Chapter 8

C H A P T E R 8

Usefulness of AccountingInformation to Investorsand Creditors

L E A R N I N G O B J E C T I V E S

After reading this chapter, you should be able to:

· Understand the link between accounting information, dividends, and stock prices.· Understand the basics of residual income models, their strengths, weaknesses, and

how they are used for valuation and performance assessment.· Understand the basics of the efficient-markets hypothesis, its implications for

accounting information, and why it is under attack.· Understand the basics of event studies and cross-sectional valuation studies.· Be familiar with the general findings of market-based accounting research regarding the

usefulness of accounting information for investors.· Understand that accounting information is useful to creditors in evaluating default

risk and predicting bankruptcy.· Understand the role of accounting information for use in forecasting earnings.

he Financial Accounting Standards Board (FASB) recognizes the existence of a diverse and pluralistic user group (see Chapter 7). However, in practice, the FASB focused on what it calls primary

user groups (investors and creditors), those assumed to be mainly interested in the amounts, timing, and uncertainties of future cash flows.' The rationale for the investor—creditor focus is that other users (e.g., governments, utility rate-setting bodies) have a commonality of interest with investors and creditors or the means of getting alternative information. The FASB's

T

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266 6 ACCOUNTING THEORY

cost–benefit calculus is similarly restricted to benefits for investors and creditors, and cost considerations are confined only to producers.

The purpose of this chapter is to examine theoretical and empirical evi-dence for the usefulness of financial accounting data to users. While we are largely focused on the FASB's primary user group—investors and creditors—we wish to note that in its broadest sense, this group is quite large. Investors include both individual and institutional shareholders, holders of interest-bearing debt (bondholders, financial institutions, etc.), and the firm's board of directors, who act on behalf of shareholders.' Although they are not strictly investors per se, equity analysts make extensive use of financial statements and are an integral part of the investing process.

Creditors are mainly considered suppliers of materials and services (accounts payable). They need financial information about their customers to determine the terms of credit. However, in a broader sense, creditors may also include taxing authorities (taxes payable) and other individuals or enti -ties that have claims on the firm before shareholders.'

Existing and potential shareholders need information to estimate the value of the firm's shares and to make wealth-enhancing capital-allocation decisions, which are also beneficial to the economy. The board of directors has the responsibility for creating and implementing strategies and policies that create wealth and ensure that management acts in the interests of the shareholders.' In this role, the board needs to be able to evaluate and reward management's efforts, abilities, and decisions, particularly management's capital-allocation decisions.'

Getting paid is certainly a major concern of the holders of interest-bearing debt, but their concern goes beyond that. While loans from com -mercial banks typically have maturities of a few years, corporate bonds have much longer maturities.' The bonds may be sold before they mature, and changes in the value of the firm affect the market value of those bonds. Bondholders must be concerned with the value of the entire firm.

Our point is that many individuals and entities have a vested interest in understanding the financial well-being of a firm. When it works well, we end up with correct securities pricing and the efficient allocation of capital in the economy (allocational efficiency). Everyone is better off—better homes, healthier children, and money for violin lessons, baseball bats, and college tuition.

We begin this chapter by examining models of equity valuation and the role of accounting information in these models. Next, we examine the role of residual income models for motivating and assessing managerial performance and valuing the firm. We then provide a background on risk and return and the efficient-markets hypothesis (EMH). Using accounting-related

Usefulness of Accounting Information to Investors and Creditors 267

capital markets research, we discuss the usefulness of accounting informa tion for the primary user groups. In that context, we show why the efficient-markets hypothesis is being challenged. We then discuss the role of accounting data for creditors and discuss the importance of earnings for forecasting. We conclude with a brief discussion of empirical research and standard setting.

Earnings, Dividends, and Stock Prices

One of the major uses of accounting data relates to valuation. In this section, we examine a model relating earnings, dividends, and stock prices. While we briefly discuss cash flows, we defer a detailed discussion of this topic to Chapter 13.

Earnings and Dividends

Lintner detailed the results of a series of interviews with corporate man-agers regarding the determinants of their dividend policies.' Managers indi -cated that major changes in "permanent" earnings were the most important determinants of the companies' dividend decisions. After giving serious consideration to both an established target payout ratio and the existing payout ratio, managers adjusted dividends to reflect the change in "per -manent" earnings. Since managers perceived that shareholders valued a smooth dividend stream, the managers made adjustments to dividend payout rates gradually. Furthermore, most managers avoided making changes to dividends that had a significant probability of being reversed in the near future. Given the seriousness and forward-looking nature of the dividend policy decision, investors regard cash dividends as credible signals of future performance. We say that a change in the cash dividend has information content.

Cash dividends are the cash flows that investors receive from a dividend-paying stock. As such, the stock price (P o) may be modeled as the present value of the future expected dividends, or

D,Po —

t=i (1 + r)t

where

D, = the dividend expected at t ime t , and r = the

rate of return expected by the shareholders.

(8.1)

268 ACCOUNTING THEORY

If the cash dividends are expected to grow at a constant rate (g), the present value of the future expected dividends may be expressed as the present value of a growing perpetuity.'

P =________________________________________________

D1(8.2)

For a firm in equilibrium, a future expected dividend can be expressed in terms of a constant dividend payout ratio (P0) and earnings per share at time t (EPS), or D, = (PO)(EPS,). This allows us to rewrite Equation 8.1 as

and Equation 8.2 as:

Po = P°

Po = P°

E P S I (8.3)1=1(1

+ r)t

(EPS1 (8.4)

r g

In these forms, we say that the stock price is equal to present value (capitalized value) of future expected earnings, adjusted by the dividend pay-out ratio. While we started with the dividend discount model, we now have the earnings model of stock valuation. Given its relation to cash dividends, it is no surprise that future earnings have a major effect on the share price.

Predicting Dividends From Current Earnings

Beaver uses the dividend valuation model to formulate the role of accounting earnings in determining firm value.' Security prices are modeled as a function of expected future dividends (Equation 8.1). Furthermore, future dividends themselves are a function of future earnings (Equation 8.3). Moreover, current accounting income is useful in predicting future earnings. As such, current income has value in predicting future dividends via its value to predict future earnings. This predictive value is one of the major arguments for the relevance of accounting information (see the discussion of SFAC No. 2 in Chapter 7).

Connecting the Dots: From Earnings to Stock Prices

Work in Financial economics regarding the theoretical value of the firm traces back to Miller and Modigliani's seminal work in which they argue that

dividend policy is irrelevant to firm valuation.' Ignoring the complicating effect of taxes, they show that the value of the firm is equal to the present value of future expected net cash flows. These net cash flows per period are defined as operating cash flow minus cash investment in assets. (This is the same definition as that used for capital budgeting analysis.)

Miller and Modigliani's net cash flow model was originally a certainty-equivalent model but has been extended to a more general model reflecting the uncertainty of future operating cash flows." The attractiveness of the cash flow valuation model for accounting is that it maps directly onto the accounting system; cash flows are explicitly measured in accounting sys tems. In contrast, dividends are a matter of corporate policy and are not a direct function of accounting systems. We make further tie-ins between cash flows and decision making in Chapter 13.

Interestingly, the FASB has implicitly adopted the cash flow valua tion model. In SFAC No. 8, The Objective of General Purpose Financial Reporting, the role of financial reporting is characterized as aiding existing and potential investors, lenders, and other creditors in assessing the amounts, timing, and uncertainty of the enterprise's prospective net cash flows. Further, the FASB asserts that accrual accounting systems, and accrual income numbers in particular, are more useful for this purpose than are simpler cash-based systems: "Accrual accounting depicts the effects of transactions, and other events and circumstances on a reporting entity's economic resources and claims in the periods in which those events occur, even if the resulting cash receipts and payments occur in a different period. This is important because information about a reporting entity's economic resources and claims and changes in its economic resources and claims dur -ing a period provides a better basis for assessing the entity's past and future performance than information solely from cash receipts and payments during that period."'

Beaver agrees with this assertion, arguing that "an accrual can be viewed as a form of forecast about the future. . . ." 13 There is empirical evidence that future cash flows are better forecast with accrual data than with cash flow data." In addition, in stock market studies, security prices are more highly correlated with accrual income than with either cash flows or working capi tal flows." Numerous studies have documented that changes in reported accounting earnings affect the value of the firm and its stock. This is not surprising if investors view such changes as permanent or persisting into the future. As such, expectations of future cash flows should also be affected; hence, the explanation for changes in stock prices as a function of the expected persistency of earnings changes.'

The implication of this literature is that accrual accounting systems ulti -mately incorporate the attribute that determines firm valuation—net cash



flow data. However, the value of the information in financial reporting does not lie in its role as a historical record but rather in its use in helping inves -tors to forecast future expected net cash flows and dividends. (This informa-tion is also useful for feedback purposes. See Chapter 7.)

Residual Income Models

Capital is necessary to generate income. Residual income is a general term for income in excess of a charge for the capital that is employed to generate that income.' The residual income concept may be applied to the enter prise as a whole or to the firm's common equity. When applied to the enter prise's operating income and invested capital, residual income is often called economic profit or Economic Value Added (EVA).' When it is applied to the firm's net income and common equity, residual income may be referred to as abnormal earnings.'

Economic Profit

It is well established that the value of a firm is equal to the present value of the future expected net cash flows.' Net cash flows are the periodic cash flows that are available to all investor claims (interest-bearing debt, pre -ferred stock, and common stock). They are much less subject to manipula tion than earnings.

One shortcoming of net cash flows is that they do not provide investors with a metric for gauging periodic performance. For example, even a highly profitable, well-managed firm can have negative net cash flows in a given period if the firm makes large investments in that period. If the investments have a positive net present value, negative net cash flows in one period is hardly a cause for concern.' Economic profit attempts to bridge the gap, providing not only a means to value the firm but also a means to assess its periodic performance.

Economic profit starts with the amount of capital that is invested at the beginning of the period. This investment has a cost. When expressed as a rate, this cost is known as the weighted average cost of capital (WACC). (We can think of the WACC as the required rate of return to all investor claims, commensurate with the risk of the net cash flows.) The WACC and the amount of capital invested determine the periodic after-tax operating income that investors expect the firm to generate. This is the dollar cost of invested capital, the charge for capital employed, or simply the capital charge. The realized after-tax operating income is compared to the amount that is expected. If the after-tax operating income exceeds the income


expected, the firm has generated an amount of income above and beyond the call of duty. This excess income is called economic profit. More formally,

Economic profit = NOPAT — capital charge (8.5)

where NOPAT is net operating profit, less taxes paid.22 Expressing the capital charge as a function of the WACC and invested capital at the beginning of the period, we have:

Economic profit = NOPAT — (WACC)(inyested capital) (8.6)

Equation 8.6 indicates that if the firm's NOPAT exceeds the capital charge, it earns an economic profit and creates wealth." To increase eco nomic profit, the firm can increase NOPAT by increasing sales or decreasing costs, decrease invested capital, or lower the firm's cost of capital (WACC).

Exhibit 8.1 presents a statement of invested capital for ABC Company. We constructed the statement from ABC's balance sheet, shown in Chapter 13, Exhibit 13.7. Note that the statement of invested capital is sim ply a rearrangement of the firm's balance sheet, putting net operating assets on the "left hand side," and all investor claims on the "right hand side."

Exhibit 8.1 Statement of Invested Capital for ABC Company

Statement of Invested Capital 2004 2005 2006 2007

Cash and equivalents $300 $244 $323 $339

Accounts receivable 930 915 1,035 1,018

Inventories 1,010 1,037 970 1,154

Accounts payable $(850) $(854) $(841) $(883)

Net operating working capital $1,390 $1,342 $1,487 $1,628

Property, plant and equipment 2,500 2,562 2,651 2,783

Invested capital (assets) $3,890 $3,904 $4,138 $4,411

Notes payable 73 58 60 67Long-term debt 657 524 539 606

Total interest bearing debt 730 582 599 673

Common stock 860 830 860 860

Retained earnings 2,300 2,492 2,679 2,878

Total common equity 3,160 3,322 3,539 3,738Invested capital (equities) $3,890 $3,904 $4,138 $4,411

272 * ACCOUNTING THEORY

Exhibit 8.2 presents a statement of economic profit for ABC Company. This statement uses invested capital from Exhibit 8.1 and operating income from ABC's income statement presented in Exhibit 13.7 in Chapter 13. Notice that economic profit is positive for all three years. However, economic profit declined in 2006 due to an increase in invested capital in 2009 and lower net operating profit after tax (NOPAT) for 2006.

Conceptually, economic profit has valuable characteristics from a perfor -mance evaluation perspective. Managers can increase economic profit, and their bonuses, by increasing NOPAT. Thus, managers have an incentive to control costs and increase sales. Furthermore, managers can increase eco -nomic profit by reducing the amount of invested capital.

In contrast, net income is a performance metric that ignores the amount of capital employed. If the firm rewards its managers based on net income alone, and if additional invested capital generates some additional net income, managers have an incentive to invest, even if the incremental investment does not earn its cost of capital.

The economic profit approach has the added benefit that it can also be used to value the enterprise. The value obtained is equal to the present value of the net cash flows.24Using the economic profit approach, the value of the firm at time 0 is equal to the invested capital in place at time 0, plus the present value of future expected economic profit, or:

NOPAT - (WACC) (invested capital), (8.7)Vo(firm) = Invested capitalo+

t=1 (1 + WACC)'

In an attempt to improve economic profit as a performance metric, some users make adjustments to the way invested capital and NOPAT are calculated. Currently, the best-known application of economic profit is EVA, a proprietary form of economic profit developed by Stern Stewart & Co. Stewart (2003) notes:

Stated in brief . . . EVA begins with . . . residual income [economic profit] . . and then proposes a series of additional adjustments to GAAP accounting that are designed to produce a reliable measure of a company's annual, sustainable cash [italics added]-generating capacity-''

Young notes that the most common accounting adjustments relate to nonrecurring gains and losses, research and development, deferred taxes,


for ABC CompanyExhibit 8.2 Statement of Economic Profit

Statement of Economic Profit 2004 2005 2006 2007

Invested capital $3,890.0 $3,904.0 $4,138.0 $4,411.0

Operating income 578.0 555.0 587.0

Taxes on operating income (40%) (231.2) (222.0) (234.8)

Net operating profit after tax 346.8 333.0 352.2

Capital charge on invested capital (8%) (311.2) (312.3) (331.0)

Economic profit $35.6 $20.7 $21.2

provisions for warranties and bad debts, LIFO reserves, goodwill, depreciation, and operating losses.26

Residual Income and the Dividend Discount Model

Economic profit and EVA focus on the valuation and performance mea -surement of the operations of the enterprise as a whole. Residual income—sometimes called abnormal earnings—is focused on net income and the firm's common equity. It is defined as:

Residual income = actual earnings – required earnings (8.8)

where required earnings are the amount of earnings that compensates shareholders for the equity capital invested and the risk they bear. Required earnings may be written as the beginning-of-period book equity, multiplied by the cost of equity (r):

Residual income = earnings – r(book equity) (8.9)

Note the similarity between Equation 8.9 and Equation 8.6. Ohlson and, also, Feltham and Ohlson use a residual income framework to predict and explain stock prices.' The model starts with the dividend discount model (Equation 8.1). Next, it specifies that all profit and loss elements go through income. This specification, known as clean surplus accounting, relates the current book equity to previous book equity, earnings, and dividends:

Book equity, = book equity,_, + earnings – dividends, (8.10)


The FASB comprehensive orientation of SFAS No. 130 (Chapter 11) tiesin well with the clean surplus approach. Rearranging Equation 8.10 allowsdividends to be expressed in terms of book values and earnings:

Dividends, = earnings,— (book equity,— book equity,_,) (8.11)

By using Equations 8.1 and 8.11, it can be shown that the price of the

firm's stock is equal to:

[earningst r(book equityt_i )]= Book equity() +

r=1 (1 + ry(8.12)

where r is the cost of equity and the numerator of the second expression is residual income or abnormal earnings. Note the similarity between Equation 8.12 and Equation 8.7.

We started with Equations 8.1 (dividend discount model) and 8.11 and rearranged them to obtain Equation 8.12. As such, Equation 8.12 is simply a restatement of the dividend discount model in terms of future expected earnings, the cost of equity and current and future expected book equity. By itself, this model offers little additional utility over the dividend discount model per se. However, the utility of the Equation 8.12 can be increased if the user can incorporate additional information regarding forecasts of future abnormal earnings.'

Dechow, Hutton, and Sloan perform an empirical assessment of the residual income model. They find that "residual income follows a mean reverting process . . associated with firm characteristics suggested by accounting and economic analysis."29The rate of mean reversion decreases with the quality of earnings and increases with the dividend payout ratio. It is also correlated across firms in the same industry. They also find that "incorporating information in analysts' forecasts of earnings into the information dynamics increases forecast accuracy."30 Hence, the residual income model allows the user to incorporate nonaccounting information into the model to improve its forecast accuracy.

Note that the higher the abnormal earnings, the higher the value of the firm's common equity. Beaver discusses several sources that give rise to abnormal earnings.31First, firms do not carry on the balance sheet the posi -tive excess present value above the cost of the project (positive net present value). Second, many matching and recognition procedures under historical costing tend to be conservative in nature (e.g., accelerated depreciation methods and LIFO costing for inventories and cost of goods sold, immediate write-off of research and development, and possible undervaluation of other intangibles).


Qiang demonstrates that abnormal earnings increase with industry con-centration, industry-level barriers to entry, and industry conservative accounting factors. The author also finds that differences in firm abnormal earnings increase with "market share, firm size, firm-level barriers to entry, and firm conservative accounting factors."32

Residual Income and Performance

Measurement: The Good and Bad

In this section, we examine the pros and cons of residual income models used for performance measurement." While our focus is broader than EVA per se, much of the research on residual income has been done in the context of evaluating EVA.

Residual Income: The Good

Residual income is an accounting measure, which in its basic form uses financial data that follow a defined set of rules. Unlike the stock price, it can be used as a company and intracompany performance measurement tool.

It recognizes that all capital—debt as well as equity—has a cost; capital is not a free good. Making capital an explicit part of the model raises the awareness of using excess capital to generate income. Stewart notes:

If a firm cannot give its shareholders at least the return that they could earn by investing on their own, it will lose value. Thus in an economist's view, a company does not begin to earn a profit until it can cover the opportunity cost of equity capita1.34

Although not explicitly designated as an application of residual income, Berkshire Hathaway and CEO Warren Buffett explicitly recognize the cost of capital in communications with corporate shareholders and also with its subsidiary managers.

When capital invested in an operation is significant, we also both charge managers a high rate for incremental capital they employ and credit them at an equally high rate for capital they release. . . . The consequence of this two-way arrangement is that it pays [managers]—and pays [them] well—to send to Omaha any cash he can't advantageously use in his business.'


As a proprietary form of residual income, EVA goes one step further and attempts to address some of the issues related to pensions, mixing financing and operations, reserves, research and development, energy exploration, divestitures and restructuring transactions, investment, depreciation, and stock options.'

Rogerson demonstrates that residual income is an income-based com-pensation system that provides an incentive for the management to allocate capital efficiently over time. (See Berkshire Hathaway discussion above.) The corporate form of organization exhibits the separation of ownership from control. Managers are typically better informed about investment opportunities than shareholders are. This separation of ownership from control and the lack of a capital charge make it difficult to design an income-based compensation system that creates an incentive for managers to choose the correct level of investment. Calculating income, net of a charge for the capital employed, creates an incentive for efficient allocation of capital, mitigating the incentive for managers to game (beat) the system by maximizing current income at the expense of future income. 3-

Residual income models might be of direct help to investors. For exam -ple, Feltham et al. provide evidence that EVA has more explanatory power than reported earnings or cash flow from operations. 38

Residual Income: The Bad

There are a number of weaknesses associated with the various forms of residual income. For any given year, the determination of the residual income itself is dependent on an accurate estimate of the cost of capital, no simple task. For valuation purposes, forecasts are crucial."

All forms of residual income are consistent with discounted net cash flows for any book value and any method of depreciation.' While this might appear advantageous, changing depreciation schedules has a direct impact on residual income (or economic profit) for individual periods. Hence, lengthening the depreciable life of fixed assets decreases the per-period depreciation expense, increases NOPAT, and increases the residual income. In some cases, it may not be possible to determine whether the residual income calculated is actually owing to management's efforts or the lack thereof.

Residual income is an accounting measure and, as stated in the depre -ciation example above, can be manipulated for any one period. Furthermore, if improperly applied, residual income could bias management against long -term investments. Unlike the stock price, which is forward looking, residual income focuses on historical performance.


In spite of the name given to some forms of residual income, residual income is not economic income. A firm's economic income is equal to net cash flows plus a change in present value or market value of the firm.

For EVA, the additional effort to make additional adjustments to GAAP may not be justified. Chen and Dodd investigate EVA as a tool for investors to find profitable investment opportunities. They find that while EVA does provide information in addition to traditional accounting measures, it should not replace them. Furthermore, they find that there is no significant difference between EVA and residual income in terms of explaining stock returns.'

Dodd and Johns express concerns that the overemphasis on EVA might lead companies to exclude other important measures:

It appears that when companies adopt EVA, a subtle movement away from customer-related measures may occur. If these early observations represent the beginning of a trend within EVA adopt -ers, we see this as one laden with risk over the longer-term. The idea that a company can use a single financial measure to manage its operations does not make sense in today's environment.'

The evidence for the ability of residual income to explain shareholder returns is mixed. For example, in contrast to Feltham et al., Copeland and Dolgoff find that EVA does not provide much explanatory power as it relates to total shareholder returns:

It may surprise you to learn that EVA (also called economic profit) and commonly used performance measures such as earnings per share and the growth in earnings per share have at most a weak cor -relation (at least at the level of the individual company) with the total return to shareholders.43

If any adjustments are made to GAAP, EVA—and presumably other forms of residual income—may not be applied consistently or be sufficiently trans -parent to outside investors. Using survey data from 29 respondents (40% response rate), Weaver notes:

Although a consistent philosophy has been applied, none of the companies measure EVA the same way . . . Due to the measurement differences, Economic Value Added is a limited tool that cannot be used for competitive analysis. In practice, there is no one consistent definition of EVA and numerous fundamental differences exist with


respect to NOPAT [net operating profit after tax], IC [invested capital] and COC [cost of capital]. Further, some data may not be publicly reported, and more fundamentally, managers will behave differently when their performance is measured differently.'

Do firms that adopt EVA do so because of poor stock performance? Does the adoption of EVA lead to improved stock performance? Ferguson et al. examine these questions using an event study methodology. They find:

Firms that adopt EVA appear to have above average profitability relative to their peers both before and after [italics added] the adoption of EVA; further, there is some evidence that EVA adopters experience increased profitability relative to their peers following adoption.'

This suggests that EVA adopters were already good managers, already working to improve performance.

Do firms that have implemented an EVA-driven compensation sys-tem outperform the market? Is EVA a valid forecaster of stock per -formance? Griffith examines these questions using an event study methodology, estimating abnormal returns of EVA adopters for vari -ous holding periods starting from a firm's adoption to up to five years after its adoption of EVA. His findings are not encouraging: Before they adopted EVA as a measure of firm performance, the firms . . . underperformed both their peers and the market. After implementation of the EVA compensation system, the companies continued to underperform significantly"'

Are We Asking Too Much?

We think there is value in the various forms of residual income models for purposes of valuation when the user can incorporate additional information regarding forecasts of future economic profit or abnormal earnings. We also think that these models have value for performance assessment and motivating managers to control costs and avoid overinvestment. However, residual income models are no panacea for a firm or industry plagued by unsolvable problems.' Alternatively, if value-minded managers in good companies or industries adopt EVA, will the market be able to detect a difference?

For compensation purposes, Dutta and Reichelstein conclude that historical accounting measures, and even cash flows, are too backward looking

Usefulness of Accounting Information to Investors and Creditors 0 279

by themselves and must be combined with forward-looking measures. They conclude:

An optimal performance measure must rely on both accounting variables and [italics added] stock price. The familiar performance [metric] . . . of Economic Value Added (residual income) [is] useful for calibrating stock price and accounting income to the relevant history, in particular to the firm's dividend policy. 48

Finally, we note that if the value of the firm is determined as modeled by a residual income model (Equation 8.7 or 8.12), the total return to shareholders in any given year is dependent on revisions to all current and future residual income. Why should we necessarily expect a strong relationship between the current year's residual income and the total returns to shareholders?

Clearly, the jury is still out on the utility of various forms of residual income, whether for purposes of valuation or performance assessment. We think that residual income models hold promise for both security valuation and performance assessment; however, not as a single metric, as is fre -quently advertised. We suggest that residual income models' greatest poten -tial utility likely results when used in combination with complementary nonfinancial metrics.

Background on Risk and Return

The usefulness of accounting information to investors has been empirically investigated through tests of association between publicly released account -ing data and changes in security prices. If there is a significant association, then there is evidence that accounting information is useful with respect to firm valuation. These studies also constitute tests of the EMH.

Efficient-Markets Hypothesis (EMH)

Market efficiency refers to the speed with which securities in the capital markets respond to new information. The (EMH) states that capital markets fully and instantaneously reflect new information in security prices. 49 If the hypothesis is correct, the value of new information is fully and completely demonstrated via the security's price response. When this occurs, the item of information is said to have information content.

There are three forms of the EMH. The weak form says that security prices reflect information contained in historical (past) prices. The semi-strong form says that security prices reflect all publicly available information.

280 $ ACCOUNTING THEORY

Finally, the strong form says that security prices reflect all information, both public and private. The semistrong form is the most tested. Much of the information tested has been of an accounting nature—for example, financial statement data and earnings announcements. In our discussion, we concern ourselves only with publicly available information.

Rationale and Implications of the EMH

The rationale for the EMH is simple. There are thousands of self-interested investors and analysts trying to maximize their wealth by trading securities. These individuals are motivated to uncover any information that might give them a financial edge. Given that publicly available information is accessible by everyone at about the same time, it makes sense that wealth-maximizing individuals quickly analyze that information and trade accord -ingly' Given that news arrives in a random fashion, we expect that security price changes are random as well.

The implications for efficient markets are profound. If markets are effi -cient, it is useless to analyze past financial statements or read historical articles about companies. Furthermore, it is not possible to "beat the market" on a risk-adjusted basis. There is evidence to support this view. Malkiel notes that even professional mutual fund managers have difficulty beating the market after fees.

During the year ended December 31, 2003, close to three quarters of the mutual funds holding large capitalization stocks were outper -formed by the (large capitalization) Standard and Poor's 500 stock index. Results are similar for other one-year period Is]. When returns are measured over periods of 10 years or longer, over 80% of active managers are outperformed by the index. . . . We see that the typical actively managed fund underperforms the index fund by over 200 basis points.'

Anomalies

For some time, it was largely accepted that the market was indeed effi -cient. Then, De Bondt and Thaler presented convincing evidence that mar -kets often overreact or underreact. In addition, the mispricing does not appear to correct rapidly:

Consistent with the predictions of the overreacting hypothesis, portfolios of prior "losers" are found to outperform prior "winners."

Usefulness of Accounting Information to Investors and Creditors * 281

Thirty-six months after portfolio formation, the losing stocks have earned about 25% more than the winners, even though the latter are significantly more risky.'

The debate continues to rage. In fact, it has created a new field of "behavioral finance." The "technology bubble" of the late 1990s helped to fuel the fire. Consider the case of the Nasdaq Composite Index, a commonly known indicator of technology stocks. On March 10, 2000, the Index reached a level of 5049, only to fall 3935 points (78%) to 1114 by October 9, 2002. Which date reflected the correct pricing of the stocks in the Nasdaq Composite Index: March 10, 2000, or October 9, 2002? As we write this chapter in mid 2011, a decade later, the index has only recovered approximately 60% of its losses.'

Amazon.com Inc. typified the late 1990s bubble. On December 31, 1999, its stock price, adjusted for splits, was $76.12, while it reported an operating loss of almost $606 million. Exhibit 8.3 reveals why some, to their chagrin, questioned the link between Amazon's earnings and its stock price in the late 1990s. It would almost appear that the earnings were anticipating the stock price, instead of the other way around.

The bubble had devastating effects for managers who analyzed compa -nies "the old-fashioned way" Consider the demise of Tiger Management.

The sudden farewell of Tiger Management, the giant hedge fund, is being heralded in some quarters as a death knell for long-term value investing. . . . In announcing that he would liquidate and give back his investors' money, Julian Robertson Jr. . . . admitted that he is out of step with a world in which Palm, the maker of the hand-held Palm Pilot, is valued at more than GM and in which Priceline.com (which sells airline tickets but has neither earnings nor planes) was valued at more than US Airways and most of the other publicly traded air lines combined. . . . "There is no point in subjecting our investors to risk in a market which I frankly do not understand."'

Portfolio Diversification

The theoretical foundation of capital market or security price research comes from portfolio theory, which is a theory of rational investment choice and utility maximization. As long as security returns are imperfectly corre -lated (correlation is less than 1.0), the risk of a portfolio as measured by its standard deviation of return is reduced by adding additional securities. See Exhibit 8.4.

282 I ACCOL.N TINE THI-( eY

hxhibit Amazon.com iric.: Income From ()pc .rntioas anC. Scock Pricc

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Capital A,c,set Pricing Model (CAPM)

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Markel Liqe

capilal. Markel Line (0-17)

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Usefulness of Accounting Information to Investors and Creditors • 283

Exhibit 8.4 The Effect of the Number of Securities on Portfolio Risk

SOURCE: Mergent Online (www.mergentonline.com) and Yahoo! Finance (http://finance.yahoo .com). Accessed February 2, 2007.

real estate, etc.) have been added to a portfolio, we have the market port-folio. The theoretical choice of portfolios for two risky assets is graphically presented in Exhibit 8.5. The points on the curved line, the feasible set, reflect portfolios formed by combining different proportions of two risky assets. Each portfolio has its own unique expected return and standard deviation.'5

The straight line is called the Capital Market Line (CML). The CML inter -sects the Y-axis at the risk-free rate of interest, typically considered to be a 90-day Treasury bill. At this point, the standard deviation is equal to zero. The CML is tangent to the feasible set at point M. (If portfolio M contained all risky assets, it would be the market portfolio.) The points on the CML reflect various proportions of an investor's wealth invested in M and the risk-free asset. When drawn through M, the CML provides the highest risk

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premium—the expected return above and beyond the risk-free rate—per unit of standard deviation of return (risk). Since investors are risk averse, the expected portfolio return increases as risk (standard deviation of return) increases. The capital market line is linear only under restrictive conditions, but whether linear or curvilinear, a direct relationship exists between the level of risk and expected returns.

Security Market Line (SML)

Theoretically, with the formation of the market portfolio, the unsystem -atic risk of individual securities is eliminated, and only systematic risk mat -ters. Hence, the relevant risk for an individual security is systematic risk, which is the risk of the security relative to the market portfolio.' The sys -tematic risk for an individual security is measured by beta 03), which mea -sures the volatility of a security's returns relative to the market portfolio.' By definition, the beta of the market is equal to 1.0. A security with a beta of 2.0 is twice as risky as the market, whereas a security with a beta of 0.5 is half as risky as the market.

According to the CAPM, the relationship between the expected return on individual securities and beta is embodied in an equation known as the Security Market Line (SML):

R = Rr + 131IR„,–Rd (8.13)

where

R. = the expected return on security j,

Ri• = the risk-free rate of return (typically the return on Treasury bills),

Km= the expected return on the market portfolio, and

13) = the beta coefficient for security j.

Beta is estimated by performing a regression of the returns of security j on those of the market. Beta is the slope of this regression. Statistically, beta is defined as

13j = rimsjs,„/s,„2 (8.14)

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Introduction to Capital Markets Research in Accounting

Capital markets research in accounting examines the relationship between the security prices and the information contained in the firm's financial statements and associated documentation. Aside from its importance as an academic exercise, this body of research is of utmost importance to inves -tors, managers, and standard setters. Why? At a high level, the ability of markets to efficiently allocate resources (allocational efficiency) is crucially dependent on accounting information for analysis, valuation, and perfor -mance measurement. However, investors need to know if analysis of accounting data is a value-enhancing activity. Furthermore, standard setters need to know if the existing standards are fulfilling their intended purpose to improve the informational and allocational efficiency of markets. If not, it might be time for a new standard. Ultimately, everyone has a stake in the process.

In the sections that follow, we examine some of the capital markets research in accounting. Our intent is not to present a comprehensive review or critique but to provide a status report and outlook.

The Market Model

Many empirical studies in accounting use the empirical form of the CAPM known as the market model:

= Pjtkt ± Et (8.15)

where

t is a time subscript,

Rp pi, and R„, are the same as in Equation 8.13,

a = the intercept term, and

E = a random error term.

The model states that the returns for security j are a function of the return on the market. (As a rearrangement of the Security Market Line, the intercept, a, is equal to R ftl — p i].) The portion of the return not explained by the market is reflected in E, the error term.

Usefulness of Accounting Information to Investors and Creditors + 287

Event Studies

An empirical research method used in accounting and finance studies to detect the market's reaction to some event is the event study.' The announcement of an unexpected event (e.g., merger or acquisition) should have an impact on the stock price. An event study divides the period related to the event into three "windows": an estimation window, the event window, and the post-event window. The "normal" relationship between a security's returns and those of the market are estimated during the estimation window. This allows the researcher to estimate the parameters (a and (3) of Equation 8.15 using linear regression. This is shown graphically in Exhibit 8.6.

After the parameters of Equation 8.15 have been estimated, the equa tion is used to estimate the returns at the time of and subsequent to the event. The difference between the actual return and the return expected using Equation 8.15 is called an abnormal return (AR). The sum of the ARs is known as the cumulative abnormal return (CAR). In the absence of an event, the ARs should randomly fluctuate around zero, and the CARs should show no upward or downward trend.

If an unexpected event has occurred, the AR and the CAR should depart significantly from zero on the date of the event. However, if the market fully and immediately reflects the new information in the stock price, the

Exhibit 8.6 Estimation of Equation 8.15

.015

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-0.010

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0.0050 0

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0

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(j)

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subsequent ARs should again randomly fluctuate around zero, and the CARs should show no trend. See Exhibit 8.7.

In contrast, if the market does not fully, immediately, and accurately reflect the news contained in the event, we might observe an upward or downward bias in ARs and the tendency of the CARS to drift up or down. Exhibit 8.8 shows a graph of the ARs and CARs in which the market has not fully adjusted to good news at the time of the event.

Before reviewing the empirical findings, we need to make a few observations regarding the difficulties of doing this type research."' The study of price movements and the pricing mechanism in any market is an imposing task. Determining cause and effect between information and security prices is espe -cially difficult because new information is continuously arriving. Since the set of information affecting security prices is large, it is difficult to isolate the effects of one piece of information. Furthermore, we are examining only a relatively small group of investors—those at the margin who influence stock prices. This difficulty means that the tests are going to be somewhat crude rather than precise.' The research should be examined with this in mind. Failure to find evidence of information content should thus be interpreted cautiously, for the methodology is not always capable of detecting information content. For this reason, the stronger evidence from efficient-markets research exists when there is information content rather than where there is none.

Another weakness of capital market research is that it is a joint test of both market efficiency and the model used to estimate the abnormal returns. The absence of price responses is usually interpreted to mean that the information tested has no information content. This interpretation is correct only if the market is efficient and if the model used is correct. But what if the market is inefficient or if the model used is incorrect? In either case, there is no way of determining what the absence of a price response means. This is another reason why the research findings are much stronger when there is evidence of information content.

A final point is that market-based research necessarily considers only the aggregate effect of individual investor decision making. That is, the role of accounting information vis-a-vis an individual investor's decision making is implicitly modeled as a black box: An "event," occurs, and the effect of this event is then inferred from whether there was an aggregate (market) reaction.

Overview of Capital Markets Research in Accounting

Kothari provides an excellent review of the literature on capital market research in accounting.' The main areas of interest for capital markets research in accounting deal with fundamental analysis and valuation, tests of

Irivr..5.'or5 and Credi.'circ 2fl9

market efficiency relaring to accounting inforrntition, and. thc. value relevance of financial reporting. 'K. focus on. tric first Iwo .,'ircas.

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0C die future cyvected net ca::..h flaws. From 3 valuation perspective, the

Exhibit f4.7 Graph Showing WU and FrnniMiiite Adjustment to on F,vent

3 0 ' L , 5 - 2 0 - 1 5 - 1 0 - 5 0 5

Months (event OCOurs at time .1))

A R — C A R

10 15 20

Exhibit S.S Graph Showing Incomple.te Adjustment to an Evcnr.

1%.•

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0 . 0 4

0 . 0 2

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firm's financial statements are useful to the extent that they are helpful in forecasting future cash flows. Fundamental analysis deals with using eco-nomic information, including the information contained in the firm's finan-cial statements, to forecast future cash flows and estimate the firm's intrinsic value (inherent economic value).

Given that security prices serve as a mechanism to allocate resources, the informational efficiency of financial markets is of utmost importance. Short-term event studies have long been the staple for analyzing the degree to which markets are efficient. Long-horizon event studies and cross-sectional tests have increased the number of research opportunities. 63

Association studies test for correlation between some accounting perfor-mance measure and stock returns. In general, the point of these tests is to determine if and how rapidly accounting information is reflected in security prices. As we have mentioned previously, it is sometimes difficult to attribute a market reaction to a piece of accounting information as market participants may have access to other opportune sources of information. For example, some of the information contained in annual reports is revealed long before the report is published.

Early studies provided evidence that there is information content in earnings announcements, but the market's reaction may not be fully and immediately reflected in security prices. Furthermore, accounting informa-tion is not necessarily the timeliest source of data affecting security prices.

Later research focused on methodological research, alternative perfor-mance measures, valuation and fundamental analysis, and tests of market efficiency. There is evidence that accounting information is not always immediately and fully reflected in security prices. From both an academic and investor perspective, the research in the area of fundamental analysis is particularly intriguing owing to the economic implications of "mount ing evidence that suggests capital markets might be informationally inefficient and the prices might take years before they fully reflect available information."' However, Kothari notes that additional work must be clone to improve research design and develop refutable theories of market inefficiency.

The null hypothesis for much of the capital markets research in account -ing has been that the market fully and instantaneously adjusts to new infor -mation; the market price is equal to the security's intrinsic value. This "umpire view" of the market is an extreme view and may not hold up. Lee provides an intriguing and practical alternative:

A naive view of market efficiency, in which price is assumed to equal fundamental value, is an inadequate conceptual starting point for

future market-related research. . . . It is an over simplification that fails to capture the richness of market pricing dynamics and the process of price discovery. Prices do not adjust to fundamental value instantly by fiat. Price convergence toward fundamental value is better characterized as a process, which is accomplished through the interplay between noise traders and information arbitrageurs. This process requires time and effort, and is only achieved at substantial cost to society.65

Furthermore, Lee suggests that we have been asking the wrong questions:

We need to unshackle ourselves from the notion that price is equal to value. That is, we should begin thinking about fundamental value and the current market price as two distinct measures. . . . Rather than assuming market efficiency, we should study how, when, and why price becomes efficient (and why at other times it fails to do so). Rather than ignoring the current market price, we should seek to improve it.'

The Value of Accounting Information: Evidence From Return

Data

Information Contents of Earnings Announcements

The strongest evidence from capital market research concerns the information content of annual accounting earnings numbers. The semi nal study, published in 1968, showed that the direction of change in reported accounting earnings (from the prior year) positively correlated with security price movements.' The study also found that the price movements anticipated the earnings results and that there was virtually no abnormal price movement one month after the earnings were announced. This is consistent with the semistrong form of the efficient-markets hypothesis. A later study showed that the magnitude as well as direction of unexpected earnings are associated with changes in security prices.' Quarterly earnings announcements have also shown the same general results.69

These results are not surprising. We expect accounting income to be part of the information used by investors in assessing risk and return. Capital market research confirmed an almost self-evident proposition. The findings are important, though, in formally linking accounting information with investment decisions and hence with usefulness to investors.



Market Reaction to Alternative Accounting Policies

A more complex type of securities-price research examined the effect of alternative accounting policies on security prices. The initial purpose of these tests was to investigate the so-called naive-investor hypothesis. Research found that security prices respond to accounting income num bers. Alternative accounting policies—for example, flexibility in the choice of depreciation and inventory methods—can affect net income. Although these methods affect reported earnings, there is no apparent impact on company cash flows. These types of accounting alternatives simply repre sent different patterns of expense recognition or cost allocations.

The question of interest to researchers is whether alternative account ing policies have a systematic effect on security prices. If security prices do respond to income levels that differ solely because of alternative accounting methods, with no cash flow consequences, then there is support for the naive-investor hypothesis. On the other hand, if security prices do not respond to such artificial book-income differences, then there is evidence that investors in the market are sophisticated and able to see through such superficial bookkeeping differences. Virtually all the initial research interpreted the findings as a rejection of the naive-investor hypothesis. However, some research findings challenged some of the earlier conclusions and reopened what was once considered a closed issue in accounting research.'

Alternatives With No Known Cash Flow Consequences

Several studies compared companies using different accounting methods. One of the earliest studies compared companies using accelerated versus straight-line depreciation methods.' The two groups of companies had different accounting income numbers because they used alternative depreciation methods; thus there were differences in income between the two groups of companies due to the use of alternative depreciation account ing methods. There were also differences in price–earnings multiples between the two groups. Companies using accelerated methods had lower earnings but higher price–earnings multiples than companies using straight-line. However, when earnings of companies using accelerated methods were adjusted to a straight-line depreciation basis, the price–earnings multiple between the two groups of companies was not significantly different.

The assessments of the companies in the market did not appear to be affected by arbitrary and alternative accounting income numbers. This find ing is often expressed as the market not being "fooled" by arbitrary account ing

differences. Other similar research supports this conclusion. Additional


areas tested include purchase versus pooling accounting, expensing versus capitalizing research and development costs, and recognition versus deferral of unrealized holding gains on marketable securities.'

A related area of investigation concerns security price responses to a reported change in accounting policy by a company. When changes in depre -ciation policy are researched, there is no evidence that the change per se affects security prices.-3 Another area tested was a change from the deferral to flow-through method of accounting for the investment credit.' Again, no price effects were found. Although changes in accounting policies may cause the income number to change (solely because of the policy change), these research studies did not find that security prices responded to the changes. The market is not fooled by higher accounting income achieved solely from a change in accounting policy with no apparent real changes in underlying cash flows.

Evidence from the type research discussed in the preceding paragraphs supports the claim that there is no information content in accounting policy changes, at least where there are no apparent underlying changes in cash flows. This finding is also interpreted as a rejection of the naive-investor hypothesis. Investors appear to adjust accounting income to compensate for artificial bookkeeping differences with no real substance. That is, inves tors do not appear to respond mechanistically and naively to changes in reported accounting income numbers. Thus, early research appeared to be in line with the semistrong form of the EMH.

An Alternative With Cash Flow Consequences: The LIFO Choice

One type of change in accounting policy that does produce a security price response is a change from FIFO to LIFO inventory accounting. Changes to LIFO have been associated with a positive security price move -ment, even though LIFO lowers accounting income in a period of rising inventory prices.75 Given the apparent sophistication of investors in other areas of accounting policy differences, what is the logical explanation for these price responses? The suggested reason for the price response is that LIFO must be adopted for financial statement purposes if the tax benefit is desired. In a period of rising prices, tax expense is lower for companies that use LIFO, in which case there are real cash flow consequences due to the change in accounting policy. Even though book income is lowered by the use of LIFO, cash flows are higher because the taxable income is lower. Positive security price responses are, therefore, consistent with an increase in the value of the firm due to tax savings.

Later studies, however, contradicted these findings concerning the effect of the changes.' These studies either found no evidence of price


response or found evidence of a negative price response. The more recent studies suggest that the earlier research failed to isolate the real effect of the LIFO change because of a self-selection bias. (Companies selected because of a LIFO change could have also experienced other positive events, which may have been the actual cause of the positive price response.) Since LIFO lowers accounting book income, a negative price response could be inter -preted as a mechanistic response to a lower accounting number by naive investors, who did not consider the positive cash flow consequences of lower taxes.

More recent studies find support for a positive security price movement when LIFO is adopted. Pincus and Wasley examined LIFO adoptions from 1978 to 1987 and found evidence for the possibility that LIFO is a "good news" signaling event that could account for the positive security price movement presumably resulting from its adoption. -- On the other hand, Kang brings up the possibility of potentially high adoption costs relative to LIFO, such as accounting system changes and a higher probability of violat ing debt contract provisions (e.g., lower current asset ratios and higher debt-to-equity ratios) and renegotiation of management contracts involving bonus arrangements.' These factors might account for some of the negative price reactions since they might offset the future tax savings.

As discussed at the beginning of this section, security price research is extremely difficult to conduct. The LIFO choice issue amply illustrates this point. The early LIFO research rejected the naive-investor hypothesis. Later research on the LIFO question reopened what was once thought to be a closed issue with respect to market efficiency. However, more recent research shows how complex the issue of LIFO adoption is. LIFO is garnering renewed interest as a research topic, as the possibility of completely eliminating LIFO approaches, assuming International Financial Reporting Standards (IFRS) actually replaces U.S. GAAP, For better or worse, liquidity metrics significantly change for LIFO adopters forced to comply with 'FRS.'

Alternatives With Indirect Cash Consequences

Security price research is probing a more subtle issue referred to as indirect consequences. An indirect consequence occurs when an accounting policy change affects the value of the firm through an indirect effect on owners rather than a direct effect on company cash flows. One such study was motivated by an attempt to explain why securities prices of certain oil and gas companies responded negatively to a mandatory change in account -ing policy.' The required change from full costing to successful efforts is regarded as simply a change in how exploration costs are allocated to the


income statement. Therefore, it was expected that no security price response was evident since there was no direct cash flow consequence to the companies.

However, security price responses were found to exist. Since previous research predominantly rejected the naive-investor hypothesis, a search was made for the existence of some indirect cash flow consequences to explain the price response. The study posited that a change to successful efforts accounting for oil and gas exploration costs lowered firms' ability to pay divi -dends in the short term because of restrictive debt covenants. Therefore, even though the change in accounting policy appeared to affect only book income on the surface, there were indirect cash flow consequences to investors, which might explain the negative price response. This explanation derives from agency theory. When accounting numbers are used to monitor agency contracts, there can be indirect consequences from changes in accounting policies. In the case of debt covenants restricting dividend payments, account -ing numbers are used to protect the security of bondholders at the expense of stockholders. If an accounting policy change lowers accounting income (as can occur in a mandatory change to successful efforts), present or future cash dividends can be reduced, causing a negative price response.'

A similar type of study found negative security price responses for firms using purchase accounting when pooling was restricted by the Accounting Principles Board (APB) in favor of purchase accounting for combinations.' Differences between purchase and pooling accounting appear on the sur face to affect only book income, with no real cash effects. However, the reduced use of pooling accounting can affect dividend distribution because of debt covenants. Income is normally lower under purchase accounting than pooling, and the same effect of dividend restrictions, as argued in the oil and gas study, is also argued in the purchase/pooling study.

Another study along these lines examined the requirement to capitalize leases previously reported as operating leases." Although there was some evidence of negative price responses for certain companies, the price response could be caused by the constraints imposed by the existence of debt covenants.

Anomalies

Over longer periods of time, financial markets appear to be information-ally efficient. How rapidly and completely they respond to new information is an open question. While it is difficult to prove with certainty, there is con-vincing evidence that markets may not be as efficient as postulated in the semistrong form of the efficient-markets hypothesis.

296 • ACCOUNTING THEORY

Lags in Processing Fundamental Data

In a very extensive study, Ou and Penman examined the utility of funda -mental analysis. Fundamental analysis assumes that securities markets are inefficient and that underpriced shares can be found by means of financial statement analysis. This view is directly opposed to the efficient-markets view that prices of securities fully and rapidly reflect all publicly available information (the semistrong form of the hypothesis).

Ou and Penman used traditional accounting measures such as return on total assets, gross margin ratio, and percentage change in current assets in a multivariate model to predict whether the following year's income would increase or decrease. Using data for the period between 1965 and 1977, the model included almost 20 accounting measures and reflected approximately 23,000 observations.' Ou and Penman were able to describe the following year's earnings changes correctly almost 80% of the time.' The key point concerns whether their predictors were capturing information that was already reflected in security prices (indicating an efficient market) or were predicting future earnings based on analysis of the accounting measures previously mentioned. The latter situation results in abnormal security returns if investment is based on their predictions.

Ou and Penman's analysis did indeed produce abnormal returns.' They also believed that the excess security returns were not attributable to excess risk factors.' Ou and Penman's research thus suggests that markets are not as efficient as efficient-markets advocates would like to believe; fundamental analysis is still important for investment purposes. This study also suggests that "better" accounting standards might improve the predictive ability of accounting information.

Low Correlation Between Earnings and Stock Returns

Lev concentrated on an issue that is complementary to the factors in the Ou and Penman study. Specifically, his point is that both over time and within years (cross-sectional studies), the correlation between earnings numbers and stock returns has been exceedingly low" In other words, earnings have very little explanatory power (as measured by R', the coeffi-cient of correlation) relative to changes in stock prices. Lev believes that one of the principal reasons for this situation lies with the low quality of reported income numbers:

Research on the quality of earnings shifts the focus to an explicit consideration of accounting issues by calling for a systematic exam-ination of the extent to which the specific principles underlying

Usefulness of Accounting Information to Investors and Creditors + 297

accounting measurements and valuations, as well as managerial manipulations, detract from the usefulness of earnings and other financial variables. Such research has the potential both to further our understanding of the role of financial information in asset valu -ation and to contribute meaningfully to accounting policymaking. 89

Lev and the Ou and Penman papers are complementary. Lev finds a low explanatory relationship between earnings and stock returns while Ou and Penman see a predictive role for accounting data in an imperfectly efficient market. Lev focuses directly on the issue of improving accounting measure -ments while the Ou and Penman's work seems to imply this point. 9°

Post-Earnings-Announcement Drift

Further questions concerning market efficiency arise over the phenomenon known as post-earnings-announcement drift. While markets do react sig-nificantly at the time of the earnings announcement, it takes up to 60 days for the full effect of earnings announcements to be impounded in security prices. 91 This effect appears to be more pronounced for smaller firms. 92 It also appears that earnings surprises have a more persistent effect when the earnings surprise is due to higher revenue surprises than to lower expense surprises.93

This anomaly has not escaped the notice of professional investors. Transient institutions—those actively trading to maximize short-term profits—appear able to exploit post-earnings-announcement drift. Ke and Ramalingegowda find that these institutions earn a three-month mean abnormal return of 5.1% (or 22% annually) net of transactions costs from their arbitrage trades.'

At least part of the blame for post-earnings-announcement drift is laid at the feet of financial analysts. Abarbanell and Bushee concluded that financial analysts underreact to very fundamental signals stemming from securities, which in turn leads to forecast errors and incomplete security price adjust -ments.9' Sloan found evidence that shareholders do not distinguish well between cash flow portions of earnings and the accrual segment thereof 96 The cash flow portion persists longer into the future and is less subject to manipulation than the accrual part of earnings. Another possibility is that in some cases, transaction costs are too high relative to the potential gain that can be earned from the mispricing of the securities. Although securities markets may be "efficient," they may not be as efficient as once believed. This suggests that it is even more important to attempt to improve the qual ity of accounting standards.'

Finally, Mikhail, Walther, and Willis examine if analyst experience is related to post-earnings-announcement drift. Experience matters. Financial


markets are more efficient in the presence of experienced financial analysts, and the effect is not trivial:

The results . . . indicate the average magnitude of the post-earnings-announcement drift is reduced by approximately 18 percent . . . when the experience level of the analysts following the firm increases from the lowest decile to the highest decile."

Mispricing Related to Accruals

Richardson et al. focus on the reliability of accounting numbers. They develop a comprehensive definition and categorization of accruals, and decomposing accruals into broad balance sheet categories. They use their "knowledge of the measurement issues underlying each accrual category to make qualitative assessments concerning the relative reliability of each cate -gory"' They then analyze the persistence of the cash flow and accrual com-ponents of earnings. Finally, they analyze the abnormal returns for the firms' common stock to determine if the market impounds the information contained in various accruals as it relates to earnings persistence. If the information contained in accrual reliability is impounded in stock prices, accruals and future abnormal stock returns should be independent of each other.

Interestingly, they find that the less reliable the accruals, the lower the earnings persistence. More importantly, and somewhat unsettling, is that they find the market does not fully price the less reliable accruals: "Overall, the results are consistent with the naive investor hypothesis. Future stock returns are negatively related to accruals, and the negative relation is stronger for less reliable accruals.""'

Furthermore, their findings underscore the importance of distinguishing between earnings and free cash flow:

The standard textbook definition of free cash flow adjusts earnings by adding back depreciation and amortization and subtracting changes in working capital and capital expenditures. . . . The accru -als that we find to be the least reliable correspond closely to the adjustments that are made to earnings in arriving at free cash flow. Free cash flow represents a combination of actual cash flows plus the relatively reliable financing accruals."

Liu and Qi provide evidence that the potential mispricing of accruals is substantial. They form companies into portfolios based on total accruals and the "probability of information"—based trading (PIN). A hedge strategy


formed by investing in the lowest accrual decile and selling short the highest accrual decile, and confined to high PIN stocks, yielded an annualized abnormal return of almost 19%.'

Chan et al. examine three explanations of why accruals predict stock returns: manipulation, changing prospects, and overoptimistic expectations. The bulk of the evidence alludes to managers' manipulation of earnings:

A large increase in accruals marks a sharp turning point in the for -tunes of a company . . . In the year in which accruals are high . . . earnings show no weakness but continue to grow rapidly. These patterns suggest that firms with high accruals already face symp toms of a cooling in their growth, but they use creative accounting to delay reporting the bad news.103

The Incomplete Revelation Hypothesis

Questions concerning market efficiency (or the lack thereon have coalesced into a new hypothesis, the incomplete revelation hypothesis (IRH). Bloomfield sees two principal reasons for the IRH.' First, some accounting numbers or relationships are more difficult or costly to uncover and their effects are not fully revealed in security prices. For example, historically, infor mation about stock option "expense" was revealed in footnote information only as opposed to being in the body of the income statement.' Hence, the information and its import is more difficult to extract in footnote form, and it might take longer for this information to fully impact security prices. This is diametrically opposed to the efficient-markets hypothesis that disclosure—in whatever form—is all that is needed to fully impact security prices.

The second factor of the IRH is the presence of "noise traders" in the market. Noise traders are individuals who do not necessarily respond in a completely rational way to new information. They may be rebalancing their portfolios, responding to liquidity shocks, or even acting on whims.' Thus, from the perspective of information effects on security prices, we have a group of individuals who are responding to a different set of criteria. This "distraction" impedes the market from responding in a fully efficient manner. Finally, notice that the IRH is not only fully consistent with post-earnings -announcement drift, but it may help to explain that particular phenomenon.

Accounting Information and Risk Assessment

Capital market research also investigated the usefulness of accounting numbers for assessing the risk of securities and portfolios. These studies


find high correlations between the variability of accounting earnings and beta, the market-risk measure.' The high correlations imply that account -ing data is useful for assessing risk, or at least confirming it.

Other research tries to determine if alternative accounting policies have any effect on risk. The purpose of this type of research is to identify how alternative accounting policies or disclosures can affect the usefulness of accounting numbers for assessing risk. For example, one study tried to determine if unfunded pension benefits (reported in Notes) affected beta." There was no significant impact. From this evidence, it might be concluded that pension information is not useful for risk assessments. However, other studies found that supplemental segment (line of business) disclosures resulted in a revision of systematic risk, which suggests that such informa -tion is useful for risk assessments."

Other studies have tested the association of financial ratios with beta." Some of the ratios and computations tested include dividend payout ratio, leverage, growth rates, asset size, liquidity, and pretax interest coverage, as well as earnings and earnings variability In general, these tests indicate a strong association between the accounting-based ratios and beta.

Summary of Capital Market Research

We draw the following conclusions from the empirical evidence provided by capital market research:

· Accounting earnings appear to have information content and to affect security prices.

· Alternative accounting policies with no apparent direct or indirect cash flow consequences to the firm do not seem to affect security prices.

· Alternative accounting policies that have direct or indirect cash flow consequences to the firm (or its owners) do affect security prices.

· There is evidence that security markets do not react fully and instan -taneously to certain types of accounting data in certain situations (e.g., high accruals, small stocks, low analyst coverage).

· There are incentives to choose certain accounting policies, where choice exists, due to indirect cash consequences.

· Accounting-based risk measures correlate with market risk measures, suggesting that accounting numbers are useful for risk assessment.

Capital market research continues to be useful in empirically evaluating economic consequences of accounting policies vis-a-vis security prices and the usefulness of accounting numbers for risk-and-return assessments.

Perhaps more than anything else, though, the impact of capital market research is that it brought a different perspective to accounting theory and policy at a time when the emphasis was primarily on deductively based theory.

Evidence From Survey Data

Another way of determining the usefulness of accounting information is to directly ask investors how (if at all) they use annual reports. Surveys of investors have been undertaken in several countries and generally show a rather low readership of accounting information. 111 Approximately one-half of the investors surveyed indicated they read financial statements. Institutional investors show a much higher level of readership."' These sur -veys, particularly of individual investors, should be interpreted cautiously, however. Individual investors may rely on investment analysts to process accounting information. It would be simplistic to assume accounting infor -mation has no usefulness to investors merely because many individual stockholders do not read annual reports in detail.

Another type of survey research asked investors to weigh the impor tance of different types of investment information, including accounting information. Several studies of this type have been reported.' 13 Accounting information ranks fairly high in importance in these surveys, though not at the top. This status seems to be attributable to the historical nature of accounting information and the reporting-lag effect. More timely account ing information from company press releases, and nonaccounting information such as general economic conditions and company announcements on products and markets, ranks ahead of annual reports in perceived importance.

The Value of Accounting Information: Evidence From Direct

Valuation

The research discussed in the previous section primarily examined the rela -tionship between accounting data and unexpected changes in stock prices, measured as abnormal returns. Another approach is to examine the associa-tion between accounting data reported in annual financial statements and the levels of stock prices (i.e., firm valuation, measured as market capitaliza -tion)."" Conceptually, this approach, which is referred to as cross-sectional valuation, attempts to empirically estimate the theoretical model of equity valuation described at the beginning of this chapter. This approach is used to investigate how (if at all) specific components of the financial statements are



"priced" in the sense of being associated with the market valuation of the firm. If an item is priced as an asset/revenue, it should normally have a positive rela-tion to market value, whereas if the item is priced as a liability/expense it should normally have a negative relation with market value. A number of authors expressed enthusiasm for this methodology as a framework for evalu -ating the merits of alternative accounting methods/valuations."'

Evidence From Pensions

Several studies used this framework to determine that a firm's pension plan assets and liabilities (as reported off balance sheet in footnote disclo -sures) are consistent with their being viewed as on-balance-sheet assets and liabilities, respectively.' Another study determined that components of pension expense (per SFAS No. 87) are not weighted equally in terms of their association with market valuation.' Of particular interest is that the transitional asset amortization component of pension expense is implicitly valued at zero, which is consistent with the fact that there are no cash flows associated with the item.

Franzoni and Marin present evidence that the market significantly over -values firms with severely underfunded defined benefit pension plans. Furthermore, the effects of the overvaluation persist for a long time.

In particular, we show that the portfolio with the most underfunded firms earns low raw returns relative to portfolios of firms with healthier pension plans. This phenomenon persists for at least 5 years after the emergence of the large underfunding. Also, the risk-adjusted returns of this portfolio are significantly negative. The magnitude of the discount in returns is around 10% annually.'

While investors recognize the severe underfunding, it is possible that they are not adequately factoring in the implications of that underfunding, such as difficulty in refinancing at favorable terms or refinancing at all. Companies can postpone the recognition of the pension liability of its earn ings, and the underfunding eventually impacts the firm's future earnings. Franzoni and Marin also find that a severely underfunded pension is associated with higher leverage, which also constrains the ability of the firm to undertake value-enhancing investments.

One can debate whether poor operating performance and suboptimal investment decisions lead to severe underfunding, or whether poor manage-ment of the pension fund in the form of severe underfunding eventually leads to poor operating performance and suboptimal investment decisions. In any


case, it appears that investors do not fully recognize that the severe under-funding has negative valuation effects. Why this happens is not yet resolved.

Evidence From Research and Development

Another study examined the association of research and development (R&D) expenditures with firm value. The major finding was that, on average, each dollar of R&D was associated with a five-dollar increase in market value.' This result provides evidence that the market is implicitly capitalizing R&D outlays even though SFAS No. 2 prohibits explicit capitalization. In other words, the market interprets R&D as an asset (investment) rather than an expense, contrary to the accounting treatment required by SFAS No. 2. 1'

Evidence From Financial Services

The financial services industry is another area in which cross-sectional valu-ation models are used. Studies examined supplemental disclosures of nonper-forming loans (default risk) and interest rate risk in banks and thrifts.' Nonperforming loans are negatively associated with firm value, though this effect is greater for banks than for thrifts. Interest rate risk was negatively associ ated with firm value only for banks. Another study reported that banks' supplemental disclosure of the fair market value of investment securities is associated with market value over and above that explained by historical costs alone. This finding gives credence to the SEC's and FASB's push for mark-to-market accounting and eventually to fair value measurement in SFAS No. 157.1'

Accounting Data and Creditors

Theories underlying the usefulness of accounting information to creditors are not as well developed as is the role of accounting numbers vis-a-vis stock prices. Part of the problem is that interest-bearing debt securities trade infrequently. It is, however, generally agreed that the price of interest-bearing debt is based on the default risk premium, which is defined as the premium in excess of the risk-free interest rate on otherwise identical debt (for example, U.S. Treasury obligations). Thus, firm-specific information, including accounting data, aids creditors in assessing default risk.

Several distinct lines of research have emerged: (a) the usefulness of accounting data in predicting corporate bankruptcy (which encompasses loan default); (b) the association of accounting data with bond ratings wherein such ratings are presumed to proxy for default risk; (c) the association of accounting data with estimates of interest-rate risk premiums on debt; and


(d) experimental studies of the role of accounting data in lending decisions. The following is a brief overview of the research findings for the first two.

Evidence From Bankruptcies

Accounting-based ratios are very useful in discriminating between firms that subsequently go bankrupt and those that do not."' Bankrupt companies tend to have financial ratios prior to bankruptcy that differ from nonbankrupt companies. Predictability up to five years prior to bankruptcy has been demon-strated. These findings do not mean that companies with "bad" ratios necessar -ily go bankrupt in the future, but rather that bankruptcy is more probable.

Evidence From Credit Ratings

Accounting data are also associated with both bond ratings and default risk premiums.' Among the important ratios are profitability, earnings vari -ability, and leverage. Research is also used to evaluate which of alternative sets of accounting data are more highly associated with bankruptcy predic -tion, bond ratings, and risk premiums. Among the issues examined are historical cost versus price-level adjusted income, the effect of lease capital -ization versus noncapitalization, and recognition of pension liabilities versus footnote-only disclosure.'

Experimental (laboratory) studies also tested the usefulness of account ing data for creditors. Accounting data in the context of a loan-related decision (for example, loan amount, bankruptcy prediction, and interest rates) are provided to subjects to determine how, if at all, it affects their hypotheti cal decisions.'" In these experiments, the accounting data are manipulated to see if the judgments are sensitive to whatever manipulations take place. For example, changes are made to the magnitudes of accounting ratios or financial statements prepared under alternative policies (for example, lease capitalization versus noncapitalization). Generally, these studies support the sensitivity of loan-related decision making to key accounting data and, in this sense, complement the findings based on economic field data.

Importance of Earnings Forecasting

Copeland and Dolgoff examine the relationship between the annual total return to shareholders and several commonly used performance measures (sales, earnings per share, growth in earnings per share, forecasts of earn ings, etc.). They used data about analyst expectations as a proxy for investor expectations. The highest correlation (47%) was between the "annual return


to shareholders and changes during the year in expectations [italics added] about the same year's earnings, the following year's earnings, and earnings three to five years out."' This highlights the importance of business perfor -mance, measured by accounting data, relative to market expectations. The researchers also note that that the importance of expectations is "consistent with a discounted cash flow view of the world."

As we noted previously, the residual income model provides a central role for future earnings forecasts in determining the intrinsic value of a stock.' Accurate estimates might lead to abnormal stock returns. Indeed, there is evidence that better earnings forecasts make for wealthier investors. Loh and Mian examine the usefulness of accurate earnings forecasts from security ana -lysts. Each firm-year, they sort analysts based on the accuracy of their forecasts of annual earnings. If analysts with the best earnings forecasts provide the best returns, there is support for fundamental analysis of accounting data. Loh and Mian note: "If the analysts with the most profitable recommendations also exhibit superior forecasting skills, it would suggest that their stock-picking ability is real, and that it is founded on economic rationale."'

They find that the "recommendations of superior earnings forecast ers significantly outperform the recommendations of inferior forecast ers."130

This is consistent with the value of fundamental accounting analysis. 131 It also raises questions about the informational efficiency of financial markets.

While the value of the firm is equal to the present value of the expected future cash flows, earnings appear to play an important role in predicting those cash flows. Dechow, Kothari, and Watts developed a model of operat ing cash flows and the accounting process by which operating cash flows are converted into accounting earnings. The model explains why "current earn -ings, by itself, is a better forecast of future operating cash flows than current operating cash flows by itself."132 In addition, this prediction was borne out empirically using a sample of 1,337 firms. Furthermore, the forecast ability is a positive function of the firm's expected operating cash cycle.

Over the years, the relationship between earnings and stock prices has diminished. However, the ability of earnings to forecast future cash flows has not. Kim and Kross examine the ability of earnings to forecast one-year ahead operating cash flows by examining three decades of data (1972-2001). Their findings are positive: "We found an increasing relationship over time between earnings and one-year ahead operating cash flows. . . . Further, we found that the accuracy of cash flow predictions based on current earnings also increased over time."133

They hypothesize that changing accounting conservatism might play a role. In any case, we note that the value of a stock is dependent on much


more than a one-year cash flow forecast. Clearly, more work needs to be done to understand how earnings can be used to improve the cash flow forecast.

Gulliver provides an analyst's perspective on financial analysis, forecasting, and stock underperformance. He identifies five causes of stock price underperformance: aggressive accounting, financial deterioration, change in the industry or competitive situation, bad acquisitions, and overvaluation. The had news: Analyzing financial statements can be difficult. The information is contained on three separate statements and in many footnotes. Numerous assumptions are involved, and financial rules are complex and sometimes ambiguous. Finally, in some cases, the financial rules are used to conceal the truth. The good news: There are numerous cases in which "analysts and managers could have identified problem stocks in advance of market reaction by digging deeper into the data with an eye on earnings quality, operating efficiency, cash flow quality, and balance sheet quality."'"

Empirical Research and Standard Setting

In the early 1970s, some argued that capital market research could be used as a basis for choosing the best accounting policies and evaluating the economic consequences of alternative accounting policies on security prices. 135

Accounting policies that most affected security prices were thought to be most useful. In other words, such policies had the most information con tent. The argument had intuitive appeal, particularly since deductively based research proved unable to resolve the normative accounting theory debate about the most desirable form of accounting. However, the early advocates of security price research now recognize the limitations of this research for such a use.13' Reasons for these limitations are the public-good nature of accounting information, the existence of free riders, and the resultant mar ket failure in terms of optimal resource allocation. The potential impact of empirical research on the standard-setting issue recently arose again.

Opinions are mixed on whether empirical research can aid standard set -ting. Holthausen and Watts take the negative position. I3- The main obstacle for them involves the problem of different user groups with different needs, a problem discussed in Chapter 6. For example, creditors might be most interested in predicting debt default. Many standards involve contractual issues, litigation, tax issues, and conservatism (booking loss contingencies and not gain contingencies, for example). Hence, they see empirical studies examining different alternatives and their effect on valuation and cash flow predictions as not providing useful information for standard setters.

Usefulness of Accounting Information to Investors and Creditors o 307

Holthausen and Watts also believe that before empirical research is used as inputs for standard-setting purposes, a theory of accounting and standard setting must be established. What the role of such a theory might be is not made explicit. We also question whether a theory of this type can ever be developed.

Barth, Beaver, and Landsman take the opposite tack. 138They believe that multiple user groups and diverse uses of accounting information do not prevent empirical research from being useful for standard setters. For example, they cite a study showing that accumulated and projected benefit obligations in pension accounting (see Chapter 16) measure the pension liability implicit in security prices more reliably than just the vested benefit obligation (the two former measures give a fuller picture of the pension liability than the latter).

Hence, the difference between the groups involves an empirical issue, which is presently unresolved: the multiple-user-group problem. We lean toward the potential usefulness for standard-setting groups of empirical research in areas such as valuation and prediction of cash flows. On the question of diverse user groups with somewhat different purposes, we believe that complementarity rather than conflict results among users. Indeed, if extreme conflict among user groups and uses existed, we doubt that empirical research would be useful for any purpose.

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Chapter 8