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					                               INTANGIBLE ASSETS
                                 Measurement, Drivers, Usefulness



                                                        By



                                       Feng Gu and Baruch Lev*




                                                              Please note: The various intangibles
                                                              value metrics discussed here were
                                                              designed by Baruch Lev who retains
                                                              exclusive rights to the measures, and
                                                              has a patent pending for them. The
                                                              measures should not be used or
                                                              reproduced without a written
                                                              permission from Baruch Lev.




April 2001




*
    Boston University and New York University, respectively


                                                                                                  1
                                INTANGIBLE ASSETS
1.        How are The Intangibles Metrics Computed?

          It is widely accepted that intangible (knowledge or intellectual) assets are the major

drivers of corporate value and growth in most economic sectors, but the measurement of these

assets has eluded so far managers, accountants, and financial analysts valuing investment

projects.

          Why measure intangible assets? Evaluating profitab ility and performance of business

enterprise, by say, return on investment, assets or equity (ROA, ROE) is seriously flawed since

the value of the firm’s major asset— intangible capital—is missing from the denominator of

these indicators. Measures of price relatives (e.g., price-to-book ratio) are similarly misleading,

absent the value of intangible assets from accounting book values. Valuations for the purpose of

mergers and acquisitions are incomplete without an estimate of intellectual capital. Resource

allocation decisions within corporations require values of intangible capital. These and other

uses create the need for valuing intangible assets, in practically all economic sectors.

          Intangible (knowledge) assets, such as new discoveries (drugs, software products, etc.),

brands or unique organizational designs (e.g., Internet-based supply chains) are by and large not

traded in organized markets, and the property rights over these assets are not fully secured by the

company, except for intellectual properties, such as patents and trademarks. The risk of these

assets (e.g., drugs or software programs under development not making it to the market) is

generally higher than that of physical assets. 1        Accordingly, many, particularly accountants and

corporate executives, are reluctant to recognize intangible, or intellectual capital as assets in


1
     See, Baruch lev, Intangibles: Management, Measurement and Reporting, forthco ming fro m Brookings Institution
     Press, June 2001, fo r elaborat ion on the unique attributes of intangibles.


                                                                                                                2
financial reports, on par with physical and financial assets. While such attitude concerning

balance sheets may be understandable, it does not satisfy the need to seek information about and

value of intangible assets.

        Some have attempted to gauge the value of intangible assets from the difference between

the company’s capital market value and its book value (the balance sheet value of net physical

and financial assets). This approach is unsatisfactory because it is based on two flawed

assumptions: (a) that there is no mispricing in capital markets (tell this to investors who bought

Internet stocks in 1999 and saw them plummet in 2000), and (b) that balance sheet historical

values of assets reflect their current values.

        The market- minus-book approach to valuing intangibles is also unsatisfactory because it

is circulatory. One searches for measures of intangibles value in order to provide new

information to managers and investors. What is the use of a measure (market- minus-book) that

is derived from what investors already know (market and book values)? There is obviously a

need for a different approach to estimating the value of intangible assets.

1.      Preliminaries:

        Baruch Lev’s methodology for measuring the value of intangible assets is based on the

economic concept of ―production function,‖ where the firm’s economic performance is

stipulated to be generated by the three major classes of inputs: Physical, financia l, and

knowledge assets. Thus:

Economic Pe rformance = α(Physical Assets) + β(Financial Assets) + δ(Intangible Assets)


α , β and δ represent the contributions of a unit of asset to the enterprise performance.

        A key ingredient in this approach is the definition of an enterprise economic performance

as an aggregate of past core earnings (earnings excluding unusual and extraordinary items), and


                                                                                                     3
future earnings, or growth potential. A performance measure which is strictly based on past

earnings or cash flows, or a modification of earnings (e.g., the various value added measures),

misses a major part of what intangible assets are all about—creating future growth (e.g., by

investment in R&D, Internet activities, or employee training).

       Having thus defined enterprise performance, the next step is the measurement of the

performance drivers—the three major asset groups. The values of physical and financial (stocks,

bonds, financial instruments) assets are obtained from the firm’s balance sheet and footnotes

(with proper adjustments, such as converting accounting historical costs to current values). The

derivation of the value of the third performance driver— intangible capital—is, in a sense, the

solution to the above production function for the one unknown (inta ngible capital). This is done

by estimating the ―normal rates of return‖ on physical and financial assets—the α and β

coefficients in the above production function—and subtracting from the estimated economic

performance of the enterprise the contributions of physical and financial assets, namely the

normal asset returns multiplied by the values of physical and financial assets. What remains

from this subtraction is the contribution of intangible assets to the enterprise performance, which

I define as ―intangibles-driven earnings.‖ Capitalizing the expected stream of these earnings

yields an estimate of ―intangible capital.‖

       The intangibles value measurement procedure is demonstrated graphically in Figure 1.




                                                                                                    4
                           Figure 1

              INTANGIBLE ASSETS
      Past Earnings                   Future Earnings
                             +



                  Normalized Earnings

Subtract:       Return on Physical Assets

Subtract:                Return on
                      Financial Assets

Equal:         Intangibles-Driven Earnings



Capitalize:           Intangible Assets



                                                        5
2.      Specifics:

      The measurement procedure outlined in Figure 1 starts with the estimation of annual

        ―normalized earnings,‖ referred to earlier as the performance of the enterprise, which are

        based on an average of several (generally 3-5) historical years of reported core earnings

        (net earnings adjusted for extraordinary and other ―one time‖ items), and same number of

        expected years earnings. For public companies, I use two alternative approaches to

        estimate expected earnings: consensus earnings forecasts by financial analysts, and an

        earnings forecast based on the pattern of the firm’s sales. In firm-specific applications, I

        use various public and proprietary sources to estimate growth potential. Normalized

        earnings is thus an annual weighted average of 6-10 earnings numbers, giving a heavier

        weight to expected earnings.

      Based on various economic studies and analyses, I estimate the average contributions of

        physical and financial assets, the α and β in the production function above. For public

        rankings of companies (Fortune, CFO magazine), I use after tax rates of 7% for physical

        assets and 4.5% for financial assets, reflecting economy- wide averages. For company-

        specific applications, I estimate specific rates of return on assets. These rates will

        change, of course, with market and company conditions.

        I then subtract from normalized earnings (defined above), 7% of the value of physical

        assets and 4.5% of the value of financial assets.

        What remains of normalized earnings after these subtractions is the contribution of

        intangible assets to the enterprise performance, which I define as ―intangibles-driven

        earnings‖ (IDE).




                                                                                                       6
 Lastly, I forecast the series of intangibles-driven earnings over three future periods (a 3-

   stage valuation model): Future years 1-5, using financial analysts’ long-term growth

   forecasts (or a sales-based forecast); years 6-10, linearly converging the forecasts to the

   long-term growth of the economy—3%; and years 11 to infinity, where IDE are assumed

   to grow annually by 3%—the expected long-term growth rate of the economy.

 The discounted value of expected IDE series, using a discount rate which reflects the

   above-average riskiness of these earnings, yields the estimated of ―intangible assets.‖




                                                                                                 7
2.      How do They Look?

        Tables 1 and 2 present the 1999 intangibles measures computed for the five leading

companies in 22 nonfinancial industries, followed by the industry median measures. These data
                                       2
constitute the CFO 2001 ranking.

          The metrics include the firms’ intangible capital (noted as knowledge cpital in the

tables), as of August 2000; their 1999 intangibles-driven earnings; (noted knowledge earnings)

and the new value measure—―market-to-comprehensive value‖ (third column from right). This

measure modifies the well-known market-to-book ratio (market value of corporations divided by

their book value—net assets on the balance sheet), by adding to the denominator of the ratio the

estimated value of the firm’s intangible capital. Thus, the balance sheet value of physical and

financial assets (book value), plus the value of intangibles missing from the balance sheet,

comprises the ―comprehensive value.‖

          Table 2 indicates, among other things, that many, so called ―old economy‖ industries,

are reach in intangibles: aerospace and defence, food and beverages (particularly brands), home

products, industrial, oil and gas, retail. Figure 2, based on about 2000 companies for the period

1990-1999, provides a similar message.

        We will see below the results of extensive tests demonstrating the unique usefulness of

these measures reflecting intangibles assets.




2
 This work was done in cooperation with Marc Bothwell, vice president and portfolio manager at Credit Su isse
Asset Management.


                                                                                                                8
                                                                               Table 1

                                              The Scope of Intangibles
                                                                  Knowledge                      Change in       Knowledge                    Market Value /
                                                                    Capital       Knowledge      Knowledge      Capital / Book Market Value / Comprehensive     Market Value    Return 8/31/2000 -
                          Name                     Industry        8/31/2000     Earnings 1999 Earnings '99-'98    Value        Book Value        Value          8/31/2000          2/28/2001

HON      HONEYWELL INT L INC COM            Aerospace & Defense         33,839            2,157            235             3.6           3.3             0.71          30,891                 22%

LMT      LOCKHEED MART IN CORP COM          Aerospace & Defense         27,358            1,417           -333             4.2           1.8             0.34          11,407                 32%

BA       BOEING CO COM                      Aerospace & Defense         23,447            1,590            614             1.9           3.8             1.30          46,270                 17%

NOC              P
         NORT HRO GRUMMAN CORP COM          Aerospace & Defense         15,901             894              65             4.5           1.5             0.28           5,440                 21%

RT N.B   RAYT HEON CO CL B                  Aerospace & Defense          8,356             800            -595             0.8           0.9             0.50           9,457                 21%

DAL      DELTA AIR LINES INC DEL COM        Airlines                    10,792             709             -15             2.1           1.2             0.38           6,071                -15%

AMR      AMR CORP COM                       Airlines                     9,230             425            -174             1.4           0.7             0.31           4,920                  1%

LUV      SOUTHWEST AIRLS CO COM             Airlines                     6,668             374              68             2.2           3.7             1.17          11,280                 23%

U        US AIRWAYS GROUP INC COM           Airlines                     3,420             251              60 NM                NM                      0.72           2,280                 21%

AMGN     AMGEN INC COM                      Biotech                     20,876            1,041            136             6.0         22.4              3.20          77,958                 -5%

MEDI     MEDIMMUNE INC COM                  Biotech                      4,409             124              36             6.1         24.3              3.44          17,651                -48%

BGEN     BIOGEN INC COM                     Biotech                      4,377             219              44             4.4         10.2              1.90          10,229                  4%

CHIR     CHIRON CORP COM                    Biotech                      1,508              80              17             0.8           5.4             2.95           9,863                -13%

DD       DU PONT E I DE NEMOURS & CO COM    Chemical                    49,085            2,543             23             3.7           3.5             0.75          46,779                 -1%

DOW      DOW CHEM CO COM                    Chemical                    29,091            1,844            748             3.2           2.0             0.47          17,761                 28%

PPG      PPG INDS INC COM                   Chemical                     9,948             632              63             3.1           2.2             0.53           7,045                 28%

APD      AIR PRODS & CHEMS INC COM          Chemical                     6,245             379              42             2.4           2.9             0.87           7,746                 13%

ROH      ROHM & HAAS CO COM                 Chemical                     4,656             280             -29             1.3           1.8             0.77           6,356                 29%

IBM      INTERNAT IONAL BUSINESS MACHS COM Computer Hardware           128,186            6,597            212             6.7         12.1              1.58         232,413                -24%

DELL     DELL COMPUT ER CORP COM            Computer Hardware           83,519            2,490            547            12.9         17.5              1.26         113,251                -50%

HWP      HEWLETT PACKARD CO COM             Computer Hardware           49,857            2,598           -340             3.4           8.2             1.85         119,385                -52%

EMC      E M C CORP MASS COM                Computer Hardware           45,958            1,569            389             6.9         32.2              4.06         213,677                -58%

SUNW     SUN MICROSYSTEMS INC COM           Computer Hardware           44,560            1,849            470             6.1         27.7              3.91         202,719                -69%

MSFT     MICROSOFT CORP COM                 Computer Software          188,787            8,526          2,406             4.6           8.9             1.60         368,819                -15%

ORCL     ORACLE CORP COM                    Computer Software           54,304            2,314            904             8.4         39.4              4.19         254,509                -58%

CA       COMPUTER ASSOC INT L INC COM       Computer Software           38,908            1,782            279             5.7           2.7             0.41          18,763                 -2%

VRT S    VERITAS SOFTWARE CO COM            Computer Software           16,988             176             143             5.3         15.1              2.40          48,465                -46%

SEBL     SIEBEL SYS INC COM                 Computer Software            6,180             176              53             6.9         45.6              5.76          40,715                -61%

AES      AES CORP COM                       Electric Utilities          28,486             691             197             7.1           7.3             0.90          29,119                -15%

DUK      DUKE ENERGY CORP COM               Electric Utilities          15,380             934             211             1.6           2.9             1.10          27,531                 10%

SO       SOUTHERN CO COM                    Electric Utilities          10,351             847             177             1.1           2.1             0.99          19,418                  6%

FPL      FPL GROUP INC COM                  Electric Utilities           5,385             391              67             0.9           1.7             0.85           9,488                 24%

D        DOMINION RES INC VA NEW COM        Electric Utilities           3,358             418              77             0.5           1.8             1.22          12,604                 26%

EMR      EMERSON ELEC CO COM                Electrical                  24,717            1,426            130             3.9           4.5             0.91          28,273                  2%

ROK      ROCKWELL INT L CORP NEW COM        Electrical                   9,431             536              16             3.5           2.8             0.62           7,534                 15%

CBE      COOPER INDS INC COM                Electrical                   5,950             363              27             3.3           1.8             0.43           3,292                 25%

APCC     AMERICAN PWR CONVERSION CORP COM Electrical                     4,311             199              32             4.3           4.6             0.87           4,629                -49%

KO       COCA COLA CO COM                   Food/Beverages              67,165            3,484            394             7.3         14.2              1.71         130,326                  1%

PEP      PEPSICO INC COM                    Food/Beverages              50,480            2,334             67             7.5           9.1             1.08          61,593                  9%

HNZ      HEINZ H J CO COM                   Food/Beverages              18,565            1,064             85            11.4           8.1             0.65          13,223                 14%

UN       UNILEVER N V N Y SHS NEW           Food/Beverages              18,390            1,306             36             3.0           4.4             1.10          27,007                 19%

CPB      CAMPBELL SOUP CO COM               Food/Beverages              13,022             835              47            95.1         81.3              0.85          11,140                 20%

KMB      KIMBERLY CLARK CORP COM            Forest Products             25,308            1,579            201             4.5           5.6             1.02          31,514                 23%

IP       INTL PAPER CO COM                  Forest Products             11,369            1,103            841             0.9           1.2             0.63          15,361                 20%

GP       GEORGIA PAC CORP COM GA PAC GRP    Forest Products              8,884             854             369             2.2           1.1             0.35           4,568                 13%

WY       WEYERHAEUSER CO COM                Forest Products              5,762             572             285             0.8           1.5             0.81          10,322                 18%


                                                                                                                                                                                                     9
WLL     WILLAMETT E INDS INC COM            Forest Products     1,044     221      69       0.5         1.5   1.01    3,331    54%

PG      PROCT ER & GAMBLE CO COM            Home Products       63,450   3,882    143       5.2         6.6   1.07    80,719   15%

G       GILLETT E CO COM                    Home Products       26,145   1,343    124      11.0        13.3   1.11    31,590    9%

CL      COLGAT E PALMOLIVE CO COM           Home Products       19,296   1,097    109      11.8        17.8   1.40    29,257   17%

CLX     CLOROX CO DEL COM                   Home Products       8,151     502      96       4.5         4.7   0.86    8,517     0%

AVP     AVON PRODS INC COM                  Home Products       7,675     455      24 NM          NM          1.27    9,304     9%

T YC    T YCO INT L LT D NEW COM            Industrial          56,184   2,970    640       3.7         6.3   1.34    96,177   -4%

UTX     UNITED TECHNOLOGIES CORP COM        Industrial          25,856   1,564    438       3.4         3.9   0.87    29,231   26%

CAT     CAT ERPILLAR INC DEL COM            Industrial          23,132   1,166     54       4.2         2.3   0.44    12,705   15%

ITW     ILLINOIS T OOL WKS INC COM          Industrial          15,800    957     113       3.1         3.3   0.81    16,922    9%

IR      INGERSOLL-RAND CO COM               Industrial          14,453    819      77       4.5         2.3   0.42    7,340    -4%

DIS     DISNEY WALT CO COM DISNEY           Media               53,012   2,126     59       2.2         3.5   1.07    82,396   -20%

VIA.B   VIACOM INC CL B                     Media               16,759    646     188       0.3         2.1   1.55   102,113   -26%

CCU     CLEAR CHANNEL COMMUNICAT IONS COM Media                 9,536     447     119       0.9         2.7   1.40    27,518   -21%

F       FORD MT R CO DEL COM PAR $0.01      Motor Vehicles      90,338   6,685   1,680      3.7         2.1   0.44    50,941   18%

GM               T
        GENERAL M RS CORP COM               Motor Vehicles      55,026   4,257    282       1.9         1.3   0.46    38,758   -25%

DPH     DELPHI AUT OMOT IVE SYS CORP COM    Motor Vehicles      13,413    962      97       3.8         2.6   0.54    9,205    -14%

JCI     JOHNSON CT LS INC COM               Motor Vehicles      8,573     480      74       3.5         1.9   0.42    4,589    26%

PCAR    PACCAR INC COM                      Motor Vehicles      4,159     306       -4      1.9         1.5   0.51    3,246    13%

GCI     GANNETT INC COM                     Newspapers          17,733   1,087    137       3.8         3.2   0.67    14,928   18%

T RB    T RIBUNE CO NEW COM                 Newspapers          10,388    502     140       1.7         1.7   0.66    10,999   14%

NYT     NEW YORK T IMES CO CL A             Newspapers          5,619     336      44       4.2         4.9   0.95    6,594    13%

KRI     KNIGHT RIDDER INC COM               Newspapers          4,921     329      12       3.0         2.5   0.63    4,127    10%

DJ      DOW JONES & CO INC COM              Newspapers          3,562     210      10       6.6        10.1   1.33    5,467    -1%

XOM     EXXON MOBIL CORP COM                Oil                114,347   8,544    878       1.7         4.2   1.57   284,382    0%

RD      ROYAL DUT CH PETE CO NY REG GLD1.25 Oil                 27,258   3,818    585       0.8         3.7   2.10   131,204   -5%

CHV     CHEVRON CORPORAT ION COM            Oil                 24,559   2,210   1,026      1.3         2.9   1.27    55,150    3%

P       PHILLIPS PET E CO COM               Oil                 8,697     877     198       1.7         3.1   1.14    15,756   -13%

UCL     UNOCAL CORP COM                     Oil                 8,453     376      42       3.4         3.3   0.74    8,106     7%

PFE     PFIZER INC COM                      Pharaceuticals     128,610   5,796   3,017      8.6        18.2   1.90   273,069    5%

MRK     MERCK & CO INC COM                  Pharaceuticals     109,217   6,583    902       8.6        12.6   1.32   160,694   15%

JNJ     JOHNSON & JOHNSON COM               Pharaceuticals      76,446   4,336    699       4.3         7.1   1.35   127,891    7%

BMY     BRIST OL MYERS SQUIBB CO COM        Pharaceuticals      74,002   4,254    424       8.3        11.7   1.26   104,255   21%

PHA     PHARMACIA CORP COM                  Pharaceuticals      55,373   2,193    543       4.7         6.5   1.13    75,998   -11%

LLY     LILLY ELI & CO COM                  Pharaceuticals      48,163   2,641    328       8.7        15.0   1.54    82,453   10%

WMT     WAL MART ST ORES INC COM            Retail              81,239   4,867   1,167      2.9         7.5   1.94   211,872    6%

S       SEARS ROEBUCK & CO COM              Retail              23,457   1,421    115       3.6         1.7   0.36    10,697   33%

TGT     T ARGET CORP COM                    Retail              15,406    885     128       2.6         3.5   0.98    20,999   68%

COST    COSTCO WHSL CORP NEW COM            Retail              6,006     349      40       1.5         3.8   1.52    15,404   21%

KSS     KOHLS CORP COM                      Retail              5,504     250      50       2.9         9.8   2.50    18,486   18%

INT C   INTEL CORP COM                      Semiconductors     208,641   9,502   2,749      5.7        13.7   2.05   502,711   -62%

AMAT    APPLIED MAT LS INC COM              Semiconductors      44,667   1,858   1,090      7.3        11.4   1.38    70,011   -51%

T XN    T EXAS INST RS INC COM              Semiconductors      39,390   1,860   1,012      3.1         8.7   2.11   109,810   -56%

BRCM    BROADCOM CORP CL A                  Semiconductors      5,704     137      38       6.8        65.8   8.48    55,509   -80%

HD               T
        HOME DEPO INC COM                   Specialty Retail    48,849   2,230    621       3.5         8.0   1.77   111,287   -11%

LOW             S
        LOWES CO INC COM                    Specialty Retail    10,962    567     171       2.1         3.3   1.06    17,154   25%

CVS     CVS CORP COM                        Specialty Retail    10,320    512      84       2.6         3.7   1.02    14,504   65%

WAG     WALGREEN CO COM                     Specialty Retail    9,243     510      73       2.3         8.2   2.50    33,231   35%

RSH     RADIOSHACK CORP COM                 Specialty Retail    4,552     271      60       6.3        15.2   2.08    10,962   -27%

VZ      VERIZON COMMUNICAT IONS COM         T elecom           114,464   6,462   1,277      3.3         3.5   0.80   118,573   15%

SBC     SBC COMMUNICATIONS INC COM          T elecom           113,618   6,903   2,730      4.0         5.0   1.00   141,514   15%

T       AT&T CORP COM                       T elecom            81,221   4,851    -222      0.7         1.1   0.62   118,288   -26%


                                                                                                                                      10
BLS               BELLSOUT H CORP COM           T elecom              53,812   3,568    660    3.3    4.3   1.00    70,185   13%

WCOM                            A
                  WORLDCOM INC G NEW COM        T elecom              23,277   1,772     30    0.4    1.9   1.35   104,734   -54%

CSCO              CISCO SYS INC COM             T elecom Equipment   162,218   4,910   2,434   6.1   18.5   2.60   489,845   -65%

LU                LUCENT TECHNOLOGIES INC COM   T elecom Equipment    62,824   3,220    315    2.4    5.3   1.57   139,633   -70%

MOT               MOT OROLA INC COM             T elecom Equipment    26,947   1,684   1,016   1.3    3.7   1.62    78,639   -58%

GLW               CORNING INC COM               T elecom Equipment    24,786    867     210    3.3   12.6   2.97    96,184   -75%

QCOM              QUALCOMM INC COM              T elecom Equipment    19,317    672     192    3.3    7.7   1.78    44,610   -8%

NM – Not Meaningful




                                                                                                                                    11
                                                                 Table 2
                                           Industry Medians (of Companies in Table1)
                                    Intangibles-   Change in     Intangible    Market   Market Value/
                      Intangible      Driven      Intangibles Capital/ Book Value/ Book Comprehensive     Market
     Industry          Capital       Earnings       Earnings       Value        Value      Value      Value(8/31/2000)
Aerospace & Defense        23,447          1,417            65         3.58         1.77           0.50          11,407
Airlines                    7,949            399            22         2.12         0.96           0.55           5,496
Biotech                     4,393            171            40         5.18        16.29           3.07          13,940
Chemical                    9,948            632            42         3.08         2.18           0.75           7,746
Computer Hardware          49,857          2,490           389         6.69        17.53           1.85         202,719
Computer Software          38,908          1,782           279         5.68        15.15           2.40          48,465
Electric Utilities         10,351            691           177         1.11         2.09           0.99          19,418
Electrical                  7,690            450            29         3.70         3.63           0.75           6,081
Food/Beverages             18,565          1,306            67         7.48         9.13           1.08          27,007
Forest Products             8,884            854           285         0.87         1.48           0.81          10,322
Home Products              19,296          1,097           109         8.10         6.57           1.11          29,257
Industrial                 23,132          1,166           113         3.65         3.30           0.81          16,922
Media                      16,759            646           119         0.94         2.72           1.40          82,396
Motor Vehicles             13,413            962            97         3.50         1.87           0.46           9,205
Newspapers                  5,619            336            44         3.77         3.18           0.67           6,594
Oil                        24,559          2,210           585         1.71         3.30           1.27          55,150
Pharaceuticals             75,224          4,295           621         8.44        12.16           1.34         116,073
Retail                     15,406            885           115         2.89         3.75           1.52          18,486
Semiconductors             42,029          1,859         1,051         6.23        12.57           2.08          89,911
Specialty Retail           10,320            512            84         2.62         8.01           1.77          17,154
Telecom                    81,221          4,851           660         3.26         3.47           1.00         118,288
Telecom Equipment          26,947          1,684           315         3.25         7.73           1.78          96,184




                                                                                                                    12
13
Figure 2




           15
3.         What Drives Intangible Capital?

           Intangible (intellectual) capital is driven by diverse factors: innovation, human capital,

organizational processes, customer and supplier relations, to name some major ones. For most of

these drivers (e.g., customer satisfaction), there are no standardized, public information

available. I, therefore, limit the analysis here to the several intangibles drivers which are

publicly available: R&D, advertising (brand support), capital expenditures, information systems,

technology acquisition.

           Table 3, based on data for about 2000 companies, spanning the period 1989-1999,

identifies five major drivers of intangibles-driven earnings (IDE): R&D, advertising (brand

enhancement), capital expenditure (intangibles embedded in physical assets), information

technology, and technology acquisitions. It is clear from the table that these are indeed drivers-

their intensity is positively correlated with the ratio of IDE to sales. 3

           In current work (conducted with Towers Perrin and Feng Gu of Boston University), we

find that various measures reflecting human resource practices (e.g., extent of incentive-based

compensation, termed LPCT in Table 4, employee training, etc.), are also strongly correlated

with intangibles earnings and capital. This is reflected in Table 4.

           This is just the beginning of a detailed identification and quantification of the drivers of

intangible capital, and in turn, corporate value. Business and investment decisions are predicated

on the understanding and quantification of the major drivers of corporate value and growth.




3
    This work is conducted with Feng Gu of Boston University.


                                                                                                        16
Table 3




          17
Table 4




          18
                                                               4. Do They Work?

         Given the proliferation of new measures and indicators, proposed to managers and investors, it’s incumbent on the proponents of such

   measures not only to argue that they are needed and useful, but to prove empirically that they indeed are doing the job. Such a proof is

                              unfortunately missing from most of the proposed measures and analytical techniques.

         Below, are comprehensive statistical tests indicating the superiority of the intangibles metrics as indicators of enterprise performance

over conventional ones. A frequently used methodology in finance and accounting research to gauge relevance of information a nd data is to

correlate the proposed information with the consequences of investors’ decisions, such as reflected in stock price changes. A weak

correlation indicates that the decision makers (e.g., investors) did not find the information very useful, and vice versa for a strong correlation.

         Following this approach, I correlated (with Feng Gu) annual stock returns (stock price changes adjusted for dividends), reflecting

investors’ decisions, with the annual growth in firms’ intangibles-driven earnings, over the period 1989-1999 (about 2,000 companies in each

year). For comparison purposes, I did the same for the annual growth in reported cash flows (from operations) and earnings, two of the most

widely used corporate performance measures.

         Figure 3 shows the clear superiority of intangibles-driven earnings (IDE), over accounting earnings and cash flows. Specifically,

while the correlations between stock returns and reported cash flows or earnings are 0.11 and 0.29, respectively (so much for ―cash is king‖),

the correlations between returns and IDE (based on sales’ growth) is 0.40, and between returns and IDE (based on analysts’ forecasts) is 0.53.

Thus, both version of intangibles-driven earnings, with and without analysts’ forecasts, beat earnings and cash flows in the ―return correlation

race.‖




                                                                                                                                                 19
         The conclusion: the earnings stream generated by intangible assets (IDE) provide substantially more relevant information to investors

than reported earnings and cash flows. The reason: while total earnings, or cash flows reflect the performance of all assets, some of which

(e.g., various kinds of physical assets) don’t contribute to growth, IDE focuses on the contribution of intangibles—the major growth

contributes. Also, while earnings and cash flows are strictly historic (backward- looking) measures, IDE explicitly reflect growth

expectations. 4

         While I cannot perform similar statistical analyses on managerial decisions, analogous to the capital market analysis reported here, it

stands to reason that the intangibles metrics reported here will also provide new and useful information for corporate managers. The reason:

most corporate decisions are guided by accounting metrics, such as earnings and return on investment measure, which appear inferior to the

intangibles metrics.




4
  For those interested in a regression analysis, supplementing the univariate correlations of Figure 3, Tab le 5 provides the ap propriate estimates, where annual stock
returns are regressed on reported earnings (level and change) and various configurations of the intangibles metrics.


                                                                                                                                                                           20
Figure 3




           21
Table 5




          22
       5. Can They Predict?

           The statistical validation tests reported in Section 4 were contemporaneous; namely stock

       return correlated with same year growth in intangibles-driven earnings. Contemporaneous

       correlations indicate the relevance of an information item to investors. But if the item is

       widely available, despite it being relevant, you will not be able to use it to gain superior

       investment returns (the information is already priced).

           To test whether intangibles measures can be used to gain ―abnormal returns‖ one must

       use a multiperiod predictive test. Such a preliminary test is reported in Table 6. With Marc

       Bothwell of Credit Swiss Asset Management, I estimated for each of the 105 companies in

       Table 1, its market-to-comprehensive value (M/C) indicator for August 31, 2000. (Recall

       that the M/C ratio is a modified market-to-book ratio, where the value of intangible capital is

       added to the denominator). We then correlated the M/C values with the subsequent stock

       performance of these companies (during September 1, 2000 through December 31, 2000; a

       period of sharp stock price declines). 5 We found a strong negative correlation, confirming

       that companies with above-average M/C values (i.e., overvalued by investors, according to

       the intangibles measures) were subsequently downgraded by investors, and vice versa for

       companies with below-average M/C value (undervalued companies).

           Table 6 indicates that the 53 companies with below- median M/C values (undervalued)

       gained, on average, 7% in the subsequent period, while the 52 stocks with above-median

       M/C (overvalued) lost, on average, 15.5% during September-December 2000.

           The market-to-comprehensive measure thus appears to distinguish between undervalued

       and overvalued stocks. With Feng Gu (Boston University) I derive even stronger results for

       a much longer period:1989-1999, and a larger sample of about 2,000 companies. The M/C
5
    These numbers appear in the right, and third fro m right colu mns in Tab le 1.


                                                                                                      23
    investment scheme is profitable during the three-years after portfolio formation and easily

    beats the widely used measure of Market-to-Book.

         Table 7 provides portfolio returns for three investment strategies: book-to-market (B/M),

    comprehensive-to-market based on analysts’ forecasts (C/M), and comprehensive-to-market

    based on a sales growth model (AC/M). 6 In each case, the sample companies (about 2000

    companies, over 1989-1999) are classified into five portfolios according to increasing size of

    B/M or C/M. The portfolio return data for one, two, and three years subsequent to portfolio

    formation indicate: (a) For each year and portfolio strategy, returns are monotonically

    increasing from the first to the fifth portfolios, a finding documented in finance literature for

    the B/M portfolios. (b) The increases are steeper for the C/M than for B/M portfolios, see the

    right column of ―Q5 – Q1 Difference‖ in the three panels of Table 7. (c) The total returns are

    also higher for the C/M strategy than for the B/M strategy (e.g., for portfolio Q5, the 36

    months return is 71.8% for C/M vs. 62.1% for B/M). (d) There are no distinguishable

    differences in performance between the two versions o f C/M; with and without analysts’

    forecasts. This is graphically indicated by Figure 4.

         Tables 8-10 pit directly the B/M strategy against the C/M portfolio choice. In a series of

    5x5 classifications, five by B/M and five by C/M, for 12 months ahead (Table 8) and 24 and

    36 months subsequent to portfolio formation (Tables 9 and 10), one can observe the

    generation of returns for one strategy, when the other is held constant (movement across

    rows or columns). It is clear from each of the three tables that the significant returns are

    exhibited across rows, from low to high C/M portfolios (see returns on the right column: CM

    Q5-Q1). Once the C/M portfolios are accounted for, the B/M portfolio strategy does not


6
    In empirical work, the inverse of the mu ltiples (e.g., book-to-market) is preferred , to avoid negative values in
    the denominator.


                                                                                                                         24
generate substantial returns (bottom row in Tables). Thus, the C/M strategy subsumes the

well known B/M (―Value‖) strategy. Results for AC/M—the intangibles-based

comprehensive value based on sales growth model (in contrast with the C/M which is based

on analysts’ forecasts), are essentially identical to those using analysts’ forecasts presented in

Tables 8-10.

    Finally, Tables 11-12 present tests of C/M (or AC/M) portfolio returns adjusted for

various risk factors: beta, size, book-to-market, and the ―return momentum.‖ This is the

well-known 4- factor model in finance research. The numbers in the tables are risk-adjusted

monthly return. It is clear that for both C/M and AC/M, the portfolio returns are sharply

increasing from low C/M (AC/M) to high C/M (AC/M) portfolios. The abnormal returns are

economically very meaningful. For example, the monthly return for portfolio Q4, 0.236

(Table 11), translate to an annual return of over 3.0 percent above risk benchmark.

    Summarizing, the extensive, large sample empirical tests reported in this section indicate

that the market-to-comprehensive value metric, based either on analysts’ forecasts or on a

sales growth model, exhibit a consistent ability to generate subsequent abnormal stock

returns, whether evaluated against a market-to-book strategy, or a combination of risk

factors.




                                                                                               25
                   Table 6

  Market Value / Comprehensive Value
   (8/31/2000) and Subsequent Stock
  Performance (8/31/2000-12/31/2000)


                Master Table
                  Weighted
                 Subsequent
 Market Value /    Return
 Comprehensive Averages for      Count in
     Value         Group         Sample
low                       7.0%              53
high                    -15.5%              52




                                                 26
Table 7




          27
Figure 4




           28
Table 8




          29
Table 9




          30
Table 10




           31
Table 11




           32
Table 12




           33
6.      Takeaway Points
 The Intangibles Scoreboard adds an essential, and hitherto missing, valuation tool for

     managers and investors concerned with intangible (intellectual) assets, and with the optimal

     resource allocation of intangible and physical assets.

 R&D, advertising, information technology and various human resource practices were

     empirically identified as drivers of intangible capital, and in turn corporate value.

 Intangibles measures provide more relevant information than conventional performance

     measures, as indicated by the strength of correlations with stock returns.

 Intangibles measures successfully distinguish between over-and under-valued stocks, as

     indicated by the research presented above.

 Lastly, the data and findings reported above are based on publicly

     available information, and uniform return and discount rates. It can be expected that

     substantially improved valuations will be obtained by tailoring the intangibles measures to

     the specific circumstances of companies, subsidiaries, or stocks.




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