Financial Accounting Theory

Seventh Edition

William R. Scott

Chapter 3

The Decision Usefulness Approach to

Financial Reporting

Chapter 3

The Decision Usefulness Approach to Financial Reporting

3.2 The Decision Usefulness Approach

• Investors are an important constituency of accounting

• It is the investor’s responsibility to make own investment decisions

• The theory of rational decision making helps the accountant to know

investors’ decision needs

• Knowing investors’ decision needs enables the accountant to

prepare useful financial statements

3.3 The Rational Decision Theory Model

• Investors make decisions in a variety of ways

• Their buy and sell decisions interact to form the market price of a

security

• The rational decision theory model does not claim to capture the

decision process of an individual investor

• It claims to capture the decision process of the average investor

– That is, it claims that investor decisions are, on average, rational

– A rational investor makes decisions to maximize his/her expected utility

» Continued

The Rational Decision Theory Model

• Role of the rational decision theory model in financial reporting

– Helps us understand how financial statement information helps the average

investor to make investment decisions

– Thereby helps the accountant to provide useful information for investment

decisions

Theory of Decision (How Do We Decide)

Theory of Decision

• How we make decisions when uncertain

• Check probabilities (internal, external, consensus)

• That is how we make most of our decisions

• Examples

– Choosing what time to wake up

– Choosing what clothes to wear

– Choosing which restaurant to have lunch at

– Choosing which class to take

– Choosing which group to join

– Choosing which presentation to do .....

• But that is only the first step

Theory of Decision

• We update our decisions over time (we change our mind)

• We get NEW information and we combine new information with our

existing view

• Can be continuous and unconscious process

• There is a name for our views before and after the change

– Prior probabilities (before)

– Posterior probabilities (after)

• Examples

Theory of Decision For Accounting

Theory of Decision

• How does it work under the context of this course?

• Investor / users has a view on a company’s performance

– His prior probabilities of being a good company or bad company

• He updates his view when he receives new information that we

provide

– Probabilities of good earnings if it is a good company

– Probabilities of good earnings if it is a bad company

Bayes’ Theorem

• A device to revise state probabilities upon receipt of new

evidence

– Θ is state of nature

– m is message received

– P(θ) is prior probability of θ (subjective)

• Formula

( )( ) ( )

( ) ( )∑=

θ

θθ

θθθ

PmP

mPPmP

/

//

Bayes’ Theorem Applied to

Accounting Information • θ is state of firm

θ1 = H = high future firm performance

θ2 = L = low future firm performance

• m is evidence received from the financial statements

m1 = GN = financial statements show good news

m2 = BN = financial statements show bad news

• Suppose GN is received:

3.3.2 The Information System Shows Evidence Probabilities, Conditional on

Each State, for Input into Bayes’ Theorem

Current Financial Statement

Evidence

GN BN

Total

H

State of

Nature

L

P(GH/H) P(BN/H) 1

P(GN/L) P(BN/L) 1

• Examples

• Restaurant review

• Feedback from friends on quality of employer

• Mid-term exam feedback on quality of students

The Information System (continued)

• The higher the main diagonal probabilities, the better the investor

can predict the state of nature (i.e., future firm performance)

– The main diagonal probabilities capture financial statement informativeness

– Highly informative financial statements also called:

• Transparent

• Precise

• High quality

>> Continued

The Information System (continued)

• Prior probabilities are subjective

– Investor assesses them based on all information available prior to the investment decision

• Information system probabilities are objective

– Reflect quality of GAAP

– How known by investor? The theory assumes rational expectations, that is, the investor quickly figures out the probabilities

>> Continued

The Information System (continued)

• Prior probabilities and information system probabilities input into

Bayes’ theorem to give posterior probabilities

• If prior probabilities are subjective, so are posterior probabilities

– However, if financial statement information is informative, posterior

probabilities are better predictors of future firm performance than prior

probabilities

>> Continued

3.3.3 Definition of Information

• Information is evidence that has the potential to affect an

individual’s decision

3.4 The Rational, Risk-Averse Investor

• A model of the average investor

– Does not claim that all investors are rational

• Investor is usually assumed risk-averse

– Concave utility function for wealth

• Risk-averse investor trades off risk and return

– If risk increases, demands higher return, and vice versa

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3.5 The Principle of Portfolio Diversification

• Divide all events affecting the returns on firms’ shares into two types

(factors)

– Market-wide factors

– E.g., central bank changes the interest rate

– Firm-specific factors

– E.g., GN or BN in a firm’s financial statements

– If investor buys a portfolio of securities, firm-specific factors tend to cancel out

– A fully diversified portfolio is one where firm-specific factors completely cancel

out, leaving only undiversifiable market-wide factors to affect returns, called

holding the market portfolio

Management Discussion and Analysis

Management’s outline and explanation of the firm’s

operations

– To supplement the financial statements

– Forward-looking orientation

– Includes discussion of risks facing the firm

– Consistent with rational decision making

• Forward orientation and risk information may increase

main diagonal probabilities of information system

– More relevant than the financial statements

– Less reliable?

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3.6.4 Is MD&A Decision Useful?

• Li (2010) studied the ability of MD&A to predict future

firm performance (earnings)

• An application of decision theory

• Select 30,000 forward-looking sentences from a large

sample of MD&As

• Manually classify each sentence into its “tone”. Results:

• Positive tone, 20% of sentences

• Negative tone, 40% of sentences

• Neutral tone, 40 % of sentences

• These give prior probabilities of states of nature (i.e., of

the tone of a forward-looking MD&A sentence)

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Is MD&A Decision Useful? (continued)

• The information system• For the 6,000 positive tone sentences, count number of times the word

“will” appears

• If it appears, say, 300 times, the probability that “will” appears in a

forward-looking sentence conditional on that sentence being of positive

tone is 300/6000 = 0.05

• Repeat for all other words in the 6,000 sentences

• Repeat same procedure for the negative and neutral tone sentences

• The result is a (large) information system, giving for each state of nature

(tone) the probability of each word appearing, conditional on the tone

of the sentence in which that word appears.

>> Continued

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Is MD&A Decision Useful? (continued)

• Extract 13 million forward-looking sentences from all U.S.

MD&As, 1994-2007

• For each MD&A, classify each of its forward-looking sentences into its

tone

• To do so, use the prior tone probabilities, and, from the information

system, the conditional probabilities of each word of that sentence, in

Bayes’ theorem to assess the posterior probability that the sentence is of

positive tone

• Repeat to assess the posterior probability that sentence is of negative

tone and of neutral tone.

• The tone of the sentence is taken as that tone with the highest

posterior probability

• The tone of the MD&A is taken as the average tone of the forward-

looking sentences it contains

>> Continued

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Is MD&A Decision Useful? (continued)

• The result was 145,479 MD&As classified into their

tones

• Does the tone of an MD&A predict earnings over the

following 4 quarters?

• Answer was yes, consistent with MD&A being decision

useful

• This study shows the potential of computer analysis of

large verbal data bases to increase our understanding

of accounting information

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3.7 The IASB/FASB Conceptual

Framework

– Oriented to investors’ investment decisions (primary users)

• Financial statements provide information that is useful to investors about the amount,

timing, and uncertainty of future cash flows (i.e., of future firm performance)

– Decision usefulness is implied

– Investor risk aversion is implied

– Information system is implied, since information system links current and future

performance

– “Past (including current)” firm performance is “usually helpful in predicting” future

performance

– Suggests that investors use current performance to update their probabilities of future firm

performance

– Overall, reasonably consistent with decision theory » Continued

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The IASB/FASB Conceptual

Framework (continued)

• Role of accruals in the Framework

– To predict future cash flows

• Consistent with balance sheet primary financial statement

– (i.e., accruals role is not to match costs and revenues)

• Desirable characteristics of accounting information

– Relevance

• Information about future economic prospects

– Reliability

• Called “faithful representation” in the framework

• Complete, free from material error, and unbiased

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Conclusions

• Rational decision theory provides a theoretical underpinning for

study of information needs of investors

– Helps accountants to provide information that is useful

• The Conceptual Framework seems consistent with the rational

decision theory model