ii

CURRICULUM VITAE

Patricia Mary Dechow was born on July 11. 1964 in Missoula. Montana.

United States. In 1987 she received a Bachelor of Commerce degree with first class

honours in Accounting and Finance from the University of Western Australia. Dechow

entered the doctoral program at the William E. Simon Graduate School of Business

Administration at the University of Rochester in the fall of 1987. specializing in

accounting and finance. While at the Simon School, she was the recipient of an Olin

Foundation fellowship from the University of Rochester. In 1990, she received a

Masters of Science in Business Administration and was admitted to candidacy for the

Ph.D. degree. During her studies at Rochester. she taught introductory financial

accounting to undergraduate students.

111

ACKNOWLEDGEMENTS

I am grateful to the members of my dissertation committee, S. P. Kothari, Jay

Shanken, Jerry Zimmerman and especially Ross Watts (Chairman) for their advice and

encouragement throughout the project. I am also grateful to Richard Sloan for his

insightful comments and intuition on many of the issues raised in this study and for his

careful reading of many earlier drafts. The help of Philip Kearns in introducing me to

the literature on non-nested hypothesis testing and for many discussions on that topic

[in particular, Vuong (1989)] is also greatly appreciated. I also wish to thank Ray Ball

for his guidance and Ph.D. students and faculty at the Simon School who gave me

feedback on earlier drafts. Finally, I would like to thank my colleagues at the

University of Western Australia, Philip Brown, H. Y. Izan and Peter Kerby for

stimulating my interest in accounting research and encouraging me to continue my

studies.

iv

ABSTRACT

Accounting Earnings and Cash Flows as Measures of Firm Performance:

The Role of Accounting Accruals

by

Patricia Mary Dechow

This study investigates the role of accounting accruals. It identifies

circumstances under which accruals are predicted to improve earnings' ability to

measure firm performance, as reflected in stock returns. The importance of accruals is

shown to increase (i) the shorter the performance measurement interval, (ii) the greater

the volatility of the firm's working capital requirements and investment and fmancing

activities and (iii) the longer the firm's operating cycle. Under each of these

circumstances, cash flows are predicted to suffer more severely from timing and

mismatching problems that reduce their ability to reflect firm performance on a timely

basis. The results of empirical tests are consistent with these predictions.

Descriptive evidence is presented demonstrating how accruals improve

earnings' ability to reflect firm performance. Changes in cash flows are shown to

exhibit strong negative autocorrelation. This is consistent with part of the change in

cash flows being temporary and reversing over time. Consequently, cash flows suffer

v

from mismatching problems over short measurement intervals. Earnings are predicted

to have fewer mismatching problems than cash flows because accruals combine with

cash flows to mitigate these problems. Consistent with this prediction, accruals are

strongly negatively correlated with changes in cash flows. However, because a trade

off is made between reliability and timeliness, accruals do not eliminate all mismatching

problems. Consequently, earnings also exhibit negative autocorrelation, but to a far

lesser extent than cash flows.

Predictions are also made concerning components of accruals. If mitigating

mismatching problems in cash flows is the primary motivation for accruals, then ceteris

paribus, accruals that have existed for centuries are likely to mitigate the more severe

mismatching problems. This reasoning suggests that working capital accruals will be a

more important component for mitigating mismatching problems than long-term

operating accruals. In addition, special items are predicted to be less important because

their intended purpose is not mitigate mismatching problems in cash flows, but rather

reflect the reversal of past over or understatements of accruals. The empirical results

support these predictions. The study concludes that accruals play an important role in

enabling earnings to reflect firm performance on a timely basis.

TABLE OF CONTENTS

vi

Page

l. INTRODUCTION 1

2. REVIEW OF lHE LITERATURE 9

3. TESTABLE PREDICTIONS 14

3.1. The contracting roleof accruals 14

3.2. Measurement interval predictions 16

3.3. Cross-sectional predictions 20

3.3.l. Theeffectof themagnitude of accruals 20

3.3.2. Components of accruals 23

3.3.3. Theeffectof theoperating cycle 25

4. THE USEOF STOCK PRICEAS THE BENCHMARKMEASURE OF FIRM PERFORMANCE 27

4.l. Stockpriceas a benchmark 27

4.2. Stockmarketefficiency versus functional fixation 31

5. NON-NESTED MODEL SELECTION 34

5.1. Theencompassing approach to non-nested modelselection 34

5.1.1. TheJ-test 35

5.1.2. Theincremental approach 37

5.2. Using the Vuong likelihood ratio test to evaluate 38earnings versuscash flows

vii

Page

6. SAMPLE DESCRIPTION AND VARIABLE MEASUREMENT 43

6.1. Data 43

6.2. Variable definitions 44

6.3. Descriptive statistics 45

7. ANALYSIS OFMEASUREMENT INTERVAL PREDICTIONS 47

7.1. The effectof shortand longmeasurement intervals 47

7.2. Robustness tests 51

7.3. Mismatching problems withcash flows 55

7.3.1. Time-series properties 55

7.3.2. Additional evidence consistent withmismatching 57problems

8. ANALYSIS OFCROSS-SECTIONAL PREDICTIONS 60

8.1. The effectof themagnitude of all accruals 60

8.2. Analysis of the decline in thecoefficient on earnings 63acrossquintiles

8.3. Evaluation of accrual components 67

8.3.1. The effectof changes in working capital 67

8.3.2. The effectoflong-tenn operating accruals 69

8.3.3. The effectof special items 70

8.4. The effectof the operating cycle 72

9. SUMMARY ANDCONCLUSIONS 76

BffiLIOGRAPHY 79

APPENDIX 1 The relation between cash flows and earnings 90

APPENDIX 2 The effect of measurement error on the 93coefficient on earningsandcash flows

LIST OF TABLES

viii

~

Title Page

Table 1 Descriptive statistics of data for the quarterly, annual 96and four-year intervals.

Table 2 Tests comparing the association of earnings, the 97association of cash from operations and the associationof net cash flows with stock returns (adjusted formarket-wide movements) over varying measurementintervals.

Table 3 Results of the likelihood ratio test developed by Vuong 99(1989) for non-nested model selection. A significantpositive Z-statistic indicates that model 2 is rejected infavor of model 1.

Table 4 Comparison of earnings' and alternative cash flow 100measures' association with stock return over the annualinterval; 1,976 observations, 1987-1989.

Table 5 Firm-specific annual first-order autocorrelation 101coefficients and Pearson correlations for earnings, cashfrom operations, net cash flows and accrual measures.

Table 6 Tests comparing the association of earnings, cash from 103operations and net cash flows with stock returns afterincluding past and future realized values of thosevariables; 6,466 annual non-overlapping observations1964 to 1988.

Table 7 Test comparing the association of earnings and the 104association of net cash flows with stock returns acrossquintiles, where quintiles are formed based on theabsolute value of aggregate accruals. Quintile 5contains firms with the largest absolute value ofaggregate accruals.

Table 8 Examination of proxies for underlying determinants of 105earnings response coefficients across quintiles that areformed on the absolute value of aggregate accruals;annual observations 1960-1989.

IX

Title Page

Table 9 Test comparing the association of earnings and the 106association of cash from operations with stock returnsacross quintiles, where quinti1es are formed based onthe absolute value of the change in working capital.Quintile 5 contains firms with the largest absolutechanges in working capital.

Table 10 Test comparing the association of earnings and the 107association of cash from operations with stock returnsacross quintiles, where quintiles are formed based onthe absolute value of long-term operating accruals.Quintile 5 contains firms with the largest absolute long-term operating accruals.

Table 11 Tests comparing the association of earnings before tax 108and the association of earnings before tax and specialitems with stock returns over different measurementintervals.

Table 12 Descriptive statistics on firm level operating and trade 110cycles (measured in days) and firm level and industrylevel Pearson correlations between the absolute valueof the change in working capital and the length of theoperating and trade cycle; annual observations, 1960-1989.

Table 13 Pearson correlations (probabilities) between the R2s 111(from regressions performed by industry of stockreturns on cash from operations or stock returns onearnings) with the average length of the industryoperating and trade cycles; annual observations 1960-1989.

1

1 . Introduction

This study examines the production of accounting earnings. Earnings are the

summary measure of firm performance produced under the accrual basis of accounting.

The production of earnings is important since the earnings number is used as a

summary measure of firm performance by a wide range of users. For example, the

Conference Board's (1990) survey of top-executive compensation reveals that

earnings-based bonuses are almost universal for executives of larger U.S.

manufacturing corporations. In addition, earnings are used in debt covenants to

monitor a firm's ability to meet its future payments [Smith and Warner (1979)].

Detailed earnings information is also reported in the prospectuses of firms seeking to go

public. As a fmal example, when firms announce preliminary results of performance to

the stock market, they report earnings. The components of earnings are revealed later

[Wilson (1987)]. The objective of this study is to better understand the role of accruals

in producing earnings as one of the key outputs of the accounting process. The study

develops and tests explanations for why accrual accounting is used to produce an

internally generated measure of firm performance.

The view adopted in this study is that the accrual process evolved to overcome

problems with measuring firm performance over finite intervals when the firm is in

continuous operation (i.e., a going concern). Information asymmetries between the

2

firm's management and other contracting parties create a demand for a measure of firm

performance to be produced at regular intervals. The common interest of all contracting

parties is to determine the firm's ability to generate cash flows. However, over finite

intervals, reporting the firm's net cash receipts and disbursements (realized cash flows)

is not necessarily informative. This is because realized cash flows have timing and

mismatching problems that cause them to be a relatively noisy measure of firm

performance, To mitigate these problems, parties contracting with the firm require

management to use generally accepted accounting principles to alter the timing of cash

flow recognition in earnings.

The accounting principle that guides the timing of cash flow recognition is the

revenue recognition principle. The revenue recognition principle requires revenues to

be recognized when a firm has performed all, or a substantial portion, of services to be

provided and cash receipt is reasonably certain. Similarly, if cash is received in

advance, revenue is recognized only as the service is performed. Closely linked to the

revenue recognition principle is the matching principle. The matching principle requires

that cash outlays associated directly with revenues be expensed in the period in which

the finn recognizes the revenue. By having such principles, the accrual process is

designed to mitigate timing and mismatching problems inherent in cash flows and

produce a more timely measure of firm performance.' In this context, a timely measure

of finn performance is one that reflects the effects of events or actions on the finn's

cash generating ability in the period during which those events or actions occur.

1 Accounting principles are discussed in Paton and Littleton [(1940), pp. 69-72] and in mostaccounting texts books, e.g., Stickney, Weil and Davidson [(1990), pp. 86-87] and Kieso andWeygandt [(1989), pp. 88-89].

3

Therefore, the acceptable set of accruals is predicted to improve the ability of earnings

to measure firm performance relative to realized cash flows.2

Requiring management to make accrual adjustments, however, introduces a

new set of problems. Management typically have some discretion over the recognition

of accruals. This discretion can be used by management in two ways: they can use

their discretion to signal their private information about firm performance, or they can

use it to opportunistically manipulate earnings. Signaling is expected to improve the

ability of earnings to measure firm performance since management presumably have

superior information concerning their firm's cash generating ability [Holthausen and

Leftwich (1983), Watts and Zimmerman (1986), Holthausen (1990) and Healy and

Palepu (1991)]. Therefore, a credible signal will reduce information asymmetries and

result in more efficient contracting. However, to the extent that management use their

discretion to opportunistically manipulate earnings, it will become a less reliable

measure of firm performance.' Therefore, it is an empirical question as to whether the

net effect of management discretion is to improve or reduce earnings' ability to reflect

firm performance relative to realized cash flows.

The concern that management will use their informational advantage to

opportunistically manipulate accruals is consistent with the allowable set of accruals

being limited by a set of accounting conventions [Watts and Zimmerman (1986)].

2 The term accrual is used in a general sense and includes both accruals, e.g., accounts receivable anddeferrals, e.g., prepaid subscriptions.

3 Watts and Zimmerman (1986) and Schipper (1989) provides a review on earnings management,Healy (1985), DeAngelo (1988) and Clinch and Magliolo (1992) provide evidence of earningsmanagement 'Earnings management' is often discussed in the popular press, see for example "GM 3rdquarter net jumped as change in accounting erased operating loss," Wall Street Journal, October 10,1987, p. 2, "Will "FASBEE' pinch your bottom line," Fonune, December 19, 1988,93-108.

4

Accounting conventions, such as objectivity, verifiability and the use of the historical

cost valuation model, limit the flexibility of management to manipulate revenue and

expense recognition. In the absence of problems with information asymmetries, such

conventions would be dysfunctional since their effect is to reduce the timeliness of

earnings. However, since management manipulation is not always detectable (at least

over short measurement intervals), contracting parties desire a performance measure

that is reliable (and verifiable by auditors) so that there are bounds on the manipulation

that can occur. The accrual process is therefore the result of a trade-off between

timeliness (or relevance) and reliability.'

This study designs empirical tests to compare earnings with both net cash flow

and cash from operations. These comparisons are made because the accrual process

can be thought of as starting with cash flows and then applying accrual adjustments to

produce earnings. By comparing earnings to realized cash flows in various

circumstances, insights can be obtained into the importance of the accrual process. Net

cash flow is the change in the firm's cash balance between two points in time. This

measure is chosen because it excludes all accrual adjustments and can therefore be

thought of as the most 'primitive' cash-based measure of firm performance. Cash from

operations is chosen as the second cash-based measure because it is often prescribed as

a competing measure of firm performance [e.g., Reimann (1990) and Skala (1991)].

This measure has also been used in previous research [e.g., Rayburn (1986), Wilson

(1986), Bowen, Burgstahler and Daley (1987), and Bernard and Stober (1989)]. Cash

from operations excludes accruals relating to the finn's operating activities. However,

4 BaH (1989) and Watts and Zimmerman [(1986) p. 206] discuss this trade off. The FASB alsoidentifies relevance and reliability as qualities that increase the value of accounting earnings inStatement of Financial Accounting Concepts No.2, paragraph 90.

5

as with earnings, cash from operations does not contain the direct cash flow effects of

the firm's capital investment and financing activities.

In order to compare the relative ability of earnings and cash flows to measure

finn performance, it is necessary to obtain a benchmark measure of finn performance,

Stock returns (net of market-wide movements) are used as the benchmark because they

are assumed to reflect a wider information set than either earnings or realized cash

flows concerning the finn's ability to generate future cash flows. A sufftcient condition

for this assumption to hold is that the stock market "correctly" evaluates the information

in earnings and cash flows so that it is "fully reflected" in stock price [Fama (1976,

133)].5 Market-wide movements are removed from stock returns to improve the power

of the empirical tests. Previous research suggests that market-wide movements are

dominated by macro-economic factors that have little impact on earnings or realized

cash flows [Sloan (1992a)]. In addition, if market-wide movements are 'noise' from

the perspective of evaluating firm-specific performance, then their removal will produce

a 'stronger' signal of the measure desired in contracts [Holmstrom (1982)]. Thus, the

measure (earnings or cash flows) that is more highly associated with market-adjusted

stock returns is judged to be the more useful measure of firm performance.

This study hypothesizes that accruals mitigate mismatching and timing problems

inherent in cash flows so as to produce a more useful summary measure of firm

performance. A mismatching problem exists when a cash outlay is made in one

measurement interval but the cash inflow associated with that outlay is received in

5 The assumption that the stock market is efficient with respect to publicly available information isimplicit in most capital market research performed in accounting. beginning with Ball and Brown(1968).

6

another measurement interval. For example, assume a firm pays cash for inventory and

then sells the inventory on account within one measurement interval. Cash flows will

reflect the cost but not the benefit associated with the sale. However, if the cash receipt

is reasonably certain, then earnings will reflect the net benefit, A timingproblem exists

when a firm performs a service in one measurement interval but the net cash receipt

(although reasonably certain) is received in another measurement interval. In the

example discussed above, assume that the firm both purchases and sells the inventory

on account so that there are no cash flow effects. Again, earnings will reflect the net

benefit of the sale. Whereas, cash flows will reflect the net benefit only in the next

measurement interval when cash is paid to the supplier and cash is received from the

customer. Cash flows do not suffer from mismatching problems in this circumstance

but they are an untimely measure of firm performance. Timing and mismatching

problems are predicted to become more severe, the shorter the performance

measurement interval.

Consistent with the prediction that accruals mitigate the timing and mismatching

problems inherent in cash flows, realized cash flows are demonstrated to be a poor

measure of firm performance relative to earnings. An examination of cash flows time­

series' properties indicates that changes in cash flows exhibit strong negative

autocorrelation. This is consistent with part of the change in cash flows being

temporary and reversing over time. Consequently t cash flows suffer from

mismatching problems over shorter measurement intervals. Earnings are predicted to

have fewer mismatching problems than cash flows because accruals combine with cash

flows to mitigate these problems. Consistent with this prediction, accruals are strongly

negatively correlated with changes in cash flows, while earnings itself, displays little

negative autocorrelation.

7

The study builds on the results of Easton, Harris and Ohlson (1992) who show

that the association of earnings with stock returns improves over longer measurement

intervals. The results presented here indicate that both cash flows and earnings

improve as measures of firm performance over longer measurement intervals, but that

cash flows improve relatively more than earnings. This result suggests that because

accrual accounting trades-off timeliness and reliability, accruals do not eliminate all

timing and mismatching problems in cash flows. Therefore, earnings also suffers from

timing and mismatching problems over short measurement intervals. However,

earnings suffer relatively less than cash flows because they include accruals.

The study also makes cross-sectional predictions concerning the importance of

accruals. The study predicts that for firms in 'steady state' (i.e., firms with cash

requirements for working capital, investments and financing that are relatively stable),

cash flows will have few mismatching problems and will be a relatively useful measure

of firm performance. However, for firms operating in volatile environments with large

fluctuations in their working capital requirements and their investment and financing

activities, cash flows will have more severe mismatching problems. Thus, cash flows'

ability to reflect firm performance will decline as the volatility of firms' working capital

requirements and investment and financing activities increases. Accruals are predicted

to mitigate mismatching problems in cash flows so that earnings' ability to reflect firm

performance is expected to vary less on these dimensions. The results are consistent

with this prediction. This finding is then used to obtain additional cross-sectional

predictions. The volatility of firms' working capital requirements is predicted to

increase with the length of their operating cycle. Thus, accruals are predicted to be

more important for firms in industries with long operating cycles. The results are

consistent with this prediction.

8

Finally, the study investigates specific accrual components. Short-term

working capital accruals are predicted to be relatively more important than long-term

operating accruals for mitigating the timing and mismatching problems inherent in cash

flows. Working capital accruals include the earliest developed accruals [Littleton

(1966)]. If mitigating mismatching problems in cash flows is the primary motivation

for accruals, then ceteris paribus, these accruals are predicted to mitigate the more

severe mismatching problems. In addition, special items (including write-downs and

write-offs of receivables, equipment, etc.) are investigated. Special items reflect the

cumulative effect of past over or understatement of accruals. These adjustments are not

made to mitigate mismatching problems in contemporaneous cash flows, rather they are

included in earnings primarily to make management accountable for past misstatements

of accruals and to maintain 'clean surplus' (e.g., Paton and Littleton [(1940), pp. 98­

102] and APB Opinion No. 30). Therefore, special items are not expected to improve

earnings' ability to reflect firm performance. The results are consistent with these

predictions.

The next chapter summarizes previous empirical research of relevance to this

study and describes the contribution of this study. Chapter 3 develops the research

hypotheses. Chapter 4 evaluates the role of price as the benchmark measure of firm

performance. Chapter 5 introduces and describes a recently developed statistical test

that is used to evaluate the research hypotheses. Chapter 6 discusses sample selection

issues and variable measurement. Chapter 7 and 8 analyze the empirical results.

Finally, chapter 9 summarizes the study and provides its conclusions.

9

2 • Review of the Literature

The issue of whether earnings or cash flows is a more useful measure of firm

performance is at the heart of determining if the accruals made by accountants are

useful. Thus, when Ball and Brown (1968) first examine the usefulness of earnings by

evaluating its association with stock returns, they also addressed this concern. Ball and

Brown find that earnings are more successful than their cash flow measure in predicting

the sign of annual stock returns. Similar results are documented by Beaver and Dukes

(1972). Both studies however, use crude cash flows proxies (earnings before

depreciation). Therefore, one explanation for their findings is that the cash flow proxy

is inappropriate. For example, Bowen Burgstahler and Daley (1986) show that

earnings before depreciation is more highly correlated with earnings than other more

finely defined measures of cash flows. Their evidence also indicates that for most of

the cash flow measures that they investigate, past realizations of the cash flow measures

predict future realizations of the cash flow measures better than do earnings.

Recent research has adopted a slightly different perspective from the earlier

studies to investigate the usefulness of accrual or cash flow information. Following

Patell and Kaplan (1977), recent work has focused on determining the components of

earnings that provide incremental information. This is referred to here as the

10

incremental approach. The question of interest is to determine which financial variables

the market finds informative when assessing firms' future cash flows. Various models

have been used to obtain abnormal returns and different techniques have also been used

to obtain the unexpected components. A regression is then performed of abnormal

stock returns on the various unexpected components of earnings. The interpretation of

the results is that if the coefficients on the unexpected components are significant, then

the market finds these components incrementally informative.

Patell and Kaplan (1977) investigate whether total funds from operations has

incremental information over earnings. They find that this surrogate for cash flows

does not provide any incremental information beyond earnings. Rayburn (1986)

extends Patell and Kaplan by determining whether a more refined measure of cash

flows provides incremental information, She decomposes earnings into cash from

operations, current and noncurrent accruals. Rayburn finds that current accruals and

cash flows have about equal incremental information content but fmds weaker evidence

for noncurrent accruals. Bowen, Burgstahler and Daley (1987) build on the results of

Patell and Kaplan by showing that their more refined measure of cash flows has

incremental information beyond earnings. They include both earnings and cash from

operations in a regression and show that both cash flows and earnings are significant.

Similar results are also reported by Schaefer and Kennelley (1986). Jennings (1990)

provides further analysis on the results of Rayburn and Bowen, Burgstahler and Daley.

He suggests that Rayburn's results are consistent with cash flows and current accruals

having similar incremental information content but that Bowen, Burgstahler and

Daley's results are consistent with these components being valued differently. Finally,

Livnat and Zarowin (1990) analyze whether cash flows relating to investing, fmancing

and operations have incremental information content over earnings. Their results

11

suggest that decomposing earnings into these finer partitionings provides incremental

information over earnings.

Wilson (1987) addresses the question of incremental information content in a

novel manner. The contribution of Wilson (1987) is to provide a test that specifically

controls for the information content of earnings. This is important since one concern

with Patell and Kaplan (1977) is that when the component of interest is highly

correlated with earnings (as is total funds from operations), it is difficult to disentangle

the information content of the component from the information content of earnings.

Wilson observes that the Wall Street Journal usually publishes the earnings number

prior to the release of the financial statements. This means that the components of

earnings are publicly available only when the financial statements are released.

Therefore, by analyzing the returns around the date when the financial statements are

released, he can control for the information in earnings and focus on the incremental

information content of the components.

Wilson's evidence is consistent with there being incremental information in the

cash from operations (and the current accrual) component. Wilson (1986) using a

different method of aggregating returns and assessing information content, provides

evidence consistent with the total accrual component being incrementally informative

beyond the cash component. Bernard and Stober (1989) perform similar tests to

Wilson using a more comprehensive data set. However, their evidence suggests that

Wilson's findings cannot be generalized. They find little evidence of incremental

information content for cash flows or accruals apart from the years that Wilson

examines. They also test whether the valuation implications of cash flows vary with

the economy or with a model that links the mix of currerit accruals to future sales.

However, no evidence is found that supports either prediction.

12

When summarizing this area of the literature, both Bernard (1991) and Neill,

Schaefer, Bahnson and Bradbury (1991) conclude that the results are mixed. It is not

clear which components of earnings are relatively more important for revising stock

prices. Studies using annual holding periods and refined cash flow measures generally

find that cash flows have incremental information content. However, studies

employing daily holding periods that have less problems with collinearity have obtained

inconsistent results. The conclusion generally drawn from this line of research is that

the incremental value of cash flows or accruals may depend on the specific contexts

analyzed.

The perspective adopted in this study differs from evaluating the incremental

information of accruals and cash flows and is similar to that of earlier studies by Ball

and Brown (1968) and Beaver and Dukes (1972). That is, the objective of this study is

to determine which measure, earnings or cash flows, is a more useful summary

measure of finn performance, This perspective is adopted because it is hypothesized

that the role of accruals is to mitigate timing and mismatching problems in cash flows in

order to produce earnings as an alternative, more useful summary measure of finn

performance. Evaluating the incremental content of cash flows or accruals does not

provide a direct test of which measure, earnings or cash flows, is a more useful

summary measure of finn performance. This is because observing that accruals and

cash flows have incremental information when included separately in a regression does

not tell us which of the two summary measures, earnings or cash flows is superior. In

summary, this study builds on previous research by (i) demonstrating the role of

accruals in mitigating temporary mismatching problems in cash flows, (ii) formally

establishing that earnings is a superior summary measure of firm performance and (iii)

13

identifying the determinant of mismatching problems in cash flows, thus highlighting

the circumstances under which accruals playa more important role.

14

3. Testable Predictions

3.1. The contracting role of accruals

The existence of information asymmetries between firms' managers and outside

parties contracting with the finn creates a demand for an internally generated measure of

firm performance, This measure can be used to evaluate management and as a source

of information to investors and creditors on the firm's cash generating ability. The

problem faced by contracting parties is that although management is the most informed

party to report on the firm's performance, they are also evaluated and rewarded based

on the finn's performance. Therefore, in the absence of objective procedures to

determine performance, external parties have difficulty assessing the reliability of

signals produced by management. On the one hand, contracting parties could demand

that managers report realized cash flows. These can be objectively measured but are

influenced by the timing of cash receipts and outlays. For example, management

would be penalized for purchasing inventory (above beginning inventory levels) even if

this was a positive net present value decision." On the other hand, management could

6 In the analysis undertaken here it is assumed that if the only numbers reported were cash flows, thencash flows would not change. However, management can also manipulate the timing and recognition

15

attempt to determine the change in the net present value of the firm's expected future

cash flows in each reporting period. The use of net present values however, could

provide management with so much reporting flexibility that any signal produced would

be difficult toverify and would result in an unreliable measure of finn performance.

The accrual process can be viewed as trading-off these two problems when

producing earnings as a summary measure of firm performance. The accrual process

provides rules on the recognition of cash flows so that earnings will be a more timely

measure of firm performance than realized cash flows. However, accruals are also

required to be objective and verifiable. For example, expenditures can only be

capitalized when there is objective and verifiable evidence that the expected cash flows

will be realized. Similarly, cash received in advance is not recognized as revenue until

there is verifiable evidence that the firm has performed the service. Requiring

objectivity and verifiability limits management's discretion in reporting a measure of the

firm's cash generating ability. This will reduce the timeliness of reported earnings in

circumstances where management is more informed and wishes to signal private

information. However, it will also reduce the ability of management to falsely signal.

Ifexisting accruals are the outcome of efficient contracting, then the use of accruals is

expected, on average, to improve the ability of earnings to measure firm performance

relative to cash flows. Alternatively, if the dominant effect of accruals is to provide

management with flexibility to manipulate earnings, then cash flows will provide a

relatively more useful summary measure of firm performance over short measurement

intervals.

or cash flows. The economic implications of manipulating cash flows could be greater than that ofmanipulating accruals andis an additional explanation for theexistence of accruals [seeBall (1989)].

16

This study compares the ability of earnings to reflect finn performance relative

to the ability of net cash flows and cash from operations. Net cash flows measure the

change in the finn's cash balance over the period. This measure will fluctuate with

cash inflows and outflows associated with the finn's investment and financing activities

as well as the finn's operating activities. No accrual adjustments are made to net cash

flows. Therefore, 'aggregate accruals' refers to the difference between earnings and

net cash flows. Cash from operations reflects the net cash flows generated by the

finn's operating activities. This measure includes accruals that are 'long-term' in nature

that control for timing and mismatching problems associated with the firm's investment

and financing activities." For example, cash from operations excludes the cash flow

effects associated with purchasing capital investments, paying dividends or issuing new

stock. It is, however, sensitive to decisions by management to capitalize rather than

expense cash outlays for assets. Earnings include additional accruals beyond those

contained in cash from operations. In particular, it includes accruals that are short-term

in nature that control for temporary fluctuations in firms' working capital requirements.

Appendix 1 provides a detailed break-down of the accruals made to net cash flows to

obtain earnings.

3.2. Measurement interval predictions

If the accrual process evolved so as to produce a more timely measure of finn

performance than realized cash flows, then net cash flows are, on average, expected to

be a relatively poor measure of finn performance. Net cash flows have no accrual

adjustments and will suffer severely from timing and mismatching problems. Cash

7 Accruals relating to thefirm's investments andfinancing areconsidered long-term since they are notexpected to becompletely reversed for at least oneyear.

17

from operations are also expected to be a poor measure of firm performance because

they suffer from timing and mismatching problems associated with changes in firms'

working capital requirements. Earnings are expected to be, on average, a more useful

measure of firm performance than either cash flow measure. Earnings contain accruals

that mitigate the mismatching problems associated with firms' investment and fmancing

cash flows as well as working capital accruals that mitigate temporary fluctuations in

operating cash flows.

Stock returns are assumed to encompass the information about firm

performance provided in cash flows and earnings. Therefore, the measure (either cash

flows or earnings) that explains more of the variation in stock returns is assumed to be

a more useful measure of firm performance over the period. This generates the first

prediction:

Hypothesis 1: Overshortmeasurement intervals, there is a stronger association

between contemporaneous earnings and stock returns than

between either contemporaneous cash from operations and stock

returns or contemporaneous net cash flows and stockreturns.

The alternative view is that the accrual basis of accounting has gone 'too far.'

That is, management has been given so much flexibility to manipulate accruals that any

signal produced is primarily noise. Under this view, if a performance measure is

desired, then the measure of choice is cash flows. This view is often expressed in the

popular press, for example, Skala (Chemical Week, May 8,1991) states:

"Many financial analysts regard operating cash flow as a better gauge ofcorporate financial performance than net income, since it is less subject todistortion from differing accounting practices."

As a second example, Stem (Planning Review, JanlFeb 1988) states:

18

.. Think cash and risk - forget earnings per share."

As a final example, Wilson (1987) provides the following quote from a Chase

Financial brochure:

"... It is cash-in minus cash-out, or Free Cash Flow, that counts - notaccounting earnings or their growth."

Thus, it is an empirical question whether the first-order effect of accruals is to

produce a more timely summary measure of finn performance (as predicted under

efficient contracting) or a more noisy measure of finn performance (as predicted under

management manipulation).

Additional implications of the relation between earnings and cash flows can be

obtained by considering the following simplified example of a finn with only one

accrual, accounts receivable. [For a more comprehensive model of accruals the reader

is referred to Jones (1991)].

Let Ct = cash collected in accounting period 1.

St = revenues generated from sales made during accounting period t.

q> =proportion of accounting period t-l sales for which cash is not collected

until the next accounting period t. q> is assumed constant for each

accounting period and all cash is collected by t.

\

Now C] =(1- q»St + q>St-I· (3-1)

Thus, earnings will differ from cash flows in each period to the extent that credit sales

are excluded from current performance under the cash basis of accounting. Consider

doubling the time interval over which performance is measured. Under these

19

circumstances, the importance of accounting accruals diminishes. Originally, the

proportion of uncollected sales equaled cpo With a doubling of the time interval, total

revenues are (St + St- I). Total accruals at the end of the period are still cpSt. So the

proportion of uncollected sales cp' is:

, cpStcp =St + Sj; I' (3-2)

As long as St-l > 0, then cp > cp' and, ceteris paribus, increasing the time interval will

always result in accruals constituting a smaller proportion of the total revenues

generated over the period. Equation (3-2) reveals that over longer intervals earnings

and realized cash flows are expected to converge as measures of firm performance.

Hypothesis 2 builds on hypothesis 1 by predicting the direction of convergence:

Hypothesis 2: The contemporaneous association of realized cash flows with

stock returns improves relative to the contemporaneous

association of earnings with stock returns as the measurement

interval is increased.

The alternative hypothesis is that due to the manipulation of accruals, earnings

are a noisy measure of firm performance over short intervals. Under the alternative

hypothesis, earnings will improve relative to cash flows over longer measurement

intervals. Note however, that the ability of earnings to reflect firm performance is also

expected to improve over longer measurement intervals [see, Easton, Harris and

Ohlson (1992)]. This is because accruals do not completely mitigate all short-term

timing and mismatching problems in realized cash flows. An empirical investigation of

hypothesis 2 can provide insights into the economic importance of accruals. Evidence

that cash flows' ability to measure firm performance is poor over intervals that are

20

commonly used to report finn performance (e.g., one year) and converge to that of

earnings only over long measurement intervals, would confirm the economic

significance of accruals.

3.3. Cross-sectional predictions

3.3.1. The effect of the magnitude of accruals

Equation (3-1) can also provide insights into determinants of cross-sectional

variation in the usefulness of accruals. Recall that in equation (3-1):

Ct =(1- lp)St + <PSt-I.

If a steady state firm is defined as one that is neither growing nor declining

(i.e., neither increasing nor reducing sales), then this implies that,

St =St-l.

Substituting St for St-l in equation (3-1):

and so Ct =St·

Therefore, in a steady state firm there will be no difference between the

numbers reported under a cash system or an accrual system. Thus, this is not a

situation where accruals are important Consider instead, the case of a second firm that

has identical sales in period t-l to the steady state firm but has an increase (or decrease)

in sales in period 1. In this case St :/: St-l and:

Ct =St - <p(St - St-l),

21

and so

(3-3)

where 65t =(5t - 5t-l)·

Equation (3-3) reveals that the magnitude of the difference between revenues

and cash flows for any period will be greater (i) the larger cp, i.e., the proportion of

sales on credit; and (ii) the larger the magnitude of the change in revenues (65t).

Alternatively stated, the difference between revenues and cash flows over the period is

increasing in the absolute magnitude of the change in the balance of accounts

receivable, cp65t ' over the period.

This analysis highlights where accruals are expected to play an important role in

measuring firm performance. The accrual process is most important for firms that have

had large changes in the net balance of their non-cash accounts. Consider for example,

a ship building firm that obtains a lucrative construction contract. The construction

takes several accounting periods and the payment by the customer occurs on completion

of the contract. Under generally accepted accounting principles, revenue recognition

for this contract is based on an engineer's estimate of the degree of completion. If cash

collection is reasonably certain, then the actual timing of the cash collection is not

relevant for reporting purposes. Cash flows for the firm could easily be negative in the

early periods because of purchases required for the construction contract. Revenues on

the other hand (through an increase in accounts receivable) are positive, and the

application of the matching principle will lead to positive earnings. Thus, earnings will

better reflect the contract's value and indicate that the firm has performed well in each of

the periods. This highlights an important feature of the accrual process. If accruals

reduce timing and mismatching problems, then earnings are expected to reflect

22

relatively more value-relevant events when earnings and cash flows differ by the

greatest magnitude.

While the analysis focuses on accounts receivable, it is readily generalizable to

other accruals (changes in other non-cash accounts). When the net change in all non­

cash accounts is large in magnitude (either positive or negative), earnings will more

closely reflect firm performance than realized cash flows. Equation (3-3) suggests that

cash flows are not a poor measure of firm performance for firms that are in 'steady

state'. However, when firms undertake new investment and financing activities or

experience large changes in their working capital requirements, (when ASt is large in

absolute magnitude) cash flows are expected to be a relatively poor measure of firm

performance. Under such circumstances, cash flows suffer from timing and

mismatching problems and are less able to reflect firm performance. Accruals are

predicted to reduce these problems in earnings. This leads to the following hypothesis:

Hypothesis 3 The larger theabsolute magnitude ofaggregate accruals madeby

a firm, the lower the contemporaneous association betweennet

cash flows and stock returns relative to the association of

earnings andstockreturns.

Hypothesis 3 predicts that as aggregate accruals increase in magnitude, net cash

flows will suffer more greatly from timing and mismatching problems. Thus, in firms

with relatively small changes in aggregate accruals, net cash flows will have few

mismatching problems and will be a useful measure of firm performance. Whereas,

when aggregate accruals are relatively large in magnitude, net cash flows will have

more timing and mismatching problems and will be a poor measure of firm

performance. As earnings includes accruals that mitigate these timing and mismatching

23

problems, earnings association with stock returns is not expected to decline as much

with increases in the magnitude of accruals. Note that by considering the magnitude of

accruals irrespective of the sign, a more powerful test of the relative importance of the

accrual process is obtained.

3.3.2. Components of accruals

This study investigates several components of accruals to provide insights into

which accruals are relatively more important for reflecting firm performance. One

subset of accruals investigated is short-term working capital accruals. Watts (1977)

suggests that accruals evolving in an unregulated economy are more likely to be the

outcome of efficient contracting. Many of the components of working capital (for

example, accounts receivable, inventory and accounts payable) have existed for

centuries [see Littleton (1966)]. Therefore, ceteris paribus, if accruals evolved to

mitigate mismatching problems in realized cash flows, then working capital accruals are

likely to mitigate the more acute mismatching problems. Therefore, working capital

accruals are predicted to be important for reflecting firm performance over short

measurement intervals.

Hypothesis 4(a): The larger the absolute magnitude of the change in working

capital, the lower thecontemporaneous association between cash

from operations and stock returns relative to the association of

earnings andstock returns.

In contrast, long-term operating accruals (such as depreciation), are predicted to

be relatively less important for two reasons. First, long-term operating accruals are

more recent accrual innovations and therefore, ceteris paribus, are likely to mitigate less

severe mismatching problems in cash flows. Second, many of these accruals were

24

introduced following the regulation of accounting practices and so the motivation for

their introduction can be influenced by other factors [see Watts (1977) and Watts and

Zimmerman (1979)].8 Therefore, the association of cash from operations with stock

returns is not expected to be a declining function of long-term operating accruals. Cash

from operations is used as the cash-based measure of firm performance because the

objective of the test is to focus on working capital and long-term operating accruals (the

accruals made to cash from operations to obtain earnings).

The final component of accruals investigated is special items. Special items

represent the cumulative effect of previous under or overstatement of accruals. Prior to

APB No. 30 special items were predominantly classified as 'extraordinary' since they

are non recurring in nature and are not expected to be relevant for measuring current

performance [e.g., Nichols (1974) and Barnea, Ronen and Sadan (1975)]. However,

management had discretion to determine what special items would be classified as

'extraordinary' and therefore excluded from earnings (from continuing operations).

This discretion was perceived to be used by management to manipulate earnings. For

example at the time APB No. 30 was released the Wall StreetJournal notes than?

"critics ...contend the proliferation of special items has confused investors andenabled corporate managements to gloss over bad business decisions. Toooften, they charge, routine losses are allowed to pile up. Then, when finallywritten off as an "extraordinary" loss, the write-off is inflated, sweeping all the"garbage" off the books and setting up a healthy profit rebound."

8 Accruals introduced following regulation willnotnecessarily reduceearnings' ability to measure fumperformance. Manytransactions that resultin accruals did not occurprior to regulation. Therefore, thesameprocedures mayhaveevolved in an unregulated environment and beconsistentwith theobjectivesof contracting parties.

9 See n Accounting Panel seen curbing the use of special items," the Wall Street Journal, March 15,1973, p. 2.

25

APB No. 30 reduced the discretion of management by requiring that 'special

items' flow through income from continuing operations so that 'clean surplus' is

maintained and cumulative earnings is measured objectively.l? Therefore, special items

are an accrual adjustment that is predicted to reduce earnings' ability to reflect firm

performance.

Hypothesis 4(b): There is a stronger association between earnings (before special

items) and stock returns than between earnings (after special

items) andstockreturns overshortmeasurement intervals.

3. 3.3. The effect of the operating cycle

The final hypothesis predicts the type of firms in which the volatility of accruals

will be large and hence realized cash flows will be a poor measure of firm performance.

Equation (3-3) reveals that the change in accounts receivable, <pASt, is composed of two

components <p, and ASt. Therefore, the magnitude of accruals is larger, the greater the

change in the level of sales ASt, and the larger the proportion of sales on credit, cpo

Generalizing from sales, St can be proxied by the level of operating activity and cp can

be proxied by the length of the operating cycle. The operating cycle measures the

average time elapsing between the disbursement of cash to produce a product and the

receipt of cash from the sale of the product. Firms with longer operating cycles are

expected to have larger working capital requirements for a given level of operating

10 Prior to APB No.9 (issued in 1966) the primary concern had been whether to disclose extraordinaryitems in retained earnings or in the net income figure. APB No.9 defined extraordinary items as 'of acharacter significantly different from the typical or customary business activities of the entity' and'which would not be expected to recur frequently.' APB No. 30 (issued in 1973) tightened thisdefmition by requiring items to be classified as extraordinary only if they were both unusual in natureand infrequent in occurrence.

•26

activity. Therefore. in firms with longer operating cycle. a given change in the level of

operating activity [t\Stl. is expected to translate into a larger change in the required level

of working capital [cpt\Stl. Thus. the length of the operating cycle is predicted to be an

underlying determinant of the volatility of working capital. Cash from operations

excludes accruals relating to the finn's operating activities. Hence the ability of cash

from operations to measure firm performance is expected to decline as the length of the

operating cycle increases. II

This leads to the following hypothesis:

Hypothesis 5: The longer afirm's operating cycle, the more variable thefirm's

working capital requirements and the lower the

contemporaneous association between cashfrom operations and

stockreturns.

Short-term working capital accruals are hypothesized to reduce the timing and

mismatching problems inherent in cash from operations. Hence, the ability of earnings

to reflect finn performance is not expected to be as sensitive to the length of the

operating cycle.

II The analysis focuses on cash from operations rather than net cash flows because cash fromoperations is directly affected by the firm's operating activities (and hence the operating cycle). Netcash flows is only indirectly affected by the firms operating cycle since it will also fluctuate with theinvestment and fmancing activities undertaken by thefirm,

(4-1)

27

4. The Use of Stock Price as the BenchmarkMeasure of Firm Performance

4.1. Stock price as a benchmark

The question of interest in this study is: given an internally generated measure

of finn performance is desired for contracting, which measure, earnings or cash flows

better reflects the firm's performance over a given measurement interval? This study

assumes that stock markets are efficient in the sense that stock prices encompass the

information provided in cash flows, earnings and other sources of information about

firms' expected stream of future cash flows. Therefore, stock price performance is

used as the benchmark measure of firm performance, because it is assumed to reflect in

a timely manner, the net cash flow effects of current events or actions taken by the firm.

In the empirical analysis each performance measure is scaled by beginning of

period price. This reduces problems with heteroskedasticity [see Christie (1986)].

Thus,

p. M·~ =a+~_l_t.Pit-l Pit-l

where Pit is the price of firm i at time t, Mit is either earnings-per-share, net cash flows-

per-share or cash from operations per-share for firm i measured from t-l to 1.

28

Subtracting Pp~t-l from both sides results in a regression of stock returns (R) onIt-l

earnings or cash flows-per-share scaled by price:

M·Rot = (n-I) + A~.

I p Pit-l (4-2)

This study compares each measures' association with stock returns (the

benchmark measure of firm performance) and judges the one with the highest

association to be a more useful measure of firm performance. In equation (4-2), stock

returns are regressed on the 'level' of earnings or cash flows per-share.P Thus, if

either earnings or cash flows contain temporary components that are not reflected in

stock returns, then these are not removed when assessing the ability of each measure to

reflect firm performance. Note that some portion of this temporary component may be

predictable based on the past time-series of each variable.P However, these

predictable components are not removed because one of the hypothesized roles of

accruals in this study is to remove both the predictable and non-predictable temporary

components in cash flows. Therefore, in this context, attempting to eliminate

predictable temporary components in cash flows would ignore the fact that accruals

already incorporate this adjustment.

In the empirical analysis stock returns net of market-wide movements are used

as the dependent variable. The reason for removing market-wide movements is to

12 Existing research has used the 'level' specification of earnings [Easton and Harris (1991), Easton,Harris and Ohlson (1992) and Kothari and Sloan (l992)]. Ohlson (1991) and Kothari (1992)analytically demonstrate that the earnings 'level'specification improves the explanatory powerof theregression overtherust difference specification.

13 It may also be possible to predict temporary components using other accounting data, see, forexample, Lev andThiagarajan (1991).

29

obtain a 'stronger' signal of the performance measure desired by contracting parties. In

this study it is assumed that market-wide movements are predominantly driven by

macro-economic factors that are beyond management's control (such as changes in

discount rates). Therefore, they can be considered 'noise' from the perspective of

evaluating the firm's relative performance [see Holmstrom (1982)]. Sloan (1992a)

provides evidence that market-wide movements are not reflected in earnings or cash

flows. This is consistent with both of these internally generated measures of firm

performance excluding factors such as changes in discount rates. It is therefore

assumed that the desired performance measure to be used in contracts excludes these

macro-economic factors.

From an empirical view point there is an added advantage of removing market­

wide movements. Bernard (1986) points out that removing market-wide movements

reduces problems with cross-sectional dependence in regressions. Note however, that

removing market-wide movement is not critical to the analysis since, empirically, both

earnings and cash flows have a low association with market-wide movements over each

of the measurement intervals examined. Therefore, similar results are obtained when

raw stock returns are substituted as the dependent variable.

The approach of evaluating the usefulness of accounting information such as

earnings by determining its association with stock returns is not new and is widely used

in accounting research. For example, when Lev (1989) reviews the state of accounting

research he evaluates the usefulness of earnings' by determining its association with

stock returns. Ball and Brown (1968) and Beaver and Dukes (1972) evaluate the

relative usefulness of earnings and earnings before depreciation by comparing each

measure's association with stock returns. In addition, Beaver and Landsman (1983)

evaluate the usefulness of FASB Statement No. 33 earnings by determining if it can

30

explain any of the residual variation from a regression of stock returns on historical cost

earnings. As Beaver and Landsman [(1983), p. 2] point out, obtaining alternative

measures of expected cash flows other than stock price based measures is difficult to

achieve and any other proxy (such as actual future cash flows) introduces additional

assumptions and noise into the analysis.

Even though stock prices are assumed to encompass the information in earnings

and cash flows about firm performance, an internally generated measure of firm

performance is not necessarily redundant. As discussed in chapter 1, stock markets

react to the release of earnings information and to forecasts of earnings [e.g., Foster

(1977) and Patell (1976)]. Thus, the production of financial information such as

earnings is an integral part of price formation. If it is assumed that for competitive

reasons it is costly for firms to disclose all information [see Black (1992)], then a

summary measure is the most desirable format to release information to the stock

market. Alternatively, aggregating information into a summary measure of firm

performance could be the most efficient way for management to communicate with

users when there are information processing costs [e.g., Beaver and Demski (1979)

and Beaver (1981, p. 167)].

Another important reason why internally generated measures of firm

performance, such as earnings are not redundant even when stock prices are available is

highlighted by Sloan (1992b). Sloan (1992b) presents evidence consistent with

earnings-based incentives being incrementally useful over stock price-based incentives

for rewarding management. He shows that earnings reflect firm-specific changes in

value, but are less sensitive to market-wide movements in equity values. Thus,

including earnings-based performance measures in compensation contracts helps shield

executives from fluctuations in firm value that are beyond their control [see Banker and

31

Datar (1989)]. Smith and Watts (1982) also point out that within firms or in private

firms, where there are no stock prices, alternative measures are required for evaluating

and rewarding management. Finally, unlike stock prices, earnings can be decomposed

into components, this is useful in debt covenants since debt holders can provide

management with incentives to increase overall firm performance as well as to protect

their claims [e.g., Smith and Warner (1979)].

4.2. Stock market efficiency versus functional fixation

An assumption made in the analysis is that the stock market is efficient. That is,

price is an unbiased measure of expected future cash flows and so any information in

earnings or cash flows is fully revealed in price. However, if price deviates from

fundamentals and contains noise, then the implicit assumption is that the noise in price

is uncorrelated with either cash flows or earnings. This assumption implies that no bias

in favor of either measure is introduced by using price as a proxy for firm performance.

A violation of this assumption would occur if the market is functionally fixated on one

of the two measures. For example, if the market is functionally fixated on earnings,

then the noise in stock price is correlated with earnings but not with cash flows. Under

this scenario, a higher association between earnings and stock returns would be found

even if earnings are not a more 'useful' measure of firm performance. The higher

association would be a consequence of using an inappropriate benchmark of firm

performance. A similar problem would exist if the market is functionally fixated on

cash flows.

Studies investigating functional fixation have focused on determining whether

the market is fixated on earnings. To date, however evidence on functional fixation has

been mixed. Early studies investigating functional fixation of earnings examined

32

whether the market can 'see through' accounting procedure changes. Both Kaplan and

Roll (1972) and Ball (1972) do not find statistically significant stock price reactions to

the accounting procedure changes. However, these studies suffer from industry

clustering and other confounding event that makes interpretation difficult [see Watts and

Zimmerman (1986)]. Hand (1990) tests for functional fixation by determining whether

the market reacts to earnings that contain gains from previously disclosed debt-equity

swaps. Hand suggests that his evidence is consistent with the stock market reacting to

these previously disclosed 'paper' gains. However, Ball and Kothari (1991) argue that

Hand's results are indistinguishable from the previously documented size effect in

stock returns at announcement dates. Although, Hand (1991) argues that he presents

additional evidence that is inconsistent with Ball and Kothari's explanation.

Recent work by Sloan (l992c) provides evidence consistent with the functional

fixation hypothesis. Sloan shows that high operating accruals are followed by negative

accrual reversals that cause earnings reductions (and vice versa). He argues that if the

market is fixated on earnings, these predictable earnings reversals caused by accruals

will not be fully anticipated by the share price. Therefore, future returns will be

predictable based on the magnitude of accruals. Sloan presents evidence consistent

with this prediction. Sloan finds that at most, ten percent of accruals reverse (cause

predictable changes in subsequent earnings) while the remaining 90 percent of accruals

capture permanent changes in firms' earnings generating ability. Therefore, consistent

with the results presented in this study, the overriding effect of accruals appears to be

an improvement in the ability of earnings to reflect firm performance. However,

because the market does not fully incorporate the predictable earnings reversals, excess

returns are documented by Sloan, for up to three years following the original earnings

release.

33

One test performed in this study directly addresses the concern of functional

fixation. This study examines a subset of accruals that are made to correct for past over

or understatement of accruals. The subset of accruals is special items. Special items

include write-off or write-downs of assets, any adjustment applicable to prior years etc.

These accruals are not predicted to be made to improve earnings' ability to measure finn

performance but rather to maintain 'clean surplus' and to ensure that management is

accountable for the effect of such adjustments. Therefore, their inclusion in earnings is

predicted to reduce the ability of earnings to measure firm performance. The evidence

is consistent with earnings before special items having a higher association with stock

returns than earnings from continuing operations over short measurement intervals.

This evidence is inconsistent with functional fixation, since the market 'backs out' this

component when assessing finn performance.l?

14 A direct test controlling for the evidence of functional fixation documented by Sloan is alsoperformed. Sloan's (l992c) evidence is consistent with predictable accrual reversals taking up to threeyears to be fully incorporated intoprice. Therefore, returns cumulated from the beginning of yeart tothe end of year t+3 will incorporate the effectof any reversals. The resulting R2s for regressions ofearnings and cash from operations using this return metric as the dependent variable are 14.61% forearnings and 6.01% for cash from operations (the sample consists of 4,175 non-overlapping finn­observations). When contemporaneous annual stock returns are used, the R2 on earnings is 17.23%and 4.20% for cash from operations. Therefore, the tenor of the results do not change using thisalternative four-year return metric. Earnings havemore explanatory power thancashflowsevenaftercontrolling for thepotential effectof functional fixation,

34

5 • Non-Nested Model Selection

5.1. The encompassing approach to non-nested model

selection

The research question addressed in this study is: which measure, earnings or

cash flows is a 'better' estimate of firm performance as reflected in stock returns?

Thus, the objective of the study is to determine the conditions under which earnings

explain more of the variation in stock returns than cash flows. If earnings do explain

more of the variation than cash flows, then earnings can be thought of as a more useful

measure of firm performance.

A simple approach to selecting the 'best' model is to compare the coefficients of

determination (R2s) from the separate regressions of stock returns on earnings and

stock returns on cash flows, choosing the model with the highest R2. This seemingly

ad hoc approach has been justified by Gaver and Geisel (1974) and Pollak and Wales

(1991). Gaver and Geisel show that a comparison of R2s can be justified on Bayesian

grounds when the prior information on the distribution of the model parameters is

diffuse (noninformative). Pollak and Wales using a classical approach, show that

35

when both models have the same number of parameters, the likelihood dominance

criterion implies a comparison ofR2s.

An alternative way of addressing this question is the encompassing approach to

model selection [for a review of this literature, see Mizon and Richard (1986)]. The

encompassing principle is based on the idea that a model can be considered superior to

rival models if it can account for the salient features of rival models. The approach

adopted is to test for misspecification of one model in the direction of competing

models. The procedure is done in two steps. First, one model is assumed to be true

and the test involves determining if this model 'encompasses' or explains the salient

characteristics of the competing model. This occurs if we cannot reject the specification

of the null model in the direction of the alternative. The second step is to do the same

procedure in reverse, i.e., determine if the second model explains the relevant

characteristics of the first model (when the second model is assumed true). If the first

model explains the relevant characteristics of the second model but the second model

does not explain the relevant characteristics of the first model, then we can

unambiguously conclude that the first model 'encompasses' the second model and is

the model of choice. The problem with this approach is that ambiguous results are

obtained when both models reject each other or neither model rejects the alternative.

Under these circumstances, such tests do not indicate which model is closer to the 'true

data generating process.'

5.1.1. The .l-test

One 'encompassing test' is the I-test developed by Davidson and MacKinnon

(1981). This test is discussed and used in Biddle and .Seow (1990). Consider

applying the I-test to determine the relative ability of earnings and cash flows to explain

36

stock returns. In these circumstances, the J-test is simply a multiple regression of stock

returns on earnings (E) and cash flows (C), (for simplicity the time subscripts are

excluded):

(5-1)

The test then determines whether the coefficients on either earnings or cash flows is

significant. Thus, tests of the hypothesis that earnings relative to cash flows has a

stronger association with stock returns can lead to the four potential outcomes, as

illustrated on the following table.

Hypothesis:

~=o

Not Rejected

Not Rejected

Cannot Distinguish

Hypothesis: "( =0

Rejected

Reject Cash Flows inFavor of Earnings

Rejected Reject Earnings inFavor of Cash Flows Cannot Distinguish

When applied to the actual data used in this study, only the coefficient on earnings is

significant at conventional levels over the quarterly interval (an outcome in the top right

cell). This can be interpreted as earnings 'encompassing' the salient features of cash

flows and therefore earnings is selected as the 'superior' model. However, over the

annual and four-year intervals, the coefficient on both cash flows and earnings are

significant at conventional levels (the outcome is in the bottom right cell). Under these

circumstances, the J-test cannot rank the two competing models (earnings or cash

flows) or indicate which is 'better.' This occurs since under the null hypothesis, one

37

model (e.g., earnings) is assumed to be 'true' and thus if cash flows provide any

additional information the original presumption that earnings is the true model must be

incorrect. A similar rejection of cash flows in favor of earnings occurs when cash

flows are assumed under the null to be 'true.' Therefore, this test lacks power at

conventional levels, to distinguish earnings from cash flows as competing non-nested

models. [See Maddala (1988, pp. 443-447) for additional discussion on the Davidson

and MacKinnon test].

5.1.2. The incremental approach

Consider decomposing earnings into cash flows and accruals (C + A), so that

equation (5-1) is now restated in terms of these components:

or

(5-2)

where 0 = ~+'Y.

Ifwe are only interested in determining if accruals have incremental information

content, then all that is necessary is to determine if'Y is significant in the regression.

However, in this study it is hypothesized that the reason for accruals is so that earnings

relative to cash flows is a more useful summary measure of firm performance..

Producing earnings therefore, not only involves determining the set of accruals that will

be included in earnings but also the form the accruals will take so that they can be

aggregated to produce earnings. This places additional structure on accruals since they

must not only be informative (have incremental information content) but also be of a

38

form that any information lost through aggregation is not so large as to render earnings

a poorer summary measure of firm performance than cash flows. Therefore, if we are

interested in determining if earnings explains relatively more of the variation in stock

returnsthancash flows, then two conditions are required:

(a)yis significantly different from zero

(b) the linear restriction, 0=y,cannotbe rejected

Since equation (5-2) is identical to (5-1) the results of this test are obvious.

Although, accruals have incremental content [as documented by Rayburn (1986)], the

linearrestriction is rejected over the annual andfouryear intervals. Therefore, although

accruals have incremental information over that of cash flows, no statistical inference

can be made concerning which measure earnings or cash flows is a superior summary

measure of firm performance,

5.2. Using the Vuong likelihood ratio test to evaluate

earnings versus cash flows

A recent development in model selection techniques is Vuong (1989). Vuong

has provided a statistical test to determine which of two models better explains the

dependent variable. The difference between the Vuong test and other non-nested tests,

such as the f-test, is that Vuong has derived the distribution of the likelihood ratio

statistic without the assumption under the null hypothesis that either model is 'true.'

This test is directional and can be used to determine which of two imperfect models is

closer to the true 'data generating process.' The advantage of the Vuong test in the

circumstance outlined above is that Vuong's test statistic allows both models to have

explanatory power(be in thebottom rightcell) but provides direction concerning which

39

of the two is closer to the 'true data generating process'. Therefore. the Vuong test

allows rejection of cash flows in favor of earnings in situations where the tests

described above would not

Consider first. the model of stock returns depending on earnings (again. for

simplicity the time subscripts are excluded):

(5-3)

This implies that Ri are independently and normally distributed with mean (lE + ~EEi

and a common variance O'E2. The joint density of the observations is.

(5-4)

The log likelihood function L«l,~.0'2) is:

(5-5)

When maximizing L with respect to c, ~ and 0'2, as noted in Maddala (1988),

the maximum likelihood estimators of (l and ~ are the same as the least squares1\ 1\

estimators of (l and ji, Substituting (lEand ~E for (lE and ~E we can see that for each

i, Ri - ~E - ~EEi = eEio while the maximum likelihood estimate of O'E2 is R~SE , where

RSSE is the residual sum of squares from the regression of stock returns on earnings.

Now consider the model of stock returns depending on cash from operations:

(5-6)

40

A similar log likelihood function can be obtained for cash from operations:

n n 1 1 ]log L(RcFO) = .L log L(RCi) =.Lf. 2 10g (27tO'c2) -~2Rr - (Xc - ~cCFOi)2

1=1 1=11. 20'c

(5-7)

Again, the maximum likelihood estimate for 0'2 is R;SC and eci = Ri -~ - ~cCFOi.

/\ /\Substituting eEi for Ri - (XE - f3EEi in equation (5-4) and similarly substituting

/\ /\and eCi for R; - (Xc - f3cCFOi in equation (5-7), and obtaining estimates of O'c2 and

O'E2, we can determine which of the two models explains relatively more of the

dependent variable. This is done by first forming a likelihood ratio test comparing cash

flows to earnings:

(5-8)

An estimate of the variance, ro2, of LR is given by [see Vuong (1989, equation 4.2)]:

The statistic is then formed as:

Z=_1 LR...[0/\

CJ)

(5-9)

(5-10)

which tends in distribution to a standard normal random variable. This test is

directional in the sense that if the Z-statistic is positive and significant the test indicates

that earnings explain significantly more of the variation in stock returns than cash from

41

operations, whereas if the Z-statistic is negative and significant the opposite conclusion

can be drawn.

In the case at hand a simpler approach to estimating the Z-statistic is available.

Mter substituting estimates R~SE for O'E2 and eEi for Ri - ~E - ~EEi in equation (5-4)

and R~Sc for O'c2 and eCi for Ri -~ - acCFOi in equation (5-7), and then substituting

(5-5) and (5-7) into (5-8) we can obtain for each observation i,

LRj = 10g[L(REi)] - 10g[L(RCi)]

1 (27t ) 1 (27t ) n 2 n 2=210g n RSSc - 2log n RSSE + 2RSSc (eci) - 2RSSE (eEi) .

Simplifying we can obtain mj for each observation:

which if summed results in the likelihood ratio statistic (5-8).

(5-11)

(5-12)

The next step is to estimate the standard deviation of LR. Vuong notes (see p.

318), instead of estimating the standard deviation ofLR directly to form a Z-statistic, in

this simple case we can obtain the Z-statistic by regressing mj on unity. The coefficient

in this regression will equal ~ 10g[~~~~J and tells us the mean difference in

explanatory power between earnings and cash flows. The standard error, from the

regression tells us whether the relationship is unusual, i.e., if the difference is

significant. The Z-statistic can be obtained by multiplying the t-statistic from the

regression by (n~1f. Note that a positive Z-statistic implies that the residuals

produced by the cash from operations' regression are larger in magnitude than those

from the earnings regression. Hence, a positive and significant Z-statistic indicates that

42

earnings explain significantly more of the variation in stock returns than cash from

operations.

6. Sample DescriptionMeasurement

and

43

Varia hie

6.1. Data

The sample consists of firms listed on the New York Stock Exchange or the

American Stock Exchange. Three measurement intervals are examined: quarterly,

annual and four yearly. Firms are required to have accounting data available on either

the 1990 versions of the COMPUSTAT Merged Expanded Annual Industrial file, the

COMPUSTAT Merged Research Annual Industrial file, or the COMPUSTAT Quarterly

Industrial file. Firm observations are excluded if they do not have data to calculate

earnings-per-share, cash from operations per-share or net cash flows per-share. This

results in a sample of 26,793 firm-quarter observations, 30,489 firm-year observations

and 10,041 firm-four-year observations. The firms are also required to have monthly

returns available on the CRSP tapes. This reduces the sample of firms to 20,716 firm­

quarter observations from 1980 to 1989,28,647 firm-year observations from 1960 to

1989 and 5,454 firm-four-year (non-overlapping) observations from 1964 to 1989.

The sample excludes firm observations with the most extreme one percent of earnings-

44

per-share, cash from operations-per-share or net cash flows-per-share. 15 This reduces

the sample to 19,733 firm-quarter observations, 27,308 firm-year observations and

5,175 firm-four-year observations.

6.2. Variable Definitions

All financial statement variables used in the empirical tests are on a per-share

basis and scaled by beginning of period price. The variables are defined as follows:

E = earnings per-share (excluding extraordinary items and discontinued operations),

scaled by beginning of period price.

AWC = change in (non-cash) working capital per-share, scaled by beginning of period

price, where the change in (non-cash) working capital is defined as:

AWorking capital =AM +Mnv +AOthCA - AAP - ATP - AOthCL

where A is the change in each variable from period t-1 to t, AR is accounts

receivable, Inv is inventory, OthCA is other current assets, AP is accounts

payable, TP is tax payable and OthCL is other current liabilities. 16

15 Initial testsshowed thatoutliers wereoftenmorethanfiveor six standard deviations from the meanand in some cases unduly affected the regression results, The decision to exclude observations isconsistentwith previous research in this area. Collins and Kothari (1989) truncate their sample byexcluding observations where earnings changes are greaterthan 200 percent Bowen, Burgstahler andDaley (1987) also reportresults for a winsorized sample where extremeobservations are scaled to thesame value. The cut-off point is however, arbitrary; footnotes will report the main results for thesampleincluding outliers.

16 Other current assets includes items such as prepaid insurance and suppliesapart from inventory.Other current liabilities includes items such as dividends payable. deferred income tax payable andcontracts payable. As in Bowen, Burgstahler andDaley (1987) and Rayburn (1986), short-term accrualssuch as notes payable and the currentportion of long-term debt are excluded under the premise thattheserelatemore to financing activities than to operations.

45

CFO =cash from operations per-share, scaled by beginning of period price.

{Operating income before depreciation - interest - taxes - ~working caPital} IP

number of common shares outstanding t-l

NCF =the change in the balance of the cash account on a per-share basis, (net cash

flow per-share) scaled by beginning of period price.

LTA = Earnings - Cash from operations - AWorkingcapital

is long-term operating accruals per-share scaled by beginning of period price.

AA =Earnings - Net cash flows

is the net change in all non-cash accounts (aggregate accruals) on a per-share

basis scaled by beginning of period price.

Special items = COMPUSTAT item 32 on the quarterly tape and item 17 on the annual

tape. Special items include adjustments applicable to prior years, any

significant non recurring item, non recurring profit or loss on sale of assets,

investments etc., write-downs or write-offs of receivables, intangibles etc.,

. flood, fire, and other natural disaster losses.

Rit = CRSP buy-and-hold stock return (including dividends) for firm i over time

interval t, where t is the contemporaneous quarter, year or four-year period, less

the CRSP value-weighted market index (including dividends) over the

corresponding fiscal period.

6.3. Descriptive Statistics

Table 1 presents descriptive statistics on the variables used in the analysis.

Eamings-per-share scaled by price has a median value of 0.016, 0.090 and 0.383 for

46

the quarterly. annual and four-year intervals respectively. Annual earnings are greater

than four times the quarterly number. while the four-year earnings are greater than four

times the annual earnings. A similar pattern is observed for cash from operations and

net cash flows.I? Since the variables are scaled by beginning of period price. average

reported values will tend to increase over longer intervals due to the reinvestment of

earnings. A second difference between the quarterly and annual observations is the

shorter time period available for quarterly data. In table 1, net cash flows have a lower

mean than earnings. This is expected since a firm's financing and investment policies

affect net cash flows but not earnings. For example. when a firm pays dividends it

reduces retained earnings and cash but not reported earnings.

Table I indicates that over the quarterly interval. relative to earnings. both cash

from operations and net cash flows have more negative realizations. In addition. both

cash flow measures have higher standard deviations than earnings. Over longer

intervals. both the standard deviation and the proportion of negative realizations for the

cash flow measures decline relative to earnings. One explanation for this pattern is that

accruals off-set extreme negative and positive cash flow realizations associated with

mismatched cash receipts and disbursements over short measurement intervals.

Evidence that accruals and cash flows are negatively correlated would support this

explanation. This explanation is investigated in more detail in the next chapter.

17 Table 1 indicates that on average changes in working capital are positive. The components of thechange in working capitalwereinvestigated for the annual data. Of the total changein currentassets,47 percent is due to increases in accounts receivable and 48 percentis due to increases in inventory.For current liabilities, 47 percentof the change is due to accounts payable, and 10 percent is due toincreases in tax payable. Cbanges in current assetsare on average twice as large as changes in currentliabilities. Also note thatdespite changes in working capital beingpositive, cash from operations hasa larger mean and median than earnings. This is because long-term operating accruals, such asdepreciation, are largerin magnitude than changes in working capital and theirnet effecton earnings isnegative.

47

7. Analysis of Measurement Interval Predictions

Discussion of the results is divided into two chapters. This chapter provides

tests of hypotheses 1 and 2. Evidence of cash flows' time-series properties is also

presented that is consistent with cash flows suffering from mismatching problems.

Chapter 8 provides the results of the cross-sectional predictions on where accruals are

expected to be relatively more important in improving earnings' association with stock

returns.

7.1 .. The effect of short and long measurement intervals.

Hypothesis 1 predicts that earnings will have a stronger association with stock

returns relative to net cash flows or cash from operations over short measurement

intervals. Hypothesis 1 is examined by performing three pooled regressions: (1) stock

returns on earnings (2) stock returns on cash from operations and (3) stock returns on

net cash flows, then determining which measure has significantly more explanatory

power using Vuong's (1989) test. The regression performed is:

(7-1)

where (X) is either earnings (E), cash from operations (CFO) or net cash flows (NCF).

48

Table 2 presents the results of tests of hypothesis 1. For each measurement

interval, the R2 is larger in regressions including earnings relative to the regressions

including cash flows. The R2 for the quarterly observations is 3.24 percent for

earnings, 0.01 percent for cash from operations and 0.01 percent for net cash flows.

The R2s increase to 16.20 percent for earnings, 3.18 percent for cash from operations

and 2A7 percent for net cash flows over the annual interval. Over the four-year

interval the R2s increase further to 40.26 percent for earnings, 10.88 percent for cash

from operations and 6.12 percent for net cash flows.18 Over each measurement

interval, earnings are more strongly associated with stock returns than either cash flow

measure. These results support hypothesis 1. They are also consistent with Easton,

Harris and Ohlson (1992), who show that earnings' association with stock returns

improves over longer measurement intervals.

Hypothesis 2 predicts that as the measurement interval increases, cash flows

relative to earnings will capture a greater proportion of the variation in stock returns.

This occurs because over longer measurement intervals the mismatching problems with

cash flows are less acute and so accruals are relatively less important for improving

earnings' association with stock returns. Consider the following ratios:

Since the dependent variable is the same in both the cash flows and earnings

regressions these ratios measure the relative explanatory ability of earnings and cash

18 When the outliersare included in the regressions the coefficients and R2s decline in magnitude forboth earningsand cash flows, but the tenorof theresultsis unchanged. Regressions for the annualandfour-year interval werealsoperformed usingonly the1980to 1988period (equivalent to the period usedfor the quarterly interval). The tenorof the resultsis unchanged.

49

flows over different measurement intervals. A ratio less than one indicates that

earnings explain more of the variation in stock returns than cash flows. If these ratios

increase as the measurement interval is lengthened, then this is consistent with

hypothesis 2. Table 2 indicates that as the measurement interval increases from one

quarter to one year to four years, both the earnings and the cash flow measures have a

higher association with stock returns. This suggests that both earnings and cash flows

suffer less from timing and mismatching problems over longer measurement intervals.

However, in table 2 the ratio r~%Q) increases from 0.003 for quarterly, to 0.20 for

annual, to 0.27 for the four-year interval. A similar but smaller effect is observed for

net cash flows. This is consistent with cash flows relative to earnings, having more

ability to explain the variation in stock returns as the measurement interval is

lengthened.

The adjusted R2s reported in table 2 are consistent with the hypothesis that

earnings are more strongly associated with stock returns than cash flows. However,

simply comparing R2s does not provide statistically reliable evidence that earnings is

superior to cash flows. In order to formally discriminate between the two competing

specifications, they are evaluated as competing non-nested models. One of the

premises of the paper is that neither earnings nor cash flows are a perfect measure of

firm performance because both suffer to varying degrees from timing and mismatching

problems. As discussed in chapter 5, Vuong (1989) provides a likelihood ratio test for

model selection without presuming under the null that either model is 'true.' This

allows a directional test indicating which of the competing hypotheses, if either, is

closer to explaining the data. Intuitively, Vuong's tests allows us to determine which

model has relatively more explanatory power. An alternative test for non-nested model

selection is the J-test by Davidson and MacKinnon (1981). This test simplifies to

50

performing a multiple regression including both cash flows and earnings. However,

when both variables have incremental explanatory power (as is typically the case in the

tests performed here), the J-test lacks power and cannot distinguish between the

competing hypotheses. Intuitively, Vuong's test is a more powerful test than the J-test

because it can reject one hypothesis in favor of the alternative, in circumstances where

the J-test cannot.

Table 3 reports the results of Vuong's test of non-nested models. Over each

interval, earnings explain significantly more of the variation in market-adjusted stock

returns than either cash from operations or net cash flows. Since earnings explain

significantly more of the variation in stock returns than cash from operations, accruals

made to cash from operations to obtain earnings are relatively important for controlling

for the timing and mismatching problems inherent in cash from operations. Cash from

operations, however, does not explain significantly more of the variation in stock

returns than net cash flows over the quarterly interval, although the Z-statistic does

increase in significance over longer intervals. Since the difference between net cash

flows and cash from operations is the long-term investment and financing accruals,

these accruals seem relatively less important for reflecting firm performance. One

explanation for this result is that firms use their internally generated cash from

operations to finance their investment decisions so that the net cash inflow (outflow)

from these two sources is relatively small. Thus, the role of accruals in controlling for

these mismatching problems is relatively less important. Consistent with this

explanation cash from operations is found to have a strong negative correlation of

approximately -0.8 with cash from investment and financing.

51

7.2. Robustness tests

An alternative explanation of the results reported in table 2 is that cash flows

suffer more greatly from a random coefficients problem than earnings. If the

coefficient on cash flows varies across firm and a pooled regression is performed, then

the reported R2 will be understated. If the coefficient on cash flows varies much more

than the coefficient on earnings, then this could lead to an incorrect inference that cash

flows have a lower association than earnings with stock returns. To investigate this

issue, firm-specific regressions are performed on all firms that have more than 10

observations. The average adjusted R2 (in percent) from these regressions for the

quarterly interval for earnings is 5.43, for cash from operations is 0.84 and for net cash

flows is 0.86. For the annual interval, the average adjusted R2 for earnings is 21.87,

for cash from operations is 7.28 and for net cash flows is 4.19. This analysis was not

conducted over the four year interval because of the few time-series observations

available per firm. The results for firm-specific regressions are consistent with

hypothesis 1 and 2. Performing firm-specific regression improves the R2 for both cash

flows and earnings. Thus, the results reported in table 2 are not due solely to cash

flows suffering more greatly from a random coefficients problem.

A second concern is that the Vuong Z-statistic reported in table 3 are unduly

influenced by a few unusual years. To determine if this is the case, the Vuong test was

repeated over the annual interval for each of 23 years that had more than 100

observations (1967 - 1989). The results (not reported) indicate that in all 23 years,

earnings outperforms both cash flow measures, therefore the results are not driven by a

few unusual years. In addition, the Z-statistics are significant at the 0.01 level in 21 out

of 23 years when earnings are compared to cash from operations, and 20 out of 23

52

years when earnings are compared to net cash flows. However, when cash from

operations is compared to net cash flows, the Z-statistic is only positive in 12 of the 23

year and significant in four of the 23 years. Therefore, less reliability can be placed on

cash from operations relative to net cash flows being significantly more strongly

associated with stock returns.

A third potential concern with the tests in table 2 and 3 is that the cash flow

proxies are inappropriate. Prior to 1988, firms were not required to report cash from

operations but instead could report 'funds' under a variety of different formats. To

avoid problems with comparability across firms, one consistent definition is used for

cash from operations over the entire sample period. This approach has also been

adopted in existing research [e.g., see Rayburn (1986) and Bernard and Stober

(1989)]. However, since balance sheet data is used to obtain the changes in working

capital, this number will contain noise. The effect of the noise in this measure is

reduced by eliminating outliers, however the noise may still be of a large enough

magnitude that the observed association with stock returns is understated. The

consequence of this could be an incorrect conclusion that earnings has a higher

association with stock returns than cash from operations.

A fourth concern is that alternative cash flow measures may be more consistent

with firm performance. For example, theoretical models such as Fama and Miller

(1972, chapter 2) suggest that cash flows after investment expenditures may be the

variable of interest. In addition, it could also be argued that since earnings includes a

charge for the effect of investment decisions (depreciation), the appropriate cash flow

proxy should be one that includes cash outlays for investments. Alternatively, if

investment decisions are assumed to be exogenous, investors may be primarily

concerned with cash flows relating to the firms' financing decisions.

53

To provide some insights into the third and fourth concerns table 4 compares

the cash flow measures reported in table 2 to various alternative definitions of cash

flows. The alternative definitions of cash flows are obtained from The Financial

Accounting Standards Board's FAS 95, Statement of Cash Flows. FAS 95 requires

firms to separately report cash flows relating to operations, investments and financing

and therefore mitigates problems with obtaining cash flow proxies. FAS 95 also

requires replacement of the old funds statement with a new cash flow statement for

fiscal years ending after July 15, 1988. Some firms adopted the standard in 1987,

therefore data is obtained for all firms using the cash flow statement format. Table 4

provides seven different cash flow measures and compares each of them to earnings.

The seven measures are:

(i) cash from operations as required by FAS 95 (CF095)(ii) cash from operationas measured in table 2 (CFO)(iii) CF095 plus investments cash flows (CF095 + Inv CF)(iv) investmentcash flows (negative for investment outlays) (Inv CF)(v) financing cash flows (positive for financing inflows) (Fin CF)(vi) investment cash flows plus financing cash flows (Inv CF + Fin CF)(vii) net cash flows as measured in table 2 (NCF).

The results in table 4 indicate that earnings has a higher association with stock

returns than any of the cash flow measures. The R2 on earnings is 14.58 percent,

while the largest R2 for the cash flow variables is 5.20 percent (for CF095). The

Vuong Z-statistics comparing earnings to each cash flow measure are all significant at

the one percent level and indicate that earnings has significantly more explanatory

power than the cash flow measures.

The cash flow measure most comparable to earnings is (CF095+Inv CF)

because as with earnings, this measure includes charges for investment outlays.

However, in the production of earnings the investment charge is allocated as

'depreciation' over the life of the investment. The effect of this is to better match the

54

cost of the investment outlay with the revenue that it generates. The results indicate that

(CF095+Inv CF) has a zero association with stock returns. Combining cash from

operations with investment outlays produces a poor measure of firm performance. The

reason for this can be seen by noting that (Inv CF) has a negative association with stock

returns. When firms have negative investment cash flows (make investment outlays)

this is generally associated with positive expected future cash flows. Therefore,

allocating all of the negative investment cash flow to one period and not recognizing the

future benefit, produces a measure that suffers severely from mismatching problems.

The results in table 4 indicate that CF095 has an adjusted R2 of 5.20 percent

where as CFO has an adjusted R2 of 2.48 percent. The Vuong Z-statistic is 2.76

(significant at the 0.01 level, two-tailed test) indicating that the cash flow measure as

described by FAS 95 has significantly more explanatory power than CFO. This is

consistent with CFO being a noisier measure of cash from operations than CF095.

This noise could be the result of including certain accounting entries with no direct cash

flow consequences in CFO. For example, the book-keeping effects of divestiture or

mergers will be included in CFO but not CF095. Alternatively, the higher R2 for

CF095 could be due to a sample selection bias; early adopters of FAS 95 anticipated

that providing CF095 would be more informative than CFO.19 However, as noted

above, CF095 still has significantly less explanatory power than earnings. In

summary, the evidence in table 4 is consistent with hypothesis 1 and suggests that the

low explanatory power of cash flows is not due solely to the choice of cash flow

measures.

19 When 418 'early adopters' are excluded from the sample. there is no significant difference betweenthe explanatory power of CF095 and CFO. For the 418 'early adopters' the explanatory power ofCF095 is over seven percent while the explanatory power of CFO is less than one percent.

55

7.3. Mismatching problems with cash flows

7.3.1. Time-series properties

Tables 2 and 3 provide evidence consistent with cash flows being a relatively

poor measure of firm performance. The next set of tests examine whether cash flows

have time-series properties consistent with them suffering from mismatching problems.

If cash flows suffer from temporary mismatching of cash receipts and disbursements,

then this suggests that (i) changes in cash flows will exhibit negative autocorrelation,

i.e., a large cash outflow this period is more likely to be followed by a large cash

inflow next period. For example, in the ship building firm discussed in chapter 3, cash

flows are expected to be negative in the first period, when expenditures are outlaid and

positive in the next period when cash is collected. Therefore, changes in cash flows are

likely to contain temporary components that are reversed over time. If accruals are used

to match cash receipts and disbursements associated with the same economic event,

then this suggests that (ii) changes in accruals will also exhibit negative autocorrelation.

If accruals are used to match cash receipts and disbursements, then this suggests that

(iii) accruals will be negatively correlated with changes in cash flows. Finally, if

mismatching problems are less important over longer intervals, then (iv) cash flows and

accruals will have a smaller (in magnitude) negative correlation over longer intervals.

Evidence in support of these predictions is provided in table 5. Panel A of table

5 presents firm-specific first-order annual autocorrelations for each performance

measure: net cash flows, cash from operations and earnings. The results indicate that

changes in net cash flow per share exhibit average negative autocorrelations of -0.523.

Changes in operating cash flow per share exhibit slightly smaller (in magnitude)

average negative autocorrelations of -0.434, while changes in earnings-per-share has an

56

even smaller negative autocorrelation of -0.175.20 The change in each accrual measure

also exhibits negative autocorrelation. These result are consistent with predictions (i)

and (ii) above. They are consistent with cash flows containing larger temporary

components than earnings.

Turning to the third point discussed above. If accruals are used to smooth

temporary fluctuations in cash flows, then changes in cash flows and accruals will be

negatively correlated. In addition, if mismatching problems are more acute over short

measurement intervals, then the correlations will be more negative over short intervals.

The results for this test are reported in panel B of table 5. The results are consistent

with these predictions. The average correlation between changes in net cash flows and

aggregate accruals is -0.876 over the quarterly interval, -0.553 over the annual interval

and -0.407 over the four-year interval. Similar result are reported for correlations

between changes in cash from operations and changes in working capital. Table 5

panel B also reports the correlation between changes in cash from operations and

changes in earnings. Over longer intervals, as the temporary components in cash flows

'cancel each other out', changes in earnings and changes in cash from operations are

expected to have a higher positive correlation with each other. The results indicate that

the correlation increases from 0.059 for the quarterly interval, to 0.132 for the annual

interval, to 0.300 for the four-year interval.

The results presented in table 5 are consistent with the matching principle. They

are also consistent with the alternative view that management use accruals to 'smooth'

20 Both quarterly and the four year data exhibit a similar pattern to theannual data. Changes in cashflows and accruals exhibit negative autocorrelations, while earnings exhibit close to zeroautoeorrelations.

57

earnings regardless of whether this improves earnings' ability to measure firm

performance. However, the empirical results in tables 2 and 3 demonstrate that

accruals on average, improve the association of earnings with contemporaneous stock

returns. This suggests that earnings are not 'arbitrarily' smoothed but are smoothed in

a way that increases their ability to accurately reflect firm performance. The results in

table 5 also suggest that assuming all changes in cash flows and accruals are permanent

(a random walk model for expected cash flows and accruals) is not necessarily

appropriate [see for example, DeAngelo (1988), Rayburn (1986) and Pourciau (1992)].

This could be particularly important in studies attempting to determine if accrual

manipulation has occurred, since last period's accruals are unlikely to be the best

estimate of this period's accrual. Identifying the mean reverting component in cash

flows and accruals could also be important when modeling the unanticipated

components of each variable in market reaction studies.

7.3.2. Additional evidence consistent with mismatching problems

One extension of the tests performed in table 2 is to show that part of cash

flows' low association with stock returns is driven by its time-series properties, i.e.,

because cash flows have temporary components (or mismatching problems). If these

temporary components are 'canceled out' with past and future realizations of cash

flows, then by taking the time-series average of the cash flow variables or by including

additional realizations of cash flows in the regression with annual stock returns, a

higher association will be observed. Note that if the role of accruals is to reduce these

mismatching problems, then taking the average of earnings is not expected to result in

as much improvement as that observed for cash flows. The point of this section is not

to obtain the highest possible R2 for the cash flow regressions. The objective is to

show that by allowing the regression procedure to perform the role of accruals, (i.e.,

58

place weights in the current period, on past and future cash flows) an improved

association will be documented between cash flows and stock returns.

In table 6 the following regressions are performed:

(7-2)

(7-3)

(7-4)

where Rit is the adjusted stock return measured over the fiscal year for each firm, X is

either earnings, cash from operations or net cash flows on a per share basis scaled by

price at t-l. The regressions are performed every three years beginning in 1964. This

is done so that there are no overlapping observations, since including overlapping

observations can lead to overstated R2s. However, the results are similar even when

overlapping observations are included in the regressions. The analysis is limited to

three realizations ofeach variable in order to maintain a sufficiently large sample size.

The results in table 6 indicate that the average cash from operations variable has

a higher association with stock returns than the regression that only includes the current

realization. The R2 increases from 4.79 when only CFO t is included in the regression,

to 5.63 when the average of the three years is included in the regression. In addition,

when the coefficients on the past and future realizations are allowed to vary, the R2

increases to 6.73 percent. Similar results are documented for net cash flows. When

the average of three realizations are included in the regression, the R2 increases from

3.18 to 4.58 percent. These results are consistent with cash flows having temporary

components that 'cancel out' since the average cash flow variable is a better proxy of

future cash flows then the current realization. In contrast, when average earnings is

59

included in the regression instead of the current realization, the R2 declines. The R2 is

17.26 when E t is included in the regression, and 14.68 for average earnings.

However, as also shown by Collins, Kothari, Shanken and Sloan (1992), including

future realizations of earnings (separately) in the earnings regressions does improve the

R2. This is consistent with earnings exhibiting timing problems.

These results are consistent with accruals mitigating mismatching problems in

cash flows. When average cash flows are included in a regression with stock returns,

the R2 increases over that obtained for the current realization. This is consistent with

average cash flows exhibiting fewer mismatching problems and therefore being a less

noisy measure of firm performance than currently reported cash flows. This occurs

since the overall effect of averaging is to mitigate the (large) temporary components in

cash flows. In contrast, since earnings includes accruals and suffers to a lesser extent

from mismatching problems, the overall effect of taking the average is to reduce

earnings' association with stock returns.

60

8 . Analysis of Cross-sectional Predictions

This chapter provides cross-sectional tests of hypotheses 3 and 4. Section 8.1

analyzes the effect of aggregate accruals on the ability of earnings and cash flows to

measure firm performance. Results of tests concerning accrual components are then

presented. Finally, tests concerning the operating cycle are performed to determine if

this is an important economic determinant of where cash flows and earnings are likely

to differ in their ability to measure firm performance.

8.1 .The effect of the magnitude of aggregate accruals

The results in the previous chapter suggest that, relative to cash flows, earnings

are more strongly associated with stock returns over short measurement intervals.

These results are consistent with the predictions of hypotheses 1 and 2. Hypothesis 3

predicts that in firms with more volatile investment, financing and operating activities,

net cash flows will be a relatively poor measure of firm performance. In these

circumstances, cash flows suffer to a greater extent from timing and mismatching

problems. Since accruals attempt to control for these problems, cash flows are

expected to have a relatively low association with stock returns when accruals are large

in magnitude.

61

Table 7 provides results of a test to determine whether the ability of net cash

flows to reflect firm performance declines as the absolute value of aggregate accruals

[abs(AA)] increases. In this test, all firm-period observations are ranked on the basis

of abs(AA), quintiles are then formed and separate regressions of stock returns on

earnings and stock returns on net cash flows are performed for each quintile. Quintile I

contains firm-observations for which the magnitude of abs(AA) is small, while quintile

5 contains firm-observations for which the magnitude of abs(AA) is large. For firms

that are in 'steady state', where abs(AA) is small, earnings and cash flows are expected

to have a similar association with stock returns (a similar R2). However in quintile 5,

where abs(AA) is large, indicating more timing and mismatching problems with cash

flows, cash flows relative to earnings are predicted to have a lower association with

stock returns. Since accruals are expected to be relatively more important over short

time intervals, the decline in R2 is expected to be greatest over the quarterly and annual

intervals. Cash flows are also more likely to suffer from errors in variables in quintile

5 relative to quintile 1. If excluding abs(AA) is an important source of measurement

error in the cash flow regressions, then the coefficient on net cash flows will decline

across quintiles (see Appendix 2).

The empirical implications of hypothesis 3 are supported in table 7. Over the

quarterly interval, in quintile 1, where abs(AA) is small and earnings and cash flows

are most similar, cash flows are expected to suffer from fewer mismatching problems.

In this quintile, the R2 on cash flows is 3.44 and the R2 on earnings is 3.55.

However, when abs(AA) is large (quintile 5), net cash flows has an R2 of 0.15 percent

while earnings has an R2 of 4.96 percent. Thus when earnings and cash flows differ

by the greatest magnitude, earnings has a higher association with stock returns than

cash flows. The same finding is observed over the annual and four-year interval.

62

When abs(AA) is large in magnitude, indicating greater timing and mismatching

problems with cash flows, earnings relative to cash flows, has a higher association

with stock returns. Moving from quintile 1 down to quintile 5, the R2 on quarterly

cash flows declines monotonically from 3.55 to 0.15 percent. A close to monotonic

decline is observable for cash flows over the annual and four-year intervals. In

contrast, earnings shows no obvious decline across quintiles. This is consistent with

cash flows suffering from more timing and mismatching problems as accruals increase

in absolute magnitude.

The coefficient on cash flows also declines in size across quintiles over each

measurement interval. For the quarterly interval the coefficient on cash flows is 1.60 in

quintile 1 and an insignificant -0.08 in quintile 5. This is consistent with cash flows

being a 'noisier' measure of firm performance in quintile 5 relative to quintile 1 because

it suffers more greatly from timing and mismatching problems. If accruals mitigate but

do not eliminate these mismatching problems in cash flows, then a similar (but smaller)

decline will be observable for earnings. However, although the coefficient on quarterly

earnings declines from 1.69 in quintile 1 to 0.60 in quintile 5, the R2 on earnings does

not decline. This result suggests that the decline in the coefficient on cash flows and

earnings is not due solely to 'noise' but inter-portfolio variation in underlying

determinants of the coefficients. This issue is investigated in the next section.

Table 7 also reports the Z-statistic and probability from the Vuong test for each

quintile. The results indicate that as expected, in quintile 1, earnings does not explain

significantly more of the variation in stock returns than cash flows. However, in

quintile 5, where abs(AA) is large in magnitude, the Z-statistic is significant. This

suggests that earnings explain more of the variation in stock returns than cash flows in

63

quintile 5. This is consistent with accruals mitigating mismatching problems in cash

flows so that earnings is a more timely measure of firm performance.

The results of the tests presented in table 7 support hypothesis 3. The results

identify the conditions under which cash flows are less effective in measuring firm

performance. They demonstrate that cash flows are not a poor measure of firm

performance per se. In 'steady state' firms where the magnitude of accruals is small

and cash flows and earnings are most similar, cash flows are a relatively 'accurate'

measure of firm performance (have similar R2s to that of earnings over each interval as

reported in table 2). However, when the magnitude of accruals is large, cash flows'

association with stock returns declines and earnings are significantly more strongly

associated with stock returns. In other words, the results indicate that accruals increase

the ability of earnings to reflect performance on a timely basis. Overall, the results are

consistent with the hypothesis that accountants accrue revenues and match expenditures

to revenues so as to produce a performance measure (earnings) that better reflects firm

performance than realized cash flows. This suggests that management manipulation of

accruals is a second-order effect and the first-order effect of the accrual process is to

produce a more timely measure of firm performance.

8.2. Analysis of the decline in the coefficient on earnings

across quintiles

The results in the previous section indicate that the coefficients and R2s on cash

flows decline across quintiles formed on the absolute value of aggregate accruals

[abs(AA)]. One reason for this is that as the abs(AA) increases, cash flows suffer more

greatly from timing and mismatching problems and are a 'noisy' measure of firm

performance. The effect of this noise is to bias down the coefficient and R2 on cash

64

flows (see appendix 2). However, the results in table 7 indicate that although there is

no observed decline in the R2s on earnings, there is a decline in the coefficient (the

earnings response coefficient) across quintiles. If the decline in the earnings response

coefficient is due to noise, then both the coefficient and the R2 are expected to decline

across quintiles. This suggests that the decline in the earnings response coefficient is

due to inter-portfolio variation in the 'true' value of the coefficient Existing literature

has identified a number of determinants of cross-sectional variation in 'true' earnings

response coefficients [see Kormendi and Lipe (1985), Collins and Kothari (1986) and

Easton and Zmijewski (1986)]. This section demonstrates that the decline in the

earnings response coefficient can be explained by these determinants.

Existing research investigating earnings response coefficients predicts that,

ceteris paribus, the earnings response coefficient is inversely related to the expected

return on a security [see Kormendi and Lipe (1985), Collins and Kothari (1986) and

Easton and Zmijewski (1986)]. Earnings response coefficients are also expected to be

greater for firms with growth opportunities, since a given shock in earnings is expect to

be magnified in future earnings [see Collins and Kothari (1986)].21

The following proxies for risk and growth opportunities are investigated to

determine if they vary systematically across quintiles formed on the absolute value of

aggregate accruals [abs(AA)]:

21 Konnendi and Lipe (1985) and Collins and Kothari (1986) hypothesize that earnings responsecoefficient will vary based on the persistence of earnings. However. if earnings have more temporarycomponents (a given change does not persist) then this is expected to affect both the R2 and theearnings response coefficient. Therefore persistence is unlikely to explain the observed decline inearnings response coefficients across quintiles. Consistent with this prediction, temporary componentsin earnings (as measured by fum-specific autocorrelation coefficients, see section 7.3) did not varysignificantly across quinliles.

65

Risk (i)

(ii)

(iii)

(iv)

Growth (v)opportunities

(vi)

(vii)

EJP = earning per share from t-2 to t-I scaled by price at t-1.

Leverage =assets at t-I scaled by book value of equity at t-1.

Mkt/Book =market value of equity scaled by book value ofequity both measured at t-I.

Size = market value of equity at t-1.

R&DIAssets =research and development expenditures scaled byassets at t-1.

Capital explDepr = capital expenditures scaled by depreciationexpense.

Net/Gross = the net book value of fixed assets scaled by thegross book value of fixed assets.

Variables (i) to (iv) are proxies for the risk attributes of firms. Firms with high

EJP ratios or high leverage are expected to have higher expected returns [see Beaver and

Morse (1978) and Kothari (1988)]. Fama and French (1992) also suggests that firm

size and market to book ratios are inversely related to firms' expected returns.

Variables (v) to (vii) are proxies for growth opportunities. Firms that spend a relatively

large proportion of their assets on R&D are often assumed to have a greater proportion

of their value in growth opportunities [see Smith and Watts (1992)]. Firms with

growth opportunities are likely to outlay more on capital expenditure relative to their

depreciation. They are also likely to be relatively 'young' firms (have newer assets).

Table 8 reports mean and median values for each of these variables across

quintiles. Medians are reported since they are less sensitive to the effects of outliers.

Consistent with inter-portfolio variation in risk. firms in quintile 5 relative to other

quintiles, have higher FJP ratios. are more highly levered. have lower market to book

values and are smaller in size. Results from difference in means tests (not reported)

indicate that quintile 5 differs significantly from quintile 1 and all other quintiles based

on these four variables. This is consistent with the decline in the earnings response

66

coefficients across quintiles being due to risk differences. There is also evidence in

table 8 consistent with growth opportunities varying in a systematic manner across

quintiles. Median R&D scaled by assets is 0.026 in quintile 1 and declines

monotonically to 0.015 in quintile 5. However, there is less variation across quintiles

in Capital explDepr or Net/Gross.

The results in table 8 can also be used to reconcile why the earnings response

coefficients decline across quintiles but the R2 on earnings increase in quintile 5. If the

release of financial statements is a relatively more important source of information for

firm-observations in quintile 5, then the explanatory power of earnings is expected to

be greater. Table 8 reveals that the mean and median firm size in quintile 5 is lower

than for other quintiles. This is consistent with the predictions of Atiase (1985) and the

empirical results of Collins, Kothari and Rayburn (1986). Earnings explains a

relatively greater proportion of the variation in stock returns for small firms since there

are fewer competing sources of information.

. In summary, the results in table 7 are inconsistent with the decline in the

earnings response coefficients across quintiles being due to 'noise' because there is no

observable decline in the R2 on earnings. This section presents evidence to explain the

observed decline in the earnings response coefficients. The results in table 8 indicate

that cross-sectional determinants of earnings response coefficients vary systematically

across quintiles formed on the absolute magnitude of accruals.22

22 A regression was also performed to determine if abs(6AA) still explained earnings responsecoefficients after controlIing for variables (i) to (vii), To obtain the observations for the regression,fum-specific earnings response coefficients are determined for 926 flrms that had between 10 and 27annual observations; then the time-series average value of variables (i) to (vii) and abs(6AA) isobtained for each fum. Thesevariables are then included in a multiple regression where the earningsresponse coefficient is the dependent variable. The resultsof the regression indicate that even aftercontrolIing for variables (i) to (vii), abs(6AA) still has explanatory power. It should be noted

67

8.3. Evaluation of accrual components

This section provides the empirical results concerning accrual components. The

analysis is divided into three sections. The first section presents the results for working

capital accruals. These accruals are predicted to be relatively important for mitigating

the timing and mismatching problems in cash flows. The second section provides

additional support for this prediction by showing that cash flows' ability to reflect firm

performance does not vary systematically with the magnitude of long-term operating

accruals. Finally, a specific accruals is identified that in contrast to previous results

actually reduces earnings' association with stock returns.

8.3.1. The effect oJ changes in working capital

The previous results suggest that on average, aggregate accruals as a group,

improve the ability of earnings to reflect firm performance. Table 9 examines a subset

of accruals, specifically, short-term working capital accruals. A comparison is made

between earnings and cash from operations since both measures include the effects of

long-term investment and financing accruals. Working capital accruals are expected to

reverse within one year and hence these accruals are predicted to directly mitigate

temporary fluctuations in firms' cash from operations. If working capital accruals

mitigate temporary mismatching problems in operating cash flows, then firms with

more volatile working capital requirements are expected to have a relatively low

association between stock returns and cash from operations.

however, that the results from this regression are notdirectly comparable to the resultsreported in table7 sincein that table quintiles are formed based on pooled observations.

68

Table 9 presents results of quintile regressions where observations are ranked

based on the absolute value of the change in working capital [abs(~WC)]. For each

measurement intervals, the R2s on cash from operations are more similar in magnitude

to those of earnings in quintile 1. However, as abs(~WC) increases in magnitude, the

R2 on cash from operations declines and in quintile 5, is close to zero. For example,

the R2 on quarterly cash flows is 1.98 in quintile 1 and declines to 0.16 in quintile 5.

This contrasts with the results for earnings for each interval. The R2s in quintile 5 are

of a similar magnitude to those reported in quintile 1. For example, the R2 on quarterly

earnings is 2.81 in quintile 1 and increases to 3.71 in quintile 5. As in table 7, the

coefficients on cash from operations and earnings decline across quintiles, suggesting

that not all of the decline in the coefficient on cash from operations can be attributed to

the exclusion of working capital accruals. The results of the Vuong test indicate that

over the quarterly interval, the Z-statistic is insignificant in quintile 1 and significant in

quintile 5. This is consistent with working capital accruals being relatively important

over short time intervals. Over the annual and four-year interval the Z-statistic is

significant and positive for all quintiles, with the Z-statistic being largest in magnitude

in quintile 5.23

The results in table 9 provide support for hypothesis 4(a). They are consistent

with working capital accruals mitigating the timing and mismatching problems in cash

flows. Thus, working capital accruals play an important role in improving earnings'

ability to measure firm performance.

23 When outliers are included similar results are report in tables 7 and 9 in that the R2on cash flowsis always lowest in quintile 5 relative to quintile I. Table9 wasalso replicated using annualcash fromoperations as reported in FAS 95. The R2 on CF095 declined across quintiles, being smallest inmagnitude in quintile 5. However, the decline is not perfectly monotonic since quintile4 exhibited ahigherR2 than quintile 1.

69

8.3.2. The effect of long-term operating accruals

This section focuses on the effect of long-term operating accruals on the

association between cash from operations and stock returns. In the previous section it

was hypothesized that working capital accruals are made specifically to reduce timing

and mismatching problems with realized cash flows. Long-term operating accruals by

defmition, take several years to reverse. They are included in earnings primarily so that

in the long run, cash-in minus cash-out will be equal to earnings, e.g., depreciation,

gains on sales. They are not expected to be as important for mitigating mismatching

problems in currently realized operating cash flows. Thus, cash from operations'

association with stock returns is not expected to be a declining function of the

magnitude of these long-term operating accruals.

Table 10 presents results of quintile regressions where observations are ranked

based on the absolute value of the long-term operating accruals [abs(LTA)]. Quintile 1

contains observations where abs(LTA) is small in magnitude, while quintile 5 contains

observations where abs(LTA) is large. There are three things worth noting in this

table. First, for each measurement intervals, the R2s on cash from operations are no

longer most similar in magnitude to those of earnings in quintile 1. Second, the R2 on

cash from operations are not a declining function of [abs(LTA)]. For example, over the

annual interval the R2 on cash from operation is 2.24 percent in quintile 1 and increases

to 4.00 percent in quintile 5. Third, over each interval, the R2 on cash from operations

observed for each quintile is of a similar magnitude to that observed in the pooled

regressions reported in table 2 (approximately zero over the quarterly interval, three

percent over the annual interval and ten percent over the four-year interval). Therefore,

any variation across quintiles seems random. This contrasts with the working capital

70

results reported in table 9. In that table over each interval, quintiles 1 to 4 have R2s on

cash from operations that are larger in magnitude than those reported for the pooled

regressions in table 2. The evidence is consistent with long-term operating accruals

being less important for mitigating timing and mismatching problems in cash from

operations. Thus, the results are consistent with working capital accruals playing an

important role (and long-term operating accruals playing a less important role) in

improving earnings' ability to measure firm performance.P

8.3.3. The effect of special items

The section tests hypothesis 4(b) that predicts that special items are an accrual

adjustment that will not improve earnings' ability to reflect finn performance over short

measurement intervals. Results of several empirical studies suggest that special items

or subsets of special items are less useful for measuring current performance. For

example, Jones and Bublitz (1991) find that there is a greater frequency of surprise

write-offs found in the fourth quarter and there is a smaller market reaction to

unexpected earnings in that quarter. Dechow, Huson and Sloan (1992) find that a

subset of special items (those relating to restructuring charges) are filtered out of

management compensation. Finally, DeAngelo, DeAngelo and Skinner (1992) find

that by excluding such items from earnings, they are able to obtain a better model of

expected future earnings and dividends.

24 Tests comparing net cash flows to cash from operations as long-term investment and financingaccruals increase in magnitude were also performed. The difference in R2s acrossquintiles werenotsignificant, therefore consistent with the findings in table 3, these long-term accruals seemrelativelylessimportant for improving theability of earnings tomeasure fum performance.

71

Table 11 contains results for two separate samples. The first sample consists of

firm-observations reporting a special item. the second sample consists of firm­

observations where no special items are reported.25 Earnings before tax are reported

in the table so that both special items and earnings are measured on a consistent basis.

Hypothesis 4(b) predicts that if special items are included in earnings primarily to

reduce management discretion. then over short measurement intervals their inclusion in

earnings will reduce earnings' association with stock returns. Over longer intervals.

such adjustments are likely to be less important since the choice of depreciating an asset

versus a one time write-off will have zero impact on total net income (if clean surplus

holds).

The results in table 11 indicate that over the quarterly interval. the R2 on

earnings is lower than the R2 on earnings before special items. Similar results are

found for the annual interval. This is consistent with special items reducing the ability

of earnings to measure firm performance over short time intervals. The Z-statistics

from the Vuong test are significant in favor of earnings before special items at the three

percent level for the quarterly interval and at the one percent level for the annual

interval. In addition. when special items are included as a separate explanatory variable

in regressions including earnings before special items. the coefficient on special items is

insignificant over both the quarterly and annual intervals (not reported). Over the

longer four year interval however. there is no significant difference between earnings

and earnings before special items.

25 The second sample is provided for comparative purposes because results are reported withoutremoving the extreme one percent of observations. Special items usually result in unusual earningsnumbers so that many of the observations for the 'with special items sample' are from the extremepercentiles.

72

These results are consistent with special items reducing the ability of earnings to

measure firm performance over short measurement intervals. The results also indicate

that over the annual and four-year interval, the sample of firms with special items

generally has a lower association between stock returns and earnings (before special

items) than the sample of firms with no special items. One explanation for this is that

firms with special items are undergoing significant changes in their operating,

investment and financing activities and therefore the earnings number is a poorer

predictor of these firms' expected future cash flows.

To summarize, the results presented for components are consistent with the

predictions. Working capital accruals are shown to be relatively important for

improving earnings' ability to measure firm performance, while long-term operating

accruals are shown to be relatively less important. This is consistent with short-term

working capital accruals mitigating the mismatching problems inherent in cash flows.

The results for special items suggest that not all accruals are included in earnings with

this objective in mind. Special items do not improve earnings' ability to measure firm

performance over short measurement intervals. This is because special items do not

mitigate mismatching problems in realized cash flow but instead reflect the cumulative

effect of past under or overstatement of accruals.

8.4. The effect of the operating cycle

The results in the previous section indicate that cash flows have a lower

association with stock returns in firms experiencing large changes in their working

capital requirements. This section identifies an underlying economic determinant that

influences the variability of firms' working capital requirements. Hypothesis 5 predicts

that if the variability of working capital is associated with the length of a firm's

73

operating cycle, then cash flows will have a weaker association with stock returns in

firms with long operating cycles.

To investigate the association between firms' working capital requirements and

the length of the operating cycle, two proxies for the length of the operating cycle are

calculated for the annual interval [see Bernstein (1990), p. 104]:

. I (ARt + ARt_l)/2) ( (Invt + Invt_l)12 )operating cyc e = Sales/360 + Cost of goods sold/360

d I _(ARt + ARt_ d/2 ) ( (Invt + Invt.l)12 ) (APt + APt-l)/2 )tra e cyc e - Sales/360 + Cost of goods sold/360 - Purchases/360 .

Where AR is accounts receivable, Inv is inventory and AP is accounts payable. The

first component measures the number of days' sales in accounts receivable. The

second component measures the number of days it takes to produce and sell the

product. The third component of the trade cycle is the number of days credit obtained

from suppliers.w

Panel A of table 12 provides descriptive statistics on firms' operating and trade

cycles. A minimum of 10 observations per finn is required to calculate each firm's

operating and trade cycle. This results in a sample of 1,252 firms with 20,115 annual

observations. It takes the average (median) firm in the sample 146 (138) days from

taking delivery of inventory to produce a product, to sell the product and receive the

cash from the trade receivable. The average (median) trade cycle is 108 (101) days.

Measures of the operating and trade cycle are sensitive to outliers. To reduce the effect

of outliers the data is aggregated by industry. The aggregated industry operating (trade)

26 Purchases are calculated as ending inventory pluscostof goodsoldless beginning inventory. Noadjustment is madefor depreciation in costof goodsoldsinceCOMPUSTATdoesnot recordthisas aseparate item.

74

cycle is obtained by: (i) estimating firm-specific operating (trade) cycles and (ii)

averaging the operating (trade) cycles for the firms in each industry. The minimum

industry operating cycle is 28 days (Eating and Drinking Places) and the maximum is

277 (Real estate).27

Panel B of table 12 analyzes firm-level correlations between the length of the

operating (trade) cycle and the variability of the change in working capital. The results

suggest that firms with longer operating and trade cycles also tend to have more volatile

working capital requirements. The results in panel C indicate that by aggregating the

data by industry, a stronger association is obtained between the length of the operating

(trade) cycle and the variability of working capital requirements. Thus, in industries

where the operating or trade cycle is long, working capital requirements also tend to be

more volatile. This is consistent with the length of the operating cycle being an

economic determinant of the volatility of working capital requirements.

The results in panel B and C of table 12 suggest that cash flows' association

with stock returns will vary in cross-section with the length of the operating (trade)

cycle. To investigate the effect of the operating (trade) cycle on cash from operations'

and earnings' association with stock returns, the following procedure is performed (i)

all firms with an estimated operating (trade) cycle are categorized by two digit SIC

code, (ii) separate regressions of returns on earnings and returns on cash from

operations are performed for each industry and (iii) Pearson correlations are obtained

between the length of the operating (trade) cycle for the industry and the size of the R2

27 A trade-off between obtaining more firms per industry and a more accurate measure of averageoperating cycles perfum resulted in thechoice of tenobservations perfum. The tenor of theresults isunchanged when thenumber of observations perfum range from eightto 20.

75

for earnings and cash flows from these industry-specific regressions.

Table 13 reports Pearson correlations between the length of the average

operating (trade) cycle for the industry and the R2 from regressions of stock returns on

cash from operations performed for each industry. A negative correlation indicates that

industries with long operating cycles tend to have weaker associations between stock

returns and cash from operations. The results indicate a significant negative correlation

of -0.483 between the R2 from the cash flow regressions and the length of the

operating cycle. Similar results are found for the trade cycle. Earnings also exhibit

negative correlations, however they are not significant. This suggests that accruals play

a relatively more important role in firms with long operating cycles.28 The evidence in

table 13 supports hypothesis 5. The results are consistent with the length of the

operating cycle being an important economic determinant of the size of the change in

firms' working capital requirements and hence the ability of cash flows to measure finn

performance. The results also suggest that accruals mitigate this problem in earnings.

Earnings therefore reflect finn performance on a more timely basis than cash flows, for

firms in industries with long operating cycles.29

28 The volatility of firms' (industry) operating and trade cycle was also investigated since firms thathave large changes in the length of their operating cycle may also have large changes in their workingcapital requirements. However the relation is weak, the correlation between the volatility of theoperating cycle with the R2 from regressions ofretums on cash flows is -0.040 (probability=0.15) on afirm basis and -0.230 (probability=0.08) on an industry basis. While the correlation between thevolatility of the trade cycle with the R2 from regressions of returns on cash flows is -0.028(probability=0.33) on a firm basis and -0.144 (probability=0.28) on an industry basis. Thus, thevolatility of the operating and trade cycle does not explain cross-sectional variation in cash flows'.asscciation with stock return.

29 The analysis was also conducted on a firm basis for 1,252 firms that had at least 10 observations.The correlation for cash from operations between the firm-specific R2s and the operating cycle is-0.109 (probability=O.OOO) and the trade cycle -0.084 (probability=0.OO2). For earnings, the correlationbetween the R2s and the operating cycle is 0.049 (probability=0.078) and the trade cycle 0.080(probability=0.OO5).

76

9 • Summary and Conclusions

This study hypothesizes that the role of accounting accruals is to provide a

measure of short-term performance that more closely reflects expected future cash

flows than realized cash flows. The results support this prediction. First, earnings,

relative to cash flows, are more strongly associated with stock returns over short

intervals. In addition, the ability of cash flows to measure firm performance improves

relative to earnings as the measurement interval is lengthened. Second, earnings,

relative to cash flows, have a higher association with stock returns in firms

experiencing large changes in their working capital requirements and their investment

and financing activities. Under these conditions, cash flows suffer more greatly from

timing and mismatching problems and are less able to reflect finn performance.

This study also predicts that although accruals on average, improve earnings

association with stock returns, certain accruals are less likely to mitigate mismatching

problems in cash flows. Evidence is presented that indicates that long-term operating

accruals playa less important role in this respect. In addition, the inclusion of special

items in earnings is shown to reduce earnings' association with stock returns over short

intervals. However, this does not imply that special items should be excluded from

77

earnings from continuing operations. It may be important to include special items in

earnings so that management is accountable for such charges.

The contribution made by this study is to document the benefits of accrual

accounting and to provide an explanation for its prevalence. In particular, the study

helps explain why earnings are more often reported and used in contracts than cash

from operations or net cash flows. The approach taken here differs from that typically

adopted in previous research. This study assumes that cash flows are a more

'primitive' performance measure than earnings and the value added by accountants is in

accruing cash receipts and disbursements so as to attain a more useful measure of firm

performance over short measurement intervals. Therefore, the set of existing accruals

are expected, on average, to improve earnings' ability to measure firm performance.

The results demonstrate that isolating the conditions under which earnings and cash

flows are expected to differ by the greatest magnitude provides more powerful tests of

the usefulness of accounting accruals. Overall, the evidence suggests that accruals play

an important role in improving the ability of earnings to reflect firm performance on a

timely basis.

Finally, the study also provides new insights into two branches of existing

research. First, recent research has documented inter-industry variation in the

association between cash flows and stock returns [e.g. Biddle and Seow (1990)]. This

study identifies an underlying determinant of this variation. Specifically, the strength

of the association between cash flows and stock returns is shown to be negatively

related to the length of the operating cycle at the industry level. Second, this study

contributes to the long window analysis performed by Easton, Harris and Ohlson

(1992). They show that the association between earnings and stock returns improves

over longer measurement intervals. This result is consistent with earnings' suffering

78

from timing and mismatching problems over short measurement intervals. The

evidence in this study indicates that cash flows suffer more greatly than earnings in this

respect and that accruals help to mitigate these problems.

79

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90

Appendix 1.

The Relation Between Cash Flows and Earnings

This appendix provides a conceptual description of the changes in cash in terms

of all other (non-cash) accounts recorded on firms' balance sheets. It indicates the

types of accruals that are made to obtain cash from operations and earnings. The

relation between cash flows and earnings is discussed in most accounting texts books,

see for example, Stickney, Weil and Davidson [(1990), pp. 172-201] and Pratt

[(1990), pp. 747-749].

The basic accounting equation can be stated as (assets = liabilities +

stockholders' equity).

A=L+SE (A-I)

Total assets can be divided into cash (CASH) and non-cash assets (NA), and

shareholders' equity into contributed capital (CC) and retained earnings (RE).

CASH + NA = L + CC + RE (A-2)

Liabilities (L) can be separated into current liabilities (CL) and long-term

liabilities (LTL) while non-cash assets can be divided into current non-cash assets

(CNA) and long-term non-cash assets (LTNA)

CASH + CNA + LTNA = CL + LTL + CC + RE. (A-3)

Rearranging the above equation gives

CASH=CL+LTL+CC+RE -CNA-LTNA. (A-4)

91

Since the balance sheet equation holds at every point in time, it must also hold

between points in time. Therefore, the change in the cash balance can be expressed as:

ACASH =ACL + ALTL + ACC + ARE - ACNA - ALTNA. (A-5)

The change in retained earnings is equal to revenues (R) less expenses (EX),

less dividends (D), while the change in long-term liabilities can be separated into those

affecting cash (ALTLc) and those not affecting cash (ALTLnC). Similarly, the change in

long-term assets can be separated into those affecting cash (ALTNAc) and those not

affecting cash (ALTNAnc). Substituting and rearranging, the change in the cash

balance [net cash flows (NCF)] can be expressed in terms of changes in non-cash

accounts.

NCF =R - EX + ~CL - ~CNA + M;rLnc - ~TNAnc - ~TNAc + ~TI..c + ~CC - D

1 I' IEarnings Changes in

workingcapital

Changes innoncurrent accounts(e.g. depreciation,gains andlosses andspecial items)

I IPurchasesaxlretirementsoflong­term assets

1-----Long-termborrowings andrepayments, stockissuances andrepurchases anddividends

Cash from operations Cash from invesunent andfmancing activities

(A-6)

Thus, the difference between earnings and net cash flows is equal to the net

change in the balance of all non-cash accounts (AA). This is termed 'aggregate

accruals' in this study.

From the above equation, cash from operations (CFO) is equal to:

CFO =R - EX +ACL - ACNA +ALTLnc - ALTNAnc (A-7)

92

and the difference between earnings (E) and cash from operations each period is:

E - CFO = IJ.WC - !J.L'fLoc + !J.LTNAnc.

or,

E - CFO = IJ.WC + LTA.

(A-8)

(A-9)

This difference is equal to the change in working capital accruals (IJ.WC =

ACNA - IJ.CL) as well as long-term operating accruals (LTA =!J.LTNAnc - ALTLnd.

Long-term operating accruals include depreciation, amortization, gains and losses on

debt retirement. gains and losses on long-term assets retirements and other adjustments

generally classified as special items by the firm.

93

Appendix 2.

The Effect of Measurement Error on the Coefficient on

Earnings and Cash Flows

The role of earnings is to provide a measure of firm performance over a given

measurement interval. However, due to problems with information asymmetries

between management and other contracting parties, earnings are also required to be

objective and verifiable. As a result, earnings reflect realized and reasonably certain

cash flows related to the firm's activities during the measurement interval. The

implications of uncertain future cash flows for the period's performance are not

reflected in earnings. This can be viewed as earnings imperfectly measuring firm

performance. Therefore, we can describe earnings for a given firm i in period t as:

(A-lO)

where x is the expected net cash flows associated with the period's activities. Cash

flows can be viewed as a more 'noisy' signal of firm performance than earnings since

accruals are hypothesized to help reflect the cash flow implications of the finn's current

operating activities (by reducing timing and mismatching problems). Cash flows can

be defined as:

(A-ll)

where n is the effect of excluding the information in accruals. Assume initially that

cov(x,u) =0 and cov(x,n) =0.

Therefore in a regression of stock returns on earnings per-share scaled by price:

94

since u is assumed not to be value relevantcov(R,u)=0

then:

where Wit =eit + Uit - bUit·

This is a classical errors in variables problem since cov(w,E);t: 0

cov(w,E) = -bou2

(A-12)

(A-13)

d li cov(Rx)an p irn bRE = var(x) + var(u)

and similarly, the R2 on cash flows, RRC2

and for cash flows per-sharescaled by price:

plim bRC = B1 + ( au 2 + an2 + 2aun)/ax2

Where O'un is the covariance betweenUand n , which is initially assumed to be equal to

zero.

Therefore ~ > bRE > bRC.

The R2 will also decline becauseof the noise terms. The R2for earnings will be:

R 2 _ bRE2 var(x)RE - var(R)

bRC2 var(x)var(R)

95

If quintiles are formed on the basis of the magnitude of the change in net

accruals, then the coefficient on cash flows will decline across quintiles. This will

occur since on2 is expected to be larger where the change in accruals is large, and

smaller where the change in accruals is small. Now, when cov(u,n) =0, earnings

relation with stock returns will not vary with the magnitude of the change in net

accruals. However, if cov(u,n) > 0, firms that have large changes in accruals also have

more uncertainty associated with their expected future cash flows (or more 'noisy'

earnings), then the coefficient on earnings will also decline as n (the magnitude of the

change in accruals) increases, but less so than for the coefficient on cash flows.

96

Table 1

Descriptive statistics of data for the quarterly, annual and four-year intervals.

mean standard median upper lower percentdeviation quartile quartile negative

Quarterly (observations = 19,733)

Earnings(E)8 0.009 0.044 0.016 0.258 0.006 17.61Change in

0.033 -0.023 44.93workingcapital (AWC) 0.003 0.097 0.004Cash fromoperations (CFO)8 0.025 0.098 0.023 0.059 -0.009 30.32Net cash flows (NCF)8 0.000 0.058 0.000 0.017 -0.017 50.29Stock returns'' -0.007 0.160 -0.020 0.079 -0.111 55.60

Annual (observations =27,308)

Earnings(E)8 0.086 0.134 0.090 0.147 0.046 11.40Change inworkingcapital (AWC) 0.026 0.203 0.023 0.094 -0.030 36.84Cash fromoperations(CFO)8 0.138 0.234 0.107 0.222 0.025 19.13Net cash flows (NCF)8 0.016 0.110 0.004 0.044 -0.024 44.75Stock returns" 0.027 0.431 -0.030 0.213 -0.238 53.63

Four YearC (observations =5,175)

Earnings(E)8 0.405 0.453 0.383 0.638 0.175 11.90Change inworkingcapital (AWC) 0.145 0.451 0.086 0.267 -0.022 29.41Cash fromoperations(CFO)8 0.555 0.589 0.464 0.834 0.195 10.76Net cash flows (NCF)8 0.059 0.191 0.018 '0.098 -0.025 38.07Stock returns'' 0.172 1.203 -0.099 0.592 -0.581 54.24

a All financial statement variables are on a per share basis and scaled by beginning of period price.Observations for the quarterly intervalare from 1980 to 1989, the annual intervals from 1960 to 1989and for the four year interval from 1964 to 1989.b Stock returnsafter adjustingfor the CRSP value-weighted index.c The four-yearobservationsarenon-overlapping and are the cumulatedone year values per share (afteradjusting for the numberof commonsharesoutstanding) scaledby beginningperiod price.

97

Table 2

Tests comparing the association of earnings. the association of cash from operationsand the association of net cash flows with stock returns (adjusted for market-wide

movements) over varying measurement intervals.s

Rit =a. + ~ (X)it + £it

Independent variable (X)

Eamings(E)Cash from

Operations (CFO)Net Cash

Hows (NCF)

Quarterly

Intercept(t-statistic)

Coefficient(t-statistic)

Adjusted R2 (%)

Annual

Intercept(t-statistic)

Coefficient(t-statistic)

Adjusted R2 (%)

Four Year

Intercept(t-statistic)

Coefficient(t-statistic)

Adjusted R2 (%)

-0.013(10.40)

0.742(25.71)

3.24

-0.084(-29.58)

1.297(72.65)

16.20

-0.510(-29.42)

1.686(59.06)

40.26

-0.008 -0.007(-5.75) (-5.51)

0.022 0.036(1.70) (1.61)

0.01 0.01

R2CFO =0.003R2NCF = 0.003

R2E R2E

-0.017 0.018(-5.87) (6.86)

0.328 0.614(29.98) (26.31)

3.18 2.47

~=0.20R2NCF = 0.15

R E . R2E

-0.199 0.081(-9.19) (4.76)

0.675 1.56(25.16) (18.40)

10.88 6.12

R2c FO =0.27R2NCF = 0.15

R7E R7E

98

a Reported parameter estimates are from pooled regressions. Rit is the stock return adjusted for theCRSP value-weighted index for finn i calculated over the time interval 1, where t is equal to onequarter, one year or four years. E is earnings per share, CFO is cash from operations per share and NCFis net cash flows per share. All variables are scaled by beginning of period price. The four-year valuesare the cumulated one year values per share (after adjusting for the number of common sharesoutstanding) scaled by beginning period price. The total number of observations is 19,733 for quarterly,27,308 for annual and 5,175 for four years. Observations for the quarterly interval are from 1980 to1989, the annual intervals from 1960 to 1989 and for the four year interval from 1964 to 1989.

99

Table 3

Resultsof the likelihood ratio test developed by Vuong (1989) for non-nested modelselection. A significant positive Z-statistic indicates thatmodel2 is rejected in favorof

model l.s

Comparison ofModell vs Model 2:

Quarterly

Earnings vs Cash from operations

Earnings vs Net cash flows

Cash from operations vs Net cash flows

Annual

Earnings vs Cash from operations

Earnings vs Net cash flows

Cash from operations vs Net cash flows

Four Year

Earnings vs Cash from operations

Earnings vs Net cash flows

Cash from operationsvs Net cash flows

Z-statisticfor difference in

explanatory power''

7.60

7.62

0.06

24.16

23.27

2.27

17.04

18.03

3.67

Probability

« 0.001)

«0.001)

(0.954)

«0.001)

« 0.001)

(0.013)

« 0.001)

« 0.001)

«0.001)

a The number of observations in thepooled regressions is 19,733 for quarterly, 27,308 for annual and5,175 for four years. Observations for the quarterly interval are from 1980 to 1989, the annualintervals from 1960to 1989 andfor thefour yearinterval from 1964 to 1989.b For more detail on the test developed by Vuong (1989) see chapter 5. Reported probabilities arefrom a two-tailed test

Table 4

Comparison of earnings' and alternative cash flow measures' association with stock returns over the annual interval; 1,976observations, 1987-1989.a

Rit =0. + J3 (X)it + tit

Independent Variable (X)

Earnings CF095 CFO CF095+ InvCF FinCF Inv CF + NCFInvCF FinCF

Intercept -0.087 -0.103 -0.074 -0.047 -0.070 -0.047 -0.082 -0.048(t-statistics) (11.00) (-10.55) (-8.14) (-5.60) (-7.68) (-5.63) (-8.40) (-5.80)

Coefficient 1.016 0.478 0.283 0.019 -0.192 0.037 -0.300 0.458(t-statistics) (18.39) (10.46) (7.16) (0.65) (-6.17) (1.26) (-6.84) (5.70)

Adjusted R2 (%) 14.58 5.20 2.48 0.00 1.84 0.00 2.27 1.57

Vuong Z-statisticb

comparing: model 1vs model 2

Earnings vs cash flows measures 5.40 6.45 7.89 6.97 7.77 6.88 6.81

CF095vsCFO 2.76

a Reported parameter estimates are from pooled regressions. Rit is the stock return adjusted for the CRSP value-weighted index for ftrm i calculatedover the contemporaneous annualinterval. Earningsis earnings from continuing operations, CFOis cash fromoperations, NCFis net cash flows, all asdescribed in table2. CF095 is cash from operations as required by FAS95 (COMPUSTAT # 308), Inv CF is investment cash flows (COMPUSTAT #311) and is negative for investment outlays, Fin CF is cash inflows from ftnancing (COMPUSTAT # 313),. All variables are on a per sharebasis andscaled by beginning of period price.b A positiveZ-sratistic indicates thatmodel2 is rejected in favorof model I (all Z-statistics are signiftcant at the0.01 level). -8

101

Table 5

Finn-specific annual first-order autocorrelation coefficients and Pearson correlations forearnings, cash from operations, net cash flows and accrual measures.a

PanelA: Annualfirst-order autocorrelation coefficientsr'

Perfonnance measures Mean Median

dNet cash flow per share -0.523 -0.53960perating cash flow per share -0.434 -0.4396Earnings per share -0.175 -0.177

Accrual measures

Mggregate accruals per share -0.438 -0.4706Change in working capital per share -0.465 -0.472

Panel B: Firm specific Pearson correlations:Mean Median

corr(6Net cash flow per sharecjj, All accruals per sharej)

Quarterly -0.876 -0.952Annual -0.553 -0.602Four years -0.407 -0.698

corr(6Cash from operations per Sharet-l,b6Working capital per sharej)

QuarterlyAnnualFour years

-0.702-0.646-0.362

-0.720-0.672-0.616

corr(6Cash from operations per Sharet-l,t, 6Eamings per sharet-l,V

Quarterly 0.059Annual 0.132Four years 0.300

corr(6Net cash flow per sharet-l,b 6Earnings per sharet-l,J

0.0600.3980.545

QuarterlyAnnualFour years

0.3840.3520.230

0.4230.4110.469

a A sample of 595 firms (from a total of 1222) is used to calculatethe correlations and over thequarterly interval; each firm is required to have at least 16 quarterly observations. A sample of 827(from a total of 2761) rums is used to calculate the correlations and autoeorrelations over the annual

102

interval; each firm is required to have at least 16 annual observations. A sample of 715 firms (from atotal of 2024) are used to calculate the correlations over the four year interval; each firm is required tohave at least 4, four-year observations. Observations for the quarterly interval are from 1980 to 1989,the annual intervals from 1960 to 1989 and for the four year interval from 1964 to 1989.b To obtain fust-order autocorrelation coefficients the following regression is performed for each fum:~t,t+l= a + P~t-l,t + £t,t+l. Where X is earnings per share, net cash flows per share, cash fromoperations per share, change in working capital per share or aggregate accruals per share, ~t,t+1 is thechange in X from time interval t to t+1. All accrualsi is measured as the difference between earningsand net cashflows per share in time period 1.

103

Table 6

Tests comparing the association of earnings, cash from operations and net cash flowswith stock returns after including past and future realized values of those variables;

6,466 annual non-overlapping observations 1964 to 1988.a

Rit =a + ~IXit + Eit

Rit =a + ~ave(Xit + Xit-l + Xit+l)/3 + eu

Rit =a + ~IXit + ~2Xit·l + ~3Xit+l + Eit

a ~1 ~2 ~3 ~ave AdiR2

Cash from -0.043 0.446 4.79operations (-6.87) (18.06)

-0.070 0.637 5.63(-10.12) (19.67)

-0.071 0.386 0.281 0.02 6.73(-10.37) (20.06) (11.27) (0.78)

Net cash flows 0.009 0.737 3.18(1.67) (14.60)

-0.003 1.564 4.58(-0.59) (17.64)

-0.003 1.500 0.481 0.341 5.39(-0.65) (18.45) (10.10) (7.57)

1.490(36.74)

Earnings -0.125(-19.94)

-0.136(-20.02)

-0.137 1.253 -0.167 0.503(-20.62) (33.36) (-3.69) (11.79)

1.624(33.36)

17.26

14.68

19.11

a Rit is the fiscal stock return measured for year t adjusted for the CRSP value-weighted index. X iseither earningsper share,cash from operations per share or net cash flows per share. All variables arescaledby the price at t-I. Observations are obtained from everythirdyearbeginning in 1964.

104

Table 7

Testscomparing the association of earnings and the association of net cash flows withstock returns across quintiles, wherequintiles are formed based on the absolutevalueof aggregate accruals. Quintile 5 contains finn-observations with the largest absolute

valueof aggregate accruals,"

Rit = an + ~nNCFit + enit

Rit = a e + ~eEit + £eit

Quintile 1 = small absolute aggregate accruals, abs(AA)

Z-statisticTlDle Net cash flows Earnings fordifference in Probability

Interval ~n Adj R2(%) ~ Adj R2(%) explanatory power''

Quarterly

Quintile 1 1.60 3.44 1.69 3.55 0.58 0.561Quintile2 1.09 1.88 1.44 2.82 2.35 0.019Quintile3 0.67 1.17 1.19 3.03 3.28 0.001Quintile4 0.26 0.32 1.24 4.69 5.99 0.000Quintile5 -0.08 0.15 0.61 4.96 4.78 0.000

Annual

Quintile 1 2.37 16.20 2.50 16.84 1.72 0.085Quintile2 1.89 12.23 2.18 15.44 4.96 0.000Quintile3 1.47 8.76 1.91 14.49 6.18 0.000Quintile4 1.03 6.51 1.56 14.82 7.25 0.000Quintile5 0.14 0.24 0.97 21.98 15.65 0.000

Four Year

Quintile 1 2.50 27.25 2.09 26.99 -0.16 0.446Quintile2 1.96 18.45 1.83 22.66 1.78 0.074Quintile3 2.32 18.97 1.77 26.79 3.00 0.003Quintile 4 1.73 8.99 1.51 23.84 5.43 0.000Quintile5 1.13 2.83 1.29 31.78 10.37 0.000

a Rit is the stock return adjusted for the CRSP value-weighted index for firm i calculated over thetime interval t. where t is equal to one quarter, one year or four years. E is earnings per share, NCF isnet cash flows per share and Abs(AA) is the absolute value of the aggregate accruals per share. Allvariablesare scaledby beginning of periodprice.The four-year valuesare the cumulatedone year valuesper share (after adjusting for the number of common shares outstanding) scaled by beginning periodprice. The total number of observations is 19,733 for quarterly, 27,308 for annual and 5,175 for fouryears. Observationsfor the quarterly interval are from 1980 to 1989, the annual intervals from 1960 to1989and for the four year intervalfrom 1964 to 1989.b Vuong's (1989)Z-statisticcomparesearningsand net cash flowsas competingnon-nestedmodels. Asignificant positive Z-statistic indicates that net cash flow is rejected in favor of earnings. Reportedprobabilitiesfor the Z-statisticsare from a two-tailedtest

105

Table 8

Examination of proxies for underlying determinants of earnings response coefficientsacrossquintiles formed on the absolute valueof aggregate accruals; annual observations

1960-1989.a

Small abs(AA) Large abs(AA)

Quintile 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5

Coefficient on 2.50 2.18 1.91 1.56 0.97Earnings

Predictedchange invalue across quintiles

Mean ValuesRisk

EJP + 0.054 0.058 0.076 0.091 0.077Leverage + 2.387 1.973 2.316 2.436 2.847MktIBook 2.325 1.880 1.553 1.184 0.862Size - 653.984 762.803 863.653 521.710 251.744

Growth Opportunities

R&D/Assets 0.038 0.034 0.031 0.028 0.024Capital explDepr 2.041 2.151 2.104 2.081 1.982Net/Gross 0.593 0.597 0.593 0.585 0.572

Median ValuesRisk

EJP + 0.055 0.065 0.085 0.109 0.140Leverage + 1.985 1.964 2.010 2.099 2.229MktIBook 1.600 1.588 1.349 1.028 0.741Size 88.241 125.843 116.736 64.017 27.696

Growth Opportunities

R&D/Assets 0.026 0.023 0.021 0.018 0.015Capital explDepr 1.522 1.685 1.718 1.696 1.609Net/Gross 0.592 0.597 0.591 0.582 0.572

a Quintiles are formed based on fum-year observations of the absolute value of aggregate accrualsAbs(AA). Size is measured as market value of equity at t-I. FJP is the earnings from t-2 to t-I toprice at t-I. Leverage is measured as assets at t-l scaled by book value of equity at t-I. MktIBook isthe firms market value of equity scaled by book value of equity both measured at t-I. R&D/Assets isresearch and development expenditures scaled by assets at t-I. Capital explDepr is capital expendituresscaled by depreciation expense. Net/Gross is the net book value of fixed assets scaled by the grossbook value of fixed assets.

106

Table 9

Tests comparing the association of earningsand the association of cash from operationswithstock returnsacrossquintiles, wherequintilesare formed based on the absolute

valueof thechange in working capital. Quintile 5 containsfirms with the largestabsolute changes in working capital.a

Rit =<:xc + ~cCFOit + £Cit

Rit =(Xe + ~eEit + Eeit

Quintile 1 = small absolute change in working capital, abs(L\We)

Z-stansucTime Cash from operations Earnings fordifference in Probability

Interval ~c Adj R2(%) ~e Adj R2(%) explanatorypower''

Quarterly

Quintile 1 0.81 1.98 1.16 2.81 1.49 0.135Quintile2 0.66 1.64 1.21 3.99 2.55 0.011Quintile3 0.51 1.74 1.01 3.72 2.50 0.012Quintile4 0.18 0.41 0.90 3.94 5.13 0.000Quintile 5 -0.05 0.16 0.60 3.71 3.88 0.000

Annual

Quintile 1 0.88 7.72 1.71 14.24 6.93 0.000Quintile 2 0.90 8.69 1.71 15.73 7.44 0.000Quintile3 0.76 8.24 1.57 16.54 9.00 0.000Quintile 4 0.59 7.34 1.47 19.08 10.24 0.000Quintile 5 0.11 0.79 1.02 18.19 15.09 0.000

Four Year

Quintile 1 1.16 27.19 2.12 45.69 5.92 0.000Quintile 2 1.05 26.06- 1.80 42.08 4.45 0.000Quintile 3 1.06 23.20 1.71 34.31 4.09 0.000Quintile4 0.85 19.01 1.70 45.22 9.52 0.000Quintile 5 0.28 2.25 1.42 34.46 11.37 0.000

a Rit is the stock return adjusted for the CRSP value-weighted index for firm i calculated over the timeinterval t, where t is equal to one quarter, one year or four years. E is earnings per share, CPO is cashflows from operations per share and Abs(6.WC) is the absolute value of the change in working capitalper share. All variables are scaledby beginning of periodprice. The four-yearvalues are the cumulatedone year values per share (after adjusting for the number of common shares outstanding) scaled bybeginning period price. The total numberof observations is 19,733 for quarterly, 27,308 for annual and5,175 for four years. Observations for the quarterly interval are from 1980 to 1989, the annualintervals from 1960 to 1989 and for the four year interval from 1964 to 1989.b Vuong's (1989) Z-statistic compares earnings and cash from operations as competing non-nestedmodels. A signlficant positive Z-statistic indicates that cash from operations is rejected in favor ofearnings. Reportedprobabilities for the Z-statisticsare from a two-tailedtest.

107

Table 10

Tests comparing the association of earnings and the association of cash from operationswith stock returns across quintiles, where quintiles are formed based on the absolute

value of long-term operating accruals. Quintile 5 contains firms with the largestabsolute long-term operating accruals.a

Rit = <Xc + ~cCFOit + £Cit

Rit = <Xe + ~eEit + £eit

Qulntile 1 = small absolute long-term operating accruals, abs(LTA)Z-statistic

Time Cash from operations Earnings for difference in Probability

Interval ~c Adj R2(%) ~e Adj R2(%) explanatory power''

Quarterly

Quintile 1 0.01 0.00 1.44 3.28 4.42 0.000Quintile 2 0.02 0.00 1.51 4.42 3.75 0.000Quintile 3 0.05 0.05 1.15 3.34 3.87 0.000Quintile 4 0.04 0.02 1.30 6.03 5.85 0.000Quintile 5 0.01 0.00 0.56 3.95 4.23 0.000

Annual

Quintile 1 0.43 2.24 1.88 12.68 9.32 0.000Quintile 2 0.38 2.21 2.01 17.66 13.45 0,000Quintile 3 0.35 . 2.34 1.82 18.49 9.25 0.000Quintile 4 0.36 3.17 1.60 20.65 12.51 0.000Quintile 5 0.28 4.00 0.96 20.46 14.10 0.000

Four Year

Quintile 1 1.07 11.18 2.37 45.00 8.44 0.000Quintile 2 0.79 7.88 2.09 44.75 6.99 0.000Quintile 3 0.89 10.17 2.08 44.01 9.39 0.000Quintile 4 0.98 18.04 1.67 48.51 10.14 0.000Quintile 5 0.55 8.86 1.30 34.39 7.95 0.000

a Rit is the stock return adjusted for the CRSP value-weighted index for fum i calculated over the timeinterval 1, where t is equal to one quarter, one year or four years. E is earnings per share, CFO is cashflows from operations per share and Abs(LTA) is the absolute value of long-term operating accruals pershare. All variables are scaled by beginning of period price. Long-term operating accruals are obtainedby deducting cash from operations and changes in working capital from earnings (see Appendix 1). Thefour-year values are the cumulated one year values per share (after adjusting for the number of commonshares outstanding) scaled by beginning period price. The total number of observations is 19,733 forquarterly, 27,308 for annual and 5,175 for four years. Observations for the quarterly interval are from1980 to 1989, the annual intervals from 1960 to 1989 and for the four year interval from 1964 to1989.b Vuong's (1989) Z-statistic compares earnings and cash from operations as competing non-nestedmodels. A significant positive Z-statistic indicates that cash from operations is rejected in favor ofearnings. Reported probabilities for the Z-statistics are from a two-tailed test.

108

Table 11

Testscomparing the association of earnings before taxes and the association of earningsbefore special itemsand taxes withstock returns over different measurement intervals.a

Quarterly

Earnings beforetax(including special items) Adj R2(%)

Earnings before taxand special itemsAdj R2 (%)

Vuong Z-statistic(probability)b

Numberof observations

Annual

Earnings before tax(including special items) Adj R2 (%)

Earnings before taxand specialitems Adj R2 (%)

Vuong Z-statistic(probability)b

Numberof observations

Four Year

Earnings before tax(including special items) AdjR2 (%)

Earningsbeforetaxand special itemsAdj R2(%)

Vuong Z-statistic(probability)b

Numberof observations

Sample of firmobservations with

special items

0.92

2.96

2.14(0.03)

2,535

6.34

9.34

2.77(0.01)

5,832

34.48

33.95

-0.73(0.47)

2,083

Sampleof finnobservations withno specialitems

1.31

18,181

18.70

22,815

41.07

3,369

109

a Stock returns are adjusted for the CRSP value-weighted index and calculated over the time interval t,where t is equal to one quarter,one year or four years. Earnings before tax and earnings before tax andspecial items are on a per share basis and scaled by beginning of period price. The four-year values arethe cumulated one year valuesper share (after adjusting for the numberof common shares outstanding)scaled by beginning period price. Observations for the quarterly interval are from 1980 to 1989, theannual intervals from 1960 to 1989and for the four year interval from 1964 to 1989.b Vuong's (1989) Z-statistic comparesearningsbefore tax and special items and earnings before tax ascompeting non-nested models. A significant positive Z-statistic indicates that earnings before tax isrejected in favor of earnings before tax and special items. Reported probabilities are from a two-tailedtest.

110

Table 12

Descriptive statistics on firm level operating and trade cycles (measured in days) andfirm level and industry level Pearson correlations between the absolute value of thechange in working capital and the length of the operating and trade cycle; annual

observations, 1960-1989.a

Panel A: Mean Standard Median Upper Lower NumberDeviation Quartile Quartile of Firms

Operatingcycle 146.02 72.99 138.03 184.62 96.35 1,252

Trade cycle 108.11 78.86 101.07 147.49 60.02 1,252

Panel B: Finn-level correlations (probabilities inparentheses)

(Number of observations = 1,252)

corr (abs(~WC),operating cycle) 0.187(0.000)

corr (abs(~WC),trade cycle) 0.163(0.000)

Panel C: Industry-level correlations (probabilities inparentheses)

(Number of observations = 58)

corr (abs(~WC),operatingcycle)

corr (abs(~WC),tradecycle)

0.405(0.002)

0.450(0.000)

a abs(~WC) is the absolute value of the change in non cash working capital per share scaled by beginningof period price. Industry operating cycles, trade cycles and abs(~WC) are calculated by (i) averaging thetime-series of fum specific values and (ii) taking the average of the fum specific values across two digitSIC classifications.

. I (ARt + ARt-I)I2) ( (Invj + Invt-I)12 )operating cye e = +Sales/360 Cost of goods sold/360

trade cle=(ARt + ARt-I)/2 ) + ( (Invt + Invt-l)12 ). (APt + APt-I)12 )cy Sales/360 Cost of goods sold/360 Purchases/360

Table 13

Pearson correlations (probabilities) between the R2s (from regressions performedby industry of stock returns on cash from operations or stock returns on earnings)

with the average length of the industry operating and trade cycles; annualobservations 1960-1989.a

Correlation between the R2 from 58 industry specific regressions ofstockreturnson cash from operations (CFO) with theaverage industry operating or trade cycle

III

corr (R2.operating cycle)

corr (R2.trade cycle)

-0.483(0.001)

-004.18(0.001)

Correlation between theR2 from 58 industry specific regressions ofstockreturnson eaminu (E) with the average industry operating or trade cycle

corr (R2.operating cycle)

corr (R2.trade cycle)

-0.083(0.538)

-0.012(0.926)

a The R2s for cash from operations are obtained by performing separate regressions of returns(adjusted for the CRSP value-weighted market return) on cash from operations for each of 58 twodigit SIC industry classifications. The R2s for earnings are obtained in a similar manner. Cashfrom operations and earnings are on a per share basis and scaled by beginning of period price. Theoperating cycle for each industry is obtained by first calculating firm-specific mean operatingcycles and then taking the average across firms in the same two digit SIC industry classifications.A similar procedure is used to obtain the trade cycle. The minimum number of observationsrequired per firm is 10.

. I (ARt + ARt-l)/2) ( (Invt + Invt-l)/2 )operating eyc e = +Salesl360 Cost of goods sold/360

tradec cle=(ARt + ARt-l)/2 ) + ( (Invt + Invt-l)/2 ) _ (APt + APt-l)/2 )y Sales/360 Cost of goods sold/360 Purchasesl360