Download The Effects of Unrecorded Assets and Information

The Effects of Unrecorded Assets and Information Disclosure
on Future Earnings Response Coefficients
Shaw-Ping Chen, Associate professor, Department of Accounting, Providence University, Taiwan
Yu-Chih Lin, Associate Professor, Department and Graduate Institute of Accounting,
National Yunlin University of Science and Technology, Taiwan
Chung-Jen Fu, Professor, Department and Graduate Institute of Accounting,
National Yunlin University of Science and Technology, Taiwan
ABSTRACT
The purposes of this paper are to investigate the relationship between unrecorded assets,
information disclosure, and future earnings response coefficients (FERC)and to compare the disclosure
effects on the return-earnings relation for enterprises with different unrecorded assets. R&D intensity and
Capital expenditures are used as proxies of unrecorded assets. The results show that the relationship
between unrecorded assets and information transparency is significantly positive. Firms with higher
unrecorded assets have higher FERC. In addition, compared to firms with less unrecorded assets, the
firms with higher unrecorded assets how more sensitive moderating effects for earnings response
coefficient (ERC) and future earnings response coefficient (FERC).The management implication of this
paper suggests that firms with high R&D intensity or high capital expenditures could increase their
information transparency to decrease the information asymmetry problems, and hence increase their
enterprise value.
INTRODUCTION
Based on the generally-accepted accounting principles, the accountants treat research and
development (R&D) expenditures as current expense which reduce current earnings immediately.
Future cash flow that is expected to be generated by research and development (R&D) expenditure is only
partially reflected or responded to in current earnings (Collins, Kothari, Shanken, and Sloan, 1994). A
lack of timeliness in the disclosure of accounting information results a weak relationship between current
returns and current earnings. When economic events occur, a well-informed capital market can determine
the overall or total effects. Rational investors from the capital market tend to adjust the perceived or
expected future earnings, which alters corporate stock prices and returns on investment. This result has
led to studies examining the relationship between current earnings and the future earnings response
coefficient (FERC). Lundholm and Myers (2002) investigated how companies’ disclosure activities
affected the relationship between current returns, current earnings, and future earnings, and found that
companies that disclosed relatively more information also disclosed more forward-looking information.
Consequently, their current returns reflected significantly higher FERC.
Collins et al. (1994) indicated that a lack of timeliness and random interferences or disturbances
(noises) resulted in inferior current earnings informativeness. One of the main contributors to the lack of
timeliness for accounting information is the recognition or determination of intangible assets.
Underestimation of intangible assets is mainly caused by issues related to R&D expenditure and
The Journal of Global Business Management Volume 11* Number 1 * April 2015 Issue
27
underestimation of future earnings from newly acquired fixed assets. The R&D expenditures recognized
as expenses when they occurred. If the R&D is successful, the company would obtain significant
development opportunities, indicating that the company possessed unrecorded intangible assets. However,
if the R&D was not successful, the company would be equivalent to companies that have no intangible
assets (Chin, Lin, and Qiu, 2005). Signaling theory holds that when companies have good news or when
they are undervalued, management tends to release more information; therefore, the higher the company’s
R&D expenditure, the greater the underestimation of intangible assets. There exist the motivations for
management to disclose more information. The first objective of this study tries to find out the
relationship between unrecorded assets and information transparency.
Lundholm and Myers (2002) believed that increased disclosures of future earnings information
would reduce the effects that current earnings have on current returns. That is, the influences of current
earnings and future earnings information on current returns could be substituted. However, these findings
have not yet to be verified. In this study, we contend that Lundholm and Myers did not consider the
influences of various characteristics for each company. Hence, thesecond objective of this study was to
add a specific company characteristic (degree of unrecorded assets) when investigating whether the
influences of current earnings and future earnings information on current returns could be substituted.
LITERATURE AND HYPOTHESES
To date, only a few studies have investigated the relationships between current returns, current
earnings, and future earnings. When investigating the effects that various levels of information disclosure
had on the relationships between current returns, current earnings, and future earnings, Lundholm and
Myers (2002) found that companies with higher information transparency disclosed more
forward-looking information. The transparency of information has a positive moderating relationship for
the correlation between current returns and future earnings information. Tucker and Zarowin (2006)
found that compared to changes in share prices for non-income smoothing companies, changes in current
share prices for income smoothing companies contained more future earnings information. Therefore, the
smoothness of earnings increased their inform ativeness. Orpurt and Zang (2009) used the FERC to
provide evidence and explain how investors employing information from cash flow statements prepared
using the direct method could contribute to the projections of company future operating performance.
In a knowledge-based economy, innovation has become the key to the success or failure of all
companies. The innovations and technologies created from research expenditure, as well as the
subsequent capital expenditure, all contribute to companies gaining a competitive edge (Chin, Lin, and
Qiu, 2005). Previous studies have shown that a positive correlation exists between R&D and company
value (Sougiannis, 1994; Lev and Sougiannis, 1996).
Because of the high risks associated with the future operations of companies, generally-accepted
accounting principles consider R&D expenditure as current expenditures. For managers, to prevent the
underestimation of share prices, they tend to disclose more information. Highertransparent a company’s
information is, higher investors’ confidence in the expectation of company’s future earnings will be.
While the R&D expenditures lead to potentially valuable patents, direct disclosure should be a good
signal, and such information is considered usefulness to investors (Hughes, 1986). Thus, we proposed the
following hypothesis:
H1: The relationship between unrecorded assets and information transparency is positive.
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The Journal of Global Business Management Volume 11 * Number 1 * April 2015 Issue
Examining how increases in the level of disclosures affected market expectations, Healy, Hutton,
and Palepu (1999) found that the regression formula for current earnings and returns indicated that the
higher the disclosure level, the greater the current earnings coefficient. Lundholm and Myers (2002)
believed that increases in the current earnings coefficient, as mentioned previously, were caused by
changes in the expected future earnings not being applied to the regression formula. If increasing the level
of disclosures could enhance the relationship between current returns and future earnings, the current
returns of companies with poorer transparency would be decided more by current earnings, because these
companies demonstrate relative insufficiency regarding future earnings information. This is because
current earnings are a proxy variable for changes in future earnings. With increases in the level of
disclosure and more future earnings information made public, the influence that current earnings have on
current returns declines. This means that the influence of current and future earnings information on
current returns can be substituted based on the level of disclosure. However, study results did not support
the argument that current and future earnings information has a substitution effect for current returns
(Lund holm and Myers, 2002).
In this study, we contend that when considering companies with varying characteristics, because the
level of changes in expected future earnings differs, the level of disclosure required by investors also
differs. Therefore, the effects that the level of disclosure has on the correlations between current returns
and current and future earnings would differ. For investors, the higher the companies’ R&D expenditure,
the higher the values of intangible innovation; thus, investors would desire more future earnings
information. Additionally, the greater the information transparency, the more information asymmetry
would be reduced, and the stronger confidence in adjustments of future earnings would be, thereby
increasing the market FERC values. Simultaneously, the effects that current earnings have on current
returns would decline. However, for companies with less R&D expenditure,because of the lower inform
ativeness of their future earnings, the effect that information transparency had on current earnings and
current returns would be unclear. Thus, we proposed the following hypotheses:
H2: Because unrecorded assets differ between companies, the effects that information transparency has
on the correlations between current returns and current earnings also differs.
H2a: For companies with high unrecorded assets, the correlation between current returns and current
earnings declines as the level of disclosures increases.
H2b: For companies with low unrecorded assets, the relationship between the level of disclosures and the
correlation between current returns and current earnings is unclear.
SAMPLE AND RESEARCH DESIGN
Empirical Models for Hypothesis 1
The following model was used to test hypotheses 1. Based on signaling theory, we contend that the
firms with higher unrecorded assets disclosures more information.We organized the sample companies
from highest to lowest according to their unrecorded assets, where the top 50% of the sample were
considered companies with high unrecorded assets, and the other half were considered companies with
low unrecorded assets. R&D intensity index and capital expenditure index are the proxies of unrecorded
assets. Both are indicator variables, 1 for high unrecorded assets and 0 otherwise. Company size, and
industry are included as control variables (Huang, Huang, Chang, and Fu, 2011).For this study, we used
results obtained from the Information Disclosure and Evaluation System developed by the Taiwan
Securities & Futures Institute (SFI) as proxy variables for information transparency and information
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29
quality. The SFI divided the overall evaluation results into five categories or rankings: A+, A, B, C, and
C-, where C- denoted the lowest level of information transparency.
, for this ranking was 0 and
represented the base group for this study. Values of 1, 2, 3, and 4 for
, represented the
information evaluation result of C, B, A, and A+, respectively. A
of
4
denoted
the optimum
,
level of information transparency.
∝ ∝ &
∝
∝
,
,
,
,
,
, (1)
Where, for firm i the variables are defined as follows:
= Information transparency index
,
=
R&D intensity index(1 if high R&D intensity firms, 0 otherwise)
&
,
=Capital expenditure Index(1 if high R&D intensity firms, 0 otherwise)
= nature log of total assets
, = indicator variable (1 if electronic industry firms, 0 otherwise)
,
= the residuals
,
For Hypothesis 2, the focus of the regression formula was on the coefficient∝
. A
positive ∝
indicated that unrecorded assetswas positively correlated with information
transparency.
Empirical Models for Hypothesis2
For hypotheses 2. We contend that for different level of unrecorded assets, information transparency
has different moderating effect on the correlation between returns, ERC and FERC.We adapt the model
(Lundholm and Myers, 2002; Tucker and Zarowin, 2006)to test hypothesis 2.We use the method, as stated
previously, to separate the sample companies into two subgroups: high unrecorded assets firms and
unrecorded assets firms,
and then use the following model to test and compare the moderating effect of
information transparency:
,
,
,
,
, ∗
,
, ∗
,
, ∗
,
, ∗
,
, ∗
, ∗
, (2)
Where, for firm i the variables are defined as follows:
= current returns, which is the rate of return for common shares in the
Ri,t
tthyear(from May 1 in the tth year to April 30 in the t+1th year)
=previous earnings, which is the EPS in the t-1th year
Xi,t-1
=current earnings, which is the EPS in the tth year
Xi,t
=sum of future earnings, which is the sum of EPS for Years t+1, t+2, and t+3
Xi,t+3
= future returns, which is the rate of return for common shares from Years
Ri,t*3
t+1 to t+3 calculated based on compound interest
= Information transparency index
,
= cross multiplication of transparency index and previous earnings
, ∗
,
= cross multiplication of transparency index and current earnings
, ∗
, = cross multiplication of transparency index and sum of future earnings
∗
,
,
= cross multiplication of transparency index and future return
∗
,
, ∗
=
the residuals
,
The coefficients 1, 2, 3, and 4 measured the relationships between current returns and previous
period earnings, current earnings, future earnings, and future returns for companies that received an
evaluation rating of C-. measured the relationships between previous earnings and current returns, and
possessed a negative expected sign. was the response coefficient for current earnings (the greater the
current earnings, the greater the returns), and possessed a positive expected sign. measured the effects
that changes in expected future earnings had on current returns, and possessed a positive expected sign.
measured the relationship between returns and measure errors (the greater the measure errors, the lower
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The Journal of Global Business Management Volume 11 * Number 1 * April 2015 Issue
the returns), and possessed a negative expected sign. 6, 7, 8, and 9 measured the differences in the
slopes of each independent variable for companies from different evaluation rating groups, when
compared to the lowest evaluation rating companies. For Hypothesis 2, the focus of the regression
formula was on the coefficient 8. A positive 8 indicated that information transparency was positively
correlated with the relationship between earnings and returns from previous and future periods. The focus
of the regression formula was coefficients 8 and 7. When the coefficient 8 was significantly positive,
information transparency was positively correlated with the relationship between earnings and returns
from the previous and future periods. When coefficient 7 was significantly negative, information
transparency was negatively correlated with the relationship between current returns and current earnings.
When 8 was positive and 7 was negative, a substitution effect existed between the two factors.
EMPIRICAL RESULTS AND ANALYSES
Sample Selection
This study used listed and over-the-counter (OTC) companies in Taiwan between 2005 and 2007 as
samples. Because we used these companies’ actual earnings and returns for the next three years as proxy
variables for future earnings information and error measurement, information regarding 2006 sample
companies was collected until April 30, 2011. The data evaluation results were obtained from the Taiwan
Stock Exchange Market Observation Post System, and the financial reports, stock prices, and returns of
the sample companies were acquired from the Taiwan Economic Journal (TEJ) databases. The following
companies were excluded from this study: financial and insurance companies, chiefly because of their
varying evaluation methods and regulations; companies with an accounting period that was not based on a
calendar year system because the periods in which the returns were calculated differed; and companies
that had incomplete information regarding the variables. Consequently, we obtained a total of 2,884
annual company sample data. Table 1 shows the annual distribution of the sample companies. In 2005,
2006, and 2007, totals of 914, 970, and 1,000 companies were obtained, respectively. The number of
companies increased every year. There were 1,574 and 1,311 companies from the information and
electronic (I&E) and non-information and electronic industries, respectively.
Year
94
95
96
Total
Table 1: The annual distributions of the sample companies
I&E Industries
Non-I&E industries
488
426
533
437
553
447
1,574
1,311
Total
914
970
1,000
2,884
Table 2 presents the regression results of the relationship between unrecorded intangible assets and
disclosure. We focused on the coefficient ∝ of R&D intensity index ( &
, ) and ∝ of capital
expenditure index (
, ). From table 2, a value of 0.1223 was obtained for this coefficient∝ ,
which suggests that higher the R&D intensity, greater the firms’ information transparency (t = 4.3578,
p< .01). A value of 0.0141 was obtained for this coefficient∝ , which is positive, but not significant
(t=0.5998, p>0.10). Therefore, Hypothesis 2 is partially supported. Further, this results might show that
the undervalued assets of R&D is stronger than those of capital expenditure and that results in revealing
more information.
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31
Table 2: The regression results of the relation between
unrecorded intangible assets and disclosure
∝ ∝ &
∝
∝
,
,
,
,
Dependent variable:
Expected
sign
coefficient
,
Intercept
-0.6061***
?
&
0.1223***
+
,
0.0141
+
,
0.1548
?
,
0.1804***
+
,
Adjusted R2
0.0950
F-statistics
76.6211***
Sample size
2884
,
,
t value
-3.6535
4.3578
0.5248
14.2772
6.3335
Note 1：
1. variables are defined as follows: &
, =R&D intensity index;
, =Capital expenditure index;
, =Company
size;
, =number of employers;
, =industry index.
2. ***, **, and * represent significance levels of 0.01, 0.05, and 0.10 (when expected signs were present, we used a one-tailed test;
when expected signs were not present, we used a two-tailed test)
3. The t-value was obtained by heteroskedasticity processing (White, 1980) Table 3 the moderating effect of information transparency under different R & D intensity firms.
The samples are divided into two groups: high R&D intensity firms and low R&D intensity firms. We use
the evaluation results obtained through the Information Disclosure and Transparency Evaluation System
as the proxy variables for information disclosure. Based on the overall evaluation results, the Grade Ccompanies were used as the base group and , , ,
measured the relationship between the current
returns ( , ),previous earnings, current earnings, future earnings, and measurement errors of the lower
quality information transparency companies. The previous earnings ( , ) coefficient (
was
-213.8960 and -60.6086, demonstrating a significant negative correlation with current returns ( , )
(t=-3.23；p<0.01; t=-2.61, p<0.01). The results showed that the previous earnings ( , ) of Grade Ccompanies increased by NTD$0.1, and that, as the unexpected earnings decreased, the current period
returns decreased by 21.39% and 6.06%, which corresponded to the expected signs. The current earnings
( , ) coefficient ( was 228.7792 and 99.3699, demonstrating a significant positive correlation with
current returns ( , ) (t = 3.31, p< .01; t= 4.11, p<0.01). This result suggests that current earnings and
return increased by NTD$0.1 and 22.88% and 9.94%, respectively which corresponded to the expected
signs. The sum of future earnings ( , ) coefficient (FERC,
was 22.0161 and 16.5181. Although it
possessed a positive correlation with current returns ( , ), the result was not significant (t = 0.97,p>0.1;
t=1.27, p> 0.1), further indicating that investors do not trust information regarding future earnings from
lower quality information transparency companies. The coefficient ( of future return ( , ∗ ) was
-8.3816 for high R&D intensity firms,
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The Journal of Global Business Management Volume 11 * Number 1 * April 2015 Issue
Table 3: The moderating effect of information transparency under different R & D intensity firms
,
,
,
,
, ∗
,
, ∗
,
(3)
, ∗
,
, ∗
,
, ∗
, ∗
,
High R&D intensity firms
Low R&D intensity firms
Dependent variable: ,
Expected sign
Coefficient
t value
Coefficient
t value
？
Intercept
23.3041***
4.26
29.9141***
6.99
***
***
Xi,t-1
-213.8960
-3.23
-60.6086
-2.61
+
228.7792***
3.31
99.3699***
4.11
Xi,t
+
22.0161
0.97
16.5181
1.27
Xi,t+3
-8.3816
-1.24
-27.4531***
-3.97
Ri,t*3
*
*
-1.76
-4.633
-1.83
?
-4.7941
,
**
*X
-2.08
?
37.6462
1.26
-29.8689
i,t-1
,
**
*X
-1.96
6.5647
0.44
-64.1582
i,t
,
***
**
*X
2.39
12.4996
1.82
+
26.4365
i,t+3
,
-1.45
3.7737
1.21
?
-4.8379*
, *Ri,t*3
Adjusted R2
0.332
0.232
F-statistics
80.6664***
(<0.01)
49.2780***
(<0.01)
Sample size
1,442
1,442
Note 1：
1. , =current rdturn; Xi,t-1= previous earnings; Xi,t= current earnings; Xi,t+3 = sum of future earnings; Ri,t*3 = future return;
= cross multiplication of transparency index and previous
, = transparency index;
, ∗
,
earnings;
= cross
, ∗
, = cross multiplication of transparency index and current earnings;
, ∗
,
multiplication of transparency index and sum of future earnings;
, ∗
, ∗ = cross multiplication of transparency index
and future returns
2. ***, **, and * represent significance levels of 0.01, 0.05, and 0.10 (when expected signs were present, we used a one-tailed test;
when expected signs were not present, we used a two-tailed test)
3. The t-value was obtained by heteroskedasticity processing (White, 1980) indicating a negative, but not significant (t=-1.24,
p>0.1). The coefficient ( of future return was -27.4531, indicating a significant negative correlation with current returns ( , )
(t = -3.97, p< .01), which corresponded to he expected signs.
From table 3, the cross multiplication coefficient 8 of the transparency index and the sum of the
future earnings (
), in which the FERC of the high and low R&D intensity companies
, ∗
,
were 26.4365 and 12.4996, respectively, suggesting that the FERC of the high and low R&D intensity
companies were positive and significant (t = 2.39, p< .01; t = 1.82, p< .05). The results further suggest that
information transparency has a positive effect on the correlation between current returns and future
earnings. The cross multiplication coefficient
of the transparency index and current earnings
(
∗
)
measured
the
influence
that
information
transparency had on the correlation between
,
,
current returns and earnings. The results showed that the current earning response coefficient (ERC) of
high R&D intensity companies was -64.1582, which suggests that information transparency has a
significant negative effect on the correlation between current returns and earnings (t = -1.96, p< .05).
Furthermore, the information transparency of high R&D intensity companies has a positive and negative
correlation with the relationships between returns-future earnings and returns-current earnings,
respectively. Therefore, a substitution effect existed between the two factors and we retained Hypothesis 2.
From table 4, the coefficients 1, 2, 3, and 4 measured the relationships between current
returns and previous earnings, current earnings, sum of future earnings, and future returns for companies
that received an evaluation rating of C-.Additionally, the expected signs for these relationships were the
same as those mentioned previously.the cross multiplication coefficient 8 of the transparency index and
the sum of the future earnings (
), in which the FERC of the high and low capital
, ∗
,
expenditure companies were 31.7175 and 17.5018, respectively, suggesting that the FERC of the high and
The Journal of Global Business Management Volume 11* Number 1 * April 2015 Issue
33
low capital expenditure companies were positive and significant (t = 2.16, p< .05; t = 1.93, p< .05). The
results further suggest that information transparency has a positive effect on the correlation between
current returns and future earnings. The cross multiplication coefficient of the transparency index and
current earnings (
, ∗
, ) measured the influence that information transparency had on the
correlation between current returns and earnings. The results showed that the current earning response
coefficient (ERC) of high capital expenditure companies was-65.9474, which suggests that information
transparency has a significant negative effect on the correlation between current returns and earnings (t =
-1.89, p< .05). Furthermore, the information transparency of high capital expenditure companies has a
positive and negative correlation with the relationships between returns-future earnings and
returns-current earnings, respectively. Therefore, a substitution effect existed between these two factors
and we retained Hypothesis 2.
Table4: The moderating effect of information transparency under different capital expenditure
firms
,
,
,
,
, ∗
,
, ∗
,
∗
∗
∗
,
,
,
,
,
, ∗
,
Dependent
High capital expenditure firms
Low capital expenditure firms
Expect-e
variable: ,
d sign
Coefficient
t value
Coefficient
t value
？
Intercept
9.1442
1.57
33.0934***
7.57
-98.8469***
-2.45
-113.0085***
-3.36
Xi,t-1
+
256.5460***
3.38
105.3954***
3.10
Xi,t
+
11.9615
0.38
17.8702
1.08
Xi,t+3
-8.1593
-0.86
-21.6000***
-3.40
Ri,t*3
-2.89
?
1.2390
0.69
-6.3380***
,
?
-20.2824
-0.91
2.09268
0.13
, *Xi,t-1
-65.9474**
-1.89
-4.3194
-0.25
, *Xi,t
2.16
17.5018**
1.93
+
31.7175**
, *Xi,t+3
*R
?
-6.9595
-1.51
1.4968
0.48
i,t*3
,
0.3286
0.2234
Adjusted R2
F-statistics
61.6023***
(<0.01)
57.7400***
(<0.01)
Sample size
1,442
1,442
Note 1：
1. , =current rdturn; Xi,t-1= previous earnings; Xi,t= current earnings; Xi,t+3 = sum of future earnings;
Ri,t*3 = future return;
= cross multiplication of
, = transparency index;
, ∗
,
transparency index and previous earnings;
, ∗
, = cross multiplication of transparency
= cross multiplication of transparency index and sum of
index and current earnings;
, ∗
,
future earnings;
∗
=
cross
multiplication
of transparency index and future returns
,
, ∗
2. ***, **, and * represent significance levels of 0.01, 0.05, and 0.10 (when expected signs were present,
we used a one-tailed test; when expected signs were not present, we used a two-tailed test)
3. The t-value was obtained by heteroskedasticity processing (White, 1980)
Previous studies regarding transparency and earning information obtained differing results because
they did not consider the significance of using future earnings information or inform at iveness. This
study showed that higher quality information transparency companies are more informative regarding
future earnings information. Furthermore, the reason for the weak correlation between returns and
earnings may be the underestimation of future profitability based on unrecognized assets. We categorized
sample companies into groups of high and low R&D expenditure and investigated the relationships
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The Journal of Global Business Management Volume 11 * Number 1 * April 2015 Issue
between information transparency and non-current returns and earnings. The results showed that high
R&D intensity companies have better the information transparency of a company, the more informative
the future earnings that are reflected by current returns, and, conversely, the less informative the current
earnings. Therefore, future and current earnings demonstrate a substitution effect. We get the same results
for high and low capital expenditure firms. The management implication of this paper suggests that firms
with high unrecorded assets could increase their information transparency to decrease the information
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