© Baruch Lev, April 2003. All Rights Reserved.

ACCOUNTING FOR ACCOUNTING FOR INTANGIBLESINTANGIBLES

ByBaruch Lev

New York UniversityTel: 212-998-0028

Email: blev@stern.nyu.eduWeb: www.baruch-lev.com

This presentation, or any part of it, should not be reproduced, or otherwise used in any form without Baruch Lev’s written permission.

© Baruch Lev, April 2003. All Rights Reserved. 2

AT A GLANCE Intangible Assets are the Major Drivers of

Corporate Value and Growth.

The Economics of Intangibles: Value-Drivers and Value-Detractors.

Intangibles Challenge Investor Valuations.

© Baruch Lev, April 2003. All Rights Reserved. 3

AT A GLANCE - Continued

The Traditional Accounting System is of Little Help in Monitoring and Accounting for Intangibles, and in Providing Useful Information to Investors.

Despite Widespread Disbeliefs, Accounting Data Can be Adjusted, to Better Reflect Value, and Intangibles Can Be Valued.

Source: Testimony before the Committee on Financial Services, U.S. House of Representatives, February 27, 2002.

4

Alan Greenspan

From one perspective, the ever-increasing proportion of our GDP that represents conceptual as distinct from physical value added may actually have lessened cyclical volatility. In particular, the fact that concepts cannot be held as inventories means a greater share of GDP is not subject to a type of dynamics that amplifies cyclical swings. But an economy in which concepts form an important share of valuation has its own vulnerabilities.

 As the recent events surrounding Enron have highlighted, a firm is inherently fragile if its value added emanates more from conceptual as distinct from physical assets. A physical asset, whether an office building or an automotive assembly plant, has the capability of producing goods even if the reputation of the managers of such facilities falls under a cloud. The rapidity of Enron's decline is an effective illustration of the vulnerability of a firm whose market value largely rests on capitalized reputation. The physical assets of such a firm comprise a small proportion of its asset base. Trust and reputation can vanish overnight. A factory cannot.

I. What They Say

Source: Leonard Nakamura, " A Trillion Dollars a Year in Intangibles Investment and the New Economy," 2001.

5

Leonard Nakamura

I argue that U.S. private gross investment in intangibles is at least $1 trillion. Most of this investment goes uncounted. This is not surprising, in that it is new: the rate of investment in intangibles, and its economic value, accelerated significantly beginning around 1980.

An intangibles investment rate of $1 trillion suggests that U.S. businesses are investing nearly as much in intangibles as they are in plant and equipment.

If we are investing $1 trillion a year in intangibles…then the long-run equilibrium value of intangibles is $6 trillion.

Source: Factset 6

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

Month

Market-To-Book

S&P 500 Average Market-To-Book Ratio: 1995-2002

© Baruch Lev, April 2003. All Rights Reserved. 7

II. WHAT ARE INTANGIBLES?

I. DEFINITIONIntangible assets are sources of future benefits which do not have a physical embodiment.

II. THE MAJOR CATEGORIES OF INTANGIBLESDiscovery/Learning: New products, services, patents, communities

of practice, Intranet, adaptive capacity.

Customers: Brands, trademarks, on-line distribution channels,marketing alliances.

Human Resources: Work and compensation practices, employee training, incentives.

Organizational Structure: Business structures and processes, incentive systems, information and control systems.

III. ALLIANCES PREVALENT IN DISCOVERY/LEARNING AND CUSTOMERS INTANGIBLES

© Baruch Lev, April 2003. All Rights Reserved. 8

MANAGERIAL AND INVESTOR CHALLENGES

Non-Tradeablility No exit strategy Absence of

comparables Absence of

futures markets

Information Challenged Insufficient

performance data Missing input-

output linkages Non-standardized

measures

Partial Excludability

Value dissipates Hazy property

rights Alliance partners

capture IP

High Risks

Sunk costs Technology and

commercial uncertainty

© Baruch Lev, April 2003. All Rights Reserved. 9

Merck & Co.: Return on Equity (ROE) Based on Expensing (top curve) and Capitalization

(bottom curve) of R&D

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.55

0.6

0.65

1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991

Year

RO

E

Source: "Managing an Alliance Portfolio," MckInsey Quarterly, 2002 Number 3. 10

A MAJOR PROBLEM: MONITORING ALLIANCES

“Most large companies now have at least 30 alliances, and many have more than 100. Yet despite the ubiquity of alliances—and the considerable assets and revenues they often involve—very few companies systematically track their performance. Doing so is not a straightforward task… Our experience suggests that fewer than one in four has adequate performance metrics… Few Senior management teams know whether the alliance portfolio as a whole really supports corporate strategy.”

© Baruch Lev, April 2003 All Rights Reserved. 11

III. Mismeasurement & Biased Reporting of IntangiblesThe myth of conservative accounting:

Mismeasurements of Assets and Income of Intangibles-Intensive Enterprises.

Endogenous Software Capitalization: Computer Associates-Yes; Microsoft-No.

Asymmetric Accounting: Expense Internally-Generated Intangibles, Capitalize Acquired Intangibles.

© Baruch Lev, April 2003. All Rights Reserved. 12

Mismeasurement and Biased Reporting of Intangibles - Continued

Manipulation with In-Process R&D.

Manipulation with R&D Expenditures (and Other Intangibles?).

Reporting Opaqueness: No Information on Employee Training, Brand Enhancement, Software and Technology Acquisitions, R&D Breakdowns, Innovation Revenues, etc., etc.

The Myth of Enron, Global Crossing and Winstar Being Intangibles-Intensive.

© Baruch Lev, April 2003. All Rights Reserved. 13

IV. Overcoming Accounting Limitations

Capitalizing Intangibles.

Forming Investment Strategies From Intangibles’ Values.

Source: Lev, Nissim, Thomas. 2001. "On the Informational Usefulness of R&D Capitalization." 14

Table 1Descriptive Statistics

Panel A: Distribution of R&D intensity by industry*

Industry (abbreviation; SIC) Obs. Mean SD Median Chemicals and Pharmaceutics (Chem.; 28) 2,981 0.0423 0.0655 0.0272 Fabricated Metal (Fab.; 34) 1,431 0.0262 0.0653 0.0075 Machinery and Computer Hardware (Mach.; 35) 3,803 0.0929 0.2081 0.0423 Electrical and Electronics (Elec.; 36) 4,311 0.0836 0.1526 0.0411 Transportation Vehicles (Trans.; 37) 1,354 0.0454 0.0687 0.0203 Scientific Instruments (Scient.; 38) 3,400 0.0930 0.1405 0.0552 Business Services (Bus.; 73) 3,223 0.0659 0.1887 0.0013 Total 20,503 0.072 0.153 0.032 Panel B: Observations by industry and year (subsequent returns analysis)

Year Chem. Fab. Mach. Elec. Trans. Scient. Bus. Total 1983 119 79 152 172 68 119 83 792 1984 135 84 178 198 81 139 106 921 1985 126 81 173 185 76 138 104 883 1986 122 73 163 181 71 130 99 839 1987 116 72 169 183 69 128 98 835 1988 116 74 154 188 64 138 103 837 1989 114 71 157 178 62 138 108 828 1990 124 67 172 184 63 154 115 879 1991 135 66 179 197 67 166 134 944 1992 142 67 185 193 69 172 139 967 1993 160 75 190 202 68 178 171 1044 1994 170 72 194 223 70 190 183 1102 1995 173 68 194 232 71 183 184 1105 1996 179 65 197 242 74 188 192 1137 1997 180 62 195 242 69 190 187 1125 1998 185 61 184 228 66 192 187 1103

Total 2296 1137 2836 3228 1108 2543 2193 15341

* R&D Intensity is measured as the ratio of R&D expense to the market value of equity at the end of the fiscal year.

Source: Lev, Nissim, Thomas. 2001. "On the Informational Usefulness of R&D Capitalization." 15

Table 2Analysis of the Change in the Association of Earnings and Book Value with Price from Capitalization and Amortizing

R&D

Panel A: Statistics from the reported numbers regression (T = 0)

P/A =

2000

1983yy1yDβ + 2 1/A + 3 B0/A + 4 E0/A + 5 DNE E0/A + 6 DNE +

Chem. Fab. Mach. Elec. Trans. Scient. Bus.

1/A 0.090 1.583 1.071 0.022 0.070 0.440 0.968

0.330 9.222 6.929 0.132 0.183 2.285 5.399

B0/ A 2.056 0.568 1.168 1.130 0.963 1.389 1.309

17.303 7.546 16.358 14.669 12.540 14.667 14.160

E0/ A 8.789 7.341 6.304 7.708 8.661 4.581 10.688

15.271 15.289 16.410 20.504 20.024 10.350 19.870

DNE E0/ A

-13.918 -11.630 -8.634 -10.071 -9.976 -7.534 -13.623

-22.056 -21.249 -21.041 -24.621 -18.749 -15.108 -24.083

DNE 0.002 -0.223 -0.063 0.054 0.092 0.094 0.037

0.017 -3.899 -1.134 0.904 1.561 1.091 0.453

R2

0.268 0.418 0.226 0.250 0.458 0.164 0.284

N 2981 1431 3803 4311 1354 3400 3223

Source: Lev, Nissim, Thomas. 2001. "On the Informational Usefulness of R&D Capitalization." 16

Panel B: Percentage increase in R2 relative to T = 0

T Chem. Fab. Mach. Elec. Trans. Scient. Bus.

1 7.950 1.198 4.457 3.983 1.169 11.743 4.087 2 14.921 2.175 7.433 7.393 2.175 18.130 5.895 3 19.621 2.823 9.408 9.637 2.839 20.441 6.891 4 23.392 3.377 10.205 11.730 3.289 20.910 7.656 5 26.283 3.803 9.808 13.764 3.531 20.584 7.715 6 28.659 3.749 9.186 15.239 3.594 19.638 7.074 7 30.590 3.474 8.552 16.185 3.496 18.505 6.004 8 32.283 3.346 8.123 16.706 3.168 17.351 4.803

Panel C: Test statistic (standard normal) for the change in R2

T Chem. Fab. Mach. Elec. Trans. Scient. Bus. 1 7.322 1.597 4.223 4.316 2.689 2.435 3.309 2 7.948 1.695 4.272 5.797 2.902 2.544 3.210 3 8.035 1.738 4.247 6.224 2.823 2.615 3.155 4 8.209 1.747 3.960 5.918 2.725 2.560 3.171 5 8.169 1.619 3.471 5.062 2.583 2.447 2.977 6 8.086 1.500 3.061 4.361 2.432 2.288 2.563 7 7.965 1.432 2.651 3.902 2.244 2.116 2.051 8 7.838 1.333 2.294 3.564 1.941 1.949 1.558

Source: Lev, Nissim, Thomas. 2001. "On the Informational Usefulness of R&D Capitalization." 17

Panel D: Statistics from the “optimal” regression

P/A =

2000

1983yy1yDβ + 2 1/A + 3 BT*/A + 4 ET*/A + 5 DNE ET*/A + 6 DNE +

Chem. Fab. Mach. Elec. Trans. Scient. Bus.

1/ A 0.233 1.541 1.057 -0.031 0.253 0.441 1.111

0.905 9.095 6.933 -0.198 0.673 2.338 6.285

B0/ A 2.220 0.643 1.117 1.028 0.970 1.384 1.227

24.023 8.575 17.525 16.903 12.845 15.761 14.904

E0/ A 10.459 7.087 6.743 8.760 8.402 6.918 11.061

19.549 15.066 18.825 26.113 20.592 15.247 22.588

DNE E0/ A -13.581 -11.308 -8.671 -10.379 -9.522 -9.356 -13.404

-22.300 -21.049 -22.341 -27.519 -18.699 -18.383 -25.532

DNE 0.480 -0.218 0.030 0.272 0.136 0.367 0.208

4.808 -3.868 0.555 4.645 2.350 4.277 2.578

R2

0.355 0.434 0.249 0.292 0.475 0.198 0.306

N 2981 1431 3803 4311 1354 3400 3223 Panel E: Mean (first row) and standard deviation (second row) of the “optimal” book value and earnings adjustments Chem. Fab. Mach. Elec. Trans. Scient. Bus.

BT*/ A – B0/ A 0.1246 0.0189 0.0729 0.1329 0.0408 0.0954 0.0892

0.1692 0.0323 0.0847 0.1574 0.0493 0.0868 0.1444

ET*/ A – E0/ A 0.0111 0.0002 0.0031 0.0082 0.0026 0.0058 0.0052 0.0334 0.0083 0.0232 0.0296 0.0107 0.0332 0.0345

P is market value of common equity, A is total assets, Dy is a dummy variables that equals one for year y, BT (ET) is pro-forma

book value (earnings) assuming T years useful R&D life (hence T = 0 implies the reported book-value and earnings), and DNE is a

dummy variable that equals one when pre-R&D earnings are negative. Panel B reports the percentage change in R2 (relative to the

benchmark T = 0 regression) from using earnings and book value that have been adjusted to reflect R&D capitalization and

amortization over the subsequent T years. The test statistics in Panel C are calculated as (N.5 mean[r02 – rT

2]) / std[r02 – rT

2], where

N is the number of observations, r0 is the residual from the benchmark regressions, and rT is the residual from the adjusted earnings

and book value regression. The test statistics have a limiting standard normal distribution. T* denotes the value of T that maximizes

the percentage change in R2 (identified in panel B using bold font).

© Baruch Lev, April 2003. All Rights Reserved. 18

Cisco SystemsR&D Capitalization and Amortization

($millions)I. R&D Amortization for 2002 and 2001: Based on Table 2, Cisco’s

R&D life is four years (25% annual amortization).

Vintage/Year

R&D Expense

2002 Amortization

2001 Amortization

2002 $3,448 -- -- 2001 3,922 $980 -- 2000 2,704 676 $676 1999 2,065 516 516 1998 1,614 403 403 1997 1,207 -- 302 Annual Amortization 2,575 1,897

Original Expense 3,448 3,992

II. Adjusted Earnings

2002 2001

Reported Earnings 1,893 (1,014) Add: R&D expense 3,448 3,922 Subtract: R&D amortization (2,575) (1,897) Adjusted earnings 2,766 1,011

© Baruch Lev, April 2003. All Rights Reserved. 19

III. Adjusted Book Value (equity) 2002 2001

Reported 28,656 27,120

R&D Vintages: Current year 3,448 3,922 Year -1 2,941 2,028 Year -2 1,352 1,032 Year -3 516 403 Year -4 0 0 R&D Capital 8,257 7,385

Adjusted book value 36,913 34,505

IV. Return on Equity 2002

1,893

Reported (28,656+27,120)/2

= 0.068

2,766

Adjusted (36,913+34,505)/2

= 0.077

© Baruch Lev, April 2003. All Rights Reserved. 20

V. Earnings Growth

Reported: Undefined

Adjusted: (2,766-1,011)/1,011 = 174%

VI. BVDIST(Book Value Distortion)

1.117x(36,913/46,052-28,656/46,052) = 0.201

Source: Lev, Nissim, Thomas. 2001. "On the Informational Usefulness of R&D Capitalization." 21

Figure 2: Cumulative Abnormal Returns (CAR) to BVDIST Portfolios

-0 .2

-0 .1 5

-0 .1

-0 .0 5

0

0 .0 5

0 .1

0 .1 5

0 .2

1 3 5 7 9 1 1 1 3 1 5 1 7 1 9 2 1 2 3 2 5 2 7 2 9 3 1 3 3 3 5

M on th

CAR

p o rt. 1 ( lo w B V D IS T )

p o rt. 2

p o rt. 3

p o rt. 4

p o rt. 5 (h ig h B V D IS T )

Ja n u a

Ja n u a

Ja n u a

Cumulative abnormal return (CAR) is measured as the cumulative sum of the portfolio monthly abnormal returns. Portfolio monthly abnormal return for each of the 36 months is calculated as the average abnormal return for the corresponding month across all firm-year observations that “belong” to the portfolio. Monthly abnormal return is calculated as the difference between the firm’s return and the contemporaneous return on a SIZE and B/M matched portfolio (SIZE and B/M are updated every twelve months).

Baruch Lev, 2002. All rights reserved. 22