Annette Holler

New Metrics for Value-Based Management

GABLER RESEARCH

Unternehmensführung & Controlling

Herausgegeben von Universitätsprofessor Dr. Dr. habil. Wolfgang Becker,Otto-Friedrich-Universität Bambergund Universitätsprofessor Dr. Dr. h.c. Jürgen Weber,WHU – Otto Beisheim School of Management, Vallendar

Die Schriftenreihe präsentiert Ergebnisse der betriebswirtschaftlichen Forschung

im Themenfeld Unternehmensführung und Controlling. Die Reihe dient der Weiter-

entwicklung eines ganzheitlich geprägten Management-Denkens, in dem das

Controlling als übergreifende Koordinationsfunktion einen für die Theorie und

Praxis der Führung zentralen Stellenwert einnimmt.

Annette Holler

New Metrics for Value-Based Management Enhancement of Performance Measurement and Empirical Evidence on Value-Relevance

With a foreword by Professor Dr. Dirk Schiereck

RESEARCH

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Dissertation European Business School, Oestrich-Winkel, 2009

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For Raphaela, Giulia, and Mauro

Foreword

Still today, the vast majority of the German DAX 30 corporations are explicitly comit-ted to the shareholder value idea. However, the stock return to shareholders is an inappropriate measure for internal performance management, so that companies revert to so-called Value-Based Management Systems. These systems derive accounting-based performance measures, which shall quantify whether and how much shareholder value has been generated by the management over a specific period (overall and by business unit). Data applied for calculating the performance measure has to be publicly available and, preferably, also separately disclosed, to allow capital market participants to project results of the performance measure on the stock price.

Various metrics (net earnings, residual income, EVA, REVA), which also demonstrated some correlation with stock returns in empirical studies, have been implemented for performance measurement in the past, but these measures still show methodological deficits and also the correlation with the stock performance can still be increased considerably. Also in this respect, the study of Annette Holler makes a substantial contribution, demonstrating that two new metrics (CRI, CEVA) show superior results both methodologically and in the empirical test. To date, such an examination of various yet existing and newly developed performance measures has not been known to me. Hence, the dissertation of Ms. Holler extends, in an amazing way, preceding academic research. In several also explorative analyses, a detailed picture of the information content of diverse measures of Value-Based Management is documented. Therewith, an objective state of knowledge is achieved, based on that well-founded recommendations for the design of the performance measurement and management system can be derived, which, in turn, should lead to a further increase in the effectiveness of corporate management.

Ms. Holler optimally fulfills the independently defined goals in her dissertation. The work entails numerous interesting results and is written in a way that it will surely be a pleasure for the reader to read to the end. I wish that this work will be paid the due attention it deserves.

Professor Dr. Dirk Schiereck Chair for Corporate Finance

Faculty of Law and Economics Technische Universität Darmstadt

VIII Foreword

Die ganz überwiegende Mehrzahl der deutschen DAX 30-Konzerne bekennt sich heute (immer noch) ganz explizit zum Shareholder Value-Gedanken. Als direkte Steuerungs-größe innerhalb eines Unternehmens ist die Aktienrendite allerdings ungeeignet, so dass auf sogenannte Value-Based Management Systeme zurückgegriffen wird. Diese Systeme leiten aus Rechnungslegungsdaten Steuerungsgrößen ab, die erfassen sollen, ob und wie viel Wert in der jeweils zurückliegenden Periode vom Management (insge-samt und heruntergebrochen auf Business Units) für die Aktionäre erwirtschaftet wurde. Damit von den Kapitalmarktteilnehmern ein Transfer von Ergebnissen der Steuerungsgröße auf den Aktienkurs vorgenommen werden kann, müssen die Daten zur Berechnung der Steuerungsgröße öffentlich verfügbar und möglichst auch noch separat ausgewiesen sein.

Verschiedene Maßzahlen (Net Earnings, Residual Income, EVA, REVA) wurden in der Vergangenheit als Steuerungsgrößen implementiert, zeigten auch in empirischen Studien gewisse Korrelationen zur Aktienrendite, weisen aber immer noch methodische Defizite auf, und auch die Korrelationen zur Aktienperformance sind noch deutlich steigerungsfähig. Auch hier setzt die Arbeit von Frau Holler an, um zu zeigen, dass zwei neue Maßzahlen (CRI, CEVA) sowohl methodisch als auch im empirischen Test überlegene Ergebnisse zeigen. Eine derartige Untersuchung ver-schiedener länger existierender und neu entwickelter Steuerungsgrößen ist mir bis dato nicht bekannt. Die Dissertationsschrift von Frau Holler betritt somit (in erstaunlicher Weise) wissenschaftliches Neuland. In mehreren, auch explorativ angelegten Untersuchungen wird ein detailliertes Bild des Aussagegehalts verschiedener Steuerungsgrößen des Value-Based Managements dokumentiert. Damit wird ein objektiver Kenntnisstand erreicht, auf dessen Basis sich fundierte Handlungs-empfehlungen für die Gestaltung der Performanceermittlung und Steuerungsmodelle ableiten lassen, die wiederum zu einer weiteren Effektivitätssteigerung der Unternehmenssteuerung führen sollten.

Frau Holler kann die selbst gesetzten Ziele in ihrer Dissertationsschrift bestens er-füllen. Die Arbeit enthält zahlreiche spannende Resultate und ist so geschrieben, dass es den Lesern sicherlich Freude machen wird, sie bis zum Ende zu lesen. Ich wünsche der Arbeit eine ihr gebührende weite Verbreitung.

Professor Dr. Dirk Schiereck

Lehrstuhl für Unternehmensfinanzierung Fachbereich Rechts- und Wirtschaftswissenschaften

Technische Universität Darmstadt

Acknowledgments

This dissertation summarizes research I conducted during my doctoral studies at the chair for banking and finance of the EUROPEAN BUSINESS SCHOOL (ebs) at Oestrich-Winkel. Many people contributed to making this PhD study a valuable and successful experience. Without their support, I could neither have reached the heights nor explored the depths.

Above all, I am in full debt to my PhD advisor Professor Dr. Dirk Schiereck, who transferred by now from the ebs to the TU Darmstadt, for providing his committed supervision and expertise. He managed to focus my ideas, direct my enthusiasm, provide invaluable ideas, and to motivate me. I also wish to thank Professor Dr. Michael Henke from the EBS Oestrich-Winkel for volunteering as a second advisor and always providing constructive comments and valuable suggestions.

Moreover, other persons specifically contributed to my work: First of all, I very deeply appreciate the efforts of Mauro Risi, CEO Agip Deutschland and Benelux, who provided the initial ideas for this research, gave his time to read an early version of this work, and always understood to challenge and enrich my work. I also want to thank Professor Sanford J. Leeds from the University of Texas at Austin, with whom I verified the relevance of the research topic, for sharing his knowledge and offering me valuable contacts to discuss my research plans. I thank Felix Zeidler and Mike Stenglein for assisting me at all times with data requests. I very much acknowledge the support on the selection and implementation of statistical methods that I received from Dr. Wolfgang Rauch from the University of Frankfurt. At the same time, I would like to thank Alexander Schmidt for developing customized software that was a great help in performing the statistical analysis.

Additionally, I thank my employer Bain & Company for giving me valuable support and time off to conduct this study and providing me a stimulating and effective back-ground. I want to thank Britta Heinrich for helping me to collect literature and beyond that all my colleagues for supporting my research intentions and numerous valuable discussions, in particular, Carsten Prussog, Christian Kinder, Arndt Kaminski, Pascal Schweizer, Joachim Krebs, and Heike Moses.

Last but not least, I would like to thank all my family and friends; particularly, Natalie, Susi, and Josef for their patience and persistence with regard to our friendship, Raphaela and Alex for their confidence and encouragement, my parents Anneliese and Konrad for their support, and Mauro, the love of my life, for his dedication.

Annette Holler

Endowed Chair for Banking and Finance EUROPEAN BUSINESS SCHOOL (ebs)

International University Schloß Reichartshausen

List of Contents

Foreword ......................................................................................................................VII Acknowledgments......................................................................................................... IX List of Contents............................................................................................................. XI List of Figures ..............................................................................................................XV List of Tables ............................................................................................................XVII Abbreviations............................................................................................................. XIX Symbols...................................................................................................................... XXI

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

1.1 Motivation .................................................................................................... 1 1.1.1 Inadequacy of Performance Measures .............................................. 1 1.1.2 Inconsistencies and Deficiencies of Prior Empirical Studies............ 5

1.2 Research Objectives ..................................................................................... 8 1.3 Structure of the Study................................................................................. 10

2 Fundamentals.................................................................. 13

2.1 Value-Based Management (VBM)............................................................. 14 2.1.1 Emergence of VBM Responding to Increasing Shareholders’

Pressure ........................................................................................... 14 2.1.2 Maximization of Shareholder Value as an Overall Objective ........ 16 2.1.3 Critical Success Factors for VBM Implementation ........................ 22 2.1.4 Validity of VBM Systems within Sustainability and

Stakeholder Models......................................................................... 25 2.2 Value-Based Performance Measures ......................................................... 28

XII List of Contents

2.2.1 Unsuitability of Traditional Performance Measures for VBM Scopes.............................................................................................. 29

2.2.2 Introduction to Common Value-Based Performance Measures ..... 30 2.2.3 Evaluation of Metrics Favoring Residual Income Variants............ 39 2.2.4 Widespread Familiarity of Managers with Value-Based

Metrics............................................................................................. 42 2.2.5 Multiple Uses of Value-Based Metrics ........................................... 45 2.2.6 VBM Systems Effectively Addressing Management Decisions..... 53

2.3 The Economic Value Added (EVA®) Concept .......................................... 56 2.3.1 EVA Computation Going Far beyond Subtraction of Equity

Costs ................................................................................................ 56 2.3.2 Accuracy and Complexity of EVA Definition in Practice.............. 62 2.3.3 EVA Applying across Sectors, Business Units, and

Management Functions ................................................................... 64 2.3.4 EVA Perceived as Panacea While Improvements Are Still

Needed............................................................................................. 70 2.4 Summary .................................................................................................... 72

3 Development of New Value-Based Metrics .................. 75

3.1 Distortions of Residual Income Caused by Accounting Depreciation....... 75 3.1.1 Definition and Relevance of Age Bias............................................ 75 3.1.2 Pervasiveness of Age Bias under Varying Cases............................ 77

3.2 Adjustment Techniques Using Figurative Economic Depreciation........... 84 3.2.1 Available Metrics Replacing Book Depreciation ........................... 84 3.2.2 Insufficient Advantages of Depreciation-Adjusted Metrics ........... 96

3.3 Introduction of New Value-Based Metrics Using Economic Depreciation98 3.3.1 Definition of CRI and CEVA as New Depreciation-Adjusted

Metrics............................................................................................. 98 3.3.2 Advantages of CRI and CEVA versus Common VBM Metrics... 104

3.4 Summary .................................................................................................. 105

4 Applied Methods for the Empirical Research ........... 107

4.1 Review of Prior Value-Relevance Research ............................................ 107

List of Contents XIII

4.1.1 Empirical Studies Relating Accounting Performances to Market Value................................................................................. 108

4.1.2 Empirical Studies Relating Accounting Performances to Stock Returns........................................................................................... 113

4.1.3 Gaps in Previous Studies............................................................... 119 4.2 Development of the Empirical Study Design........................................... 122

4.2.1 Research Hypotheses..................................................................... 122 4.2.2 Regression Models Relating Performance to Market Value and

Returns........................................................................................... 124 4.2.3 Relative and Incremental Information Content Tests ................... 131 4.2.4 Sample Selection Process Gaining Panel Data ............................. 134 4.2.5 Definition of Independent and Dependent Variables.................... 137

4.3 Summary .................................................................................................. 149

5 Results............................................................................ 151

5.1 Case Study................................................................................................ 151 5.1.1 Accounting-Based Measures of Shareholder Value Creation....... 152 5.1.2 Market-Based Measures of Shareholder Value Creation.............. 169 5.1.3 Examination of Interrelationships ................................................. 171

5.2 Regression Analysis ................................................................................. 173 5.2.1 Descriptive and Correlations Statistics ......................................... 173 5.2.2 Relative Information Content: Apparent Predominance of

Earnings......................................................................................... 175 5.2.3 Incremental Information Content: Importance of Earnings’

Accruals......................................................................................... 183 5.3 Summary .................................................................................................. 188

6 Discussion ...................................................................... 191

6.1 Implications .............................................................................................. 191 6.2 Limitations................................................................................................ 192 6.3 Outlook..................................................................................................... 193

References ........................................................................... 195

Appendix ............................................................................. 209

List of Figures

Figure 1 Structure of the Study................................................................................. 11 Figure 2 Shareholder Value Network ....................................................................... 17 Figure 3 Value-Based Management (VBM) Pyramid .............................................. 19 Figure 4 Cycle of Value Creation for Shareholders ................................................. 21 Figure 5 Definitions of Corporate Responsibility .................................................... 26 Figure 6 Qualitative Characteristics of Common Performance Metrics .................. 41 Figure 7 Value-Based Metrics Used by German VBM Firms ................................. 43 Figure 8 Value-Based Metrics Used by U.S. VBM Firms ....................................... 44 Figure 9 Usage of VBM Metrics by Corporate Area ............................................... 46 Figure 10 Usage of VBM Metrics for Compensation and Promotion........................ 47 Figure 11 Key Characteristics of Economic Value Added (EVA)............................. 57 Figure 12 EVA Calculations from Financing and Operating Perspectives ................ 61 Figure 13 Illustrative EVA Value Driver Tree ........................................................... 66 Figure 14 Market Value Added (MVA) Calculation.................................................. 69 Figure 15 Age Bias of RI – Constant Cash Flows...................................................... 78 Figure 16 Age Bias of RI – Cash Flow Changes by Fixed Amount .......................... 80 Figure 17 Age Bias of RI – Cash Flow Changes by Fixed Factor ............................. 82 Figure 18 Outline of (Depreciation-Adjusted) VBM Metrics .................................... 93 Figure 19 Robustness Test of (Depreciation-Adjusted) VBM Metrics ...................... 95 Figure 20 Assessment of Depreciation-Adjusted VBM Metrics................................ 98 Figure 21 Characteristics of Reference Studies Compared to the Present Study..... 121 Figure 22 Decomposition of Newly Introduced CRI and CEVA Metrics ............... 133 Figure 23 Sample Composition ................................................................................ 135 Figure 24 Case Study - Cash Flow from Operations................................................ 152 Figure 25 Case Study - Comparison of Cash Flow and Earnings ............................ 153 Figure 26 Case Study - Comparison of Earnings and Residual Income .................. 154 Figure 27 Case Study - Comparison of RI and EVA................................................ 161 Figure 28 Case Study - Comparison of RI and CRI ................................................. 165 Figure 29 Case Study - Comparison of RONA and ROGA ..................................... 166 Figure 30 Case Study - Comparison of EVA and CEVA......................................... 168

XVI List of Figures

Figure 31 Case Study - Comparison of ROCE and CROCE.................................... 169 Figure 32 Case Study - Relation of Accounting Metrics to Market Performance ... 172

List of Tables

Table 1 Common Uses of Value-Based Performance Measures ............................ 45 Table 2 Outline of Value-Based Performance Rankings ........................................ 52 Table 3 Evidence on the Association of VBM Adoption with Firm Performance . 53 Table 4 Performance Improvements of RI

– Constant Cash Flows ............................................................................... 79 Table 5 Performance Improvements of RI

– Cash Flows Increasing by Fixed Amount ............................................... 81 Table 6 Performance Improvements of RI

– Cash Flows Increasing by Fixed Factor .................................................. 83 Table 7 Summary of EVA and ROCE Calculation................................................. 85 Table 8 Summary of CVA and CFROI Calculation................................................ 86 Table 9 Summary of ‘Revised’ EP and ROIC Calculation ..................................... 89 Table 10 Summary of EP and EM Calculation ......................................................... 90 Table 11 Summary of ‘Revised’ EVA and ROCE Calculation ................................ 92 Table 12 Studies Relating Performance Measures to Firm Value .......................... 109 Table 13 Studies Relating Performance Measures to Stock Returns ...................... 114 Table 14 Campbell Soup Corp.: Residual Income (in m USD) .............................. 154 Table 15 Campbell Soup Corp.: Economic Value Added (in m USD)................... 155 Table 16 Campbell Soup Corp.: Conceptual EVA Adjustments (in m USD) ........ 156 Table 17 Campbell Soup Corp.: US-GAAP EVA Adjustments (in m USD) ......... 158 Table 18 Campbell Soup Corp.: Weighted Average Cost of Capital (in m USD).. 160 Table 19 Campbell Soup Corp.: Economic Depreciation (in m USD) ................... 163 Table 20 Campbell Soup Corp.: Cash Residual Income (in m USD) ..................... 164 Table 21 Campbell Soup Corp.: Cash Economic Value Added (in m USD).......... 167 Table 22 Campbell Soup Corp.: Market Value of the Firm (in m USD)................ 170 Table 23 Campbell Soup Corp.: Abnormal Stock Returns (in m USD) ................. 170 Table 24 Descriptive and Correlation Statistics Based on Firm Value................... 173 Table 25 Descriptive and Correlation Statistics Based on Stock Returns............... 174 Table 26 Relative Information Content Tests from Associations with Firm Value 175 Table 27 Sensitivity Tests on Associations of Metrics with Firm Value................ 177

XVIII List of Tables

Table 28 Relative Information Content Tests referring to Stock Returns............... 179 Table 29 Sensitivity Tests on Associations of Metrics with Stock Returns............ 181 Table 30 Incremental Information Content Tests referring to Firm Value ............. 184 Table 31 Sensitivity Tests on Associations of Components with Firm Value........ 185 Table 32 Incremental Information Content Tests referring to Stock Returns......... 186 Table 33 Sensitivity Tests on Associations of Components with Stock Returns.... 187 Table 34 Used NOPAT Calculation Methodology ................................................. 209 Table 35 Used Capital Calculation Methodology ................................................... 210 Table 36 List of Firms Contained in the Sample..................................................... 215 Table 37 Relative Information Content Tests from Associations with Firm Value

– Including Outliers.................................................................................. 216 Table 38 Relative Information Content Tests referring to Stock Returns

– Including Outliers.................................................................................. 216 Table 39 Incremental Information Content Tests referring to Firm Value

– Including Outliers.................................................................................. 217 Table 40 Incremental Information Content Tests referring to Stock Returns

– Including Outliers.................................................................................. 217

Abbreviations

AccAdj Accounting adjustments Accr Accruals ADA Accumulated depreciation and amortization AR (Market-adjusted) abnormal stock returns ATInt After-tax interest AV Added value BCG Boston Consulting Group BV Book value of net assets CapChg Capital charge CAPM Capital asset pricing model CEBI Cash earnings before interest CEVA Cash economic value added CIP Construction in progress CFO Cash flow from operations CFROI Cash flow return on investment COPAT Cash operating profits after taxes CRI Cash residual income CROCE Cash return on capital employed CV Corporate value CVA Cash value added DA Depreciation and amortization DCF Discounted cash flow DD Double declining balance depreciation method Dep (Accounting) depreciation DepAdj1 Depreciation adjustment (including goodwill amortization) DepAdj2 Depreciation adjustment (excluding goodwill amortization) EBEI Earnings before extraordinary items ED Economic depreication EM Economic margin EOY End of year balance EP Economic profit ESOP Employee stock ownership plan EVA Economic value added FCF Free cash flow FGV Future growth value GA Book value of gross assets GDA Gross book value of depreciable assets GI (Inflation-adjusted) gross investments

XX Abbreviations

GIC Gross invested capital IC Invested capital IFRS International financial reporting standards IntExp Interest expense IRR Internal rate of return LIFO Last-in-First-out MV Market value of the firm MVA Market value added MVE Market value of common equity NA Book value of net assets NDA Non-depreciable assets NEBI Net earnings before interest NI Net investments NIBCLs Non-interest bearing current liabilities NOPAT Net operating profits after taxes NOPLAT Net operating profits less adjusted taxes OCF Operating cash flows OGCF Operating gross cash flows OPAT Operating profits after taxes PI Performance improvement R&D Reasearch and development REVA Refined economic value added RI Residual income ROCE Return on capital employed ROGA Return on gross assets ROIC Return on invested capital RONA Return on net assets RR (Unadjusted) raw stock returns S/L Straight-line depreciation method SoY Sum-of-the-years-digits depreciation method SS Stern Stewart & Company SVA Shareholder value added TBR Total business return TCO Total cost of ownership TSR Total shareholder return US-GAAP United States generally accepted accounting principles VBM Value-based management WACC Weighted average cost of capital WAI Wealth added index

Symbols

Beta factor of the share used within the CAPM i Regression coefficient

C Incremental unique information component D/E Dept-to-equity ratio Constant parameter from a discrete linear stochastic process

r Risk-adjusted discount rate E Future performance expectation Random disturbance term

FEX Forecast error for a performance measures X M Arithmetic mean

Autoregressive parameter from a discrete linear stochastic process P Stock price R Stock returns r Risk-adjusted rate rd Cost of debt re Cost of equity rf Risk-free rate of return ri Stock return of firm i rm Market-wide rate of return rS Pearson product-moment correlation coefficient SD Standard deviation t Tax rate T Total useful life of an investment T* Remaining useful life of an investment wd Capital weight of debt capital we Capital weight of equity capital X Accounting-based measure of firm performance

1 Introduction

Substantial pressure to maximize shareholder wealth compels firms to adopt a value-based management system. As centerpiece of such a system, a value-based performance measure quantifies periodic value addition for shareholders. Prevalent value-based measures imply distortions from accounting depreciation and empirical evidence on prevailing measures is somewhat biased. Consequently, this study aims to develop depreciation-adjusted performance measures and to provide empirical evi-dence on prevailing and newly introduced measures. Specifically, this study concludes examining the relationship between bottom-line accounting measures of corporate performance with stock prices. However, in a broader sense, it also relates to strategic management and key drivers and dynamics of capital markets.

In the following, the underlying rationales are first presented and, afterwards, the objectives and the structure of the present study.

1.1 Motivation

1.1.1 Inadequacy of Performance Measures

This study refers to the basic concept of various value-based management systems, i.e., to consider maximization of shareholder value as main (when not even the only) overall corporate objective. Value-based management systems gained predominance in the 1990s and still prevail today. 1 At the core of an integrated value-based management system, periodical performance measures, based on financial statutory accounts or interim results, quantify management’s additions to shareholder wealth and constitute the main reference for addressing decision making processes in all main financial, operating and general management activities, such as strategic planning, capital budgeting, acquisition pricing, performance measurement, internal communication, investor relations, and management compensation.2

External accountability of a value-based performance measure is essential. Only measures based on official financial data, publicly accessible, and on objective and 1 See section 2.1.1. 2 See Chew, Stern, and Stewart (1996) and O'Byrne and Young (2001, p. 18).

2 1 Introduction

consistent methodologies can be used effectively by and communicated to the financial community, shareholders, and other stakeholders, to monitor management performance, assess investment and evaluate corporate value creation. At a first glance, stock prices, earnings, residual income, and economic value added, may be valid measures of the overall corporate performance. However, all these measures involve some problems and deficiencies for properly representing and quantifying shareholder value creation.

The change in stock price is the most obvious measure of added shareholder wealth. However, such market-derived measure is primarily driven by economy- and industry-wide factors beyond the control of management and other factors unrelated to the operating performance of the firm, such as noise trading and portfolio insurance.3 Consequently, market-based stock returns constitute only indirect and often inappropriate value-based performance measures.

Among accounting measures, management normally considers net earnings as key performance indicator, responding to investors, who are primarily concerned about long-term earnings and use earnings as main input for valuation models.4 Focus on earnings contradicts valuation theory, which assumes that expected future free cash flows determine stock price, and, thus, shareholder value.5 Nonetheless, earnings pre-vail even after the introduction of the statement of cash flows in 1987, since the investment community continues to believe that earnings are a better indicator of a firm’s present and future ability to generate free cash flows than cash flow informa-tion.6 However, net earnings do not accurately measure changes in shareholder wealth: Positive earnings may imply positive or negative addition to shareholders’ net worth, depending on the amount of equity costs.

Accordingly, ‘Residual Income’ (RI), defined as net earnings after the cost of debt and equity capital, represents an alternative accounting estimate, overcoming some defect of net earnings. Since RI includes charges for the cost of equity, realizing that equity capital has to be remunerated, it is a superior method compared to net earnings in describing changes in shareholder wealth. For centuries, economists used RI to describe the value creation of the firm as excess return after return expectations of investors given the systematic risk class of the firm’s debt and equity capital. 7 However, RI was not considered until the twentieth century.8 Further, only few large firms adopted RI for internal performance management or external reporting before 3 See Jensen and Murphy (1990) and Milbourn (1996). 4 See Foster (1986) and Lev (1989) for the predominance of earnings and the price-earnings ratio. 5 See section 4.2.2. 6 Introduction of the cash flow statement following FASB Statements of Standards No. 95, 1987;

further, FASB's Statement of Financial Accounting Concepts No. 1, 1978, underlines the prevalence of earnings.

7 E.g., Hamilton (1777); equivalently, Marshall (1890, p. 142): “What remains of his profits after deducting interest on his capital at the current rate may be called his earnings of undertaking or management.”

8 See Canning (1929), Edey (1957), Edwards and Bell (1961), Kay (1976), Peasnell (1981, 1982), and Preinreich (1936, 1937, 1938).

1.1 Motivation 3

the emergence of value-based management, such as General Motors in the 1920s and General Electric in the 1950s.9 However, also RI does not measure shareholder value creation accurately, since it is affected by several non-cash accruals and other accounting principles.

Consequently, several variants of RI, adjusting for such distortions, have been developed by business consultancies. 10 Among those, ‘Economic Value Added’ (EVA), developed by Stern Stewart & Company, prevails. The measure has been first mentioned in 1989.11 By 1998, EVA has yet become a leading management tool.12 Its popularity is attributable to a supporting press coverage, enthusiastic corporate spon-sors, and bold claims by Stern Stewart & Company, as follows: First, extensive press coverage created broad awareness of the EVA concept in the business and investment community. E.g., Fortune magazine and the Journal of Applied Corporate Finance praised EVA as outstanding measure and published annual EVA league tables. 13 Second, well-known firms, which adopted EVA and publicly commented on their satisfaction, built further trust in EVA; moreover, managers commonly reported that EVA adoption motivated them to optimize capital utilization and, consequently, increase shareholder value. 14 In addition, major financial management firms and investment banks such as Calpers, Oppenheimer, Credit Suisse First Boston, and Goldman Sachs reported to use EVA-based equity pricing models. 15 Third, Stern Stewart’s bold claims stating that EVA explains stock prices considerably better than earnings drew practitioners’ and researchers’ attention. 16 Despite its recognition among practitioners, EVA involves two major flaws:17 The first major flaw refers to application of book capital rather than market values for calculating the capital charge 9 See Stern (1994). 10 Value-based performance measures, marketed by other consultancies such as Marakon Associates,

Monitor, Boston Consulting Group, HOLT Value Associates, Alcar, or KPMG, differ by name, but all refer to the RI concept.

11 See Finegan (1991); EVA® is a trademark of Stern Stewart & Company. 12 As identified by Michael C. Jensen, see Tully (1998). 13 E.g., in the first Fortune magazine article on EVA, Tully (1993) describes EVA as “real key to

creating wealth” and "today's hottest financial idea and getting hotter". 14 E.g., Coke stated that “EVA forces you to find ingenious ways to do more with less capital”

(Tully, 1993, p. 48). Coke CEO Goizueta further said: “It’s the way to keep score. Why everybody doesn’t use it is a mystery to me.” (Ross, 1996, p. 107).

15 See Tully (1998); most prominently, Credit Suisse First Boston supported EVA, stating “At CS First, we use EVA as our primary equity valuation tool because it works”, (see advertisement of Stern Stewart & Company, in: Fortune, 1997, January 13, p. 10)

16 "The theory and the evidence all point to the same fundamental conclusion: increasing EVA should be adopted as the paramount objective of any company that professes to be concerned about maximizing its shareholders' wealth." (G. B. Stewart, 1990). “Abandon earnings per share” (Stewart, 1991, p. 2). “The best practical periodic performance measure is economic value added (EVA)” (Stewart, 1991, p. 66). “Earnings, earnings per share, and earnings growth are misleading measures of corporate performance” (G. B. Stewart, 1991, p. 66). “Forget EPS, ROE and ROI, EVA is what drives stock prices” (see advertisement of Stern Stewart & Company, in: Harvard Business Review, 1995, November-December, p. 20).

17 See Tham (2001c); notably, flaws apply identically to the basic RI measure.

4 1 Introduction

for debt and equity capital and has yet been resolved by a modified EVA measure called ‘Refined Economic Value Added’ (REVA).18 The second identified flaw relates to the dependence of EVA on book depreciation schedules: Straight-line or accelerated book depreciation is front-end loaded, ignoring the time value of money.19

In particular, for new investments, straight-line book depreciation leads to relatively low EVA in the first years and a growing profile in the following years. For this reason, straight-line book depreciation penalizes the apparent EVA performance of companies with a high growth momentum of the capital employed (and the opposite occurs in companies with a low investment rate and having most of the assets almost fully depreciated - cash cows). Overcoming such distortions from accounting deprecia-tion is central, since biased EVA implies difficulties for management and investors, as follows: EVA provides underinvestment incentives to management, referred to as ‘old plant / new plant trap’, since also significant value-adding investments provide less favor-able EVA than retention of old assets.20

EVA involves external communication hurdles to management if, despite the ‘old plant /new plant trap’, management conducts significant value-adding investments, because deteriorated EVA performance suggests that management destroyed shareholder value.

EVA is not comparable for firms using different depreciation methods. EVA favors equity investments in firms with a relatively old asset base, showing relatively high levels of EVA. Common value-based performance measures that do not account book depreciation,

such as ‘Cash Value Added’ or ‘Economic Margin’, generally involve complex computations, adjustments not easy to understand, arbitrary judgments, and/or interpretation difficulties, constituting a major hurdle for external application. 21 Therefore, in 2005, EVA still prevailed as gold standard, measuring value creation for performance monitoring, investor relations, and investment analysis.22 Nevertheless, bias of EVA due to accounting depreciation remains still a major problem.

18 See Bacidore, Boquist, Milbourn, and Thakor (1997). 19 See section 3.1. 20 Empirical studies examining managerial behavior under EVA or similar concepts, e.g., Biddle,

Bowen, and Wallace (1999) and Kleiman (1999), provide evidence for implicit divestment incentives.

21 E.g., CFROI estimates for the Cash Value Added are rather complex, see O'Byrne and Young (2001, p. 407); alternatively, Cash Value Added, following Ottosson and Weissenrieder (1996) and Weissenrieder (1997, p. 5), requires subjective classification of strategic and non-strategic investments; Economic Margin, following Obrycki and Resendes (2000), involves subtraction of a combined charge for cost of capital and depreciation. For a more detailed discussion of depreciation-adjusted measures, see section 3.2.1.

22 See Stewart (2005).

1.1 Motivation 5

1.1.2 Inconsistencies and Deficiencies of Prior Empirical Studies

In today’s competitive environment, value-relevance of a performance measure, i.e., the empirical evidence that the measure is driving stock prices, serves as important argument to adopt a measure for value-based investor communication and performance monitoring. Regarding this, Stern Stewart heavily promoted EVA as being by far superior to earnings in explaining stock prices.16 Consequently, researchers extended value-relevance research to include EVA, to examine the accuracy of Stewart’s claims.23

Testing the value-relevance of performance measures involves relating accounting performance to the market value of the firm and to stock returns.

The former approach derives from financial theory, which suggests that expected future residual income (or EVAs) explain market value. 24 Accordingly, studies conducted by Stern Stewart always relate EVA to market value.25

However, most stock valuation models used by equity analysts are mainly focused on stock returns.26 Additionally, accounting research has widely adopted stock return as criterion for evaluating the information ‘usefulness’ of performance measures.27 Starting in the 1960s, studies examined the association of accounting earnings with stock returns, based on the fact that (expected) earnings are of particular interest to investors.28 Since then, assessment of earnings usefulness became a major objective of accounting research, representing “the most concerted research effort in accounting history”.29 Associations with stock prices are used as operational test of usefulness, since theory suggests that capital markets are efficient and unbiased.30 Research on earnings showed that associations with returns are persistently weak. 31 In the late 1980s, usefulness studies started to examine cash flows, while RI or RI variants did not yet gain any attention.32

Value-relevance research on EVA started with a correlation analysis on EVA and market value, conducted by Stern Stewart in 1991 to substantiate the predominance of

23 See section 4.1. 24 See section 4.2.2. 25 See Finegan (1991), O’Byrne (1996), and Stewart (1991); notably, they relate EVA to market

value less book value of capital, referred to as ‘Market Value Added’ (MVA), since theory suggests that market value equals the sum of book value and present value of future RIs.

26 See Foster (1986) and Lev (1989). 27 See Biddle, Bowen, and Wallace (1997), Cheng, Cheung, and Gopalakrishnan (1993), Easton and

Harris (1991), Jacobson (1987), and Lev (1989). 28 See Ball and Brown (1968) and Beaver (1968). 29 See Lev (1989, p. 153). 30 See Ball and Brown (1968, pp. 160-161). 31 See Ball and Brown (1968), Beaver (1968), and Lev (1989). 32 Research commonly examined usefulness of cash flows (see Bernard & Stober, 1989; R. M.

Bowen, Burgstahler, & Daley, 1987; Rayburn, 1986; G. P. Wilson, 1986, 1987).