. 2445) are associated

with corporate hedging. To protect against the rises in oil price, the U.S. airline industry

hedges jet fuel costs (Carter et al., 2006) because corporate hedging is an important part

of business for the successful airlines because fuel is an airline's second highest cost

69

(after labor). Jin and Jorion (2006) reported companies with higher production costs are

less likely to hedge in the U.S. oil and natural gas industry.

Reynolds et al. (2009) argued derivative instruments are significant across

industry sectors in New Zealand. Brailsford, Heaney, and Oliver (2005) stated, "It is not

expected that value maximizing incentives generally applicable to the private sector will

also be critical in explaining derivative use in the public sector" (p.63). However, Adam

et al. (2008) studied 92 U.S. gold mining companies, a homogeneous industry group, and

found payoffs of corporate hedging activities are not economically significant.

Comparing a sample of Australian industrial companies and Australian mining

companies, Berkman et al. (2002) concluded financial advantage and derivative uses are

more significant and positively related in industrial companies than in mining companies.

Evidence was supplied by Hsu et al. (2009) to support the electronics, electric machinery,

and machinery industries are more influential on corporate hedging than other industries.

However, from a sample of 150 Polish companies listed on the Warsaw Stock Exchange,

no evidence was found to support the differences in corporate hedging between industries

(Klimczak, 2008).

Companies in regulated industries provide company managers with few

opportunities for discretion in corporate investment and financing decisions (Smith &

Watts, 1992). Therefore, if regulated companies face tighter scrutiny and lower

contracting costs, company representatives are less likely to use derivative instruments to

hedge (Mian, 1996; Rogers, 2002). Furthermore, companies in regulated industries do

not have the same growth opportunities as companies in unregulated industries (Smith &

Watts, 1992). As such, operated in more stable environments, companies in regulated

70

industries have a lower demand for corporate hedging than companies in unregulated

industries (Fabling & Grimes, 2008). By analyzing a sample of nonfinancial companies

traded on the U.S. exchanges in the four most developed Latin American countries,

Schiozer and Saito (2009) confirmed company managers in regulated industries are less

likely to use currency derivatives for corporate hedging.

The U.S. defense industry is regulated by the Federal Government of the U.S.

Demand in the U.S. defense industry is driven by the U.S. Government (Deloitte

Development LLC, 2012). One of the key U.S. defense industry-specific characteristics

is to conduct business with the U.S. Government (Watts, 2008). After what kinds of

systems and weapon that will be built are decided, a defense company, based on price

and performance, will be chosen. The U.S. defense companies typically bid for U.S.

government contracts by submitting proposals for development of specific systems and

weapons programs funded by the Department of Defense (DoD) (Arnold et al., 2009;

Tortoriello, 2011). The U.S. government contracts have unique risks to U.S. defense

companies because the U.S. defense companies are subject to regulations, audits,

inquiries, and investigations by U.S. government agencies (The Boeing Company, 2009;

Eiteman et al., 2007; Lockheed Martin Corporation, 2009) and due to U.S. government

budget cuts, funding the development of specific systems and weapons programs in the

U.S. defense industry would be impacted (Arnold et al., 2009; Deloitte Development

LLC, 2012; Tortoriello, 2011; Watts, 2008). Therefore, given the heightened risks to

U.S. defense companies because of U.S. government policies, regulations, and budget

cuts, the U.S. defense companies may be pressured to restrict corporate hedging to shift

financial risks and contend for U.S. government contracts (Mian, 1996; Rogers, 2002).

71

Revenues derived from U.S. government contracts, as an industry-specific attribute of

U.S. defense companies, were presented in the study.

Country-specific characteristics. Financial markets differ in different countries

(Eiteman et al., 2007). Although corporate hedging in emerging financial markets is the

same conceptually as in developed financial markets, the corporate hedging decisions are

more complex in practice (Whaley, 2006). Financial expertise in corporate hedging

within different countries also develops over time (Bartram et al., 2009; Eiteman et al.,

2007). Investors are asked to decide on factors normally taken for granted in the

developed financial markets, such as location of counterparty, application of hedge, and

convertibility restrictions (Whaley, 2006). Furthermore, institutional and legal

environment are diverse across countries (Allayannis, Lei, & Miller, 2012; Bartram et al.,

2009; Bodnar, De Jong & Macrae, 2003; Lei, 2006; Marsden & Prevost, 2005).

Corporate reporting standards are country-specific and legal requirements on reporting

are not the same in every country (Naylor & Greenwood, 2008). Therefore, corporate

hedging practices vary in different countries, and country-specific characteristics may

play an important role in corporate hedging decisions at the organizational level

(Allayannis et al., 2012; Bartram et al., 2009; Bodnar, De Jong & Macrae, 2003; Lei,

2006; Marsden & Prevost, 2005).

Lei (2006) and Marsden and Prevost (2005) considered financial market

developments, legal environment, and macroeconomic characteristics of the country as

possible reasons for differences in corporate hedging practices. Lei (2006) argued

companies in emerging economies expose higher macroeconomic risks, and thus are

more likely to use derivative instruments in corporate hedging. Evidence provided by

72

Allayannis et al. (2012) indicated companies within an English legal origin engage in

significantly more corporate hedging activities than companies within a non-English legal

origin. Financial distress cost factors are more important for U.K. companies than U.S.

companies due to differences in the bankruptcy codes in the two countries, which result

in higher expected costs of financial distress for the U.K. companies (Judge, 2006).

By analyzing a sample of 7,319 nonfinancial companies from 50 countries,

Bartram et al. (2009) suggested companies using derivative instruments are more often

located in countries with larger derivatives markets and higher gross domestic product

(GDP) per capita and are Organization for Economic Co-operation and Development

(OECD) members. Bodnar et al. (2003) indicated Dutch companies might be more

exposed to foreign currency risk than U.S. counterparts because of differences in

economy orientation and the presence of legal structure. After applying a matched-

industry procedure, Gebhardt (1999) concluded German companies hedge more with

derivative instruments than U.S companies. Surveying a sample of companies in Sweden

and Korea, Pramborg (2004) compared the use of hedging instruments to manage foreign

exchange and currency risk and found similarities between companies in the both

countries. However, with notable exception, the aim of hedging activity differed between

companies in the countries. Swedish companies favored minimizing fluctuations of

earnings or protecting the appearance of the balance sheet, while Korean companies were

focused more on minimizing the fluctuations of cash-flows (Pramborg, 2004). The

proportion of companies that use derivative instruments is significantly lower in the

Korean sample than in the Swedish sample, which suggested the Korean derivative

markets are not easily accessible because of strict government regulations and is also less

73

sophisticated than the Swedish market (Pramborg, 2004). Naylor and Greenwood's

(2008) results showed the usage of derivative instruments in New Zealand, Swedish, and

Asian companies was higher than in the U.S., Dutch, and German companies of

comparable size. Corporate hedging generally aims to accounting objectives such as

ensuring a company's budget outcomes are met.

The comparative studies examining the relationship between country-specific

characteristics and corporate hedging are not widely available. The results of the prior

studies were varied. Furthermore, the participants of the study are U.S. defense

companies only, therefore, the country-specific characteristics, as a determinant of

corporate hedging, were excluded in the study.

Accounting reporting methods. Explanations of corporate hedging, based upon

accounting reporting methods in derivative instruments, are provided since the FASB

issued FAS 133 on accounting for derivative financial instruments and hedging activities.

According to U.S. FAS 133 and internationally as IAS 39 standards, companies are

required to report fair value and related carrying value of derivative instruments in annual

financial reports and specify if the derivative instruments are used for trading or other

purposes (Apostolou & Apostolou, 2008; Chance & Brooks, 2007; Power, 2010;

Ramirez, 2007). The fair value is defined as the exchange price that "would be received

to sell an asset or paid to transfer a liability in an orderly transaction between market

participants at the date of measurement" (Power, 2010, p. 199). The FAS 133 standard is

a significant departure from earlier standards and accounting traditions. Financial

instruments, except in a few defined exceptions, are accounted for at the historical

(amortized) cost. Therefore, a distinction between derivative instruments (at fair value)

74

versus financial instruments (amortized cost) exists when derivative instruments are

reported in the company's annual financial reports (Apostolou & Apostolou, 2008;

Chance & Brooks, 2007; Power, 2010; Ramirez, 2007).

The FAS 133 standard has been intensely debated both theoretically and

empirically. At a theoretically level, the controversy about the FAS 133 standard centers

on how disclosing information about derivatives and hedging activities affects a

company's risk-management practices (Apostolou & Apostolou, 2008; Chance &

Brooks, 2007; Power, 2010; Ramirez, 2007). At an empirical level, researchers

supported disclosures of derivatives and hedging activities focus on earnings volatility

rather than the companies' real actions in risk management practices (Apostolou &

Apostolou, 2008; Power, 2010; Ramirez, 2007). Proponents of the FAS 133 standard

argue income fluctuations using derivative instruments in corporate hedging are created

because gains or losses in the values of derivative instruments are not appropriately

disclosed or recognized under historical cost accounting (Apostolou & Apostolou, 2008;

Chance & Brooks, 2007; Power, 2010). Since corporate hedging is designed to reduce

financial risk, increase in a level of income volatility would lead to the exact opposite

impression (Chance & Brooks, 2007). Fair value recognition defined in the FAS 133

makes the use of derivative instruments more transparent. Therefore, a company's

prudent risk management is encouraged (Apostolou & Apostolou, 2008; Power, 2010).

Opponents of the FAS 133 standard insist companies use derivative instruments to hedge

the inherent business risk, and fair value accounting induces higher short-term volatility

in the financial statements. As such, the legitimate use of derivative instruments for

75

hedging purposes is deterred (Sapra, 2002). Therefore, the accounting reporting methods

may affect corporate hedging activities in risk management (Brown, 2001).

Empirical evidence indicating the relationship between accounting reporting

methods and corporate hedging is various. Glaum and Klocker (2011) studied 114

nonfinancial companies in German and Switzerland and found companies applying the

hedge accounting rules have more frequently used derivative instruments for hedging.

They concluded the application of hedge accounting rules influence corporate hedging

behaviors (Glaum & Klocker, 2011). Lins, Servaes, and Tamayo (2010) indicated the

risk management activities of more than 42% of the 229 sample companies are affected

by the FAS 133 standard. Since the fair value of derivative instruments reveals

quantitative information about the level of corporate risk management and a company's

underlying risk exposure, Nguyen et al. (2007) suggested using fair value of derivative

instruments makes tests of hypotheses on the determinants of the volume of corporate

hedging in the foreign exchange and currency risk management markets possible.

Melumad et al. (1999) illustrated derivative accounting with fair value measurement

reveals a company's underlying risk exposure, and thereby keeps to have the best

derivative instruments selected, as in a setting with no asymmetric information. Lins et

al. (2010) found the accounting reporting methods of derivative instruments are more

likely to affect companies that take active derivative positions, companies that write

earnings based contracts, and companies that consider reducing earnings volatility to be

important. Supanvanij and Strauss (2010) concluded derivative reporting transparency is

a significant factor in determining the use of corporate hedging.

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Sapra (2002) investigated the opposing effects of fair value accounting from the

capital market valuation perspective and showed an extreme position in the derivative

market signals favorable private information about the future spot price which, in turn,

leads to a higher capital market price. Sapra suggested increased reporting transparency

resulting from the FAS 133 standard may induce a company to take an excessive

speculative position. From a sample of Fortune 500 derivative users, Singh (2004)

indicated no significant change in earnings volatility, cash flow volatility, or the notional

amount of the derivatives after the adoption of the FAS 133 standard. Singh concluded

the impact of the FAS 133 standard might not be as significant as claimed. Using a

sample of U.S. companies whose annual revenues were between $1 and $5 billion in

2001, survey results showed only 25% of the respondents believed the FAS 133 standard

imposes a beneficial discipline on a company's risk management activities (Association

of Financial Professional, 2002).

Overall, the empirical evidence indicating the impact of accounting reporting

methods on corporate hedging in risk management is not certain. No studies assessing

the relationship between accounting reporting methods and corporate hedging have been

performed using data from U.S. defense companies. However, due to unavailability of

direct data in accounting reporting methods from U.S. defense companies, accounting

reporting methods, as a determinant of corporate hedging, were not chosen for

examination in the study.

The comprehensive review shows the key determinants from corporate hedging

theories may lead to corporate hedging decisions at the organizational level (Froot et al.,

1993; Graham & Smith, 1999; Jensen & Meckling, 1976; Smith & Stulz, 1985; Shapiro,

77

2005). However, other rationales of corporate hedging with derivatives are equally

important to explain corporate hedging behaviors for nonfinancial companies (Adam et

al., 2007; Judge, 2006). Numerous researchers have pointed out real blind spots

corporate hedging theories cannot explain (Allayannis & Ofek, 2001; Borokhovich et al.,

2004; Breeden & Viswanathan, 1996; DeMarzo & Duffie, 1991; Gebhardt, 1999; Jorion,

1990; Kelohaxju & Niskanen, 2001; Lins et al., 2010; Melumad et al., 1999; Raposo,

1997; Rogers, 2002; Sapra, 2002; Tufano, 1996; Whidbee & Wohar, 1999). For

example, Borokhovich et al. (2004), Marsden and Prevost (2005), and Whidbee and

Wohar (1999) indicated the board characteristics such as board independence, board size,

board composition, and directors' characteristics may influence corporate hedging

decisions in risk management. Rogers (2002) suggested companies in regulated

industries use corporate hedging less than companies in unregulated industries. Since

regulated companies face tighter scrutiny and have lower contracting costs, company

managers are less likely to hedge in risk management. Lins et al.'s (2010) empirical

evidence indicated the accounting reporting methods of derivative instruments are more

likely to affect companies that take active derivative positions.

However, the empirical evidence on these additional corporate hedging factors

using organizational data still reigns challenged, and much remains debatable about the

impact of these additional determinants on corporate hedging in risk management (Artez

& Bartram, 2010; Nguyen & Faff, 2010; Stulz, 2003). "The effect of some variables on

risk management is more complex than typically considered, and a detailed

understanding of the underlying structural parameters is required to capture these effects

properly in empirical analyses" (Artez & Bartram, 2010, p. 366). Therefore, further

78

research on these additional determinants of corporate hedging in risk management will

be needed.

As a highly regulated industry in the U.S., one of the U.S. defense industry-

specific characteristics is to conduct business with U.S. Government through bidding

contracts (Watts, 2008). Given the heightened risks to U.S. defense companies because

of U.S. government policies, regulations, and budget cuts, the U.S. defense companies

might restrict corporate hedging practices. Therefore, revenues from U.S. government

contracts, as an industry-specific attribute of U.S. defense companies, were included for

examination in the study. Other additional corporate hedging factors discussed in this

section were not selected for the study due to unavailability of direct data.

Corporate Hedging in Foreign Exchange and Currency Risk Management

Within the framework of corporate hedging in risk management, foreign

exchange rate movement is one major source of risk for companies (The Boeing

Company, 2009; Eiteman et al., 2007; Homaifar, 2004; Lockheed Martin Corporation,

2009). In effect, foreign exchange and currency risk management has become an

essential part of the companies' corporate hedging decisions against foreign exchange

rate risk (Papaioannou, 2006). To hedge exposures to foreign exchange and currency

risk, knowing the types of foreign exchange and currency risk companies expose to and

deciding whether to hedge these risks are fundamental to company managers (Eiteman et

al., 2007; Stulz, 2003).

Companies operating in the global marketplace have significant exposure to

changes in foreign exchange and currency risk in the various countries where the

companies conduct business (Eiteman et al., 2007; Homaifar, 2004). Foreign exchange

and currency risk is the effect that unanticipated foreign exchange rate changes have on

the value of the company (Eiteman et al., 2007; Fabling & Grimes, 2008). The exposure

to foreign exchange and currency risk may limit the company's production and capital

investment such as R&D investment projects (Eiteman et al., 2007). Therefore, to

manage foreign exchange and currency risk, understanding the types of foreign exchange

and currency risk companies are exposed to is important.

Generally, companies are exposed to three types of foreign exchange and

currency risk: (a) translation risk, (b) transaction risk, and (c) economic risk (Eiteman et

al., 2007; Homaifar, 2004; Papaioannou, 2006). Translation risk is the potential for

change from translation of account balances recorded in foreign currencies to an entity's

reporting currency due to fluctuations in foreign exchange rates (Eiteman et al., 2007;

Papaioannou, 2006). Company managers should not manage the translation risk

exposure for the following reasons: the translation risk focuses on accounting flows

rather than cash flows, is important from the narrow standpoint of reported earnings and

balance sheet values, and does not have any meaningful impact on future cash flows

(Hagelin, 2003). Moreover, if exchange rates do not move in the anticipated direction,

hedging translation risk may cause either cash flow or earnings volatility (Papaioannou,

2006). Research has shown evidence that does not indicate support of the value of

reporting translation adjustment in financial statements. Hagelin (2003) indicated the

reported earnings could be poor estimators of real changes in the market value of a

company, which suggests hedging translation risk is also inefficient in reducing the stock

price volatility. Dhaliwal, Subramanyam, and Trezevant (1999) argued the translation

adjustments do not provide meaningful information. According to Louis (2003), the

80

translation adjustment provides misleading information about companies with foreign

manufacturing operations.

Transaction risk is the most identifiable form of foreign exchange and currency

risk exposure (Eiteman et al., 2007). Because of fluctuations in foreign exchange rates,

transaction risk rises when a company involved in international trade executes a sale or

purchases at one point in time, but the transfer of funds takes place at a different point in

time, which results in an uncertainty about the amount of revenue or expenditure

involved in the transaction in the company's home currency (Eiteman et al., 2007;

Papaioannou, 2006). Transaction risk that concentrates on contractual commitments,

which involve the actual conversion of currencies, can be hedged using derivative

instruments. The transaction risk is usually short term in nature. Most MNCs estimate

the transaction risk and take steps to hedge and control the risk (Eiteman et al., 2007;

Hagelin, 2003; Papaioannou, 2006).

Economic risk is the potential for foreign exchange rate fluctuations to affect a

company's long-term competitive position, such as future cash flows and discount rates,

in domestic and international product markets (Eiteman et al., 2007; Papaioannou, 2006).

If a company has competitors from other countries with a cost base in a foreign currency

because of foreign productions, foreign exchange and currency changes can potentially

influence future cash flows. Unlike the former two risks, economic risk can be managed

through long-term strategic decisions (Papaioannou, 2006; Whaley, 2006). For the study,

the determinants that represent the rationales for corporate hedging in foreign exchange

and currency risk management can be expected to be related to the usage of derivative

81

instruments aimed to hedge transaction risk and economic risk, rather than translation

risk.

To mitigate the impact of foreign exchange and currency risk exposure, corporate

hedging, as a means of reducing financial risk, becomes one of the key components of the

overall corporate financial risk management perspective (Chance & Brooks, 2007;

Papaioannou, 2006). Corporate hedging in foreign exchange and currency risk

management refers to the ability to manage the financial risk exposure to an extent that

makes the financial risk bearable (Chance & Brooks, 2007; Whaley, 2006). The

objective of corporate hedge in foreign exchange and currency risk management should

be to help companies achieve the optimal risk profile that balances the benefits of

protection against the costs of corporate hedging (Chance & Brooks, 2007; Nguyen &

Faff, 2010; Papaioannou, 2006). The derivative instruments used by company managers

to hedge the foreign exchange and currency risk exposure include forward contracts,

future contracts, option, and swap (Hancock-Weise, 2011; Hull, 2006; Whaley, 2006).

Empirical studies showed foreign debt can be used as an alternative of derivative

instruments to hedge the foreign exchange and currency risk exposure (Aabo, 2006;

Allayannis et al., 2003; Clark & Judge, 2009; Judge, 2009; Kelohaiju & Niskanen, 2001;

Lei, 2006; Luiz & Junior, 2011; Schiozer & Saito, 2009).

Theoretically, companies benefit from corporate hedging in foreign exchange and

currency risk management because of shareholder value maximization and managerial

utility maximization (Froot et al., 1993; Graham & Smith, 1999; Jensen & Meckling,

1976; Morellec & Smith, 2007; Smith & Stulz, 1985; Shapiro, 2005). Corporate hedging

theories have been empirically tested to examine if nonfinancial companies benefited

82

from corporate hedging in foreign exchange and currency risk management (Allayannis

& Weston, 2001; Bartram et al., 2009; Berkman et al., 2002; Brown, 2001; Carter et al.,

2006; Davies et al., 2006; Dolde & Mishra, 2007; Fabling & Grimes, 2008; Graham &

Rogers, 2002; Hagelin, 2003; Judge, 2006; Kapitsinas, 2008; Lei, 2006; Luiz & Junior,

2011; Marsden & Prevost, 2005; Menon & Viswanathan, 2005; Nguyen & Faff, 2003;

Reynolds & Boyle, 2005; Schiozer & Saito, 2009; Spano, 2008). Some of the empirical

researchers used survey data while others relied on the availability of quantitative data in

commercial databases or annual financial reports made possible by the FAS 133 or IAS

39 standards (Bartram et al., 2009; Hagelin, 2003; Judge, 2006; Kapitsinas, 2008; Luiz &

Junior, 2011; Nguyen & Faff, 2003; Reynolds & Boyle, 2005; Schiozer & Saito, 2009;

Spano, 2008). In these empirical studies, researchers tried to determine why nonfinancial

companies use derivative instruments or foreign debt to hedge the foreign exchange and

currency risk exposure (Bartram et al., 2009; Hagelin, 2003; Judge, 2006; Kapitsinas,

2008; Luiz & Junior, 2011; Nguyen & Faff, 2003; Reynolds & Boyle, 2005; Schiozer &

Saito, 2009; Spano, 2008). However, the existing empirical validation of the corporate

hedging theories has been confronted with the sample specific interpretations of

empirical results and the unavailability of reliable data on corporate hedging activities

(Artez & Bartram, 2010; Nguyen & Faff, 2010; Stulz, 2003).

For a successful validation of corporate hedging theories, provision of a valid

measure for corporate hedging in foreign exchange and currency risk management is a

basic requirement and depends on the data availability of corporate hedging activities

(Artez & Bartram, 2010; Judge, 2006). In the prior empirical studies, the most common

measure for corporate hedging in foreign exchange and currency risk management was to

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use a dummy variable indicating if the company uses derivative instruments for corporate

hedging (Allayannis & Weston, 2001; Bartram et al., 2009; Carter et al., 2006; Davies et

al., 2006; Hagelin, 2003; Judge, 2006; Luiz & Junior, 2011; Nguyen & Faff, 2003;

Reynolds & Boyle, 2005; Schiozer & Saito, 2009; Spand, 2008). However, the major

disadvantage of using the dummy variable is the lack of quantitative information about

the corporate hedging level in a company.

According to the FAS 133 and IAS 39 standards, the derivative instruments are

required to be booked and adjusted to fair value in the company's financial statements.

Therefore, using fair value of derivative instruments makes hypothesis testing on

corporate hedging determinants in foreign exchange and currency risk management

possible. As such, the fair value of the derivative instrument scaled by the market value

of the company was proposed in prior empirical studies (Howton & Perfect, 1998;

Mardsen & Prevost, 2005; Reynolds & Boyle, 2005). However, Graham and Rogers

(2002) argued the fair value of derivatives provides "information on the extent of price

movements in derivative contracts, rather than in the amount of derivatives held" (p.

837). Therefore, the fair value of derivatives does not present a reliable estimate of the

usage of derivative instruments (Graham & Rogers, 2002).

Another quantitative approach to measure corporate hedging in foreign exchange

and currency risk management is a notional value of derivative instruments, which was

proposed in the existing empirical studies (Allayannis & Weston, 2001; Graham &

Rogers, 2002; Lei, 2006; Luiz & Junior, 2011; Menon & Viswanathan, 2005; Nguyen &

Faff, 2003; Reynolds & Boyle, 2005; Rogers, 2002; Schiozer & Saito, 2009). According

to the FAS 133 standard, companies are required to disclose the notional value of

84

derivative instruments in their annual financial reports. The size of a risk exposure for a

financial transaction using derivative instruments can be characterized by the notional

value of derivative instruments (Chance & Brooks, 2007). As such, like the fair value of

derivative instruments, the notional value of derivative instruments has an advantage over

the dummy variable. However, the notional value of derivative instruments has a limit.

The notional value of derivative instruments may overestimate the corporate hedging

activities in a company (Allayannis & Ofek, 2001). Overall, none of these three

measures is appropriate for all situations.

In today's 21st century global economy, companies are exposed to foreign

exchange and currency risk if foreign exchange rate changes are not fully anticipated

(Eiteman et al., 2007; Homaifar, 2004). To reduce the impact of foreign exchange and

currency risk exposure, identifying the type of risk for corporate hedging practices

becomes necessary (Eiteman et al., 2007; Stulz, 2003). The exposure to foreign

exchange and currency risk can be classified into three types: (a) translation risk, (b)

transaction risk, and (c) economic risk. Since company managers should not manage the

exposure to translation risk (Hagelin, 2003; Papaioannou, 2006), hedging transaction risk

and economic risk at the corporate level was the focus of the study in terms of corporate

hedging practices in foreign exchange and currency risk management.

While corporate hedging theories and additional factors have been empirically

tested to examine if nonfinancial companies could benefit from corporate hedging in

foreign exchange and currency risk management, in these empirical studies, researchers

tried to determine the decisive factors for nonfinancial companies to hedge the foreign

exchange and currency risk exposure (Allayannis & Weston, 2001; Bartram et al., 2009;

85

Berkman et al., 2002; Brown, 2001; Carter et al., 2006; Davies et al., 2006; Dolde &

Mishra, 2007; Fabling & Grimes, 2008; Graham & Rogers, 2002; Hagelin, 2003; Judge,

2006; Kapitsinas, 2008; Lei, 2006; Luiz & Junior, 2011; Marsden & Prevost, 2005;

Menon & Viswanathan, 2005; Nguyen & Faff, 2003; Reynolds & Boyle, 2005; Schiozer

& Saito, 2009; Spand, 2008). Furthermore, in these empirical studies three measures of

corporate hedging in foreign exchange and currency risk management were deployed: (a)

a dummy variable indicating derivative uses, (b) fair value of derivative instruments, and

(c) notional value of derivative instruments. However, each of these three measures is

limited.

Summary

For the study, the theoretical area of interest is corporate hedging determinants in

risk management. To improve corporate hedging practices, the proper identification of

the theoretical determinants on corporate hedging yields value-enhancing risk

management decisions (Artez & Bartram, 2010; Petersen & Thiagarajan, 2000; Stulz,

2003). Therefore, the theoretical and empirical literature in corporate hedging was

presented.

The most important consideration of financial research in risk management has

been to develop theoretically sound corporate hedging theories. The two leading

theoretical explanations on corporate hedging, shareholder value maximization and

managerial utility maximization, have been subjected to rigorous empirical testing for

more than 10 years (Artez & Bartram, 2010). From the shareholder value maximization

theory, due to inefficiencies in the perfect capital market, corporate hedging can add

value by reducing various costs involved with future cash flows and alleviating problems

86

associated with these costs. Corporate hedging decisions are influenced by a company's

financial distress (Smith & Stulz, 1985), tax benefits (Graham & Smith, 1999; Smith &

Stulz, 1985), and underinvestment problems (Froot et al., 1993). From the managerial

utility maximization theory, company managers might pursue a corporate hedging policy

that is in their own best interest, rather than a company's shareholders (Jensen &

Meckling, 1976; Shaprio, 2005; Stulz, 2003).

While the effects of key determinants on hedging must be understood to survive

in corporate hedging theories, empirically studying additional factors associated with

companies' usage of derivative instruments in risk management is equally vital to explain

corporate hedging behaviors (Adam et al., 2007; Judge, 2006). A review of each of these

additional factors related to corporate hedging at the organizational level was addressed.

In spite of the voluminous research, the effect of additional corporate hedging factors for

nonfinancial companies remains as ambiguous as key determinants of corporate hedging

theories. The conclusions of the existing empirical assessments are largely sample

specific, and the measurement of these determinants for corporate hedging is not

consistent (Artez & Bartram, 2010; Nguyen & Faff, 2010; Stulz, 2003). Finally, a

discussion of the types of foreign exchange and currency risk exposure, an examination

of the relationship between the risk attributes of U.S. defense companies and corporate

hedging in foreign exchange and currency risk management markets was presented, and a

description of three measures of corporate hedging in foreign exchange and currency risk

management was discussed.

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Chapter 3: Research Method

In the previous chapters, an introduction for the quantitative correlation study was

presented including background, problem statement, purpose of the study, and seven

research questions and corresponding hypotheses. In addition, a foundation of theoretical

support to this quantitative correlation study was established through a review of relevant

literature including corporate hedging theories and previous empirical studies. The

introduction of the study served to direct the research design and data analysis. The

problem addressed within the study was that the U.S. defense companies are exposed to

financial risks resulting in a potential loss of millions of dollars of profits as a result of

corporate hedging practices in foreign exchange and currency risk management markets.

The purpose of the study was to examine the relationship between the risk attributes of

U.S. defense companies and corporate hedging in foreign exchange and currency risk

management markets. The overarching research question for the study was: To what

extent, if any, is each of the seven risk attributes of U.S. defense companies related to

corporate hedging in foreign exchange and currency risk management markets? The

findings of the study could be used to add to the body of knowledge regarding the

organizational determinants of corporate hedging in foreign exchange and currency risk

management.

In the current chapter, the methodology used to achieve the purpose of the study

is discussed. Included in this chapter will be a description of research design and

method; participants; research instruments; operational definition of variables; data

collection; data analysis; methodological assumptions; delimitations, and limitations; and

88

ethical assurances. The chapter ends with a summary of the key components of the

methodology.

Research Design and Methods

A quantitative correlational method was most appropriate for the study because

the statistical relationship between the risk attributes of U.S. defense companies and

corporate hedging in foreign exchange and currency risk management markets was the

focus. Quantitative research is based on the positivistic research philosophy (Creswell,

2003). A positivistic researcher generalizes results to the larger population using the

deductive approach (Creswell, 2003; Trochim & Donnelly, 2008). In the positivistic,

deductive research approach, theory must be first generated and then tested by empirical

observations. If theory is falsified, it has to be rejected, and a new one formulated to

replace it (Creswell, 2003; Trochim & Donnelly, 2008). By adopting a positivistic view,

the study was used to test the tenet of corporate hedging theory that risk attributes are

related to corporate hedging in foreign exchange and currency risk management markets

is clearly warranted. Therefore, a positivistic, deductive orientation was appropriate for

this study, making the choice of a quantitative research design appropriate (Creswell,

2003; Trochim & Donnelly, 2008).

Quantitative research methods work with data in numerical form collected from a

representative sample and analyzed usually through statistical methods (Zikmund &

Babin, 2010). Johnson and Onwuegbuzie (2004) indicated that quantitative methods are

most appropriate when identifying the factors that might influence a specific outcome or

when testing a particular theory, which was precisely the purpose of the study. A

correlation design for the study was most appropriate because the predictor variable

89

cannot be manipulated (Creswell, 2003; Zikmund & Babin, 2010). Financial data

collected for the study were used to capture a measurement of the current level of the risk

attributes of U.S. defense companies and corporate hedging in foreign exchange and

currency risk management markets. Given the nature of the research purpose, the

research questions, and the adequate availability of previous empirical studies to

formulate hypothesized relationships for examination, a quantitative correlational method

was employed in the study.

For the study, the quantitative variables examined included the independent

variables of the risk attributes of U.S. defense companies and the dependent variable of

corporate hedging in foreign exchange and currency risk management markets. Designed

for variables in ratio scale of measurement, bivariate linear regression analyses were

performed to assess the relationship between seven constructed risk attributes and

corporate hedging for a random sample of U.S. defense companies that are faced with

foreign exchange and currency risk exposures. To support the interpretation of

correlation for the study, the correlation metric for measurement included the direction

and strength of the linear relationship between the risk attributes of U.S. defense


markets (Weiers, 2002). A sign of regression coefficients was used to indicate either a

positive or a negative relationship between each of the risk attributes of U.S. defense

companies and corporate hedging (Allen, 2004; Weiers, 2002). A coefficient of

determination was used to determine the strength of the relationship between each of the

risk attributes of U.S. defense companies and corporate hedging (Allen, 2004; Weiers,

2002). By testing the relationship through defined and operationalized variables,

90

sampling strategies, study design, and statistical analysis, the outcome of the study may

be utilized to provide useful insight for corporate hedging to company managers in the

U.S. defense industry, and improve the effectiveness of strategic thinking and decision

making for U.S. defense companies' corporate hedging in foreign exchange and currency

risk management markets.

Validity and reliability are important concepts in quantitative research, reflecting

the rigor of research methodology and the replicability of the results, respectively

(Creswell, 2003; Trochim & Donnelly, 2008; Zikmund, 2003). Therefore, steps were

taken in the study to ensure that validity and reliability were maintained. To achieve

internal and external validity in studies of groups of subjects, the primary methods used

are random selection and assignment and the use of a research design and statistical

analysis that are appropriate to the types of data collected and the questions the researcher

tries to answer (Golafshani, 2003; Zikmund, 2003). A quantitative correlational method

was employed in the study because the purpose of the study was to examine the


in foreign exchange and currency risk management markets. The review of literature for

the study was an important step in identifying the relevant variables of inquiry in the

quantitative study. Therefore, to establish content validity, the relevant variables of the

concept were identified, and the test adequately reflected those variables were

demonstrated (Creswell, 2003; Trochim & Donnelly, 2008; Zikmund, 2003). When a

proxy for the risk attributes of U.S. defense companies was used to measure a variable,

the logic behind the selection was sound and well-documented by the researcher from

literature reviews. Furthermore, to increase confidence in the validity of the findings of

91

the secondary researches for the study, redundant patterns that cut across different

sources and studies were examined (Zikmund & Babin, 2010). Reliability was also

addressed through the use of instrumentation and procedures that allow for the

identification of relationships through random variation or irrelevant events (Allen, 2004;

Weiers, 2002; Zikmund, 2003).

Participants

The purpose of the quantitative correlational study was to examine the


in foreign exchange and currency risk management markets. The population being

addressed in the study consisted of U.S. defense companies that met the following three

criteria: (a) U.S. based defense companies that conducted defense-related business from

2000 to 2010, (b) U.S. defense companies that must disclose financial information about

the use of financial derivatives for hedging in the annual financial report on Form 10-K,

and (c) either a multinational or a domestic U.S. defense company that is exposed to

foreign exchange and currency risk as a result of global competition. The sample was

obtained via a random selection from this population. The narrative market risk

disclosure for U.S. defense companies can be found from Item 7A in the annual financial

report on Form 10-K. Currently, there were 194 defense companies operating in the U.S.

as indicated in the NAARS database (American Institute of Certified Public Accountants,

2005).

For the study, the U. S. defense companies in the population were sampled by a

random process using a random number generator (Zikmund, 2003; Zikmund & Babin,

2010), so that each U.S. defense company remaining in the population had the same

probability of being selected for the sample (Zikmund, 2003; Zikmund & Babin, 2010).

A random sample for the study was drawn from the list of 194 U.S. defense companies.

The procedure of selecting a random sample of U.S defense companies is described in

Appendix A.

To generalize from a sample, the sample must be representative of the population

(Golafshani, 2003; Trochim & Donnelly, 2008; Zikmund, 2003). To ensure findings

from the data analysis can be generalizeable to all U.S. defense companies, a random

sample of the population was used for the study. The objective of a random sample was

to make sure that every U.S. defense company of the population had an equal chance of

being selected (Zikmund, 2003; Zikmund & Babin, 2010). The necessary sample size

was determined using a simple random sampling technique. Since the U.S. defense

companies selected for inclusion in the sample were chosen using probabilistic methods,

the simple random sampling allowed the researcher to make generalizations from the

sample to the population. Such generalizations are more likely to be considered to have

external validity (Golafshani, 2003; Trochim & Donnelly, 2008; Zikmund, 2003). The

researcher also considered whether a sample for U.S. defense companies were

representative of the rest of the population of all U.S. defense companies following U.S.

FAS 133 and IAS 39 standards, especially when the companies are from one industry. If

systematically filtering out some potential U.S. defense companies from the sample was

necessary, the study would have disclosed the filter used.

A power analysis was used to determine the proper sample size necessary to

confirm meaningful effects about the research hypotheses in the study (Cohen, 1989;

Zikmund & Babin, 2010). Sample size determinations depend on three parameters in a

93

power analysis: (a) the desired level of statistical power, set at .80 for the study; (b) the

alpha level (i.e., acceptable Type I error rate), which will be set at .05 for the study; and

(c) the effect size (Allen, 2004; Cohen, 1989; Weiers, 2002; Zikmund, 2003). Cohen

(1989) proposed that a medium effect size off2 = .15 for regression analysis because this

would be able to approximate the average size of observed effects in various fields.

Therefore, the effect size was set at/2 = .15 for the study. An a priori power analysis

was performed using G*Power 3.1 software (see Appendix B), and the sample size

necessary for the study was determined to be 55 U.S. defense companies.

Research Instruments



in foreign exchange and currency risk management markets. Variables were developed

theoretically and abstractly in the mind of the researcher (Zikmund, 2003). For the study,

the researcher drew on corporate hedging theories and prior empirical evidence of

corporate hedging to identify and specify the variables. This section includes a

description and justification of the selected dependent and independent variables for the

study.

In the study, eight instruments were employed to measure eight constructs (seven

independent variables and one dependent variable). The seven independent variables

were (a) financial distress, (b) tax benefits, (c) underinvestment problems, (d) managerial

incentives, (e) scale economies, (f) level of foreign involvement, and (g) revenues

derived from U.S. government defense contracts. The dependent variable was corporate

hedging by U.S. defense companies in foreign exchange and currency risk management

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markets. All of financial data about each U.S. defense company were collected from

annual financial report on Form 10-K and the annual proxy statement, which had been

filed in the EDGAR database system of the SEC.

The interpretations of the results of the study were tempered by an awareness of

the difficulties involved in measuring these selected constructs (Nguyen & Faff, 2010;

Stulz, 2003). As such, for this quantitative correlational study, choosing measurements

of the eight constructs was proceeded with the words of caution in mind. A justification

of each selected instrument is explained below.

Measurement of financial distress. To examine the costs of financial distress

(see hypothesis 1), financial leverage that is measured by a debt ratio (an independent

variable) represents financial distress of a U.S. defense company in the study. Suggested

by Allayannis and Ofek (2001) and also used by Bartram et al. (2009), Berkman et al.

(2002), Graham and Rogers (2002), Hagelin (2003), Hagelin et al. (2007), Haushalter

(2000), Lei (2006), Reynolds et al. (2009), Spand, (2008), a debt ratio provides an

indication of financial strength and the probability of financial distress for a company. A

company with a high debt ratio is more likely experiencing financial difficulties in

honoring the debt payments in the future and will be more financially distressed (Smith &

Stulz, 1985). Therefore, the greater the debt ratio, the greater financially distressed is the

company, and the more incentives the company has to hedge (Allayannis & Ofek, 2001;

Bartram et al., 2009; Berkman, 2002). The internal and predictive validity underlying

this independent variable have been demonstrated to be high in existing empirical studies

of corporate hedging in foreign exchange and currency risk management (Bartram et al.,

2009; Berkman et al., 2002; Graham & Rogers, 2002; Hagelin, 2003; Hagelin et al.,

95

2007; Haushalter, 2000; Lei, 2006; Reynolds et al., 2009; Spano, 2008). As such,

financial leverage measured by a debt ratio was appropriate for use to identify financial

distress of a U.S. defense company in the study.

Measurement of tax benefits. To examine the benefits of expected taxes (see

hypothesis 2), income tax credit range (an independent variable) represents tax benefits

of a U.S. defense company in the study. A company's tax liability is a convex function

of a company's taxable income (Graham & Smith, 1999; Stulz, 2003). Income tax credit

can affect the convexity of the company's taxable income and may reduce a company's

expected tax payments (Graham & Smith, 1999; Stulz, 2003). To use the income tax

credit, a company must have a sufficiently large taxable income (Graham & Rogers,

2002). If the company does not hedge, the company's taxable income may be too low to

use the income tax credit in some years, and so the company will lose the tax benefits.

As such, the company might have incentives to hedge (Graham & Smith, 1999; Stulz,

2003) and increase the probability of taking advantage of the income tax credit. The

internal and predictive validity underlying this independent variable have been

demonstrated to be high in existing empirical studies of corporate hedging in foreign

exchange and currency risk management. Allayannis and Ofek (2001), Mardsen and

Prevost (2005), and Lin and Smith (2007) suggested by reducing the probability of low

taxable income, corporate hedging increases the probability of using tax preference items

and thus the expected tax benefits increase. A sample of 7,319 nonfinancial companies

from 50 countries was examined by Bartram et al. (2009), and they concluded income tax

credit to measure tax incentives is an explanatory factor of corporate hedging with

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derivative uses. Therefore, income tax credit range was appropriate for use to pinpoint

tax benefits of a U.S. defense company in the study.

Measurement of underinvestment problems. To examine underinvestment

problems (see hypothesis 3), R&D spending that is measured by a ratio of R&D expenses

to net sales or revenues (an independent variable) represents underinvestment problems

of a U.S. defense company in the study. Used by Froot et al., 1993, Bartram et al. (2009),

Carter et al. (2006), Dolde and Mishra (2007), Graham and Rogers (2000), Klimczak

(2008), Lei (2006), Lin and Smith (2007), Mseddi and Abid (2010), Schiozer and Saito

(2009), and Spano (2008), a ratio of R&D expenses to net sales or revenues reflects a

company's needs of internal funds and external financing and the future for where the

company's revenue or earnings might come from. To ensure the availability of internal

funds and external financing for a company's investment opportunities, the company with

higher R&D spending might have stronger incentives to hedge (Froot et al., 1993). The

internal and predictive validity underlying this independent variable have been

demonstrated to be high in existing empirical studies of corporate hedging in foreign

exchange and currency risk management. Graham and Rogers (2000), Lei's (2006), and

Mseddi and Abid (2010) reported investment opportunities measured by the R&D

spending are positively related to usages of derivative instruments in foreign exchange

and currency risk management. In other studies, investment opportunities measured by

the R&D spending were negatively related to corporate hedging, according to Bartram et

al. (2009) and Dolde and Mishra (2007). Therefore, the R&D spending measured by a

ratio of R&D expenses to net sales or revenues was appropriate for use to evaluate

underinvestment problems of a U.S. defense company in the study.

97

Measurement of managerial incentives. To examine managerial risk aversion

(see hypothesis 4), presence of CEO stock shares that is measured by a ratio of a

company's stock shares held by the corporate executives to total stock shares on issues

(an independent variable) represents managerial incentives of a U.S. defense company in

the study. When company managers own more stock shares of a U.S. defense company,

the company managers have greater incentives and capacity to hedge in order to reduce

their own personal wealth portfolio's risk since the company managers are overinvested

in their own U.S. defense company (Coles et al., 2004; Jensen & Meckling, 1976; Perry

& Zenner, 2000; Shapiro, 2005; Smith & Stulz, 1985; Stulz, 2003; Tufano, 1996). The

higher the ratio of a company's outstanding stock shares held by the corporate executives

to total stock shares on issues for a company, the greater the degree of preference of

corporate hedging to which company managers' actions are subjected (Marsden &

Prevost, 2005). The internal and predictive validity underlying this independent variable

have been demonstrated to be high in existing empirical studies of corporate hedging in

foreign exchange and currency risk management. Marsden and Prevost (2005) used the

ratio of a company's outstanding stock shares held by the corporate executives to total

stock shares on issues with a sample of 97 companies in 1991 and 91 companies in 1997

listed in New Zealand Stock Exchange and found a significantly positive relationship

between managerial incentives and corporate hedging. Supanvanij and Strauss (2010)

confirmed increases in executive's stock shares are significant related to corporate

hedging. "A $1 increase in CEO equity compensation results in additional $1.26 in

corporate risk activities" (Supanvanij & Strauss, 2010, p. 175). Therefore, the ratio of a

98

company's outstanding stock shares held by the corporate executives to total stock shares

on issues was appropriate for use to valuate managerial incentives in the study.

Measurement of scale economies. To examine scale economies (see hypothesis

5), firm size is measured by a natural logarithm of a company's book value of total assets

(an independent variable) and represents scale economies of a U.S. defense company in

the study. Allayannis and Ofek (2001) and Graham and Rogers (2002) attributed the

predictive power of the natural logarithm of a company's book value of total assets for

firm size to corporate hedging. Given the evident positive skewness in firm size, the

natural logarithm of a company's book value of total assets is the most effective

representation for firm size in many existing empirical studies (Bartram et al., 2009;

Berrospide et al., 2007; Carter et al., 2006; Davies et al., 2006; Guay & Kothari, 2003;

Hagelin et al., 2007; Haushalter, 2000; Hsu et al., 2009; Jong et al., 2006; Judge, 2006;

Kelohaiju & Niskanen, 2001; Lei, 2006; Mseddi & Abid, 2010; Nguyen et al., 2007;

Reynolds et al., 2009; Spano, 2008). The internal and predictive validity underlying this

independent variable have been demonstrated to be high in existing empirical studies of

corporate hedging in foreign exchange and currency risk management (Carter et al.,

2006; Jong et al., 2006; Judge, 2006; Lei, 2006; Nguyen et al., 2007; Spano, 2008). The

researchers of the existing empirical studies concluded firm size is significantly and

positively related to corporate hedging with derivative instruments (Berrospide et al.,

2007; Carter et al., 2006; Davies et al., 2006; Guay & Kothari, 2003; Hagelin et al., 2007;

Haushalter, 2000; Hsu et al., 2009; Jong et al., 2006; Judge, 2006; Klimczak, 2008; Lei,

2006; Mseddi & Abid, 2010; Nguyen et al., 2007; Spano, 2008). Therefore, the natural

99

logarithm of a company's book value of total assets was appropriate for use to estimate

scale economies in the study.

Measurement of level of foreign involvement. To examine the U.S. defense

company's extent of foreign involvement (see hypothesis 6), foreign sales ratio is a ratio

of international sales to net sales or revenues (an independent variable) and represents

level of foreign involvement of a U.S. defense company in the study. Level of foreign

involvement is a potential determinant of corporate hedging (Jorion, 1990). To

appropriately measure a company's foreign involvement, the researchers have primarily

relied upon one accounting number, namely foreign sales ratio (Allayannis & Ofek, 2001;

Bartram et al., 2009; Clark, & Mefteh, 2011; Dolde & Mishra, 2007; Jong et al., 2006;

Jorion, 1990; Pantzalis et al., 2001). A foreign sales ratio is to be the least biased at the

organizational level (Jorion, 1990), and the primary motivation has been the easy

availability of historical data (Allayannis & Ofek, 2001; Bartram et al., 2009; Clark, &

Mefteh, 2011; Dolde & Mishra, 2007; Jong et al., 2006; Jorion, 1990; Pantzalis et al.,

2001). A high foreign sale ratio indicates the level of foreign involvement grows and

increases the company's exposure to the foreign exchange and currency risk (Allayannis

& Ofek, 2001; Bartram et al., 2009; Clark, & Mefteh, 2011; Dolde & Mishra, 2007; Jong

et al., 2006; Jorion, 1990; Pantzalis et al., 2001). The internal and predictive validity

underlying this independent variable have been demonstrated to be high in existing

empirical studies of corporate hedging in foreign exchange and currency risk

management (Allayannis & Ofek, 2001; Bartram et al., 2009; Clark, & Mefteh, 2011;

Dolde & Mishra, 2007; Jong et al., 2006; Jorion, 1990; Pantzalis et al., 2001). The higher

foreign sales ratio a company has, the higher is the probability the company uses

100

corporate hedging to reduce the foreign exchange and currency risk exposure (Allayannis

& Ofek, 2001; Bartram et al., 2009; Clark, & Mefteh, 2011; Dolde & Mishra, 2007; Jong

et al., 2006; Jorion, 1990; Pantzalis et al., 2001). Bartram et al. (2009) reported a positive

relationship between the level of foreign involvement and corporate hedging with foreign

currency derivative holdings using foreign sales ratio as a measure of the extent of

foreign involvement. Therefore, foreign sales ratio was appropriate for use to define the

level of foreign involvement of a U.S. defense company in the study.

Measurement of revenues from U.S. government contracts. To examine the

U.S. defense company's business involvement with U.S. government (see Hypothesis 7),

sales to the U.S. government is measured by a ratio of sales to U.S. government to net

sales or revenues for a U.S. defense company (an independent variable) and represents

revenues from U.S. government defense contracts in the study. A percent of revenues

that are derived from U.S. government contracts indicates how much a U.S. defense

company is engaged in business with the DoD (The Boeing Company, 2009; Lockheed

Martin Corporation, 2009). Increase in sales to the U.S. government may increase the

degree of scrutiny in auditing from U.S. government agencies (The Boeing Company,

2009; Eiteman et al., 2007; Lockheed Martin Corporation, 2009). To shift the risks, a

U.S. defense company might tend to have a lower demand for corporate hedging.

Therefore, the sales to U.S. government for a U.S. defense company offered much

potential as an approach to measure the revenues derived from U.S. government defense

contracts in the study.

Measurement of corporate hedging in foreign exchange and currency risk

management. The dependent variable, corporate hedging by U.S. defense companies in

101

foreign exchange and currency risk management markets, was measured by notional

value of foreign exchange and currency derivatives. According to the FAS 133 standard,

companies are mandated to disclose the notional value of derivative instruments in the

annual financial reports. For the study, only the amount of derivative instruments used

for the purpose of corporate hedging in foreign exchange and currency risk management

were selected. According to Purnanandam (2007), the notional value of derivative

instruments in corporate hedging captures "the firm's total ownership of risk

management instruments and is thus able to distinguish between companies with different

intensities of hedging" (p. 719). The construct validity underlying this dependent

variable has been demonstrated to be high in existing empirical studies of corporate

hedging in foreign exchange and currency risk management (Allayannis & Weston, 2001;

Graham & Rogers, 2002; Lei, 2006; Luiz & Junior, 2011; Menon & Viswanathan, 2005;

Nguyen & Faff, 2003; Purnanandam, 2007; Reynolds & Boyle, 2005; Schiozer & Saito,

2009). Therefore, the notional value of foreign exchange and currency derivative

instruments was appropriate for use with the U.S. defense companies' corporate hedging

in the foreign exchange and currency risk management.

Operational Definition of Variables



in foreign exchange and currency risk management markets. In the study, the operational

definition of the dependent and independent variables are defined as follows. Table 1

shows a summary of independent variables, description, and data types for the study.

102

Table 1

Summary of Independent Variable, Description and Data Type

Independent variable Description Data type

Financial distress Debt ratio Ratio

Tax benefits Income tax credit range Ratio

Underinvestment problems R&D spending Ratio

Managerial incentives Presence of CEO stock shares Ratio

Scale economies Firm size Ratio

Level of foreign involvement Foreign sales ratio Ratio

Revenues from U.S. government contracts Sales to U.S. government Ratio

Independent variable/Financial distress. Financial distress of a U.S. defense

company is measured by a debt ratio, which is a ratio of book value of debt to book value

of equity (an independent variable). Data for book value of debt and book value of

equity can be collected from the annual financial report on Form 10-K. The level of

measurement for the variable is a ratio scale.

Independent variable/Tax benefits. Tax benefits of a U.S. defense company are

measured by an income tax credit range (an independent variable). Data for a company's

income tax credit can be collected from the annual financial report on Form 10-K. The

level of measurement for the variable is a ratio scale.

Independent variable/Underinvestment problems. Underinvestment problems

of a U.S. defense company are measured by R&D spending, which is a ratio of R&D

103

expenses to net sales or revenues (an independent variable). Data for R&D expenses and

net sales or revenues can be collected from the annual financial report on Form 10-K.

The level of measurement for the variable is a ratio scale.

Independent variable/Managerial incentives. Managerial incentives of a U.S.

defense company are measured by presence of CEO's stock shares, which is a ratio of a

company's stock shares held by the corporate executives to total number of stock shares

on issues (an independent variable). Data for a company's stock shares held by the

corporate executives and total number of stock shares on issues can be collected from the

annual proxy statement and the annual financial report on Form 10-K. The level of


Independent variable/Scale economies. Scales economies of a U.S. defense

company are measured by firm size, which is the natural logarithm of a company's book

value of total assets (an independent variable). Data for a company's book value of total

assets can be collected from the annual financial report on Form 10-K. The level of


Independent variable/Level of foreign involvement. Level of foreign

involvement of a U.S. defense company is measured by foreign sales ratio, which is a

ratio of international sales to net sales or revenues (an independent variable). Data for

international sales and net sales or revenues can be collected from the annual financial

report on Form 10-K. The level of measurement for the variable is a ratio scale.

Independent variable/Revenues from U.S. government contracts. Revenues

from U.S. government contracts of a U.S. defense company are measured by sales to U.S.

government, which is a ratio of sales to U.S. government to net sales or revenues (an

104

independent variable). Data for sales to U.S. government and net sales or revenues can

be collected from the annual financial report on Form 10-K. The level of measurement

for the variable is a ratio scale.

Dependent variable/Corporate hedging in foreign exchange and currency

risk management. Corporate hedging in foreign exchange and currency risk

management is measured by notional value of derivative instruments (a dependent

variable). Data for the notional value of derivative instruments can be collected from the

annual financial report on Form 10-K. The level of measurement for the variable is a

ratio scale.

Data Collection, Processing, and Analysis

The purpose of the study was to examine the relationship between the risk


currency risk management markets. A quantitative correlational methodology of data

analysis was utilized for the study. The annual financial reports on Form 10-K and the

annual proxy statement refer to fiscal year 2010. The data collection and data analysis

procedures employed in the study are presented in this section.

Data collection. A sample of a financial dataset used for the study included a

U.S. defense company's book value of debt, book value of equity, income tax credit,

book value of assets, R&D expenses, net sales or revenues, stock shares held by the

corporate executives, total number of stock shares on issues, international sales, sales to

U.S. government, and the notional value of derivative instruments. Since U.S. defense

companies' annual financial report on Form 10-K and the annual proxy statement have

been filed in the EDGAR database system of the SEC, and the financial data from these

105

reports cannot be manipulated and are in "the form of numbers that can be quantified and

summarized" (Golafshani, 2003, p. 598), the richness and accuracy of data necessary to

establish the ability to draw statistical interfaces was provided for the study.

By employing secondary data, "researchers can avail themselves to new sources

of data and can shed new light on or provide important corroborating evidence to

established streams of research that have relied on a limited variety of methodological

approaches" (Houston, 2004, p. 154). With the passage of the Sarbanes-Oxley Act of

2002, corporate executives must certify the financial statements are faithful

representations of the financial positions and results of operations of the company

(Whittington & Pany, 2004). Because of the disclosure improvements for a company's

business and financial information, more empirical studies on the use of financial

derivatives have employed the data on corporate hedging activities contained in the

company's annual financial report (Apostolou & Apostolou, 2008; Bartram et al., 2009;

Carter et al., 2006; Hsu et al., 2009; Judge, 2006; Nguyen et al., 2007; Ramirez, 2007;

Reynolds et al., 2009; Schiozer & Saito, 2009; Spano, 2008; Sprfiic, 2007). Since the

sample data from the annual financial report on Form 10-K is monetary figures with

description, the sample data had face validity (Zikmund, 2003). The study had high

external validity even though the internal validity was not as strong because the study

used actual financial data on real companies.

A problem of using the annual financial report on Form 10-K was a lack of

uniformity in the parts of the annual financial statements where the use of derivative

instruments is reported. Companies disclosed financial derivatives use in a variety of

footnotes to the financial statements, and footnotes were frequently not cross-referenced

106

making it difficult to know if all financial derivatives disclosures had been identified. As

a result, the data collected for analysis may have been skewed to a certain extent. To

improve internal validity and ensure the data gathered in the study was suitable to a

quantitative analysis, several questions were asked as part of an attempt to evaluate the

usefulness of data from the annual financial report on Form 10-K (see Figure 2).

Searching keywords related to corporate hedging by U.S defense companies in foreign

exchange and currency risk management markets on Form 10-K was performed for the

study. The keywords included Item 7A, quantitative disclosure, accounting for hedging,

risk management, financial risk, risk factors, off balance sheet, derivative, hedging,

sensitivity analysis, eamings-at-risk, cash flow at risk, value at risk (VaR), international

sales, foreign sales, foreign exchange rate, foreign currency risk, foreign currency debt,

price risk, market risk, futures contract, forward contract, option, swap, notional value,

and U.S. government sales and contracts. The robustness of data or information can also

be enhanced through multiple-source validation (Zikmund, 2003; Zikmund & Babin,

2010). Therefore, one check included a comparison of financial data collected from the

annual financial report on Form 10-K with information provided from other sources.

Established research as determined that if the sets of data are comparable, the data

collected for the study may have had some degree of reliability.

Data processing and analysis. Methods for analyzing data fall into two

categories of statistical procedures: nonparametric and parametric, which are

distinguished by whether or not assumptions about the distribution of the data are met

(Weiers, 2002). The parametric methods were selected to test hypothesis for the study

because the normality, independence of errors, and equal variance assumptions

107

r

Applcabiity ID the current -<

project

Vs.

Do the data help to answer questions set out in the

problem definition?

• Yw

Do the data apply to the time period of interest?

YM Do the data apply to the population of hterest?

Do other terms and variable calssificatais presented apply to the

current project?

• YM

Are the units of measurement comparable?

No*

No*

No*

No*

No*

Can the data be reworked?

If yea, continue

No*

Accuiacyof j the data ̂

Is using the data worth the risk?

Is it possible to go to the original source of the data?

• Y<* Is the oost of the data acquisition worth it?

• Yw Is there a possibility

of bias?

• N»

No*

No*

VIM*

Can the accixacy of the data collection be verified?

No* (Inaccurate

• YM (aocurate) or unsure)

Use data

Figure 2. Evaluating secondary data. From Exploring marketing research (10th ed.) by W. G. Zikmund and B. J. Babin, 2010, p. 160. Copyright 2010 by South-Westem, a part of Cengage Learning, Inc. Reproduced by permission, www.cengage.com/permissions (see Appendix C).

108

underlying the bivariate linear regression for the study are required to be validated

(Allen,2004; Weiers, 2002). If any of the assumptions are violated, insights yielded by

parametric statistical analyses may be inefficient, seriously biased, or misleading. In

other research studies in the proposed research area, Bartram et al. (2009), Berkman et al.

(2002), Carter et al. (2006), Hsu et al. (2009), Jin and Jorion (2006), Jong et al. (2006),

Judge (2006), Khediri (2010), Lei (2006), Marsden and Prevost (2005), Nguyen et al.

(2007), Nguyen and Faff (2010), Reynolds et al. (2009), Spano (2008), and SprCi6 (2007)

demonstrated that parametric methods were appropriate.

Next, the selection of the category of statistical procedures is also determined by

the scale of measurement of variables (Zikmund, 2003). The parametric methods require

an interval or ratio scale of measurement of the variables while the nonparametric

methods require a nominal or ordinal scale of measurement of the variables (Weiers,

2002). For the study, the dependent variable (corporate hedging in foreign exchange and

currency risk management markets) and the independent variables (U.S. defense

company-specific risk attributes) have a ratio scale of measurement. Finally, large

sample sizes are more likely to show significant deviations from normality, and the

nonparametric methods lack statistical power with small samples (Allen, 2004; Weiers,

2002; Zikmund, 2003). For the study, the sample size was less than 100 based upon the

power analysis. To detect any given effect at a specified significance level, a larger

sample size would have been needed for the nonparametric methods. Therefore,

parametric methods to test the hypotheses were selected for the study.

In prior empirical studies, the outcome of corporate hedging decisions was

considered to be a linear function of the independent variables, which are proxies of the

109

determinants of corporate hedging (Allayannis & Weston, 2001; Berrospide et al., 2007;

Carter et al., 2006; Hagelin, 2003; Jin & Jorion, 2006; Judge, 2006; Khediri, 2010; Lei,

2006; Nguyen et al., 2007; Nguyen & Faff, 2010; Reynolds et al., 2009; Spano, 2008;

SprCic, 2007). For the study, the relationship between each U.S. defense company-

specific risk attribute and corporate hedging in foreign exchange and currency risk

management markets was tested using bivariate linear regression analyses. The

dependent variable for each hypothesis in the study was the level of corporate hedging in

foreign exchange and currency risk management. In each hypothesis, an independent

variable was one of the seven U.S. defense company-specific risk attributes. Bivariate

linear regression analysis was applied to address the research questions for the study

because bivariate regression analysis can be used to ensure the relationships identified by

correlation analysis as significant are in fact statistically significant, not a chance

occurrence (Allen, 2004; Weiers, 2002; Zikmund, 2003).

In hypothesis testing, there are always two contradictory hypotheses under

consideration (Allen, 2004; Creswell, 2003; Weiers, 2002; Zikmund, 2003). The

objective of hypothesis testing is to decide, based on information derived from a sample,

which of the two hypotheses is correct (Allen, 2004; Creswell, 2003; Weiers, 2002;

Zikmund, 2003). The two competing statements are called the null hypothesis (Ho) and

the alternative hypothesis (Ha). The following steps were taken for conducting

hypothesis testing to address the research questions in the study: stated the hypothesis to

be tested, analyzed the assumptions of underlying linear regression, selected test statistic

used for measures of association, and defined decision criterion to either reject or fail to

reject the hypothesis (Allen, 2004; Weiers, 2002; Zikmund, 2003).

110

State the hypothesis to be tested. For the study, the relationship between each

U.S. defense company-specific risk attribute and corporate hedging in foreign exchange

and currency risk management markets was defined as a bivariate linear regression with

corporate hedging in foreign exchange and currency risk management markets as the

dependent variable and each U.S. defense company-specific risk attribute as the

independent variable. The bivariate linear regression can be expressed as follows:

YJ = AO + BJ XJ + EI

where Xt is the independent variable, which represents for U.S. defense company-specific

risk attribute i. Seven linear regression analyses were performed, with each analysis

including one of the seven risk attributes: Xj is financial distress, X2 is tax benefits, X3 is

underinvestment problems, X4 is managerial incentives, X5 is scale economies, X$ is level

of foreign involvement, and Xj is revenues from U.S. government contracts. Ao is a

constant amount for corporate hedging in foreign exchange and currency risk

management markets with zero U.S. defense company-specific risk attribute, Bt is the

regression coefficient, e, is the random error reflecting other factors that influence

corporate hedging in foreign exchange and currency risk management markets, and F„

denoted corporate hedging in foreign exchange and currency risk management markets

for the ith U.S. defense company-specific risk attribute, is the dependent variable.

Given a random sample of pairs of Xt and Yh the method of ordinary least squares

(OLS) was used to estimate the values of Ao and Bt such that the value of e, is minimized

(Allen, 2004; Weiers, 2002; Zikmund, 2003). If there is a linear relationship between

U.S. defense company-specific risk attribute (Xj) and corporate hedging in foreign

Ill

exchange and currency risk management markets (Yt), the value of B, will be different

from zero. If there is no linear relationship between U.S. defense company-specific risk

attribute (X,) and corporate hedging in foreign exchange and currency risk management

markets (7/), the value of 5, will be equal to zero. Since to demonstrate that something is

true is statistically impossible, and statistical techniques are much better at demonstrating

something is not true (Weiers, 2002; Zikmund, 2003), for the study, the null hypothesis

(Ho) was used to predict there is no linear relationship between U.S. defense company-

specific risk attribute (X,) and corporate hedging in foreign exchange and currency risk

management markets (7/). As such, to determine the existence of a significant linear

relationship between U.S. defense company-specific risk attribute (X,) and corporate

hedging in foreign exchange and currency risk management markets (F,), the null and the

alternative hypotheses can be stated as follows:

Ho. Bj = 0

H„. Bit 0

Validate the assumptions of underlying linear regression. The proper use of

bivariate linear regression in the study depended on the underlying assumptions of

linearity, independence of errors, normality, and equal variance (Allen, 2004, Weiers,

2002). Among the best ways to validate the linearity, normality, and equal variance

assumptions for the bivariate linear regression is via visual inspections of residual plots

(Weiers, 2002). Although different ways to generate residual plots exist, two types of

residual plots were selected for the study: a normal probability plot of residuals for

assessing the normality of distribution of residuals and a residual scatter plot to provide a

visual indicator of both the linearity of the relationship and the homogeneity of variance

112

for the residuals. When outliers were encountered, the researcher needed to decide

whether or not to include the outliers in the analysis (Weiers, 2002). Regardless of the

decision, the presence of outliers was acknowledged. If the decision was to exclude the

outliers, the researcher provided a clear rationale for deleting the outliers and reported the

regression coefficient both with and without the outliers.

The assumption of independence of errors for the bivariate linear regression was

evaluated with the Durbin-Watson statistic for the study because the Durbin Watson

statistic is a well-known formal method of testing if autocorrelations is a serious problem

undermining the inferential suitability of the linear regression model (Weiers, 2002). The

test statistic of the Durbin-Watson procedure is d and is calculated as follows:

± { e - e , _ x ) 2

d = ̂

T E ] T=i

where e, and et., represent observed residuals, and n is number of observations. The value

of d is between 0 and 4. For a given level of significance, sample size, and number of

independent variables, the critical values of d are tabulated as pairs of values: A, and Dv

(Weiers, 2002). With one independent variable in bivariate linear regression and a

sample size of 55 U.S. defense companies for the study, the critical values, Di = 1.53 and

Du= 1 -60, were given for a two-tail test at the 0.05 level of significance (Weiers, 2002).

For the present study, Table 2 shows decision zones and appropriate interpretation for a

calculated value of the Durbin-Watson statistic, d.

Select test statistic used for measures of association. Appropriate parametric

methods to discover whether or not the linear regression is effective in fitting the data are

113

Table 2

General Guidelines for Interpreting the Calculated Value of Durbin-Watson Statistics (d)

Decision zone Interpretation

0 < d < 1.53 Positive autocorrelation is strong.

1.53 < d < 1.60 The test is inconclusive.

l . 6 0 < d < 2.40 Autocorrelation is absent.

2.40 < d < 2.47 The test is inconclusive.

2.47 < d < 4 Negative autocorrelation is strong.

either F-test or /-test (Allen, 2004; Weiers, 2002). The F-test tests the overall linear

regression model (Allen, 2004; Weiers, 2002). The test for significance of regression in

multiple linear regression analysis is carried out using the F-test. Multiple /-tests analyze

the significance of each regression coefficient (Allen, 2004; Zikmund & Babin, 2010).

Because only one coefficient exists in a bivariate linear regression, the F-test and the /-

test will be identical and provide the same conclusions of the statistical analysis (Allen,

2004; Weiers, 2002). Given the bivariate linear regression for the study, the /-test was

selected to determine the existence of a significant linear relationship between each U.S.

defense company-specific risk attribute and corporate hedging in foreign exchange and

currency risk management markets.

The two-tailed test always uses = and ^ in the statistical hypotheses and are

directionless in that the alternative hypothesis allows for either the greater than (>) or less

than (<) possibility (Allen, 2004; Weiers, 2002). Based upon the null and the alternative

114

hypotheses stated in the study, the two-tailed test were performed in the hypothesis

testing because results that are obtained for the study may be in opposition to the

direction that the researcher thinks would occur. Knowing the opposite results from what

they expected are true was also important for the study.

Define decision rules to either accept or reject the hypothesis. Alpha level (a),

denoted the probability of Type I error, designated the risk of rejecting the hypothesis if it

is actually true (Allen, 2004; Weiers, 2002; Zikmund, 2003). The alpha level is typically

.05 or .01 (Zikmund, 2003). In previous empirical studies, the accepted alpha level has

been established at 0.05, or a 5% probability that a significant difference will occur by

chance (Bartram et al., 2009; Brown, 2001; Carter et al., 2006; Gay & Nam, 1998;

Graham & Rogers, 2000; Hsu et al., 2009; Judge, 2006; Nguyen et al., 2007; Reynolds et

al., 2009; Spand, 2008). Therefore, all decisions on the statistical significance of the

findings were made using a criterion alpha level of .05 in the hypothesis testing for the

study.

The decision rules to either reject or fail to reject the hypothesis are described by

two equivalent approaches: region of acceptance, and p-value (Allen, 2004; Weiers,

2002). The /?-value is used to quantitatively measure the strength of evidence against the

null hypothesis, and the smaller p-value provides stronger evidence against the null

hypothesis (Allen, 2004; Weiers, 2002). Based upon the hypotheses and research

questions for the study, the p-value approach was selected. If the p- value was less than or

equal to the alpha level (p < .05), the researcher rejected the null hypothesis for the study.

If the p-value was greater than the alpha level (p > .05), the researcher failed to reject the

null hypothesis for the study.

115

Interpretation of correlation. Creswell (2003) defined the final step in

quantitative data analysis as the action "to interpret the findings in light of the hypotheses

or research questions set forth in the beginning" (p. 167). For the study, to support the

interpretation of correlation in bivariate linear regression analysis, the researcher first

looked at the signs of the regression coefficients (B,). These signs are used to give insight

into the effects of the explanatory variables on the linear outcome (Weiers, 2002). The

positive regression coefficient indicates that there is a positive relationship between U.S.

defense company-specific risk attribute and corporate hedging in foreign exchange and

currency risk management markets for the study. For the opposite direction, the negative

regression coefficient indicates that there is a negative relationship between U.S. defense

company-specific risk attribute and corporate hedging in foreign exchange and currency

risk management markets for the study.

Next, the strength of correlation between U.S. defense company-specific risk

attribute and corporate hedging in foreign exchange and currency risk management

markets was measured by the coefficient of determination (Allen, 2004; Weiers, 2002).

For bivariate linear regression, coefficient of determination (R ) represents what

proportion of the variation in the dependent variable is associated with the regression of

an independent variable (Allen, 2004; Weiers, 2002). The value of R2 ranges from 0 to 1.

As a high level of shared variance, a large value of R2 indicates a strong linear

relationship between U.S. defense company-specific risk attribute (the independent

variable) and corporate hedging in foreign exchange and currency risk management

markets (the dependent variable). As a low level of shared variance, a small value of R

is considered as being of little or no practical importance, even though the association

116

between U.S. defense company-specific risk attributes and corporate hedging in foreign

exchange and currency risk management markets is statistically significant. While

performing linear regression analysis for the study using Microsoft Excel 2007 with

PHStat2 add-in, the value of coefficient of determination is provided in the model

summary of linear regression analysis.

Allen (2004) and Zikmund (2003) noted that correlations do not imply causality.

When the researcher finds U.S. defense company-specific risk attribute and corporate

hedging in foreign exchange and currency risk management markets with a strong

correlation, a relationship between U.S. defense company-specific risk attribute and

corporate hedging in foreign exchange and currency risk management markets is

concluded, not changes in U.S. defense company-specific risk attribute causes changes in

corporate hedging in foreign exchange and currency risk management markets.

Linear regression analysis conducted in the study may be one of the most

commonly used statistical analysis techniques in business research (Zikmund & Babin,

2010). Statistical conclusion validity refers to the degree to which one's analysis allows

one to make the correct decision regarding the truth or approximate truth of the null

hypothesis (Creswell, 2003; Zikmund & Babin, 2010). Various threats to making valid

conclusions exist in linear regression analysis (Allen, 2004; Creswell, 2003). The threats

can be reduced by increasing the sample size to increase the statistical power to find a

relationship, accepting lower significance levels (a = .10 instead of a = .05) to reduce the

chance of ignoring relationships that do exist, and by increasing the reliability of

instrumentation and procedures so that relationships can be shown over the noise of

random or irrelevant events (Allen, 2004; Weiers, 2002; Zikmund, 2003). By probing the

117

evidence of direction, magnitude, statistical significance, and variance, together with the

objective and research questions of the study, the researcher can reduce the chance of

reporting trivial findings. Simultaneously, the communication of findings from the study

is improved. Finally, reliability is maintained by revealing every reference and data

source explicitly, and presenting every equation and sampling process adopted in the

study transparently, so that any calculations are able to be audited.

Methodological Assumptions, Delimitations, and Limitations



in foreign exchange and currency risk management markets. The methodological

assumptions of the study included financial data collected in annual financial reports was

reliable, consistent, and accurate from the EDGAR database system of the SEC, and the

underlying assumptions of linear regression analysis are linearity, independence of errors,

normality, and equal variance. If the financial data did not satisfy these underlying

assumptions, the statistical results for the study would not be a true reflection of the

relationship between the risk attributes of U.S. defense companies and corporate hedging.

Therefore, if the financial data did not meet the underlying assumptions, a transformation

procedure was required. For the study, a natural logarithmic function was selected for

transformation on a data set (Allen, 2004). Both the dependent and independent variables

were subjected to the same transformation. Using the transformed variables, bivariate

linear regression analyses were performed. The bivariate linear regression can be

expressed as follows:

Log(7/) =A 0 + Bi LogPQ + Ej

118

Participants in the study were delimited to U.S. defense companies that conducted

defense related business from 2000 to 2010 in the U.S.. Because the study only focused

on certain aspects of U.S. defense companies' corporate hedging in foreign exchange and

currency risk management, the limitation of the study was the outcome of the study

would not provide a complete understanding of complexity and richness of corporate


companies. The results of the study can only be generalized to the population of 194

U.S. defense companies from which the sample was obtained. The generalization of the

study to other industries or foreign defense companies was not warranted.

Ethical Assurances



in foreign exchange and currency risk management markets. Ethical issues for the study

were addressed at each phase in the study. In compliance with the regulations of the

Institutional Review Board (IRB), permission for conducting the study was obtained from

Northcentral University's (NCU) IRB before the sample of financial data for the study

was collected. The request for review form was filed, providing information about the

principal investigator, the study title and type, source of funding, type of review

requested, and number and type of subjects. Application for the study permission

contained the description of the study and its significance, methods and procedures,

participants, and research status.

The credibility of a study critically depends on the integrity with which the study

is designed, analyzed, and concluded (Zikmund & Babin, 2010). The researcher's

119

responsibility is to ensure the study is conducted in an ethical and responsible manner.

The researcher's involvement with data collection for this study included manual

gathering of financial data from the annual financial report on Form 10-K and the annual

proxy statement using the defined procedures, including sampling, data evaluation, and

reliability and validity checks of the research instruments. Selection of samples was a

critical issue in the study. A sample must represent a population; otherwise,

generalizability of the findings using the sample for the study would be limited (Zikmund

& Babin, 2010). To ensure findings from the data analysis can be generalizeable to the

population of 194 U.S. defense companies, a random sample of the population was used

for the study. The necessary sample size was determined using well-developed statistical

techniques.

Another researcher's responsibility is to analyze the data appropriately (Zikmund

& Babin, 2010). Although inappropriate data analysis does not certainly indicate

misbehavior, an intentional exclusive of results from the study will mislead the readers

and cause misinterpretation (Zikmund & Babin, 2010). The researcher therefore needed

to make sure the sample of financial data was gathered, analyzed, and interpreted

honestly and fairly in the study. To ensure appropriate data analysis in the study, all

relevant sources and research methods used to gather related information were

completely disclosed. Failure to have done so may have led misinterpretation of the

results without considering the likelihood of the study being underpowered (Humphrey &

Lee, 2004). The data analysis was performed using rigorous statistical analysis

techniques, and the results were interpreted based on the established values for the

statistical significance of the functions. Any issues of bias were addressed in the study,

120

and the researcher explained how the issues of bias were handled in the design, analysis,

and conclusions of the study.

Summary

The methodology used in conducting the present study was detailed within

chapter 3. Corporate hedging theories were the theoretical foundation of the study. The

findings of the study were formed by an inductive research method. By empirically

testing the relationship between the risk attributes of U.S. defense companies and

corporate hedging in foreign exchange and currency risk management markets through

defined and operationalized variables, sampling strategies, study design, and statistical

analysis, generalization from the sample to population will be possible, which was the

purpose of the study. Based upon the identified research questions and objective, the

quantitative correlational design was most appropriate for the study.

The population for the study was 194 defense companies operating in the U.S., as

indicated in the NAARS database (American Institute of Certified Public Accountants,

2005). Using a quantitative correlational method, the researcher randomly selected 55

U.S. defense companies to examine the relationship between the risk attributes of U.S.


management markets. For the study, bivariate linear regression analysis was selected as

the most appropriate statistical technique to determine if the existence of the risk

attributes of U.S. defense companies, such as costs of financial distress, investment

opportunities, tax benefits, and managerial incentives, would significantly relate to U.S.

defense companies' hedging in foreign exchange and currency risk management markets.

The coefficient of determination and sign of regression coefficients were used to

121

determine the strength and direction of the relationship between the risk attributes of U.S.


management markets.

The findings from the study must yield both internal and external validity because

the ability to generalize research results from the sample to the population of U.S.

defense industry was one of the main purposes of the study. Because the researcher only

focused on certain aspects of corporate hedging in foreign exchange and currency risk

management, the outcome of the study would not provide a complete understanding of

complexity and richness of corporate hedging in foreign exchange and currency risk

management markets for U.S. defense companies. Finally, the researcher's responsibility

was to ensure the study was conducted in an ethical and responsible manner so that the

credibility of the study was achieved. In accord with the IRB regulations, no financial

data for the study were collected prior to the approval for conducting the study.

122

Chapter 4: Findings



in foreign exchange and currency risk management markets. Seven research questions

were operationalized based from a single research question: To what extent, if any, is

each of the risk attributes of U.S. defense companies related to corporate hedging in

foreign exchange and currency risk management markets? Seven constructed

independent variables were constructed representing the risk attributes of U.S. defense

companies: (a) financial distress, (b) underinvestment problems, (c) tax benefits, (d)

managerial incentives, (e) scale economies, (f) level of foreign involvement, and (g)

revenues derived from U.S. government contracts. Data collected for the seven

constructed independent variables aligned with (a) debt ratio, (b) income tax credit range,

(c) research and development spending, (d) presence of CEO stock shares, (e) firm size,

(f) foreign sale ratio, and (g) sales to U.S. government. As a constructed dependent

variable for the study, corporate hedging in foreign exchange and currency risk

management markets was defined as "a component of a more general process called risk

management, the alignment of the actual level of risk with the desired level of risk"

(Chance & Brooks, 2007, p. 355). Data collected for the constructed dependent variable

was a notional value of derivatives, as mentioned in Chapter 3.

The results from the analysis of data that were used to address these seven

research questions are described in this chapter. Sections of this chapter include

quantitative results, and the evaluation of the findings. A summary of the findings are

highlighted at the end of the chapter.

123

Results

Descriptive statistics. A random sample for the study was taken from 194

defense companies operating in the U.S. as indicated in the NAARS database (American

Institute of Certified Public Accountants, 2005). According to the power analysis

description noted in Chapter 3, a sample size of 55 U.S. defense companies was required

to establish statistical significance. Information on corporate hedging practices in foreign

exchange and currency risk management was gathered from annual financial reports

(Form 10-K and the annual proxy statement) submitted to the SEC by each of the U.S.

defense companies. A total of 55 U.S. defense companies' financial reports in 2010 were

obtained. All the data for the study was extracted manually from each company's

financial report.

As stated in the financial reports, all 55 U.S. defense companies were found to

have been exposed to foreign exchange and currency risk. In this study, corporate

hedging by U.S. defense companies in foreign exchange and currency risk management

markets (the dependent variable) was measured by a notional value of foreign exchange

and currency derivatives. Reporting the notional value of foreign exchange and currency

derivatives showed many U.S. defense companies had either less than $100 million of

notional value of derivative instruments (n = 18,32.73%) or between $100 and $500

million (n = 19, 34.55%). The remaining U.S. defense companies had either between

$500 and $1,500 million of notional value of derivative instruments (n = 9,16.36%) or

over $1,500 million (n = 9,16.36%). Frequencies and percentage for corporate hedging

in U.S. defense industry are presented in Table 3.

124

Table 3

Frequencies and Percentages of Corporate Hedging in Foreign Exchange and Currency

Risk Management Markets

Variable Frequency Percentage

Corporate hedginga

Under 100 18 32.73%

101-500 19 34.55%

501-1,500 9 16.36%

Over 1,500 9 16.36%

Total 55 1 00.00%

Note. a Represented by a notional value of derivative instruments (dollars in million).

The seven risk attributes of U.S. defense companies (the independent variables)

were defined as (a) financial distress, (b) tax benefits, (c) underinvestment problems, (d)

managerial incentives, (e) scale economies, (f) level of foreign involvement, and (g)

revenues derived from U.S. government defense contracts. Financial distress of a U.S.

defense company was measured by a debt ratio, which is a ratio of book value of debt to

book value of equity. Of the 55 U.S. defense companies, many U.S. defense companies

had either less than 1.0 of debt ratio (n = 20, 36.36%) or between 1.0 and 2.0 (« = 19,

34.54%). The remaining U.S. defense companies had either between 2.1 and 3.0 of debt

ratio (n = 8,14.55%) or over 3.0 (« = 8,14.55%). Frequencies and percentages of

financial distress for U.S. defense companies are presented in Table 4.

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Table 4

Frequencies and Percentages for Financial Distress


Financial distress

Under 1.0 20 36.36%

1.1-2.0 19 34.54%

2.1-3.0 8 14.55%

Over 3.0 8 14.55%

Total 55 100.00%

Tax benefits of a U.S. defense company were measured by an income tax credit

range. Reporting the tax benefits showed the majority of the U.S. defense companies (n =

31, 56.36%) had less than $100 million of income tax credits. In addition, 25.45% of

U.S. defense companies (n = 14) were $100 to $500 million income tax credits. The U.S.

defense companies with over $500 million categories of income tax credits were roughly

18% (18.19%). Frequencies and percentages of tax benefits for U.S. defense companies

are presented in Table 5.

126

Table 5

Frequencies and Percentages for Tax Benefits


Tax benefits3

Under 100 31 56.36%

101-500 14 25.45%

501-1,500 4 7.27%

Over 1,500 6 10.92%

Total 55 100.00%

Note. a dollars in million.

Underinvestment problems of a U.S. defense company were measured by R&D

spending, which is a ratio of R&D expenses to net sales or revenues. Reporting the

underinvestment problems showed the majority of the U.S. defense companies (n = 29,

52.73%) had less than 2.0% of R&D spending. The underinvestment problems least

reported were 5.01-8.00% of R&D spending at 7.27% (n = 4). The U.S. defense

companies with 2.01-5.00% (n = 15) and over 8.00% (n = 11) of R&D spending were

27.27% and 12.73%, respectively. Frequencies and percentages of underinvestment

problems for U.S. defense companies are presented in Table 6.

127

Table 6

Frequencies and Percentages for Underinvestment Problems


Underinvestment problems8

Under 2.00 29 52.73%

2.01-5.00 15 27.27%

5.01-8.00 4 7.27%

Over 8.00 7 12.73%

Total 55 100.00%

Note. a units in percentage.

Managerial incentives of a U.S. defense company were measured by presence of

CEO stock shares, which is a ratio of a company's stock shares held by the corporate

executives to total number of stock shares on issues. Reporting the managerial incentives

showed a large number of U.S. defense companies in = 23,41.82%) had under .05% of

presence of CEO stock shares. The U.S. defense companies with .051-.100% (n = 10),

.101-.200% (n = 11), and over .200% (n = 11) of presence of CEO stock shares were

18.18%, 20% and 20%, respectively. Frequencies and percentages of managerial

incentives for U.S. defense companies are presented in Table 7.

128

Table 7

Frequencies and Percentages for Managerial Incentives


Managerial incentives8

Under .05 23 41.82%

.051-.100 10 18.18%

.101-.200 11 20.00%

Over .200 11 20.00%

Total 55 100.00%


Scale economies of a U.S. defense company were measured by firm size, which is

the natural logarithm of a company's book value of total assets. Reporting the scale

economies showed 47.27% of U.S. defense companies (n = 26) were greater than 9.50,

but no more than 10.5. Furthermore, the U.S. defense companies had either under 9.50 of

firm size (n = 12, 21.82%) or 10.51-11.50 (n = 16, 29.09%). The remaining 1.82% of

U.S. defense companies was over 11.50 of firm size (n = 1). Frequencies and

percentages of scale economies for U.S. defense companies are presented in Table 8.

129

Table 8

Frequencies and Percentages for Scale Economies


Scale economies

Under 9.50 12 21.82%

9.51-10.50 26 47.27%

10.51-11.50 16 29.09%

Over 11.50 1 1.82%

Total 55 100.00%

Level of foreign involvement of a U.S. defense company was measured by

foreign sales ratio, which is a ratio of international sales to net sales or revenues.

Reporting the level of foreign involvement showed a large number of U.S. defense

companies (n = 24,43.64%) with less than 20% of foreign sales ratio. Additionally, the

U.S. defense companies had either 20.1-40.0% of foreign sales ratio (n = 11, 20.00%) or

40.1-60.0% (n = 12, 21.82%). The remaining 14.55% of U.S. defense companies were

over 60.0% of foreign sales ratio (n = 8). Frequencies and percentages of level of foreign

involvement for U.S. defense companies are presented in Table 9.

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Table 9

Frequencies and Percentages for Level of Foreign Involvement


Level of foreign involvement8

Under 20.0

20.1-40.0

40.1-60.0

Over 60.0

Total

24

11

12

8

55

43.64%

20.00%

21.81%

14.55%

100.00%


Revenues derived from U.S. government contracts of a U.S. defense company

were measured by sales to U.S. government, which is a ratio of sales to U.S. government

to net sales or revenues. Reporting the revenues derived from U.S. government contracts

showed a majority of U.S. defense companies (52.73%) with less than 40.0% of sales to

U.S. government (n = 29). In addition, the U.S. defense companies had either 40.1-

60.0% of sales to U.S. government (n = 11, 20.00%) or over 80.0% (n = 11, 20.00%).

The lowest revenues derived from U.S. government contracts (n = 4, 7.27%) were the

U.S. defense companies with 60 to 80% of sales to U.S. government. Frequencies and

percentages of revenues derived from U.S. government contracts for U.S. defense

companies are presented in Table 10.

131

Table 10

Frequencies and Percentages for Revenues Derivedfrom U.S. Government Contracts


Revenues from U.S. government contracts8

Under 40.0

40.1-60.0

60.1-80.0

Over 80.0

Total

29

11

4

11

55

52.73%

20.00%

7.27%

20.00%

100.00%

Note, units in percentage.

As shown in Table 11, descriptive statistics were calculated to report the mean

values and standard deviations among the sample of 55 U.S. defense companies for each

of organizational risk attributes. The average financial distress, as measured with debt

ratio, was 2.28, SD = 3.6. The average tax benefits, as measured with income tax credit

range, were $522.81 million, SD = $1,295.43 million. The average underinvestment

problems, as measured with R&D spending, were 3.46%, SD = 4.61%. The average

managerial incentives, as measured with presence of CEO stock shares, were .15%, SD =

.20%. The average scale economies, as measured with firm size, was 10.08, SD = .79.

The average level of foreign involvement, as measured with foreign sale ratio, was

30.20%, SD = 24.08%. The average revenues derived from U.S. government contracts,

as measured with sales to U.S. government, were 39.11%, SD = 33.84%. The average

132

corporate hedging in foreign exchange and currency risk management, as measured with

notional value of derivatives, was $1,012.85 million, SD = $1,850.99 million.

Table 11

Descriptive Statistics of the Risk Attributes of U.S. Defense Companies and Corporate

Hedging in Foreign Exchange and Currency Risk Management Markets

Variable M SD

The Risk Attributes of U.S. Defense Companies

Financial distress 2.28 3.6

Tax benefits8 522.81 1,295.43

Underinvestment problems'5 3.46 4.61

Managerial incentives'3 .15 .20

Scale economies 10.08 .79

Level of foreign involvementb 30.20 24.08

Revenues derived from U.S. government contracts11 39.11 33.84

Corporate Hedging

Notional value of derivative instruments8 1,012.85 1,850.99

Note. M— mean; SD = standard deviation.

8 dollars in million. b units in percentage.

Finally, in order to detect an outlier in sample data sets and determine if any cases

should not have been included in the analysis, a standard Z score was computed for the

variables in the study (Weiers, 2002). Since the sample size of the study is less than 80, a

criterion for identification of an outlier for a standard Z score is less than -2.5 or greater

133

than +2.5 (Weiers, 2002). The calculated Z scores of the variables were between -2.1 to

+2.1 thereby confirming that none of the variables had outliers in the analyzed data sets

for the study.

To address the research questions and related hypotheses, seven sets of hypothesis

testing using bivariate linear regression were implemented in the study. Prior to

hypothesis tests associated with each research question, assumptions of underlying

bivariate linear regression were validated. A criterion alpha level of .05 was employed

for all hypothesis tests in the study.

Evaluating the assumptions of underlying bivariate linear regression. Two

sets of the validation of assumptions were performed. To evaluate the linearity,

normality, and equal variance assumptions of underlying bivariate linear regression, the

first set of assumption validations was performed by inspecting visually the residual plots

and normal probability plots of the residuals. To access linearity and equal variance, the

residuals were plotted against each of the seven independent variables for the study (see

Appendix D, Figures D1 through D7). Although scatter occurred in the residual plots, no

relationship between the residuals and each independent variable was evident. The

residuals were randomly and equally distributed relatively above and below -500 for the

differing values of the independent variable. As such, the linearity assumption of

underlying bivariate linear regression was satisfied. Furthermore, no major differences in

the variability of the residuals for different values of each independent variable were

present. The patterns of figures in Appendix D indicated no substantial

heteroscedasticity and potential violation of the equal variance assumption of underlying

134

bivariate linear regression. Therefore, the equal variance assumption of underlying

bivariate linear regression was satisfied.

Normal probability plots of residuals were generated for the dependent variable

on the seven independent variables for hypothesis tests (see Appendix E, Figures El

through E7). The data residuals of the dependent variable in relation to the independent

variables were not distributed normally. The patterns of the figures indicated the data

sampled during the study were skewed. However, the sample of the study was small; to

test the normality would be difficult (Weiers, 2002; Wuensch, 2006). Due to the

robustness of regression analysis with respect to the assumption of normality (Weiers,

2002), the departures from the normality assumption in the sample data of U.S. defense

companies should not be the cause for concern.

To assess the assumption of independence of errors for the bivariate linear

regression, the second set of the validation of assumptions was to calculate the Durbin-

Watson statistic, d. At the 0.05 level of significance, the calculated Durbin-Watson

statistics of independent variables for the study had a value between 1.60 and 2.20 (see

Table 12). Based upon decision zones defined in Table 2, no evidence of

autocorrelations among residuals for the independent variables was present. Therefore,

the assumption of independence of errors for the study was satisfied.

Overall, the assumptions of linearity, equal variance, and independence of errors

were satisfied. The assumption of normality was not to be seriously violated. The use of

bivariate linear regression was appropriate for the study.

135

Table 12

The Calculated Value of Durbin-Watson Statistic (d) for Independent Variables in the

Analyzed Data Sets

Independent variable Calculated d

Financial distress 1.6210

Tax benefits 2.1582

Underinvestment problems 1.6882

Managerial incentives 1.6216

Scale economies 1.6687

Level of foreign involvement 1.6653

Revenues derived from U.S. government contracts 1.6648

Correlational analyses. As described in Chapter 3, to assess the relationship

between the risk attributes of U.S. defense companies (X,) and corporate hedging in

foreign exchange and currency risk management markets (Y,), a bivariate linear

regression was defined as:

Y, = A, + B, Xt + £,

For the study, correlational analyses using the bivariate linear regression were performed

on the seven independent and one dependent variables: (a) X] = financial distress, (b) X2

= tax benefits, (c) X3 = under-investment problems, (d) X4 = managerial incentives, (e) X5

= scale economies, (f) Xs = level of foreign involvement, (g) X7 = revenues derived from

136

U.S. government contracts, and (h) Yt = corporate hedging in foreign exchange and

currency risk management markets for the rth U.S. defense company-specific risk

attribute. These constructs were operationalized according to the description of

operational definition of variables in Chapter 3. A Mest was performed to determine the

existence of a significant linear relationship between each U.S. defense company-specific

risk attribute and corporate hedging. The research questions and the corresponding null

and alternative hypotheses are restated. The results of the hypothesis tests are presented

as organized by research questions.

Financial distress. The purpose of the first research question was to investigate

the possible relationship between financial distress and corporate hedging in U.S. defense

industry. The research question and corresponding hypotheses are presented as follows.

Ql. To what extent, if any, is financial distress related to corporate hedging in


Hlo. Financial distress, as measured with debt ratio, is not correlated to corporate



HI,. Financial distress, as measured with debt ratio, is correlated to corporate



The research instrument defined for hypothesis 1 as related to financial distress

(X j ) was debt ratio. As shown in Table 13, the sign of the regression coefficient (Bj) was

positive. As such, the relationship between financial distress and corporate hedging was

137

positive. Furthermore, financial distress accounted for 3% (R 2 = .03) of the variance in

corporate hedging.

For a two-tail test at the .05 level with n- 2 = 53 degrees of freedom, the critical

values are t — -2.006 and t = +2.006. The calculated test statistic t was between the

critical values. The p value of .24 was greater than .05. The results of the bivariate linear

regression analysis for hypothesis 1, 53) =1.18, p > .05, indicated that financial

distress was not statistically significant and positively correlated with corporate hedging

in foreign exchange and currency risk management markets for U.S. defense companies.

Therefore, the null hypothesis (Hlo) was not rejected. The alternative hypothesis (Hla)

was not supported. Results of testing the significance of the linear relationship between

financial distress and corporate hedging are shown in Table 13.

Table 13

Results of Testing the Significance of the Linear Relationship between Financial Distress

and Corporate Hedging (n = 55)

Variable B SEB t P R2 R

X, 82.29 69.69 1.18 .24 .03 .16

Note. X] = financial distress. SE = standard error. * p < .05.

Tax benefits. The purpose of the second research question was to investigate if

tax benefits relate to corporate hedging for U.S. defense companies. The research

question and corresponding hypotheses are presented as follows.

Q2. To what extent, if any, are tax benefits related to corporate hedging in


138

H2o. Tax benefits, as measured with income tax credit range, are not correlated to



H2». Tax benefits, as measured with income tax credit range, are correlated to



The research instrument defined for hypothesis 2 as related to tax benefits (Xj )

was income tax credit range. As shown in Table 14, the sign of the regression coefficient

(JBi) was positive. As such, the relationship between tax benefits and corporate hedging

was positive. Additionally, tax benefits explained 45% (R2 = .45) of the variance in

corporate hedging.

Table 14

Results of Testing the Significance of the Linear Relationship between Tax Benefits and

Corporate Hedging (n = 55)


*2 .96 .14 6.64* .00 .45 .67

Note. X2 = tax benefits. SE = standard error. * p< .05.


values are t = -2.006 and t = +2.006. The calculated test statistic t was within the range

of the critical values. The p value of .00 was less than .05. The results of the bivariate

linear regression analysis for hypothesis 2, /(53) = 6.64, p < .05, demonstrated a

statistically significant and positive relationship between tax benefits and corporate

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companies. Therefore, the null hypothesis (H2o) was rejected. The alternative

hypothesis (H2a) was supported. Results of testing the significance of the linear

relationship between tax benefits and corporate hedging are shown in Table 14.

Underinvestment problems. The purpose of the third research question was to

investigate whether the relationship between underinvestment problems and corporate

hedging for U.S. defense companies exists. The research question and corresponding

hypotheses are presented as follows.

Q3. To what extent, if any, are underinvestment problems related to corporate


companies?

H3o- Underinvestment problems, as measured with R&D spending, are not



H3a. Underinvestment problems, as measured with R&D spending, are correlated



The research instrument defined for hypothesis 3 as related to underinvestment

problems (X3) was R&D spending. As shown in Table 15, the sign of the regression

coefficient (B3) was positive. As such, the relationship between underinvestment

problems and corporate hedging was positive. Furthermore, underinvestment problems

accounted for 10% (R2 = .10) of the variance in corporate hedging.

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values are t = -2.006 and t = +2.006. The calculated test statistic t was outside the critical

values. The p value of .02 was less than .05. The results of the bivariate linear regression

analysis for hypothesis 3, r(53) = 2.44, p < .05, indicated a positive relationship between

underinvestment problems and corporate hedging in foreign exchange and currency risk

management markets for U.S. defense companies. Therefore, the null hypothesis (H3o)

was rejected. The alternative hypothesis (H3a) was supported. Results of testing the

significance of the linear relationship between underinvestment problems and corporate

hedging are shown in Table 15.

Table 15

Results of Testing the Significance of the Linear Relationship between Underinvestment

Problems and Corporate Hedging (n = 55)


x3 127.66 52.33 2.24* .02 .10 .32

Note. Xj = underinvestment problems. SE = standard error. * p< .05.

Managerial incentives. The purpose of the fourth research question was to

investigate if managerial incentives and corporate hedging are related in the U.S. defense

industry. The research question and corresponding hypotheses are presented as follows.

Q4. To what extent, if any, are managerial incentives related to corporate


companies?

141

H4o. Managerial incentives, as measured with presence of corporate executives'



defense companies.

H4„. Managerial incentives, as measured with presence of corporate executives'

stock shares, are correlated to corporate hedging in foreign exchange and currency risk

management markets, as measured with notional value of derivatives, for U.S. defense

companies.

The research instrument defined for hypothesis 4 as related to managerial

incentives (X4) was presence of CEO stock shares. As shown in Table 16, the sign of the

regression coefficient (B4) was negative. As such, the relationship between managerial

incentives and corporate hedging was negative. Additionally, managerial incentives

explained 7% (R2 = .07) of the variance in corporate hedging.

Table 16

Results of Testing the Significance of the Linear Relationship between Managerial

Incentives and Corporate Hedging (n = 55)

Variable B SEB T P R2 R

-2398.87 1247.17 -1.92 .06 .07 -.26

Note. X4 = managerial incentives. SE = standard error. * p < .05.


values are t = -2.006 and t = +2.006. The calculated test statistic t was between the

critical values. The p value of .06 was greater than .05. The results of the bivariate linear

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regression analysis for hypothesis 4, r(53) = -1.92, p > .05, indicated managerial

incentives were not statistically significant and negatively correlated with corporate


companies. Therefore, the null hypothesis (H4o) was not rejected. The alternative

hypothesis (H4a) was not supported. Results of testing the significance of the linear

relationship between managerial incentives and corporate hedging are shown in Table 16.

Scale economies. The purpose of the fifth research question was to investigate

the possible relationship between scale economies and corporate hedging for U.S.

defense companies. The research question and corresponding hypotheses are presented

as follows.

Q5. To what extent, if any, are scale economies related to corporate hedging in


H5o. Scale economies, as measured with firm size, are not correlated to corporate



H5a. Scale economies, as measured with firm size, are correlated to corporate



The research instrument defined for hypothesis 5 as related to scale economies

(Xs) was firm size. As shown in Table 17, the sign of the regression coefficient (Bi) was

positive. As such, the relationship between scale economies and corporate hedging was

positive. In addition, the result in the correlation analysis of the study indicated scale

economies accounted for 28% (R2 = .28) of the variance in corporate hedging.

143

For a two-tail test at the .05 level with n - 2 = 53 degrees of freedom, the critical

values are t = -2.006 and t = +2.006. The calculated test statistic t was outside the critical

values. The p value of .00 was less than .05. The results of the bivariate linear regression

analysis for hypothesis 5, 53) = 4.54, p < .05, concluded a statistically significant and

positive relationship between scale economies and corporate hedging in foreign exchange

and currency risk management markets for U.S. defense companies. Therefore, the null

hypothesis (H5o) was rejected. The alternative hypothesis (H5a) was supported. Results

of testing the significance of the linear relationship between scale economies and

corporate hedging are shown in Table 17.

Table 17

Results of Testing the Significance of the Linear Relationship between Scale Economics

and Corporate Hedging (n = 55)


1241.44 273.31 4.45* .00 .28 .53

Note. Xs = scale economies. SE = standard error. * p< .05.

Level of foreign involvement. The purpose of the sixth research question was to

investigate whether level of foreign involvement relates to corporate hedging in U.S.

defense industry. The research question and corresponding hypotheses are presented as

follows.

Q6. To what extent, if any, is level of foreign involvement related to corporate


companies?

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H60. Level of foreign involvement, as measured with foreign sale ratio, is not



H6». Level of foreign involvement, as measured with foreign sale ratio, is



The research instrument defined for hypothesis 6 as related to level of foreign

involvement (Xg) was foreign sales ratio. As shown in Table 18, the sign of the

regression coefficient (Bg) was positive. As such, the relationship between level of

foreign involvement and corporate hedging was positive. In addition, level of foreign

involvement accounted for 4% (R2 = .04) of the variance in corporate hedging.

Table 18

Results of Testing the Significance of the Linear Relationship between Level of Foreign

Involvement and Corporate Hedging (n = 55)


x6 15.02 10.35 1.45 .15 .04 .20

Note. X(, = level of foreign involvement. SE - standard error. * p< .05.


values are t = -2.006 and t = +2.006. The calculated test statistic t was between the

critical values. The p value of. 15 was greater than .05. The results of the bivariate linear

regression analysis for hypothesis 6, /(53) = 1.45, p > .05, showed that level of foreign

involvement was not statistically significant and positively correlated with corporate

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companies. Therefore, the null hypothesis (H6o) was not rejected. The alternative

hypothesis (H6a) was not supported. Results of testing the significance of the linear

relationship between level of foreign involvement and corporate hedging are shown in

Table 18.

Revenues derived from U.S. government contracts. The purpose of the seventh

research question was to investigate if revenues from U.S. government contracts and

corporate hedging are related in U.S. defense industry. The research question and

corresponding hypotheses are presented as follows.

Q7. To what extent, if any, are revenues from U.S. government contracts related

to corporate hedging in foreign exchange and currency risk management markets for U.S.

defense companies?

H7o. Revenues derived from U.S. government contracts, as measured with sales

to U.S. government, are not correlated to corporate hedging in foreign exchange and



H7a. Revenues derived from U.S. government contracts, as measured with sales

to U.S. government, are correlated to corporate hedging in foreign exchange and currency


defense companies.

The research instrument defined for hypothesis 7 as related to revenues derived

from U.S. government contracts (A» was sales to U.S. government. As shown in Table

19, the sign of the regression coefficient {Bj) was negative. As such, the relationship

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between revenues derived from U.S. government contracts and corporate hedging was

negative. Furthermore, the result of the study showed revenues derived from U.S.

government contracts explained 9% (R2 = .09) of the variance in corporate hedging.


values are t = -2.006 and t = +2.006. The calculated test statistic t was not within the

range of the critical values. The p value of .02 was less than .05. The results of the

bivariate linear regression analysis for hypothesis 7, t(53) = -2.39, p < .05, displayed a

negative relationship between revenues derived from U.S. government contracts and

corporate hedging in foreign exchange and currency risk management markets for U.S.

defense companies. Therefore, the null hypothesis (H7o) was rejected. The alternative

hypothesis (H7a) was supported. Results of testing the significance of the linear

relationship between revenues derived from U.S. government contracts and corporate

hedging are shown in Table 19.

Table 19

Results of Testing the Significance of the Linear Relationship between Revenues Derived

from U.S. Government Contracts and Corporate Hedging (n = 55)


*7 -17.05 7.14 -2.39* .02 .09 -.31

Note. Xy - revenues derived from U.S. government contracts. SE - standard error.

*p< .05.

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Evaluation of Findings

With the level and amount of corporate hedging increasing, U.S. defense

companies are exposed to financial risks resulting in a potential loss of millions of dollars

of profits (The Boeing Company, 2009; Chance & Brooks, 2007; Eiteman et al., 2007;

Gregory, 2010; Lockheed Martin Corporation, 2009; Stulz, 2003). However, whether

organizational risk factors relate to corporate hedging in the U.S. defense industry is not

determined (Artez & Bartram, 2010). To ensure the success of company managers

performing corporate hedging in risk management, a need exists for empirical assessment

regarding the relationship between organizational risk attributes and corporate hedging in

the U.S. defense industry (Artez & Bartram, 2010; Petersen & Thiagarajan, 2000; Stulz,

2003). The results of this study illustrated the need for the assessment of the relationship


exchange and currency risk management markets. According to the research questions

and related hypotheses in the study, the findings of the correlation analyses are discussed

below.

HI. Financial distress, as measured with debt ratio, is not correlated to corporate



The evidence of the correlational analysis in the study indicated financial distress,

as measured by the debt ratio, is not related to corporate hedging in foreign exchange and

currency risk management markets for U.S. defense companies, /(53) = 1.1 S,p > .05. In

theory, the higher leveraged company with debts might have a strong incentive to hedge

(Geczy et al., 1997; Smith & Stulz, 1985). A large number of empirical studies

148

supported financial distress is significantly and positively related to corporate hedging

(Bartram et al., 2009; Berkman, 2002; Berrospide et al., 2007; Dolde & Mishra, 2007;

Graham & Rogers, 2002; Haushalter, 2000; Lei, 2006; Nguyen & Faff, 2003; Reynolds et

al., 2009; Schiozer & Saito, 2009; Spano, 2008). In direct contrast to theoretical and

empirical predictions, the evidence of the study showed financial distress is not

considered to be a significant organizational risk factor related to corporate hedging in

the U.S. defense industry. The lack of association between financial distress and

corporate hedging in this study could be applied in support of the findings by Davies et

al. (2006) and Sprfiic (2007) that financial leverage with debts is not an explanatory

factor for corporate hedging. Therefore, the results of this study, in conjunction with the

conclusions made by Davies et al. (2006) and Sprcic (2007), signify that financial distress

is not significantly related to corporate hedging.

H2. Tax benefits, as measured with income tax credit range, are correlated to



The evidence of the correlational analysis in the study showed tax benefits, as

measured by the income tax credit range, are significantly and positively related to

corporate hedging in foreign exchange and currency risk management markets in the U.S.

defense industry, t(53) = 6.64, p < .05. The positive regression coefficient indicated a

higher level of tax benefits is correlated to a higher level of corporate hedging. The

evidence of the study indicated the U.S. defense companies with $500 million of tax

benefits are more likely to hedge, compared to those with $100 million of tax benefits.

This finding is aligned with other empirical studies indicating a more significant

149

convexity of progressive tax function (tax incentives) will lead to a likelihood of

corporate hedging (Berrospide et al., 2007; Graham & Smith, 1999; Lin & Smith, 2007).

Therefore, the results of this study, in conjunction with the conclusions made by

Berrospide et al. (2007), Graham and Smith (1999), and Lin and Smith (2007), signify

that tax benefits and corporate hedging are significantly and positively related.

H3. Underinvestment problems, as measured with R&D spending, are correlated



The evidence of the correlational analysis in the study indicated underinvestment

problems, as measured by the R&D spending, are positively related to corporate hedging

in foreign exchange and currency risk management markets for U.S. defense companies,

t(53) = 2.44, p < .05. The positive regression coefficient indicated a higher level of

underinvestment problems is correlated with a higher level of corporate hedging. The

evidence of the study showed the U.S. defense companies with 5.0% of underinvestment

problems are more likely to hedge, compared to those with 2.0% of underinvestment

problems. This finding is aligned with the empirical research in the body of literature,

which indicated the companies with high investment opportunities hedge more with

derivative instruments (Carter et al., 2006; Crabb, 2006; Graham & Rogers, 2000; Hsu et

al., 2009; Lei, 2006; Mseddi & Abid, 2010; Sprdic, 2007; Schiozer & Saito, 2009).

Therefore, the results of this study, in conjunction with the conclusions made by Carter et

al. (2006), Crabb (2006), Graham and Rogers (2000), Hsu et al. (2009), Lei (2006),

Mseddi and Abid (2010), Sprdic (2007), and Schiozer and Saito (2009), signify that

underinvestment problems and corporate hedging are significantly and positively related.

150

However, given the relatively small amount of variance noted in the study results (see

Table 15), the significance of the positive relationship between underinvestment

problems and corporate hedging in foreign exchange and currency risk management

markets is considered weak in U.S. defense industry.

H4. Managerial incentives, as measured with presence of corporate executives'



defense companies.

The evidence of the correlational analysis in the study indicated managerial

incentives, as measured by the presence of corporate executives' stock shares, are not


markets for U.S. defense companies, t(53) = -1.92, p > .05. The evidence of the study

showed managerial incentives are not considered to be a significant organizational risk

factor related to corporate hedging in the U.S. defense industry. In contrast to other

empirical research findings, this study did not indicate the empirical support to the

managerial incentives hypothesis developed by Gonzalez et al. (2010), Marsden and

Prevost (2005), Purnanandam (2007), Sprdic (2007), and Supanvanij and Strauss (2010)

who specifically concluded increases in executive's stock shares are significantly related

to corporate hedging. Therefore, the results of this study, in contrast to the conclusions

made by Gonzalez et al. (2010), Marsden and Prevost (2005), Purnanandam (2007),

SprCic (2007), and Supanvanij and Strauss (2010), signify that managerial incentives are

not significantly related to corporate hedging.

151

H5. Scale economies, as measured with firm size, are correlated to corporate



The evidence of the correlational analysis in the study showed scale economies,

as measured by the firm size, and corporate hedging in foreign exchange and currency

risk management markets for the U.S. defense companies are significantly and positively

related, /(53) = 4.54, p < .05. The positive regression coefficient indicated a higher level

of scale economies is correlated with a higher level of corporate hedging. The evidence

of the study indicated the U.S. defense companies with 11.50 of scale economies are

more likely to hedge, compared to those with 9.50 of scale economies. The finding of

this study is consistent with the findings of previous empirical studies supporting the

hypothesis that corporate hedging exhibits scale economies (Berrospide et al., 2007;

Carter et al., 2006; Davies et al., 2006; Guay & Kothari, 2003; Hagelin et al., 2007;

Haushalter, 2000; Hsu et al., 2009; Jong et al., 2006; Judge, 2006; Klimczak, 2008; Lei,

2006; Mseddi & Abid, 2010; Nguyen et al., 2007; Spano, 2008). Therefore, the results

of this study, in conjunction with the conclusions made by researchers in previous

empirical studies (Berrospide et al., 2007; Carter et al., 2006; Davies et al., 2006; Guay &

Kothari, 2003; Hagelin et al., 2007; Haushalter, 2000; Hsu et al., 2009; Jong et al., 2006;

Judge, 2006; Klimczak, 2008; Lei, 2006; Mseddi & Abid, 2010; Nguyen et al., 2007;

Spano, 2008), signify that scale economies and corporate hedging are significantly and

positively related.

152

H6. Level of foreign involvement, as measured with foreign sale ratio, is not



The evidence of the correlational analysis in the study indicated the level of

foreign involvement, as measured by the foreign sales ratio, is not correlated to corporate

hedging in foreign exchange and currency risk management markets for the U.S. defense

companies, t(53) = 1.45, p > .05. The evidence of the study showed the level of foreign

involvement is not considered to be a significant organizational risk factor related to

corporate hedging in the U.S. defense industry. The finding of the present study does not

concur with Jorion's (1990) expectations, who suggested companies with the greater

level of foreign involvement have greater benefits from corporate hedging at the

corporate level. The finding of the study does coincide with the conclusion of Howton

and Perfect (1998) who posited that level of foreign involvement is not a theoretical

determinant in corporate hedging by analyzing 461 U.S. nonfinancial companies.

Therefore, the results of this study in conjunction with the conclusion made by Howton

and Perfect (1998) signify the relationship between the level of foreign involvement and

corporate hedging is not supported.

H7. Revenues derived from U.S. government contracts, as measured with sales to

U.S. government, are correlated to corporate hedging in foreign exchange and currency


defense companies.

The evidence of the correlational analysis in the study revealed revenues derived

from U.S. government contracts, as measured by the sales to U.S. government, are

153

negatively related to corporate hedging in foreign exchange and currency risk

management markets for the U.S. defense companies, /(53) = -2.39, p < .05. The

negative regression coefficient indicated a higher level of revenues derived from U.S.

government contracts is correlated with a lower level of corporate hedging. The evidence

of the study showed the U.S. defense companies with 40.0% of sales to U.S. government

are more likely to hedge, compared to those with 60.0% of sales to U.S. government.

This finding indicated the U.S. defense companies may be pressured to restrict corporate

hedging in order to contend for U.S. government contracts. The finding of the study is

aligned with the conclusions of Rogers (2002) and Schiozer and Saito (2009) indicating

companies in regulated industries are less likely to use financial derivatives for corporate

hedging. However, given the relatively small amount of variance indicated in the study

results (see Table 19), the significance of the inverse relationship between revenues

derived from U.S. government contracts and corporate hedging is considered weak in the

U.S. defense industry.

Summary

This researcher sought to answer research questions regarding the relationship


exchange and currency risk management markets. The preceding chapter presented an

analysis of the data obtained through following the methodology outlined in Chapter 3.

In the study, a random sample of 55 U.S. defense companies from the population was

analyzed by using a correlation analysis method. Descriptive statistics for the sample as

well as information on the risk attributes of U.S. defense companies and corporate

hedging were included. The bivariate linear regression analyses with Mest were

154

performed to assess whether each of the risk attributes of U.S. defense companies

associates with corporate hedging in foreign exchange and currency risk management

markets. A total of seven hypotheses for the study were tested. The findings of the study

supported tax benefits and scale economies were significantly and positively related to


defense industry, and underinvestment problems were positively related to corporate

hedging in foreign exchange and currency risk management markets in the U.S. defense

industry, and revenues derived from U.S. government contracts were negatively related

to corporate hedging in the U.S. defense industry. However, the findings of the study did

not support the hypotheses that financial distress, managerial incentives, and level of

foreign involvement were correlated with corporate hedging in foreign exchange and

currency risk management markets for U.S. defense companies. The current study

expanded on prior empirical investigations that researchers have conducted in applying

corporate hedging theories towards understanding corporate hedging behaviors in risk

management. Consequently, the findings from the study provided the understanding of

the risk attributes of U.S. defense companies in relation to corporate hedging practices in

foreign exchange and currency risk management markets. A number of implications

produced from this study will be discussed in the next chapter.

155

Chapter 5: Implications, Recommendations, and Conclusions

The problem investigated in the study was U.S. defense companies are exposed to

financial risks resulting in a potential loss of millions of dollars of profits as a result of

corporate hedging practices in foreign exchange and currency risk management markets

(The Boeing Company, 2009; Chance & Brooks, 2007; Eiteman et al., 2007; Gregory,

2010; Lockheed Martin Corporation, 2009; Stulz, 2003). The purpose of the study was to

examine the relationship between the risk attributes of U.S. defense companies and

corporate hedging in foreign exchange and currency risk management markets. The

overarching research question for the study was: To what extent, if any, is each of the risk

attributes of U.S. defense companies related to corporate hedging in foreign exchange

and currency risk management markets? A quantitative research methodology was

employed to address the research questions. The research design involved correlation

analyses in hypothesis testing. The results from the present study must be interpreted in

the context of limitations.

The primary limitation of the study was the outcome of the study did not provide

a complete understanding of the complexity and richness of corporate hedging in foreign

exchange and currency risk management markets for U.S. defense companies. The

existing corporate hedging literature suggested a range of factors that might influence

corporate hedging decisions in risk management (Artez & Bartram, 2010; Stulz 2003).

Due to the scope of the study and data availability, only seven organizational risk

attributes related to corporate hedging were selected for the study. Furthermore, the

generalization of the findings was limited by the size and nature of the sample. The

findings of the study only generalized to the population of 194 U.S. defense companies

156

from which the sample was obtained. The generalization of the study to other industries

or foreign defense companies was not warranted.

Another important limitation of the study was related to the study design. A

quantitative correlational method was employed in this study. The correlational design of

the study permitted an analysis of the direction of relationships, but could not be utilized

to address issues of cause and effect (Allen, 2004; Zikmund, 2003). Therefore, any

significant relationship found between the risk attributes of U.S. defense companies and

corporate hedging in foreign exchange and currency risk management markets in the

study cannot be characterized as a causal relationship.

Despite the limitations, the researcher strictly adhered to NCU's IRB guidelines.

Approval to conduct data collection for the present study was obtained from the IRB

prior to the data collection. See Appendix F for the approval letter.

In this chapter, the implications of the study are provided, including conclusions

for each finding in relation to previous empirical studies. Practical recommendations for

future research regarding the organizational determinants of corporate hedging in the

U.S. defense industry are presented. The current chapter ends with conclusions of the

findings.

Implications

One of the most important issues of corporate hedging decisions in risk

management has been to develop robust, internally consistent, and quantifiable

determinants of corporate hedging (Artez & Baxtram, 2010; Petersen & Thiagarajan,

2000; Stulz, 2003). At the simplest level, corporate hedging is designed to reduce or

even eliminate risk exposures such as the fluctuation of foreign exchange rates (Chance

157

& Brooks, 2007; Stulz, 2003). To understand what rationale companies typically use to

engage in corporate hedging and what the effects of corporate hedging can be, the

imperative consideration of research has been to develop sound corporate hedging

theories (Artez & Bartram, 2010; Stulz, 2003).

The two leading theoretical explanations of corporate hedging, shareholder value

maximization and managerial utility maximization, have been subjected to rigorous

empirical challenges for more than 10 years (Artez & Bartram, 2010). Although the

empirical evidence is inconclusive, the theoretical explanations of corporate hedging

remain significant because, in the theories, corporate hedging is expressed as a function

of one or more organizational risk attributes that systematically influence all corporate

hedging decisions in risk management (Artez & Bartram, 2010; Stulz, 2003). In

particular, the risk attributes are financial distress (Smith & Stulz, 1985),

underinvestment problems (Froot et al., 1993), tax benefits (Graham & Smith, 1999;

Smith & Stulz, 1985), and managerial incentives (Jensen & Meckling, 1976; Morellec &

Smith, 2007; Shapiro, 2005).

Since corporate hedging theories do not completely explain the determination of

which companies use derivative instruments for hedging (Artez & Bartram, 2010),

researchers have investigated additional factors associated with corporate hedging in risk

management. These additional factors include scale economies (Allayannis & Ofek,

2001; Nance et al., 1993), firm value (Carter et al., 2006; Jin & Jorion, 2006), level of

foreign involvement (Howton & Perfect, 1998; Menon & Viswanathan, 2005), foreign

debt (Judge, 2009; Nguyen & Faff, 2006), asymmetric information (Breeden &

Viswanathan, 1996; DeMarzo & Duffie, 1991), board characteristics (Borokhovich et al.,

158

2004; Prevost, 2005), industry-specific characteristics (Rogers, 2002; Schiozer & Saito,

2009), country-specific characteristics (Lei, 2006; Marsden & Prevost, 2005), and

accounting reporting methods (Sapra, 2002; Supanvanij & Strauss, 2010). Despite the

intense debates about various risk factors associated with corporate hedging at the

organizational level, the findings of the literature are controversial. The actual

organizational determinants for corporate hedging decisions remain unsettled (Artez &

Bartram, 2010; Nguyen & Faff, 2010; Stulz, 2003).

This researcher's intent was to renew the challenge of explaining the determinants

of corporate hedging from the U.S. defense companies' perspective. Specifically, the

purpose of the study was to assess the relationships between the risk attributes of U.S.


management markets. The organizational risk attributes of U.S. defense companies

considered in the study were drawn from literature pertaining to corporate hedging

theories and prior empirical studies. The findings of the study have the potential to be

used to inform and guide company managers in U.S. defense industry in identifying

organizational risk factors that may be related to corporate hedging in risk management.

As a result, efficiency in corporate hedging practices at the organizational level might be

improved (Artez & Bartram, 2010; Stulz, 2003).

The need to assess the relationships between the risk attributes of U.S. defense


markets led to seven research questions and related hypotheses. For the study, evidence

showed four organizational risk attributes are associated with corporate hedging in the

U.S. defense industry: (a) tax benefits, (b) underinvestment problems, (c) scale

159

economies, and (d) revenues derived from U.S. government contracts. No statistically

significant relationship was found in answering research question 1 (financial distress),

research question 4 (managerial incentives), and research question 6 (level of foreign

involvement). The findings and implications related to each research question and

associated hypotheses are described below. Limitations affecting the implications are

discussed when appropriate.

Financial distress. The purpose of research question 1 was to examine the

relationship between financial distress and corporate hedging for U.S. defense

companies. Bivariate linear regression was used to test the hypotheses associated with

this question. The analysis using a /-test demonstrated financial distress did not relate to


defense industry, /(53) = 1.18, p> .05. The evidence of the study indicated that financial

distress is not an important organizational risk factor in relation to corporate hedging in

the U.S. defense industry.

Financial distress can impose significant costs on a company (Andrede & Kaplan,

1998; Korteweg, 2006; Warner, 1977; Weiss, 1990). Companies that face greater risk of

financial distress may benefit from corporate hedging (Artez & Bartram, 2010). The

study results contrasted with the conclusions made by researchers in previous empirical

studies. The previous empirical studies suggested financial distress is significantly and

positively related to corporate hedging (Bartram et al., 2009; Berkman, 2002; Berrospide

et al., 2007; Dolde & Mishra, 2007; Graham & Rogers, 2002; Haushalter, 2000; Lei,

2006; Nguyen & Faff, 2003; Reynolds et al., 2009; Schiozer & Saito, 2009; Spano,

2008). The study results could be applied in support of claims by Davies et al. (2006)

160

and Sprcic (2007) that financial leverage with debts is not an explanatory factor for

corporate hedging. The contradiction might be explained by the differences in

instruments that measured financial distress. The implication of the finding demonstrated

the difficulty of selecting the proper instruments to measure the financial distress.

Further research is needed to understand these instruments in relation to corporate

hedging for the U.S. defense industry.

Tax benefits. The purpose of research question 2 was to examine the relationship

between tax benefits and corporate hedging for U.S. defense companies. Bivariate linear

regression was used to test the hypotheses associated with this question. The analysis

using a /-test demonstrated tax benefits were significantly and positively related to


defense industry, t(53) = 6.64, p < .05. The evidence of the study indicated tax benefits

are an important organizational risk factor in relation to corporate hedging in the U.S.

defense industry.

Tax benefits are one of the key elements in shareholder value maximization

theory used to explain corporate hedging (Graham & Smith, 1999; Smith & Stulz, 1985).

Theorists predicted tax benefits could impact corporate hedging decisions (Graham &

Smith, 1999; Smith & Stulz, 1985). The study results showed support of other empirical

studies that showed higher tax benefits were related to increases in corporate hedging

(Berrospide et al., 2007; Graham & Smith, 1999; Lin & Smith, 2007; Smith & Stulz,

1985). The implication of the significantly positive relationship between tax benefits and

corporate hedging in foreign exchange and currency risk management markets is U.S.

defense companies with higher tax incentives will hedge more in foreign exchange and

161

currency risk management. Given the relatively large amount of variance observed in the

study results (see Table 14), the significance of the positive relationship between tax

benefits and corporate hedging in foreign exchange and currency risk management

markets is reinforced.

Underinvestment problems. The purpose of research question 3 was to examine

the relationship between underinvestment problems and corporate hedging for U.S.

defense companies. Bivariate linear regression was used to test the hypotheses

associated with this question. The analysis using a /-test demonstrated underinvestment

problems were positively related to corporate hedging in foreign exchange and currency

risk management markets for U.S. defense companies, /(53) = 2.44, p < .05. The

evidence of the study indicated underinvestment problems are an important

organizational risk factor related to corporate hedging in the U.S. defense industry.

Companies with R&D investment opportunities will hedge to reduce the

variability of the internal funds so the companies have adequate internal funds to finance

the R&D investment opportunities (Froot et al., 1993). The theoretical and empirical

analysis indicated a significantly positive relationship between R&D investment

opportunities and corporate hedging (Carter et al., 2006; Crabb, 2006; Graham & Rogers,

2000; Hsu et al., 2009; Lei, 2006; Mseddi & Abid, 2010; Sprcic, 2007; Schiozer & Saito,

2009). This finding is consistent with the conclusions made in previous empirical studies

showing companies with high investment opportunities hedge more (Carter et al., 2006;

Crabb, 2006; Graham & Rogers, 2000; Hsu et al., 2009; Lei, 2006; Mseddi & Abid,

2010; SprCic, 2007; Schiozer & Saito, 2009). The implication of the positive relationship

between underinvestment problems and corporate hedging in foreign exchange and

162

currency risk management markets is U.S. defense companies with higher R&D

investment opportunities will hedge more in foreign exchange and currency risk

management.

However, the practical significance of the positive relationship between

underinvestment problems and corporate hedging is weak, as underinvestment problems

account for a small amount of corporate hedging for U.S. defense companies (see Table

15). The reasons for the low level of shared variances between underinvestment

problems and corporate hedging cannot be identified from the study results. In addition,

the small coefficient of determination denotes that other independent variables

unaccounted for in the study could have a significant influence on the relationship

between underinvestment problems and corporate hedging for U.S. defense companies

(Allen, 2004; Weiers, 2002). Therefore, the implication of the positive relationship

between underinvestment problems and corporate hedging in foreign exchange and

currency risk management markets must be considered carefully with this limitation.

Further research is needed to explore other independent variables that might account for

the level of shared variance between underinvestment problems and corporate hedging in


Managerial incentives. The purpose of research question 4 was to examine the

relationship between managerial incentives and corporate hedging for U.S. defense

companies. Bivariate linear regression was used to test the hypotheses associated with

this question. The analysis using a t-test demonstrated managerial incentives were not

related to corporate hedging in foreign exchange and currency risk management markets

for U.S. defense companies, t(53) = -1.92, p > .05. The evidence of the study indicated

163

that managerial incentives are not an important organizational risk factor in relation to

corporate hedging in the U.S. defense industry.

Company managers may seek to maximize their own self-interest and have

incentives to hedge their private wealth at the expense of the shareholders (Jensen &

Meckling, 1976; Shapiro, 2005; Stulz, 2003). To prevent company managers from

advancing their own private wealth at the expense of the shareholders, managerial

compensation policy must ensure company managers to act in the best interest of

shareholders by maximizing the value of the company (Jensen & Meckling, 1976; Smith

& Stulz, 1985; Tufano, 1996). Company managers and shareholder interests must be

aligned regarding value maximization with an appropriately structured managerial

compensation package including stock and option holdings (Coles et al., 2004; Jensen &

Meckling, 1976; Perry & Zenner, 2000; Smith & Stulz, 1985; Tufano, 1996). The study

results contrasted with the conclusions made by researchers in previous empirical studies.

The study results could not be utilized to support the managerial incentives hypothesis

developed by Gonzalez et al. (2010), Marsden and Prevost (2005), Purnanandam (2007),

Sprcic (2007), and Supanvanij and Strauss (2010), thereby indicating increases in

executive's stock shares are significantly related to corporate hedging. The contradiction

might be explained by the differences in instruments that measure managerial incentives

such as executive option shares in the U.S. defense industry. The implication of the

finding showed the difficulty of selecting the proper instruments to measure the

managerial incentives. Further research is needed to understand the differences of these

instruments in relation to corporate hedging.

164

Scale economies. The purpose of research question 5 was to examine the

relationship between scale economies and corporate hedging for U.S. defense companies.

Bivariate linear regression was used to test the hypotheses associated with this question.

The analysis using a t-test demonstrated scale economies were significantly and

positively related to corporate hedging in foreign exchange and currency risk

management markets in the U.S. defense industry, t(53) = 4.54, p < .05. The evidence of

the study indicated scale economies are an important organizational risk factor in relation

to corporate hedging in the U.S. defense industry.

Theorists suggested scale economies and corporate hedging in risk management

are related (Allayannis & Ofek, 2001; Nance et al., 1993; Smith & Stulz, 1985). Large

companies are more likely to hedge than small companies because the large companies

may have better access to external financing in capital markets (Allayannis & Ofek,

2001). The study results aligned with prior empirical evidence indicating larger

companies are more likely to hedge (Berrospide et al., 2007; Carter et al., 2006; Davies et

al., 2006; Guay & Kothari, 2003; Hagelin et al., 2007; Haushalter, 2000; Hsu et al., 2009;

Jong et al., 2006; Judge, 2006; Klimczak, 2008; Lei, 2006; Mseddi & Abid, 2010;

Nguyen et al., 2007; Spano, 2008). The implication of the significantly positive

relationship between scale economies and corporate hedging in foreign exchange and

currency risk management markets is larger U.S. defense companies will hedge more in

foreign exchange and currency risk management. Given the relatively large amount of

variance identified in the study results (see Table 17), the significance of the positive

relationship between scale economies and corporate hedging in foreign exchange and

currency risk management markets is reinforced.

165

Level of foreign involvement. The purpose of research question 6 was to

examine the relationship between level of foreign involvement and corporate hedging for

U.S. defense companies. Bivariate linear regression was used to test the hypotheses

associated with this question. The analysis using a /-test demonstrated level of foreign

involvement was not related to corporate hedging in foreign exchange and currency risk

management markets for U.S. defense companies in the U.S. defense industry, /(53) =

1.45, p > .05. The evidence of the study indicated level of foreign involvement is not an

important organizational risk factor in relation to corporate hedging in the U.S. defense

industry.

Corporate hedging reduces exposure to foreign exchange and currency risk

(Allayannis & Ofek, 2001; Jorion, 1990). Foreign sales are significantly and positively

correlated with corporate hedging decisions (Allayannis & Ofek, 2001). However, the

study results contradicted with Jorion's (1990) expectations, which indicated companies

with a greater level of foreign involvement have greater benefits from corporate hedging

at the corporate level. The study results can be used in support of the conclusion of

Howton and Perfect (1998), who indicated the relationship between the level of foreign

involvement and corporate hedging was not demonstrated in a random sample of 461

U.S. nonfinancial companies. The contradiction might be explained by the differences in

instruments that measure foreign involvement. The implication of the finding showed the

difficulty of selecting the proper instruments to measure the level of foreign involvement.

Further research is needed to understand these instruments in relation to corporate

hedging activities for the U.S. defense industry.

166

Revenues derived from U.S. government contracts. The purpose of research

question 7 was to examine the relationship between revenues from U.S. government

contracts and corporate hedging for U.S. defense companies. Bivariate linear regression

was used to test the hypotheses associated with this question. The analysis using a /-test

demonstrated revenues derived from U.S. government contracts were negatively related

to corporate hedging in foreign exchange and currency risk management markets in the

U.S. defense industry, /(53) = -2.39, p < .05. The evidence of the study indicated

revenues derived from U.S. government contracts are an important organizational risk

factor in relation to corporate hedging in the U.S. defense industry.

Industry-specific characteristics may influence corporate hedging decisions at the

organizational level (Jorion, 1991). One of the U.S. defense industry-specific

characteristics is to conduct business with the U.S. Government using contract bidding

(Watts, 2008). The study results showed support for the conclusions of other empirical

studies indicating if regulated companies are subjected to increased scrutiny and lower

contracting costs, company managers are less likely to use derivative instruments to

hedge (Rogers, 2002; Schiozer & Saito, 2009). The implication of the negative

relationship between revenues derived from U.S. government contracts and corporate

hedging in foreign exchange and currency risk management markets is as U.S. defense

companies increase their business activities with the U.S. government, U.S. defense

companies will hedge less in foreign exchange and currency risk management markets.

However, the practical significance of the negative relationship between revenues

derived from U.S. government contracts and corporate hedging is weak, as revenues

derived from U.S. government contracts account for a small amount of corporate hedging

167

for U.S. defense companies (see Table 19). The reasons for the low level of shared

variances between revenues derived from U.S. government contracts and corporate

hedging cannot be identified from the study results. In addition, the small coefficient of

determination denotes that other independent variables unaccounted for in the study

could have a significant influence on the relationship between revenues derived from

U.S. government contracts and corporate hedging for U.S. defense companies (Allen,

2004; Weiers, 2002). Therefore, the implication of the negative relationship between

revenues derived from U.S. government contracts and corporate hedging in foreign

exchange and currency risk management markets must be considered carefully within

this limitation. Further research is needed to explore other independent variables that

might account for the level of shared variance between revenues derived from U.S.

government contracts and corporate hedging in the U.S. defense industry.

Recommendations

To establish an analytical framework for guiding the empirical research on

corporate hedging is a difficult task (Artez & Bartram, 2010; Nguyen & Faff, 2010). The

analytical framework developed by this study can be used to provide researchers and

company managers in the U.S defense industry with the ability to investigate the

relationships between U.S. defense company's risk attributes and corporate hedging in

foreign exchange and currency risk management markets. The findings of the study led

to several recommendations for future studies in corporate hedging at the organizational

level. The recommendations resulting from the study findings could be applied to

potentially contribute to the body of knowledge on corporate hedging in foreign exchange

168

and currency risk management markets. These recommendations are based upon the

study results.

Since significant correlations between tax benefits, underinvestment problems,

scale economies, revenues derived from U.S. government contracts, and corporate

hedging in foreign exchange and currency risk management markets were identified,

future research should continue to examine the relationship between these organizational

risk attributes and corporate hedging in foreign exchange and currency risk management

markets. The validation of measurements of constructs plays a critical role in a broader

effort to understand corporate hedging determinants at the organizational level (Nguyen

& Faff, 2010; Stulz, 2003). A potential area for future research is to identify and use

other relevant instruments to replicate the study and assist in obtaining additional

information about the relationship between the risk attributes of U.S. defense companies

and corporate hedging. The more company managers know about the relationship

between the organizational risk factors and corporate hedging, the better they can

improve the effectiveness of decision-making in corporate hedging practices.

From the study, the establishment of a significant correlation between the risk

attributes of U.S. defense companies and corporate hedging was important, but should be

considered preliminary. In the study, only seven organizational determinants of

corporate hedging were selected. However, various risk factors might relate to corporate

hedging decisions in the U.S. defense industry (Artez & Bartram, 2010; Berrospide et al.,

2007; Dolde & Mishra, 2007). To evaluate efficacy more fully, additional research is

needed to expand the study and include a more comprehensive set of organizational risk

factors other than those tested in the study. However, time and resource constraints do

169

not permit such studies to be conducted at this time. Nevertheless, the additional research

would broaden the perspective of what attributes the U.S. defense companies have used

to engage in corporate hedging and which attributes have practical benefits for company

managers in the U.S. defense industry.

Since the researcher did not address the causal relationship between the risk


currency risk management markets, the final recommendation for future studies is to

investigate the influence of key risk attributes of U.S. defense companies on corporate

hedging decisions. The researcher also did not make any assumptions about the

correlations being causal. By ascertaining the impact of the organizational determinants

on corporate hedging, additional conclusions could be made to strengthen the

understanding of corporate hedging practices in risk management for the U.S. defense

industry (Allayannis & Ofek, 2001; Carter et al., 2006; Judge, 2006). The type of

relationship identified in the study could be the foundation for other studies of U.S.

defense companies' corporate hedging in risk management.

Conclusions

Corporate hedging has led to significant advances in corporate risk management

and become an integral part of furthering risk management objectives in the U.S. defense

industry. With the level and amount of corporate hedging increasing, however, U.S.

defense companies are exposed to financial risks resulting in a potential loss of millions

of dollars of profits. To improve the effectiveness of decision-making for corporate


industry, the forefront of advancements in identifying and measuring the organizational

170

determinants of corporate hedging is demanded (Artez & Bartram, 2010; Petersen &

Thiagarajan, 2000; Stulz, 2003). The researcher specifically addressed the assessment of

relationships between the risk attributes of U.S. defense companies and corporate

hedging in foreign exchange and currency risk management markets.

In the study, seven organizational risk factors were used to measure financial and

managerial characteristics for U.S. defense companies. First, evidence in the study

indicated a significantly positive relationship exists between tax benefits and corporate


industry, a positive relationship exists between underinvestment problems and corporate


industry, a significantly positive relationship exists between scale economies and


defense industry, and a negative relationship exists between revenues derived from U.S.

government contracts and corporate hedging in foreign exchange and currency risk

management markets in the U.S. defense industry.

Findings of this study demonstrate the importance of organizational risk attributes

in corporate hedging practices in the U.S. defense industry. Tax benefits,

underinvestment problems, scale economies, and revenues derived from U.S. government

contracts are considered important organizational risk attributes in relation to corporate

hedging practices in the U.S. defense industry. The implication of the significantly

positive relationship between tax benefits and corporate hedging in foreign exchange and

currency risk management markets is high tax benefits are associated with more

corporate hedging. Similarly, the implication of the positive relationship between

171

underinvestment problems and corporate hedging in foreign exchange and currency risk

management markets is corporate hedging may be increased as far as underinvestment

problems are increased. The implication of the significantly positive relationship

between scale economies and corporate hedging in foreign exchange and currency risk

management markets is large scale economies are associated with more corporate

hedging. Finally, the implication of the negative relationship between revenues derived

from U.S. government contracts and corporate hedging in foreign exchange and currency

risk management markets is as revenues derived from U.S. government contracts are

high, less corporate hedging is discovered.

The study results indicated tax benefits and scale economies contributed

significantly to corporate hedging in the U.S. defense industry. However, due to the

relatively small amount of shared variances noted in the study results, the relationships

between underinvestment problems, revenues derived from U.S. government contracts,

and corporate hedging in the U.S. defense industry were weak. Therefore, the

implications of the relationships between underinvestment problems, revenues derived

from U.S. government contracts, and corporate hedging should be interpreted with some

reservation. Additional research is needed to identify other independent variables that

might be applied to explain the level of shared variances between underinvestment

problems, revenues derived from U.S. government contracts, and corporate hedging in


Next, evidence in the study showed financial distress is not related to corporate


industry, managerial incentives are not related to corporate hedging in foreign exchange

172

and currency risk management markets in the U.S. defense industry, and level of foreign

involvement is not related to corporate hedging in foreign exchange and currency risk

management markets in the U.S. defense industry. Therefore, financial distress,

managerial incentives, and level of foreign involvement are not considered important

organizational risk attributes in relation to corporate hedging in the U.S. defense industry.

The implications showed a complete understanding of the differences in instruments to

measure financial distress, managerial incentives, and the level of foreign involvement is

required. Further research is needed to explore these instruments in relation to corporate

hedging activities in the U.S. defense industry.

The empirical evidence obtained in the study will potentially make a substantial

contribution to the body of knowledge regarding the organizational determinants of

corporate hedging in foreign exchange and currency risk management markets. As

important organizational risk attributes, the relationships between financial distress,

underinvestment problems, tax benefits, managerial incentives, scale economies, level of

foreign involvement, and revenues from U.S. government contracts, and corporate

hedging provide ways to understand the organizational determinants of corporate hedging

activities in risk management for U. S defense companies (Artez & Bartram, 2010; Stulz,

2003). These organizational determinants could therefore be used to evaluate the U. S

defense companies' corporate hedging activities. As such, using these organizational

determinants would establish a roadmap for improving the effectiveness of corporate

hedging decisions in the U.S. defense industry (Artez & Bartram, 2010; Stulz, 2003).

Finally, in light of the study results indicating a significant correlation between

tax benefits, underinvestment problems, scale economies, revenues derived from U.S.

173

government contracts, and corporate hedging in foreign exchange and currency risk

management markets, additional empirical research is recommended to enhance the

understanding of corporate hedging practices in the U.S. defense industry. The

recommendations for further studies stem from the findings of the present research,

including to identify and use other relevant instruments to the study to assist in obtaining

additional information about the relationship between corporate hedging and the risk

attributes of U.S. defense companies, assess the relationship between corporate hedging

and the risk attributes of U.S. defense companies other than those tested in the study, and

investigate the influence of key risk attributes of U.S. defense companies on corporate

hedging decisions.

174

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Appendixes

195

Appendix A:

A Random Sampling Procedure

To select a sample of U.S. defense companies from the population, the following

steps were involved. First, the researcher constructed a list of names for 194 U.S.

defense companies into a column in an Excel spreadsheet using Microsoft Excel 2007.

Second, the researcher assigned a random number to each U.S. defense company by

using the RAND() function. That is, enter the RAND() function in the column right next

to the list of names for the 194 U.S. defense companies column, and a series of random

numbers between 0 and 1 would fill in the cells in the random number column. Third,

the researcher sorted both the list of names for 194 U.S. defense companies and the

random number columns by the random numbers generated. Now the list of names for

the 194 U.S. defense companies was arranged in a random order from the lowest to the

highest random number. The first 55 U.S. defense companies in the sorted list would be

taken as the sample of U.S. defense companies for the study.

196

Appendix B:

Determination of Sample Size with a Priori Power Analysis

To determine the necessary sample size of the quantitative correlational study, a

priori power analysis provides an efficient method of controlling statistical power

before the study is actually conducted (Cohen, 1989). Power of a statistical test

refers to the probability of wrongly accepting the null hypothesis when it is actually false

or failure to reject the null hypothesis that is false, which is called Type II error (Allen,

2004; Cohen, 1989; Weiers, 2002; Zikmund, 2003). By convention, power of .80 or

above is usually judged to be adequate (Cohen, 1989). For the study, the desired level of

statistical power was set at .80.

Alpha level (a) determines the probability of obtaining an erroneously significant

result (Allen, 2004; Weiers, 2002; Zikmund, 2003). The alpha level is typically .05 or

.01 (Zikmund, 2003). The accepted Alpha level in previous empirical studies has been

established at the 0.05 level of significance (Bartram et al., 2009; Brown, 2001; Carter et

al., 2006; Gay & Nam, 1998; Graham & Rogers, 2000; Hsu et al., 2009; Judge, 2006;

Nguyen et al., 2007; Reynolds et al., 2009; Spano, 2008). As such, the alpha level was

set as .05 for the study.

Effect size means the degree to which the phenomenon is present in the

population or the degree to which the null hypothesis is false (Cohen, 1989). Cohen

(1989) proposed that a medium effect size off2 = .15 for regression analysis as it would

be able to approximate the average size of observed effects in various fields. Therefore,

the effect size was set at/2 = .15 for the study.

A power analysis using G* Power 3.1 is used to determine the sample size of U.S.

197

defense companies required for the study. To perform a priori estimation, test conditions

must be specified. Within G*Power 3.1 software application, the "Linear multiple

regression: Fixed model, single regression coefficient: procedure was selected because

bivariate linear regression analyses will be performed to test the hypotheses (seven

independent variables and a dependent variable) of this study. After the above input

parameters were specified in G*Power 3.1, the a priori power analysis was performed with

results shown in Figure A1. The relationship between the achieved power and the sample

size for the study is shown in Figure A2. For the study, an effect size of/2 = . 15 requires

a minimum of 55 U.S. defense companies to reach a power of .80. Therefore, the

required sample size of 55 U.S. defense companies was determined in the study.

Central and noncentral distributions | Protocol ot ntmtr imlytw |

critical t - 2.00575

0.3

0.2

0.1

0

Test famiiy

*• ul

Statistical test

Type of power analysis

Input Parameters

Effect size P

si err prob

0.1 S

0.05

Power (1 -p err prob)

Number of predictors

| SO I

1

Output Parameters

NoncentraHty parameter 6

Critical t

Df

Total sample size

Actual power

2.8722813

2.0057460

53

55

0.8050826

Figure Bl. Determination of the required sample size with G* Power software

198

t tests - Linear multiple regression: Fixed model, single regression coefficient Tail(s) = Two, Number of predictors = 1, a err prob = 0.05, Effect size P = 0.15

90

80

a 60

40

0.6 0.65 0.7 0.75 Power (1 -0 err prob)

0.8 0.85 0.9 0.95

Figure B2. The relationship between the achieved power and the sample size. For the study, an effect size off2 = .15 will require a minimum of 55 U.S. defense companies to reach a power of .80.

199

Appendix C:

Permission to Use the Diagram of Evaluating Secondary Data

• 4 CENGAGE Learning*

NEL80N • D U C A T I O N

Rights Administration and Content Reuse

20 Davis Drive, Belmont, California 94002 USA Phone: 800-73(5-2214 or 65CM13-7456 Fax: 800-730-2215 or 650-595-4603 Email: [email protected]

Submit all requests online at vyww.cengage.com/Derniissions.

12/19/2011

Charlie Shao Northcentral University Business 10000 University Drive Prescott Valley, AZ 86314

Permission is granted by Cengage Learning/Nelson Education, or one of their respective subsidiaries, divisions or affiliates (collectively, "Cengage/Nelson") for one-time use to photocopy the material indicated here for educational purposes only during the term specified below. Title: Exploring Marketing Research (with Qualtrics Card) 10E Authors): ZIKMUND/BABIN ISBN: 9780324788440 (0324788444) Publisher: South-Western Year: 2010 Specific material: Diagram for Evaluating secondary data on p. 160. Total pages: 1

For use by Instructor: Steven Munkeby Course title/number: Business Research Term of use: Life of Adoption 2011 Number of users: 1 School/University/Company: Northcentral University

The permission granted in this letter extends only to material that is original to the aforementioned text.

As the requestor, you will need to check all on-page credit references (as well as any other credit / acknowledgement section(s) in the front and/or back of the book) to identify all materials reprinted therein by permission of another source. Please give special consideration to all photos, figures, quotations, and any other material with a credit line attached. You are responsible for obtaining separate permission from the copyright holder for use of all such material.

This credit line must appear on the first page of text selection and with each individual figure or photo:

From ZIKMUND/BABIN. Exploring Marketing Research (with Qualtrics Card), 10E. © 2010 Southwestern, a part of Cengage Learning, Inc. Reproduced by permission, www.cengage.com/permissions

Permission to use Cengage Learning material has been granted per gratis.

Sincerely, Donna Phillips Permissions Associate

Request # 267187

200

Appendix D:

Residual Plots for the Independent Variables

Debt Ratio Residual Plot 8000

7000

6000

5000

« 4000

TZ

•f 3000 Qd ̂ 2000

1000

0

-1000

-2000

• •

•

•

0.00 5.00 10.00 15.00

Debt ratio

20.00 25.00

Figure Dl. Residual plot for financial distress.

Income Tax Credit Range Residual Plot

6000

5000

4000

3000

« 2000

"3 *5 iooo >r.

Oi w 0

-1000

-2000

-3000

•

•

-4000 0.00 1,000.00 2,000.00 3,000.00 4,000.00 5,000.00 6,000.00 7,000.00 8,000.00 9,000.00

Income tax credit range

Figure D2. Residual plot for tax benefits.

R&D Spending Residual Plot 8000

6000

4000

tA "S K 2000 3 ai

0

•2000

• •

-4000 0.00 5.00 1000 15.00 20.00

R&D spending

25.00 30.00

Figure D3. Residual plot for underinvestment problems.

202

Presence of CEO Stock Shares Residual Plot

8000

7000

6000

• •

5000

•n 4000 i •

•

•6 '3 ai

3000

2000 •

•

1000

0

-looo j Si' • # •>

• •

-2000 -2000 : T i 1 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80

Presence of CEO stock shares

Figure D4. Residual plot for managerigal incentives.

Firm Size Residual Plot

7000

6000

5000

4000

3000

g 2000

$ 1000 Oi

0

-1000

-2000

-3000

-4000

• •

X 0.00 2.00 4.00 6.00 8.00 10.00 12.00 14,00

Finn size

Figure D5. Residual plot for scale economies.

203

Foreign Sales Ratio Residual Plot

8000

7000

6000

5000

«a "3

4000

•6 •ra 3000 Ui 1> 0C

2000

1000 ;

o*

-1000

-2000

•

••

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00

Foreign sales ratio(°o)

Figure D6. Residual plot for level of foreign involvement.

Sales to U.S. Government Residual Plot

7000

6000 !

5000 )

4000 j +

"I 3000 | •€? -J} 2000 |

I • « 1000 j •

° u

-1000 i . A.

-2000

y * •' • * •

0.00 20.00 40.00 60.00 80.00

Sales to U.S. government 100.00 120.00

Figure D7. Residual plot for revenues from U.S. government contracts.

204

Appendix E:

Normal Probability Plots of Residuals for the Dependent Variable

Normal Probability Plot: Debt Ratio

8000

7000

6000

5000

« "000

2 •§ 3000 tJi o> 06 2000

1000

0

-1000

-2000

• ••

-2.5 -2 -1.5 -0.5 0 0.5

Z Value 1.5 2.5

Figure El. Normal probability plot of residuals for corporate hedging in foreign exchange and currency risk management on finacial distress.

Normal Probability Plot: Income Tax Credit Range

6000

5000

4000

3000

V, 2000

"3 •§ 1000

<u o£ 0

-1000

-2000

-3000

-4000

• •

-2.5 -1.5 -1 -0.5 0 0.5

Z Value

1 1.5 2 2.5

Figure E2. Normal probability plot of residuals for corporate hedging in foreign exchange and currency risk management on tax benefits.

8000

6000

4000

"3 "§> 2000 •r.

CrZ

-2000

-4000

Normal Probability Plot: R&D Spending

, • •

-2.5 -2 -1.5 -1 -0.5 0 0.5

Z Value 1.5 2 2.5

Figure E3. Normal probability plot of residuals for corporate hedging in foreign exchange and currency risk management on underinvestment problems.

Normal Probability Plot: Presence of CEO's Stock Shares

8000

7000

eooo

5000

4000

•e 3000

s cac 2000

1000

0

-1000

-2000

• • ••

-2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

Z Value

Figure E4. Normal probability plot of residuals for corporate hedging in foreign

exchange and currency risk management on managerigal incentives.

206

7000

5000

5000

4000

3000 V5

*3 2000

<u 1000 Oi 0

-1000

-2000

-3000

-4000 -2.5

Normal Probability Plot: Firm Size

• •

-1.5 -1 -0.5 0 0.S

Z Value 1 1.5 2 2.5

Figure E5. Normal probability plot of residuals for corporate hedging in foreign exchange and currency risk management on scale economies.

Normal Probability Plot. Foreign Sales Ratio

8000

7000

6000

5000

* 4000 ~3 •% 3000 'A "2 C£

2000

1000

0

-1000

-2000

• •

• • •••

2.5 -2 -1.5 -1 -0.5 0 0.5

Z Value 1.5 2.5

Figure E6. Normal probability plot of residuals for corporate hedging in foreign exchange and currency risk management on level of foreign involvement.

207

Normal Probability Plot: Sales to U.S. (jovernment

5000

4000

73 3000 T3 | 2000

•1000

2000 5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5

Z Value

Figure E7. Normal probability plot of residuals for corporate hedging in foreign exchange and currency risk management on revenues from U.S. government contracts.

208

Appendix F:

Approval Letter for the Research Study from the University's IRB

March 19, 2012

Reference: Charlie Shao IRB: 2012-03-19-061

Dear Dr. Steven Munkeby, Dissertation Chair:

On March 17, 2012, Northcentral University approved Charlie's research project entitled, Examining the Relationship between U.S. Defense Firms' Risk Attributes and Corporate Hedging.

IRB approval extends for a period of one year and will expire on March 19, 2013.

Please inform the Northcentral University IRB when the project is completed.

Should the project require an extension, an application for an extension must be submitted within three months of the IRB expiration date.

In the interim, if there are any changes in the research protocol described in the proposal, a written change request describing the proposed changes must be submitted for approval.

Sincerely,

Dr. Chris Cozby IRB Committee Chair Northcentral University

examining the relationship between organizational risk attributes hedging

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