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REVISITING THE EXCESS PROFITABILITY OF U.S. DEFENSE CONTRACTORS FACT OR FICTION? By JOHN S. CANZIO A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF BUSINESS AT THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR IN BUSINESS ADMINISTRATION UNIVERSITY OF FLORIDA 2020

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2 2020 John S. Canzio

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3 ACKNOWLEDGEMENTS I am very grateful to my dissertation co chairmen , Dr. Gary McGill and Dr. Johannes Impink. Their knowledge, guidance, and constant support was instrumental in the completion of my dissertation journey. I would also like to thank the members of my informal panel of defense industry experts. Their counsel and valued debate added depth to my dissertation. Finally, I thank my wife and family for their love and support during my studies. Their encouragement and motivation kept me moving through the many challenges of completing this paper .

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4 TABLE OF CONTENTS ACKNOWLEDGEMENTS ................................ ................................ ................................ ............ 3 LIST OF TABLES ................................ ................................ ................................ .......................... 6 ABSTRACT CHAPTER CHAPTER 1. INTRODUCTION ................................ ................................ ................................ .................... 9 CHAPTER 2. INDUSTRY BACKGROUND & HISTORY ................................ ................................ ..... 13 2.1 Defense Market Overview ................................ ................................ ................................ ......... 14 2.2 Department of Defense ................................ ................................ ................................ .............. 15 2.3 Defense Industrial Base ................................ ................................ ................................ ............. 17 2.4 Hi storical Overview & Industry Formation ................................ ................................ ........ 18 2.5 Defense Industry Maturity Stage ................................ ................................ ............................ 20 2.6 Defense Industry Consolidation & Restructuring ................................ ............................ 21 2.7 Defense Industry Today ................................ ................................ ................................ ............. 23 2.8 DoD Profit Policy ................................ ................................ ................................ ........................... 25 2.9 Key Procurement Regulations & Practices ................................ ................................ ......... 26 CHAPTER 3. LITERATURE REVIEW ................................ ................................ ................................ .... 31 3.1 Research Studies . 33 3 2. Research Studies Today) ................................ ................................ ................................ ................................ ...................... 40 3.3 Cost Shifting Hypothesis Studies ................................ ................................ ............................ 48

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5 CHAPTER 4. HYPOTHESIS DEVELOPMENT ................................ ................................ ..................... 54 CHAPTER 5. METHODS ................................ ................................ ................................ ............................. 58 5.1 Defense Firm Sample Selection ................................ ................................ ............................... 59 5.2 Benchmark Firm Sample Selection ................................ ................................ ........................ 62 5.3 Measurements & Model ................................ ................................ ................................ ............. 63 5.4 Supplemental Analysis Fama French Model ................................ ................................ .... 65 5.5 Supplemental Analysis Accounting Based Profitability Returns ............................. 67 CHAPTER 6. RESULTS & DISCUSSION ................................ ................................ ................................ 69 6.1 Market Based Profitability Results Defense & Benchmark Samples .................... 69 6.2 Supplemental Market Based Profitability Results Defense Firm Sample ........... 71 6.3 Accounting Based Profitability Results Supplementary Data ................................ . 72 6.4 Stock Market Performance Supplementary Data ................................ ........................... 77 CHAPTER 7. LIMITATIONS & ADDITIONAL RESEARCH ................................ ............................ 79 CHAPTER 8. CONCLUSION ................................ ................................ ................................ ..................... 81 REFERENCES ................................ ................................ ................................ ................................ ................ 86 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ........................ 102

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6 LIST OF TABLES & EXHIBIT Exhibit Page 3 1. The Consolidation of US Defense Manufacturing, 1993 2007 ....................... ......... 89 Table 4 1 . Summary Academic Studies ...................................................................................... 90 4 2 . Summary Non Academic Studies .............. .............................................................. . . 9 1 5 1. Defense Firm Baseline Sample Sources and Adjustments ........................................ 9 2 5 2. Defense Firm Sample 77 Pu blic U.S. Firms .............................................................. 9 3 5 3. Defense Firm Sample Distribution and Frequency of SIC Codes ............................. 9 5 6 1. Market Based Returns Full Study Pe riod (1986 2019) ........................................... . 9 6 6 2. Defense Firm Sample Market Based Returns by Firm Size and % Defense............ . 9 7 6 3. Defense Firm Sample Market Based Returns by Interim Period ........................... ... 9 8 6 4. Accounting Based Returns Interim P eriods and Full Period ..................................... 9 9 6 5. Defense Firm Sample Accounting Based R eturns Firm Size and % Defense......... 100 6 6. Stock Market Return Performance.......... ...................................... .............................. 10 1

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7 Abstract of Dissertation Presented to the Graduate School o f the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor in Business Administration REVISITING THE EXCESS PROFITABILITY OF U.S DEFENSE CONTRACTORS FACT OR FICTION ? By John S. Canzio August 2020 Chair: Dr. Gary McGil l Cochair: Dr. Johannes Impink Major: Business Administration This study revisits the long standing debate surrounding the profitability of the United States (U.S . ) defense industry. Prior research on this topic has revealed conflicting and inconsistent results. Several studies have asserted that defense industry pr ofitability is excessive relative to comparable commercial or industrial firms. R esearch on this topic has been limited Th e primary objective i s to examine whether U.S. defense industry profitability is similar to the profitability of comparable non defense commercial or industrial firms over the period 1986 to 2019. Profitability is measured using market based return, which is comprised of the annual change in a fi stock price plus the dividends received . This is the first study of defense industry profitability that utilizes a Fama French model to evaluate abnormal profitability. The study uses a judgmentally selected defense firm sample and a benchmark firm sample is established for comparison purposes.

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8 results show that the market based profitability re turns of the defense firms and comparable non defense commercial or industrial firms are both abnormally high and similar over the total study period. The defense firm results reveal a positive annual profitability alpha of 4.2 4 % and the findings are statistically significant. The test results of the benchmark firm sample of comparable commercial or industrial firms ha d a similar positive alpha return of 4.08% and the findings were also statistically significant . A t test reveal s that the difference between the returns is not statistically different. Additional supplementa r y testing reveal s tha t defense firm profitability improved star t ing in the mid , and that larger sized defense firms and firms that de ri ve higher percentages of their total sales from defense sales are more profitable. This research finds that the market based profitability of the U.S. defense industry has been strong over the past three decades. However, the study results do not find thi s profitability to be excessive when compared to a benchmark group o f similar commercial or industrial firms . The defense industry market based profitability results also indicate that the investment community has viewed the industry as an attractive marke t sector. This is a positive sign for sustaining a critical strategic and economic asset of the U .S.

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9 C HAPTER 1. I NTRODUCTION For several decades, it has been a common assertion that U. S. defense contractors obtain excessive profits on their business with the U.S. government. Those assertions have typically been made by the media, politicians, Congressional committees, and periodically by academics. At the same time, defense contractors, industry experts, industry trade associations, and the U .S. Department of Defense (DoD) have asserted that defense contractors do not earn excessive or adequate profits. The motivations of these assertions vary widely and the bases of the assertions are often questionable. The assertions have often evolved into significant research studies. The primary purpose of this study is to revisit the topic of whether U.S. defense contractors receive excess profits on their business with the U.S Government. Prior studies on this subject have revealed conflicting results. Some studies find that defense contractor profitability is exceedingly high, and other studies find that comparable commercial firms enjoy higher earnings. The various studies suffer from a lack of consistency. They have differed in the profitability measu rements used, breadth of the samples selected, commercial benchmarking firms or indexes used, time periods and lengths used, statistical methodologies used, and in several cases the overall quality of the study. The studies have typically attempted to meas ure excess profitability by comparing the profitability of a sample of U.S. defense contractors with or industrial firms. Profitability studies of the U.S. Defense Industry have been perf ormed for a variety of reasons. Several studies have been performed to ensure that U.S. taxpayer interests are being protected through the effective oversight of government spending and government contractors. Studies have also been performed to measure wh ether the DoD is allowing its contractors to earn equitable returns on their investments in the defense market. It is important that this topic be

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10 accurately and fairly evaluated. The U.S. Defense Budget is the largest discretionary component of the overal l U.S. Budget. The effective and efficient spending of those funds needs to be assured. Additionally, properly incentivizing and maintaining a strong defense industry is critical to the security of our nation. A number of profitability studies of U.S. defe nse contractors have been made over the most comprehensive studies have often been directed and managed by the DoD or by various committees of the U.S. Cong ress. In addition to analyzing profitability, those studies also were performed to identify potential improvements in the defense acquisition system. Studies have also been performed by independent consultants, industry associations, public accounting firm s, and by academics. Academic research o n this topic has been particularly sparse in the past two decades. Wang and San of avoidance of military related research among academics. As a result, studies in this field are quite limited. Second, the already limited studies on this topic stopped in 1990, leaving a blank A prime example of conflicting study results occurred in the mid commissio ned by the DoD, the Defense Financial and Investment Review (DFAIR 1986), and a review of that study commissioned by committees of the U.S. Congress and performed by the U.S. General Accounting Office (GAO). The DoD study concluded that the profitability o f defense contractors and comparable commercial businesses were approximately equivalent. The GAO review strongly disputed those results and concluded that the profitability of defense contractors significantly exceeded commercial firm profitability during the same time periods.

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11 The utilization of different profitability measurement approaches was the primary reason for the widely divergent results. electing a representative sample of companies that represent the U.S. defense industry. This lack of consistency and definition leads to varying results and increases the potential for measurement bias. In this study, defense contractors are defined as lar ge or medium sized firms that are publicly traded, and who supply products and related services that are primarily designed and manufacture d for defense purposes. These products include fighter and transport aircraft, helicopters, aircraft carriers, battle ships, aircraft and helicopter engines, missiles, tanks, surveillance, and space rockets and vehicles. The defense firms that support the manufacture of these products and services are typically the firms that have received the brunt of negative publicity claiming excess profitability, and also the claims of fraud, waste, and abuse . The definition of defense contractors for this study excludes firms who provide commercial or commodity type items or services that are primarily sold in the commercial marketpl ace but are also used by the DoD. Examples of these items include fuel, food, medical services, insurance, and housing. The pricing of those goods and services are primarily determined on a competitive basis utilizing market based pricing. Several past pro fitability studies have broadly included this group of contractors in their defense firm samples and this can distort the specificity and relevance of the results of the research. The selection of the appropriate profitability measurement to use has been debated extensively in the literature. The majority of prior studies utilized accounting based rate of return measures such as return on assets (ROA), return on equity (ROE), or return on sales (ROS) as the primary profitability measures. Accounting based rate of return measures introduce several

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12 problematic measurement issues when evaluating the profitability of a group of companies over an extended time period. This study utilizes market based rate of return (monthly change in stock price and dividends paid) as the primary measure of firm and ind ustry profitability. Market based returns measure profitability and return on investment from the perspective of the stockholder. The U.S. has been the leading military power in the world since the end of World War II. This position has been aided by seve ral factors. A key factor of this advantage has been the innovative talents and skills of the U.S. Defense Industrial Base (DIB). The DIB is a combination of people, technology, firms, and facilities that design, manufacture, and maintain the products and services needed to meet U.S. national security objectives. The DIB has enabled the U.S. military to enjoy a strong technological lead over our enemies. Technology leadership in this area is a critical national asset and it has been a vital part of keeping the peace, especially during the Cold War. However, the world is rapidly changing and the speed of technological change is constantly increasing. It is clear that this critically important advantage over our rivals and allies is decreasing. It is also clea r that the U.S. is highly dependent on a strong DIB to sustain the peace and protect our economy. Scholarly and government research on this topic has been particularly scarce in the last twenty years and prior literature has had conflicting results. This s tudy builds on prior defense industry profitability research, fills the gap created by limited recent research, and extends the literature in several directions. First, it utilizes a more focused definition of defense industry firms. It excludes contractor s who primarily provide commercial or commodity type items to the government. It utilizes a defense contractor selection baseline that includes fifty three leading defense contractors that were previously included in two major DoD directed profitability st udies, Profit 76 Study ( 1977 ) and DFAIR (1986). In addition to th e baseline selection, twenty -

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13 four large and medium sized defense firms that became significant during the study period are included in the defense firm sample. The study follows the profitab ility of those firms over an extended time period (1986 2019). It also compares the profitability of those defense firms with the profitability of a comparable sample of commercial or industrial firms. Secondly, this is the first study of defense industry profitability that uses a Fama French model for determining which . Finally, the study adds to the literature by identifying and assessing factors that affected the profitability of the d efense i ndustry over the study p eriod. During the time period of the study, a multitude of factors and events occurred that influenced the profitability of the defense industry. This study identifies and measure s several key factors that affected this profitability. Prior studies have no t broadly analyzed those factors, especially over a time period of this length. Th e remainder of this paper is organized as follows. The U.S. Defense Industry operates in a highly unique and regulated environment. In order to provide context and understand ing, Chapter Two includes an overview of the DoD and defense industry structure, key procurement laws and regulations, and a concise history of the defense industry. A literature review is esis is included in Chapter Four. Chapter Five provides the empirical methodologies used in the study , and Chapter Six includes the empirical results, supplemental analyses, and a discussion of the results. Chapter Seven notes the limitations of the study and opportunities for additional research. The conclusion of the study is presented in Chapter Eight . CHAPTER 2. INDUSTRY BACKGROUND & HISTORY The U.S. defense industry operates in a complex and unique environment. This chapter provides an overview of the size, structure, spending, and recent history of the DoD and the U.S.

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14 d efense i ndustry. It also provides a summary of the key DoD procurement regulations and practices that affect the pricing and profitability of defense contracts. The chapter also provides context for identifying the key events and factors that have shaped the profitability of firms in the defense industry since the end of World W ar II through the present time. 2.1 Defense Market Overview The U.S defense market does not operate like a free market. The DoD is a monopsony buyer and through its power directs a highly regulated industry. As essentially the only buyer, it dominates and controls the market for the goods and services that it procu res from the defense industry. The DoD establishes the rules and regulations for setting the contractual terms, pricing, and payments for its contracts. It also establishes the characteristics and quality acceptance requirements of the goods and services t hat it purchases. Even when U.S. defense firms wish to sell their products to allies or other foreign government s they must receive approval from the DoD , and usually the U.S. State Department, in order to market and support their products. After years o f industry consolidation and downsizing, the DoD now purchases many of its major systems from a limited number of large prime contractors. Industry consolidation ts after the end of the Cold War. As a result, today there are significant barriers to entry and exit from the industry. Only a small number of significant new U.S. firms have entered the defense industry in the past several decades. The limited new compet ition in the market has often come from foreign suppliers. Due to these circumstances, the defense industry can now be characterized as a monopsony buyer primarily purchasing from an oligopolistic supply base. Watts (2008) notes that the U.S. defense indus try operates in an industry that is heavily reliant on continuous technology improvements. The industry is highly cyclical with dramatic

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15 surges in spending as a result of conflicts in the world or changes in the strategic directions of the U.S. government for dealing with new threats. The industry is also significantly affected during economic downturns that take place in the national and international environment. Defense spending has also been impacted by the shifting of U.S. government spending to other priorities such as reducing budget deficits, increased spending on popular social programs such as Medicare, social security and unemployment, and the payment of higher interest costs necessary to service the national debt. Other factors significantly affe cting the industry include: changes in the technology of military products; increased purchases of U.S. military products by foreign governments; the globalization of the defense industry supply chain; and changes in procurement regulations . The national s ecurity policy that the U.S. has utilized is based on a strategy of deterrence. policy of deterrence requires that we maintain a substantial technological ad vantage in our military systems over our potential enemies. The strategy assumes that our potential adversaries will be deterred by their fear of the overwhelming technological strengths of our weapon systems (Watts 2008) . Our policy also is to use our tec hnological advantages to develop systems that minimize the casualties of our troops. 2.2 Department of Defense The U.S. DoD is one of the largest and most complex organizations in the world. To describe the DoD as complex and bureaucratic is likely a big u nderstatement. The major segments of the DoD include the Office of the Secretary of Defense, the departments of the Army, Navy, and Air Force, and the Joint Chiefs of Staff. Key agencies and other departments that are significantly involved in procurement and contractor oversight activities include the

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16 Office of the Inspector General (IG), Defense Contract Audit Agency (DCAA), Defense Contract Management Agency (DCMA), and the Defense Finance and Accounting Service (DFAS). In 2019, the DoD had approximate ly 2.2 million active duty and ready reserve soldiers. Additionally, the DoD employed approximately 775,000 civilian personnel (Under Secretary of Defense Comptroller 2020). These employment levels have remained relatively constant since approximately one million primarily as a result of the end of the Cold War (Fox 2010). The DoD operates thousands of installations across the world in order to achieve its national sec urity objectives and its security agreements with our allies. To support these requirements the DoD purchases a wide variety of goods and services. It executes the acquisition of these items with detailed rules and regulations that attempt to provide fairn ess and consistency. To achieve its objectives, the DoD spends billions of dollars each year acquiring and approximately $686 billion (Chantrill 2019). This amount excludes t he nearly $200 billion spent annually on healthcare and retirement benefits for U.S. veterans. The overall U.S. spending on defense represented approximately 20% of the total U.S. government budget in 2019 ($4.45 trillion). This percentage has dropped stea dily over the past several decades. As a percentage of GDP, defense spending peaked at 41% of GDP during World War II, ranged between 6% and 10% of the GDP during the Cold War, and has steadily declined to approximately 4% today. This reduction is primaril y the result of moderate increases in defense spending combined with the large growth in GDP and the large programs such as retirement, disability, health care, welfare, education, and debt service to pay

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17 for the increases in the national debt (Chantrill 2019). Despite these reductions the DoD is the largest customer of defense equipment in the world. It is estimated that in 2017 the U.S. spending on national defense exceeded the combined spending of the ne xt seven highest countries. Those seven countries were China, Russia, Saudi Arabia, India, France, United Kingdom, and Japan (Peter G. Peterson Foundation 2018). 2.3 Defense Industrial Base The DIB is an extensive and complex combination of firms, technol ogy, facilities, and talented people which together design and develop, manufacture, and support the wide array of weapon systems the DoD utilizes. The DIB includes both public and private sector firms with the vast majority of work performed by firms in t he private sector. There are approximately fifteen very large contractors who currently dominate the industry. Several of the most recognizable contractors are Lockheed Martin, Northrup Grumman, General Dynamics, Raytheon, and Boeing. However, there are hu ndreds of mid sized firms and thousands of small contractors who also provide products and services to the DoD. Including both direct and indirect employees, it is estimated that approximately 2.8 million private sector employees support the DIB (Deloitte, 2016). The number of employees supporting the DIB leveled off during the prior decade after dropping significantly for many years. However, as a result o f budget cuts in the beginning of this decade, the Deloitte study estimated that employment levels in the private sector dropped by approximately 18% between 2010 and 2014. The DIB firms are divided into three major tiers: prime contractors, large subcontractors, and suppliers of parts and raw materials. The DOD primarily contracts through the prime contra ctors who are responsible for integrating and delivering the end products. The prime contractors typically contract with and manage the supporting group of subcontractors, parts

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18 suppliers, and raw material suppliers. The DoD has identified nine major indus trial sectors which primarily comprise the DIB Aircraft, Electronics, Ground Vehicles, Materials, Munitions & Missiles, Radar & Electronic Warfare, Space, Shipbuilding, and Command & Control. tegories are 1) military personnel, 2) operations & maintenance, 3) procurement, and 4) research, development, test & evaluation (RDT&E). The DIB business volumes are primarily dependent on procurement and RDT&E spending levels. The procurement category i ncludes spending on major combat systems and other supplies and services. Procurement spending is subject to large swings in volume usually as a result of conflicts or changes in strategies such as the Reagan defense build RDT&E inclu des spending on new technologies and the development and testing of new military combat systems. Large swings in the purchase of those items greatly influences industry profitability and the attractivenes s of the industry to investors. 2.4 Historical Overview & Industry Formation The defense industry that exists today had its roots es tablished supporting World War I existing arsenal system and the r apid mobilization of private sector firms. The U.S. arsenal was a system of government owned and operated facilities that supplied the majority of Army ammunition needs and a portion of its aircraft and ships. The private sector firms that were utilized pr imarily produced commercial items and in many instances were reluctant to convert

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19 their production to military needs. At the time, the private sector defense industry was minimal with only a small number of firms producing primarily military products. In both World War I & II the U.S. initially adopted a neutrality position and delayed participating in those conflicts. Subsequently, the U.S. began supplying our allies with critically needed arms and goods and eventually was drawn into the conflicts. In bot h instances the ability to quickly ramp up to meet the requirements of our allies and our military services was impeded by poor prewar planning and preparedness. It was also impeded by the existing strategy of depending on a limited arsenal system and the rapid mobilization and conversion of private sector firms. The ability to supply the needed armaments and supplies was often delayed. In both wars it required nearly two years before the defense industry supply chain became fully operational. A large port ion of the required armaments were produced by private sector firms that needed to convert their existing production lines from commercial goods to military goods. Despite those challenges the U.S. was able to effectively meet the enormous military require ments of its war fighters and its allies. This primarily ad hoc mobilization approach had some amazing results and an instrumental part of how the Allies were successful in both wars. Fortunately, the delay of the U.S. entering World War I & II provided the U.S. with time to ramp up its weapon producing capabilities. Additionally, the manufacturing capabilities of the U.S. were protected by its significant geogr aphic separation from the main areas of conflict. After both World War I & II, the U.S. immediately demobilized and defense spending plummeted. This resulted in private sector firms stopping their production of military equipment and returning to the comme rcial markets that they previously served. These reconversions

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20 resulted in numerous plant closings and significant employment reductions. A standing defense industry was not maintained in the aftermath. This seemingly ad hoc approach was not conducive to t he establishment of a stable or efficient defense industry. When the Korean conflict broke out in 1950 the U.S. was again unprepared to quickly supply its troops with the needed weapons. Additionally, the immediacy of that conflict did not allow the U.S. t he extended time period to ramp up its manufacturing capabilities. Watts ( 2008 ) formation and early growth after World War II (1945 1960); 2) stabilization as a distinct industry duri ng the Cold War (1960 1990); and 3) post Cold War fundamental restructuring (1990 to contain the Soviet Union. Watts notes that the strategy of containment requ ired the scale peace time military force. Investments in research large set of private sector companies supporting the US milit DoD and industry achieved significant technological advances in a wide variety of weapon systems. This technological advantage in weapon systems is still maintained in many areas today. The DoD purchased these new weapon s ystems in such large quantities that by 1960 the defense industry emerged as one of the leadi ng sectors of the U.S. economy (Watts 2008) . 2.5 Defense Industry Maturity Stage Between 1960 and 1990, the DIB matured into a large and relatively strong industry . However, growth rates slowed dramatically from the prior decade and the industry experienced two dramatic surges and subsequent contractions due to the Vietnam War (1968 1973) and the Reagan defense build the DIB enhanced its

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21 technological and manufacturing advantages and developed and produced the most advanced weapon systems in the world. The U.S. military forces remained focused on the Soviet Union as the primary threat. Both countries spent hundreds of billions of dollars on weapons as they competed in a dangerous arms race. This period was also notable for the expansion of the power of the DoD civilian leadership over the procurement of weapon systems and RDT&E spending. Civilian leadership in the DoD b ecame a powerful force in the justification process for new weapon systems. New program budgeting and planning systems were developed to evaluate program performance. Very comprehensive review and monitoring systems were also imposed on industry and these requirements became significant cost burdens for the DoD and industry. This increase in power was accompanied by the shift in power from the services (Army, Navy, Air Force) to the Secretary of Defense within the DoD. The position of the Secretary of Defen se was established in 1947 and was initially more of an advisory position to the services. Due to the volatile sales volumes experienced by the defense industry the attractiveness of the industry to investors declined. At the same time, the attractiveness of the various commercial industries in the private sector steadily improved with significant growth opportunities due to increased international opportunities and technological advances. Additionally, significant increases in U.S. government spending on social programs began to compete with defense spending in the annual budget. The combination of these factors led to a reduction of the significance of the defe nse sector in the U.S. economy. 2.6 Defense Industry Consolidation & Restructuring The end of th defense spending by the U.S. government. This downturn had dramatic effects on the

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22 procurement of weapon systems and had negative effects on a majority of major defense contractors. T his resulted in significant industry consolidation and the exiting of several major contractors from the industry. Defense industry consolidation was particularly dramatic after an capacity by the Clinton administration an d his Secretary of and his Deputy Secretary, William Perry, met with the chief executives of the top fifteen U.S. defense contractors. They stated that the industr y faced a continued downturn in defense spending over the foreseeable future and that the firms needed to reduce their overhead costs dramatically. They stated that they expected that half of the companies at the meeting would not exist in five years (The Economist 1997). This blunt message helped spur a flurry of downsizing and consolidation activity in the industry. It was acknowledged by all participants that the defense industry suffered from significant over capacity. Mergers and acquisition activity r apidly created mega firms and many firms divested their defense businesses to these mega firms and exited the industry. Exhibit A . provides a dramatic overview of the extensive consolidation activity during 1993 2007. These actions created the five major d efense firms that continue to lead the industry today, Boeing, Raytheon, Northrup Grumman, Lockheed Martin, and General Dynamics. Initially the DoD and the Justice Department (DoJ) adopted a hands off approach regarding anti trust regulation and did not in acquisition activity. However, starting in 1997 the DoJ and the Federal Trade Commission (FTC) began to challenge the larger proposed mergers based on concerns of lessening competition in the industry. This rea ched a peak in 1998 when the DoJ challenged the proposed merger of Northrup Grumman and Lockheed Martin. The proposed merger was called off prior to reaching

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23 a scheduled trial. Subsequently, merger activities of major contractors tapered off significantly . However, by then the merger and acquisition activity had changed the landscape of the DIB. many U.S. defense firms began selling their weapon systems to certain foreign allies. These sales were approved and supported by the U.S. government and partially offset the effect of reduced DoD procurements. As part of these sales the foreign countries o ften required that certain elements of the weapon systems were co with the most capable foreign suppliers in those countries. The effect on the DIB was significant with large portions of the subcontractor requirements being off shored. This resulted in the loss of manufacturing capabilities in the DIB and further reduced the business volumes of many U.S. firms. It also resulted in the loss of certain proprietary advantages and in some cases helped create very capable competitors. As expected, investor sentiment of the future of the U.S. defense industry was not strong during this time American companies have chosen to leave the defense industry but no major non defense firms have cho 2.7 Defense Industry Today As a result of the extensive consolidation of the industry over the prior two decades there is significantly less competition today. Often only one or two contractors exist that can provide the critical products and services that the DoD requires. For example, during the 19 number of aircraft manufacturers dropped from eight to three, Navy shipbuilders dropped from

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24 six to three, armored vehicle producers were reduced from three to two, and missile manufacturers dropped fro m thirteen to three (Dombrowski et al. , 2002) . An additional study noted that in 1992 the top four and top ten aerospace contractors accounted for approximately 26% and 50%, respectively, of the contracts going to the top 100 defense contractors. By 2002, those percentages had increased to 50% and 63 %, respectively (Weidenbaum 2003). The remaining large prime contractors now clearly dominate the design, development, and manufacturing of major military systems. The security threat today has now moved past a primary focus on the Soviet Union. Today, the U.S. is required to a focus on a wide variety of new threats that necessitate a change in military strategies and the weapons and systems needed to deal with those threats. The new threats today involve dealing with non state terrorism, cyberterrorism, a rapidly strengthening China, a resurgent Russia, and nuclear threats from Iran and North Korea. The attacks on September 11, 2001, and the accompanying conflicts in the Middle East, created a large surge in U.S. defense spending beginning in 2002. This sur ge in spending continued throughout the decade and peaked during the 2010 time period. Subsequently, spending dropped precipitously through 2016 as war efforts in the Middle East were reduced. During the past decade the DoD has significantly revised its pr ocurement plans and several large military systems were cancelled, reduced, or stretched out. This surge and contraction again created stress for the DIB. The Trump administration has ended the recent defense budget cuts. Defense spending increased signifi cantly starting in 2017 as the military services reple nished their system shortfalls.

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25 2.8 DoD Profit Policy It is commonly viewed that it is the responsibility of the U.S. government to make acquisition laws, regulations, and strategic decisions that susta in the DIB. One of the key factors in that process is the profit policy that the DoD has established. This profit policy is implemented through extensive rules and regulations that have evolved over time. The DoD believes that profit is a basic motivating force of its private industry contractors. Therefore, the primary objectives of the DoD profit policy are to provide its contractors with reasonable profits in order to stimulate efficient contract performance, attract the best capabilities of qualified l arge and small business concerns to government contracts, and maintain a viable industrial base. The contractors that take on more difficult tasks that r equire higher risk; 2) encourage contractors to accept greater responsibility for cost risk through differing contract types; and 3) encourage contractors to make cost effective capital investments for reducing future costs (Federal Acquisition Regulation 15.404 2019 ). the industry. The DoD believes that competition between its contractors fosters innovation and lowers costs. This objective is complemented by socio economic programs that the DOD has implemented with the goal of increasing the use of minority owned firms and small businesses. However, the reality of the situation has been a consolidation of the industry and an exodus of numerous contractors from the DIB over the past twenty to thirty years. Many firms were squeezed out of the industry by extensive merger and acquisition activity. Other firms lost interest due to the excessive regulatory burdens and the low profitability that they believed the industry offers 08) . This has resulted in limited competition and often results in sole

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26 source procurements that primarily utilize cost based pricing. Industry experts believe that cost based pricing results in lower productivity and higher product costs. The reduction in competition also created a must win attitude when the remaining firms competed for new major military systems. Firms bid very aggressively knowing that the winner was likely to receive a sole source position on the new program for many years. The loser wa s often forced to close down that product line or become a supplier or a supporting partner of the winning prime contractor. 2.9 Key Procurement Regulations & Practices The defense industry operates in a highly regulated environment and the DoD procures a wide variety of goods and services. The procedures that the DoD must follow for contracting with its suppliers are much more complex than the practices found in the commercial marketplace. Many of these practices can be attributed to the statutory requirem ents that the government must consider when they enter into transactions with commercial enterprises. Due to its sovereignty role, the government must follow practices that are fair to all potential contractors and represent sound business decisions. These practices must assure that the prices paid by the DoD to its contractors are fair and reasonable, the quality of goods and services received are appropriate, and the government only purchases what it needs (Federal Acquisition Regulation 15.404, 2019). In 1795, the U.S. Government enacted the first law governing the purchase of military goods and services for the Army and Navy. New laws were passed periodically thereafter and with limited exceptions these statutes required competitive bidding. The practice of competitive bidding was implemented to ensure that favoritism, political corruption, and profiteering were reduced in federal contracting. These bidding practices continued until World War II.

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27 Unfortunately , these practices were slow and cumbersome and resulted in shortages and delays of the products and services needed during wartime. In 1942, the War Production Act passed Directive 2. That directive provided significant relief from competitive bidding requirements and required that all contracts be ne gotiated based on established criteria for selecting contractors during the war (McDonnell 1999) . Subsequent to World War II several new procurement statutes were enacted for negotiating contracts with DoD suppliers. In 1947, the Armed Services Procurement Act (ASPR) was implemented. Amongst many requirements, ASPR required that sealed bidding be the preferred procurement method. However, exceptions were allowed under certain circumstances or through specific justifications. ASPR was subsequently revised by the Defense Acquisition Regulation (DAR) in 1978 and then replaced in 1984 by the Federal Acquisition Regulation (FAR) along with its agency supplement the Defense Federal Acquisition Regulation (DFAR). Since the early years of our country allegations of excessive profits by producers of wartime goods have been made. These allegations were made during the Revolutionary War and the U.S. Civil War. During World War I, these allegations again arose and subsequently the Vinson Trammel Act of 1934 (Vinson Tramm el Act) was enacted. The Vinson Trammel Act placed limits on the profits that contractors could earn on their contracts with the U.S. government (12% on military aircraft, and 10% on naval contracts). The issue of profiteering by defense contractors became an issue again during World War II. As a result, Congress passed The Renegotiation Act of 1942 (Renegotiation Act). This act authorized the government to re determine what a fair and reasonable profit was on a contract by contract basis after the delivery of the products. The government was then was able to recover any excess profits from the contractor. The Renegotiation Act was amended several times and

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28 lasted until 1976. It was an exceptionally intrusive and expensive requirement for defense contractors . It was also a one way street. Contracts that experienced low returns were not considered in the profit recovery determinations. The legislation had a lasting negative impact on Defense contracts are subjec t to unique accounting, regulatory, reporting, and oversight requirements that significantly increase the costs of doing business with the DoD and often stretch out the timelines for contract negotiations and performance. The following procurement regulati ons and practices are examples of unique requirements for contracting with the DoD that have no equivalencies in the commercial marketplace: 1) Specific cost accounting rules that are utilized for contract pricing, reporting, and billing. 2) The use of varying c ontract types based on the degree of risk inherent in contract performance. The contract types range from fixed price type contracts to cost reimbursable type contracts. 3) The use of the weighted guidelines methodology for establishing profit/fee objectives for contract negotiations. 4) The submission of cost or pricing data by contractors to support estimated costs used in their contract proposals. 5) Technical and administrative surveillance and auditing by government representatives during the performance of a c ontract for ensuring the quality of the goods and services procured by the DoD and the reasonableness of the prices and payments paid to the contractor. 6) The ability of the government to terminate contract performance whenever it is in the public interest either for convenience of the government or for the fault of the contractor.

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29 7) The ability of the government to unilaterally change the contract after it was signed. 8) A variety of contract financing terms such as progress payments and cost reimbursements duri ng contract performance. These payments are a significant differentiator when comparing profitability performance between a DoD contractor and a commercial firm. They can have a dramatic effect on asset measurements and therefore ROA calculations. 9) The disallowance of recovery of certain contractor costs in the pricing of government contracts. Examples of these unallowable costs include interest, advertising, public relations, entertainment, lobbying, certain fines & penalties, certain executive compensa tion costs, contributions, goodwill, and certain restructuring costs. The disallowance of interest costs has a significant impact when evaluating the comparability of defense and commercial firm profitability. quisition reforms have been proposed and implemented. These actions are often driven by political motivations because the large defense budget is an attractive target for politicians of both major parties (Fox 2011) . As a result, acquisition reform efforts Additionally, each newly appointed Secretary of Defense often brings his own brand of through 20 09, more than twenty seven major studies of defense acquisition were commissioned by presidents, Congress, secretaries of defense, government agencies, studies and analyses rs typically came up with the same findings and similar recommendations. The motivation of these reform efforts is usually the result of allegations of inefficiencies within the DoD or in the defense industry. Large cost overruns, delays in development pro grams,

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30 or technical failures tend to be the biggest motivations. Other reform efforts also examine wasteful spending by either defense contractors or the DoD. A large number of these reform initiatives placed significant pressure on the DIB and often led t o negative effects on industry profitability and cash flow. The constant wave of reform efforts has often been cited as a key factor that makes the defense industry less attractive to both firms contemplating entering the industry and to the investment com munity. Due to the extensive regulations and required processes, large defense contractors are subject to extensive and constant oversight. This oversight includes auditors or inspectors from the following organizations or functions DCAA, DCMA, Inspector G eneral, GAO, IRS, company internal auditors, and certified public accountants. Often the work of these auditors or inspectors takes place simultaneously and greatly burdens the contractors. This costly and often duplicative oversight greatly exceeds the ov ersight encountered by firms in the commercial sector. Accounting Standards (CAS). Nineteen standards were established to achieve uniformity and consistency in the cos t accounting of defense contractors. These cost accounting practices are used in the pricing, billing, and the cost accounting of government contractors. Certain contracts are exempt from these standards and dollar threshold levels exist on contracts cover ed by CAS. A contractor must submit a Disclosure Statement that identifies his cost accounting practices. Any changes to these practices must be disclosed to the government. The original Disclosure Statement, and any revisions to this statement must be au dited and approved by the government. This process is used to inhibit contractors from implementing changes in cost accounting practices adverse to the government . For the purposes of this study, and based on the significant size of the defense firms selected, it can be assumed that all firms selected must

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31 follow these standards. Certain research on the topic of excess profitability focuses on cost shifting as a possible cause. While no system is perfect, the use of CAS, and the accompanying aud iting requirements, makes cost shifting a more difficult practice for large defense contractors. CHAPTER 3. LITERATURE REVIEW The question of whether U.S. defense contractors have obtained excess profits on their business with the U.S. government has been the subject of a number of studies over the past fifty years. Research of this topic was more frequent during the mid However, the frequency of research on this topic has greatly tapered off since that period. Only five aca demic studies of significance were performed in the past twenty years. With the exception of annual surveys performed by industry associations and industry consultants, such as the Aerospace Industries Association, Deloitte, and PricewaterhouseCoopers, non academic research has also become relatively scarce during the past twenty five years. The research on this topic is divided between academic research and non academic research. Non academic research primarily consists of large scale studies commissioned by either the DoD, or by congressional committees of the U.S. Congress. Non academic research also has been performed by industry experts, industry consultants, and by trade organizations. The ability to obtain adequate data directly from defense contracto rs to perform these studies has proven to be very difficult. For a variety of proprietary reasons, defense contractors will not provide this data unless significant leverage is placed on them. In several large scale non academic research studies, the DoD o r the U.S. Congress used its leverage to obtain comprehensive data from industry participants. Unfortunately, due to these constraints academic research on defense industry profitability principally resorted to the use of data available from public domain sources.

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32 Tables 3 1 and 3 2 outline the results of the most significant research performed on defense industry profitability since 1969. The tables summarize the profitability measurements used, time periods analyzed, sample sizes, comparability groups, an d major findings. Table 3 1 summarizes the academic research performed and Table 3 2 summarizes the non academic research performed. Two objectives have been the primary motivations of prior research on defense contractor profitability. The first objective is whether U.S. defense contractors achieve excess profitability at the expense of U.S. taxpayers. A presumption of several studies is that defense contractor profitability is excessive if it exceeds comparable non defense commercial or industrial firm pr ofitability. The second objective is whether defense contractors receive adequate profitability from their business with the DOD. Additional motivations noted include: 1) the effectiveness of of improvements of the DoD acquisition process; 3) identifying issues, such as cost shifting, that may create opportunities that segment; and 4) identifying fa ctors that may lead to differing profitability levels amongst defense contractors. The research on defense industry profitability has frequently exhibited contradictory results that are often caused by the use of differing measurements and methodologies. T he various studies have used different profitability measurements, sample selection criteria, sample sizes, sampling methods, variation in time periods analyzed, and variation in the definition of the variables used. The methodology approach for analyzing defense industry profitability also has varied. Several studies analyzed profitability differences by comparing a selection of defense firms with a selection of comparable non defense commercial or industrial firms. Other studies

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33 analyzed profitability by comparing the segment profitability of firms that have both defense and non defense related business segments. Additionally, several studies that utilized the segment approach, analyzed the use of cost shifting as a method that firms may use for enhancing the overall profitability of a mixed segment company. This literature review is presented in three sections. The first section includes research performed during the industry formation and maturity periods. This period primarily runs from Section Three reviews research that primarily focused on cost shifting as a cause of higher profitability leve ls. 3.1 Research Studies Research in this pe riod was dominated by research sponsored by the DoD or by committees of the U.S. Congress. The primary motivations of those studies we re: 1) to determine the effectiveness of implemented or proposed changes in defense procurement rules and regulations; or 2) to determine if the profitability of defense firms is adequate or excessive and consistent with the regulations. In December 1969, the Logistics Management Institute (LMI) completed a study named Defense Industry Profit Review (LMI, 1969). The study was performed under the direction of the DoD. LMI is a highly respected non profit consulting firm that primarily provides services to th e federal government. LMI has extensive consulting experience in the defense industry. The ticular significance, was

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34 the new DoD profit policy implemented in 1963, which adopted the weighted guidelines methodology for determining profits in negotiated procurements. The LMI study analyzed the profitability of the defense industry over a period of ten years (1958 to 1967). A sample of 40 large and medium sized defense contractors was selected and the selected firms also had significant commercial sales. The sample represented a significant portion of U.S. defense industry sales. The information req uested for the survey was extensive and the contractors participated on a voluntary basis. Firm profitability data was allocated between its defense and commercial segments. Despite the large volume of data requested, response rates were strong with an 86% response rate by the large contractors and a 61% rate by the medium sized contractors. Additionally, profitability data and ratios were compiled for a selection of durable goods industrial firms using Federal Trade Commission (FTC) and Securities and Exch ange Commission (SEC) financial reports (FTC SEC Durable Goods). The primary profitability measurement used was ROA and the secondary metric analyzed was ROS. ROA was determined by dividing pre tax profit by total capital investment (TCI). TCI was equity capital investment plus long term debt. The study results revealed that defense industry profitability (ROA) declined by approximately 25% during the ten year period. Defense segment profitability exceeded both commercial segment profitability and FTC SEC Durable Goods profitability during 1958 to 1961. However, between 1962 and 1967, defense profitability was found to be lower than those two groupings. Defense segment ROS (pre tax profit/sales) was significantly lower than commercial segment and FTC SEC Du rable Goods ROS over all the years surveyed.

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35 The LMI study concluded that the reduction in defense profitability in 1962 to 1967 was largely attributable to the increased competition in the defense market. During that period, the mix of government contract s shifted to a higher percentage of fixed price contracts versus cost reimbursement type contracts. The study notes that the increased competition created a must win or buy in mentality for many defense contractors on contract competitions. Fixed price con tracting was typically used during those competitions. Additionally, high rates of inflation during the period were viewed as another cause of lower profitability for contractors holding fixed price contracts. Shortly after the completion of the LMI study, the GAO was directed to re examine the profitability of defense contractors. The LMI study was heavily criticized during Senate directed by the DoD and defense c ompany participation was voluntary. In March 1971, the Defense Industry Profit Study ( Comptroller General , 1971) was issued. The study period covered the four year period 1966 through 1969. The study included a judgmental sample of 74 large and medium size d DoD contractors. Similar to the LMI study the GAO study obtained data directly from the selected firms. Using this information, the study calculated separate profitability and this required significant judgmental allocations in order to determine the estimated amounts. The GAO study utilized three profitability measurements based on pre tax profit; 1) return on TCI (ROA), 2) ROS, and 3) return on ECI (ROE). The study noted that results of the study were consistent with LMI, 1969 with regards to ROS. For the four year period the ROS on defense sales (4.3%) was considerably lower than ROS on commercial sales

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36 (9.9%). However, the differences between ROE and ROA were considerably lower than the LMI study results revealed. The difference in returns on ECI (ROE) was approximately equal with ROE of 21.1 % on defense sales and 22.9% on commercial sales. Similarly, the difference in ROA was lower at 11.2% for defense sales and 14% for commercial sales. The GAO observed that the primary reason that ECI and TCI rates of return were similar was due to the large amounts of capital provided by the government to contractors during the performance of their contracts. The capital that the government provides includes progress payments for fixed price contracts, cost reimbursement payments for cost type contracts, and certain equipment and faciliti es. This capital significantly reduces the asset requirements of a government contractor and reduces the interest costs that a contractor would incur to finance its capital needs. The Comptroller General , 1971 study recommended that the government revise its profit policy. It recommended the inclusion of an additional factor in the weighted guidelines methodology that recognizes contractor capital requirements in the profit objective of negotiated contracts. The purpose of this change was to motivate contr actor investment in new capital in order to improve production efficiencies and reduce the cost of defense products. profitability. Stigler and Friedland (1971) analy zed profitability of the defense industry using stock market performance as the primary profitability measurement. The study tracked the stock market performance of the leading defense contractors versus all New York Stock Exchange (NYSE) stocks over two different time periods. Stock market performance included the change in stock price plus the reinvestment of dividends. Stigler justified this profitab ility measurement

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37 accounting practices, including the difficulties of segregating assets and income within the The first period (1948 1961) measured t he performance of 54 leading defense contractors versus the NYSE measure. The study revealed that a $1,000 investment in 1948 in the NYSE stocks grew to $6,740 by 1961. Defense stock performance was nearly two times better and the results showed that inves ting $1,000 in the leading defense contractor shares grew to $12,573. The second period (1958 1968) included a revised grouping of the top 50 defense contractors. The study revealed that a $1,000 investment in 1958 in the NYSE stocks grew to $4,702 versus $3,860 for the top defense contractors. The results for the second period were consistent with the results of the LMI (1969) study but not the GAO (1971) study. Bohi (1973) believed that the contrasting results of the LMI (1969) and GAO (1971) studies were caused by the difficulty in separating and allocating profits and assets between a defense business. Bohi selected a judgmental sample of 36 large defense results for the selected 36 firms were based on firm level profitability and were not allocated between their defense and non defense businesses. The profitability measurement used by Bohi was pre tax income divided by net worth. This measurement is consistent with return on equity (ROE). The profitability resul ts of the defense firm sample were compared with the profit rates of the 500 largest manufacturers as reported by Fortune (Fortune 500) for the period 1960 to 1969. Bohi finds that the profitability between the defense firms and the Fortune 500 was approxi mately equal over the ten year period. Those results are consistent with GAO (1969) but not LMI (1969). Additionally, the lack

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38 of declining profitability of the defense firms over Bohi study period contradicts the LMI (1969) study conclusion that the defen se industry was becoming more competitive. In 1977, the DoD completed a study (Profit 76 Study ) to examine the effectiveness of its current profit policy. In particular, a goal of the study was to develop policy revisions that would encourage defense cont ractors to invest in capital that could reduce product costs. Two major shortfalls identified in the existing policy were an overemphasis on cost as a profit determinant, and the lack of consideration of contractor investment as a profit determinant. An im portant secondary objective of the study was to examine the strength of the defense industrial base. LMI was responsible for providing an assessment of the defense industrial base. The study was considerably more comprehensive than prior studies. A major p S tudy was the review of defense contractor profitability and investment levels. The review was for the five year period 1970 through 1974 and data was obtained from 64 large defense contractors with 168 profit centers. Comparisons of profitability comparison was also made to a grouping of durable goods manufacturers. The FTC published a quarterly financial report that tracked the financial performan ce of approximately 5,000 durable goods manufacturers (FTC Durable Goods). This grouping was the main comparability group of the study. To ensure the integrity and accuracy of the study, the public accounting firm of Coopers & Lybrand was designated as the lead firm to aggregate and review the survey data. The selected defense contractors represented approximately 73% of the durable goods volume purchased by the DoD during the period.

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39 The primary profitability measures of the study were ROS and ROA. The ROA calculation included the reduction of progress payments and advances from the asset amounts. Consistent with prior studies, defense contractor profit center ROS was lower than FTC Durable Goods and the commercial profit centers. The five year averages wer e 17.1% for the commercial profit centers, 6.7% for FTC Durable Goods, and 4.7% for defense profit centers. The five year averages for ROA were 17.6% for the commercial profit centers, 10.7% for the FTC Durable Goods, and 13.5% for the defense profit cent ers. Similar to the GAO, 1971 study, the ROA results were significantly impacted by government financing of defense contractors through the use of progress payments on fixed price contracts and cost reimbursement payments on cost type contracts. As result of this study, the government enacted revisions to its profit policy by issuing Defense Procurement Circular (DPC) 76 3 in 1976. The primary changes involved; 1) including apital, and 2) recognizing as an allowable cost in contract negotiations the imputed cost of capital of a Two additional early academic research papers also examined defense industry profitability. Weide nbaum (1968) compared the profitability of six major aerospace defense contractors with six commercial firms of similar size. The study covered two time periods, 1952 to 1955, and 1962 to 1965. Weidenbaum concluded that the defense firms were more profitab le than the commercial firms. However, the small sample sizes and the omission of 1960 and 1961 results were criticized as weaknesses of the study. During 1960 and 1961, the commercial aerospace industry experienced significant losses.

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40 Agapos and Galloway (1970) studied the profitability of the aerospace industry during almost no evidence that aerospace firms in contemporary America are able to reap unusually large or excessive profits from the presence of positive shifts in the demand for military 3 2. Research Studies Today) In 1985, the DoD completed a seventeen month study regarding its contract pricing, financing, and profit policies. The Defense Financial and Investment Review (DFAIR) of public funds and at the same time were sufficient to mainta in the viability of the defense contractor profitability that has been performed. The last major profitability study performed by the government prior to DFAIR was the Pr earlier. The DFAIR study analyzed financial data for the years 1975 through 1983. These results 1974. A judgmental sample of 76 major defense contractors with 194 business segments was utilized in the study (see Exhibit G.). The selected contractors voluntarily participated in the study. To ensure data accuracy and confidentiality, the CPA firm Touche Ross coordinated the data compilati on and analysis process. The data was reviewed for reasonableness but not subject to audit. The DFAIR study utilized a more refined determination of a durable goods manufacturers (DGM) industry grouping. The profitability of the DGM grouping was compared w ith the defense firm sample.

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41 The most controversial aspect of the DFAIR study was the adjustments made to the profitability measurements in order to improve comparability between defense and commercial firms. Excluding those adjustments, DFAIR used a prof itability measurement methodology that ROA and ROS. The major adjustments made to the profitability measures in the DFAIR study primarily revolved around the treatme nt of progress payments and cost reimbursement amounts in the financial ratio calculations. Defense contractors typically receive significant progress payments or cost reimbursement payments from the government to defray the costs of carrying inventory. Th ose payments are interest free and save the contractor from raising capital to pay for them. The procurement regulations do not reimburse contractors for interest costs. In order to improve comparability between defense and commercial firms, the DFAIR stu dy essentially removed this financing from the asset base calculations. Previous studies included this government financing as a contra asset and netted the payments against the inventory balances. DFAIR also created an economic profit amount by making adj ustments to profits and revenues. The economic profit amount included an imputed value amount to account for the disallowance of interest costs. The most significant differences in the profitability calculation methodology between DFAIR and the pr ior studi es are depicted below. DFAIR ROS: Profit Before Interest & Taxes + Imputed Value of Government Financing/ Sales + Imputed Value of Government Financing ROA: Profit Before Interest & Taxes + Imputed Value of Government Financing/ Total Assets Cash (progress payments are not netted against inventory)

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42 Prior Studies ROS: Profit Before Taxes/ Sales ROA: Profit Before Taxes/ Total Assets Cash Progress Payments Using these modified profitability measures the following results were noted in the DFAIR study. The ROS for defense firms was 1% lower than DGM ROS for the 1970 1983 period (7.4% versus 6.4%). Defense firm ROS only exceeded DGM ROS during the 1980 to 1983 period when the commercial sector encountered a recessionary period. The ROA fo r deteriorated greatly during the 1980 to 1983 recessionary period. The DFAIR study concl uded that defense contractors had made significant capital investments since the adoption of DPC 76 3 in 1976. The DFAIR study also concluded that the current DoD policies were protecting taxpayer interests and were enabling the U.S. defense industry to ac hieve equitable returns. DFAIR also recommended that the profitability of the defense industry should be monitored on a periodic basis versus the ad hoc method that was being used. In mid 1985, the U.S. Senate Committee on Governmental Affairs and the U.S. House Committee on Government Operations, requested that the GAO perform a review of the DFAIR report. Members of Congress were skeptical of the results of the DFAIR study for a variety of reasons. The most basic reason for the skepticism was that the rep ort was performed under the direction of the DoD. At the time of the report Congress was divided. Republicans controlled the Senate and Democrats controlled the House of Representatives. President Ronald Reagan was

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43 supporting the rapid build up and moderni zation of the U.S. military to put pressure on the Soviet Union. The high levels of defense spending were adding to the U.S. budget deficits. The GAO performed a comprehensive review of the DFAIR study (GAO 1986). They also performed parallel testing on se veral matters that were done in the DFAIR study. The GAO disagreed or challenged nearly every major finding of the DFAIR report. In particular, the GAO disputed the profitability results of the DFAIR study. The GAO disagreed with the modifications that wer e done to the profitability measurements. They asserted that progress payments should be treated as contra assets and that generally accepted accounting methods (GAAP) and conventional financial analysis methods supported their position. The GAO recalculat ed the DFAIR results using the conventional methodology for treating progress payments as contra assets. The DFAIR study indicated that the profitability of defense contractors was roughly comparable to the profitability of commercial businesses during 19 70 to 1979 and was higher between 1980 and 1983. The GAO review concluded that the profitability of defense contractors was substantially greater than the profitability of commercial businesses during all years . The GAO results indicated that defense contr actor profitability exceeded commercial profitability by 35% during 1970 1979, and by 120 percent during 1980 1983 . The GAO also performed a separate analysis of defense business profitability using a sample of 84 large defense contractors and 228 commerc ial firms. The study used publicly available data from Compustat and analyzed profitability at the firm level. Six profitability equity, and Market return). The GAO study r evealed that defense firm profitability exceeded

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44 commercial business profitability during the 1975 to 1983 time period in all categories except market return. The separate GAO profitability study results revealed defense firm ROS and ROA of 5.7% and 5.8%, respectively. Commercial firm ROS and ROA were 4.0% and 5.1%, respectively. It should be noted that the period 1975 to 1983 was a strong growth period for defense spending. As noted earlier, commercial firms encountered a significant recession during the 1980 to 1983 time period. Considering those facts, it is fairly remarkable that defense and commercial firm profitability was so close. The GAO also disagreed with several other findings of the DFAIR study. The GAO study recommended greater fee reductions in the weighted guideline method than the DFAIR study institute interim or milestone payments for certain contracts. Additionally, the GAO disputed e contractors had been increasing their capital investments over the past ten years. The GAO used a capital intensity measure and observed that while the defense industry had increased its capital spending it was still lagging the spending by commercial fi rms. The GAO also recommended that the government institute a mandatory Profitability Reporting Program for defense contractors. They believed this program would create more accurate and consistent information for monitoring the industry than the existing ad hoc approach. Despite those recommendations, the government never implemented a periodic profit monitoring program of the defense industry. In fact, the government has not performed a review of DFAIR in the past thirty plus years.

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45 In 1992, Robert Higgs issued a research paper (Higgs 1992) that analyzed defense industry profitability using stock market returns as the primary profitability measurement. This was the first comprehensive rev iew of profitability using that measurement approach since Stigler and Friedland (1971). The stock market performance is based on the change in the market price of the stock and the dividends received for a year (MRET). The study covered the period 1970 to 1989, and complemented the Stigler study that examined defense industry stock market performance of the prior two decades. Similar to the approach in the Stigler study, Higgs broke D espite criticizing the usefulness and accuracy of accounting based rates of returns, Higgs also supplemented his study with two accounting based measures of profitability, ROA and ROI. The study analyzed the performance of the top ten and top fifty defense contractors Compustat and only publicly traded U.S. firms were selected. The performance of this sample of defense contractors was compared to the Standard & Poo The study results revealed that defense contractor profitability equals or exceeds the year period. ificantly exceeded the performance of the S&P grouping on the MRET and ROA measures. The ROI measures were approximately equal. For performance significantly exceeded the S&P study results (GAO, 1989), defense firm MRET performance was particularly strong in the

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46 over the twenty year pe riod. The study computed betas of the MRET for 1970 to 1989 and the betas ranged between 1.22 and 1.27. However, the analysis of the higher risk was not deemed statistically significant. A more recent study (Zhong and Gribbin 2009) examined defense industr y profitability through a different perspective. Instead of just comparing the profitability of defense firms and commercial firms, this study investigates which factors led to varying levels of profitability amongst defense contractors. The study covers the period 1984 to 1998. A sample of 11,051 firm year observations was selected using Compustat segment data. All firms selected were U.S. firms and had government sales. The profitability measure used was R&D adjusted ROA (AdROA). This measure is calculat ed as income before extraordinary items and discontinued operations plus R&D expenses, divided by average assets. The researchers believed that this adjustment reduces revenue and expense mismatches that occur during periods of high R&D spending. R egressi on analysis was used to test the hypotheses. The study uses the percentage of effect variable for defense contractor profitability. Three hypothesized factors were selected as moderating variables. Those va riables were: 1) risk of defense business; 2) innovation involved in defense business task: and 3) influence of defense contractor. defense sales are related to a lower AdROA. This suggests that defense sales are less profitable than commercial sales. Also, the results suggest that defense contractor profitability is higher

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47 when they are more innovative, assume higher risks, or are more influential. Rewarding higher risk Wang and San Miguel ( 2012) emphatically asserted the excessive profitability of defense contractors. Wang and San Miguel challenge d the previous methodologies used in defense profitabili ty studies. They particularly disagree with the use of the comparison of profitability against broadly defined indexes. The authors note that the defense industry is comprised of a wide range of industries and profitability is very industry specific. The s tudy claims the use of an innovative method to measure the excessive profitability of the defense industry. Their innovative approach utilizes an industry year size matched measure to evaluate the excessive profitability of the defense industry. The study identifies two factors effecting excessive profitability: 1) defense contractor excessive profitability became more pronounced after the significant industry consolidation activity of 1992; and 2) excessive profitability increases with poorer corporate gov ernance. The study identifies the top 500 defense contractors in 2008. From this group the study identifies 112 publicly traded firms for analysis. The sample selection covers a wide range of industries as measured through SIC codes. Using this contractor selection, the results of 4,099 firm years for the period of 1950 to 2010 were obtained. A review of the firms selected finds that a significant number of the firms provide products or services that clearly are of a commercial and/or commodity nature and w ere not specifically designed for the DoD. Examples include, food, fuel, insurance, facilities, and medical items or services. Wang and San Miguel ( 2012 ) use ROA, return on common equity (ROCE), net income divided by sales (PMR), and EBIT divided by sales (OMR) as the profitability measures. Their findings assert that defense contractors achieve consistently excessive levels of profitability as

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48 measured by ROA, ROCE, and PMR. However, the term excessive appears to be an overly strong term considering the di fferences identified. For example, the study noted mean differences of ROA and PMR at levels of 1% and .45%, respectively. Wang (2014) built on the profitability research of Wang and San Miguel (2012). The the impact of political connections on the the military services. Wang ( 2014 ) uses the empirical results of Wang and San Miguel (2012) that indicated that defense contractors achieve excess profitability. Wang (2014) uses a slightly slimmed down version of the sample from Wang and San Miguel (2012). It trims the sample from 11 2 to 90 firms due to the lack of available information regarding the political connections of a selected tested the ROA results of the revised 2008 sample selection and the re testing revealed that defense c ontractors achieved an excessive ROA of 3% in 2008. The sample used for this study also includes a large number of firms that primarily provide commercial or commodity type products. The primary results of the study revealed that excessive profits are lower for defense contractors with more politically connected board of directors. Additionally, the study finds that DoD contractors are more likely to have politically connected board me mbers and to have higher discretionary expenditures during periods of cost plus contracts. 3.3 Cost Shifting Hypothesis Studies Several studies examined excess profitability by analyzing whether cost shifting between defense segmen

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49 profitability : Lichtenberg (1992), Thomas and Tung (1992), Rogerson (1992), and McGowan and Vendrzyk (2002). A mixed segment firm is a firm that has substantial sales to the DoD and to commercial customers. A m ixed segment firm also may have completely separate defense and non defense business segments. If cost shifting takes place, the ability to analyze segment profitability becomes more complicated. Frequently, firms that sell to defense contractors also sell similar or dissimilar products to commercial customers. A primary assertion of the cost shifting hypothesis is that a firm can shift certain of its overhead costs from its non defense contracts to its defense contracts. Cost shifting can be accomplished t hrough the use of generally accepted cost accounting methods for allocating costs between business segments or between contracts. Cost shifting can also occur between different time periods. The cost shifting hypothesis is based on the assumption that defense contract pricing is more cost sensitive than non defense contracts. The pricing of a majority of defense contracts is based on the actual or estimated costs that are allocable to those contracts. Therefore, higher cost allocations r esult in higher prices on those defense contracts. Alternatively, the pricing of commercial contracts is usually competitively determined and not directly based on cost. If additional overhead costs can be shifted to defense contracts then the profitabilit is recovered through higher prices. This is particularly true when price competition in the defense sector is lower. Additionally, cost allocatio n practices can also be changed over time when the business mix of a firm changes. Rogerson (1992) postulates that defense procurement regulations create incentives for multiple product firms to shift costs and to utilize inefficient production methods. He notes that

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50 costs of the products. Therefore, the pricing of those products are highly cost sensitive. This is particularly the case when firms have cost re imbursable or sole source contracts with the DoD. When the firm also sells commercial type products, the pricing of those products are much less responsive to cost allocations. The differences in cost sensitivity on price provide incentives for a firm to a llocate higher amounts of overhead cost to defense products and away from commercial type products. Rogerson (1992) also notes that defense firms are more likely to allocate certain overhead costs based on direct labor and direct material. Due to those all ocation methods, multiple product firms will undercapitalize the production of products with cost sensitive revenues (defense products) and overcapitalize the production of products with less cost sensitive revenue (commercial products). Similarly, those f irms are also more likely to utilize in house labor to produce their more cost sensitive revenue products (defense products) and use subcontractors for their less cost sensitive revenue products. These allocation methods result in higher cost allocations f or a firms defense products then for a firms commercial products and also creates the In summary, Rogerson (1992) believes that DoD procurement regulations prov ide firms the ability to shift additional overhead costs to their defense business. Subsequently, those increased costs are substantially recovered in the pricing of the defense contracts. At the same time, the costs on commercial sales are reduced and the overall profitability of the firm is increased. Additionally, these incentives increase the opportunity for inefficiencies in the production of defense products. Firms are motivated to produce their defense products with higher levels of direct labor, use less automation, and subcontract their commercial work to

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51 potentially more efficient suppliers. Rogerson includes several models in his research to demonstrate his theories. However, no empirical testing was performed in the study. Thomas and Tung (1992) also examine the ability of defense contractors to shift costs to their cost sensitive revenue defense business. The researchers state that the primary objective of der cost 1983) and used a sample of eighty large defense contractors. The study notes pension costs can be shifted on an inter contract basis and inter time basis. Based on the differences in pension plan funding levels identified in the study, a primary observation of the study is that pension plans are overfunded when a higher proportion of a equently, excess pension plan assets are withdrawn from the pension plan when a higher proportion of employees are working on non profitability is enhanced through the initial recovery of the overfunding of the pension plan in the pricing of its cost sensitive defense contracts and the subsequent withdrawal of this excess funding when the business mix shifts to higher proportions of non defense business. It is also assumed that the firm funding. Despite the varying funding level observations and manipulation opportunities noted, ese hypothesized strategies result in contractors earning abnormal profits by overcharging the Similarly, Lichtenburg (1992) suggests that cost shifting could be responsible for the excess profits of government contractors that his study obse rved. Lichtenburg (1992) performs

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52 an econometric analysis of 9,300 firm industry segments for the period 1983 1989. From this group the study identified approximately 800 firms with reported sales to the U.S. government. Using ROA, the primary findings ind icate that the profit rates of defense contractors are between 68 and 82 percent higher then the profitability of non defense contractors. Further, by grouping study reveals that the profitability of the firms increases significantly as their concentration increases. The quartile profitability rate of the most concentrated defense firms is approximately three times higher than the rate of the remaining quartile g roupings. Using U.S. defense industry employment data from 1940 to 1993, the study also finds that defense firms with the highest concentration levels are significantly less capital intensive. This would tend to indicate that defense contractors potentiall y over utilize labor in their operations. The three studies noted above, Rogerson (1992), Thomas and Tung (1992), and Lichtenberg (1992), all imply that cost shifting is a potential reason for excess defense firm nly one that measures excess profitability of defense contractors. However, that study only covers a relatively short period of time and that period includes a large increase in U.S. defense spending. McGowan and Vendrzyk (2002) revisit this topic a decad e later with an arguably more robust and nuanced research methodology. Compustat segment data for 1984 1989 and 1994 1998 is utilized to generate a sample of 701 segments for the earlier time period and 422 segments for the later time period. The reduction in segments in the later time period is attributed to the significant industry consolidation activity that occurred between the two periods. The 1984 to 1989 time period represents a period of high defense spending and a period of low competition in the d efense industry. During 1994 1998, defense spending was significantly lower and the

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53 industry experienced higher competition. To test the relationship between cost shifting and excess profitability, the study compares relative profitability of three segment groupings during those periods. The segment groupings for the defense firms selected were: segments with only commercial revenues, segments with predominately defense revenues, and mixed segments. If cost shifting was responsible, it would be expected tha t the profitability of the commercial and mixed segments would reveal higher profitability than the defense segments. The primary results of McGowan and Vendryzk (2002) did not confirm the results of prior studies that proposed that excess defense firm pro fitability is attributable to cost shifting. 1989, revealed that defense contractor business segments that receive the predominate percentage of their revenues from government contr acts were more profitable (19.4% ROA) than segments that derived their revenues either from purely commercial sources (12.4% ROA) or were mixed segments (14.1% ROA). During the more competitive time period (1994 1998), the results for the three segment gro upings were approximately equal (12.3%, 12.0%, and 12.3%, respectively). The biggest reduction in profitability between periods was reported in the predominately government segment. McGowan and Vendryzk (2002) attribute this change to the reduction in co government contracts when competition is low is more likely explained by non accounting A recent study by Chen and Gunny (2014), also examined whether cost shifting was responsible for higher profitability by certain government contractors. The primary objective of their study was to determine whether government contractors that obtai n cost plus contracts achieve higher profitability levels and whether those higher levels are due to cost shifting. ROA

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54 was used as the primary profitability measurement. A secondary objective of the study was to determine if profitability levels were lowe r for government contractors with cost plus contracts when government cost accounting standards (CAS) were in effect. Their study was the first research paper that analyzed excess profitability and cost shifting using contract data. Detailed information id entifying which government contractors were awarded cost plus contracts was not available in the public domain until 2004. The period covered by study was 2005 2010 and for the main test a sample of 258 firms and 1,505 firm years was used. Only government contractors that were awarded a cost plus contract in a year of the sample period and only a fixed price contract in a different year of the sample period were included. The contractors selected were also required to be publicly traded U.S. firms. Chen and Gunny (2014) concluded that higher profitability levels (ROA) were associated with cost plus contract activity than with fixed price contract activity. They report evidence that indicates that cost shifting is a factor in the higher profitability levels. They also provide evidence that this excess profitability is reduced when CAS rules apply and when increased monitoring of the contractor by the government is performed. It should be noted that even if the conclusions are accurate, essentially all large an d medium sized defense contractors are subject to CAS rules. They are also subject to extensive oversight by various government auditors. C HAPTER 4 . H YPOTHESIS D EVELOPMENT D efense industry profitability literature reveals varying results over the past sixt y years. The existing literature is clearly conflicted in the results observed. The literature also reveal s inconsistencies in profitability measurements used, representative samples selected, and methodological approaches taken. It is evident that t here approach for evaluating the profitability of the defense industry , or for asserting that it s profits are excessive .

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55 A summary analysis of the selected research studies finds defense firm profitability higher for ten time periods rev iewed, non defense commercial /industrial firm profitability higher for four time periods, and profitability approximately equal fo r five time periods reviewed. An approximation of the study results by decade finds defense firm profitability higher in t he , and non defense c ommercial /industrial firm profitability higher in reduced number of studies after does not allow for such an assessment. Based on t hese varying results, it appears diffi cult to assert that defense contractor profitability is excessive, especially all the time. These varying results are consistent with the peaks and valleys that many other cyclical industries go through. The two basic measure ment approaches used for analyz ing profitability are accounting based rate of returns and stock market based rate of returns. Selecting the best accounting based rate of return method to use is a challenging task especially when comparing profitab ility between different industries or different industry segments. The comparability of th o se measures also becomes more difficult when they are used over extended periods of time or when significant judgmental allocation s of costs, assets , and liabilities are required . Several e xamples of the difficulties encountered when utilizing accounting based rate of return measures are : 1 ) differing accounting practices exist between firms and industries; 2 ) changing accounting rules and disclosure requirements over time ; 3) results are ba sed on historical cost and not on market prices; 4) relying on segment data which varies in methodology and transparency over time; and 5) using judgmental allocations to separate defense and non defense business activity and asset bases. The most comprehensive studies that utilized accoun ting based rates of returns were Study (1977), DFAIR ( 1986 ) , and GAO ( 198 6 ) . Those studies examined relatively

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56 short periods of time , required numerous judgmental allocations, and exhibited conflicting results. T he DFAIR study attempted to im prove comparability by making adjustments to certain profitability and balance sheet measures in order to account for the unique effect s of government financing and pricing . However, the DF AIR methodology was strongly criticized by the GAO for not using GAAP or conventional financ ial analysis methodologies . The DFAIR study w disputing GAAP, it was using a different methodology in an attempt to improve the comparability of the results. Only two studies utilized stock market based rate of return measures as their primary measurement method , Stigler and Friedland (1971), and Higgs (1992). Stock m arket based rate of return measures have seve ral weaknesses especially if used for short periods of time. However, their util ization over long er periods of time tends to normalize the effects of short term periods of volatility or transient events . The studies also varied in the sampling methodologies used for select ing representative defense firm samples and selecting samples of comparable commercial or industrial firms . The breadth of the samples varied with some studies using relatively small samples (Weidenbaum 1968 , Bohi 1973 ), and so me studies using very large samples (Lichtenburg 1992, Zhong and Gribbin 2009, and Wang and San Miguel 2012). The large defense firm samples were particularly broad based and often included a significant number of firms that were producers of products prim arily sold in the commercial marketplace , not products designed for use by the defense industry . There has been limited research on defense contractor profitabil i ty This study extends the literature by examining the profitability of a focused selection of le ading defense contractors over an extensive time period. This extensive period includes periods of

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57 significant industry consolidation and downsizing, defense budge t reductions and surges, combat and terrorism, DoD procurement reforms, and economic recessions and expansions . To extend and add to the literature on defense firm profitability, hypothesis will revisit and update the assessment of defense con tractor profi tability since the mid through the use of market based profitability measures . Consistent with prior literature, this study compares the results of a defense sample with a benchmark sample comprised of a peer group of commercial or industrial firms. T he findings of prior literature ha ve varied on whether defense contractors have achi eved higher or lower profitability then their non defense commercial or industrial peers . Based on those conflict ing results the following null hypothesis is proposed . Hypothesis : During the past thirty four years (1986 201 9 ) , U.S. defense contractor profitability does not differ from the profitability of comparable non defense commercial or industrial firms. Additionally , p rior literature has included l imited an alysi s of the key factors that have impacted defense industry profitability. Several studies have included anecdot al commentary regarding the factors that they believed favorably or unfavorably affected defense or commercial firm profitability during the periods studied . Only t hree studies ( Zhong and Gribbin, 2009, Wang and San Miguel 2012, and Wang, 2014 ) performed empirical testing of certain factors to evaluate their effect on defense industry profitability. Zhong and Gribbin evaluated firm risk taking, innovation, and influence as possible indicators of increased defense firm profitability. Wang and San Miguel researched whether increased industry consolidation activity commencing in 199 3 , or corporate governance practices , a ffected defense firm profitability . Wang, 2014 examined political connections as a possible factor.

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58 hypothesis results , this study analyze s the effect of a defense firm size on its profitability as a percentage of its total sales on its profitability. Additionally, an analysis of the variability of defense firm profitability over five interim time periods within the study period is performed . This sup plemental analysis is performed using market based measurements and accounting based measurements. C HAPTER 5 . M ETHOD S The methodologies used i n prior research on the topic of defense industry profit ability have varied greatly . The most significant issues affecting prior research methodology were: 1) data access i bility ; 2) profitability measurement approach used (accounting based returns versus market based return s ); 3) study period used (length and timing); and 4) development of suitable defense firm and comparable commercial or industrial firm sample s . The in ability to obtain detailed financial information directly from defense contractors without significant leverage has resulted in academic researchers primarily using public domain dat a for their studies . Those studies utilize d data compiled at either the firm level or at the operating segment level. Data for this study w as also obtained from public sources. Only firms that are publicl y traded on major U.S. stock market exchanges are included in th is study. Accounting data for the firms selected w as obtained from Compustat database and s tock market data w as obtained from the Center for Research in Security Prices ( CSRP ) database . Information regarding me rger and acquisition activity w as obtained from applicable firm 10 several secondary sources. This study avoids the problematic issues concerning accounting based measures and utilizes stock market based measures as the primary measure to evaluate long term profitability.

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59 Also, the study uses a more focused sample of defense contractors. The defen se contractors selected represent the firms that produce or support the principal weapon system needs of the DoD. This section is divided into the following five sections . The first section describes the selection process for compiling the defense firm jud gmental sample. Section two describes the process for developing the benchmark sample of non defense commercial or industrial firms. four describes the suppleme ntary analysis approach used for segmenting the Fama French results. Section five provides the supplementary analysis approach used for obtaining accounting based profitability measures of the defense and benchmark firm samples. 5.1 Defense Firm Sample Selection A multi stage approach was used to compile a representative and focused defense firm judgmental sample. As noted in the literature, the approaches used in prior studies for developing their defense sample s varied greatly. The initial step of this approach was to develop a baseline selection of defense firms using firms included in prior defense profitability studies The baseline se lection of defense firms for this study w as drawn from two comprehensiv e research studies performed in 1977 and 198 5 . T he Profit 76 Study ( 1977 ), and DFAIR ( 198 6 ) studies were both commissioned by the DoD . Both of those studies focused on large and medium sized defense contractors that primarily produce d durable goods . Participation in both studies was voluntary and strong participation rates were achiev ed based on the leverage placed on the contractors by the DoD .

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60 Sixty seventy six firms participated in the DFAIR study. Fifty contractors participated in both studies . These studies represent an excellent starting point for this research since the key objectives of both studies were to evaluate defense industry profitability and the stability and strength of the DIB at that time. profitability levels and the st rength and health of the DIB. Conflicting views by interested parties led to the performance of several studies , including the Study (1977) and DFAIR (1986) . Participating firms from those two studies w ere combined and adjusted for mergers, acqu isitions, and divestitures that took place between 1976 and 1985. Additionally, forty nine defense firms who elected to not participate in the DFAIR study w ere identified and added to the baseline sample selection. Th is resulted in one hundred and twenty f ive firms and provided a very representative baseline selection of the most significant defense contractors in the mid In order to create a more focused defense firm sample , t he following adjustments were subsequently made to the baseline sample : 1) firms that spun off , sold , or discontinued their due to the short period of time that they existed during the study period : 2) firms that were acquired during the mid to were excluded due to the short period of time that they existed during the study period ; 3) firms th at primarily sell commercial or commodity type items (e.g. petroleum, food products, insurances, furniture & fixtures, and health care ) were exc luded; 4) privately held or closely held firms were excluded; and 5) foreign owned or controlled firms were excluded . These adjustments resulted in a more representative baseline sample of the defense firms that provide d the U.S.

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61 government its major defen se and security products, systems , and support services in the mid . A reconciliation of this process is summarized on Table 5 1 . These steps re sulted in a n adjusted baseline sample of 53 defense firms studies. The next step involved the identification of new large and medium sized defense firms that emerged over the study period or were not included in the two studies used as the baseline . These firms w ere p rimarily identified based on a review o f the Top 100 Contractors Report compiled annually by the U.S. General Services Administration . This step was further supplemented by identifying the creation of new firms through a review of applicable 10 K information of the baseline sample firms. New firms that were identified were primarily created through the merger of smaller defense firms or through spin offs from larger firms who were exiting the defense industry . New firms that were identified were added to the baseline firm sample at the time they achieved significant size (over $100 million in annual sales). Twenty four new firms were identified by this process and were added to the baseline sample. This resulted in a total defense firm sample of seventy seven firms. A summary of the firms i ncluded in the defense sample , and their source, is included on Table 5 2 . Merger, acquisition, and divestiture activity of the selected defense firms over the study period was significant . This activity was greatly accelerated by the message that Secretary of Defense Les Aspin delivered at the to senior executives of the top defense contractors. Profitability results for defense firms that became defunct as a result of mergers, acquisitions, divestitures , or spin offs are included in the study results up to the point of their delisting or their exit from the defense sector .

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62 Fo r purposes of this study, defense contractors are more broadly defined as firms who contract with the DoD , NASA, Department of Homeland Security, or the intelligence organizations of the U.S government. Together, t hese organizations provide the U.S. govern ment with its national security needs and their contractors primarily follow the same procurement regulations when negotiating government contracts . 5.2 Benchmark Firm Sample Selection A selection of a comparable benchmark sample of non defense commercial and/or industrial firms w as made. The benchmark firms produce non defense products and services of comparable technology and function with the defense firm sample. To develop a matching benchmark sample a common research approach utilizing Stand ard Industrial Classification (SIC) codes for matching firms was adopted. The seventy seve n firms in the defense sample represent fifteen unique industry sectors based on their two digit codes , and forty four sub sectors based on their four digit codes . This distribution is illustrated on Table 5 3. A multi step approach was used to identify matching firms for the benchmark sample . First, all firms in Compustat with non missing values for assets, sales, end of year stock price, number of shares ou tstanding, and positive equity in any of the two digit SIC codes of the defense firm sample were selected as a pool of potential matches. Secondly, for each two digit SIC code year, assets were standardized using a zero mean and a standard deviation of one . Then for each defense firm year, the closest non defense firm year was matched in terms of similarity of standardized assets (up to a 0.5 standard deviation difference), where a benchmark firm year was only allowed to be matched once to one defense firm year (that is, unique matches). This was first done at the four digit SIC level, and repeated at the 3 digit and 2 digit levels for defense firm years that had no matched non defense firm year.

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63 5.3 Measurement s & Model For the main test, p rofitability is m easured using a stock market based rate of return approach (annual stock price change plus dividends received ) . Using a longitudinal design, the measurement period w as 1986 through 201 9 . The main test for the hypothesis i s comprised of three steps. The first step is to determine if the defense firm sample generate s a positive or negative profitability alpha for the measurement period and to determine if it is statistically significant . The second step determine s the profitab ility alpha of the benchmark firm sample for the same time period . Step three compares the results of the two sample portfolios using a t test . In an investment context, alpha is a performance measure used to evaluate the excess or abnormal rates of return of an investment or portfolio. A positive alpha indicates that the investment return over the time period analyzed exceeded the expected return based on a expected . Alpha is a key parameter of the capital asset pricing model (CAPM). CAPM has been extensively used for evaluating the pricing of equi ty investments. However, CAPM has also been widely criticize d due to its simplicity and due to the use of volatility (beta) as the single factor in the model . As a result, s everal alternative models have arisen that propose the use of additional factors f or improving the evaluati on of investment pricing and performance . Over the p ast two decades, t he Fama French + momentum factor model ( Fama French Model ) has become a preferred methodology for determining alpha because it extends the CAPM with additional f actors for analy zing investment risk and performance . To determine alpha for th e main test the following steps w ere performed using the CRSP data base : 1) the average monthly returns of the selected defense firms w ere obtained; 2) the risk -

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64 free rate w as subtracted fr om those returns ; 3) the results w ere regressed against the market return and the Fama French Model factors . Portfolio returns were calculated using a simple average method. Additionally, the Fama French re sults were also calculated on a winsorized basis to limit the influence of outliers o n the data. The percentiles used in the winsorization process were set at 1% and 99% . The following regression equation w as used to determine the profitability alph a of the defense firm and benchmark firm samples : RET = a + b1 * HML + b2 * SMB + b3 * MKTRF + b4 * UMD + e ( 5 1 ) The additional factors used in the Fama French M odel are: 1) High Minus Low (HML) is a value premium factor. It reveals the historic excess returns of value stocks (high book to price ratio) over growth stocks (low book to price ratio) ; 2) Small Minus Big (SMB) is a size effect factor based on the market capitalization of a firm. It reveals the historic excess returns of small cap firms over large cap firms ; 3) Excess Return on Market (MKTRF) factor is computed as the market return minus the risk free rate and controls for the difference in return due to varying market risk ; and 4) M omentum F actor (UMD) is the tendency of the stock price to continue rising if it is going up or to continue declining if it is going down. These additional factors more or specific risk factors when dete rmining excess or abnormal returns. Fama 3 (Fama and French 199 3 ) . The vast majority of studies on defense industry profitability were performed prior to that date. Accordingly, this study appears to be the first study that utilizes the Fama French methodology to identify defense industry excess or abnormal profitability.

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65 5.4 Supplemental Analysis Fama French M odel To provide additional insight into the main test results, supplemental analysis was performed by partitioning the sample results. The sample results were partitioned by time period, by firm size, and by percentage of total sales derived from defense sales. A majority of the prior studies i ncluded time series analyses ranging from five to ten years in length . Bohi ( 1973 ), ( 1977 ), DFAIR ( 1986 ), GAO ( 1987 ), and LMI ( 1969) are examples of studies that used that approach . Three studies utilized multi ple decade periods for compari ng profitability over different time periods , Stigler and Friedland (1971), Higgs (1992), and Wang and San Miguel (2012) . results using the effect of a key event . They evaluated the change in defense indust ry profitability 9 3 through 2010. They determined that industry profitability improved after that watershed event and attributed it to t he decreased industry competition that resulted from industry consolidation . The de fense firm sample results were partitioned into five time p eriods for analyzing profitability trends and the effect of key events . The f ive time periods that were selected for analysis is based on significant events ment period. Defense industry consolidation was significant throughout the study period. The most significant period of industry consolidation occurred during period 2 (mid 1993 through August 31, 2001). n 1993 and saw the creation of mega sized defense firms as some of the largest firms in the industry merged. The periods and key events effecting the defense industry and the stock market are noted below : 1) 1/1/1986 to 6 /3 0 /1993 Post DFAIR study period meeting period . Major events include: Reagan defense build up in early to mid -

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66 War and beginning of Peace Dividend with large defense budget cuts; and defense industry consolidation and downsizing . 2) 7 /1/199 3 to 8/31/200 1 period up to the 9/11/2001 terrorist event. Major events include: Significant industry consolidation especially at major prime contractor levels; Peace Dividend with large defense budget cuts; and significant defe nse procurement acquisition reform . 3) 9/ 1/2001 to 1 0 /31/2008 Major events include: 9/11/2001 event; Iraq and Afghanistan conflicts; significant defense budget grow th ; SARS virus event in 2002 2003 ; and 2008 financial crisis which resulted in a severe recess ion and stock market collapse . 4) 1 1 /1/2008 to 10/31/201 6 Major events include: 2008 financial crisis recovery and stock market recovery ; Obama presidency; military conflicts reduced; defense budget growth ends and budget cuts begin. 5) 11/1/201 6 to 12/31/2019 Major events include: Trump presidency; defense budget grows significantly to replenish defense system needs; and large rise in U.S. stock market indexes. Usi ng market capitalization, t he defense firm sample results were also partitioned by size . The defense firm sample was divided into terciles to determine if differential profit performance was based on the relative size of the defense contractor (large, med ium, and small). Similar analysis was also done in Higgs (1992), LMI (1969), and Comptroller General (1971). Additionally, to identify potential differential profitability results, the defense firm sample results were also segmented into terciles total sales t hat are derived from defense sales (high, medium, low). based on a n average compiled over the time it was included in the study (using every fifth year) .

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67 The sales percentage in the last year a firm was listed on the stock exchange s , or when a firm exited the defense industry , was excluded from the average . The segmentin g by tercile was performed annually based on the relative percentages of the firms in the sample. Firms moved from tercile to tercile based on changes in the mix of their ited during the study period. The high percentage tercile included firms where defense sales represented approximately 80% or more include d firms where defense sales represented approximately 26% to 79% of total sales. The l ow percentage tercile include d firms where defense sales were approximately 25% or lower of total sales . In light of the significant industry consolidation, th e above analysis examines the impact on profit ability of firms who derive a higher share of the ir business from the sale of defense products and services. Stigler and Friedland (1971), Bohi (1973), Higgs (1992), and GAO (1986) also evaluated profitability were derived from defense sales. Those studies found that defense oriented firms with a higher percentage of defense sales tended to outperform firms with lower percentages. No prior studies evaluated all three attributes or factors (time periods, firm size, and percent of a total sales derived fro m defense sales) in their studies. 5.5 Supplemental Analysis Accounting Based Profitability Returns Further supplementing the main test results, accounting based returns for the defense firm sample and the benchmark firm sample w ere compiled . The primary p rofitability and asset performance measures utilized include return on sales ( RO S ) , return on assets ( RO A ) , return on equity ( RO E ) , asset turnover (AT) , and goodwill as a percentage of total assets (G OODWILL

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68 %) . Initial analysis of the sample results noted that the defense firms accumulated significant goodwill on their balance sheets over the study period due to the significant industry merger & acquisition activity. Earnings before interest and taxes (EBIT) was used as the profit numerator in the profitability calculations. For purposes of this study EBIT is deemed more representative of comparable operating profitability than net income (NI). NI tends to vary considerably due to significant fluctuations in redu ctions for interest, income taxes, goodwill impairment, and other non operating items. The following equations were used for calculating the profitability and asset performance measurement s: RO S = EBIT/ Sales ( 5 2) ROA = EBIT/Total Assets ( 5 3) ROE = EBIT/Total Equity ( 5 4) AT = Sales/Total Assets ( 5 5 ) GOODWILL % = Goodwill/Total Assets ( 5 6 ) Trend analysis of the defense accounting based financial performance was performed . This analysis was performed by partitioning the results by time period t o determine if industry profitability improved or deteriorated over the study period. This analysis was also performed for the benchmark firm sample and a c omparison of those results was made . based resul ts were also partitioned by firm size, and by the that are derived from defense sales . The methodologies used for partitioning the accounting based and market based results were consistent.

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69 C HAPTER 6 . R ESULTS & D ISCUSSIO N f our sections. The first section includes the main test results. These results include the market based profitability results for the defense and benchmark samples and a comparison of those results. Section two includes supplemental test results for the defense sample . Included in this section are market based profitability results for the defense firm sample partitioned by fir m size, by derived from defense sales , and by time period . also included. S ection three includes accounting based profitability results for the defense and benchmark firm samples. For the defense firm sample this also includes p ar ti ti oning the accounting based results by firm size , by defense sa les , and by time period . Analysis by time period for the benchmark firm sample is also p resented . The f ourth section analyzes stock market performance of the defense firm sample, benchmark firm sample, and the S&P 500 index over the study period. 6.1 Market Based Profitability Results Defense & Benchmark Sample s The French Model. The monthly returns of the defense and benchmark sample s were regressed against the market return and the Fa ma French Model factors. The study period was 1986 through 2019 and included 408 months. The number of defense firms during that period ranged between a high of 61 in 19 90 and a low of 29 firms in 201 9 . This resulted in 18,089 monthly return observations. The decrease in the number of firms observed was due to the significant industry consolidation during the study period . The number of benchmark firms during the study period ranged between a high of

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70 54 firms in 1990 and a low of 19 firms in 2 019. This resulted in 13,939 monthly return observations. The results for the defense sample are shown on Table 6 1 (Panel A). T he defense firm sample results for the total study period reveal a positive monthly profitability alpha of 0.00353 and the findings are statistically significant at p<.05 ( t statistic 2.48 ) . Annu alizing this positive abnormal return over a twelve month period equate s to a positive annual profitability level of 4. 24 %. A dditionally, on a winsorized basis, the positive monthly profitability alpha is 0.003 25 and remains statistically significant at p <.05 (t statistic 2.47 ). The results of the benchmark sample are included on Table 6 1 (Panel B). The full period results reveal a positive monthly prof itability alpha of 0.00340 and is statistically significant at p < .05 (t statistic 2.25). Annualizing this positive abnormal return equates to 4.08%. After those results are winsorized, the profitability alpha was reduced to 0.0178 and was no longer stat istically significant (t statistic 1.47). The similarity of the market based profitability results between the defense sample and the benchmark sample indicates that the defense industry profitability is not excessive to its non defense peer group. To test this assumption, a t test was performed f or testing the differences of the alphas of these independent samples. The results of that testing found a t value of 0.0613 on an unwinsorized basis and 0.8276 on a winsorized basis. Both of these results were not statistically significant. Th e above res ults reveal that the market based profitability returns for the defense firm sample and the benchmark firm sample are both abnormally high . The results also support the null hypothesis that defense industry profits, as measured by market based prof itability, are similar to the profitability of comparable non defense commercial or industrial firms .

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71 6.2 Supplemental Market Based Profitability Results Defense Firm Sample Table 6 2 (Panel A.) shows the results of partitioning the defense firm sample based on relative firm size (large, medium, or small). The results reveal that large and medium sized firms achieve d higher positive alpha returns than small sized firms. Large sized firms have a positive monthly profitability alpha of 0.00405 (t st atistic 2.68), and medium sized firms have a positive monthly profitability alpha of 0.00462 (t statistic 2.60) . Both were statistically significant at p < .01. Small sized firm s have a positive monthly profitability alpha of 0.00189 (t statistic 0.94) , but the results were not statistically significant . These results are consistent with the realities of an industry which h ad significant consolidation and downsizing activity over the study period. Many of the leading firms in the industry survived and thrived by growing larger through strategic and successful mergers and acquisitions . The p a rti ti oning of the defense firm sample based on a firm s percentage of total sales that are derived from defen se sales (high, medium, or low percentage) is presented on Table 6 2 (Panel B.) . Both high and medium percentage firms achieved positive profitability alphas that were statistically significant. High percentage firms had a positive monthly profitability al pha of 0.00566 and was s tatistically significant at p < .01 (t statistic 2.6 0 ). Medium percentage firms had a positive monthly profitability alpha of 0.00349 and the results were statistically significant at p < .05 (t statistic 2.04). L ow percentage firms had a positive monthly profitability alpha of 0.00141 (t statistic 0.89) , but the results were not found to be statistically significant. The results of partitioning the defen se firm sample by time period is included on Table 6 3 . Four of the five time periods revealed positive profitability alphas . However, none of the individual results for th o se four periods w ere found to be statistically significant. Period 1 had a

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72 negative monthly profitability alpha of 0.00248 but was also not found to be statistically significant. A contributing factor to the lack of statistical significance in the results by interim time period is caused by partitioning the sample into five time period s. This partitioning greatly reduced the number of sample r esults per time period. The full study period, firm size, and percent of total sales derived from defense sales analyses each had 408 monthly observations. The number of monthly observations per interim time period ranged from 38 to 98 months. This reduced the statistical power of those smaller sample tests . Although the results of the individual five periods were not statistically significant, the direction of th o se results are consistent with actions and major events effecting the defense industry during those time periods . included significant merger & acquisition activity and the creation of several highly successful mega firms such as Lockheed Martin, Northrup Grumman, Honeywell growth in t he defense market with its monthly profitability alpha of 0.00450 with a t statistic of 1.90 . Similarly, Period 3 exhibited a positive monthly profitability alpha of 0.0 0 569 with a t statistic of 1.70. results are also consistent with period events which included the significant military conflicts in the Middle East. Those military conflicts resulted in large sales growth throughout the defense industry. re consistent with an industry in turmoil as defense budgets dropped rapidly with the end of the Cold War and the beginning of the Peace Dividend. 6.3 Accounting Based Profitability Results Supplementary Data To supplement the market based profitability results, accounting based profitability results were compiled using Compustat data for the defense and the benchmark samples. The

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73 total period results for the defense sample, and the five interim periods are inc luded on Table 6 4 (Panel A) . The corresponding results for the benchmark sample are also included on Table 6 4 (Panel B) . Defense firm sample sales over the full study period totaled $15 . 3 trillion and averaged $44 8.9 billion per year . Approximately 40% of those sales were defense industry related. The number of defense firms in the sample averaged 42 firms per year and t otal firm year observations were 1,4 30 . The benchmark sales over the full study period totaled $2.5 trillion and avera ged $74.6 billion per year. The number of benchmark firms in the s ample averaged 34.25 firms per year and total firm year observations were 1,165 . The primary reason for the significant difference in sales between the defense and benchmark firm samples is due to the fact that the benchmark peer group does not include as many very large firms as the defense industry has. Table 6 4 (Panel A) shows the following defense firm sample mean value results: ROS of 11. 7 % ; ROA of 6.7% ; ROE of 32. 9 % ; AT of .578 ; and GOODWILL % of 1 5.0 %. Table 6 4 (Panel B) shows the following benchmark firm sample mean value results: ROS of 9.8%; ROA of 7.6%; ROE of 20.0%; AT of .780; and GOODWILL % of 15. 2 %. Several key observations are evident in the above analysis. First, the defense firm sample ROS is higher by 1. 9 % than the benchmark ROS. Secondly, the benchmark firm sample AT rate is significantly better than the defense firm AT rate (. 202 ). This favorable asset turnover performance results in the benchmark firm sample ROA slightly exceeding the defense firm sample ROA despite the lower ROS and EBIT performance of the benchmark firm sample . Additionally, the defense firm sample ROE is significantly higher than the benchmark firm sample ROE (32. 9 % vs 20.0%). This results from a combination of higher defense firm sample ROS and EBIT and the lower equity investment by defense sample firms than the benchmark

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74 sample firms. The defense firm sample equity to total asset ratio is .21 while the corresponding benchmark firm sample ratio is .38. Table 6 4 (Panel A) also provides accounting based results for the defense firm sample by time period. ROS results by period are consistent w ith the market based results as shown by the highest ROS returns being attained in Period 2 (12. 4 %) and Period 3 (13. 8 %). Similarly, Period 1 reveals the lowest returns at 8. 5 %. These improved results indicate that the industry consolidation activities tha t accelerated in Period 2 resulted in improved and sustained profit performance for the defense industry. Other significant trends revealed by Table 6 4 (Panel A) for the defense firm sample is the large deterioration in asset efficiency performance and the significant growth in goodwill. Defense firm sample AT dropped from 0.814 turns in Period 1 to 0.545 turns in Period 4. This resulted in ROA remaining relatively flat over the study period despite impr oved ROS and EBIT performance. Contributing to this asset performance deterioration was a significant growth in goodwill by the defense sample firms. Goodwill as a percentage of total assets for the defense sample firms increased fro m 3 .2 % in Period 1 to 2 5.6 % in Period 5. The average goodwill balance by year grew from $12.2 billion in Period 1 to over $200 billion starting in Period 4. This growth can be attributed to the continu ous acquisition activity that occurred in the defense industry. The benchmark firm sample accounting based profitability results by time period are included on Table 6 4 (Panel B) . The results indicate improving ROS from Period 1 (8.7%) through Period 4 (12.2%). Although the defense firm sample ha d higher ROS results over the total study period, the benchmark firm sample ROS exceed ed the defense sample ROS in p eriod s 1 and 4. Benchmark firm sample asset performance is higher than defense firm sample asset

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75 performance throughout the study period. Benchmark firm sample ROA exceeds defense sample ROA by approximately 1% and AT was also significantly higher (0.780 turns versus 0.578 turns) . This difference is consistent with prior research studies which find th at defense contractor s asset efficiency is lower than their non defense industry peers (GAO 1987). The defense firm sample accounting based profitability results were also partitioned by ense sales. These results revealed additional consistencies between the accounting based and market based results. Table 6 5 (Panel A) shows the results by firm size (large, medium, or small sized firms). Large sized firm ROS of 12.6% significantly exceeds the ROS of medium sized firms ( 6.8% ) and small sized firms (6.0%) . Th e data clearly shows the dominance of the defense industry by large sized firms. The large sized firms in the sample represented 83.7% of the total sample sales. The large sized firms a lso achieved higher ROE performance over the study period. Their ROE was 33. 9 % in comparison to medium sized firms earning 25.4% and small sized firms earning 27.1%. While large size d firms achieve greater profit rates, the AT performance of the large sized firms of 0.524 turns clearly trails the performance of the medium sized (1.259 turns) and small sized firms (1.117 turns). The more favorable ROS and ROE performance results of the large sized firms is consistent with the market based performance re sults noted earlier for the large sized firms. Table 6 5 (Panel B) shows the partitioning of the defense firm sample accounting based percentage). This data revea ls that the ROS for low percentage firms (14. 3 %) very significantly exceeds the ROS of medium percentage firms (8.3%) and high percentage firms ( 9.4%). At the same time the results reveal that low percentage firms greatly lagged the ROA and AT

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76 performance of medium and high percentage firms. Low percentage firms had a 5.9% ROA and an AT of .415, medium percentage firms had a 7.9% ROA and an AT of .94 8 , and high percentage firms achieved a 9. 9 % ROA with an AT of 1.05 1 . ROE results were approximately equal be tween low percentage firms (32.2%) and high percentage firms (3 2.0 %). Medium sized firms had slightly higher ROE at 36. 9 %. Interestingly, for the full study period the market base d and accounting based profitability returns of the low percentage defense firms are not consistent relative to the returns of the high percentage defense firms. High percentage firms had higher market based results with a positive alpha of 0.00566 in comparison to low percentage firms who had a positive al pha of only 0.00141. However, o n an accounting based return basis high percentage firms had a lower ROS of 9.4% versus the low percentage firm ROS of 14. 3 % . approximately equal . Further analysis of this inconsistency resulted i n performing an alternative calculation of ROS and ROE. This alternative calculation us es net income instead of EBIT as the numerator for determin ing ROS and ROE. I t can be argued that using net income for calculating ROS and ROE is more closely aligned with stock market performance. Based on using net income as the numerator in the calculation of ROS and ROE, the gap between the low and high percentage firms changes considerably. ROS for high percentage firms is revised to 5.2% and the ROS for low percentage firms was revised to 6.0% . ROE changes were even more dramatic , with high percentage firm ROE of 17.8% now exceeding low percentage firm ROE of 13.6%. This revised analysis is more consistent with the marke t based analysis that found high percentage defense firms are more profitable than low percentage defense firms.

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77 This change was primarily generated by significant profit and tax adjustments that are not included in EBIT. For example, General Electric (GE ) is a very large conglomerate with a significant annual volume of defense sales . However, defense sales only represent approximately 3 5 % of total annual sales volume . Accordingly, GE is classified as a large sized firm and a low percentage defen se contractor in this study . During 201 5 through 201 9 , GE restructured its business and recorded a significant amount of charges that were not included in EBIT . r eported EBIT for that five year period was $5 5.0 billion while its reported net income was $ 30.4 billion . Goodwill impairment charges in 2018 alone w ere $22.1 billion. Additional analysis noted that distor tive effect on the other accounting based and market based def ense firm result s . 6.4 Stock Market Performance Supplementary Data As a final supplementary analysis, the annual stock market performance of the defense firm sample, benchmark firm sample, and the Standard & Poor 50 0 (S&P 500) was compiled and compared. S&P data was obtained from Investopedia (Investopedia, 2020). Table 6 6 shows the performance results of the samples and the S&P 500 for the total study period and for the five interim periods within the study period. Consistent with the main test results, the defense sample stock market performance has been strong over the study period. Over the total study period the defense sample realized a compound annual rate of return of 15.3%. This exceeds the 13.5% compound annual rate of return for the benchmark s ample, and the 10. 9 % compound annual rate of return for the S&P 500. These returns include the annual change in stock price and the dividends paid. The interim period stock market performance results are also consistent with the market based and the accoun ting based supplementary profitability results. During periods 2 and 3, the

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78 defense firm sample results significantly exceeded the benchmark firm sample results and the S&P 500 results. During the significant defense industry consolidation of Period 2, the defense firm sample compound annual rate of return was 21. 4 % as compared to the benchmark firm sample return of 14.5%, and the S&P 500 return of 1 4.1 %. During Period 3 ( military conflict period in Iraq and Afghanistan and the 2008 recession), the defense sample compound annual rate of return was 11.1% versus the benchmark sample compound annual rate of return of 4. 6 % and the S&P 500 negative rate of return of 1. 7 %. Investing $100 in th o se samples or the S&P 500 for the total study period would have grown to $12,638 for defense firm sample, $7,456 for the benchmark firm sample, and $3,3 4 2 for the S&P 500. These results point to a strong presumption that defense firm stock market returns w ere extraordinarily strong and potentially abnormal or excessive. However, further analysis of the interim period returns reveal that the returns of the benchmark firm sample exceeded the defense firm sample return during periods 1, 4, and 5. On a cumulati ve basis, the benchmark firm sample return on a $100 investment during that nineteen year period is $1,848 versus the defense firm sample return of $1,266 (S&P 500 return was $1, 306 ). Additionally, since 2008 the benchmark firm sample compound annual rate of return of 20. 5 % was slightly favorable to the defense firm sample return of 18.5% . T his supplementary analysis is consistent with the other supplementary testing results and the main test findings . It reveals the variability by period of whether defense industry profitability is higher or lower than it s non defense commercial or industrial firm peers. I t also findings must be considered in that context. Seve ral prior defense profitability studies have made strong conclusions about excess defense industry profitability based on quite short time periods.

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79 CHAPTER 7. LIMITATIONS & ADDITIONAL RESEARCH It is recognized that several limitations exist that may impact th is most significant limitations are: 1) the judgmental selection process of the defense sample; 2) the defense contractors wh o are closely held corporations , privately owned firms , or foreign owned contractors; and 4 ) the sample size of small defense firms may not be adequate . To obtain maximum sample c overage, a judgmental selection was made of large and medium sized publicly held defense contractors. T he coverage rate significant. During sevent annual Top 100 Contractors list (Forecast International, 2019). Additionally, the objective was to have a more focused sample than what was used in p rior research studies , and to have the ability to obtain detailed financial data of the firms selected . As a result, the study excluded firms that provide the DoD with products, services, or commodity items that are primarily sold in the commercial marketplace. These firms were categorized as commercial suppliers and not suppliers of defense oriented products or services. The study also excluded p rivately owned firms, closely held corporations, and foreign owned firms from the sample . Those firms were primarily excluded due to the inability to obtain adequate information concerning their financial results. A s a result of the sampling design, the study results may not be generalizable to th e se excluded industry supplier groups. For a variety of reasons, the abilit y to obtain adequate financial survey data direct l y from defense contractors is not achievable for academic researchers. As a result, academic studies and

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80 this study utilize public domain information for compiling financial results. The in ability to obtain study data directly from defense firms reduces accounting based financial results. In addition, without such direct access it is not possible to obtain adequate financial information of privately ow ned firms, closely held corporations, and foreign owned contractors. sampling design was primarily focused on large and medium sized firms. While the study results were partitioned into large, medium, and small size d firms, this segmenting was based on the relative size of the firms in the sample . The number of small sized Therefore, the study results may not be generalizable to that supplier segment. Due to the above limitations, s everal areas are noted where additional research would a dd to th e This study excluded foreign owned or controlled contractors. The use by the DoD of foreign owned contractors to support its major defense sys tem requirements has increased over the past several decades. This use has increased in importance at both the prime contractor level and at all subcontractor and supplier levels. A separate study analyzing the profitability of this important industry segm The DoD has implemented several strategies and programs over the years to incentivize small firms to become defense industry suppliers. However, the rules and regulations required in contracting with the DoD are costly and burdensome. This has made the industry unattractive to many smaller firms. The results of this study indicate that smaller firms have lower profitability leve ls than large or medium sized firms. A more focused study on the profitability of this separate industry segment sh ould be performed to further validate these findings.

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81 It has been over thir t y years since the DoD or the U.S. Congress has directed a compreh ensive study of the profitability of the defense industry. The leverage that they have over the contractors is needed to motivate appropriate participation. In prior studies (DFAIR 86, GAO 87), it was recommended that periodic profitability studies of the industry should be performed using consistent methodologies. Those recommendations were not implemented. It is recommended that a new study of defense industry profitability be commissioned by the DoD in the near future. Such a study would provide more acc urate results and insight into the key factors affecting defense industry profitability and better ensure that the DIB is properly being rewarded and motivated . C HAPTER 8 . C ONCLUSION Th is industry profitability. A majority of the prior literature finds that defense industry profitability is higher than the profitability of comparable non defense commercial or industrial firm s . In several cases the findings deemed defense industry profitability as excessive. This study contributes to the literature on defense industry profitability in several ways. First, academic and non academic research on this topic has been very scarce over the past twenty five years. This study helps close the gap in the literature by analyzing defense industry profitability between 1986 and 2019. Secondly, this study is the first research study to use a Fama French model to evaluate the market based profitabil ity of the defense industry. Fama French models did not become popular until after the majority of research on this topic was completed. The Fama French models use sev e ral factors for accurately measuring abnormal returns for stock portfolios or investment s . This study use d the Fama French + momentum

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82 m based profitability over an extended time period. The study also adds to the literature by utilizing a more focused approach for selecting a re presentative defense industry sample. It derives its baseline selection of defense firms from two were primarily performed to evaluate defense industry profitabil ity and the health of the defense industrial base. Added to this baseline were significant defense firms that were established after 1985. P rior studies often included defense firm samples that were overly broad or narrow in selection criteria. This study exclude s contractors whose product s , services, or commodities were primarily sold for non defense purposes. breadth to the literature by evaluating defense industry profitab ility using several factors. Through supplemental market based and accounting based profitability analysis, the study evaluated from defense sales. Earlier stu dies often evaluated profitability over relatively short time periods which inhibited the adequacy of factor trend analysis . null hypothesis that defense firm market based profitability over the past thirty four years is similar to the profitability of its non defense commercial or industrial peers . The testing also reveals that the profitability of the defense firms and their non defense peers has been abnormally positive d uring the study period. This conclusion is based on test results using the F ama F rench Model. The total study period results for the defense firm sample reveal a positive monthly profitability alpha of 0.00353 and the findings were statistically significan t at p< .05. Th o se results equate to a positive annual

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83 profitability alpha of 4. 24 %. The test results for the benchmark sample reveal a positive monthly alpha result of 0 . 0340 (4.08% annual rate) and was also statistically significant at p< .05. T o evaluate if the differences between the profitability alphas of the defense and benchmark sample s were statistically significant a t test was performed . The t test results indicate that the differe nces are not statistically significant on both a winsorized and non wi n sorized basis. This testing provides support that while defense firm profitability was abnormally high during the study period , it is similar in comparison to a benchmark sample of non defense commercial or industrial firms. Additional supplementary market based and accounting based profitability testing w as performed. Those testing results were consistent with each other and were supportive of the main test results. Those results also indicate d similar profitability levels between the defense and benchmark firm samples . Defense firm accounting based profitability results, as measured by ROS and ROE , w ere higher than the returns of the benchmark firm s over the total study period . However , benchmark firm profitability was higher during several interim time periods, and achieved significantly higher asset return performance (ROA and AT) over the full study period . The market based supplementary results also revealed several key factors infl uencing defense firm profitability during the study period. The results show that large and medium sized defense firms achieved positive abnormal alpha levels that were statistically significant. Small sized defense firms did not. The results also revealed that high and medium % defense firms also achieved positive abnormal alpha levels while low % defense firms did not. These results point to higher profitability performance for defense firms who attain greater size and whose defense sales are a higher per al e s .

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84 The market based and accounting based supplementary results also revealed that defense firm profitability strongly improved beginning in the mid when the industry was essentially forced into extensive consolidation and downsizing actions due to large defense budget reductions . In retrospect, the motivat ion of those actions by senior DoD leadership in 1993 w as instrumental in help ing the industry su rvive and become more financially sound. The interim period financial results also indicate that the defense industry was able to successfully and consistently adapt to the multitude of changes and challenges it faced over the past three decades. The finan cial health of the firms that comprise the U.S. DIB is crucial to the economic and national security of the country. The DIB firms must achieve and maintain adequate profitability levels in order to remain an attractive investment in the very competitive capital markets. If defense profitability levels deteriorate the investment community will reallocate its capital investments to other market sectors. This will unfavorably affect the industr remain cost competitive, productive , and innovative. At the same time, the government must ensure that taxpayer dollars are spent wisely and frugally. The government must establish procurement policies, rules, and regulations that control a nd monitor this spending and motivate the performance of it s contractors. T he use of profit has been a key motivator for ensuring that this happens and the p rofitability levels of the DIB should not be excessive or inadequate. Accurate periodic assessments of defense contractor profitability are necessary to ensure that the government maintains policies and regulations that properly rewards and sustains the DIB. to the profitability of its non defense commercial or industrial peer firms over the past thirty four

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85 years (1986 2019). T he study results also reveal that defense industry market based profitability results were abnormally positive over the study period . This confirm s that the investment community has viewed the defense sector a s an attractive business sector based on its financial performance and prospects. Th o se results are favorable signs for sustaining a critical asset of this nation .

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86 REFERENCES Agapos, A.M., and L.E. Galloway. 1970. Defense Profits and the Renegotiation Board in the Aerospace Economy. Journal of Political Economy . 78(5): 1093 1105. Bohi, D.R. 1973. Profit Performance in the Defense Industry. Journal of Political Economy 81(3): 721 728. C h antrill, C. 2019. U.S. Government Spending. usgovernmentspending.com/defense. Chen, H., and K. Gunny. 2014. Profitability and Cost Shifting in Government Procurement Contracts. AAA 2015 Management Accounting Section (MAS) Meeting . Comptroller General of the United States (Comptroller General) 1971. Defense Industry Profit Study . Wa shington, D.C. Deloitte. 2016. US Aerospace & Defense Labor Market Study . Available at: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/manufacturing/us ad labor market study 2016.pdf . Department of Defense. 1977. Profit 76 Study . Washington, D.C. Department of Defense. 1986. Defense Financial and Investment Review . Washington, D.C. Dombrowski, P.J., E. Gholz, and A.L.Ross. 2002. Military Transformation and the Defense Industry After Next: The Defense Indust rial Implications of Network Centric Warfare. Naval War College . Newport, Rhode Island. Fama, E., and K. French. 1993. Common Risk Factors in the Returns on Stocks and Bonds. Journal of Financial Economics . 33:3 56. Federal Acquisition Regulation 15.404 4. Contract Pricing Acquisition. Available at: www.acquisition.gov/content/subpart 154 contract pricing . tractors 2019. Available at: http://www.fi aeroweb.com/Top 100 US Government Contractors.html Fox, J.R., & Center of Military History. 201 1 . Defense acquisition reform, 1960 2009. Center of Military History, U nited States Army . Washington, D.C. General Accounting Office. 1986. Government Contracting: Assessment of the Study of Defense Contractor Profitability . Washington, D.C. Higgs, R. 1992. Profits of U.S. Defense Contractors. Defense Economics and Peace Economics . 3(3): 211 218.

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87 Investopedia. 2020. What is the Average Annual Returns for the S&P 500? Available at: https://www.investopedia.com/ask/answers/042415/what average annual return sp 500.asp Lichtenberg, F.R. 1992. A Perspective on Accounting for Defense Contracts. The Accounting Review . 67(4): 741 752. Logistics Mana gement Institute. 1969. Defense Industry Profit Review . Washington, D.C. McDonnell, J.A. 1999. A History of Defense Contract Administration. Available at: www.dcma.mil McGowan, A.S., and V.P. Vendrzyk. 2002. The Relation between Cost Shifting and Segment Profitability in the Defense Contracting Industry . The Accounting Review. 77(4). 949 969. Office of the Under Secretary of D efense (Comptroller) / Chief Financial Officer. 2020. Defense Budget Overview Fi scal Y ear 2021 Budget Request. Available at: https://comptroller.defense.gov/Portals/45/Documents/defbudget/fy2021/fy2021_Budget_ Request _Overview_Book.pdf Peter G. Peterson Foundation. 2018. U.S. Defense Spen d ing Compared to Other Countries. Available at: www.pgpf.org/chart archive/0053_defense comparison . Renegot iation Act, Ch. 247, 56 Stat. 245, 50 U.S.C. Appx. 1191, enacted April 28, 1942. Rogerson, W.P. 1992. Overhead Allocation and Incentives for Cost Minimization in Defense Procurement. The Accounting Review . 67(4): 671 690. Stigler, G.J., and C. Friedland. 1971. Profits of Defense Contractors. American Economic Review . 61(4): 692 694. The Economist. 1997. Land of the Giants Global Defense Industry. Available at: www.economist.com/special report/1997/06/12/land of the giants . Thomas, J., and S. Tung. 1992. Cost manipulation incentives under cost reimbursements: Pension costs for defense contractors. The Accounting Review . 67(4): 691 711. Vinson Trammel Act of 1934, 48 Stat. 503, 10 U.S.C., 40 U.S.C., March 27, 1934. Wang, C., and J. S an Miguel. 2012. The Excessive Profits of Defense Contractors: Evidence and Determinants. Journal of Public Procurement . 12(3): 386 406. Wang, C., 2014. Pol itical Connections of the Board of Directors and Department of Defense Journal of Public Procurement . 14(1): 96 122.

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88 Watts, B.D. 2008. The US Defense Industrial Base: Past, Present and Future. Center for Strategic and Budge tary Assessments . Washington, D.C. Weidenbaum, M.L.1968. Arms and the American Economy: A Domestic Convergence Hypothesis. American Economic Review . 58(2): 428 437. Weidenbaum , M.L. 2003. The Changing Structure of the U.S. Defense Industry. Orbis . 47 (4): 693 703. Zhong, K., and D.W. Gribbin. 2009. Are Defense Contractors Rewarded for Risk, Innovation, and Influence? Q uarterly Journal of Finance and Accounting . 48(3): 61 73.

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89 Exhibit 3 1 . 1 Source: Watts B. 2008. The US Defense Industrial Base: Past, Present and Future The US Defense Industrial Base: Past, Present and Future. Center for Strategic and Budgetary Assessment s . Washington, DC: p.33. Available at: https://csbaonline.org/uploads/documents/2008.10.15 Defense Industrial Base.pdf (Downloaded May 17, 2020) .

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90 Table 4 1. Summary Academic Studies Study Name Years Measured Primary Profitability Measure Sample Size Defense Firms Comparable Group Findings Stigler 1971 1948 1961 , 1962 1967 Market based rate of return Top 50 & 54 defense firms NYSE all stocks Defense profits higher (1948 1961); lower (1958 1968) Bohi 1973 1960 1969 ROE 36 large defense firms Fortune 500 largest mfgs. Equal profitability Higgs 1992 1970 1979 , 1980 1989 Market based rate of return Top 10 & Top 50 defense firms S&P 500 stock index Defense profits higher (1970 79); equal (1980 89) Lichtenburg 1992 1984 1989 ROA 833 defense segments Between defense firms and other segments Defense firms more profitable: cost shifting likely Thomas & Tung 1992 1980 1983 NA Pension funding levels 80 defense firms Inter and intra firm variation in pension funding Cost shifting likely McGowan & Vendryzk 2002 1984 1989, 1994 1998 ROA Multi segment defense firms 35 & 27 Between segments Defe nse profits higher (1984 1989; p rofits equal ( 1994 1998). Cost shifting not found. Zhong & Gribbin 2009 1984 1998 R&D adjusted ROA (AdROA) 11,051 firm year observations Within multi segment firm (defense & non defense) comparison Defense firm profits lower Wang & San Miguel 2012 1950 2010 (2008 used for sample selection baseline) ROA, ROCE, PMR, OMR 112 defense firms Between defense firms and comparably sized commercial firms Defense firm profits higher (1950 2010) Wang 2014 Revalidated 2008 for lower sample size (based on Wang & San Miguel 2012) ROA 90 defense firms Between defense firms and comparably sized commercial firms Defense firm profits higher (2008) Chen & Gunny 2014 2005 2010 ROA 258 defense firms, 1,505 firm years Cost type vs fixed price contracts Profits increase with increase in cost type contracts. Cost shifting indicated.

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91 Table 4 2. Summary Non Academic Studies Study Name Years Measured Primary Profitability Measure Sample Size Defense Firms Comparable Group Findings LMI 1969 1958 1961, 1962 1967 ROA 40 large & medium sized defense firms FTC and SEC durable goods mfgs. Defense firm profits higher (1958 1961); Comml . firm profits higher (1962 1967) Comptroller General 1971 1966 1969 ROA 74 large defense firms Between the defense & comml . segments Profitability approximately equal 1977 1970 1974 ROA, ROS 64 large defense firms: 168 profit centers Between defense and comml . profit centers; and FTC durable goods grouping Defense firm ROS lower; Comml . profit center ROA higher, FTC ROA lower than defense profit centers DFAIR 1986 1970 197 9, 1980 1983 Adjusted ROA 76 large defense firms Refined selection of durable goods grouping Profitability approx. equal (1970 79); Defense firm profits higher 1980 83 GAO 1987 Re calculated DFAIR results; and 1979 1984 ROA, ROE, ROS, Cash flow , Mkt. based returns 84 large defense firms DFAIR comparison: b etween defense and comml. segments DFAIR results contradicted defense firm profits higher in both periods; GAO study also finds defense firms more profitable

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92 Table 5 1. Defense Firm Baseline Sample Sources and Adjustments DFAIR & Profit '76 DFAIR non response Totals Total Firms 76 49 125 Less Adjustments: 1) Mid to late 1980's merged/acquired 12 13 25 2) Private/closely held 6 8 14 3) Foreign owned 3 0 3 4) Commercial/commodity products or services 13 13 26 5) Other 1 3 4 Adjusted Sample 41 12 53 This table summarizes the sources of the defense firm baseline sample and the adjustments made to that baseline sample. The primary sources of the baseline sample were the seventy six firms who participated in either the DFAIR (1986) or Profit '76 (1977) studies, and the forty nine firms who elected to not pa rticipate in the DFAIR study (DFAIR non response). Several adjustments were made to the baseline sample to create a more focused defense sample. The following eliminations were made: 1) firms that ceased to exist in the mid to late 1980's due acquisition, merger, spin off, or exiting the defense industry; 2) private or closely held firms; 3) foreign owned firms; 4) firms that primarily provide commercial or commodity goods or services; and 5) firms with unavailable data .

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93 Table 5 2. Defense Firm Sample 77 Public U.S. Firms Name Study Source Years in Study Stock Ticker SIC Sales Year ($ billions) Lockheed Martin DFAIR/Profit 76 1986 2019 LMT 3761 $59.8 2019 Martin Marietta DFAIR/Profit 76 1986 1995 ML 3761 $9.4 1993 Boeing DFAIR/Profit 76 1986 2019 BA 3721 $101.1 2019 McDonnell Douglas DFAIR/Profit 76 1986 1997 MD 3721 $13.8 1996 Northrup Grumman DFAIR/Profit 76 1986 2019 NOC 3812 $33.8 2019 Grumman Aircraft DFAIR/Profit 76 1986 1994 GQ 6711 $3.2 1993 Harris DFAIR/Profit 76 1986 2019 HRS 3812 $6.8 2019 General Dynamics DFAIR/Profit 76 1986 2019 GD 3731 $39.4 2019 Raytheon DFAIR/Profit 76 1986 2019 RTN 3812 $29.2 2019 United Technologies DFAIR/Profit 76 1986 2019 UTX 3724 $66.5 2018 Honeywell (Allied Signal) DFAIR/Profit 76 1986 2019 HON 3714 $36.7 2019 ITT DFAIR/Profit 76 1986 2011 ITT 3561 $11.0 2010 Kaman Aerospace DFAIR/Profit 76 1986 2019 KAMN 5084 $.7 2019 CACI International DFAIR/Profit 76 1986 2019 CACI 7373 $5.0 2019 Rockwell International DFAIR/Profit 76 1986 1996 ROK 3714 $10.4 1996 Aerojet Rocketdyne DFAIR/Profit 76 1986 2019 AJRD 3812 $2.0 2019 General Electric DFAIR/Profit 76 1986 2019 GE 3511 $95.2 2019 Litton DFAIR/Profit 76 1986 2001 LIT 3812 $5.6 2000 E Systems DFAIR/Profit 76 1986 1995 ESY 3662 $2.0 1994 EDO DFAIR/Profit 76 1986 2007 EDO 3662 $.7 2008 Harsco DFAIR/Profit 76 1986 1997 HSC 3446 $1.7 1998 TRW DFAIR/Profit 76 1986 2002 TRW 3714 $16.4 2001 Todd Shipyards DFAIR/Profit 76 1986 2011 TOD 3731 $.2 2009 United Industrial DFAIR/Profit 76 1986 2007 UIC 8731 $.6 2006 AEL Industries DFAIR/Profit 76 1986 1996 AELNA 3662 $.1 1994 FMC DFAIR/Profit 76 1986 1997 FMC 3523 $4.4 1998 Logicon DFAIR/Profit 76 1986 1997 LGN 8911 $.6 1996 Talley Industries DFAIR/Profit 76 1986 1998 TAL 3873 $.5 1996 Texas Instruments DFAIR/Profit 76 1986 1997 TXN 3674 $8.5 1998 Westinghouse Electric DFAIR/Profit 76 1986 1996 WX 3613 $6.3 1995 Watkins Johnson DFAIR/Profit 76 1986 1999 WJ 3662 $.1 1998 Arvin Industries DFAIR/Profit 76 1986 2000 ARV 3714 $3.1 1999 EG&G DFAIR/Profit 76 1986 1999 EGG 8911 $1.4 1998 Thiokol DFAIR/Profit 76 1989 2000 TKC 2891 $2.5 1999 Hercules DFAIR/Profit 76 1986 1995 HPC 2816 $2.8 1994 UNISYS DFAIR/Profit 76 1986 1995 UIS 3573 $7.4 1994 SEQUA (Sun Chemical) DFAIR/Profit 76 1987 2003 SQA 2893 $2.0 2005 LTV DFAIR/Profit 76 1986 1992 LTV 3316 $3.8 1992 Tenneco DFAIR/Profit 76 1986 1996 TEN 4922 $6.6 1996 Computer Sciences DFAIR/Profit 76 1986 2015 CSC 7373 $13.0 2013 Morrison Knudson DFAIR/Profit 76 1986 1996 MRN 1622 $1.7 1995 Textron DFAIR NR 1986 2019 TXT 3999 $13.6 2019 Leidos (Original SAIC) DFAIR NR 2006 2019 LDOS 7373 $11.1 2019

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94 Table 5 2. (Continued) Name Study Source Years in Study Stock Ticker SIC Sales Year ($ billions) Loral DFAIR NR 1986 1996 LOR 3679 $5.5 1994 Whittaker DFAIR NR 1986 1999 WKR 5051 $.1 1998 Goodrich DFAIR NR 1986 2012 GR 3761 $8.1 2011 Cubic DFAIR NR 1986 2019 CUB 3723 $1.5 2019 Curtiss Wright DFAIR NR 1986 2019 CW 3724 $2.5 2019 Sparton DFAIR NR 1986 2019 SPA 3672 $.4 2018 Rohr DFAIR NR 1986 1997 RHR 3728 $.9 1997 Sundstrand DFAIR NR 1986 1999 SNS 3541 $2.0 1998 California Microwave DFAIR NR 1986 1999 CMIC 3662 $.3 1998 Teledyne DFAIR NR 1986 1999 TDY 3662 $2.3 1999 Orbital Science NEW 1990 2015 ORB 3663 $1.4 2013 Oshkosh NEW 1986 2019 OSK 3711 $8.4 2019 Alliant Techsystems NEW 1990 2018 ATK 3764 $4.7 2017 Rockwell Collins NEW 2001 2018 COL 3728 $8.7 2018 L 3 Technologies NEW 1998 2019 LLL 3812 $10.2 2018 Huntington Ingalls NEW 2011 2019 HII 5088 $8.9 2019 SAIC (new) NEW 2013 2019 SAIC 8731 $6.4 2019 Exelis NEW 2011 2015 XLS 3812 $3.3 2014 DRS Technologies NEW 1986 2008 DRS 3662 $3.3 2007 Teledyne Technologies NEW 1999 2019 TDY 8711 $3.2 2019 Vectrus NEW 2014 2019 VEC 8744 $1.4 2019 AECOM NEW 2007 2019 ACM 8711 $20.2 2019 URS NEW 1986 2014 URS 8911 $11.0 2013 KBR NEW 2006 2019 KBR 1629 $5.6 2019 MOOG NEW 1986 2019 MOG 3494 $2.9 2019 Newport News Shipbldg NEW 1996 2002 NNS 3731 $2.1 2000 Mantech International NEW 2002 2019 MANT 7373 $2.2 2019 Titan NEW 1986 2005 TTN 3679 $2.0 2004 Transdigm NEW 2006 2019 TDG 3728 $5.2 2019 Fluor Corp. NEW 1986 2019 FLR 1623 $19.2 2018 CSRA NEW 2015 2018 CSRA 7374 $5.0 2016 Woodward NEW 1997 2019 WWD 3728 $2.9 2019 RBC Bearings NEW 2005 2019 ROLL 3562 $.7 2019 Jacobs Engineering NEW 1986 2019 JEC 8711 $12.7 2019 This table presents the seventy seven firms included in the study's defense sample. The firms were obtained from the following sources: DFAIR (1986) and Profit '76 (1977) studies; DFAIR (NR) non respondents to the DFAIR study; and NEW medium or large firms that were not included in the DFAIR study in 1986 or new firms that were formed after the DFAIR s tudy. New firms were included in the study when their sales levels exceeded $100 million. Firms ceased to be included when they were de listed from the applicable stock exchange or exited the defense industry. The table includes the years the firms were in cluded in the study, stock ticker, standard industrial classification (SIC) code, and sales in the most recent year that financial data was available.

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95 Table 5 3. Defense Firm Sample Distribution and Frequency of SIC Codes Industry Sector Name 2 Digit SIC Code Firm Frequency Number of 4 Digit SIC Sub Codes 1) Transportation Equipment 37 21 9 2) Electronic & Other Electric Equipment 36 13 6 3) Instruments & Related Products 38 8 2 4) Industrial Machinery & Equipment 35 6 6 5) Engineering & Management Services 87 6 3 6) Business Services 73 5 2 7) Chemical & Allied Products 28 3 3 8) Wholesale Trade Durable Goods 50 3 3 9) Heavy Construction Except Building 16 3 3 10) Services, Not Elsewhere Classified 89 3 1 11) Fabricated Metal Products 34 2 2 12) Primary Metal Industries 33 1 1 13) Miscellaneous Manufacturing 39 1 1 14) Holding & Other Investment Offices 67 1 1 15) Electric, Gas, & Sanitary Services 49 1 1 Totals 15 sectors 77 firms 44 sub code groups This table summarizes the standard industrial classification (SIC) codes of the defense firm sample. Industry name, 2 Digit SIC codes, and frequency of sample firms in the various 2 Digit SIC codes are presented. The defense firm sample is comprised of fif teen separate 2 Digit SIC code sectors. Over half of the firms in the defense sample are included in the top three 2 Digit SIC code sectors. Also presented is the number of 4 Digit sub code groupings of the defense firm sample. The defense sample is compri sed of forty four separate 4 Digit sub code groupings. Over half of the defense firms were included in the top four 4 Digit SIC sub code groupings.

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96 Table 6 1. Market Based Returns Full Study Period (1986 to 2019) Panel A Panel B Defense Sample Benchmark Sample Returns Returns Winsorized Returns Returns Winsorized Abnormal Returns Alpha 0.00353* 0.00325* 0.00340* 0.00178 (2.48) (2.47) (2.25) (1.47) MKTRF 0.968** 0.920** 1.078** 1.036** (21.38) (25.26) (28.29) (33.87) SMB 0.309** 0.285** 0.658** 0.583** (3.61) (3.72) (11.52) (10.81) HML 0.421** 0.398** 0.0831 0.105 (5.48) (5.38) (1.17) (1.90) UMD 0.054 0.0289 0.232** 0.181** ( 1.21) ( 0.70) ( 3.79) ( 5.51) R Squared 0.744 0.737 0.824 0.846 Observations months 408 408 408 408 Statistical significance *=p<0.05; **= p<0.01. T statistics in parentheses This table shows market based returns and factor loadings of the defense firm and benchmark firm samples for the full study period. The study period is 1986 through 2019. The returns are calculated using the Fama French + momentum model (FF Model). The pro fitability return alpha is the intercept in a time series regression of monthly excess returns of the sample. The explanatory variables used in the FF Model are market return minus risk free rate (MKTRF), excess return of value stocks (HML), size effect ba sed on market capitalization (SMB), and momentum of stock price (UMD). The returns are in monthly percentage and t statistics are shown below the coefficient estimates. Statistical significance, if any, is indicated at 5% and 1% levels. Returns were also c alculated on a winsorized basis to limit the influence of outliers. The percentiles used in the winsorization process were set at 1% and 99%. Panel A reports the study's main test results for the defense firm sample for the full study period. Panel B repor ts the results for the benchmark sample for the full study period.

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97 Table 6 2. Defense Firm Sample Market Based Returns by Firm Size and % Defense Panel A Firm Size Large Medium Small Abnormal Returns Alpha 0.00405** 0.00462** 0.00189 (2.68) (2.60) (0.94) MKTRF 0.983** 1.057** 0.858** (22.30) (18.31) (14.63) SMB 0.115 0.312* 0.742** ( 1.75) (2.43) (6.78) HML 0.347** 0.485** 0.432** (4.36) (5.08) (4.56) UMD 0.0329 0.0398 0.0912 ( 0.75) ( 0.79) ( 1.18) R Squared 0.693 0.667 0.621 Observations months 408 408 408 Panel B % Defense High Medium Low Abnormal Returns Alpha 0.00566** 0.00349* 0.00141 (2.60) (2.04) (0.89) MKTRF 0.833** 0.910** 1.161** (13.32) (16.98) (25.73) SMB 0.385** 0.304** 0.228** (3.89) (3.12) (2.65) HML 0.372** 0.401** 0.477** (3.53) (4.58) (6.37) UMD 0.002 0.0416 0.117* ( 0.03) ( 0.79) ( 2.30) R Squared 0.505 0.644 0.758 Observations months 408 408 408 Statistical significance *p<0.05; **= p<0.01. T statistics in parentheses. This table shows market based returns and factor loadings of the defense firm sample based on relative firm size and based on percent of a firm's sales derived from defense sales. The period is 1986 throug h 2019. The returns are calculated using the Fama French + momentum model (FF Model). The profitability return alpha is the intercept in a time series regression of monthly excess returns of the sample. The explanatory variables used in the FF Model are ma rket return minus risk free rate (MKTRF), excess return of value stocks (HML), size effect based on market capitalization (SMB), and momentum of stock price (UMD). The returns are in monthly percentage and t statistics are shown below the coefficient estim ates. Statistical significance, if any, is indicated at 5% and 1% levels. Panel A includes results partitioned by firm size. The defense sample was annually divided into terciles (Large, Medium, Small) based on market capitalization of the sample's firms. Panel B includes results partitioned by percentage of total sales derived from defense sales. The sample was annually divided into terciles (High, Medium, Low) based on defense firm sales percentages.

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98 Statistical significance *= p<0.05; ** =p<0.01. T statistics in parentheses. This table shows market based returns and factor loadings of the defense firm sample for interim time periods within the full study period. The full study period is 1986 through 2019. The returns are calculated using the Fama French + momentum model (FF Model). The profitability return alpha is the intercept in a time series regression of mont hly excess returns of the sample. The explanatory variables used in the FF Model are market return minus risk free rate (MKTRF), excess return of value stocks (HML), size effect based on market capitalization (SMB), and momentum of stock price (UMD). The r eturns are in monthly percentage and t statistics are shown below the coefficient estimates. Statistical significance, if any, is indicated at 5% and 1% levels. The interim time periods used are based on significant events that impacted the defense indust ry and stock market. Period 1 was 1986 through June, 1993. Period 2 was July, 1993 through August, 2001. Period 3 was September, 2001 through October, 2008. Period 4 was November, 2008 through October, 2016. Period 5 was November, 2016 through 2019. Table 6 3. Defense Firm Sample Market Based Retur ns by Interim Period Period 1 Period 2 Period 3 Period 4 Period 5 Abnormal Returns Alpha 0.00248 0.0045 0.00569 0.00231 0.00498 ( 1.03) (1.90) (1.70) (1.09) (1.09) MKTRF 1.078** 1.018** 1.028** 1.053** 1.119** (21.00) (15.67) (9.72) (15.41) (8.95) SMB 0.603** 0.339** 0.417** 0.390** 0.373 (7.50) (3.61) (2.88) (4.29) (2.03) HML 0.193* 0.777** 0.387 0.0196 0.36 (2.27) (5.75) (1.96) ( 0.22) (1.60) UMD 0.149 0.224** 0.240** 0.0846 0.137 ( 1.61) ( 3.85) (2.95) ( 1.95) (0.78) R Squared 0.899 0.695 0.725 0.872 0.786 Observations months 90 98 86 96 38

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99 Table 6 4. Accounting Based Returns Interim Periods and Full Period Panel A Defense Firm Sample ($ billions) Period 1 Period 2 Period 3 Period 4 Period 5 Full Period (1986 1993) (1994 2001) (2002 2008) (2009 2016) (2017 2019) (1986 2019) Sales $2,446 $2,718 $3,488 $4,823 $1,788 $15,263 ROS 8.5 % 12.4 % 13.8 % 11.5 % 11.3 % 11.7 % ROA 6.9 % 7.4 % 6.6 % 6.3 % 7.3 % 6.7 % ROE 30.9 % 38.8 % 33.3 % 28.9 % 39.3 % 32.9% Asset Turnover 0.814 0.601 0.48 0.545 0.652 0.578 Goodwill $97 $438 $1,102 $1,612 $703 $3,953 Goodwill % 3.2 % 9.7 % 15.2 % 18.2 % 25.6 % 15.0 % Panel B Benchmark Firm Sample ($ billions) Period 1 Period 2 Period 3 Period 4 Period 5 Full Period (1986 1993) (1994 2001) (2002 2008) (2009 2016) (2017 2019) (1986 2019) Sales $610 $539 $517 $568 $303 $2,538 ROS 8.7 % 8.3 % 9.7 % 12.2 % 10.2 % 9.8 % ROA 7.1 % 8.1 % 8.6 % 7.6 % 6.8 % 7.6 % ROE 22.7 % 22.8 % 19.4 % 17.9 % 18.9 % 20.0 % Asset Turnover 0.812 0.977 0.883 0.625 0.667 0.78 Goodwill $20 $61 $109 $218 $85 $494 Goodwill % 2.6 % 11.1 % 18.6 % 24.0 % 18.8 % 15.2 % This table presents the defense sample's accounting based profitability and asset performance results for the total study period (1986 through 2019). Additionally, the total period results are partitioned into five interim time periods for analyzing perfor mance trends during the study period. The interim time periods used are based on significant events that impacted the defense industry and the stock market. Period 1 was 1986 through 1993. Period 2 was 1994 through 2001. Period 3 was 2002 through 2008. Per iod 4 was 2009 through 2016. Period 5 was 2017 through 2019. The financial data was obtained from Compustat and is not adjusted for inflation . Balance sheet amounts were based on a firm's end of fiscal year or calendar year results. The measurements used are calculated as follows: 1) Return on Sales (ROS) equals Earnings Before Interest and Taxes (EBIT)/Sales; 2) Return on Assets (ROA) equals EBIT/Total Assets; 3) Return on Equity equals EBIT/Total Equity; 4) Asset Turnover (AT) equals T otal Assets/Sales; and 5) Goodwill % equals Goodwill/Total Assets.

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100 Table 6 5. Defense Firm Sample Accounting Based Returns Firm Size and % Defense Panel A Defense Firm Sample Firm Size ($ billions) Large Medium Small Sales $12,780 $2,052 $431 ROS 12.6% 6.8 % 6.0 % ROA 6.6 % 8.6 % 6.7 % ROE 33.9 % 25.4 % 27.1 % Asset Turnover 0.524 1.259 1.117 Goodwill $3,499 $370 $85 Goodwill % 14.4% 22.7 % 21.9 % Panel B Defense Firm Sample % Defense ($ billions) High Medium Low Sales $3,614 $3,771 $7,878 ROS 9.4 % 8.3% 14.3% ROA 9.9 % 7.9 % 5.9 % ROE 32 % 36.9 % 32.2 % Asset Turnover 1.051 0.948 0.415 Goodwill $1,178 $504 $2,273 Goodwill % 34.2 % 12.7 % 14.9 % This table presents the results of partitioning the defense firm sample's accounting based profitability performance results. The results are partitioned based on relative firm size and based on the percentage of a firm's total sales that are derived from defense sales (% Defense). The resu lts are for the total study period (1986 2019) and are not adjusted for inflation . The data was obtained from Compustat. Balance sheet amounts were based on end of fiscal year or calendar year results. The measurements are calculated as follows: 1) Return on Sales (ROS) equals Earnings Before Interest and Taxes (EBIT)/Sales; 2) Return on Assets (ROA) equals EBIT/Total Assets; 3) Return on Equity (ROE) equals EBIT/Total Equity; 4) Asset Turnover (AT) equals Total Assets/Sales; and 5) Goodwill % equals Goodw ill/Total Assets. Panel A includes results partitioned by firm size. The defense firm sample was annually divided into terciles (Large, Medium, Small) based on the market capitalization of the sample's firms. Panel B includes the results partitioned by % D efense. The defense firm sample was annually divided into terciles (High, Medium, Low) based on the % Defense of the sample's firms.

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101 Table 6 6. Stock Market Return Performance Panel A Cumulative Compound Returns Period 1 Period 2 Period 3 Period 4 Period 5 Full Period (1986 1993) (1994 2001) (2002 2008) (2009 2016) (2017 2019) (1986 2019) Defense Sample 197.3% 471.5% 209.2% 397.7% 163.3% 12638.3% Benchmark Sample 238.7% 295.3% 36.7% 425.0% 182.1% 7456.3% S& P 500 290.5% 286.9% 11.0% 293.7% 152.7% 3342.4% Panel B Average Annual Returns Period 1 Period 2 Period 3 Period 4 Period 5 Full Period (1986 1993) (1994 2001) (2002 2008) (2009 2016) (2017 2019) (1986 2019) Defense Sample 8.9% 21.4% 11.1% 18.8% 17.8% 15.3% Benchmark Sample 11.5% 14.5% 4.6% 19.8% 22.1% 13.5% S& P 500 14.3% 14.1% 1.7% 14.4% 15.2% 10.9% Study years 8 8 7 8 3 34 This table shows stock market performance of the study's defense and benchmark firm samples and the Standard & Poor 500 (S&P 500) for the full study period (1986 through 2019) and for the five interim periods. The five interim periods used are consistent with the interim time periods used in the accounting based profitability analysis (Table 6 4). Defense and benchmark firm returns were obtained from CRSP. S&P 500 returns were obtained from Investopedia. Annual returns are measured by the calendar year change in a firm's stock price and the dividends paid. Results are not adjusted for inflation. Panel A presents the cumu lative compound returns for the five interim periods and the total study period for the defense firm sample, the benchmark firm sample, and the S&P 500. Panel B presents the average annual return for the five interim periods and the total study period for the defense firm sample, benchmark firm sample , and the S&P 500 .

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102 BIOGRAPHICAL SKETCH John Canzio was born in Fitchburg, Massachusetts. John received his Bachelor of Science degree with a major in Accounting from Quinnipiac University. John also has earne d a Master in Business Administration from the University of Hartford, and a Master of Science in Entrepreneurship from the University of Florida. John is currently enrolled in the Doctor of Business Administration program at the University of Florida. Joh n has been a licensed CPA in the state of Connecticut since 1982. Waterhouse working on several Fortune 500 clients. John was also the Director of Internal Audit at T extron Division for over fifteen years. Pratt & Whitney is the world leader in jet engines for military fighter and transport planes. John also served as the CFO for Aerojet until 2015. John is currently a financial consultant specializing in aerospace, government contracting, and personal financial planning. He also serves on the Corporate Board and the Finance Committee of the Jupiter Medical Center in Jupiter, Florida.