1
Do Real Economic Choices Sway Asymmetric Timeliness of Earnings?
Jacob Oded and Dan Weiss
Tel Aviv University
March 6, 2013.
Abstract
This study uses a general framework and new empirical tests to examine how real
economic choices sway asymmetric timeliness of earnings. Specifically, earnings
reported in financial statements are viewed as the outcome of two nonlinear processes: (i)
profit generation through real economic activities, and (ii) conservative accounting rules
that transform these profits into reported earnings. Results suggest that real economic
choices generate substantial variation in the asymmetric timeliness of earnings. These
findings hold after controlling for the impact of earnings management. Overall, the
results suggest that controlling for real economic choices is crucial for proper inference
of conservatism from empirical evidence on asymmetric timeliness of earnings.
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Do Real Economic Choices Sway Asymmetric Timeliness of Earnings?
1. Introduction
The more timely recognition of bad news than good news in earnings, referred to as
asymmetric timeliness of earnings, has been attracting much attention (Ewert and
Wagenhofer, 2011). Researchers have interpreted empirical evidence on the asymmetric
timeliness of earnings as consistent with conservative accounting rules (Basu, 1997;
Khan and Watts, 2009). Recently, Banker, Basu, Byzalov and Chen (2012), hereafter
BBBC, report that asymmetric timeliness of earnings may also arise from sticky cost
structures, which are a fundamental real choice, not a financial reporting choice. They
conclude that the Basu measure overestimates the actual degree of conservatism because
it does not control for the potential confounding effect of cost stickiness. Earlier, Hanna
(2002) and Watts (2003b) argued that earnings management may also partially explain
empirical evidence on asymmetric timeliness of earnings. Therefore, we are motivated to
explore the impact of non-conservatism explanations on the degree of asymmetric
timeliness of earnings.
Focusing on real economic choices underlying firm activities, our study offers several
novel insights. First, we present a broad framework and new tests facilitating an
empirical examination of the relative impact of real economic choices versus financial
reporting choices on the degree of asymmetric timeliness of earnings. Second, we show
that real economic choices, above and beyond conservative accounting rules, generate
substantial variation in the asymmetric timeliness of earnings. Third, we utilize Khan and
Watts' (2009) Cscore1 and earnings skewness2 to find that, on average, the interpretation
1
Khan and Watts (2009) build on Basu (1997) in presenting a firm-year specific measure of the
asymmetric relation between earnings and signals of good or bad news (stock returns), which they attribute
to conservatism. We formalize their argument and explicitly show how conservative accounting rules
generate asymmetric distributions of reported earnings.
2
Earnings skewness directly measures the degree to which earnings are asymmetrically distributed. Prior
studies infer conservatism from negatively skewed earnings distributions because bad news is reported
under conservative accounting in a more timely manner than good news (e.g., Ball et al., 2000; Givoly and
Hayn, 2000; Lang et al., 2003; Ball and Shivakumar, 2005; Kwon et al., 2006; Lang et al., 2006; Beatty et
al., 2008; Chung and Wynn, 2008; Callen et al., 2009; Garcia-Lara et al., 2009; Kim and Pevzner, 2010;
Donovan et al., 2013). These studies assume that if conservatism leads to an immediate and complete
recognition of negative events and a delayed and gradual recognition of positive events, it is likely to
induce negatively skewed earnings distributions. This assumption has never been empirically tested.
3
of asymmetric timeliness of earnings as evidence of conservatism prevails after
controlling for real economic choices and earnings management.
Our framework views earnings reported in financial statements as the outcome of two
nonlinear processes. First, a firm generates profits by performing real economic activities,
which transform resources into goods and into services sold to customers. Second, the
firm applies conservative accounting rules to transform its profits into earnings reported
in financial statements.
The proposed framework facilitates the investigation of the impact of three real
economic choices on the degree of asymmetric timeliness of earnings: a stock option
based compensation scheme choice, a cost structure choice (sticky costs), and a firm’s
monopolistic power.3 A model presented in Section 2 predicts an asymmetric impact on
profits before the application of accounting rules for each of these real choices. Consider,
for example, the asymmetric profits generated by the choice of a stock option based
compensation scheme. Suppose a firm grants its manager stock options at the beginning
of a year, where the exercise price equals the market price of the stock. If demand for the
firm’s products rises during the year (good news, option in the money), the manager is
highly motivated to increase profits. Alternatively, if demand falls during the year (bad
news, option out of the money), the option does not generate an incentive to moderate a
decline in profits. That is, stock option based incentives lead to an increase in profits
when demand rises (good news) that is greater than the decrease in profits when demand
falls (bad news) by an equivalent amount. The outcome is asymmetric profits before
accounting rules are applied. Overall, we predict that stock option based compensation,
sticky costs and monopolistic power induce asymmetric profits before accounting rules
are applied.
Utilizing the Khan and Watts (2009) firm-year specific Cscore and earnings skewness
to empirically test these predictions, we find that the three real economic choices
significantly influence the degree of asymmetric timeliness of earnings. Specifically,
While compensation schemes and cost structures are straightforward choices of firms, viewing a firm’s
market power as a choice requires further elaboration. The power of a firm in a product market is an
outcome of an early choice to penetrate that market. Indeed, the strategy literature reports that market
power is influenced by choices such as product pricing decisions, choices to strengthen brands by
advertising or choices to invest in innovative technologies (Tirole, 1988, and Dhaliwal et al., 2008).
3
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stock option based incentives and monopolistic power reduce the Cscore and induce less
negative earnings skewness (i.e., they lessen the left-tail of earnings distribution). That is,
stock option based incentives and monopolistic power moderate the impact of
conservative accounting rules. In contrast, sticky costs increase the Cscore and induce
more negative earnings skewness (i.e., they expand the left-tail of earnings distribution).
That is, sticky costs intensify the impact of conservative accounting rules. Overall, the
results suggest that, on average, real economic choices have a significant impact on the
degree of asymmetric timeliness of earnings.
Moreover, results from a portfolio analysis show that real economic choices generate
substantial variations in both the Khan and Watts Cscore and in earnings skewness.
Consider Cscore first. For a portfolio with three real choices that moderate the impact of
conservatism, namely, high (above median) stock option based incentives, anti-sticky
costs, and high (above median) monopolistic power, we find the mean Cscore to be
0.047. In contrast, for a portfolio with three real choices that intensify the impact of
conservatism, namely, low (below median) stock option based incentives, sticky costs,
and low (below median) monopolistic power, we find the mean Cscore to be 0.179. The
difference is significant at the 1% level. The mean Cscore in the portfolio with all three
real choices intensifying the conservatism effect is 3.8 (=0.179/0.047) times larger than
the mean Cscore in the portfolio with all three real choices moderating the conservatism
effect. Notably, the Cscore remains positive in both portfolios. This result, in turn,
suggests that the Khan and Watts (2009) inference of conservatism from asymmetric
timeliness of earnings holds even after controlling for three real economic choices.
With respect to earnings skewness, our findings shed light on a subtle issue. Several
prior studies argue that earnings skewness is a proxy for conservatism (e.g., Ball et al.,
2000; Kwon et al., 2006; Garcia-Lara et al., 2009), while other studies utilize the
difference between earnings skewness and cash flow skewness as a proxy for
conservatism (e.g., Givoly and Hayn, 2000; Beatty et al., 2008; Callen et al., 2009; Kim
and Pevzner 2010; Donovan et al., 2013). We presume that real choices influence cash
flow similarly to the way they influence earnings, while conservative accounting rules
affect earnings, not cash flows. Therefore, the difference between earnings skewness and
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cash flow skewness is expected to be influenced by conservatism, not by real choices.
Indeed, our results show that real choices heavily affect the degree of earnings skewness,
but do not affect the difference between earnings skewness and cash flow skewness.4
Therefore, we conclude that the difference between earnings skewness and cash flow
skewness is less sensitive to real choices and more appropriate than earnings skewness
per se for testing conservatism.
Finally, we test the robustness of the findings to two financial reporting choices: a
choice to manage earnings and a choice to report negative special items. With respect to
earnings management, Hanna (2002) and Watts (2003b) argue that earnings management
serves as an alternative explanation for the asymmetric timeliness of earnings. In our
setting, stock option based incentives are likely to affect reporting choices, not only real
choices, because they motivate managers to manipulate earnings. In line with Hanna’s
(2002) and Watts’ (2003b) argumentation, we find that earnings management is
significantly and positively associated with the Cscore and significantly and negatively
associated with the degree of earnings skewness (it induces left-tailed skewness).
With respect to reporting special items, we further validate the findings in the
presence of a direct proxy of conservatism. Callen et al., (2010) suggest that a choice to
report negative special items serves as a tool to facilitate conservatism in financial
reporting. Our evidence indicates that reporting negative special items is significantly and
positively associated with the Cscore and significantly and negatively associated with the
degree of earnings skewness (it induces left-tailed skewness). That is, conservatism
facilitated through negative special items increases the degree of asymmetric timeliness
of earnings. More importantly, the impact of the three real choices remains significant in
the presence of conservatism facilitated through negative special items and of earnings
management, in line with our prediction.
The contribution of this study is three-fold. First, the findings suggest that real
economic choices introduce substantial variation in the degree of asymmetric timeliness
of reported earnings. Particularly, their impact is above and beyond that of applying
4
To clarify, the findings reveal that the three real economic choices significantly influence the extent of
earnings skewness, However, real economic choices are insignificantly associated with the difference
between earnings skewness and cash flow skewness, which is consistent with an equivalent effect of real
choices on the shapes of both earnings and cash flow distributions.
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conservative accounting rules, which has been explored extensively in the vast
conservatism literature. Real choices serve as intensifying forces (sticky costs inflate the
Cscore and expand the left-tail earnings skewness) or as moderating forces (stock option
based incentives and monopolistic power moderate the Cscore and lessen the left-tail
earnings skewness). Thus ignoring real economic choices may lead to either
overestimation or underestimation of conservatism depending on the correlated omitted
real variables. Our approach provides the means to empirically separate the relative
impact of conservatism on asymmetric timeliness of earnings from that of real economic
choices when the two phenomena coexist. The framework offers powerful new empirical
tests for inferring conservatism in the presence of confounding real economic choices.
Second, the nonlinear framework generalizes the piecewise linear approach of Basu
(1997), Khan and Watts (2009), and BBBC. The motivation for the BBBC study lies in
the similarity between the piecewise linear specifications underlying Basu’s (1997)
conservatism measure and the measure of cost stickiness introduced by Anderson et
al.,(2003). While our findings corroborate BBBC’s results, we take a step forward.
Specifically, we present an integrative framework of two nonlinear processes: real
economic choices leading to profits, and reporting choices made in transforming profits
into earnings reported in financial statements. Moreover, while BBBC argue that cost
stickiness overstates the Basu measure, we show that cost stickiness may have an
opposite effect – anti-sticky costs understate the effect of conservatism reported by Basu
(1997).
Finally, we show that earnings management serves as a non-conservatism explanation
of asymmetric timeliness of earnings, as argued by Hanna (2002) and Watts (2003b).
Furthermore, we find that the inference of conservatism from evidence on asymmetric
timeliness of earnings prevails in the presence of earnings management and the three real
economic choices and earnings management.
The rest of this paper is organized as follows. The general framework and the
hypotheses are developed in Section 2. The research design and sample are presented in
Section 3. Sections 4 and 5 present the empirical findings. Sensitivity analyses are in
Sections 6 and 7. Section 8 concludes.
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2. Hypothesis development
The conservatism literature has treated reported earnings as emerging from a black
box spinning out reports that reflect profits generated by real economic activities as well
as financial reporting procedures. This literature has, to a large extent, ignored a potential
effect of real activities on the asymmetric timeliness of earnings. Conservative
accounting rules underlie financial reporting procedures, which transform profits
generated by real activities into earnings reported in financial statements. In this section,
we offer a general framework to facilitate an empirical examination of the manner in
which both real economic activities and conservative accounting rules generate
asymmetric timeliness of earnings. Specifically, we break down the earnings generating
process into real economic activity and reporting procedures. This breakdown enables (i)
a testing of the impact of real economic activities on the asymmetric timeliness of
reported earnings, and (ii) a re-examination of the inference of conservative accounting
rules from evidence on the asymmetric timeliness of earnings controlled for real
economic activities.
2.1
Asymmetric timeliness of earnings – A general framework
To penetrate the black box, we develop a new framework to investigate the sources of
the asymmetric timeliness of earnings. The goal is to facilitate an empirical examination
of the relative impact of conservative accounting rules versus that of real economic
activities on the asymmetric timeliness of earnings. We view reported earnings as the
outcome of two processes. First, a firm generates profits by performing real economic
activities, which transform resources into goods and services sold to customers. Second,
the firm applies conservative accounting rules to transform its profits into earnings
reported in financial statements. We focus on the impact of favorable versus unfavorable
changes in the business environment on earnings, keeping in mind that both conservative
accounting rules and real economic activities may influence this relationship. Modeling
the shape of the two parts of the earnings generating process serve as a basis for an
empirical examination of the sources of the asymmetric timeliness in reported earnings.
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We utilize a two-period model. The primitive inputs in the first period are economic
fundamentals (e.g., customer demand, commodity prices, the firm’s technology and
knowhow). The firm faces uncertainty in the form of an ex-ante distribution, where each
economic fundamental is a continuous random variable X on .
E(X) denotes the
expected value of an economic fundamental. In the second period, X realizes a value x
and an earnings generating process, , transforms x into reported earnings. The earnings
generating process is (x)=g(f(x)), where f is the real economic activity, which transforms
economic fundamentals into profits, and g is a reporting procedure, which applies
conservative accounting rules to transform profits into earnings reported in financial
statements (see Diagram 1 below). The ex-ante earnings expectation in the first period is
denoted E[(X)]= E[g(f(X))].
Diagram 1: The earnings generating process, (x)=g(f(x))
Economic fundamentals, X
Demand
Commodity prices
Technology & knowhow
Conservative
accounting
rules
Real
economic
activity
Real
function
f(.)
Profits
Reporting
function
g(.)
Earnings
reported in
financial
statements
Earnings
(x)=g(f(x))
Preparing financial statements, a firm views a realized value of demand below its
expectation as bad news, denoted xb<E(X). In similar vein, the firm views a realized value
of demand above its expectation as good news, denoted xg>E(X). That is, good news is a
demand realization that exceeds demand expectations, and vice versa. We note that bad
and good news relate to the unexpected value of a realized economic fundamental with
respect to the ex-ante expectation.
2.2.
The real economic activity (real function, f)
Our framework provides room to accommodate various patterns of real economic
activities. We focus on three real effects that naturally imply an asymmetric impact on
profits: stock option based incentives, a cost behavior choice and monopolistic power.
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Particularly, we argue that these three effects induce an asymmetric shape of the real
function f.
Stock option based incentives – Stock options are granted to encourage managers to
take actions that increase firm value (Jensen and Meckling, 1976). When the exercise
price equals to the stock price, managers benefit from taking actions that increase firm
value, but are not penalized by taking actions that decrease firm value. That is, managers
are paid for increasing firm value, but are not fined when firm value deteriorates. Agency
theory teaches us that granting stock options motivates managers to make efforts to
increase firm value, but is less effective in motivating actions to restrain a decline in firm
value (e.g., Myers 1977).
Suppose a firm grants its manager stock options in the first period and the exercise
price equals the current market price of the stock. Consider the second period real profits.
In the face of bad news ,i.e., demand is below expectations, xb<E(X), the firm’s profits
are f(xb). Alternatively, in the face of good news, i.e., demand exceeds expectations,
E(X)<xg, the firm’s profits are f(xg). That is, a manager is less likely to meet the money in
the presence of an unfavorable demand condition than in the presence of favorable
demand condition. Therefore, stock option based incentives generate strong incentives in
the presence of a favorable demand condition and low (or no) incentives in the presence
of an unfavorable demand condition. Focusing on the impact of stock option based
incentives on real profits, the manager has a greater incentive to increase profits in
response to good news than to restrain a decrease in profits in response to bad news of an
equivalent amount. Assuming that greater incentives result in real performance,5 stock
option based incentives lead to a convex real function, f.
Stock option based incentives imply convex real function f:
xg-E(X)=E(X)-xb  f(xg) - E[f(X))] > E[(f(X))] - f(xb).
(1)
Sticky Costs – Anderson et al.,(2003) termed costs as sticky if they increase more
when the activity level rises than they decrease when the activity level falls by an
equivalent amount. This means that costs tend to “stick” on the downside and hence do
not go away when the activity level declines. Cost stickiness has been widely
5
The effect of stock option based incentives on the reporting function (earnings management) is discussed
later in Section 5.
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documented in recent managerial accounting research on cost behavior (e.g., Anderson et
al., 2003; Weiss, 2010; Chen et al., 2011; Banker et al., 2012; Kama and Weiss 2013).
Anderson et al.,(2003) argue that cost stickiness arises because of two fundamental
features of cost behavior: deliberate resource commitments made by managers, and
adjustment costs such as hiring and firing costs for labor, or installation and disposal
costs for equipment (Cooper and Haltiwanger, 2006). The concept of sticky costs is all
about differential changes in costs resulting from good news versus bad news with
respect to customer demand: demand rising above expectations is good news, while
demand falling below expectations is bad news.6 Stickier costs result in lower
(proportional) cost savings when the activity level falls below expectation, which, in turn,
leads to a greater decrease in profits. Under sticky costs, profits decrease more when the
activity level falls than they increase when the activity level rises by an equivalent
amount. When the good news and the bad news are equivalent in magnitude, xg-E(X)=
E(X)- xb. Equation (2) below indicates that cost stickiness implies, by definition, a
concave real function f: 7
Sticky costs imply a concave real function f:
xg-E(X)=E(X)-xb  f(xg) - E[f(X))] < E[(f(X))] - f(xb).
(2)
Our argument is in line with the recent refinement by BBBC of Basu’s (1997)
conservatism measure to account for cost stickiness. BBBC argue that a similar piecewise
linear relation also arises from a real choice that results in cost stickiness. Since costs
directly enter earnings, cost stickiness implies that earnings should respond less to sales
increases than to sales decreases. That is, the asymmetric response of costs to changes in
sales due to stickiness results in asymmetric behavior of earnings. Therefore, BBBC find
that asymmetric timeliness of earnings is also attributable to cost stickiness. They show
that Basu’s measure of conservatism is biased because of the confounding role of cost
stickiness. BBBC’s argument builds on the similarity between the empirical specification
6
For simplicity, we implicitly assume that demand expectation is based on a random walk model. All the
results hold with alternative conventional prediction models.
7
To clarify, the economic literature discusses transformations of demand into earnings that are concave in
some ranges of demand and convex in others (Mas-Colell et al., 1995, p. 144). We concentrate on
transformations within a relevant range only.
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of Basu’s measure of asymmetric timeliness of earnings and the cost stickiness measure
(Anderson et al., 2003). Our approach, though, offers the economic rationale underlying
the relationship between cost stickiness and asymmetric timeliness of earnings.8
Monopolistic Power – Market (monopolistic) power is an ultimate candidate because
its asymmetric impact on profits has been modeled in the literature (Kreps, 1990, p. 299).
To see this, consider a firm with some monopolistic power. In the first period, this
monopoly faces an uncertain demand X which is realized in the second period.9 In the
case of bad news, i.e. demand is below expectations, xb<E(X), and the monopoly’s profits
are f(xb). Alternatively, in the case of good news, demand exceeds expectations, E(X)<xg,
and the monopoly’s profits are f(xg). The monopoly exercises its market power to
increase its profits when demand rises and also to moderate profits decline when demand
falls (e.g. Mas-Colell et al.,1995, p. 384). When a firm has some monopolistic power, the
increase in profits in response to good news exceeds the decrease in profits in response to
bad news of an equivalent amount. That is, monopolistic power leads to a convex real
function, f:
Monopolistic power implies a convex real function f:
xg-E(X)=E(X)-xb  f(xg) - E[f(X))] > E[(f(X))] - f(xb).
2.3
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(3)
The reporting process (reporting function, g)
Extending BBBC, our general framework provides room not only for sticky costs but also for anti-sticky
costs. Weiss (2010) terms costs as anti-sticky if they increase less when activity level rises than they
decrease when activity level falls by an equivalent amount. In other words, costs are anti-sticky if managers
expedite cost cutting when sales falls. The literature reports that costs are, on average, sticky, but exhibit
substantial variation (e.g., Balakrishnan et al., 2004; Balakrishnan and Gruca, 2008; Weiss, 2010). Under
anti-sticky costs, profits decrease less when activity level falls than they increase when activity level rises
by an equivalent amount. By construction, anti-sticky costs imply a convex real function f:
xg-E(X)=E(X)-xb  f(xg) - E[f(X))] > E[(f(X))] - f(xb).
Overall, sticky costs result in a concave real function f, whereas anti-sticky costs result in a convex real
function f.
9
Demand here indicates demand quantity. Banker and Chen (2006) use the term “activity level” with the
same meaning. While we demonstrate our argument using demand, this is done without loss of generality.
Other factors that affect earnings distribution could also be considered.
12
We focus on conservative accounting rules as a primary aspect of the reporting
process that induces asymmetry into the reporting procedure. We build on a linear real
function f for a simple presentation of how conservative accounting rules shape the
reporting function g, and, in turn, shape the earnings generating process . For instance,
suppose the realized resource price in the second period is either $1 below expectations
or $1 above expectations. That is, E(X)-xg=1 is good news realized in the second period
and xb-E(X)=1 is the corresponding bad news. The real function captures profits from
customer orders fulfilled in the second period, in which the consumed resource is a
variable cost (no inventory). In this example, the function f(.) is linear (in contrast with
stock option based incentives, cost stickiness and monopolistic power). That is, the profit
growth due to a decrease in resource price is equal to the profit decline due to resource
price increase:10
A linear real function:
xg - E(X)=E(X)- xb  f(xg)- E[f(X))] = E[(f(X))] - f(xb). (4)
Now, we consider how conservative accounting rules shape the reporting function g
and, in turn, the earnings generating process . Suppose a firm has made a contractual
commitment to supply the good in the future at a predetermined price. Conservatism
implies that earnings respond more completely or quickly to bad news than to good news
(Basu, 1997; Watts 2003a). Therefore, earnings are more timely or concurrently sensitive
in reflecting bad news than good news. Under conservative accounting, the firm has to
immediately recognize expected loss from future supplies when the price of resources
rises,11 but does not recognize unrealized profit from future supplies when the price of
resources falls. Recalling the above example, the decrease in earnings in response to bad
news (resource price increase) exceeds the increase in earnings response to good news
(resource price decrease) of an equivalent amount. If the real function f is linear,
conservative accounting rules imply a concave reporting function g.
Conservatism implies a concave reporting function g:
xg-E(X)= E(X)- xb  f(xg) - E[f(X))]= E[(f(X))] - f(xb) 
 g(f(xg)) - E[(g(f(X))] < E[(g(f(X))] – g(f(xb)).
10
(5)
For simplicity of exposition, we implicitly assume a priori contractual commitment to supply the goods
and no substitution between resources. The argument holds under mild substitution as well.
11
We implicitly assume that changes in the resource price are expected to last over the relevant horizon.
13
2.4
The earnings generating process, (x)=g(f(x))
The general framework focuses on the composite earnings generating process,
(x)=g(f(x)), which combines the real function f with the reporting function g. The
composite earnings generating process, =g(f(x)), is concave if both the real function f
and the reporting function g are concave. That is, low stock option based incentives, cost
stickiness and low (or no) monopolistic power (resulting in a concave real function f)
accompanied by conservative accounting rules (resulting in a concave reporting function
g) lead to a concave earnings generating process, .12 Alternatively, the composite
earnings generating process, , is convex if both the real function f and the reporting
function g are convex. That is, high stock option based incentives, cost anti-stickiness and
monopolistic power (resulting in a convex real function f) with aggressive accounting
(resulting in a convex reporting function g) lead to a convex earnings generating process,
. When one effect is convex and another effect is concave, the composite effect depends
on the relative power of each effect.13 The general specification of the composite earnings
generating process facilitates an empirical examination of the impact of each of the
effects on the shape of the earnings generating process, .
2.5
Asymmetric timeliness of earnings
How does the concavity or convexity of the earnings generating process, , affect the
degree of asymmetric timeliness of earnings? We present two approaches for addressing
this question and for measuring the degree of asymmetric timeliness of earnings.
Earnings skewness – we build on the skewness of earnings distributions to present
an analytical analysis of the impact of the concavity (convexity) of the earnings
generating process on the asymmetric timeliness of earnings. The literature frequently
utilizes earnings skewness as a proxy of conservatism (e.g., Ball et al., 2000; Kwon et al.,
2006; Garcia-Lara et al., 2009). Givoly and Hayn (2000) present negative skewness of
12
Economic theory tells us that a composite function of two concave functions is concave (Mas-Colell et
al., 1995, p. 144). Similarly, a composite function of two convex functions is convex.
13
This argument builds on MacGillivray (1986) and on Van Zwet (1970).
14
earnings over time and interpret it as driven by conservative accounting rules.14 Prior
studies infer conservatism from negatively skewed earnings distributions because bad
news is reported under conservative accounting in a more timely manner than good news.
That is, earnings skewness measures the degree to which earnings are asymmetrically
distributed. These studies assume that if conservatism leads to an immediate and
complete recognition of negative events and a delayed and gradual recognition of positive
events, it is likely to induce negatively skewed earnings distributions. This assumption,
though, has never been empirically tested.15 Prior studies implicitly assumed without
testing that conservatism is the sole source of negatively skewed earnings distributions.
However, additional determinants influencing the degree of earnings skewness may
cast doubt on the inference of conservative accounting from negatively skewed earnings.
An empirical examination can offer a broad understanding of how real economic choices
influence the degree of asymmetric timeliness of earnings. Specifically, we gain insights
into how concave and convex earnings generating processes influence the degree of
earnings skewness. To explore the skewness of distributions X and (X), we consider the
standard definition of skewness,  (Bickel and Doksum, 1977; Greene, 2010): skewness
defined as (Y)=E[(Y-y)/y]3 where the statistics y and y are the mean and standard
deviation of the distribution of random variable Y.
For a symmetric distribution, (Y)=0. For asymmetric distributions, (Y)<0 if the
“long tail” is in the negative direction, i.e., on the left-hand side, the skewness is
negative. Similarly, (Y)>0 if the “long tail” is in the positive direction, i.e., on the righthand side, the skewness is positive (Greene, 2010).
The analysis concentrates on the skewness of the earnings distribution, ((X)).
Focusing on the impact of the reported earnings function on the skewness of the reported
earnings distribution, the following proposition builds on Van Zwet (1970) in presenting
the effect of concave earnings generating process on the skewness of the earnings
14
Negative earnings skewness has also been documented by Deakin (1976), Frecka and Hopwood (1983),
and Watson (1990), Gu and Wu (2003), and Ball and Shivakumar (2005).
15
Basu (1997) and a series of subsequent studies attribute an asymmetric relation between earnings and
signals of good or bad news (stock returns) to conservatism. We extend Basu’s argument and explicitly
show how conservative accounting rules generate asymmetric distributions of reported earnings,
empirically measured by earnings skewness.
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distribution. We also extend the analysis presented by Van Zwet (1970) to convex
earnings functions.
Proposition 1
(1a). Suppose the earnings generating process π is an increasing and strictly concave
function of an economic fundamental, x. Then the ex-ante distribution of earnings is
more negatively skewed than the ex-ante distribution of the economic fundamental,
((X))<(X).
(1b). Suppose the earnings generating process π is an increasing and strictly convex
function of an economic fundamental, x. Then the ex-ante distribution of earnings is
less negatively skewed than the ex-ante distribution of the economic fundamental,
((X))>(X).
Proof appears in the appendix.
The proposition presents a relationship between the shape of the earnings generating
process and the skewness of the earnings distribution. Given a distribution of the
economic fundamental, X, and a concave (convex) earnings generating process, (X), the
resulting distribution of reported earnings is more (less) negatively skewed than the
distribution of the economic fundamental. To clarify, a smaller value for  indicates more
skewness to the left. That is, the skewness of the earnings distribution, ((X)), is smaller
(more negative) than the skewness of the distribution of the economic fundamental, (X).
Figure 1 illustrates a concave transformation of a symmetric distribution, X, into a
negatively skewed earnings distribution, (X).
[Insert Figure 1 here]
Proposition (1a) suggests that if low stock option based incentives, sticky costs, low
monopolistic power, and conservative accounting rules lead to a concave earnings
generating process, , then these effects will generate negative skewness into the
distribution of earnings. On the other hand, Proposition (1b) suggests that if high stock
option based incentives, anti-sticky costs, high monopolistic power, and aggressive
16
accounting rules yield a convex earnings generating process, , then these effects will
generate positive skewness into the distribution of earnings. Overall, the proposition
establishes the direction in which stock option based incentives, cost stickiness,
monopolistic power, and conservative accounting rules influence the skewness of
earnings distributions.16
Basu (1997) and the Khan-Watts (2009) Cscore – Assuming a piece-wise linear
specification, Khan and Watts (2009) offer a firm-year proxy of the asymmetric
timeliness of earnings based on the Basu (1997) asymmetric timeliness of earnings
notion. Specifically, Khan and Watts (2009) follow the piece-wise linear earnings-returns
specification presented by Basu (1997), where the differential slope (the Basu coefficient)
serves as a proxy of asymmetric timeliness of earnings. Khan and Watts estimate the
cross-sectional Basu regressions, specifying the Basu coefficient as a linear function of
three firm-specific characteristics – size, market-to-book ratio, and financial leverage. A
piece-wise linear specification serves as a first-order approximation for the concavity or
convexity, where a positive (negative) Basu coefficient indicates a concave (convex)
function of news (proxied by stock returns).
Basu (1997) and Khan and Watts (2009) view the Basu coefficient as a measure of
the asymmetric timeliness of earnings, which they interpret as a conservatism measure.
They assume that conservative accounting rules lead to asymmetric timeliness of
earnings because earnings are more timely or concurrently sensitive in reflecting bad
news than good news.
Our nonlinear approach directly extends Khan and Watts (2009) because a piece-wise
linear specification can serve as a first-order approximation of a concave or convex
function. Generalizing the approach in Basu (1997) and in Khan and Watts (2009), we
formally showed above that conservative accounting rules generate a concave reporting
function, which increases the concavity of the earnings generating process. Accordingly,
the Khan and Watts’ (2009) Cscore is an approximation of asymmetric timeliness of
16
In the case where some effects are concave and others are convex, the cumulative effect depends on the
relative strength of each of the components (Johnson and Kotz, 1970; Van Zwet, 1970).
17
earnings. Therefore, if real economic choices influence earnings skewness as predicted
by the proposition, then they are predicted to influence the Cscore as well.
2.6
Hypothesis
Based on the general framework presented above, we examine the impact of each of
the three real effects (stock option based incentives, cost stickiness, and monopolistic
power), on the asymmetric timeliness of earnings. The following hypothesis summarizes
the arguments.
Hypothesis 1
(1a). Stock option based incentives moderate the asymmetric timeliness of earnings
(reduce the Khan-Watts Cscore, generate positive earnings skewness).
(1b). Cost stickiness increases the asymmetric timeliness of earnings (increases the
Khan-Watts Cscore, generates negative earnings skewness).
(1c). Monopolistic power moderates the asymmetric timeliness of earnings (reduces the
Khan-Watts Cscore, generates positive earnings skewness).
3. Choice of variables and sample
This section presents our choices for the variables and sample.
3.1
Explanatory variables
Stock option based compensation – Numerous studies associate managers’ stock
option based compensation schemes with incentives to increase firm value (e.g., Jensen
and Murphy 1990; Hall and Liebman 1998; Core and Guay 1999). Focusing on
incentives for taking real actions to increase firm value, we compute the incentive ratio
for each firm-year as in Bergstresser and Philippon (2006), employing an incentive ratio,
defined as the share of increase in the CEO’s total compensation that would come from a
1% increase in the value of the equity of the firm, as follows:
INCEN it 
ONEPCTit
ONEPCTit  BONUS it  SALARYit
18
BONUS and SALARY are the CEO’s bonus and salary in year t, respectively, and
ONEPCT is the change in the value of the CEO’s equity holdings for a 1% increase in the
value
of
the
firm’s
equity.
ONEPCT
is
calculated
as
0.01×PRICE×
(SHARES+OPTIONS), where PRICE is share price at the beginning of the fiscal year,
SHARES is the number of shares held by the CEO, and OPTIONS is the number of
options held by the CEO.
We note that the incentives captured by this ratio are likely not only to encourage
managers to increase firm value by making real transactions, but also to manipulate
reported earnings (Feng et al., 2011). Testing Hypothesis (1a), we later control for a
potential effect of earnings management on both the Cscore and earnings skewness.
Cost Stickiness – We estimate cost stickiness using the firm-specific stickiness
measure introduced by Weiss (2010). Specifically, we estimate the difference between
the rate of cost decrease for recent quarters with decreasing sales and the corresponding
rate of cost increase for recent quarters with increasing sales:
 ΔCOST 
 ΔCOST 
 log 
STCKit = log 


 ΔSALE  i, τ
 ΔSALE  i, τ
 ,  {t,..,t-3},
where  is the most recent of the last four quarters with a decrease in sales and  is the
most recent of the last four quarters with an increase in sales,
SALEit = SALEit - SALEi,t-1,
COSTit = (SALEit – OIit) - (SALEi,t-1 – OIi,t-1),
and OI is operating income.
Following Weiss (2010), STCKit is defined as the difference in the cost function slope
between the two most recent quarters from quarter t-3 through quarter t, such that sales
decrease in one quarter and increase in the other. If costs are sticky, meaning that they
increase more when activity rises than they decrease when activity falls by an equivalent
amount, then the proposed measure has a negative value. For each firm-year, we compute
STCKit on the fourth quarter of the fiscal year using data from all four quarters on that
fiscal year. A lower value of STCK expresses more sticky cost behavior.
19
Monopolistic Power – We measure monopolistic power by estimating the market
share of each firm in each industry. This choice follows the conventional Herfindahl
concentration measure, assuming that higher market share of a firm indicates greater
market power (Li 2010; Cheng et al., 2012). We define MPit as the sales of firm i in
quarter t divided by the total sales of all firms in the industry, where the industry is
defined by its four-digit SIC code. A high market share indicates greater market power
than a low market share (Tirole, 1988).
3.2
Asymmetric timeliness of earnings
Following the discussion in Section 2.5, we utilize the following two measures:
Earnings Skewness - measures the degree to which earnings are asymmetrically
distributed. Its estimation refers to distributions of earnings at each point of time. Since
skewness of a distribution cannot be estimated from a single observation, prior studies
use a rolling window around the relevant period, assuming that the distribution is
stationary within that window. Givoly and Hayn (2000) use annual data with a five-year
window. Similarly, Gu and Wu (2003) use quarterly data and employ a window of eight
quarters prior to the relevant quarter and eight quarters subsequent to the relevant quarter
for estimating earnings skewness for that quarter. We follow Gu and Wu (2003) in
assuming a window of 17 quarters to estimate earnings skewness. Focusing on real
effects, our main variable of interest is operating income (Givoly and Hayn, 2000; Gu
and Wu, 2003). We follow Givoly and Hayn (2000) in deflating operating income by
total assets at the beginning of quarter t, (OI/ASSETS). Using deflated variables mitigates
heteroscedasticity in the regressions. We require data availability for at least five quarters
in each window and exclude observations with values of OI/ASSETS below -1 or above 1.
We estimate skewness as (Y)=E[(Y-y)/y]3, where the statistics y and y are the mean
and standard deviation of the distribution of random variable Y.
SKEWit is estimated for firm i in year t using 17 actual values of quarterly operating
income from the eighth quarter prior to the end of year t till the eighth quarter subsequent
to the end of year t. Operating income is deflated by total assets on prior quarter end.
20
The Khan-Watts (2009) Cscore – Our second firm-year specific measure of
asymmetric timeliness of earnings, labeled KW_CSCORE, is the measure developed by
Khan and Watts (2009), building on Basu (1997). Ettredge et al.,(2012) find that the
KW_CSCORE and Basu’s DT parameter provide similar results in measuring
conservatism surrounding overstatements of earnings.17
KW_CSCORE is estimated using annual Basu (1997) regressions, specifying the
differential timeliness coefficient as a linear function of company size, market-to-book
equity ratio, and financial leverage. To obtain the KW_CSCORE, we follow the
procedures described in Khan and Watts (2009, Section 2) and substitute firm size,
market-to-book and leverage into the estimated regression model.18 Khan and Watts
(2009) estimate the timeliness of good news and bad news and document evidence
consistent with the KW_CSCORE increasing with conservatism.
3.3
Sample
We downloaded Execucomp data on CEO compensation from fiscal years 1992 to
2008, resulting in 27,909 firm-year observations. We exclude financial institutions (firms
with 6 as the first digit of their SIC code), observations with non-positive values of sales,
and observations without available data for computing SKEW, KW_CSCORE, STCK, and
MP. We note that the data availability requirements for computing SKEW on a window
with 17 quarters and for computing STCK result in loss of data (see Weiss 2010). The
sample-selection criteria yield a total of 20,999 firm-year observations.
3.4
Descriptive statistics
Table 1 reports summary statistics for SKEW and KW_CSCORE estimates. The mean
value of SKEW is -0.0378, negative and significant (tested as in Sheskin, 2004). This
17
A number of studies utilized a time-series Basu measure as a firm-specific measure of conservatism (e.g.,
Roychowdhury and Watts, 2007; Lafond and Roychowdhury, 2009; Hui et al., 2012). Khan and Watts
(2009) offer a firm-year specific measure of conservatism in the spirit of Basu’s measure. While there has
been some debate about the validity of measures derived from the Basu (1997) model (Givoly et al., 2007;
Dietrich et al., 2007; Patatoukas and Thomas, 2011), Ettredge et al., (2012) report that the Khan and Watts
(2009) measure properly captures expected variations in conservatism.
18
See Khan and Watts (2009, p. 136) for details of the estimation procedure.
21
statistic suggests that earnings distributions are negatively skewed (left-tailed), consistent
with results reported by Givoly and Hayn (2000) and Gu and Wu (2003). The mean value
of KW_CSCORE, 0.1124, in line with Khan and Watts (2009).
Table 2 reports the Pearson and the Spearman correlation coefficients. The Pearson
(Spearman) correlation between SKEW and KW_CSCORE is -0.180 (-0.158), significant
at the 5% level. Keeping in mind that greater earnings asymmetry is captured by lower
values of SKEW (more negative values of SKEW) and by higher values of KW_CSCORE,
these correlations confirm that the two metrics are reasonably consistent with each other.
The correlations between each of the real choices (INCEN, STCK and MP) and SKEW
are positive and significant at the 5% level. Keeping in mind that more negative values of
STCK indicate more sticky costs, these correlations are in line with the hypothesis. Also,
the correlations between each of the real choices (INCEN, STCK and MP) and
KW_CSCORE are negative and significant at the 5% level, again in line with the
hypothesis.
[Insert Tables 1 and 2 here]
4. The effect of real economic choices on asymmetric timeliness of earnings
We utilize regression analyses for testing the association between the three real
choices and the asymmetric timeliness of earnings. We start by separately regressing
SKEW and KW_CSCORE on the three real choices: INCEN, STCK and MP. In estimating
all the following regression models, we use pooled cross-sectional regressions, include
annual indicator variables, and cluster observations by firm to eliminate serial correlation
and heteroscedasticity, as suggested by Petersen (2009):
Model 1
SKEWit
=  +1 INCENit + 2 STCKit + 3 MPit + it.
(1a)
KW_CSCOREit
=  +1 INCENit + 2 STCKit + 3 MPit + it.
(1b)
Results from estimating model 1 are reported in Table 3. (For completeness, the table
includes also partial models). Using SKEW as a dependent variable in model (1a), we find
a positive association between INCEN and SKEW (0.256, t-value=2.33), a positive
22
association between STCK and SKEW (0.018, t-value=2.01), and a positive association
between MP and SKEW (0.186, t-value=2.45). The findings suggest that high stock
option based incentives, anti-sticky costs, and high monopolistic power are associated
with less negatively skewed earnings.19 Therefore, these three real choices significantly
influence the degree of earnings skewness.
Similarly, using KW_CSCORE as a dependent variable, coefficient estimates of
model (1b) reported in Table 3 (right-most column) show a negative association between
INCEN and KW_CSCORE (-0.062, t-value=-2.76), a negative association between STCK
and KW_CSCORE (-0.012, t-value=-3.03), and a negative association between MP and
KW_CSCORE (-0.150, t-value=-5.65). Since a higher value of KW_CSCORE indicates
greater asymmetric timeliness of earnings, the findings suggest that high stock option
based incentives, anti-sticky costs, and high monopolistic power are associated with
lower values of KW_CSCORE, hence moderate the degree of asymmetric timeliness of
earnings. Again, the three real choices significantly influence the degree of
KW_CSCORE.
Particularly, both high stock option based incentives and high monopolistic power
generate positively-skewed earnings and reduce KW_CSCORE. In contrast, sticky costs
generate negatively-skewed earnings and increase KW_CSCORE. That is, these three real
choices affect the degree of asymmetric timeliness of earnings in the directions predicted
by the hypothesis.
Importantly, we note that the estimated intercepts in model (1a) are negative and
highly significant, suggesting that earnings are, on average, negatively skewed after
controlling for the three real economic choices. This finding is consistent with the
interpretation that financial reporting is, on average, conservative after controlling for the
three real economic choices. Similarly, the estimated intercepts in model (1b) are positive
and highly significant, suggesting that KW_CSCORE is, on average, positive after
controlling for the three real economic choices. Again, the finding supports the
19
Keeping in mind that lower values of STCK indicate more sticky costs, the positive association suggests
that more sticky costs are associated with more negatively skewed earnings. That is, sticky costs generate
left-skewed earnings distributions.
23
interpretation that financial reporting is, on average, conservative after controlling for the
three real economic choices.
[Insert Table 3 here]
To gain further insights on the relative impact of the three real choices, we regress
SKEW and KW_CSCORE on three dummy variables: INCEN_DUM, STCK_DUM and
MP_DUM. We estimate the following model:
Model 2
= +1 INCEN_DUMit+2 STCK_DUMit+3 MP_DUMit +i,
(2a)
KW_CSCOREit= +1 INCEN_DUMit+2 STCK_DUMit+3 MP_DUMit+ I,
(2b)
SKEWit
where
INCEN_DUMit equals one if INCENit exceeds the median and zero otherwise.
STCK_DUMit equals -1 if STCKit < 0 and zero otherwise.20
MP_DUMit equals one if MPit exceeds the median and zero otherwise.
Results from estimating model 2 are reported in Table 4. Consistent with the earlier
results, we find positive and significant associations between each of the three dummy
variables and SKEW. Results from estimating model (2a) show that the coefficients on
STCK_DUM and on MP_DUM are significantly smaller than the coefficient on
INCEN_DUM (p-value<0.01), indicating that the relative impact of stock option based
incentives on the degree of earnings skewness is greater than the impact of cost stickiness
or monopolistic power.
In similar vein, we estimate model (2b) and find negative and significant associations
between each of the three real choices and KW_CSCORE. The results show that the
magnitudes of the coefficients on STCK_DUM and on MP_DUM are significantly
smaller than the magnitudes of the coefficient on INCEN_DUM (p-value<0.01),
indicating that the relative impact of stock option based incentives on KW_CSCORE is
greater than the impact of cost stickiness or monopolistic power.
As before, the estimated intercepts in model (2a) are negative and significant,
whereas the estimated intercepts in model (2b) are positive and significant. These results
20
We use -1 because more negative values of STCK indicate more sticky costs.
24
further support an interpretation that financial reporting is, on average, conservative after
controlling for the three real economic choices.
[Insert Table 4 here]
5. Reporting choices: Earnings management and special items
In this section, we add two reporting choices to our model specification, which
highlight complementary aspects of the evidence presented in the prior section.
First, Hanna (2002) and Watts (2003b) argue that active earnings management can
partially explain Basu’s (1997) findings – a non-conservatism explanation.21 Their
argument says that manipulative write-offs generating big baths are likely to inflate the
Basu measure and induce negative earnings skewness. If the stock market does not fully
recognize reporting manipulations, then the stock price effect depends on whether
management classifies the manipulative write-off as a nonrecurring charge and, if so,
whether investors ignore nonrecurring charges in valuing the firm. If the write-off is not
classified as a nonrecurring charge, then investors are likely to treat it no differently than
any other earnings component, without affecting the Basu measure.
Alternatively, if the manipulative write-off is classified as a nonrecurring charge and
investors ignore it for valuation purposes, then in a Basu regression the coefficient on
negative returns relating to nonrecurring charges is zero, indicating no association
between these charges and stock returns, which moderates the Basu measure. Also,
manipulative write-offs generating big baths are expected to generate negative skewness
into earnings distribution regardless of their effect on stock prices.
In models 1 and 2, we employed INCEN as a proxy of incentives to take real actions
that generate profits and increase firm value. Now, we add an ex-post reporting choice –
big bath. Hanna (2002) and Watts (2003b) argue that the effect of earnings management
on the degree of asymmetric timeliness of earnings is likely to be in the same direction as
conservatism. That is, big bath is predicted to introduce negative earnings skewness and
to inflate the Khan and Watts Cscore.
21
See also Gao (2013).
25
Second, we add a conservatism proxy to our analyses. Specifically, special items are
material items that are considered unusual in nature or occur infrequently. Callen et
al.,(2010) argue that special items are one of the tools through which accounting
conservatism is facilitated. Frankel and Roychowdhury (2009) report that conservatism
influences cross-sectional variation in the persistence of negative special items. The
dominance of special or unusual losses reflects the conservative bias of accrual
accounting, which requires early recognition of declines in asset values but tends to delay
recognition of most gains until realized. Controlling for negative special items can further
check the robustness of the earlier evidence because special items are generally
engendered in the process of preparing financial statements after the accounting period is
over. That is, a firm’s choice to report special items tends to involve write-offs made in
the reporting process, not real choices made during the accounting period. Since negative
special items facilitate the implementation of conservative accounting, we utilize
negative special items as a signal of conservative accounting policy. Since SKEW is
estimated using operating income, which does not include special items, we predict that
SKEW is more negatively skewed for firms with a more conservative accounting policy.
In similar vein, we expect higher values of KW_CSCORE for firms with a more
conservative accounting policy.Further testing our hypothesis, we test whether the
significant association between the real economic choices and asymmetric timeliness of
earnings holds when controlled for two reporting choices: big baths and special items.
We expand model 1 by adding two dummy variables:
Model 3
SKEWit
=  + 1 INCENit + 2 STCKit + 3 MPit
+4 SI_DUMit + 5 BIG_BATH_DUMit + it.
KW_CSCOREit
(3a)
=  + 1 INCENit + 2 STCKit + 3 MPit
+4 SI_DUMit + 5 BIG_BATH_DUMit + it.
(3b)
where
SI_DUMit equals 1 if firm i reports negative special items for year t and zero otherwise.
26
BIG_BATH_DUMit equals 1 if firm i misses financial analysts' consensus (mean)
earnings forecasts for year t and actual reported earnings before extraordinary items is
lower than actual reported earnings before extraordinary items for the prior year by at
least 20% of shareholders' equity at year end, and zero otherwise.
Results from estimating models (3a) and (3b) are reported in Table 5. (For
completeness, the table includes also partial models). Coefficient estimates for SI_DUM
are -0.016 (t-value=-2.46) in model (3a) and 0.032 (t-value=3.33) in model (3b),
suggesting that negative special items generate negative earnings skewness and inflate
KW_CSCORE, hence increasing the degree of asymmetric timeliness of earnings.
Coefficient estimates for BIG_BATH_DUM are -0.013 (t-value=-1.98) in model (3a) and
0.091 (t-value=6.77) in model (3b), suggesting that big baths generate negative earnings
skewness and inflate KW_CSCORE, hence increasing the degree of asymmetric
timeliness of earnings.
More important for testing the hypothesis, coefficient estimates for INCEN, STCK,
and MP remain significant and consistent with the earlier evidence. We conclude that real
economic choices are significantly associated with both measures of asymmetric
timeliness of earnings, as predicted in the hypothesis.
Once more, the estimated intercepts in model (3a) remain negative and significant,
whereas the estimated intercepts in model (3b) remain positive and significant in the
presence of the two control variables. These results further confirm the interpretation that
financial reporting is, on average, conservative. Moreover, the findings suggest that
negative special items, SI_DUM, and big baths, BIG_BATH_DUM, generate some of the
widely documented asymmetric timeliness of earnings.
6. The difference between earnings skewness and cash flow skewness
We find it important to shed light on another subtle aspect of conservatism. Ball et al.,
(2000), Kwon et al., (2006), and Garcia-Lara et al., (2009) utilize earnings skewness as a
proxy for inferring conservatism in financial reporting. The assumption underlying this
inference is that bad news is reported under conservative financial reporting in a more
27
timely manner than good news. If conservatism leads to an immediate and complete
recognition of negative events and a delayed and gradual recognition of positive events, it
is likely to induce a negatively skewed earnings distribution. This notion serves as the
basis for using earnings skewness as a proxy for conservatism. To clarify, the hypothesis
predicts that the three real economic choices, above and beyond reporting choices,
influence the skewness of the earnings distributions.
However, Givoly and Hayn (2000), Ahmed and Duellman (2013) and others argue
that conservative accounting rules influence earnings, not cash flows. For that reason,
they infer conservatism from the difference between the skewness of earnings
distribution and the skewness of the cash flow distribution. This distinction is meaningful
in our context. While conservative accounting rules influence reported earnings but do
not affect cash flow, our three real choices affect both earnings and cash flows. Hence,
there is no reason to expect that real choices will be associated with the difference
between earnings skewness and cash flow skewness.
We test the association between the three real choices (INCEN, STCK, and MP) and
the difference between the skewness of earnings and the skewness of the cash flows. To
do this, the dependent variable in models (1a) and (2a), earnings skewness, is replaced
with the difference between earnings skewness and cash flow skewness. We estimate the
following regression model:
Model 4
SKEW_DIFit
=  + 1 INCENit + 2 STCKit + 3 MPit
+4 SI_DUMit + 5 BIG_BATH_DUMit + it,
(4)
where SKEW_DIFit is the difference between the skewness (SKEW) in the firm’s
operating income and the firm’s cash flow from operations computed for firm i on year t.
Results from estimating model 4 are reported on the last three columns of Table 5
(for completeness partial models are also reported) The findings indicate insignificant
associations between INCEN and SKEW_DIF, between STCK and SKEW_DIF, as well as
between MP and SKEW_DIF. Controlling for the two reporting choices, negative special
items and big baths (right most column of Table 5), the coefficient estimates of STCK and
28
MP remain insignificant, whereas the coefficient estimate of INCEN is marginally
significant (0.018, t-value=1.88). Overall, the findings suggest that the difference
between the skewness of earnings and the skewness of the cash flows is insensitive to the
three real economic choices, but is sensitive to the two reporting choices. These results
are in line with the hypothesis and support the presented framework.
There is a compelling insight here for future research on conservatism. Future
conservatism studies are expected to utilize the difference between earnings skewness
and cash flow skewness as a proxy for conservatism, rather than earnings skewness per
se, because the difference between earnings skewness and cash flow skewness is less
sensitive to real choices than earnings skewness. This difference in skewness has a
meaningful advantage – it will allow future studies to infer conservatism with reasonable
confidence that real choices do not bias the inference due to omitted correlated variables.
[Insert Table 5 here]
7. Sensitivity analyses
7.1.
Variation – Portfolio analysis
To gain insights on the variation in the degree of asymmetric timeliness of earnings
introduced by real economic choices, we compare two particular portfolios: a portfolio
where all three real choices intensify the asymmetric timeliness of earnings (low stock
option based incentives, sticky costs, and low monopolistic power) with a portfolio where
all three real choices moderate the asymmetric timeliness of earnings (high stock option
based incentives, anti-sticky costs, and high monopolistic power). We classify our sample
into portfolios based on INCEN_DUM, STCK_DUM, and MP_DUM.
Results from the portfolio comparison are reported in Table 6. The mean value of
SKEW in the first portfolio, where the asymmetric timeliness of earnings is intense, is 0.098. In contrast, the mean value of SKEW in the second portfolio, where the
asymmetric timeliness of earnings is moderate, is 0.069. The difference, -0.167, is
significant at the 1% level.
Similarly, the mean value of KW_CSCORE in the first portfolio is 0.179, whereas the
mean value of KW_CSCORE in the second portfolio is 0.047. The difference, 0.132, is
29
significant at the 1% level. That is, the mean KW_CSCORE is 3.8 (=0.179/0.047) times
greater in the first portfolio than in the second portfolio, indicating a substantial variation.
Interestingly, the difference in the mean value of SKEW_DIF between the two
portfolios is insignificant – see the two columns on the right-hand side of Table 6. This
insignificant difference shows that real choices do not influence the difference between
earnings skewness and cash flow skewness.
[Insert Table 6 here]
7.2
Additional robustness checks
We performed additional robustness checks to increase our confidence in the
findings. First, because MP is correlated with firm size, which is used in the estimation of
KW_CSCORE, we replace it with a conventional estimate of Lerner’s index (1934): Lit is
gross margin of firm i in quarter t computed as gross profits divided by sales minus the
industry average gross margin, where industry is defined by a four-digit SIC code.
Elzinga and Mills (2011) suggest that Lerner’s index captures firms’ price-setting
discretion, which is in line with the framework we present in Section 2. Results from
estimating models 1 and 2 are qualitatively the same (not reported for brevity).
Second, in estimating the regression models, we employ an alternative estimation
procedure to account for the standard error of the estimates, which may understate the
true standard error due to potential serial correlation. As we calculate the skewness of
earnings distributions using a rolling window, successive quarterly estimates of skewness
may be serially correlated and a portion of this serial dependence might persist in the
regression residuals. If this is the case, successive cross-sections of the regression
residuals may be correlated and so the coefficient estimates may also be correlated over
time. The true earnings skewness itself may also be positively autocorrelated.
Addressing this issue, we follow Kothari et al., (2002) in computing standard errors
adjusted for potential dependence using the Newey and West (1987) procedure to
incorporate the effect of serial correlation. We correct for potential serial dependence in
the coefficients by estimating autocorrelations with eight lags because beyond the eighth
lag they are negligible. The results (not reported for brevity) are qualitatively the same.
30
Third, testing the sensitivity of the findings to the window size, we also estimated
SKEW using nine (rather than 17) quarter windows. The results from estimating the
regression models (not reported for brevity) support the hypothesis, but the statistical
significance of the estimated coefficients is weaker.
8. Summary
This study views earnings reported in financial statements as the outcome of two
nonlinear processes: (i) profit generation through real economic activities, and (ii)
conservative accounting rules that transform these profits into reported earnings. This
view facilitates new tests for examining how real economic choices influence the degree
of asymmetric timeliness of earnings. The results suggest that real economic choices
influence the degree of asymmetric timeliness of earnings as measured by earnings
skewness and by the Khan and Watts Cscore. Moreover, real economic choices introduce
substantial variation into earnings skewness and the Khan and Watts Cscore.
Results suggest that real economic choices generate substantial variation in the
asymmetric timeliness of earnings. These findings hold after controlling for the impact of
earnings management and special items. Overall, the results suggest that controlling for
real economic choices is crucial for proper inference of conservatism from the
asymmetric timeliness of earnings.
31
Appendix
Proof of Proposition (1a)
The proof makes use of the following lemma.
Lemma 1: Let
~
be a concave function which changes its sign twice at the points
x1  x2 and assume ~ satisfies ~(0)  0 . Then x1  0  x2 .
Proof of Lemma 1: From the continuity of
~
it follows that ~( x1 )  ~( x2 )  0 . There
are two options:
  0 x  x1

~
 ( x )   0 x1  x  x2
 0 x x
2

  0 x  x1

~
 ( x )   0 x1  x  x2
 0 xx
2

The right option contradicts convexity. Since ~(0)  0 it follows that x1  0  x2 .
Q.E.D (of Lemma 1).
Similarly to Van Zwet (1970, Theorem 2.1.1), we assume W.L.O.G. that
E ( X )  E ( ( X ))  0 and  ( X )   ( ( X ))  1 . Hence it is enough to show that
E ( X 3 )  E ( 3 ( X )) .
We use Jensen’s inequality on a concave function  (0)   ( E ( X ))  E ( ( X ))  0 .
The concave function  ( x )  x changes its sign exactly twice and we denote these points
by x1  x2 . To see this, note that since E ( ( X )  X )  0 it must change its sign at least
once. Assume it changes its sign exactly once and that  ( x )  x for x  x0 and
 ( x )  x for x  x0 . The function  ( x )  x is strictly increasing:
 ( ( x)  x)( ( x)  x)dF ( x)  2 x  ( ( x)  x)dF ( x) 2 x ( E ( ( X ))  E ( X ))  0
0
I
0
I
On the other hand,
 ( ( x )  x )( ( x )  x )dF ( x )   
I
I
2
( x )dF ( x )   x 2 dF ( x )  E ( 2 ( X ))  E ( X 2 )  0 ,
I
which contradicts the assumption. The case that  ( x )  x for x  x0 and  ( x )  x for
x  x0 is similar. Since a concave function changes its sign at most twice, we conclude
32
that  ( x )  x changes its sign exactly twice. Using Lemma 1 (with ~( x )   ( x )  x ) it
follows that
x1  0  x2  ( x1 )  x1  0  (0)  0  ( x2 )  x2  0 .
Since  is an increasing continuous function there is a unique x1  x3  0 such that
 ( x3 )  0 . The following sketch is helpful:
y x
y   ( x)
x1
x3
x2
Define:
h ( x )   2 ( x )  x ( x )  x 2
f ( x, t1 , t2 ) 
3
(t1  t2 )( ( x )  x )  3t1t2
2
Note that h( x1 )  3x12 , f ( x1 , x1 , x2 )  3x12 , h( x2 )  3x22 and f ( x2 , x1 , x2 )  3x22 . Hence,
h( x1 )  f ( x1 , x1 , x2 )  h( x2 )  f ( x2 , x1 , x2 )   ( x1 )  x1   ( x2 )  x2  0
We will show that h( x)  f ( x, x1 , x2 ) and  ( x )  x have opposite signs for all x  x1 , x2 .
To see this, consider the partial derivative of f with respect to t1 and t 2 :
 0
f ( x, t1 , x2 ) 3
 ( ( x )  x )  3x2  
t1
2
 0
 0
f ( x, t1 , x2 ) 3
 ( ( x )  x )  3x1  
t 2
2
 0
x  x2
x  x2
x  x1
x  x1
The sign of h( x)  f ( x, x1 , x2 ) will be considered in each of the five sub-regions of I .
Consider x  x1 .
33
For a fixed x, t1  x1 , f is a decreasing function of t 2 . Since  ( x)  x  x1  0 :
f ( x, x1 , x2 )  f ( x, x1 ,0) 
3
x1 ( ( x )  x )   2 ( x )  x 2  x ( x )  h( x )
2
Consider x1  x  x3 .
For a fixed x, t1  x1 , f is an increasing function of t 2 . Since x1  x   ( x)  0 :
f ( x, x1 , x2 )  f ( x, x1 ,0)  h( x)
Consider 0  x  x2 .
For a fixed x, t1  x1 , f is a decreasing function of t1 . Since the range 0  x   ( x)  x2 :
f ( x, x1 , x2 )  f ( x,0, x2 ) 
3
x2 ( ( x )  x )   2 ( x )  x 2  x ( x )  h( x )
2
Consider x  x2 .
For a fixed x, t2  x2 , f is an increasing function of t1 . Since 0  x2   ( x)  x :
f ( x, x1 , x2 )  f ( x,0, x2 ) 
3
x2 ( ( x )  x )   2 ( x )  x 2  x ( x )  h( x )
2
Finally, consider x3  x  0 . f is an increasing function of t 2 and a decreasing function
of t1 . Since x1  x  0   ( x)  x2 :
f ( x, x1 , x2 )  f ( x,  ( x ), x2 )  f ( x,  ( x ), x ) 
3
( ( x )  x ) 2  3 ( x ) x   2 ( x )  x 2   ( x ) x  h( x )

2
0
It follows that the signs of h( x)  f ( x, x1 , x2 ) are negative for x1  x  x2 and positive
outside this range. The signs of  ( x )  x are opposite. Hence their product is negative for
all x  x1 , x2 and 0 for x  x1 , x2 :
 (h( x )  f ( x, x , x ))( ( x )  x )dF ( x )  0
1
2
I

(1)
 h( x )( ( x )  x )dF ( x )   f ( x, x , x )( ( x )  x )dF ( x )
1
I
2
I
Consider each side of the last inequality:
h( x )( ( x )  x )   3 ( x )  x 3 
 h( x)( ( x)  x)dF ( x)  E (
I
and,
3
( X ))  E ( X 3 ) ( 2)
34
3
( x1  x 2 )( 2 ( x )  x 2 )  3x1 x 2 ( ( x )  x )
2
3
f ( x, x1 , x 2 )( ( x )  x )dF ( x )  ( x1  x 2 ) E ( 2 ( X )  E ( X 2 )  3x1 x 2 E ( ( X )  E ( X )  0 (3)





2
0
0
f ( x, x1 , x 2 )( ( x )  x ) 

I

Combining (1)-(3), the result follows.

Q.E.D.
Proof of Proposition (1b)
In Theorem 2.2.1, Van Zwet (1970) showed that if  is an increasing convex function
then 1 ( ( X ))  1 ( X ) . With the additional assumptions of continuity of X and strict
convexity of  the inequality is strict. The proof follows the same line that was used in
showing that the inequality in Proposition (1a) is strict.
Q.E.D.
35
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40
FIGURE 1
A Concave Function Transforms a Symmetric Distribution into a Negatively Skewed
Distribution
This figure illustrates how a concave function transforms a symmetric distribution into a negatively skewed
distribution. X is a discrete random variable evenly distributed between X=1 and X=11.The squares on the
X axis depict the realizations of the random variable X. The distribution of X is thus symmetric with
E[X]=MED[X]=6. Both 1(X) and 2(X)=0. We use the concave function Y=LN(X) to demonstrate how a
concave transformation induces a negatively skewed distribution, Y. The distribution Y=LN(X) is depicted
with round dots on the Y axis. The realizations of Y range between 0 and 2.3. We observe that Y is
negatively skewed: E[Y]=1.6<MED[Y]=1.8, i.e., 2(Y)<0. Similarly, the dots are relatively far apart under
E[Y]=1.6 and close together above E[Y]=1.6, resulting in 1(Y)<0. Thus, under both1 and 2, the
distribution Y is negatively skewed.
41
TABLE 1
Descriptive Statistics
Variables
N
Mean
Median
Std. Dev.
SKEW
20,999
-0.0378
-0.0080
0.9665
KW_CSCORE
20,999
0.1124
0.1033
0.1466
INCEN
20,999
0.2769
0.2074
0.2232
STCK
20,999
-0.0530
-0.0379
1.2060
MP
20,999
0.1541
0.0768
0.1897
SI_DUM
20,999
0.2874
0
0.4523
BIG_BATH_DUM
20,999
0.0271
0
0.1562
SKEW_DIF
20,538
-0.0830
-0.0249
0.4886
Variable definitions:
SKEWit is an estimator of skewness defined as E[(Y-y)/y]3 where the statistics y and y are the mean and
standard deviation of the distribution of random variable Y. SKEWit is estimated for firm i on year t using
17 actual values of quarterly operating income from the eighth quarter prior to the end of year t till the
eighth quarter subsequent to the end of year t. Operating income is deflated by total assets on prior quarter
end.
SKEW_DIFit is the difference between the skewness (SKEW) in the firm’s operating income and the firm’s
cash flow from operations computed for firm i on year t.
KW_CSCOREit is the firm-year-specific asymmetric timeliness score developed by Khan and Watts
(2009).
INCENit reflects the sensitivity of the CEO’s compensation to a change in the share prices,
computed according to Bergstresser and Philippon (2006):
ONEPCTi.t
INCENTIVE _ RATIOi ,t 
ONEPCTi.t  SALARYi.t  BONUS i.t
where BONUS and SALARY are the CEO’s bonus and salary, respectively, and ONEPCT is the change in
the value of the CEO’s equity holdings for a 1% increase in the value of the equity computed at the
beginning of the fiscal year.
 COST 
 COST 
STCKit = log
  log
 ,
 SALE  i, 
 SALE  i, 
 ,  {t,..,t-3}, where  is the most recent quarter with
sales decrease and  is the most recent quarter with sales increase. COSTit is operating costs for firm i in
quarter t. SALEit is sales for firm i in quarter t.
MPit is market power estimated as the sales of firm i in quarter t divided by the total sales of all firms in the
industry, where industry is defined by a four-digit SIC code.
SI_DUMit equals 1 if firm i reports negative special items for year t and zero otherwise.
BIG_BATH_DUMit equals 1 if firm i misses financial analysts’ consensus (mean) earnings forecasts for
year t and actual reported earnings before extraordinary items is lower than actual reported earnings before
extraordinary items for the prior year by at least 20% of shareholders’ equity at year end, and zero
otherwise.
42
TABLE 2
Correlation Coefficients
Pearson coefficients are reported above the diagonal line and Spearman coefficients are reported below the
line.
SKEW SKEW_DIF KW_CSCORE INCEN
STCK
MP
SI_DUM
BIG_BATH_DUM
SKEW
1
0.254
-0.180
0.057
0.012
0.046
-0.062
-0.054
SKEW_DIF
0.287
1
-0.188
0.014
0.010
0.002#
-0.070
-0.019
KW_CSCORE
-0.158
-0.158
1
-0.076
-0.081
-0.164
0.076
0.097
INCEN
0.104
0.016
-0.109
1
-0.015
0.028
-0.036
-0.040
STCK
0.020
-0.024
-0.094
-0.004#
1
0.006#
0.000#
-0.041
MP
0.039
-0.014
-0.183
0.052
0.010#
1
0.033
-0.034
SI_DUM
-0.071
-0.084
0.074
-0.024
0.001#
0.047
1
0.187
BIG_BATH_DUM
-0.046
-0.014
0.110
-0.056
-0.053
-0.047
0.194
1
All correlations are significant at the 5% level, with the exception of correlations marked by #.
Variable definitions are in Table 1.
43
TABLE 3
The effect of real economic choices on asymmetric timeliness of earnings
The table presents coefficients from estimating the following regression models:
Model 1
=  + 1 INCENit + 2 STCKit + 3 MPit + it.
(1a)
KW_CSCOREit =  + 1 INCENit + 2 STCKit + 3 MPit + it.
(1b)
SKEWit
Model
Dependent
variable
Intercept
-0.271
(-4.12)
INCEN
0.262
(2.19)
(1a)
(1b)
SKEW
KW_CSCORE
-0.019
(-1.90)
0.016
(1.91)
STCK
MP
N
Adj R2
-0.222
(-3.78)
-0.292
(-4.48)
0.135
(10.97)
0.256
(2.33)
-0.065
(-2.90)
0.018
(2.01)
0.198
(2.23)
0.186
(2.45)
0.092
(10.33)
0.136
(12.55)
0.150
(12.10)
-0.062
(-2.76)
-0.013
(-4.10)
-0.012
(-3.03)
-0.152
(-5.41)
-0.150
(-5.65)
20,999
20,999
20,999
20,999
20,999
20,999
20,999
20,999
0.076
0.021
0.055
0.101
0.065
0.032
0.077
0.105
We use pooled cross-sectional regressions, include annual indicator variables, and cluster observations by
firm to eliminate serial correlation and heteroscedasticity, as suggested by Petersen (2009). t-values are
reported in parentheses.
Variable definitions are in Table 1.
44
TABLE 4
The effect of real economic choices on asymmetric timeliness of earnings – relative
analysis
The table presents coefficients from estimating the following regression models:
Model 2
= + 1 INCEN_DUMit+ 2 STCK_DUMit+3 MP_DUMit +i.
(2a)
KW_CSCOREit= +1 INCEN_DUMit+ 2 STCK_DUMit+3 MP_DUMit+ i.
(2b)
SKEWit
Model
Dependent
variable
Intercept
-0.250
(-4.18)
INCEN_DUM
0.108
(2.42)
(2a)
(2b)
SKEW
KW_CSCORE
-0.021
(-1.88)
0.009
(1.78)
STCK_DUM
MP_DUM
N
Adj R2
-0.206
(-3.67)
-0.255
(-4.02)
0.131
(11.44)
0.107
(2.33)
-0.084
(-3.45)
0.013
(2.00)
0.020
(2.12)
0.016
(2.18)
0.088
(8.74)
0.141
(14.32)
0.146
(12.53)
-0.081
(-3.47)
-0.028
(-3.41)
-0.027
(-2.80)
-0.072
(-7.18)
-0.070
(-8.65)
20,999
20,999
20,999
20,999
20,999
20,999
20,999
20,999
0.061
0.015
0.032
0.058
0.045
0.022
0.826
0.095
We use pooled cross-sectional regressions, include annual indicator variables, and cluster observations by
firm to eliminate serial correlation and heteroscedasticity, as suggested by Petersen (2009). t-values are
reported in parentheses.
INCEN_DUMit equals one if INCENit exceeds the median and zero otherwise.
STCK_DUMit equals -1 if STCKit < 0 and zero otherwise.
MP_DUMit equals one if MPit exceeds the median and zero otherwise.
Definitions of SKEW and KW_CSCORE are in Table 1.
45
TABLE 5
The effect of special items and earnings management on asymmetric timeliness of
earnings
The table presents coefficients from estimating the following regression models:
Model 3
SKEWit
KW_CSCOREit
=  +  1 INCENit + 2 STCKit + 3 MPit
+4 SI_DUMit + 5 BIG_BATH_DUMit + it.
=  +  1 INCENit +  2 STCKit + 3 MPit
+4 SI_DUMit + 5 BIG_BATH_DUMit + it.
(3a)
(3b)
Model 4
SKEW_DIFit
=  + 1 INCENit +  2 STCKit + 3 MPit
+4 SI_DUMit + 5 BIG_BATH_DUMit + it.
(4)
Model
(3a)
(3b)
(4)
Dependent
variable
SKEW
KW_CSCORE
SKEW_DIF
Intercept
-0.092
(-4.68)
-0.271
(-4.68)
0.100
(7.82)
0.130
(11.95)
-0.053
(-2.98)
-0.064
(-3.33)
Real economic choices
INCEN
0.258
(2.41)
-0.053
(-2.78)
0.016
(0.98)
0.018
(1.88)
STCK
0.019
(2.11)
-0.012
(-1.98)
0.005
(0.55)
-0.002
(-0.85)
MP
0.182
(2.55)
-0.147
(-4.45)
0.000
(0.23)
0.009
(1.39)
Reporting choices
SI_DUM
-0.012
(-2.12)
-0.016
(-2.46)
0.030
(2.89)
0.032
(3.33)
-0.017
(-2.34)
-0.019
(-2.42)
BIG_BATH_DUM
-0.024
(-2.13)
-0.013
(-1.98)
0.088
(6.52)
0.091
(6.77)
-0.020
(-2.25)
-0.034
(-2.89)
N
20,999
20,999
20,999
20,999
20,538
20,538
20,538
Adj R2
0.035
0.112
0.068
0.135
0.025
0.001
0.023
We use pooled cross-sectional regressions, include annual indicator variables, and cluster observations by
firm to eliminate serial correlation and heteroscedasticity, as suggested by Petersen (2009). t-values are
reported in parentheses. Variable definitions are in Table 1.
46
TABLE 6
Portfolio analysis
SKEW
Portfolio
All three
real choices
intensify
the degree
of
asymmetric
timeliness
of earnings
All three
real choices
moderate
the degree
of
asymmetric
timeliness
of earnings
 Low stock
option based
incentives
(INCEN
below
median)
 Sticky costs
(STCK≤0)
 Low
monopolisti
c power
(MP below
median)
(N=3,233)
 High stock
option based
incentives
(INCEN
above
median)
 Anti-sticky
costs
(STCK>0)
 High
monopolisti
c power
(MP above
median)
(N=2,970)
Difference
** significant at the 1% level
KW_CSCORE
SKEW_DIF
Mean
Median
Mean
Median
Mean
Median
-0.098
-0.062
0.179
0.122
-0.087
-0.028
0.069
0.002
0.047
0.035
-0.091
-0.022
-0.167**
-0.064**
0.132**
0.087**
0.004
-0.006