Accounting Diversity andInternational Valuation

by

Richard Frankel*

University of MichiganBusiness School

Ann Arbor, MI 48109-1234313-763-6039

and

Charles M. C. LeeJohnson Graduate School of Management

Cornell UniversityMalott Hall, Ithaca, NY 14850

607-255-6255

August 1996May 1999

Comments welcomed

Please direct correspondence to Professor Charles M. C. Lee.

* We thank Warren Bailey, Larry Brown, Ilia Dichev, Carol Frost, Trevor Harris, Jim Leisenring, StephenPenman, Katherine Schipper, David Senteney, Terry Warfield, and participants at the Harvard FinancialDecisions and Control workshop, the University of Michigan workshop, the FASB ProfessionalDevelopment Seminar, the NYSE Conference on Recent Developments in International Equity Markets,and the 1996 AAA Annual Meetings for helpful comments. James Myers provided expert researchassistance. The international analyst earnings forecast data were provided by I/B/E/S. Financial supportfrom the Q-Group, and the KPMG Peat Marwick Foundation (Lee) are gratefully acknowledged. Much ofthis study was completed during Lee's stay at the New York Stock Exchange as the 1995-96 VisitingEconomist.

Abstract

International differences in accounting rules pose a significant challenge to investors

interested in making cross-border comparisons of firm value. While current efforts to

harmonize international standards are laudable, they are unlikely to completely eliminate

cross-border accounting diversity. In this study, we suggest an alternative, and

complementary, approach for coping with international diversity.

Our approach is based on the Discounted Residual Income or the Edwards-Bell-Ohlson

(EBO) valuation model. The model is potentially attractive because, it provides a

method for translating accounting numbers produced under alternative accounting

systems into more comparable measures of firm value. However, the model must

overcome a number of potential problems in actual implementation.

We discuss the practical problems that must be resolved in international implementations.

Specifically, we identify three major areas of potential difficulty: 1) the availability of

reliable earnings forecasts, 2) systematic violations of the clean-surplus assumption, and

3) "poor quality" accounting rules that result in delayed recognition of value changes.

These difficulties can introduce noise into the estimation process, the extent of which is

likely to be country-specific.

Finally, we provide preliminary empirical evidence on the efficacy of the model in cross-

border valuations and returns predictions. Despite the limitations discussed above, we

find that firm value estimates based on the model are highly correlated with cross-border

stock prices. Across 20 countries and over 8 years, our value estimate ("V") consistently

dominates earnings and book value in explaining variations in stock prices. Most of the

improvement arises from the use of forward-looking analyst forecasts of earnings rather

than country specific discount rates. Furthermore, we show that V/P-based cross-country

hedge strategies produce significant positive returns, suggesting that the model may be

useful in global asset allocation decisions.

I. Introduction

International accounting diversity is an old problem that has acquired a new sense of

urgency. Fueled by privatization in de-centralized economies and the globalization of

capital markets, world-wide demand for equity capital is at an all-time high.1 As

investors and corporations venture beyond domestic boundaries, cross-border differences

in accounting rules are becoming an increasing source of frustration. These differences

exact a cost on both firms seeking to raise capital in multiple jurisdictions, and investors

seeking to make global asset allocation decisions.

Currently, the International Accounting Standards Committee (IASC), with the support

of the International Organization of Securities Commissions (IOSCO), is establishing a

comprehensive core set of international accounting standards. However, legitimate

concerns remain about whether international standards can be totally harmonized.2 A

country’s accounting regulations reflect its cultural, economic and political institutions.

While legislating more uniform accounting rules may be possible, eradicating economic

and cultural differences is much more difficult. Therefore, laudable as they may be,

current efforts to harmonize accounting standards are unlikely to completely eliminate

cross-border diversity.

In this paper, we suggest a complementary approach for addressing international

accounting diversity. Our approach is based on the Discounted Residual Income or the

1 Cochrane, Shapiro, and Tobin (1995) report that total capitalization of the world’s publicly traded equity

surged from $10 trillion at the end of 1990 to $17 trillion by 1995. The same paper contains a gooddiscussion of economic reasons for these trends.2 Ball (1995) and Zarzeski (1996) are two recent studies that examine the desirability and likelihood ofinternational harmonization.

2

Edwards-Bell-Ohlson (EBO) valuation model. 3 Specifically, we examine the ability of a

residual-income valuation model to produce comparable firm value estimates across

different international accounting systems. The model is potentially attractive because, in

theory, it provides a technique for translating accounting numbers produced under

alternative accounting systems into more comparable measures of firm value. However,

the model must overcome a number of potential problems in actual implementation.

Our main objective is to explore the practical issues related to the use of the model in an

international context. In implementation, the model relies on imperfect empirical proxies

and estimation shortcuts necessitated by data constraints. We discuss the likely impact of

these problems. Specifically, we identify three practical issues that must be resolved in

international implementations: 1) the availability of reliable earnings forecasts, 2)

systematic violations of the clean-surplus assumption, and 3) "poor quality" accounting

rules that result in delayed recognition of value changes. A cursory review of

international accounting rules suggests that these problems may be more severe in code-

law countries (e.g., France, Germany, Japan) than in common-law countries (U.S.,

Australia, Canada, and the U.K.).

Our second objective is to provide some empirical evidence on how well the model

explains stock prices and how well it predicts returns across different accounting regimes.

To address these issues, we compiled a database of more than 6,000 firms across 20

countries using I/B/E/S international earnings forecasts and fundamental accounting data

from the Global Vantage database. The focus of our empirical work is on evaluating the

3 The term “Edwards-Bell-Ohlson,” or “EBO,” was coined by Bernard (1994).

3

efficacy of the model in cross-border firm valuations, and on comparing the relative

attractiveness of aggregate country portfolios.

Our empirical tests are intended to provide a basis for understanding how well the model

operates internationally. It is important to understand the exploratory nature of this

analysis. We do not look into the details of accounting differences across individual

countries. Rather, we seek to provide a general overview of how well the model works

across a large number of countries. We also aim to provide some evidence on the relative

importance of various components of the model in explaining stock prices and returns.

Two main results emerge from our empirical work. First, we find that an estimate of firm

value based on the residual income model (V) is useful in explaining cross-sectional

stock prices in all 20 countries. In most countries, our estimate of V accounts for more

than 70% of the cross-sectional price variation. In Germany and Japan, whose

accounting systems have been much maligned, the ability of V to explain prices is indeed

lower. However, even in these countries, V dominates historical book value and earnings

in terms of its correlation with current stock prices. Bernard (1994), Frankel and Lee

(1998), and Penman and Sougiannis (1998) show that the residual income model is

highly correlated with cross-sectional stock prices in the U.S. We show the model works

well in explaining stock prices even when accounting numbers derived from different

countries.

We find that V has explanatory power for stock prices beyond a linear combination of

earnings and book value. Controlling for both earnings and book value, we find V

4

continues to be an important explanatory variable in price regressions in all 20 countries.

The superiority of V over other traditional value indicators in price regressions is stable

throughout our sample period (1987 to 1994) and across all major countries.

Furthur investigations reveal that much of the predictive power of V derives from its use

of analyst forecasts of future earnings. The model's other key parameters, such as

country-specific discount rates and the dividend payout ratios, were less important to the

success of V. Interpreted in the context of the valuation model, our results suggest that a

two-period-ahead analyst consensus forecast of earnings provides a reasonable proxy of a

firm's "normalized" earnings, regardless of the accounting system from which it arises.

We also examine the usefulness of the residual income model as a predictor of cross-

country stock returns. Lee, Myers and Swaminathan (1999) show that, when price is a

noisy proxy for the true fundamental value of a firm, superior estimates of firm value

should result in P/V ratios that have superior predictive power for stock returns. We test

the ability of country-level P/V ratios to predict cross-sectional returns across different

countries.

As expected, we find that the average book-to-price ratio across individual countries is

negatively correlated with their forecasted abnormal ROEs. Countries trading at higher

premiums over reported book values tend to have higher forecasted ROEs relative to their

costs of capital. Interestingly, we also find that V/P rankings across countries are

positively correlated with subsequent 12-month returns. Specifically, we show that a

strategy of buying countries with high average V/Ps and shorting countries with low

5

average V/Ps yields consistently positive and statistically significant returns over our

sample period. While also positive, returns to similar trading strategies based on E/P or

B/P ratios are far less stable. These results suggest that the EBO model is a potentially

useful aid in assessing the relative attractiveness of aggregate country portfolios.

In sum, we conclude the residual income model is a useful part of a broader solution to

the problem of accounting diversity. The model helps highlight the fact that valuation is

a forward-looking exercise that requires forecasts of both future earnings and discount

rates. We show that sell-side analyst forecasts are a reasonable first proxy for these

forward-looking earnings in international valuations. Specifically, we find that the bias

and accuracy of analyst forecasts are no worse in most other countries than they are in the

United States. In addition, we provide some evidence that the model operates better in

common-law countries than in code-law countries.

We regard these results as an encouraging first step in an on-going effort to help investors

make better asset allocation decisions across countries. These results are a first step in

that our estimates of cross-country discount rates are crude, and we do not make country-

specific accounting adjustments. Nevertheless, our results are encouraging in that they

show even with relatively crude empirical estimates, the model is much better at

explaining prices than linear combinations of historical earnings and book value. Our

results also suggest it may lead to better cross-country returns predictions.

The remainder of the paper is organized as follows. In the next section, we develop the

EBO valuation model and discuss its implications. In Section III, we discuss the

6

minimum conditions for an accounting system to provide consistent results in an EBO

valuation. In Section IV, we consider model estimation procedures. In Section V, we

discuss sample selection and data issues. Section VI contains the empirical results.

Section VII discusses implications for current research and concludes.

II. The EBO Valuation Model

The valuation model we use to compute a proxy of Vt* is based on a discounted residual

income approach sometimes referred to as the Edwards-Bell-Ohlson (EBO) valuation

equation.4 Independent derivations of this valuation model have surfaced periodically

throughout the accounting, finance and economics literature since the 1930’s. Most

recently, alternative approaches to empirically implement the model have been discussed

extensively in several papers (e.g., Bernard (1994), Abarbanell and Bernard (1995),

Penman and Sougiannis (1998), Frankel and Lee (1997), Francis, Olsson, and Oswald

(1997), and Dechow, Hutton, and Sloan (1997)). In this section, we present the basic

EBO equation and the intuition behind it.

In a series of recent papers, Ohlson [1990, 1991, 1995] demonstrates that, as long as a

firm's earnings and book value are forecasted in a manner consistent with “clean surplus”

accounting,5 the present value of future expected dividends can be rewritten as the

reported book value, plus an infinite sum of discounted residual income:

4 The term “Edwards-Bell-Ohlson,” or “EBO,” was coined by Bernard (1994).5 Clean surplus accounting requires that all gains and losses affecting book value are also included inearnings; that is, the change in book value from period to period is equal to earnings minus net dividends(bt = bt-1 + NIt - DIVt).

7

Vt = Bt +

Et[NIt + i – (re * Bt + i – 1)]

(1 + re)iΣi = 1

∞

= Bt +

Et[(ROEt + i – re) * Bt + i – 1]

(1 + re)iΣi = 1

∞

(1)

where Bt = book value at time t

Et[.] = expectation based on information available at time t

NIt+i = Net Income for period t+i

re = cost of equity capital

ROEt+i = the after-tax return on book equity for period t+i

Equation (1) highlights the importance of forward-looking earnings information in equity

valuation. Historical book value is an inadequate proxy for intrinsic value because it

measures only the invested capital, not the value of future wealth creating activities.

Historical earnings is also an inadequate proxy for intrinsic value because it is, at best, a

crude proxy for the stream of future earnings. Moreover, the value of the future earnings

stream depends critically on the discount rate. In countries where the discount rate is

relatively high, the present value of future abnormal earnings will be relatively low.

Accounting conservatism aside, forecasted ROEs in competitive equilibrium should

equal the cost of equity (forecasted ROE = re).6

6In practice, most firms' accounting systems are conservatively biased, so reported ROEs tend to be above

long-run re, with P/B ratios generally above 1.

8

Several recent studies evaluate the ability of this model to explain cross-sectional prices

and expected returns. Penman and Sougiannis (1998) implement variations of the model

using ex post realizations of earnings to proxy for ex ante expectations. Frankel and Lee

(1998) implement the EBO model using I/B/E/S analyst earnings forecasts. They report

that the resulting V measure explains close to 70% of cross-sectional prices in the U.S.,

and that the V/P ratio is a good predictor of cross-sectional returns. Abarbanell and

Bernard (1995) use the model to address the question of market myopia with respect to

short-term versus long-term earnings expectations. Botosan (1997) uses the model to

derive an implicit cost of equity in her analysis of the relation between corporate

disclosure and cost of capital. More recently, both Francis, Olsson, and Oswald (1999)

and Dechow, Hutton, and Sloan (1998) examine the empirical properties of the model

under alternative specifications.

Collectively, these studies show that the residual income model produces intrinsic value

estimates that are highly correlated with cross-sectional stock prices in the U.S. Judging

from the reported price regression R2s, the ability of the residual income model to explain

cross-sectional prices in the U.S. is comparable to the discounted cash flow results

reported in Kaplan and Ruback (1995), and much higher than those achievable using

earnings, book-value or dividends alone. However, the empirical properties of the model

for explaining stock prices and returns across different countries are not known.

In this study, we extend the analysis to international securities. Theory suggests that

certain minimal conditions must be met for the model to produce consistent estimates of

firm value. Empirically, these conditions are violated to different degrees across

9

alternative accounting systems. Our goal is to examine the extent to which these

international accounting differences constrain the ability of the model to explain stock

prices and expected returns across countries. In the next section, we discuss the

minimum conditions needed for an accounting system to produce consistent value

estimates, and the extent to which these conditions might be violated in the international

arena.

III. Minimal Conditions for Valuation

Ohlson (1995) shows that an accounting system must obey the clean surplus relation

(CSR) to produce consistent value estimates. However, the practical implications of the

CSR for empirical researchers has not been explored in detail. In this section, we discuss

the CSR requirement, with particular emphasis on its implications for the use of

accounting numbers from foreign jurisdictions. We also discuss two other necessary

conditions for an accounting system to provide reliable input for valuation. These

conditions pertain to practical implementation challenges, rather than theoretical merits,

of the model.

A. The Clean Surplus Relation

The clean surplus relation stipulates that the period-to-period change in the capital base

(•Bt) must equal forecasted earnings (NIt), net of investor capital withdrawals or

infusions (net dividends, or Divt). Notationally, Bt = Bt-1 + NIt - Divt, where Divt is the

net dividends paid in period t (dividends + capital withdrawals - capital infusions) and

NIt is the net income for period t. In other words, the CSR requires the balance sheet and

10

income statement to “articulate,” making the bottom-line income statement item (Net

Income) equal the change in the book value (net of capital withdrawal or infusions).

Note that the EBO formula does not require firms to have followed clean surplus

accounting in the past; rather, it requires them to do so in the future. We can impose this

condition by requiring that future Bts increase only by the forecasted NIt and decrease

only by the forecasted Divt. However, mechanical imposition of this condition on

forecasted book values does not ensure that the model operates properly unless forecasts

of future earnings are also consistent with the CSR.

Analyst forecasts of GAAP earnings may violate CSR when the accounting system

allows predictable, value-relevant activities to be charged directly to shareholders’ equity,

without going through the income statement. These items are sometimes called “dirty

surplus adjustments.” For example, under U.S. GAAP, both currency exchange

gains/losses on translations of foreign subsidiaries, and unrealized gains/losses on long-

term marketable securities are charged directly to shareholders' equity. Similarly, under

U.K. GAAP, fixed assets may be reappraised to reflect their market value, with a

corresponding adjustment directly to shareholders' equity. When an accounting system

contains many dirty surplus adjustments, analyst earnings forecasts may not comply with

the CSR.

However, not all future dirty surplus adjustments represent a potential source of valuation

bias. CSR violations are problematic only if their present expected value is non-zero. If

future CSR violations are mean zero in expectation, analyst forecasts of GAAP earnings

11

will be unbiased with respect to future wealth-creating activities. Therefore, to evaluate

the suitability of a national accounting system for use in an EBO valuation framework,

we consider two factors: 1) which accounting items systematically violate the CSR; and

2) whether the present expected values of these violations are non-zero.

To illustrate, the Appendix provides an exhaustive list of the items under U.S. GAAP

which violate the CSR. On review, these adjustment items all serve to adjust the book

value of an asset or a liability to its market value. Once an asset or liability has been

marked-to-market, future market value adjustments are, by definition, mean zero in

expectation. Because these CSR violations do not affect future projections of earnings,

we can compute a consistent measure of V with current earnings forecasts made under

U.S. GAAP.7

Handling dirty surplus adjustments under other national accounting systems involves a

similar procedure. These items can be analyzed individually as to their likelihood of

recurrence. If the present expected value of future dirty surplus adjustments is zero, then

we can compute a consistent measure of V using current reported book value and analyst

earnings forecasts. However, if these current dirty surplus items represent a foreseeable

source of future earnings/losses systematically omitted from income, then either current

book value or future earnings forecasts should be adjusted to reflect these items.

7 A possible exception pertains to predictable reversals related to future sales of assets (or extinguishmentof liabilities) with unrealized holding gains or losses already recorded in book value. In non-financialfirms, these items should be generally immaterial.

12

B. Reliability and Accuracy of Earnings Forecasts

While any accounting system which meets the CSR requirement can provide consistent

firm value estimates, not all systems are equally useful. In practice, two additional

conditions ensure that we can readily operationalize the model. First, professional

analysts must have sufficient information to make reliable earnings forecasts. Second,

the country’s accounting system must capture firm value within a few forecasting

periods.

The first condition pertains to the availability of value-relevant information to

professional analysts whose estimates are central to this valuation model. The theory

shows that so long as analysts are faithful to local GAAP in forecasting earnings, it is not

necessary for users of these forecasts to make further accounting adjustments for

valuation purposes. However, this approach assumes that professional analysts have

sufficient information about a company’s accounting policies to make accurate forecasts

of future accounting accrual reversals. For example, analysts cannot make reliable

forecasts of earnings unless the company’s depreciation policies are transparent.8

Analysts might obtain the necessary information through mandated regulatory filings or

voluntary firm disclosures. Some countries, such as the U.S., have extensive regulatory

disclosure requirements. Other countries, such as France and Germany, have

environments that seem to encourage more voluntary disclosures [Meek and Gray (1989),

Frost (1996)]. The quality of the information environment for a given country is difficult

8 It is not possible to avoid this reliance on accounting disclosures by using a discounted cash flow (DCF)model. In fact, DCF models require forecasts of not only depreciation expenses, but also the timing andamount of future capital expenditures.

13

to assess. However, the number of analysts following foreign firms should indicate the

availability of forward-looking earnings information. The accuracy and dispersion of

analyst forecast errors across countries should shed further light on this issue. Later, we

provide some evidence both on the extent of analyst followings and the accuracy of their

forecasts for our sample of foreign firms.

C. Capturing value in finite horizon forecasts

In theory, any accounting system that satisfies the CSR will eventually capture firm

value. However, in practice, a higher quality accounting system will do so more quickly

[see Bernard(1995)]. In this sense, an accounting system could be described as higher

quality if the resulting V metric converges to firm value with relatively few earnings

forecast periods.

For example, the common Japanese practice of reporting on a "parent-only" basis

illustrates poor quality accounting. Although some larger Japanese firms now prepare

consolidated statements, most firms in Japan continue to use parent-only accounting.9

Under parent-only accounting, the profit or loss of majority-owned subsidiaries are

reflected in the parent's income only to the extent of the dividends paid. Therefore, when

we use forecasted Japanese GAAP earnings to value the parent, we are effectively using a

dividend discount model (DDM) for that portion of its value pertaining to its majority-

owned subsidiaries. Technically, this accounting rule does not violate CSR, because the

value created by these subsidiaries will eventually be incorporated in the parent’s income.

9 At the time of writing, 85% of the Japanese EPS forecasts in the I/B/E/S database are on a "parent-only"

basis.

14

However, this feature of Japanese GAAP prevents the accounting system from capturing

value creation in unconsolidated subsidiaries on a timely basis.

To provide some evidence on the issue, we estimate V using accounting numbers from 20

countries (including separate estimations in Japan for "parent-only" and "consolidated"

firms). Specifically, we compare the amount of cross-sectional variation in stock prices

explained by V (based on one- and two-year ahead EPS forecasts), relative to historical

measures such as book value and earnings. If a country's accounting system does not

capture value quickly, V will have little power to explain cross-sectional stock prices

beyond historical book and earnings numbers. However, if local analyst earnings

expectations are value-relevant, and are impounded in stock prices in a manner consistent

with the EBO model, V should explain prices better than either earnings or book value.

IV. Model Estimation Procedures

To operationalize equation (4), we need four parameters: the cost of equity capital (re),

the current book value (Bt), future earnings forecasts (NIt+i), and future dividends (Divt).

In this section, we discuss the specifics of the model estimation procedure, along with

assumptions we make about each parameter.

A. Cost of equity capital (re).

In theory, re should be firm and time-period specific, reflecting the premium demanded

by equity investors to invest in a firm or project of comparable risk at a given point in

time. In practice, however, there is little consensus on how this discount rate should be

15

determined. For this study, we derive a country-specific cost of equity based on average

local interest rates for each year of our sample. Because earnings forecasts are

denominated in nominal local currency, the corresponding discount rate should reflect

each country’s inflationary expectations. Allowing the discount rate to vary across

countries provides some control over cross-country differences in expected inflation.

To derive a country-specific cost of equity, we add a constant market risk premium to the

average annual yield rate on local long-term government bonds (GBYs). During our

sample period, the average yield on U.S. government bonds was 7.76 percent. The long-

term expect return on U.S. equities is approximately 12 percent (e.g., see Copeland et. al.

(1996)). This suggests an equity risk premium of 4.24 percent, which is applied to all

countries.10 Specifically, the discount rate for country i in year t (reit) is computed as:

reit = .0424 + GBYit ,

where GBYit is the government bond yield for country i in year t, obtained from the

International Financial Statistics Yearbook prepared by the Statistics Department of the

International Monetary Fund (IMF). Our choice of the GBY as a benchmark for local

interest rates is driven by the availability of this rate across many countries, and the long-

term nature of our valuation exercise. 17 of our sample countries had a complete set of

annual GBYs over our sample period. Another three countries (Finland, Korea, and

10

Note that our key results are not sensitive to the choice of 4.24 percent as the market risk premium. Weobtain similar results using constant risk premiums as low as 0.24 percent and as high as 8.24 percent.While alternatives to a constant market risk premium may be justified, particularly in hyper-inflationaryenvironments, our approach avoids ad hoc adjustments. The use of a constant market risk premium is also

16

Spain) had nearly complete records and we were able to obtain close proxies for their

GBYs.11

B. Future Dividends.

We estimate future dividends using each firm's current dividend payout ratio.

Specifically, we divide dividend to common shareholders by current net income to obtain

the current dividend payout ratio (k). If net income is negative, we estimate k by

dividing common dividends by 3% of total assets.12 As discussed later, the payout ratio is

combined with future earnings forecasts and the CSR to derive future book values.

Although firm dividend policy appears to affect firm valuation [violating Miller and

Modigliani (M&M, 1961)], in fact, it does not [see Ohlson (1995) and Lee (1996)]. That

is, the EBO equation is consistent with M&M’s dividend irrelevance theory; the

dividends in the formula simply ensure that predicted book value growth in V is

consistent with the capital base anticipated by analysts when predicting future earnings.

In effect, we assume that analysts predict this future capital base using earnings forecasts

and current dividend payout ratios.

C. Future ROEs

consistent current practice by many international investment firms.11

Specifically, we constructed annual GBY proxies using three other measures obtained from the IMFStatistical Yearbook: the central bank discount rate (CBD), the money-market rate (MMR), and theaverage consumer loan rate (CLR). All three measures were available for these three countries over theentire sample period.12

In our sample, Net Income is, on average, three percent of total assets. Only 1,275 firm-years (8% of ourtotal sample) required this estimation procedure.

17

The most important and difficult task in the EBO valuation exercise is forecasting future

ROEs (or, equivalently, future earnings). To forecast future earnings, we use the

consensus (mean) one-year-ahead and two-years-ahead EPS predictions from the I/B/E/S

International database. We combine these EPS forecasts with the current book value

using the CSR to derive future ROEs.

To compute future ROEs, the theory calls for per share book values that "match" the

capital base implicit in the analysts EPS forecasts. To obtain these values, we begin with

the Global Vantage equity to common shareholders (Item #135 minus Item #119). In

most countries, I/B/E/S analysts forecast an EPS number which is close to the

comprehensive income number required to satisfy the clean-surplus relation. Or, as in

the U. S., income items not included in analyst forecasts are mean zero in expectation.

Therefore we do not make any adjustment to the reported book value.

One possible exception to this general rule is Germany. German analysts forecast

earnings based on a formula devised by the German Institute of Financial Analysts

(DVFA/SG). As part of the DVFA/SG calculation, the amount of the goodwill

amortization is added back to reported earnings. This adjustment systematically

increases analysts' estimates of future earnings relative to the earnings reported under

Germany GAAP. In theory, we should deduct the corresponding asset (i.e., reported

goodwill on the balance sheet) from the reported book value for German firms.

However, in practice, we find that this adjustment had virtually no effect on our results.13

13

While goodwill is a major component of the DVFA/SG adjustment, not all DVFA/SG adjustments areso readily identified (See Harris, Lang, and Moeller (1994)). To the extent that unidentified systematic

18

D. Forecast horizons and terminal value estimation.

Equation (4) expresses firm value in terms of an infinite series, but for practical purposes,

an explicit forecast period must be specified. This limitation necessitates a “terminal

value” estimate -- that is, an estimate of the value of the firm based on residual income

earned after the explicit forecasting period. We estimate the terminal value by first

expanding equation (4) to T terms, and then taking the next term in the expansion as a

perpetuity. For example, if the explicit forecast period ends after T periods, the “terminal

value” is:

(FROET + 1 – re)

(1 + re)T re

BT

where FROEt = NIt/(Bt-1), and NIt is the forecasted earnings to common shareholders in

year t, net of extraordinary items, taxes, and preferred dividends and is obtained from

I/B/E/S. Dividing by re implicitly assumes that the firm will earn an abnormal return

equal to (FROET+1 - re), in perpetuity, on an asset base of size BT. We assume

additional growth will not contribute to wealth creation beyond period T. We base this

assumption on the economic intuition that, in a competitive environment, abnormal

returns that result from entry barriers eventually erode.

For an accurate value estimate, T should be set large enough for firms to reach their

competitive equilibrium. However, our ability to forecast future ROEs diminishes

adjustments exist, they will introduce noise and reduce the power of our tests.

19

quickly over time, and forecasting errors are compounded in longer expansions. Since

international I/B/E/S forecasts are typically no longer than two-years ahead, we estimate

a form of V which employs only two future earnings forecasts:

Vt = Bt + (FROEt + 1 – re)

(1 + re)Bt +

(FROEt + 2 – re)(1 + re) re

Bt + 1 (6)

Bt is total common shareholders’ equity from the most recently completed fiscal year-end

(obtained from Global Vantage) divided by total shares outstanding as of the price date.14

The forecasted ROE for period t+1 (FROEt+1) is computed by dividing the I/B/E/S

consensus forecast for period t+1 (FY1) by the reported book value per share in period t.

Bt+1 is derived using the CSR: Bt+1 = Bt + (1 - k) FY1.

V. Data and Sample Description

Our U.S. sample consists of nonfinancial firms covered by both I/B/E/S and a merged

Compustat annual industrial file, including PST, full coverage and research files.

Similarly, our foreign firms consist of all companies in the intersection of: (a) the

I/B/E/S International database, and (b) the Global Vantage Industrial and Commercial

(IC) and the Issues Files. The information in these data sets spans the years 1987 to

1994. For each year, we require I/B/E/S firms to have the actual reported EPS for the

most recent fiscal year-end, a one-year ahead EPS forecast (FY1), a two-year ahead

14 We computed V using both I/B/E/S shares outstanding and Global Vantage shares outstanding. In99.9% of the cases, these two computations were within 5% of each other. We use the I/B/E/S sharesoutstanding numbers because they are more current, and incorporate any splits or dividends since the fiscalyear end.

20

forecast (FY2), as well as the stock price and shares outstanding as of the end of

September.15

We also require the following fundamental accounting information for the most recent

fiscal year (from either Global Vantage or Compustat): total book value to common

shareholders, earnings per share, dividend per share, total common shares outstanding,

and fiscal year-end date. We limit our analysis to firms with positive stock prices, shares

outstanding, book values, sales, and total assets. To ensure firms have economically

meaningful stock prices, we examine only firms whose price at the end of September is

greater than one U.S. dollar per share.

To match the I/B/E/S forecasts and the fundamental accounting information, we use each

firm's SEDOL (or CUSIP) number and fiscal year-end. Specifically, we begin our yearly

analyses with I/B/E/S firms from the September statistical period, and match each

observation to the Global Vantage (or Compustat) file record that correspond to I/B/E/S

fiscal year 0. I/B/E/S firms that specify "parent only" (or "consolidated") accounting are

matched with Global Vantage firms with a similar label. We compute per share book

values and dividends using the shares outstanding information from I/B/E/S as of the end

of each September.

In estimating equation (6), we impose a series of additional filters on the sample firms.

The purpose of these filters is to eliminate firms with extreme data values that can have

15 In many countries, regulatory filings are not publicly available until six months after the fiscal year-end. We chose the end of September for our annual analyses to ensure December year-end firms will haveample time to make available their year-end accounting results.

21

an undue influence on the results, or can generate unreasonable input parameters. These

filters, and the number of observations eliminated by each, are set out in Panel A of Table

1. The main filters relate to the dividend payout ratio (k), the reasonableness of ROEs

and forecasted ROEs, and the requirement that V be positive. A total of 887 non-U.S.

observations (6%) were eliminated by these filters. The remaining number of

observations by country and year is presented in Panel B of Table 1. A total of 12,883

foreign and 12,026 U.S. firm-years qualified for the final sample. The total number of

observations in each foreign country ranges from 33 for South Korea to 4,459 for Japan.

Most countries have at least one firm in each of the 8 years covered by our analysis.

VI. Empirical Results

Table 2 reports descriptive statistics by country for the total sample. Total market

capitalization (in millions of U.S. dollars) and the number of analysts contributing

I/B/E/S earnings forecast estimates are presented, as well as the dividend payout ratio,

return on equity, and local interest rate (estimated cost of equity). The foreign firms in

our sample are somewhat larger in size, having a mean (median) market capitalization of

$1.48 billion ($516 million), compared to the mean (median) market capitalization of

$1.38 billion ($239 million) for U.S. firms.

Our foreign and U.S. samples are quite comparable in terms of their overall profitability,

cost of equity, and analyst coverage. Table 2 shows that the typical foreign firm has a

slightly greater analyst following than its U.S. counterpart (8 versus 6), pays out a greater

proportion of its earnings in dividends (34.5% versus 9.5%), earns a slightly lower ROE

22

(10.6% versus 11.9%), and faces a slightly lower cost of equity (11.5% versus 12%).

Except for the dividend payout ratio, these differences are not statistically significant.

Evidence on the relative accuracy of international forecasts in only emerging [e.g.,

Capstaff et. al. (1996), Conroy and Harris (1995)]. Figure 1 adds to this evidence by

documenting the accuracy of analyst forecasts for the seven major countries in our

sample. Panel A reports the mean forecast bias (FER1 and FER2) and Panel B reports

the mean absolute forecast error (|FER1| and |FER2|). To construct this graph, we

compare the actual reported EPS to the I/B/E/S consensus forecast and scale the result by

the absolute value of the actual EPS. For example, the year-one forecast error is

computed as: FER1= (Forecastt+1- Actualt+1)/ |Actualt+1|. The countries are presented in

ascending order according to their year-one forecast error (or absolute error). Japanese

firms reporting under parent-only accounting (JPN(p)) are presented separately from

those filing consolidated statements (JPN(c)).

The most salient result from Figure 1 is that earnings forecasts for U.S. firms are not any

more accurate than forecasts for foreign firms. Panel A shows that analysts are overly

optimistic across all countries: both year-one and year-two forecast errors exhibit a

significant positive bias. Among the eight country-groups, the U.S. ranks seventh in

terms of the size of its one-year-ahead forecast bias, and fifth in terms of its two-year-

ahead forecast bias. Panel B shows that, in terms of absolute error, the U.S. ranks last for

one-year-ahead forecasts and fourth for two-year-ahead forecasts. A more extensive

comparative analysis of international analyst forecast errors is beyond the scope of this

23

paper. However, our findings suggest that foreign earnings forecasts are comparable in

terms of accuracy to those available for U.S. firms.16

A. Explaining Cross-Border Stock Prices

In this section, we examine the ability of the EBO model to explain the cross-sectional

variation in stock prices over different accounting environments. Frankel and Lee (1998)

shows that an EBO value measure is able to explain close to 70% of current stock prices

in the U.S. (by comparison, reported book values explain only around 35% of the

variation in U.S. stock prices). We extend this analysis to the other countries in our

sample.

Figure 2 shows the rank regression R2 from three sets of pooled regressions with

intercepts constrained to be zero. For each country with at least 600 observations, we

separately regress ranked prices (as of September 30th) on the ranks of three accounting

variables: 1) book value per share, 2) earnings per share, and 3) the EBO value estimate.

The accounting numbers are based on the latest fiscal year-end results available as of

September 30th. The EBO value estimate is based on I/B/E/S consensus forecasts from

the September statistical period. I/B/E/S disseminates this information on the third

Friday of each month, so it is widely available by month end.

Figure 2 shows that in all seven countries, V explains much more cross-sectional price

variation than either earnings or book value. In the worst two cases, V explains 48% of

16 Managers in some foreign countries may have greater scope in the accounting rules to "manage" theirreported earnings to meet analyst expectations. We thank Jim Leisenring for pointing out this possibility.

24

the cross-sectional stock price variation in Germany, and 50% of the price variation in

Japanese firms using parent-only accounting. In the best three cases, V accounts for

approximately 70% of the price variation in France, the U.S. and the U.K. Earnings has a

higher correlation with stock price than book value, explaining approximately 33% of the

price variation, versus 25% for book value. However, neither measure works

consistently well across all countries. In Germany, for example, book value accounts for

less than 10% of the cross-sectional price variation.

Figure 3 shows that the superiority of V in explaining cross-sectional prices is stable

over time. In several countries, the correlation between historical accounting numbers

and stock prices has increased over time. For example, in Australia, France, and the

U.K., earnings explains a much greater proportion of the price variation in recent years

(1993 and 1994) than it did in years (1987 and 1988). However, the most salient result

is the consistency of V . In all seven countries, across divergent accounting systems and

economic conditions, V has a much higher correlation with stock prices than either

earnings or book value.

Table 3 examines the incremental ability of V to explain current stock prices after

controlling for earnings and book value. To construct this table, we regress end-of-

September stock prices on three variables: book value per share, earnings per share, and

V . Our model specification also includes annual indicator variables. A separate

regression is run for each country. In addition, we pool all foreign firms in a single

However, this possibility does not reduce the usefulness of foreign earnings forecasts for our purposes.

25

regression reported as "All Foreign." For this regression, we standardize all variables to a

mean of zero and standard deviation of 1 by country and year. This standardization

prevents cross-country differences in the magnitude of per share variables from

influencing the results.

Table 3 demonstrates the incremental value-relevance of V . Controlling for earnings

and book value. V is overwhelmingly significant in all 20 countries. The coefficient

estimates for V are relatively stable, ranging from 0.67 in Norway to 2.56 in Italy,

suggesting a consistent relation between price and V in different accounting regimes.

The results for book value and earnings are much less stable. Conditional on V , the

coefficient estimates for earnings are consistently negative, and the coefficient estimates

on book value are insignificant in 12 out of 20 countries. Clearly, V reflects the market's

valuation process in most countries better than a simple linear combination of current

earnings and book value.

B. Country Aggregates and Global Asset Allocation Decisions

Thus far, our evidence shows the EBO model generates a better measure of firm value

than even a linear combination of earnings and book value. However, a better valuation

model does not necessarily result in better returns predictions. While regulators are

interested in the value-relevance of numbers produced by different accounting systems,

global investors are primarily interested in predicting returns. In this section, we

investigate the usefulness of the EBO model in global asset allocation decisions -- that

26

is, decisions involving the relative attractiveness of country baskets. Specifically, we

examine the ability of aggregate V /P ratios to predict country-level returns.

Due to differences in accounting conventions, tax regimes, and financing environments,

making cross-country value comparisons using accounting-based benchmarks (i.e., price-

to-earnings ratios, price-to-book ratios, and dividend yields) is notoriously difficult.

Firms from countries such as Japan, Germany, France, Denmark and Finland rely

primarily on large financial institutions and “insiders” for their financing. These

countries typically have financial reporting systems which are closely linked to their

taxation systems. As a result, firms’ reported earnings often reflect tax considerations.

Other countries, such as the U.S., U.K., Australia, Singapore, and Hong Kong, have legal

systems based on common law and financial accounting systems that are largely separate

from their taxation system.17 These environmental differences complicate the

interpretation of country-aggregate accounting numbers.

Table 4 illustrates this point. In this table, we rank 21 country portfolios (including two

Japanese entries) by three value indicators, using the most recent stock prices and

accounting data available on September 30, 1994. Panel A orders these countries by their

average book-to-market ratio (B/P). Panel B orders these countries by their average E/P

ratio, where E is the most recent reported earnings. Panel C orders these countries by

their V /P ratio, where V is the EBO value measure.

17 See Nobes (1994, 1995) for a discussion of accounting differences across these countries.

27

While these rankings are clearly correlated, Table 4 shows that they can also differ

substantially. For example, South Africa and Thailand have the lowest average B/P

ratios, but are ranked 7th and 10th respectively by average E/P. Similarly, Belgium is

ranked 5th by its average B/P ratio, but is last (21st) by the E/P ranking. The U.S. is

ranked below the middle of the pack by either B/P or E/P (14th by B/P and 12th by E/P),

yet is the 5th most attractive alternative according to the V /P ranking.

The EBO model can offer important insights on these seemingly conflicting results.

According to the model, high P/B (low B/P) countries should be associated with high

expected abnormal ROEs. Indeed, it would be inappropriate to compare B/P ratios across

countries without considering the earning potential of each country as measured by its

forecasted ROEs, relative to its cost-of-equity. To examine this relation, Figure 4 plots

the average B/P ratio for each country against the ratio of its forecasted ROEs to its

discount rates (FROE/r) using data from September 30, 1994.

As expected, Figure 4 shows that low B/P countries tend to have higher ROEs. Fitting a

linear regression line for these observations results in a statistically significant negative

slope coefficient of -0.260. However, the EBO model suggests that the relation is non-

linear. Specifically, the model implies the relation between FROE/r and B/P should

approximate an inverse function.18 This is illustrated in the graph by a curved line.

Countries along the same curve have approximately the same V /P. Countries far above

the curve (such as Norway and the Netherlands) have higher V /P values and are

18 To see this, note that FROE/r based on two-year-ahead earnings forecast is highly correlated with theterminal value in equation (6). Accordingly, FROE/r should be a linear with respect to P/B, and should

28

potentially more attractive investments. Countries substantially below the curve (for

example, Japan) have lower V /Ps and are less attractive from a value-to-price

perspective.

Table 5 presents evidence on the efficacy of the V /P ratio in predicting cross-country

returns. To construct this table, we rank 16 country portfolios each year on the basis of

their average V /P ratios.19 Each ratio is computed using publicly available information

as of September 30th. We evaluate seven difference hedge strategies. In the "Hedge 1"

strategy, we buy the top V/P country and sell an equal amount of the bottom V /P

country. In the "Hedge 2" strategy, we buy the top two V /P countries and sell the

bottom two V /P countries. The remaining strategies follow this pattern. In each case,

we hold the hedge position for 12 months and rebalance next September 30th. Table 5

reports the individual countries in the long and short portfolios each year, as well as

annual returns to each strategy.

Table 5 shows several interesting results. First, the V /P strategy yields consistently

positive returns over the eight holding periods (1987 to 1994). This strategy is successful

in global down markets (1987, 1989 and 1991) as well as up markets (1988, 1990, 1992,

and 1993). Second, the strategy is not dependent on the same countries every year.

Some countries, such as Switzerland (Japan) had consistently high (low) V/P rankings.

However, other countries' relative ranking displayed substantial year-to-year variation.

approximate an inverse function with respect to B/P.19 Austria, Finland, South Korea, and Thailand are excluded because they do not have representation ineach of the 8 sample years. The U.S. was excluded in 1994 because the 1995 returns were not available to

29

For example, Spain had the lowest V/P ranking for 1987-1989, but moved to one of the

highest V/P rankings in 1990. Similarly, Germany was a buy in the first two years and

migrated to the sell portfolio for the last six years.

Table 6 reports the mean annual return for three sets of hedge strategies, based on V /P,

B/P and E/P, as well as t-statistics based on variations in their annual returns over time.

Panel A of this table shows that all three trading strategies have some ability to predict

aggregate country-level returns. The V /P-based strategy is particularly impressive.

Buying the top V /P country and shorting the bottom V /P country results in an average

annual return of 20.9 percent (t=3.15) with 8 out of 8 years of positive returns. All 7

V /P-based hedges result in significant positive returns, and most of these strategies yield

positive returns in 7 out of 8 years. The E/P and B/P based strategies also result in

positive returns, but neither performs as consistently as the V /P strategy.

Panel B of Table 6 reports returns for each strategy based on U.S. dollars. To construct

this panel, we use the exchange rate in effect at the end of September in year t to establish

the initial position and the exchange rate at the end of September in year t+1 to unwind

the position. Dividends received are converted at the exchange rate in effect in the month

of receipt. Panel B shows that returns in U.S. dollars are much more volatile than returns

in foreign currencies. The mean annual return for the V /P strategy is higher than in

Panel A. However, the year-to-year performance is less consistent, resulting in lower t-

statistics. Interestingly, neither the B/P nor the E/P strategy yields statistically significant

us at the time of writing.

30

returns once exchange rates are taking into account. However, the V /P strategy

continues to yield significant positive returns.

VII. Summary

In this paper, we examined the efficacy of the residual income model in explaining cross-

border stock prices and in evaluating country portfolios. We find that an empirical

estimate of firm value based on this model is much more highly correlated with

international stock prices than traditional accounting numbers such as book value and

earnings. Indeed, we find an EBO value metric has substantial explanatory power for

cross-sectional prices, even after controlling for both earnings and book value. This

result is robust over time and across a variety of accounting systems.

The main lesson we take from this analysis is that accounting numbers produced under

any system must be understood in context. Reported earnings, book values, and other

numbers are not designed to communicate a firm’s fundamental value, and should not be

used naively as surrogates for firm value. Except under strong assumptions, none of

these measures, taken alone, captures the concept of intrinsic firm value. However, when

combined with forecasted earnings in a theoretically consistent framework, accounting

numbers produced under a variety of systems all can be highly value-relevant.

We also discuss the minimal conditions necessary for successful implementation of this

valuation model. Specifically, the model requires that: 1) future “dirty surplus”

adjustments in the accounting system have zero expected value, 2) sufficient information

is available for professional analysts to make reliable earnings forecasts under local

31

GAAP, and 3) the local accounting system is capable of capturing firm value “quickly,”

using only a few earnings forecast periods. We note that these conditions are imperfectly

satisfied in our sample countries, particularly in Japan and Germany. The relatively poor

correlation between price and value for German and Japanese firm (particularly Japanese

firms on parent-only accounting) suggest these accounting problems add noise to the

value estimation process.

These results have implications for the establishment of international accounting

standards. Specifically, our findings imply that regulatory efforts to harmonize

international standards need not focus on achieving “superficially comparable” earnings

and book values, or standardizing specific rules such as the amortization of goodwill. 20

Rather, greater emphasis might be more profitably placed on finding low-cost solutions

to three implementation problems cited above. For example, the clean-surplus

accounting requirement has direct implications for the reporting of the components of

comprehensive income, a current agenda item for the Financial Accounting Standards

Board. Greater consistency in the reporting of these items will enhance users' ability to

monitor a firm's adherence to clean surplus accounting, and to assess the likelihood of re-

occurrence of "dirty surplus" items. In the same spirit, more stringent requirements to

report on a consolidated basis will mitigate the "slow value convergence" problem

confronting many Japan firms using parent-only accounting. More transparent and

20 Several recent studies address the information content of Form 20-F U.S. GAAP reconciliation items(for example, see Amir, Harris, and Venuti (1993), Bandyopadhyay et. al. (1994), Barth and Clinch(1996), Chan and Seow (1995), McQueen (1993)). Our work does not relate directly to this literature.However, our results suggest that earnings forecasts based on local GAAP may represent an omittedvariable in the valuation equations used in some of these studies. To the extent that 20-F reconciliationitems are already incorporated in analyst earnings forecasts (a possibility implied by Amir, Harris andVenuti (1993)), some of these prior studies might ascribe more value relevance to the Form 20-F itemsthan is warranted.

32

consistent accounting rules in these two areas can have a direct impact on the usefulness

of accounting information in international valuation applications.

Our analysis also highlight several important limitations of the EBO model. First, our

estimation procedure is hampered by the relative scarcity of long-term analyst earnings

forecasts for international firms. Second, the cost-of-capital estimate used in our tests is

a coarse approximation. We allow this rate estimate to vary by country and time-period,

and our results are insensitive to relatively large perturbations in the market risk premium

(+/- 4 percent). Nevertheless, we do not adjust for industry risk factors, nor do we allow

the risk premium component of the discount rate to vary across countries. Accordingly,

our estimate of V is best regarded as a first approximation of the present value of future

dividends. We expect empirical results in both valuation and returns prediction to

improve as longer-term earnings forecasts and better measures of country-specific risk

become available.

Despite these limitations, our empirical results are encouraging. We find that our

relatively simple estimate of V has more power to explain cross-border firm values than a

linear combination of earnings and book value. Moreover, we show that a trading

strategy based on country-level V /P ratios yields consistently positive returns between

1987 and 1994. This result may be due to risk differences across countries and is not

necessarily evidence of global market inefficiencies. Nevertheless, whether these return

differentials are due to market mispricings or country-specific risk premiums, the

empirical fact that V /P predicts subsequent country-level returns is, we believe, an

important contribution.

33

This study suggests several interesting venues for future research. First, our analysis

brings into sharp focus the important role of analyst forecasts of earnings in firm

valuation. A key question is whether these forecasts fully incorporate currently available

information. Frankel and Lee (1998) examine the predictability of analyst forecast errors

in the U.S., and conclude that a portion of this error is predictable using ex ante firm

characteristics. Similarly, Brown et. al. (1995) develop a model for predicting one-quarter

ahead earning surprises, and report success in a short-term trading strategy. The extent to

which such results hold in foreign markets will provide additional insights on both the

reliability of analyst forecasts for foreign firms, and the relative efficiency of foreign

capital markets.

Second, surprisingly little work has been done on the predictability of cross-sectional

returns in foreign equity markets. Brouwer, van der Put, and Veld (1996) and Haugen

and Baker (1996) evaluate value-based investment strategies in an international context.

These studies demonstrate that accounting-based ratios such as B/P, CF/P and E/P have

predictive power for cross-sectional returns in several major countries. Frankel and Lee

(1998) show that V /P ratios predict returns in the U.S. Questions remain, however, as to

whether returns to such value-based strategies are due to risk differences or market

inefficiencies. International evidence on the ability of the EBO model to predict cross-

sectional stock prices should help shed additional light on this subject.

In sum, we believe that the EBO model is a promising tool for international investment

and global asset allocation decisions. It is conceptually superior to other accounting-

34

based valuation metrics for this purpose. Empirically, our results demonstrate that this

model also exhibits surprisingly high resilience to cross-border accounting differences.

We regard these findings as a promising first step towards a unified valuation model

which will better accommodate the accounting numbers produced by the myriad of

accounting systems world-wide.

35

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AppendixSummary of Dirty Surplus Adjustments under U.S. GAAP

In U.S. GAAP, the following items are currently required to be reported directly in equityinstead of in net income. [source: Johnson, Reither, and Swieringa (1995)]

Item Description U.S. GAAPReference

Probable Effect on EBO Valuation

Foreign currency translationadjustments

FASBStatement 52,paragraph 13

Marks a firm’s net investment in foreignsubs at year-end to U.S. dollars at currentexchange rates; zero expected value;unlikely to affect earnings forecasts.

Gains and losses on foreign currencytranslations that are designated as,and are effective as, economichedges of a net investment in aforeign entity

FASBStatement 52,paragraph 20b

Mark-to-market accounting for economichedges of the above item; zero expectedvalue; unlikely to affect earnings forecasts.

A change in the market value of afutures contract that qualifies as ahedge of an asset reported at fairvalue

FASBStatement 80,paragraph 5

Mark-to-market accounting for economichedges in general; zero expected value;unlikely to affect earnings forecasts.

The excess of the additional pensionliability over unrecognized priorservice cost (that is, net loss not yetrecognized as net periodic pensioncost)

FASBStatement 87,paragraph 37

Future adjustments to this item reflectunforeseeable changes in pension liability;unlikely to affect earnings forecasts.

Unrealized holding gains and losseson available-for-sale securities

FASBStatement 115,paragraph 13

Mark-to-market accounting for marketablesecurities; zero expected value; unlikely toaffect earnings forecasts.

Unrealized holding gains and lossesthat result from a debt security beingtransferred into the available-for-salecategory from the held-to-maturitycategory

FASBStatement 115,paragraph 15c

Mark-to-market accounting for transfers tothe available-for-sale category. If analystsalready have information on the marketvalue of these assets, these transfers shouldnot affect earnings forecasts

Subsequent increases (decreases) inthe fair value of available-for-salesecurities, (if not an other-than-temporary impairment), previouslywritten down as impaired

FASBStatement 115,paragraph 16

Market-to-market accounting forpreviously impaired marketable securities;unlikely to affect earnings forecasts.

Table 1Sample Selection

Panel A. Sample Selection and Number of Observations Removed by Each FilterThis panel reports the sequential filters applied to obtain the final sample of observations. Allfirms must be in the I/B/E/S database. In addition, U.S. firms must be in the Computstatdatabase and foreign firms must be in the Global Vantage database.

Foreign U.S.

Number of Firm-years meeting the initial data requirements forboth I/B/E/S and Global Vantage (or Compustat): 13,770 13,389Eliminate:1) Firms with extreme current or forecasted ROEs: (|ROEt| or |FROEt+2| >2.0) (265) (316)2) Firms with extreme dividend payout ratios (k > 2 or K < 0) (317) (322)3) Firms with extreme B/P and V/P ratios (B/P > 10 or V/P > 10) (45) (227)4) Firms with negative EBO values ( Vt > 0.0) (256) (481)

5) Firms with significant differences in shares outstanding between fiscal year-end and September 30 (4) (17)

Total Remaining Observations 12,883 12,026

Table 1Sample Selection (continued)

Panel B. Observations by Year and CountryThis panel presents the number of observations in our sample by year and country.

YearsCountry 1987 1988 1989 1990 1991 1992 1993 1994 Country

TotalU.S. 1,320 1,368 1,420 1,398 1,429 1,491 1,685 1,915 12,026All Foreign 810 1,333 1,611 1,700 1,848 1,866 1,785 1,930 12,883Australia 68 67 82 71 71 77 83 94 613Austria 0 0 8 12 21 15 17 26 99Belgium 10 13 14 13 15 14 14 21 114Canada 164 196 206 190 178 192 194 206 1,526Denmark 8 8 8 11 16 16 14 28 109Finland 0 5 7 11 6 8 12 22 71France 50 65 76 96 98 119 95 121 720Germany 52 55 68 70 87 90 94 135 651Italy 6 7 14 16 33 42 28 29 175Japan 102 494 584 669 699 675 632 604 4,459Netherlands 17 21 25 58 61 69 57 61 369Norway 2 1 2 11 12 9 13 19 69So. Africa 8 16 22 15 19 23 23 25 151So. Korea 0 0 4 3 5 6 7 8 33Spain 7 6 15 23 32 50 32 40 205Sweden 7 9 11 11 10 11 11 20 90Switzerland 6 8 8 9 9 12 10 21 83Thailand 0 1 8 19 40 40 26 28 162U.K. 303 361 449 392 436 398 423 422 3,184YearTotal 2,130 2,701 3,031 3,098 3,277 3,357 3,470 3,845 24,909

Table 2

Descriptive Statistics by Country

Country No. ofObs

Market Cap.($U.S. million)

Number ofAnalyst

Following

Dividend Payout Return on EquityLocal

InterestRate

Mean Median Mean Median Mean Median Mean Median MeanU.S. 12,026 1,379 239 9 6 0.233 0.095 0.102 0.119 0.120All Foreign 12,883 1,482 516 9 8 0.360 0.345 0.096 0.106 0.115Australia 613 1,380 516 10 10 0.540 0.550 0.120 0.110 0.154Austria 99 604 259 7 6 0.529 0.471 0.068 0.061 0.111Belgium 114 1,836 940 8 8 0.453 0.386 0.111 0.121 0.124Canada 1,526 762 235 9 8 0.296 0.238 0.074 0.091 0.135Denmark 109 1,155 329 10 9 0.261 0.196 0.123 0.118 0.136Finland 71 436 187 7 5 0.363 0.246 0.066 0.069 0.127France 720 3,040 3,040 12 10 0.316 0.278 0.111 0.124 0.128Germany 651 1,974 667 15 13 0.499 0.494 0.074 0.078 0.106Italy 175 2,325 474 12 11 0.322 0.306 0.095 0.091 0.153Japan 4,459 1,778 609 7 6 0.377 0.319 0.062 0.058 0.081Netherlands 369 1,886 344 17 16 0.364 0.368 0.141 0.133 0.110Norway 69 624 201 9 8 0.335 0.316 0.075 0.106 0.144South Africa 151 1,070 589 3 3 0.453 0.410 0.195 0.186 0.193South Korea 33 1,568 1,278 6 5 0.486 0.493 0.054 0.045 0.120Spain 205 1,463 635 15 15 0.355 0.315 0.087 0.082 0.164Sweden 90 1,375 591 9 9 0.398 0.345 0.146 0.145 0.146Switzerland 83 6,102 1,017 16 15 0.331 0.303 0.086 0.086 0.085Thailand 162 368 117 5 4 0.440 0.418 0.171 0.165 0.136U.K. 3,184 1,405 289 9 8 0.441 0.401 0.167 0.159 0.132

Table 3Regression of Stock Price on Accounting Variables

Country BPS EPS Value R2 F-statistic Obs.

coeff. U.S 0.07 -0.10 1.23 0.88 8073.9 12026t-stat 9.16 -2.05 156.8coeff All Foreign 0.11 -0.09 0.83 0.72 3015.7 11881t-stat 17.23 -13.3 132.1coeff. Australia 0.10 -0.02 1.63 0.94 804.2 613t-stat 1.58 -0.04 31.9coeff. Austria 0.50 -0.51 1.55 0.93 137.9 99t-stat 3.59 -0.38 16.7coeff. Belgium 0.74 -1.87 1.31 0.82 49.0 114t-stat 4.94 -1.77 6.2coeff. Canada 0.13 -0.20 0.84 0.87 929.2 1526t-stat 7.53 -2.24 42.7coeff. Denmark 0.26 -1.62 1.53 0.94 166.5 109t-stat 3.50 -3.12 21.1coeff. Finland 0.02 -0.61 1.32 0.96 174.1 71t-stat 1.03 -3.33 26.5coeff. France -0.08 -1.41 1.73 0.88 474.6 720t-stat -1.24 -3.50 38.6coeff. Germany -0.02 -1.14 1.61 0.85 341.7 651t-stat -0.37 -2.84 23.8coeff. Italy 0.03 -5.07 2.56 0.91 158.7 175t-stat 0.25 -6.54 29.2coeff. Japan (C) 0.34 -6.91 2.33 0.92 623.7 585t-stat 5.35 -5.62 24.8coeff. Japan (P) 0.68 -4.08 2.30 0.85 2072.1 3874t-stat 17.48 -7.95 47.5coeff. Netherlands 0.06 -1.21 1.18 0.92 413.5 369t-stat 1.40 -3.25 33.5coeff. Norway 0.08 0.65 0.67 0.89 53.0 69t-stat 1.19 2.62 5.21coeff. South Africa -0.01 4.94 1.33 0.91 138.5 151t-stat -0.06 6.07 10.8coeff. South Korea 0.18 -1.74 1.83 0.98 217.2 33t-stat 1.38 -1.00 16.7coeff. Spain 0.21 -2.13 1.72 0.74 55.0 205t-stat 2.24 -2.75 13.4coeff. Sweden 0.02 -0.50 1.32 0.87 55.8 90t-stat 0.46 -1.63 7.87coeff. Switzerland 0.00 0.71 1.05 0.97 261.8 83t-stat -0.05 1.22 27.9coeff. Thailand 0.46 -2.17 1.66 0.80 65.1 162t-stat 1.41 -1.37 13.7coeff. U.K. 0.07 -0.40 1.77 0.91 3013.3 3184t-stat 4.59 -5.98 122.2

Table 4

Country Rankings by Various Accounting-based Value Metrics (B/P, E/P, and Vt /P)

Panel ARanking by Average B/P

(book value)

Panel BRanking by Average E/P

(earnings)

Panel C

Ranking by Average Vt /P

(EBO value)Rank Country Obs. Avg B/P Rank Country Obs. Avg E/P Rank Country Obs. Avg Vt /P

1 Switzerland 21 1.74 1 Sweden 20 0.123 1 Norway 19 1.2322 Sweden 20 1.22 2 Finland 22 0.094 2 Netherlands 61 0.8083 Finland 22 1.09 3 Switzerland 21 0.082 3 Switzerland 21 0.7654 Norway 19 0.97 4 Denmark 28 0.071 4 Finland 22 0.7505 Belgium 21 0.91 5 Norway 19 0.065 5 U.S. 1915 0.7366 Netherlands 61 0.91 6 Netherlands 61 0.052 6 Sweden 20 0.6767 Italy 29 0.89 7 South Africa 25 0.049 7 U.K. 422 0.6408 Denmark 28 0.85 8 U.K. 422 0.048 8 Denmark 28 0.6069 Spain 40 0.78 9 Australia 94 0.045 9 Canada 206 0.59710 South Korea 8 0.69 10 Thailand 28 0.043 10 France 121 0.57711 Canada 206 0.66 11 Italy 29 0.042 11 Belgium 21 0.57312 Austria 26 0.65 12 U.S. 1915 0.038 12 Austria 26 0.56413 France 121 0.64 13 Austria 26 0.030 13 Australia 94 0.52714 U.S. 1915 0.59 14 Canada 206 0.029 14 Spain 40 0.52715 Germany 135 0.57 15 Spain 40 0.027 15 Germany 135 0.46816 U.K. 422 0.52 16 France 121 0.025 16 Thailand 28 0.46617 Japan (c) 86 0.52 17 South Korea 8 0.020 17 Italy 29 0.44018 Japan (p) 518 0.51 18 Japan (p) 518 0.013 18 South Africa 25 0.33219 Australia 94 0.50 19 Germany 135 0.013 19 South Korea 8 0.31420 South Africa 25 0.48 20 Japan (c) 86 0.011 20 Japan (c) 86 0.29221 Thailand 28 0.38 21 Belgium 21 -0.006 21 Japan (p) 518 0.275

Table 5

Returns to V/P rankings at the Country Level

1987 1988CTRY V/P RET1 Strategy HRET1 CTRY V/P RET1 Strategy HRET1SPN 0.055 -0.068 Hedge 1 0.022 SPN 0.083 0.110 Hedge 1 0.549SAF 0.249 -0.378 Hedge 2 0.109 JAP 0.266 0.503 Hedge 2 0.195JAP 0.256 0.019 Hedge 3 0.070 DEN 0.515 0.381 Hedge 3 0.087AUS 0.343 -0.218 Hedge 4 0.092 SAF 0.529 0.629 Hedge 4 -0.049SWE 0.375 -0.041 Hedge 5 0.072 SWE 0.546 0.318 Hedge 5 -0.073ITA 0.461 -0.121 Hedge 6 0.061 ITA 0.582 0.211 Hedge 6 -0.029NOR 0.477 -0.683 Hedge 7 0.129 AUS 0.599 0.211 Hedge 7 0.017FRA 0.510 -0.033 FRA 0.651 0.515DEN 0.511 0.212 CAN 0.674 0.208U.K. 0.517 -0.148 GER 0.676 0.504CAN 0.539 -0.113 BEL 0.711 0.406U.S. 0.614 -0.049 U.S. 0.715 0.148GER 0.631 -0.062 U.K. 0.759 0.170BEL 0.633 0.011 SWI 0.987 0.251SWI 0.682 -0.183 NET 1.070 0.345NET 0.950 -0.045 NOR 1.324 0.659

1989 1990CTRY V/P RET1 Strategy HRET1 CTRY V/P RET1 Strategy HRET1SPN 0.067 -0.444 Hedge 1 0.225 JAP 0.251 0.130 Hedge 1 0.010JAP 0.195 -0.344 Hedge 2 0.223 SAF 0.498 0.253 Hedge 2 -0.049SAF 0.426 0.033 Hedge 3 0.058 GER 0.535 0.178 Hedge 3 0.025DEN 0.452 -0.077 Hedge 4 0.088 DEN 0.542 0.216 Hedge 4 0.063ITA 0.467 -0.254 Hedge 5 0.079 CAN 0.584 0.122 Hedge 5 0.054GER 0.560 -0.086 Hedge 6 0.104 ITA 0.629 0.044 Hedge 6 0.075CAN 0.574 -0.170 Hedge 7 0.085 NOR 0.663 0.071 Hedge 7 0.100FRA 0.586 -0.272 AUS 0.690 0.125AUS 0.596 -0.127 U.S. 0.705 0.062SWE 0.598 -0.199 SWE 0.767 0.321NOR 0.606 0.140 FRA 0.819 0.222BEL 0.621 -0.208 BEL 0.859 0.142U.S. 0.714 0.099 U.K. 0.885 0.395U.K. 0.757 -0.239 SPN 0.889 0.350NET 0.889 -0.123 NET 0.940 0.145SWI 0.914 -0.219 SWI 1.193 0.140

Table 5 (continued)

Returns and V/P rankings at Country Level

1991 1992CTRY V/P RET1 Strategy HRET1 CTRY V/P RET1 Strategy HRET1

JAP 0.248 -0.295 Hedge 1 0.188 JAP 0.355 0.267 Hedge 1 0.059SAF 0.413 -0.130 Hedge 2 0.157 SAF 0.362 0.487 Hedge 2 -0.147GER 0.456 -0.186 Hedge 3 0.205 CAN 0.518 0.448 Hedge 3 0.062ITA 0.460 -0.374 Hedge 4 0.240 AUS 0.621 0.437 Hedge 4 0.126DEN 0.461 -0.245 Hedge 5 0.162 GER 0.631 0.251 Hedge 5 0.182AUS 0.510 0.107 Hedge 6 0.122 DEN 0.645 0.265 Hedge 6 0.155CAN 0.511 0.093 Hedge 7 0.077 BEL 0.663 0.133 Hedge 7 0.148SPN 0.546 -0.303 U.K. 0.698 0.482SWE 0.552 -0.212 SPN 0.715 0.437U.K. 0.598 -0.099 U.S. 0.743 0.241BEL 0.613 0.027 FRA 0.758 0.285NOR 0.628 -0.395 ITA 0.762 0.659FRA 0.632 -0.030 NOR 0.785 0.751U.S. 0.701 0.115 SWE 0.876 0.930NET 0.846 -0.003 NET 0.982 0.132SWI 0.874 -0.107 SWI 1.238 0.326

1993 1994CTRY V/P RET1 Strategy HRET1 CTRY V/P RET1 Strategy HRET1

JAP 0.276 -0.035 Hedge 1 0.227 JAP 0.278 -0.126 Hedge 1 0.387SWE 0.447 0.102 Hedge 2 0.147 SAF 0.332 0.008 Hedge 2 0.245SPN 0.460 0.269 Hedge 3 0.089 ITA 0.440 -0.099 Hedge 3 0.193ITA 0.482 0.272 Hedge 4 0.007 GER 0.468 -0.019 Hedge 4 0.199GER 0.485 0.140 Hedge 5 0.010 SPN 0.527 0.018 Hedge 5 0.180DEN 0.487 0.096 Hedge 6 0.002 AUS 0.527 0.041 Hedge 6 0.148SAF 0.495 0.818 Hedge 7 -0.097 BEL 0.573 -0.025 Hedge 7 0.143CAN 0.502 0.050 FRA 0.577 -0.064FRA 0.531 0.103 CAN 0.597 0.084AUS 0.574 0.124 DEN 0.606 0.029U.K. 0.579 0.063 U.K. 0.640 0.122BEL 0.626 0.160 SWE 0.676 0.200U.S. 0.763 0.033 SWI 0.765 -0.011NET 0.799 0.242 NET 0.808 0.111SWI 0.816 0.168 NOR 1.232 0.261NOR 0.872 0.193

Table 6

Hedge Returns for B/P, E/P, and V/P Strategies

Panel A: Returns in Foreign Country CurrenciesV/P Portfolios B/P Portfolios E/P Portfolios

Strategy MeanAnnualReturn

T-stat YearsPositive

Strategy MeanAnnualReturn

T-stat YearsPositive

Strategy MeanAnnualReturn

T-stat YearsPositive

Hedge 1 0.209 3.152*** 8 of 8 Hedge 1 0.092 1.374 6 of 8 Hedge 1 0.246 1.905** 6 of 8Hedge 2 0.110 2.254** 6 of 8 Hedge 2 0.108 1.403 6 of 8 Hedge 2 0.143 2.593** 7 of 8Hedge 3 0.099 4.282*** 8 of 8 Hedge 3 0.099 2.597** 7 of 8 Hedge 3 0.095 2.183** 6 of 8Hedge 4 0.096 2.861** 7 of 8 Hedge 4 0.063 1.906** 6 of 8 Hedge 4 0.100 2.350** 6 of 8Hedge 5 0.083 2.624** 7 of 8 Hedge 5 0.042 1.496* 6 of 8 Hedge 5 0.078 1.905** 5 of 8Hedge 6 0.080 3.401*** 7 of 8 Hedge 6 0.046 1.943** 7 of 8 Hedge 6 0.076 2.337** 6 of 8Hedge 7 0.075 2.607** 7 of 8 Hedge 7 0.052 3.051*** 7 of 8 Hedge 7 0.080 2.566** 7 of 8

Panel B: Returns in U. S. DollarsV/P Portfolios B/P Portfolios E/P Portfolios

Strategy MeanAnnualReturn

T-stat YearsPositive

Strategy MeanAnnualReturn

T-stat YearsPositive

Strategy MeanAnnualReturn

T-stat YearsPositive

Hedge 1 0.236 1.599* 6 of 8 Hedge 1 0.012 0.154 6 of 8 Hedge 1 0.108 0.833 5 of 8Hedge 2 0.324 1.273 6 of 8 Hedge 2 0.131 1.086 5 of 8 Hedge 2 0.058 0.418 5 of 8Hedge 3 0.340 1.488* 6 of 8 Hedge 3 0.099 0.719 5 of 8 Hedge 3 0.169 1.071 5 of 8Hedge 4 0.372 1.652* 5 of 8 Hedge 4 -0.088 -0.406 5 of 8 Hedge 4 0.136 0.563 5 of 8Hedge 5 0.316 1.396 5 of 8 Hedge 5 -0.155 -0.598 3 of 8 Hedge 5 0.222 0.798 4 of 8Hedge 6 0.472 2.161** 7 of 8 Hedge 6 -0.152 -0.675 2 of 8 Hedge 6 0.194 0.633 4 of 8Hedge 7 0.570 3.468*** 7 of 8 Hedge 7 -0.110 -0.441 4 of 8 Hedge 7 0.199 0.589 4 of 8