an examination

7/30/2019 An Examination

1/28

Journal of Accounting,

Auditing & Finance27(2) 267293

The Author(s) 2012

Reprints and permission:sagepub.com/journalsPermissions.nav

DOI: 10.1177/0148558X11409153

http://jaaf.sagepub.com

An Examination of theIncremental Usefulness ofBalance-Sheet InformationBeyond Earnings in ExplainingStock Returns

Yuan Huang1 and Guochang Zhang2

Abstract

Until recently, studies in accounting research have predominantly focused on using earnings

information to explain stock returns. This article examines how information provided by the

other primary financial statementthe balance sheetis incrementally useful for determining

returns. Based on existing models of equity value, the author shows theoretically that returns

should be related to three balance sheetrelated variablesthe previous periods (equity)

capital investment, contemporaneous capital investment, and the profitability changein addi-

tion to the earnings variables used in previous studies. Our empirical analysis yields the fol-

lowing results. First, the three balance sheetrelated variables each have a statistically and

economically significant effect that is incremental to those of the earnings variables on equityreturns, and together they improve the explanatory power of an earnings-only-based model

from 11.5% to 13.9% in annual cross-sectional samples. Second, over time, the incremental

explanatory power (IEP) of the balance-sheet variables is negatively correlated with the expla-

natory power of earnings. Third, in cross sections, the balance sheetrelated variables have a

greater IEP for firms whose earnings are less informative (negative vs. positive earnings firms

and young vs. mature firms) and for firms whose future earnings are more uncertain (firms

with high vs. low analyst forecast errors, and firms with high vs. low analyst forecast disper-

sions). These results suggest that information from the balance sheet complements that con-

tained in the income statement about equity returns.

Keywords

stock returns, balance sheet, incremental usefulness, earnings

The relationship between stock returns and accounting data has been one of the most inten-

sively studied topics in accounting research. Until recently, the focus in this line of research

was predominantly on using income-statement data (such as earnings and earnings changes/

growth) to explain returns, with the other primary financial statementthe balance sheetleft

1The Hong Kong Polytechnic University, Hung Hom, Kowloon2Hong Kong University of Science and Technology, Clear Water Bay, Kowloon


2/28

largely neglected, as is evident from the reviews of Lev (1989) and Kothari (2001). This is

unsatisfactory because the balance sheet constitutes a vital part of a financial report, which

informs investors of the sources and uses of the economic resources for a firms operations

and thus provides essential information for assessing firm value and changes in firm value

(returns).1 The lack of attention to the balance sheet in return studies is in contrast to researchin related areas that has already demonstrated the importance of balance-sheet information in,

for example, explaining stock prices (as opposed to returns; e.g., Barth, Beaver, & Landsman,

1998; Burgstahler & Dichev, 1997), evaluating the quality of earnings (e.g., Baber, Chen, &

Kang, 2006), forecasting future earnings (e.g., Lev & Thiagarajan, 1993; Ou & Penman,

1989), and using residual income or EVA (which recognizes a charge on equity capital) to

explain market prices and returns (Biddle, Bowen, & Wallace, 1997; Stewart, 1994) and to

determine executive compensation (Balachandran & Mohanram, 2010).

Our study is thus motivated to better understand the role of balance-sheet information in

explaining returns beyond earnings. We address three specific questions. First, how should

balance-sheet information be integrated along with earnings in return models in ways that

are consistent with theoretical valuation models? Second, how much improvement can

balance-sheet information bring to return models that already use earnings variables?

Third, and more intriguingly, under what circumstances is balance-sheet information incre-

mentally more useful in the diverse and changing business environment? These questions

are of interest to standard-setting bodies, which need to decide whether to adopt a more

balance sheetbased or a more income statementbased model of financial reporting,2 and

to capital market investors, who rely on reported financial information to allocate capitals

among different firms.

We use two existing models of equity value developed in Ohlson (1995) and Zhang

(2000) to identify the relevant data from the balance sheet. Both models follow the dis-

counted cash flow framework, but they take different approaches to financial forecasting

(explained in more detail below). Starting from Ohlsons (1995) model, where equity value

is a linear function of earnings, current book value, and the previous years book value, we

show that returns can be expressed as a function of earnings, the earnings change (relative

to the previous year), and the change in equity book value over the prior period (lagged

capital investment). However, based on Zhangs (2000) model, wherein equity value equals

the earnings capitalization (representing the value of assets in place) plus real options to

expand or contract the scale of operations, we show that returns are a function of earnings,

the change in profitability (return on equity [ROE]) relative to the previous year, and thechange in equity book value (contemporaneous capital investment).

Based on the predictions of these two models, we set up a parsimonious return equation

that incorporates three balance sheetrelated variables (the profitability change, contem-

poraneous capital investment, and lagged capital investment) and two earnings variables

(the earnings level and the earnings change). This equation includes the factors arising

from both Ohlson (1995) and Zhang (2000). As the economic settings examined in Ohlson

(1995) and Zhang (2000) are complementary to each other in certain aspects, it is both

informationally and economically meaningful to combine the factors identified from the

two settings for empirical analysis.

Our empirical return model incorporates earnings and the earnings change as explana-tory variables, which are the factors used in previous earnings-based studies. The incremen-

t l ff t f b l h t i f ti i t d b th th th f t

268 Journal of Accounting, Auditing & Finance


3/28

distinguishing feature of Zhangs model is that firms make capital investment decisions

contingently on profitability. Profitability being normalized earnings indicates a firms abil-

ity to generate value from invested capital, and thus, it serves as a guiding signal for invest-

ment activities. This suggests that when performing firm valuations, investors first need to

determine a firms profitability, using both balance-sheet and income-statement data,3 andthen based on profitability they need to assess the firms course of operations going for-

ward (which incorporates the possibility of exercising real options) and the resulting cash

flows. Intuitively, because value generation hinges on the amount of capital invested and

the efficiency in utilizing invested capital, returns as changes in value should depend on

changes in invested capital (equity book value) and changes in efficiency (profitability),

both of which require balance-sheet data.

Although profitability derives jointly from earnings and equity book value, given that our

benchmark model already incorporates the earnings variables, any incremental explanatory

power (IEP) of profitability (ROE) is attributable to balance-sheet information. For this

reason, we classify ROE changes as a balance-sheet item in this study. In our empirical

analysis, we further exploit the nonlinearity of Zhangs (2000) model caused by real options

to examine how the coefficient on profitability changes with the level of profitability.4

Lagged capital investment is also included in our return model as another balance-sheet

item. This factor arises from Ohlsons (1995) model to recognize the charge for the addi-

tional capital used to generate the incremental earnings in the current period relative to the

prior period (the earnings change). Lagged capital investment does not arise from Zhang

(2000), wherein a firms net investment is assumed to be zero for the period preceding the

date of valuation.

In our empirical analysis, we examine the incremental usefulness of balance-sheet infor-

mation in a comprehensive data set from Compustat and Center for Research in Security

Prices (CRSP) for the period of 1968 to 2007. Our results show that controlling for the

earnings variables, the three balance sheetrelated variables (the profitability change, cur-

rent capital investment, and lagged capital investment) each have a significant incremental

effect, statistically and economically, on returns (although the effect of lagged investment

is insignificant in some of the subsamples) and that the directions of the effects are consis-

tent with the predictions of the underlying valuation models. Vuongs tests performed on

pooled sample and annual samples consistently indicate that our return model performs sig-

nificantly better than a benchmark that relies solely on earnings variables. In annual regres-

sions, the average explanatory power of our comprehensive model that combinesbalance-sheet and income-statement information is 13.9%, compared with that of 11.5%

for the earnings-only-based model.

To gain insights into when, and under what circumstances, balance-sheet information is

more useful, we conduct year-by-year analysis and analysis on various subsamples. We

find that the usefulness of balance-sheet information in supplementing earnings variables is

not uniform over time. Rather, the two tend to move in opposite directions. The Pearson

correlation between the explanatory power of earnings variables and the incremental power

of balance-sheet information in annual samples is 20.29 (t = 1.90), suggesting that

balance-sheet information supplements earnings information to a greater extent in years in

which the latter is less useful for explaining returns.We find a similar complementarity in cross sections. Prior studies have shown that earn-

i l l l t f fi ith ti i (C lli M d & W i

Huang 269


4/28

for firms with negative (vs. positive) earnings and for young (vs. mature) firms. In addition,

we find that balance-sheet information is incrementally more useful for firms with low ana-

lyst forecast accuracies or large forecast dispersions, suggesting that investors rely on the

balance sheet more when they face greater uncertainty about future earnings.

Our study contributes to the literature in several ways. First, it corroborates recent stud-ies that aim to refine the returnearnings relationship by distinguishing between different

sources of earnings growth. Balachandran and Mohanram (in press) decompose earnings

growth into a change in residual income component and a growth from investment compo-

nent, and find significant improvement in explanatory power. Similarly, Harris and Nissim

(2006) distinguish between earnings growth from profitability increases and earnings

growth from investment. Consistent with these studies, we show that the different factors

causing earnings growth (such as the profitability change and prior-period investment) each

play a distinct role in the return model. But beyond those variables causing the contempora-

neous earnings change, our study further incorporates factors that affect future earnings

growth (such as current-period capital investment).5

Second, our study provides insights into when balance-sheet information is more useful

in improving the performance of return models. Our annual regressions show that balance-

sheet variables are more useful in supplementing earnings information in the years when

earnings have low power in explaining stock returns. Our analyses of subsamples in the

cross section further show that balance-sheet information is more useful when firms are in

an operational state in which earnings are less informative as a value indicator (e.g., when

earnings are negative) and when investors face more uncertainty in predicting future earn-

ings. The study thus highlights the complementary nature of the two primary financial

statements.

Third, compared with the simpler linear models adopted in previous studies that use

earnings and equity book value in equity valuation (Barth et al., 1998; Collins et al., 1997),

our return model embodies a more comprehensive set of information. When equity value is

expressed as a linear function of earnings and equity book value, the return model derived

from it is a linear function of earnings, the earnings change, and contemporaneous capital

investment.6 As we show, these factors constitute only a subset of the information used in

our model. More importantly, we introduce balance sheetrelated variables from formal

models of equity value (Ohlson, 1995; Zhang, 2000), and in so doing, we explain the eco-

nomic rationale for why these particular variables are relevant and predict the properties of

their coefficients.Fourth, based on an extensive survey of return studies, Lev (1989) observes that earn-

ings variables alone convey limited information for returns. Subsequently, several studies

have attempted to augment the information set by bringing in future earnings numbers as

additional explanatory factors (e.g., Collins, Kothari, Shanken, & Sloan, 1994; Kothari,

1992; Kothari & Sloan, 1992) on the ground that prices (and returns) anticipate future per-

formance. However, future earnings are not observable, and in practice, investors must rely

on observable information to set prices. In our study, we take an alternative approach to

address the issue by making use of a broader set of reported financial data, thus avoiding

the hindsight problem.7

The remainder of the article is organized as follows: Section titled IncorporatingBalance-Sheet Information Into Return Models shows how in theory, balance-sheet data

b i t d d i t t d l S ti titl d E i i l R h D i d



5/28

information with broad-based samples and is followed by section titled Complementarity

Between Balance-Sheet and Income-Statement Information, which reports the subsample

analyses to explore how the usefulness of balance-sheet information varies over time and

in the cross section. We conclude the article in the section titled Summary and

Concluding Remarks.

Incorporating Balance-Sheet Information Into Return Models

In this section, we conduct a theoretical analysis to show how balance-sheet information

can be incorporated into return models. We start with two existing valuation models that

relate equity value to accounting data, namely, those of Ohlson (1995) and Zhang (2000).

Both models arise from the residual income framework, which is based on discounted cash

flow valuation and clean surplus accounting, but they adopt different approaches to fore-

casting future cash flows (or residual income). Whereas Ohlson assumes that residual

income follows a linear (AR1) process over time, Zhang incorporates capital investment

decisions that are contingent on profitability signals (which give rise to real options). As

the two models capture different aspects of the accounting-value linkage, we will draw

insights from both in designing our empirical research.8

Fundamental Factors for Explaining Returns According to Ohlsons Model

Starting with the discounted dividend model and assuming the clean surplus relation and a

linear process for residual income, Ohlson (1995) shows that equity value at date t (Vt) is a

linear function of contemporaneous earnings (Xt), book value (Bt), and dividends (net ofcapital contribution: Dt), as follows:

Vt5k(jXt Dt)1(1 k)Bt; 1

where k = r w / (1 1 r2 w) is a coefficient related to discount rate r and residual income

persistence w (0\ w\ 1), andj = (11r) / r is the earnings capitalization factor. Using

the clean surplus relation, we replace the dividend term in (1) with earnings and equity

book value Dt5Bt1 Bt1Xt, which enables us to express equity value in terms ofaccounting variables as:9

Vt5k(j 1)Xt1Bt kBt1: 2

To obtain the expression for returns, we apply Equation (2) to date t1 1 to get

Vt115k(j 1)Xt111Bt11 kBt: 3

Over the period from date t to date t1 1, the equity return is defined as

Rt115Vt111Dt11 Vt

Vt: 4

Huang 271


6/28

Rt115Vt111(Xt11 Bt111Bt) Vt

Vt

5(k(j 1)Xt111Bt11 kBt1(Xt11 Bt111Bt) k(j 1)Xt1Bt kBt1

Vt

5Xt11Vt1k(j 1)DX

t11

Vt kDB

t

Vt;

5

where DXt11 = Xt11 2 Xt is the change in earnings in period t1 1 relative to period t, and

DBt = Bt2 Bt21 is the change in equity capital at date t relative to date t2 1, which is the

previous periods capital investment. This derivation identifies the same two earnings vari-

ables as in Easton and Harris (1991), but it shows that a complete return function from

Ohlson (1995) also requires lagged capital investment.

In Ohlsons (1995) model, capital investment activities are value-neutral in that they

have zero net percent value (NPV) because, by assumption, expected future residual

income is tied only to realized residual income and not to ongoing capital investments.10

Consequently, contemporaneous capital investment plays no role for explaining equity

returns. However, lagged capital investment enters into Equation (5), along with earnings

and the earnings change, because for the additional earnings generated in the current period

relative to the prior period (i.e., the earnings change), one needs to recognize the capital

charge on the incremental capital used. This explains why the coefficient on lagged capital

investment is negative in Equation (5). Besides, the model also predicts the coefficient on

earnings level is one and that on earnings change is positive.

Fundamental Factors for Explaining Returns According to Zhangs Model

Zhang (2000) develops a valuation model incorporating capital investment decisions that

are contingent on profitability signals. A firm may expand its operation as profitability

rises and contract (or abandon) it as profitability declines. Equity value is shown to consist

of the value of the assets in place (earnings capitalization) and the real options to expand

or contract, as follows:

Vt5Bt P(qt)1qt=r1gC(qt); 6

where qt = Xt / Bt21 is the period t profitability (return on equity); g is the firms growthopportunity, which is defined as the percentage by which the scale of operations (capital

invested) may grow; and P(qt) and C(qt) are the put option to abandon operations and the

call option to expand operations, respectively, both normalized by Bt. The values of the

options derive from the benefits from exercising the options and the likelihood of exercis-

ing the options, both of which are dependent on profitability q.11

To derive a model of equity return, we take the change in Equation (6) with respect to

accounting variables Bt and qt from date t to t1 1:12

DVt11v(qt;gt; r)DBt11 1Btv0 Dqt11; 7

where v(qt;gt; r)5P(qt)1qt=r1gC(qt); DVt11 = Vt11 2 Vt is the change in equity valuef d t t t d t t 1 1 DB d D i il l d fi d h i it b k



7/28

Rt115DVt111Dt11

Vt5v

DBt11Vt

1v0 BtVtDq

t111

Dt11

Vt:

5DBt11Bt

1v0 BtVtDqt111

Dt11Vt

:

8

Using the clean surplus relation, we replace Dt11 in Equation (8) with Xt11 andDBt11and rearrange to obtain the following expression for the period t1 1 return:

Rt115Xt11Vt

1v0 BtVtDqt111(

VtBt

1)DBt11Vt

: 9

Equation (9) shows that the return in period t 1 1 is a function of the profitability

change, Dqt11, and contemporaneous capital investment, DBt11, in addition to earnings,

Xt11. Changes in profitability affect returns because they revise expectations about a firms

ability to generate value from invested capital. Investment results in a change in the capitalbase used to generate value, and so it also affects returns. Both variables revise expecta-

tions about future cash flows.

In this model, value generation hinges on two basic attributes of operations as viewed

from equity holders standpoint: the amount of capital invested (equity book value) and the

efficiency in utilizing capital to generate profit (profitability). Furthermore, as a firms

operations move forward, the scale of operation is adjusted in accordance with changes in

profitability, thus, giving rise to real options. With equity value depending on equity book

value and profitability, returns as changes in equity value naturally depend on contempora-

neous equity investment, DBt11, and changes in profitability, Dqt11, both of which require

balance-sheet data. Although the profitability variable is constructed jointly with balance-

sheet and income-statement data, we classify it as a balance-sheet variable because when

we have already controlled for earnings and the earnings change, any IEP of profitability

changes in explaining return comes from balance-sheet information.

The two balance sheetrelated factors, DBt11 andDqt11, are linked to real options through

their coefficients as in Equation (9). The coefficient on Dqt11 contains v05dv=dqt5

P0(qt)11=r1gC0(qt), which is positive and increasing in qt, given that v itself is increasing

and convex in qt. In our empirical analysis below, we exploit this nonlinearity feature caused

by real options to allow the coefficient on Dqt11 to vary with the level of profitability.

The coefficient on DBt11

is (Vt / Bt2

1) = P(qt)1

qt=r1

gC(qt)2

1, representing thenet present value per unit of incremental investment, which incorporates the effect of real

options. Empirically, this coefficient can be either positive or negative, depending on

whether the additional investment is profitable, that is, whether P(qt)1qt=r1gC(qt)21 .0.13 To the extent that firms on average make profitable (positive NPV) investments, we

expect contemporaneous capital investment (DBt11) to have a positive coefficient in the

return model. Thus, the real optionsbased model of Zhang (2000) provides an economi-

cally meaningful interpretation of the coefficient ofDBt11.

Finally, consistent with Equation (5), the coefficient on Xt11 is predicted to be one.

Empirical Research Design and SampleResearch Design

Huang 273


8/28

(2000) model, we derive two additional balance sheetrelated variables, contemporaneous

capital investment and the profitability change, together with earnings. The two models are

developed from two distinct economic settings, which are complementary in certain

aspects. Although Zhang considers contingent capital investment decisions, which give rise

to real options, his model is embedded with an assumption that a firms scale of operationsis kept constant in the period preceding the date of valuation (so that lagged capital invest-

ment is zero; Zhang, 2000); however, this condition is not imposed in Ohlsons linear

model. Due to the complementarity between the two models, the factors from one model

will not completely subsume those from the other in explaining returns. Thus, in our

empirical analysis, we combine the factors from Ohlson and Zhang, and use them to jointly

explain returns.

The main return model for our empirical analysis is the following linear specification:

Rit5a1bxit1gDxit1hDqit1uDbit1dDbit11eit: 10

In Equation (10), Dxit and Dbit21 arise from Ohlson (1995), Dqit and Dbit from Zhang

(2000), andxit from both settings. Although it is true that Dqit already contains the informa-

tion in Dxit andDbit21 (which is combined in a particular fashion), the three factors origi-

nate from two distinct economic settings (explained above), and empirically, whether Dqitis sufficient for summarizing the information in Dxit andDbit-1 to explain returns is unclear.

For this reason, we keep all three factors (Dqit, Dxit, and Dbit21) in return Model (10).

Model (10) also enables us to conveniently evaluate the incremental usefulness of balance-

sheet information beyond an earnings onlybased model (that uses only earnings and the

earnings change).

The dependent variable in (10), Rit, is the annual stock return, which is calculated from

the 4th month after the prior fiscal year end to the 3rd month after the current fiscal year

end. The independent variables are specified as follows: xit = Xit / Vit21 is the earnings in

year t (Xit) scaled by the market value of equity at the beginning of year t (Vit21); Dxit =

(Xit2 Xit21) / Vit21 is the earnings change in year t relative to year t2 1 scaled by Vit21;

Dqit = qit2 qit21 is the profitability change in year t relative to year t2 1, with qit = Xit /

Bit21; Dbit = (Bit2 Bit21) / Vit21 is capital investment (the change in equity book value) in

year t scaled by Vit21; andDbit21 = (Bit21 2 Bit22) / Vit21 is the lagged capital investment

(change in equity book value in year t2 1) scaled by Vit21.

According to Model (9), the coefficient on Dqit involves the first-order derivative of thegrowth option (included in v). Due to the convex behavior of real options, this coefficient

is an increasing function of profitability. To capture this property, we distinguish the coeffi-

cient on Dqit between high- and low-profitability firms in the extended specification below,

Rit5a1bxit1gDxit1hDqit1hHHDqit1uDbit1dDbit11eit; 10a

where H is a dummy variable equal to 1 for firms with profitability above the median in a

year and 0 otherwise. Based on the above theoretical analysis, we expect b = 1, g . 0, h

. 0, u . 0, andd\ 0 in Model (10a). In addition, following the prediction that the return

impact associated with one unit of profitability change is greater for more profitable firms,we expect hH. 0.

T l t th i t l f l f th b l h t i f ti i t d



9/28

Rit5a1bxit1gDxit1eit: 11

The factors in Model (11) are a subset of those in Model (10a). Observe that (11) can be

viewed as a cut-down version of the return Model (5), which is derived from Ohlson

(1995), without the lagged capital investment term.We assess the incremental usefulness of balance-sheet information in two aspects. First,

for individual balance sheetrelated variables, we test whether the coefficients are consistent

with the theoretical predictions. We examine the significance of these variables within our

(more comprehensive) return Models (10) and (10a), controlling for the earnings variables.

Second, we examine whether there is a significant improvement in model performance

after introducing our balance sheetrelated variables, as measured by the IEP, which is cal-

culated as the R2 of Model (10a) minus that of Model (11) (Biddle, Seow, & Siegel, 1995;

Brown, Lo, & Lys, 1999).14 That is, we attribute the IEP ofDbit21, Dbit, andDqit, beyond

Dxit and xit, to balance-sheet information. As already explained above, although Dqit com-

bines both earnings and book value, its IEP over and above that of the earnings variables isattributable to balance-sheet information. The difference in the explanatory power between

(10a) and (11) represents the IEP of the three balance-sheet variables as a group. In addi-

tion, we also estimate the IEPs of the balance-sheet variables individually. This is com-

puted as the R2 of Model (10a) minus that of Model (10a), excluding the concerned

balance-sheet variable.

Beyond examining the IEP on broad cross-sectional samples, we evaluate whether the

IEP varies over time and across subsets of firms. We describe how the IEP of balance-

sheet information fluctuates from year to year in relation to the explanatory power of earn-

ings numbers. We also compare the IEPs of firms that differ in earnings informativeness

(negative vs. positive earnings firms and young vs. mature firms) or in the predictability of

future earnings (firms with low vs. high analyst forecast accuracies and firms with large vs.

small forecast dispersions).

The Sample and Descriptive Statistics

We extract the data on earnings before extraordinary items and discontinued operations

(Xit, No. 18) and equity book value (Bit, No. 60) from the Compustat annual file. We

extract the stock returns and beginning market values of common equity from the CRSP

monthly files. Annual returns with dividends (Rit) are compounded from monthly returnsstarting from the 4th month after the prior fiscal year end to the 3rd month after the current

fiscal year end. We exclude observations with an equity book value less than US$0.5 mil-

lions or total assets less than US$1.5 millions. To reduce the impact of outliers and

extremely illiquid stocks, we require the stock price at the beginning of a fiscal year to be

higher than US$3. We exclude firms in financial industries (whose balance sheets have dis-

tinctively different features) and utility firms (whose profitability is subject to regulations).

The resulting sample consists of 87,439 firm-year observations for the period 1968 to 2007.

In some parts of the analysis, the sample size varies where we also use analyst earnings

forecasts from the Institutional Brokers Estimate System (I/B/E/S) detailed file.15 We win-

sorize the continuous variables at the top and bottom 1% of the distribution.Panel A of Table 1 presents the descriptive statistics of the main variables for the

l d l Th l t k t (R ) h ( di ) f 0 17 (0 09) Th

Huang 275


10/28

and median around 0, suggesting that the profitability tends to decline over time. Scaled

contemporaneous capital investment (Dbit) has a mean (median) of 0.06 (0.06), and scaled

lagged capital investment (Dbit21) has a mean (median) of 0.06 (0.05).

Panel B reports the pairwise correlations among the variables. We find that all of the

correlations in the panel are significant at the .01 level. The annual stock return is posi-

tively correlated with earnings (with a Pearson correlation equal to .28 and a Spearman cor-relation equal to .34) and with the earnings change (.27 and .35). More importantly, the

return is also positively correlated with the profitability change (.27 and .32), contempora-

neous capital investment (.21 and .25), and is negatively correlated with lagged capital

investment (2.05 and2.04), all having the predicted signs.

We find strong correlations among the accounting variables. The earnings level is posi-

tively correlated with the earnings change, which is expected (shocks causing earnings to

increase in year t tend to cause earnings to be higher than in year t2 1). Current capital

investment is positively correlated with earnings, earnings change, and profitability change,

and is grossly consistent with the notion of capital following profitability (Biddle, Chen,

& Zhang, 2001). Current capital investment is also positively correlated with lagged capitalinvestment, suggesting that in general firms do not alter their investment activities drasti-

ll f t th t

Table 1. Summary Statistics

Panel A: Descriptive Statistics

M SD 1% 25% 50% 75% 99%

Rit 0.17 0.46 20.57 20.13 0.09 0.36 1.82xit 0.07 0.07 20.10 0.04 0.07 0.11 0.21Dxit 0.01 0.09 20.33 20.02 0.01 0.03 0.33Dbit 0.06 0.13 20.41 0.02 0.06 0.10 0.53Dqit 20.01 0.15 20.49 20.06 0.00 0.04 0.43Dbit21 0.06 0.12 20.41 0.02 0.05 0.10 0.44

Panel B: Correlation Matrix

Rit xit Dxit Dbit Dqit Dbit-1

Rit 0.34 0.35 0.25 0.32 20.04xit 0.28 0.50 0.60 0.37 0.27Dxit 0.27 0.52 0.48 0.84 20.18Dbit 0.21 0.56 0.46 0.32 0.27Dqit 0.27 0.39 0.72 0.30 20.38Dbit21 20.05 0.20 20.30 0.17 20.37

Note: This table reports the summary statistics for our sample for the period 1968 to 2007. There are 87,439

firm-year observations. The variables are defined as follow: Rit is the annual stock return from the 4th month after

the prior fiscal year end to the 3rd month after the current fiscal year end; xit = Xit / Vit21 is the earnings in year t

(Xit) scaled by the beginning market value of equity (Vit21); Dxit = (Xit2 Xit21) / Vit21 is the earnings change in year

t relative to year t 2 1 scaled by Vit21; Dqit = (qit2 qit21) is the profitability change of year t relative to year t 2 1,

with qit = Xit / Bit21; Dbit21 = (Bit21 2Bit22) / Vit21 is the capital investment in year t 2 1 scaled by Vit21; and Dbit =(Bit2 Bit21) / Vit-1 is the current years capital investment scaled by Vit21.In Panel B, the Spearman correlation coef-

ficients are above the diagonal, and Pearson correlation coefficients are below the diagonal. All of the coefficients

are significant at the .01 level



11/28

principle, the earnings change in a year relative to the prior year can arise from two

sources: a change in book value (due to incremental investment or divestment) and a

change in profitability (due to improvement or deterioration in operational efficiency). The

high correlation between the earnings change and the profitability change suggests that,

empirically, the earnings change between two consecutive years is mostly driven by theprofitability change, rather than capital investment.

Results From Broad-Based Samples

This section examines the empirical importance of balance-sheet information in broad

cross-sectional samples. The objective here is to gain an overall view of how useful the

balance-sheet variables are beyond earnings variables in explaining stock return.

Results From the Pooled SampleUsing pooled samples, Table 2 reports the performance of our return Models (10) and

(10a), relative to the performance of several variants of these two models and earnings-

only Model (11). In running these pooled regressions, we adjust for cross and serial correla-

tions with two-way (firm and year) clustering. Panel A shows the regression results of

Models (10), (10a), and (11). Controlling for earnings and the earnings change, the three

balance sheetrelated variables, Dqit, Dbit, andDbit-1, all have a significant effect on returns

and the directions of the effects are as predicted.

The profitability change (Dqit) has a consistently positive coefficient in all the specifica-

tions in the table. In row (ii), without introducing the piecewise linear structure, the coeffi-

cient on Dqit is 0.37 (t = 13.31), significant at the .01 level. For the piecewise linear model

(row i), the coefficient on Dqit is 0.15 (t = 4.02) for the low-profitability range, significant

at the .01 level, and increases to 0.53 (=0.15 1 0.38) for the high-profitability range. The

coefficient increase from the low-profitability to the high-profitability range is significant

at the .01 level (t = 7.19). These results indicate that the effect of a change in profitability

on returns is positive and is greater for firms with higher profitability.

The magnitude of the coefficient demonstrates that the effect of the profitability change

is economically important. Ceteris paribus, an increase in profitability by one standard

deviation within the pooled sample (=0.15) is, on average, associated with a return increase

of 0.02 for low-profitability firms and 0.08 for high-profitability firms, which amounts to13.2% and 46.8% of the average annual return (0.17), respectively.

In row (i), lagged capital investment (Dbit21) has a negative coefficient of20.13 (t =

2.56), significant at the .05 level, consistent with the prediction. This suggests that a

change of lagged capital investment by one standard deviation (0.12) is associated with an

average return change of20.02.

Contemporaneous capital investment (Dbit) has a coefficient of 0.28 (row i), significant at the

.01 level (t = 4.89). In absolute terms, the coefficient on Dbit is almost twice of that on Dbit21and has a much higher t value. An increase in capital investment by one standard deviation

(0.13) is associated with an average return increase of 0.04, which is economically significant.

The coefficient on xit is highly significant; the coefficient is 1.02 (t = 3.56) in Model(10a), row (i), and is 0.97 (t = 3.40) in Model (10), row (ii). These values are not signifi-

tl diff t f th th ti l l f t th 1 l l

Huang 277


12/28coefficient is 0.84 (t = 7.08), but it decreases by more than half to 0.30 (t = 2.56) in the

h i M d l (10 ) (i) hi h i t th b l h t l t d i bl

Table 2. Pooled Sample Regressions

Intercept xit Dxit Dqit Dbit Dbit21 H 3 Dqit R2

Panel A: Comparison of our return models with earnings-only-based return models

(i) Model (10a) 0.09a 1.02a,d 0.30b 0.15a 0.28a 20.13b 0.38a .090***(3.23) (3.56) (2.56) (4.02) (4.89) (22.56) (7.19)

(ii) Model (10) 0.10a 0.97a,d 0.19c 0.37a 0.30a 20.14a .087***(3.55) (3.40) (1.73) (13.31) (5.15) (22.69)

(iii) Model (11) 0.10a 1.11a,d 0.84a .076***(3.27) (4.27) (7.08)

Panel B: The effect of individual balance-sheet variables

(iv) 0.09a 1.14a,d 0.50a 0.14a 0.42a .087***(3.22) (4.42) (4.02) (3.41) (7.51)

(v) 0.10a

0.91a,d

0.75a

0.25a

.079***

(3.26) (3.19) (6.95) (4.08)(vi) 0.10a 1.25a,d 0.72a 20.17a .077***

(3.30) (4.65) (5.35) (23.04)

Panel C: IEP of individual balance-sheet variables

(vii) 0.10a 1.06a,d 0.56a 0.30a 20.24a .081***(3.30) (3.69) (4.71) (5.09) (24.59)

(viii) 0.09a 1.20a,d 0.46a 0.13a 20.07 0.41a .087***(3.21) (4.48) (3.46) (3.40) (21.26) (7.44)

(ix) 0.09a 0.93a,d 0.38a 0.17a 0.26a 0.39a .090***

(3.23) (3.30) (3.43) (4.39) (4.32) (7.36)

Note: IEP = incremental explanatory power.

This table reports the pooled regression results for Models (10), (10a), and (11):

Rit5a1bxit1gDxit1hDqit1uDbit1dDbit11eit; 10



Rit is the annual stock return from the 4th month after the prior fiscal year end to the 3rd month after the current

fiscal year end; xit = Xit / Vit21 is the earnings in year t (Xit) scaled by the beginning market value of equity (Vit21);

Dxit = (Xit2 Xit21) / Vit21 is the earnings change in year t relative to year t 2 1 scaled by Vit21; Dqit = (qit2 qit-1) is

the profitability change of year t relative to year t 2 1, with qit = Xit / Bit21; Dbit21 = (Bit-1 2 Bit22) / Vit-1 is the capi-

tal investment in year t 2 1 scaled by Vit21; and Dbit = (Bit 2 Bit-1) / Vit21 is the current years capital investment

scaled by Vit21. H is a dummy variable equal to 1 for firms whose profitability is larger than the annual median

level. The t statistics in the parentheses are adjusted for firm-year two-way clustering.a,b, and c indicate the coefficient being significantly different from 0 at the .01, .05, and .1 levels, respectively.dindicates the coefficient is not significantly different from the predicted value of one at the .1 level.

***indicates the Vuongs Z statistics for comparing balance-sheet-information-integrated model (Model [10a] and

its variants) with earnings-only model (Model [11]) being significant at the .01 level. The Z statistics are 26.36 (row

[i]), 23.35 (row [(ii]), 26.77 (row [iv]), 11.47 (row [v]), 7.70 (row [vi]), 15.60 (row [vii]), 22.98 (row [viii]), and

25.70 (row [ix]), respectively, in favor of balance-sheet-information-integrated models.



13/28

an IEP of 1.4%. Vuongs Z statistics for comparing Models (10a) and (11) is 26.36, signifi-

cant at the .01 level, in favor of Model (10a). Similarly, Vuongs Z statistics for comparing

Models (10) and (11) is 23.35, also significant at the .01 level, in favor of 10 over 11.

Panel B details how the individual balance-sheet variables impact the role of Dxit in the

return model. Inclusion of Dqit has the greatest impact, which reduces the coefficient onDxit from 0.84 in row (iii) to 0.50 in row (iv), whereas the inclusion of Dbit and Dbit21,

row (v) and (vi), has a smaller impact. The results demonstrate that Dqit has a more robust

relationship with stock returns than does Dxit, reaffirming the usefulness of balance-sheet

information for enhancing the performance of return models.

The IEP of individual balance-sheet variables is provided in Panel C. Among the individ-

ual factors, the profitability change has the largest IEP of .9%. The IEP of contemporaneous

capital investment is .3%. The IEP of lagged capital investment is the smallest at .01%.

In Panels B and C, we conduct Vuongs tests to examine the performance of various bal-

ance-sheet-information-integrated models relative to the earnings-only model. The results

show that the models incorporating various subsets of our balance-sheet variables all per-

form significantly better at the .01 level than the earnings-only model.

Although the results in Table 2 are from regressions using raw returns as the dependent

variable (which is originally derived from the underlying valuation models), we also per-

form regressions using market-adjusted returns as the dependent variable, which aim to

mitigate potential concerns caused by the differences in the general level of returns across

years. The results, presented in Table 3, are similar to those reported in Table 2. Therefore,

our conclusion about the usefulness of the balance-sheet variables that we have identified

(Dqit, Dbit, andDbit21), both individually and as a whole, remains unchanged.16

Results From the Annual Samples

Panel A of Table 4 presents the results of Model (10a) from the annual samples. The top

part of the panel shows the mean coefficients from the annual regressions across the

sample years and the FamaMacBeth t values adjusted with NeweyWest approach. The

average coefficient on xit is 1.26 (t = 7.76), which is not significantly different from the

theoretical value of one at the .1 level. In annual regressions, the coefficient on xit is signif-

icantly different from 1 for 27 years at the 0.1 level or better and is not significantly differ-

ent from 1 for 13 years.

The average coefficient on Dqit is 0.21 (t = 4.61) for low-profitability firms, and theincremental coefficient on Dqit for high-profitability firms is 0.43 (t = 7.68), showing a

relationship between returns and Dqit that is dependent on the level of profitability. The

coefficient on Dqit is significantly positive for low-profitability firms in 21 of the 40

sample years and the incremental coefficient for high-profitability firms is significantly

positive in 30 years at the .1 level or better, and generally insignificant for the remaining

years, conditional on the earnings variables.

The average coefficient on Dbit is 0.16 (t = 3.78) and that on Dbit21 is 20.09 (t =

22.54). The coefficient on contemporaneous capital investment is significantly positive in

17 years (at the 0.1 level or better), insignificant in 21 years, and significantly negative in

2 years. The coefficient on Dbit21 is significantly negative (at the .1 level or better) in 17years, insignificant in 16 years, and significantly positive in 7 years.

I P l B f T bl 4 th l R2 f M d l (10 ) ith th f M d l

Huang 279


14/28by the significant Vuongs Z statistics. The IEP of the balance-sheet information ranges

f 6% ( 1984) t 8% ( 1969) ith f 2 4% (t 7 31) M th

Table 3. Pooled Sample Regressions With Market-Adjusted Returns

Intercept xit Dxit Dqit Dbit Dbit21 H 3 Dqit R2

Panel A: Comparison of our return models with earnings-only-based return models

(i) Model (10a) 20.04 1.06a,d 0.39a 0.15a 0.25a 20.16a 0.37a .109***(21.57) (5.40) (4.33) (5.08) (5.00) (23.56) (8.04)

(ii) Model (10) 20.02 1.02a,d 0.28a 0.37a 0.27a 20.16a .106***(21.09) (5.16) (3.27) (15.08) (5.33) (23.65)

(iii) Model (11) 20.032 1.10a,d 0.93a .094***(21.42) (6.40) (11.41)

Panel B: The effect of individual balance-sheet variables

(iv) 20.03 1.13a,d 0.58a 0.16a 0.40a .106***(21.57) (6.63) (6.49) (4.88) (8.44)

(v) 20.03 0.93a,d

0.86a

0.21a

.096***

(21.46) (4.71) (11.88) (4.11)(vi) 20.03 1.27a,d 0.79a 20.20a .096***

(21.39) (7.13) (8.01) (24.48)

Panel C: IEP of individual balance-sheet variables

(vii) 20.03 1.10a,d 0.65a 0.26a 20.26a .099***(21.43) (5.57) (7.52) (5.28) (26.10)

(viii) 20.04 1.22a,d 0.53a 0.13a 20.10b 0.40a .106***(21.57) (6.90) (5.32) (4.45) (22.20) (8.31)

(ix) 20.04 0.95a,d 0.48a 0.18a 0.22a 0.38a .108***

(21.56) (4.87) (5.99) (5.87) (4.32) (8.29)

Note: IEP = Incremental explanatory power.

This table reports the pooled regression results for models (10), (10a), and (11):

ExRit5a1bxit1gDxit1hDqit1uDbit1dDbit11eit; 10

ExRit5a1bxit1gDxit1hDqit1hHHDqit1uDbit1dDbit11eit; 10a

ExRit5a1bxit1gDxit1eit: 11

ExRit is the annual market-adjusted stock return from the 4th month after the prior fiscal year end to the 3rd month

after the current fiscal year end; xit = Xit / Vit21 is the earnings in year t (Xit) scaled by the beginning market value ofequity (Vit21); Dxit = (Xit2 Xit21) / Vit21 is the earnings change in year t relative to year t 2 1 scaled by Vit21; Dqit =

(qit2qit21) is the profitability change of year t relative to year t 2 1, with qit = Xit / Bit21; Dbit21 = (Bit21 2 Bit22) /

Vit21 is the capital investment in year t 2 1 scaled by Vit21; and Dbit = (Bit2 Bit21) / Vit21 is the current years capital

investment scaled by Vit21. H is a dummy variable equal to 1 for firms whose profitability is larger than the annual

median level. The t statistics in the parentheses are adjusted for firm-year two-way clustering.

***indicates the Vuongs Z statistics for comparing the balance-sheet information integrated model (Model [10a]

and its variants) with earnings-only model (Model [11]) being significant at the .01 level. The Z statistics for these

models are 27.63 (row [i]), 24.57 (row [ii]), 24.30 (row [iv]), 10.30 (row [v]), 9.80 (row [vi]), 16.16 (row [vii]),

24.78 (row [viii]), and 26.60 (row [ix]), respectively, in favor of balance-sheet-information-integrated models.a,b and c indicate the coefficient being significantly different from 0 at the .01, .05, and .1 levels, respectively.dindicates the coefficient is not significantly different from the predicted value of one at the .01 level.



15/28

Table 4. Annual Regression Results and the IEP of Balance-Sheet Information

Year Intercept xit Dxit Dqit Dbit Dbit21 H*Dqit R2

Mean 0.07 1.26a 0.41a 0.21a 0.16a 20.09b 0.43a .139

(2.66) (7.76) (4.71) (4.61) (3.78) (22.54) (7.68)1968 0.07a 2.45a,*** 0.91c 0.40b 0.03 20.35 1.07a .167

(2.86) (5.72) (1.76) (2.49) (0.13) (21.49) (3.98)1969 20.27a 1.59a,** 20.44 20.24b 0.94a 20.35a 20.35b .135

(217.31) (5.60) (21.41) (22.30) (6.66) (23.08) (22.27)1970 0.01 3.30a,*** 20.78a 20.55a 0.90a 20.16 0.54c .162

(0.57) (11.62) (23.03) (24.21) (4.05) (21.39) (2.03)1971 0.04b 1.99a,*** 0.61b 0.09 0.14 0.26b 0.46b .149

(2.53) (7.86) (2.26) (0.81) (0.62) (2.26) (2.05)1972 20.18a 1.08a 0.06 20.09 0.44b 20.12 1.01a .098

(211.89) (4.85) (0.24) (20.83) (2.11) (21.20) (4.62)

1973 20.27a

0.94a

0.59a

0.06 0.42b

20.15b

0.69a

.224(220.79) (7.03) (3.36) (0.67) (2.26) (22.11) (4.03)

1974 20.21a 1.23a 0.66a 20.14 0.23 20.15c 0.74a .211(211.08) (8.18) (4.37) (21.49) (1.13) (21.69) (4.07)

1975 0.23a 1.44a,** 0.43b 0.20c 0.37c 0.06 0.37a .182(9.71) (7.03) (2.49) (1.67) (1.89) (0.51) (1.88)

1976 20.07a 1.90a,*** 0.65a 20.11 20.20 0.09 0.65a .181(23.71) (11.16) (4.14) (21.16) (21.25) (0.88) (4.28)

1977 0.02 1.18a 1.29a 20.03 20.17 0.25a 1.06a .238(1.07) (6.91) (8.25) (20.34) (21.00) (2.64) (6.52)

1978 0.16a 0.28*** 1.03a 0.08 0.31 0.40a 1.06a .161

(8.02) (1.56) (5.74) (0.92) (1.60) (3.90) (5.75)1979 0.15a 20.47b,*** 1.80a 0.13 20.12 0.18 0.75a .139(6.77) (22.46) (9.79) (1.37) (20.77) (1.62) (4.54)

1980 0.47a 20.36c,*** 1.42a 0.57a 0.25 0.35a 0.54a .156(18.35) (21.65) (7.18) (5.39) (1.32) (2.76) (2.79)

1981 20.15a 1.70a,*** 20.09 0.05 0.44a 20.10 0.15 .160(210.05) (11.35) (20.62) (0.69) (3.80) (21.06) (1.16)

1982 0.38a 1.33a 0.10 0.11 0.58a 20.08 0.58a .118(16.61) (6.03) (0.53) (0.96) (3.90) (20.78) (3.20)

1983 0.08a 3.21a,*** 0.17 20.08 20.35a 20.23c 0.61a .144(5.12) (15.06) (0.91) (20.84) (22.28) (21.93) (3.76)

1984 20.10a 2.15a,*** 20.10 20.09 0.25a 20.06 20.09 .181(29.32) (16.95) (20.82) (21.53) (2.85) (20.89) (20.95)

1985 0.23a 1.56a,*** 20.10 0.22a 0.47a 20.22 0.15 .150(16.99) (8.66) (20.67) (2.68) (4.37) (22.66) (1.23)

1986 0.11a 2.39a,*** 20.14 20.10 0.30a 20.20b 0.16 .166(10.09) (13.04) (20.91) (21.26) (2.88) (22.42) (1.48)

1987 20.06a 1.28a,* 0.31b 0.01 0.12 20.13c 0.28a .122(26.25) (7.88) (2.20) (0.16) (1.38) (21.94) (3.01)

1988 0.04a 1.61a,*** 0.15 0.03 0.22b 20.05 0.23b .171(3.96) (11.16) (1.08) (0.50) (2.26) (20.79) (2.34)

1989 0.05a 0.81a 0.44a 0.26a 0.36a 0.19b 0.26b .152(4.35) (4.78) (2.72) (3.28) (3.11) (2.44) (2.21)

1990 0.01 0.90a 0.43b 0.20b 0.33a 0.05 0.39a .117(0.75) (4.55) (2.23) (2.20) (2.59) (0.48) (2.81)

1991 0 23a 1 11a 0 21 0 36a 0 18 0 07 0 81a 124

Huang 281


16/28

Table 4. (continued)

Year Intercept xit Dxit Dqit Dbit Dbit21 H*Dqit R2

(14.48) (4.94) (1.04) (3.64) (1.32) (20.66) (5.32)

1992 0.07

a

1.52

a,***

0.55

a

0.08 0.122

0.10 0.42

a

.149(6.12) (7.89) (3.49) (1.11) (1.07) (21.17) (3.68)1993 0.15a 1.02a 0.55a 0.11 0.18c 0.17b 0.35a .113

(13.05) (5.82) (3.67) (1.47) (1.95) (2.33) (3.29)1994 0.06a 0.79a 0.29c 0.26a 0.18b 20.15b 0.15c .088

(5.58) (4.78) (1.97) (3.57) (2.10) (22.19) (1.69)1995 0.30a 20.22*** 0.50a 0.64a 0.28a 20.14 0.26c .080

(21.61) (21.11) (2.74) (7.42) (2.78) (21.45) (2.32)1996 0.03a 1.96a,*** 20.21 0.28a 0.19a 20.32a 0.10 .109

(3.00) (11.41) (21.31) (4.08) (2.67) (23.59) (1.11)1997 0.28a 1.43a,** 0.40b 0.40a 0.08 0.02 0.35a .112

(22.35) (7.79) (2.41) (5.34) (1.06) (0.29) (3.61)1998 20.07a 0.79a 0.09 0.10 0.25a 20.28a 0.20b .063

(26.21) (4.27) (0.49) (1.24) (3.13) (23.36) (2.25)1999 0.28a 22.01a,*** 0.51b 0.89a 0.24c 20.31a 0.46a .073

(15.92) (28.04) (2.11) (7.70) (1.68) (22.68) (3.02)2000 0.10a 0.45b,** 0.23 0.81a 0.41a 20.39a 20.11 .091

(6.11) (2.08) (1.02) (7.76) (3.10) (23.39) (20.76)2001 0.12a 2.88a,*** 20.35b 0.13 0.06 20.57a 0.82a .194

(7.97) (13.66) (21.82) (1.24) (0.64) (25.89) (6.37)2002 20.13a 1.96a,*** 20.08 0.09 0.09 20.37a 0.13 .113

(211.80) (10.56) (20.49) (1.17) (0.79) (23.99) (1.14)2003 0.44a 20.04*** 1.34a 0.41a 20.49a 20.25a 1.14a .095

(29.43) (20.18) (6.28) (3.79) (22.64) (22.58) (5.86)2004 0.06a 2.22a,*** 0.46b 0.12 20.06 20.40a 0.18 .140

(5.00) (10.72) (2.24) (1.32) (20.47) (23.75) (1.50)2005 0.24a 0.51b,** 1.21a 0.27b 0.00 0.19 0.53a .100

(16.80) (2.05) (4.62) (2.51) (20.01) (1.53) (3.55)2006 0.08a 1.07a 0.09 0.34a 0.42a 20.32a 20.13 .121

(7.41) (5.66) (0.48) (3.73) (3.83) (23.37) (21.20)2007 20.05a 1.31a 1.03a 0.22b 20.14 0.15 0.43a .126

(23.56) (5.39) (4.35) (2.10) (21.07) (1.31) (3.24)

Panel A reports the regression results of Model (10a) from the annual samples: Rit5a1bxit1gDxit1hDqit1hHHDqit1uDbit1dDbit11eit, where Rit is the annual stock return from the 4th month after the prior fiscal year end to the3rd month after the current fiscal year end; xit = Xit / Vit21 is the earnings in year t (Xit) scaled by the beginning market

value of equity (Vit21); Dxit = (Xit2 Xit21) / Vit-1 is the earnings change in year t relative to year t 2 1 scaled by Vit21;

Dqit = (qit2 qit21) is the profitability change of year t relative to year t 2 1, with qit = Xit / Bit21; Dbit21 = (Bit21 2

Bit22) / Vit21 is the capital investment in year t 2 1 scaled by Vit21; and Dbit = (Bit2Bit-1) / Vit21 is the current years

capital investment scaled by Vit21. H is a dummy variable equal to 1 for firms whose profitability is larger than the

annual median level. In the row of mean, the t statistics in parentheses are computed with FamaMacBeth

methodology and adjusted for heteroscedasticity and autocorrelation of six lags with NeweyWest approach.a, b, and c indicate the coefficient being significantly different from 0 at the .01, .05, and .1 levels, respectively.

***, **, and * indicate the coefficient being significantly different from 1 at .01, .05, and .1 levels, respectively.

(continued)



17/28

Panel B: This panel reports the R2s of Models (10a) and (11) and the incremental explanatory powerof balance-sheet information for annual samples.

Year R2 of Model (11) R2 of Model (10a) Difference in R2

(1) (2) (2)2(1) Vuongs test

Mean .115 .139 .024 7.31a

1968 .126 .167 .041 4.21***1969 .055 .135 .080 7.60***1970 .104 .162 .057 6.79***1971 .140 .149 .009 2.46**1972 .055 .098 .044 5.28***1973 .174 .224 .050 7.33***1974 .182 .211 .029 5.27***1975 .173 .182 .009 3.05***1976 .172 .181 .009 1.63*1977 .215 .238 .023 3.67***1978 .123 .161 .038 6.03***1979 .127 .139 .012 2.49**1980 .126 .156 .030 6.10***1981 .143 .160 .017 4.81***1982 .091 .118 .027 5.38***1983 .136 .144 .007 1.86*1984 .174 .181 .006 2.94***1985 .123 .150 .027 6.05***1986 .147 .166 .019 4.99***1987 .107 .122 .015 3.79***1988 .157 .171 .014 4.01***1989 .131 .152 .021 4.88***1990 .095 .117 .023 4.62***1991 .090 .124 .034 5.05***1992 .130 .149 .019 4.26***1993 .096 .113 .016 4.21***1994 .073 .088 .015 4.64***1995 .049 .080 .031 6.82***1996 .094 .109 .015 4.99***1997 .095 .112 .017 4.88***1998 .042 .063 .021 5.61***

1999 .040 .073 .033 6.72***2000 .059 .091 .032 6.29***2001 .151 .194 .043 5.85***2002 .102 .113 .011 3.35***2003 .063 .095 .032 4.10***2004 .132 .140 .008 2.95***2005 .085 .100 .015 3.11***2006 .104 .121 .018 4.27***2007 .116 .126 .010 2.08**

Note: Annual regression results and the IEP of Balance-Sheet Information.

Panel B reports the annual regression R2

s of Model (10a) above those of Model (11), Rit5a1bxit1gDxit1eit; andthe incremental explanatory powers of balance-sheet information.aindicates the t statistics for comparing the difference in mean R2 between Model (10a) and (11) being significant at

Huang 283


18/28

average R2 of Model (10a) is significantly higher than that of Model (11) at the .01 level.

Figure 1 plots the IEP of the balance-sheet variables in Model (10a) against the explanatory

power of the earnings variables in Model (11) across the years.



To summarize, our empirical results show that the balance sheetrelated variables (Dqit,

Dbi,t, andDbit21) generally have significant effects, and they enhance the power to explain

stock returns after controlling for earnings and the earnings change. The directions of these

effects are generally consistent with the theoretical predictions, and their magnitudes are

economically important. Overall, in both statistical and economic terms, the balance-sheet

information improves the explanatory power of the return model relative to that of the earn-

ings onlybased benchmark model.

Complementarity Between Balance-Sheet and

Income-Statement Information

In this section, we explore how the incremental usefulness of balance sheetrelated vari-

ables varies over time and in cross sections With the balance sheet and the income state

0.000

0.050

0.100

0.150

0.200

0.250

1968

IEP; R-squaresR-squares of earnings-only model

IEP of balance-sheet related variables

year

2007200420011998199519921989198619831980197719741971

Figure 1. IEP of balance-sheet information. This figure plots the IEP of balance-sheet information,computed as the R2 of Model (10a) minus that of Model (11), relative to the R2 of Model (11).Note: IEP = incremental explanatory power.



19/28

therefore explore whether balance sheetbased information is incrementally more useful in

situations in which earnings variables are less informative about returns.

Time-Series Analysis

We first take a time-series perspective to examine how the usefulness of balance-sheet infor-

mation in explaining returns is related to that of earnings information. Over time, the expla-

natory power of earnings variables, denoted as R2(earnings), fluctuates, as does the IEP of

information constructed with balance sheet, denoted as IEP(BS). We find a significantly neg-

ative correlation between R2(earnings) and IEP(BS), with a Pearson correlation of2.29 (t =

1.90), which suggests that balance-sheet information complements earnings variables to a

greater extent in years in which the latter are less powerful in explaining returns.

Previous evidence suggests that there may be a time trend in the power of financial

statement information to explain returns (see, for example, Collins et al., 1997). To control

for a possible time trend, we also run a regression of IEP(BS) on R2(earnings) and a time

index (Time = 0,. . . ,39) as follows:17

IEP(BS)t5a01a1R2(earnings)t1a2 Timet1ut: 12

As reported in Table 5, IEP(BS) is negatively related to R2(earnings), both with and

without a time trend. The coefficient on R2(earnings) is 20.11 (t = 1.90) without a time

index and is 20.19 (t = 3.76) with a time index. This provides evidence that balance-sheet

information supplements earnings variables more in years in which the latter are less infor-

mative about stock returns.

We also note that the coefficient on the time index is significantly negative, indicating a

declining trend in the IEP of balance-sheet information in explaining cross-sectional

returns.

18

Cross-Sectional Analysis

Table 5. Relationship Between the IEP of Balance-Sheet Information and the Explanatory Power ofEarnings Over Time

Intercept R2 (earnings)t Timet Adjusted R2

0.04a

2.11c

.063(5.31) (21.90)0.06a 2.19a 20.08a .344(7.39) (23.76) (24.16)

Note: IEP = incremental explanatory power.

This table provides the result of time-series regressions of the IEP of balance-sheet information on the explanatory

power of earnings. The specification is as follows:

IEP(BS)t5a01a1R2(earnings)t1a2Timet1ut

where IEP(BS)t is the IEP of balance-sheet information, calculated as the R2 of Model (10a) in year t minus that of

Model (11) in year t, R2(earnings)t is the R2 of Model (11), and Timet is time index computed as year minus 1968.

For ease of exposition, we multiply the coefficient on Timet by 100.a and c indicate the coefficient being significantly different from 0 at the .01, .05, and .1 levels, respectively.

Huang 285


20/28

considered to be less informative or with future earnings that are more difficult to forecast.

They are firms with negative (vs. positive) earnings, young (vs. mature) firms, and firms

with a high (vs. low) degree of uncertainty about future earnings. We examine whether

balance-sheet information is incrementally more useful in these subsamples.

Loss versus profit firms. Rational economic behavior implies that a firms losses will notbe sustained (a loss-making firm will either have to improve its performance or face termi-

nation). This suggests that negative earnings are less informative about future cash flows

than are positive earnings (Hayn, 1995). Collins, Pincus, and Xie (1999) find that equity

book value becomes more important in explaining the stock prices of firms with negative

(vs. positive) earnings. In our context, we posit that balance sheetbased information plays

a greater role in explaining stock returns for loss firms than for profit firms.

Panel A of Table 6 compares the IEP of balance-sheet information between firms with

negative and positive earnings.19 The average R2 across the years of Model (11), in which

only earnings variables are used, is 4.6% for loss firms and 13.9% for profit firms. After

adding the balance sheetrelated variables, we obtain an average IEP of 4.3% for loss

firms. In contrast, the IEP of balance-sheet information is 2.1% for profit firms.20 The dif-

ference in IEP between the two groups is 2.2% (t = 3.46), significant at the .01 level. Thus,

balance-sheet information is incrementally more useful in explaining returns for firms with

negative earnings than for firms with positive earnings.

We note that for loss firms, the coefficient on xit is significantly negative and lower than

1, whether or not we include the balance sheetrelated variables. This might be an indica-

tion of investors belief that losses will be mean reverting. However, for profit firms, the

coefficient on xit is significantly positive, with a magnitude significantly greater than 1,

indicating that for firms making a profit investors actually place a weight on earnings that

is greater than the theoretical value on overall sample as predicted by Ohlson (1995) and

Zhang (2000).

For loss firms, adding Dqit in regressions removes the effect ofDxit, although the coeffi-

cient on Dqit is significantly positive, suggesting that the effect ofDxit is subsumed by that

of Dqit in this subsample. However, for profit firms, although adding Dqit substantially

reduces the effect ofDxit, the latter remains significantly positive together with the coeffi-

cient on Dqit. Contemporaneous capital investment has a positive coefficient in both firm

groups. The lagged capital investment is significantly negative, as predicted by Ohlson

(1995), for loss firms, but is insignificant for profit firms.

Young versus mature firms. For the purpose of our analysis, young firms refer to firmswith a relatively short history of public trading, which are usually at early stages of the life

cycle. We conjecture that earnings variables are less valuation relevant for young firms and

so the balance sheet should play a greater incremental role to supplement earnings

information.

We define a firm in a given year as a young firm if it has a listing history of 8 years

or less and as a mature firm otherwise, and we then divide the annual samples each into

subsets of young and mature firms.21 The results in Panel B of Table 6 show that

balance-sheet information explains more of the variations in stock returns for younger

firms. Across the years, the average IEP of balance-sheet information for young firms is

5.2%, compared with the IEP of 2.3% for mature firms. The difference in IEP between thetwo groups is 3% (t = 2.21), significant at the .05 level.

F t fi ddi D i i d th ff t f D ( ffi i t



21/28

6.

IEP

ofBalance-SheetInformationin

CrossSections

n

Intercept

xit

Dxit

Dq

it

Db

it

Db

it21

H

3

Dqit

AverageR2

IEP

DifferenceinIEP

:IEPofbalance-sheetinformationforlossandprofitfirms

rm

20.02

2.23a

1.41a

.139

(20.56)

(10.84)

(13.46)

20.01

2.04a

0.70a

0.47a

0.24a

0.05

0.07

.160

0.021a

(20.42)

(8.9

5)

(7.0

2)

(7.9

8)

(3.2

0)

(1.0

0)

(1.03)

(7.7

0)

m

0.00

20.83a

0.54a

.046

(20.06)(2

3.27)

(6.5

3)

0.02

20.63b

0.04

0.34a

0.12

20.20a

0.18

.089

0.043a

0.022a

(0.4

8)(2

2.24)

(0.5

3)

(7.2

2)

(1.6

0)

(23.40)

(0.36)

(6.5

9)

(3.4

6)

IEPof

balance-sheetinformationforyoungandmaturefirms

firm

0.07b

1.33a

0.84a

.118

(2.1

4)

(11.76)

(9.2

7)

0.06b

1.37a

0.33a

0.18a

0.10c

20.12b

0.48a

.142

0.023a

(2.0

3)

(8.7

4)

(3.0

8)

(3.1

0)

(1.6

8)

(22.43)

(8.42)

(4.6

7)

rm

0.13b

0.48

2.02a

.149

(2.3

4)

(0.5

8)

(2.7

1)

0.13b

0.34

0.99c

0.44a

0.47b

20.16

0.42a

.201

0.052a

0.030b

(2.5

4)

(0.4

1)

(1.9

0)

(2.8

5)

(2.0

0)

(20.92)

(5.12)

(3.3

5)

(2.2

1)

:IEPofbalance-sheetinformationforlow,medium,andhighforecaste

rrorfirms

ecaste

rrorfirm

0.10a

0.98b

0.75b

.056

(3.2

7)

(2.5

9)

(2.4

8)

0.09a

0.88b

0.52b

0.04

0.26a

20.01

20.01

.081

0.025a

(2.9

4)

(2.4

3)

(2.5

6)

(0.5

3)

(3.9

1)

(20.12)

(20.13)

(6.1

9)

foreca

sterrorfirm

0.10a

1.32a

0.84a

.074

(2.9

0)

(5.2

4)

(4.7

4)

0.09a

1.25a

0.32a

0.03

0.32a

20.06

0.43a

.107

0.033a

(2.9

3)

(4.3

3)

(2.6

2)

(0.2

9)

(3.5

3)

(21.14)

(4.76)

(5.0

2)

recasterrorfirm

0.08a

1.14a

0.81a

.098

(3.0

5)

(10.37)

(6.1

6)

0.08a

1.10a

20.01

0.34a

0.23b

20.23a

0.34a

.138

0.040a

0.015b

(3.4

3)

(6.1

9)

(20.10)

(8.3

3)

(2.0

6)

(23.73)

(4.75)

(6.6

7)

(2.3

5)

( c o n t i n u e d )


22/28


23/28

statistics of 1.90). There is strong evidence of convexity in the effect of Dqit for both the

young and mature firms (coefficients on HDqit are highly significant at the .01 level in

both subsets), consistent with the theoretical predictions.

Capital investment has a positive coefficient for both young and mature firms, as pre-

dicted. The lagged capital investment is significantly negative for mature firms and is insig-nificant for young firms.

Firms with uncertain future earnings. We further conjecture that investors rely more on the

balance sheet when they face greater uncertainty about future earnings.22 We use two

proxies for investor uncertainty about future earnings: (a) the accuracy of consensus analyst

forecasts, which is defined as the absolute value of actual earnings per share minus the

mean forecast scaled by the absolute value of actual earnings per share and (b) the disper-

sion of analyst forecasts, which is defined as the standard deviation of annual earnings fore-

casts scaled by the absolute value of actual earnings per share.23 The need for analyst

earnings forecast data in this subsection shortens the sample period to 1983 to 2007, which

reduces the sample to 34,916 observations.

We partition the annual samples into terciles and run regressions for each subsample.

Panel C of Table 6 reports the results for the partitions by forecast error. The IEP of

balance-sheet information is greater for firms with larger (absolute) earnings forecast errors

(i.e., less accurate forecasts). The IEP of balance-sheet information for the largest forecast

error group is 4%, whereas the IEP of that for the smallest forecast error group is 2.5%.

The difference in IEP between the high and low forecast error groups is 1.5% (t = 2.35),

significant at the 0.05 level.

We also note that when earnings forecasts are the least (most) accurate, the response of

investors to Dxit

is weakest (strongest), controlling for balance-sheet information. In Model

(10a), the coefficients on Dxit is insignificant for firms with high forecast errors (coefficient

= 20.01 and t = 0.1) but is significant for firms with low forecast errors. However, the

coefficients on Dqit and HDqit are significant in the high forecast error group but not so for

the low forecast error group. These results are consistent with the view that investors rely

more on balance-sheet information when earnings information is less reliable.

Panel D of Table 6 provides the results for the partitions by forecast dispersion. The

IEP of balance-sheet information for the highest dispersion group is 4.3%. In contrast, the

IEP of balance-sheet information for the lowest dispersion group is 2.3%. The difference

in IEP between these two subsamples is 2% (t = 2.96), significant at the .01 level. This

shows that balance-sheet information is incrementally more useful for firms with high (vs.low) forecast dispersions.

Similar to the above results, we find here also that the balance sheetrelated variables

largely replace the effect of the earnings change in explaining stock returns. Once controlling

for the balance sheetrelated variables, the coefficient on Dxit decreases but is still significant

in the low-dispersion group, and it becomes insignificant in the highest dispersion group. For

firms with the largest forecast dispersion, it is the profitability that is decision-useful.

To sum up, for the subsamples of firms considered above, the balance sheetrelated

variables generally have significant effects on returns, although the results on the effect of

Dbit21 are weaker or insignificant in some cases. Collectively, they significantly improve

the explanatory power of return models compared with earnings onlybased benchmarkmodels. More importantly, we find that balance-sheet information plays a greater incremen-

t l l i l i i t f fi ith i th t l i f ti ith f t

Huang 289


24/28

Summary and Concluding Remarks

This study examines the usefulness of balance-sheet information in explaining stock returns

beyond that of earnings information. Based on existing models of equity value, we show

that returns are related to three balance sheetbased factors in addition to earnings and theearnings change: the profitability change, contemporaneous capital investment, and the pre-

vious periods capital investment. The empirical results show that each of the three balance

sheetrelated variables generally has a statistically and economically significant effect on

returns (although lagged capital investment is not significant in some of the subsamples)

incremental to that of earnings variables and that the directions of the effects are consistent

with the theoretical predictions. Our expanded return model, which combines balance-sheet

and earnings variables, achieves an average explanatory power of 13.9% in annual samples,

compared with that of 11.5% for an earnings-onlybased benchmark model.

We further show that balance-sheet information complements the information in earnings

variables. Over time, the IEP of balance-sheet information is negatively correlated with theexplanatory power of earnings variables, suggesting that such information generally plays a

greater role in years in which earnings are less useful in explaining returns. In cross sections,

we similarly find that balance-sheet information is incrementally more useful for firms with

earnings that are less informative (e.g., firms with negative earnings and firms with a short

history) or with future earnings that are more uncertain (e.g, firms with high, vs. low, abso-

lute analyst forecast errors and firms with high, vs. low, analyst forecast dispersions).

Our study has implications for the question of whether to adopt a more balance sheet

based or a more income-statementbased model of financial reporting. Our results indicate

that each of the financial statements plays a distinctive informational role in determining

stock returns. More importantly, our study shows that the usefulness of the balance sheet

versus that of the income statement differs across firms, depending on a firms maturity, its

operational performance (negative vs. positive earnings), and economic environment (earn-

ings predictability). It is thus beneficial to develop reporting standards that recognize the

varying role of each financial statement under different economic conditions.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/

or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or

publication of this article:The authors gratefully acknowledge the financial support by the Hong Kong

Polytechnic University (Project No.: 4-ZZ6L).

Notes

1. The Financial Accounting Standard Board (FASB), in its Preliminary Views of the conceptualframework (Financial Accounting Series 1260-001), states that to help present and potential

investors and creditors and others in assessing an entitys ability to generate net cash inflows,financial reporting should provide information about the economic resources of the entity (its

assets) and the claims to those resources (its liabilities and equity) Information about the effects



25/28

2. A long-standing debate in the standard setting field is whether to adopt a more balance sheetbased or a more income statementbased approach to financial reporting. In recent decades, the

position of standard setting bodies such as the FASB of the United States and the International

Accounting Standard Board has shifted toward a balance sheetbased model; see, for example,

the Preliminary Views of the conceptual framework for financial reporting (FASB, 2006).However, some academics have expressed concerns about this, arguing instead for an income

statementbased approach (Dichev, 2008).

3. The distinction between profit and profitability has also been made in studies using residualincome or EVA as a performance measure (e.g., Biddle, Bowen, & Wallace, 1997; Stewart,

1994) and in studies that separate earnings growth driven by profitability from that by capital

investment in refining the return-earnings relation (e.g., Balachandran & Mohanram, in press;

Harris & Nissim, 2006).

4. There is growing evidence of nonlinearity in equity valuation; see, for example, Burgstahler andDichev (1997), Hao, Jin, and Zhang (2011), and Yee (2000).

5. A recent study by Chen and Zhang (2007) has developed a return model incorporating data fromboth the balance sheet and the income statement together with information from other sources

(such as growth opportunities and discount rates). Chen and Zhang (2007) do not focus on the

role of balance sheet per se; specifically, they do not address how much of a difference balance

sheetrelated variables make in explaining returns and for what types of firms these variables are

most useful.

6. Note that the linear model mentioned here, as used in Barth, Beaver, and Landsman (1998);Collins, Pincus, and Xie (1999); and Collins, Maydew, and Weiss (1997), is not equivalent to

Ohlsons (1995) model that is used to motivate some of the explanatory factors in our study.

7. Obviously, there is also information from sources other than financial statements that is impor-tant for investors, such as information from voluntary disclosures (e.g., Francis, Schipper, &

Vincent, 2002). These sources are beyond the scope of this study, and we omit the unspecifiedother information in Ohlsons model.

8. In our analysis, we use the reduced-form relations between value and accounting data as devel-oped in Ohlson (1995) and Zhang (2000). These relations rely on certain assumptions about the

dynamic behavior of cash flow (or residual income). Dechow, Hutton, and Sloan (1999) have

empirically examined Ohlsons linear information dynamics, and Biddle et al. (2001) have exam-

ined nonlinearities in the residual income dynamic as implied in Zhang (2000).

9. Numerous studies have empirically tested or applied the Ohlsons model (see, for example,Collins et al., 1997; 1999; Dechow et al., 1999).

10. Ohlson (1995) shows that (net) dividends (or, equivalently, capital investment) affect equity

market value dollar for dollar; as a result, investors are neither made better off nor worse off bycurrent capital investment (divestment). Also see Biddle et al. (2001) for a related discussion.

11. In contrast to the linear information dynamic in Ohlson (1995), contingent investment decisionsin Zhang (2000) lead to a convex relation between current and period-ahead residual income.

12. The derivation here is a simplified version of that given in Chen and Zhang (2007). Here, weignore information from outside financial statements.

13. Strictly speaking, the profitability of capital investment relates to a firms marginal (as opposedto average) market-to-book ratio. However, in the simplified context of Zhang (2000), the two

are assumed to be equal.

14. Following Brown et al. (1999), we use unadjusted R2s to compute the IEPs.

15. Although the I/B/E/S summary file covers a longer time period, it suffers from the problem ofstale earnings forecasts, which has the effect of reducing the standard deviations of earnings fore-

casts (Zhang, 2006), a variable that is of interest in cross-sectional analyses. For this reason, we

Huang 291


26/28

similar results for the two versions of the dependent variable. For brevity, we present only the

results using raw returns as the dependent variable in the sections below; the results based on

market-adjusted returns are available on request.

17. For ease of exposition, we multiply the coefficient on Timet by 100.

18. A decline in the IEP of balance sheetrelated information over time may be due to a changinginformation environment brought about by increased company disclosures (which act as compet-

ing information for financial statement information) or increased private information production

by analysts (Francis et al., 2002).

19. In this section, profitability dummy H is set to 1 if a firms return of equity is above the annualmedian within a subsample and 0 otherwise.

20. As indicated in Table 6, the IEP of our balance-sheet variables is statistically significant at the0.01 level in all the subsamples examined in this section.

21. We also use 5 years and 10 years as the cutoff points and find similar results.

22. Chen et al. (2002) provide evidence that firms are more likely to disclose balance-sheet informa-

tion to compensate for inefficiencies in analyst earnings forecasts.23. The mean forecast (forecast dispersion) is computed as the average (standard deviation) of theindividual earnings forecasts issued over a period of 8 months preceding the fiscal year end. If

an analyst issues multiple forecasts during the period, then only the latest is retained.

References

Baber, W. R., Chen, S., & Kang, S. (2006). Stock price reaction to evidence of earnings management:

Implications for supplementary financial disclosure. Review of Accounting Studies, 11, 5-19.

Balachandran, S., & Mohanram, P. (2010). Are CEO compensated for value destroying growth in

earnings? Review of Accounting Studies, 15, 545-577.

Balachandran, S., & Mohanram, P. (in press). Using residual income to refine the relationshipbetween earnings growth and stock returns. Review of Accounting Studies.

Ball, R., Kothari, S. P., & Robin, A. (2000). The effect of international institutional factors on proper-

ties of accounting earnings. Journal of Accounting and Economics, 29, 1-51.

Barth, M., Beaver, W., & Landsman, W. (1998). Relative valuation roles of equity book value and

net income as a function of financial health. Journal of Accounting and Economics, 25, 1-35.

Biddle, G. P., Bowen, R. M., & Wallace, J. S. (1997). Does EVA beat earnings? Evidence on associa-

tion with stock returns and firm values. Journal of Accounting and Economics, 24, 301-336.

Biddle, G. P., Chen, P., & Zhang, G. (2001). When capital follows profitability: Non-linear residual

income dynamics. Review of Accounting Studies, 6, 229-265.

Biddle, G. P., Seow, G., & Siegel, A. (1995). Relative versus incremental information content.

Contemporary Accounting Review, 12, 1-23.Brown, S., Lo, K., & Lys, T. (1999). Use of R2 in accounting research: Measuring changes in value

relevance over the last four decades. Journal of Accounting and Economics, 28, 83-115.

Burgstahler, D., & Dichev, I. (1997). Earnings, adaptation, and equity value. Accounting Review, 72,

187-215.

Chen, P., & Zhang, G. (2007). How do accounting variables explain stock movements? Theory and

evidence. Journal of Accounting and Economics, 43, 219-244.

Chen, S., DeFond, M., & Park, C. (2002). Voluntary disclosure of balance sheet information in quar-

terly earnings announcements. Journal of Accounting and Economics, 33, 229-251.

Collins, D., Kothari, S. P., Shanken, J., & Sloan, R. (1994). Lack of timeliness versus noise as expla-

nations for low contemporaneous return-earnings association. Journal of Accounting and

Economics, 18, 289-324.

Collins, D., Maydew, E., & Weiss, I. (1997). Changes in the value-relevance of earnings and book



27/28

Dechow, P., Hutton, A. P., & Sloan, R. G. (1999). An empirical assessment of the residual income

valuation model. Journal of Accounting and Economics, 26, 1-34.

Dichev, I. (2008). On the balance sheet-based model of financial reporting. Accounting Horizon, 22,

453-470.

Easton, P., & Harris, T. (1991). Earnings as an explanatory variable for returns. Journal of Accounting Research, 29, 19-36.

Financial Accounting Standards Board. (2006). Preliminary view: Conceptual framework for financial

reporting: Objective of financial reporting and qualitative characteristics of decision-useful finan-

cial reporting information (Financial Accounting Series No. 1260-001, July 6). Norwalk, CT:

Author.

Francis, J., Schipper, K., & Vincent, L. (2002). Expanded disclosures and the increased usefulness of

earnings announcements. Accounting Review, 77, 515-546.

Hao, S., Jin, Q., & Zhang, G. (2011). Investment growth and the relation between equity value, earn-

ings, and equity book value. Accounting Review, 86, 605-635.

Harris, T., & Nissim, D. (2006). The differential value implications of the profitability and investment

components of earnings (Working paper). New York, NY: Columbia University.Hayn, C. (1995). The information content of losses. Journal of Accounting and Economics, 20, 125-

153.

Kothari, S. P. (1992). Price-earnings regressions in the presence of prices leading earnings: Earnings

level versus change specifications and alternative deflators. Journal of Accounting and Economics,

15, 173-203.

Kothari, S. P. (2001). Capital market research in accounting. Journal of Accounting and Economics,

31, 105-231.

Kothari, S. P., & Sloan, R. (1992). Information in prices about future earnings: Implications for earn-

ings response coefficients. Journal of Accounting and Economics, 15, 143-172.

Lev, B. (1989). On the usefulness of earnings and earnings research: Lessons and directions from twodecades of empirical research. Journal of Accounting Research, 27(Suppl.), 153-201.

Lev, B., & Thiagarajan, R. (1993). Fundamental information analysis. Journal of Accounting

Research, 31, 190-214.

Ohlson, J. (1995). Earnings, book values, and dividends in equity valuation. Contemporary

Accounting Research, 11, 661-687.

Ou, J., & Penman, S. (1989). Financial statement analysis and pred

an examination

Documents