The relationship between profitability and the level of compliance to the International Financial Reporting Standards (IFRS): an empirical investigation on publicly listed corporations in the Philippines.
Ferrer, Rodiel C. ; Ferrer, Glenda J.
INTRODUCTION
The business world is involved in a myriad of transactions, and
accounting is the tool that seeks to simplify every aspect of this
complex environment. Through the years, business has evolved and
diversified into various forms and methodologies. This has prompted the
need for a specialized system of monitoring and evaluation of its
objective, to earn profit, without jeopardizing ethics and the welfare
of various sectors.
One of these systems is the audit. Audits are performed to
determine the validity and reliability of information, and to provide an
assessment of a system's internal controls. Classifications of
audit include: operational audit, financial audit, compliance audit,
information systems audit, and investigative or forensic audit.
Financial statements provide basically quantitative financial
information about a business enterprise that is useful to a wide variety
of users in making economic decisions. To lend credibility to said
financial statements; these must be audited by independent certified
public accountants (CPAs). Guided by generally accepted auditing
standards (GAAS), the CPA conducts the audit examination and renders a
report stating an opinion about whether such financial statements were
presented fairly in conformity with generally accepted accounting
principles (GAAP). However, the management of the business enterprise is
primarily responsible for the preparation and presentation of financial
statements that conform to GAAP. Any changes or adjustments to correct
material misstatements discovered in the audit need management approval.
If not obtained, the CPA practitioner is obliged to make the necessary
modification in the "Independent Auditor's Report"
(Racasa, 2003).
Annual reports are the primary mode of communication used by the
company to correspond with stakeholders (Botosan, 1997; and Lang and
Lundholm, 1993). Through these reports, companies disclose relevant
information which plays a crucial role in the decision-making processes.
As stakeholders rely heavily on these pieces of information when making
different types of decisions, Cooke claims that it is important to
assess the extent of disclosures made by a corporation (Cooke, 1989).
These pieces of information are crucial in the decision-making processes
regarding the allocation of scarce resources for stakeholders.
In regard to these revisions of Philippine accounting standard,
this study has an earnest desire to have a deeper and clearer
understanding regarding the extent of International Financial Reporting
disclosure of selected publicly listed corporations in the Philippines
and aims to develop strategy to which maximum compliance with
International Financial Reporting Standard. This study also seeks to
identify the relationships between profitability and the level of
compliance among publicly listed corporations in the Philippines for the
year 2008.
THEORETICAL FRAMEWORK
The framework of this study is grounded with interpretation of
Padayogdog (2003) regarding the agency theory proposed by Jensen and
Meckling (1976; as cited by Watts and Zimmerman, 1986 and Barderlipe,
2008).
Agency theory depicts a relationship wherein the principal depends
on the agent to act on the principal's behalf. Such relationship
also exists between the stakeholders (the principal) and the management
(the agent), although these parties differ from each other in terms of
executing actions that will be beneficial to them (Cataldo, 2003).
Conflicts between the two parties arise because of their self-interest
pursuits that compromise teamwork and goal congruence. The dispute may
lead to the so-called information asymmetry between the management and
the stakeholders.
Information asymmetry happens when one party has better access to
information than the other (Lee and Choi, 2002). In the firm setting,
such condition takes place when management has the ability to control
and to conceal information that is supposed to be made known to other
users. Because of a pre-disclosure environment within the organization,
management can exercise its prerogative in presenting only the
information that they want to reveal; thus, altering the outcome of
other user's decisions relying on such financial information.
With a high level of information asymmetry, stakeholders could not
avail the incentives, the resources, and the access to information in
overseeing management's actions (Richardson, 2000). This heightened
the presence of information asymmetry as a necessary requirement for
earnings management to take place (Dye, 1988; as cited by Richardson,
2000) since the environmental conditions surrounding the firm provides
opportunities for managers to manipulate information presented to the
stakeholders.
In a world of corporate asymmetric information, managers cannot
reveal all information. Finding an effective way of conveying
information is important. Companies do not just tell their investors
(current and potential) that they are "high quality, profitable
companies who practice good corporate governance to enhance
shareholder's value"; they would undertake certain activities
to signal that they really are. Management sends signals to communicate
the true value of a company. One example of such signals is a detailed
and clear financial report and consistent update of company information,
which is by way of voluntary disclosure. Such action is a signal to
investors that they are committed to reduce "agency problems"
in the company as well.
It must be noted that it is a mode of comments via financial
statement. signaling theory is needed to convey information when
transacting parties do not know each other well--that is, the reporting
company to its various users (Tan, 2003).
Chiang (2005) cited Spence (1973) on information asymmetry that it
exists between a company's managers and its investors. The company
can provide information to the investor in order to eliminate the
asymmetry. If information asymmetry exists, there is no way for the
investor to understand the real situation of the company's
operations. Prior research indicates that investors rely on the
information sent out from the company to make investment decisions. In
practice, companies with good operating performance often disclose
information to the public to promote positive impressions of their
company.
CONCEPTUAL FRAMEWORK
Agency theory laid the foundation for this study. A company's
true value, its firm characteristics, cannot be conveyed directly to its
stakeholders more importantly to its shareholders. This is for the
reason that shareholders are not involved with the company's
operations. Shareholders hire managers to oversee and run company
operations.
The managers are therefore the ones who are aware of the real value
of a company's condition and position. Thus, there exists
information asymmetry. Stakeholders are not aware on the company's
real value--firm characteristics. To be able to reduce information
asymmetry, managers prepare financial reports. These financial reports
contain information regarding the financial condition as well as
position and other financial information (such as listing status, number
of employees, external auditor) relating to a company.
One way of conveying this information is by way of disclosing such
information. Through disclosure of company information, a company's
true value that is its firm characteristics can be communicated to its
various users--stakeholders.
This study used profitability ratios such as Return on Assets,
Return on Equity, Return on Sales, Earnings Per Share, Revenues and the
level of International Financial Reporting Standard disclosure as
Independent Variables. Securities and Exchange Commission and Financial
Accounting Standard Board are the Intervening Variables.
Profitability is measured and regressed to the level of
International Financial Reporting Standard disclosure of publicly listed
firms using linear regression. The level of IFRS disclosure of each firm
will be measured using an index derived from IFRS Checklist to be
provided by SEC and IFRSC. These variables was used to try to increase
the explanatory power of the model by considering other factors that
affect the level of IFRS disclosure, financial statement disclosure
index and relationship between predicted variables with the level of
IFRS disclosure.
[FIGURE 1 OMITTED]
STATEMENT OF THE PROBLEM
The main purpose of this study is to identify the magnitude of
financial disclosures by Philippine companies and aims to develop
strategy in assuring maximum compliance with International Financial
Reporting Standard. This paper also seeks to know the relationship of
profitability measures that might affect such IFRS disclosure
requirements.
Through the aforementioned objectives this study attempts to answer
the following questions:
1. What is the extent of compliance of publicly listed corporations
in the Philippines, using IFRS disclosure checklist as indicated by the
disclosure index?
2. Is there a significant relationship between profitability and
the extent of IFRS disclosure index?
SIGNIFICANCE OF THE STUDY
This study has an earnest desire to have a deeper and clearer
understanding regarding the extent of International Financial Reporting
disclosure of selected publicly listed corporations in the Philippines
and aims to develop strategy to which maximum compliance with
International Financial Reporting Standard. This study also seeks to
identify the relationships between profitability and the level of
compliance among publicly listed corporations in the Philippines for the
year 2008. The different sectors that may benefit from such are the
Accounting Standards Council, PICPA, SEC, Academe, management and the
Auditing Firms.
The results of this study will be highly beneficial to different
members of the business community due to the fact that this study gives
them updates on the compliance of different companies that belong to
publicly listed corporations in the Philippines on the new standard
relating to presentation and preparation of financial statement.
International Accounting Standard Board
It behooves the IASB to have a better understanding of the result
of this study for they can easily determine the loopholes and weaknesses
of pronouncements involving the presentation of Financial Statements.
The IASB will also find this meaningful because it will give them
thought on which among the accounts on the face of the financial
statements are not usually given emphasis when it comes to financial
reporting. The generated results will provide this sector a basis for
suggestions for different companies to comply with the disclosure
requirements by the standard and would give them idea regarding factors
affecting the company's level of compliance with international
financial reporting standard.
Philippine Institute of Certified Public Accountants
The PICPA, with its various arms, needs to be in the know with
respect to the study in order to inform its nationwide membership the
need for unified reporting system in the midst of diversification.
The Security and Exchange Commission, since it is the governing arm
with aspect of compliance may set up additional requirements to be
followed for the regular submission of Financial Statement Reports and
for them to have glimpsed how these companies prepared and presented the
financial statement.
Academe
The Academe's knowledge on this sector would be of vital
importance. As the adage goes, learning is better achieved if you start
from the bud. The knowledge imparted to the students would help them be
aware of the proper presentation for Financial Statements especially at
a time the moment they become professionals and they could share the
idea of which factor greatly affect the extent of financial statement
disclosure. This will also minimize the curb if not totally eradicate of
differing reports.
Auditing Firms
The Auditing firms, among the entities mentioned, have the greater
level of influence in terms of compliance audit. They can recommend the
appropriate forms or even inform the clienteles in order to arrive at a
more uniform aspect of presentation. The significance of the compliance
analysis on the Investors provides an impetus for them to make a faster
comparison of the industry performance. The differing Account Titles and
presentation serves as an impediment in the typical ratio analysis for
such. They can suggest to different financial statement users as to how
to focus with different variables affecting the compliance report of the
company.
Management
This study would also be of great help to the management of
publicly listed corporations in the Philippines. The management would
identify strategy in assuring maximum compliance with International
Financial Reporting Standard. They would also know which among
profitability ratios that might affect such financial disclosures.
Future researcher
The future researchers will likewise benefit from the study. They
could make use of the data gathered as baseline information for further
researches by considering other industries and other ratios not used in
this study and to delve to other industry than Food, Beverage &
Tobacco, Telecommunication, and Information Technology Industries.
OBJECTIVE AND METHODOLOGY OF THE STUDY
This paper aims (1) to empirically identify the magnitude of
financial disclosures by Philippine companies in three selected
Industries namely Food, Beverage & Tobacco, Telecommunication, and
Information Technology Industries, (2) to investigate whether Philippine
publicly listed corporations comply with International Financial
Reporting Standard, (3) to develop strategy to aid in maximum compliance
with IFRS and (4) to study the relationship of profitability ratios with
the level of compliance with IFRS among publicly listed corporations in
the Philippines for the year 2008 as this was the most recent year for
which annual reports were available at the time of study.
To satisfy this objective, the researchers obtained the annual
report of publicly listed corporation which serves as secondary data.
The researchers quantified the disclosures found in the annual reports
by computing the disclosure index. The researchers employed the
dichotomous procedure in computing for the disclosure index wherein each
company will be awarded a score of '1' if the company appears
to have disclosed the concerned disclosure and '0' otherwise.
Once scoring of the companies is completed, each company is represented
with a score reflecting the number of disclosures against which it was
found to have disclosed. After which, the score of the respective
company is divided by the total number of score. Consistent with the
disclosure index by Cooke (1989, as cited by Hossain et. al., 2006), the
disclosure index is computed as follows:
[T.sub.j] = [[m.sup.j].summation over (i=1)] di
Where: d = 1 if the item [d.sub.i] is disclosed; and 0 if the item
[d.sub.i] is not disclosed.
[m.sub.j] = denotes the disclosure item specified in the checklist
[DI.sub.j] = [T.sub.j]/[n.sub.j]
Where: [T.sub.j] = amount computed using Equation 1
[n.sub.j] = number of items expected to be disclosed
Considering the mathematical model for the disclosure index, it is
inferred that as the value of the index approaches to 1, the level of
disclosure and compliance is higher (the entity provides more
information) and the compliance is more satisfactory until it reaches DI
= 1, in case of which we speak about full compliance.
After quantifying of the disclosures found in the financial
statements of the selected companies has been made, the regression model
was used to determine the relationship between profitability ratios with
the level of compliance with IFRS among publicly listed corporations in
the Philippines.
The hypotheses of the study can be specified as under:
Null Hypothesis (Ho1): Profitability is not significantly related
to International Reporting Standard Disclosure Index.
Alternative Hypothesis (Ha1): Profitability is significantly
related to International Reporting Standard Disclosure Index.
MODEL SPECIFICATION
To achieve the objective, an econometric model was employed.
Econometrics is an application of mathematical and statistical
techniques to economics in the study of problems, the analysis of data,
and the development and testing of theories and models. Economic
modeling technique that seeks to explain in mathematical terms the
relationships between key economic variables such as capital spending,
wages, bank interest rates, population trends, and also government
fiscal and monetary policies. Even though the main focus of econometric
models has been economic data, econometrics can still be employed using
data that are not used in economic terms (Woolridge, 2003).
Hair et. al. (1995) states that the regression analysis is the most
commonly used and is a versatile modeling technique for business
decision-making. Because of this, the econometric model that was
employed to estimate the degree and significance of the association
between profitability and the IFRS disclosure index as well as its
significance is the multiple regression model. According to Woolridge
(2003), the multiple regression analysis allows the users to explicitly
control many other factors that affect the dependent variable. Compared
to simple linear regression model, the multiple regression analysis
allows us to correlate more independent variables to our dependent
variable which in turn will be useful in determining the true
relationship between the independent variable and the dependent
variable.
The following regression has been estimated:
[IFRSDISC.sub.i] = [[beta].sub.0] + [[beta].sub.1][ROA.sub.i] +
[[beta].sub.2][ROE.sub.i] + [[beta].sub.3][BEPS.sub.i] +
[[beta].sub.4][REV.sub.i] + [[beta].sub.5][ROS.sub.i] + [e.sub.i]
where:
[IFRSDISC.sub.i] = IFRS disclosure index for a [firm.sub.i]
[ROA.sub.i] = Return on assets of [firm.sub.i]
[ROE.sub.I] = Return on Equity of [firm.sub.i]
[BEPS.sub.i] = Basic earnings per share of [firm.sub.i]
[REV.sub.i] = Log of the revenues of [firm.sub.i]
[ROS.sub.i] = Return on sales of [firm.sub.i]
[beta]0 i [beta]1 i [beta]2 i [beta]3 i [beta]4 i [beta]5i =
Percentage ownership of shareholders in firm i
[e.sub.1] = Error term
DEPENDENT VARIABLE
In this research, the International Financial Reporting Standards
Disclosure Index (IFRSDISCi) is used as the dependent variable. It is
aimed to determine how the IFRS compliance as measured by the disclosure
index is explained by the independent variables of the regression model
as discussed below.
INDEPENDENT VARIABLES
The independent variables used in this research are the various
profitability measures of the firm. These variables were utilized to
determine if the profitability of the firm explains the level of IFRS
compliance of the publicly listed corporations in the Philippines.
Specifically, the independent variables were computed as follows:
ROA: Return on assets is obtained by dividing the net income over
total assets. ROA is used since it one of the most common measures of
profitability (Hillton, 2007) and it is easy to employ (Hirschey &
Wichern, 1984). For this study we expect to have a significant
relationship between ROA and IFRS disclosure index.
ROE: Return on Equity is computed by net income over total
equities. ROE as a measure of company's profitability may affect
the IFRS disclosure. If the company is doing well and earning
exceptionally, it must be easier for that company to take necessary
measures to comply with the IFRS disclosure requirements. Ergo, it is
expected to have a significant relationship between ROE and IFRS
disclosure index.
BEPS: A basic earnings per share is calculated by dividing net
income over weighted average of ordinary shares. We expect that to have
a significant relationship between BEPS and IFRS disclosure index.
REV: Natural logarithm of sales revenue has also been considered in
measuring the profitability of the company. For this study we expect to
have significant relationship between log of revenues and IFRS
disclosure index.
ROS: Return on sales is computed by dividing net income over total
sales. Hence, we expect to have significant relationship between ROS and
IFRS disclosure index.
RESULTS AND ANALYSIS
This portion of the study answers the research problem and
objectives of the paper. This chapter presents the summary statistics of
the data gathered, the result of the regression analyses made using the
IFRS disclosure index as the dependent variable and various
profitability measures of the firm as the independent variable.
EMPIRICAL FINDINGS
The researchers examined the latest annual reports of different
publicly listed corporations that belong to three (3) industries namely
Food, Beverage & Tobacco (FBT), Telecommunication (TI) and
Information Technology Industries (IT). Disclosure scoring was performed
on 981 items of IFRS disclosure checklist 2008 issued by
PricewaterhouseCoopers. Section A of the disclosure checklist
particularly subsections A1 to A9 was used and considered in this
research. Section A includes disclosure for consideration by all
entities and has subsections such as A1 for General Disclosure, A2 for
accounting policies, A3 for Income Statement (and related notes), A4 for
Statement of changes in shareholders' equity (and related notes),
A5 for Balance sheet (and related notes), A6 for Cash flow statement, A7
for Business combination and disposal, A8 for Financial instruments and
A9 Non-current assets held for sale and discontinued operations.
Findings reveal that there are six (6) PLCs comprised the
Telecommunication Industry; seven (7) PLCs comprised the Information
Technology Industry and twenty one (21) PLCs comprised the Food
Beverages and Tobacco. It also depicts the disclosure Index of each of
the PLCs, TI garnered a DI of .9886 or 98.86%; IT obtained the maximum
level of disclosure was demonstrated scoring a DI of .9900 or 99.00% of
the applicable items; and FBT attained a DI of .9894 or 98.94%. This
average disclosure level is very satisfactory given the fact that IFRS
revisions and new pronouncements on disclosure requirements.
DESCRIPTIVE STATISTICS OF THE DISCLOSURE INDEX
As a preliminary tool for data analysis, the researchers computed
for the descriptive statistics of the data gathered. Specifically, the
researchers considered the mean of the dependent and independent
variable as well as its standard deviation. As presented in Table 1, it
can be seen that the mean of the disclosure index is .9893 which
connotes a high level of compliance with IFRS of the sample firms. Also,
it is depicted from the descriptive statistics that the mean of the
disclosure index is not far from the minimum and maximum score recorded
in the study which means that the level of compliance among the each of
the firms in the three industries selected are not far from each other.
This observation is confirmed by the computation of the standard
deviation, a measure of spread in the sample data. The low disclosure
index standard deviation shows that the data gathered are not widely
spread. Thus, the existence of an outlier in the data set is not
plausible.
DESCRIPTIVE STATISTICS OF THE PROFITABILITY MEASURES
As presented in Table 1, the average ROA of the companies chosen as
the sample of this research is .067916 or 6.79% while the lowest ROA
recorded is -.22208 or -22.21% and highest is .9474 or 94.74%.
Considering the lowest and highest ROA presented in the data set, there
is a range of 1.16 between the lowest recorded ROA and the highest
recorded ROA which may signify a very large spread in the dataset.
However, the computed standard deviation for the data set is still in an
acceptable level.
For the return on equity, the average ROE of the companies chosen
as the sample of this research is -0.026629 or 2.67% while the lowest
ROE recorded is -1.8158 and highest is .5409. The difference between the
minimum and maximum recorded amount may signify a very wide spread in
the data set. However, this problem was addressed by the computed
standard deviation for the data set is still in an acceptable level.
For the Basic Earnings per share, the average BEPS of the companies
chosen as the sample of this research is 8.16 while the lowest BEPS
recorded is -1.17 and highest is 181.65. The difference between the
minimum and maximum recorded amount signifies a very wide spread in the
data set. This observation is confirmed by the computation of the
variance and standard deviation whose values are 1116.16 and 33.41,
respectively.
For the revenue measure of profitability, the average revenue of
the companies chosen as the sample of this research is 24.80 while the
lowest revenue recorded is 16.99 and highest is 31.41. The difference
between the minimum and maximum recorded amount may signify a very wide
spread in the data set. Even though the standard deviation is greater
than 1, the researchers still accept the spread in the data set for it
is normal for the revenues of these firms to be widely spread from each
other.
Lastly, for the return on sales, the average ROS of the companies
chosen as the sample of this research is -3.24 while the lowest ROS
recorded is -109.47 and highest is .64. The difference between the
minimum and maximum recorded amount may signify a very wide spread in
the data set. This observation is confirmed by the computation of the
variance and standard deviation whose values are 342.21 and 18.49
respectively.
PRESENTATION OF REGRESSION ANALYSIS
After computing for the descriptive statistics of the data gathered
in this study, the researchers performed the multiple regression
analysis using MegaStat in order to determine the degree and
significance of association between the IFRS disclosure index and
profitability measures. The results are presented below:
Mathematically, the regression results can be written as follows:
[IFRSDISC.sub.i] = .9945 + -.0011 [ROA.sub.i] + .0010 [ROE.sub.i] +
-.000022 [BEPS.sub.i] + -.00019262 [REV.sub.i] + .000021 [ROS.sub.i] +
[e.sub.i]
Considering this regression equation, it is predicted that holding
all profitability measures at a value of 0, the level of compliance
among firms in the sample will be at .9945 as measured by the disclosure
index. The .9945 disclosure index is the measure of compliance to IFRS
considering that firms are experiencing zero profitability. Thus, this
finding implies that compliance with IFRS, regardless of profitability,
will still be at a high level.
Upon performing the regression model, the regression coefficients
were derived using MegaStat. It was discovered in the regression model
that Return on Assets has a negative coefficient for its OLS estimate.
It means that holding all other factors constant, every one unit
increase in Return on Assets will cause the IFRS disclosure by -.0011.
Thus, this coefficient implies that ROA is negatively associated with
the level of compliance with IFRS.
The regression results depicted a positive coefficient for its OLS
estimate for return on equity. This implies that holding all other
factors constant, every one unit increase in return on equity will
consequently yield to a .0010 increase in IFRS disclosure. Thus, this
coefficient shows a positive association between IFRS disclosure and
return on equity.
Looking at Table 2, the regression results showed a negative
coefficient for BEPS. The coefficient implies that for every one unit
increase in BEPS, there will be a corresponding decrease in IFRS
disclosure under the ceteris paribus assumption. This implies that a
negative association exists between BEPS and IFRS disclosure.
The researchers found out that there is a negative coefficient for
REV variable. It implies that holding all other factors constant, every
increase in unit of REV will cause a .00019 decrease in IFRS disclosure
index. Thus, it signifies a negative association between revenue and
IFRS disclosure index.
The p-value exhibited .4415 which is higher than the level of
significance ([alpha] = 0.05) therefore the overall model does not
depict significant relationship of five (5) variables such as ROA, ROE,
BEPS, REV and ROS. This is attributed to the insignificant relationship
of variables to IFRS disclosure index.
TESTING FOR PLAUSIBILITY AND ROBUSTNESS
This section highlights the test that were carried out to determine
the plausibility and robustness of the model used or make sure that the
model does not violate the fundamental assumptions of ordinary least
squares which is crucial to the precision of the results it will
generate. The OLS assumptions known as multicollinearity,
heteroskedasticity, and autocorrelation.
TESTING FOR MULTICOLLINEARITY
To determine whether the proposed model has committed the violation
of multicollinearity or the presence of a linear relationship among the
variables, this study performed the Variance Inflation Factor (VIF). As
a rule of thumb, the VIF must not exceed 10, otherwise, it is an
indication that multicollinearity exists.
The VIF as computed by Megastat and presented in Table 4, shows
that the variables are not highly correlated to each other to warrant
any changes in the model. The mean VIF of 1.253 is considerably far from
the usual threshold of 10 and even from 5 which some statisticians would
use as their decision rule. Thus, this model is relieved from committing
the violation of multicollinearity.
Although the variables would seem correlated to each other, there
was no presence of multicollinearity found. To validate the premise,
this study performed another test for multicollinearity by determining
the values of the R-squared and the tolerance values of each variable
based on the individual/ auxiliary regression with IFRS disclosure
index.
Table 5 summarizes that ROE has the lowest R-squared value of
.000965 while BEPS has the highest R-squared value of .050231.
Consistent with the Lawrence Klien's rule of thumb, if the
R-squared of the auxiliary regressions are greater than the R-squared of
the overall regression, then the evidence of multicollinearity is
presumed to exist.
In this study the overall R-squared is 0.150238 as shown in Table
5, then the variables are not collinearly related. Moreover, a tolerance
close to 1 means there is little multicollinearity whereas a value close
to 0 suggests that multicollinearity may be a threat. The tolerance
values computed by MEGASTAT indicate that values are very close to 1,
confirming that no violation was made. As noted, ROE has the highest
tolerance value of almost 1.000 while BEPS has the lowest, yet still a
very high tolerance value of 0.949769. This shows that the chances of
multicollinear relationship are very remote with a high degree of
tolerance exists.
TESTING FOR HETEROSKEDASTICITY
To test the presence or absence of any violation that the model
might have committed, the model underwent the White's Test, using
the EVIEWS software, for Heteroskedasticity which means that the error
of each observation must come form the same probability distribution
(Halcoussis, 2005).
One way of proving the non-existence of heteroskedasticity was by
comparing the pvalues and the level of significance ([alpha]). If the
p-value is greater than a, then the probability of incorrect rejection
of the null hypothesis of no heteroskedasticity is greater than its
level of significance; then indicating the absence of non-constant
variation in the residual terms. Tests exhibited that the p-values is
.67450 as shown on Appendix B which is greater than [alpha] = 0.05.
Thus, IFRS disclosure index model has no heteroskedasticity relationship
in this study.
TESTING FOR AUTOCORRELATION
The Durbin-Watson statistics is a test statistic used to detect the
presence of autocorrelation in the residuals from a regression analysis.
It is named after James Durbin and Geoffrey Watson.
Autocorrelation is commonly seen or is endemic in time-series
analysis or the presence of spatial correlation across the order of
observations in a cross-sectional econometric model, it is still
important to establish that autocorrelation is not present in the model
to enhance the integrity of the conclusion drawn from it.
This study used the Run's test to verify the true state of
autocorrelation in the IFRS index model. Using the MEGASTAT software,
the expected value of residuals [E(resid)] and the variance of residuals
([[sigma].sub.r.sup.2]) is computed as
E(resid) = 2[T.sub.1][T.sub.2]/T + 1
[[sigma].sub.r.sup.2] = 2[T.sub.1][T.sub.2](2[T.sub.1][T.sub.2] -
T)/[T.sup.2](T - 1)
where:
[T.sub.1] = number of positive residuals
[T.sub.2] = number of negative residuals
T = number of observations; and
[[sigma].sub.r.sup.2] = variance of residuals. Incidentally,
[[sigma].sub.r] refers to the standard deviation of residuals computed
as the square root of the variance.
Substituting the formula, this method obtained the figures as
presented on Table 6 that will be needed for the Run's test.
Upon substitution, a confidence interval at 5% level of
significance was generated under the following estimation:
E95%CI (Residuals) = E(resid) [+ or -] 1.96 ([[sigma].sub.r])
The lower limit was determined to be 12.217938 runs, while the
upper limit is 23.311474 runs. Under the Run's test, the number of
changes in the sign of residuals should fall within the confidence
interval, or there might be a possibility of spatial correlation in the
model. Because this study identified 13 runs that fall within the
confidence interval, the IFRS disclosure index model is said to be
relieved from committing such violation.
IMPLICATIONS OF THE FINDINGS
This study is concerned with the firm's profitability as an
explanatory variable to the level of compliance of the sample firms to
IFRS. As the regression results showed, the researchers found out that
there is an insignificant relationship between profitability measures
and the level of IFRS compliance among the sample firms, thus rejecting
the alternative hypothesis presented in this paper. The result of the
study was interesting for it shows that profitability does not explain
the level of compliance to IFRS of the sample firms selected in this
study. It implies that the level of compliance to IFRS will not differ
even if the firms have different profitability. According to the study
of Valahi and Iatridis (2007), different financial measures such as
leverage, profitability, liquidity and growth has an effect on the
decision of firms to voluntarily adopt to new accounting policies and
pronouncements. Based on this study, the results of this study
presenting insignificant relationship showed evidence to the contrary.
However, the findings of Valahi and Iatridis (2007) are not unqualified.
It was mentioned in their study that firm's compliance with
accounting regulation is determined by the different financial measures
in a manner described as follows:
"Firms may voluntarily abide by an accounting regulation in
order to influence their financial performance and suit their corporate
plans. For example, following that IAS 1 enhances the quality of
financial reporting, firms with higher leverage might be inclined to
voluntarily adopt IAS 1 in order to favourably affect their financial
position. Voluntary IAS 1 disclosers are generally firms that perform
well and particularly tend to exhibit higher profitability and growth.
Voluntary IAS 1 disclosers are also firms that tend to provide voluntary
accounting disclosures about their financial performance and display
high managers' remuneration and stock returns. Also, firms that
raise equity capital appear to voluntarily adopt IAS 1. The study also
indicates that large firms, which are more visible in the stock market,
voluntarily abide by the reporting requirements of IAS 1 in order to
provide evidence of quality in their reported financial numbers and
positively influence investors" (Valahi et. al, 2007).
Considering these statements, the relationship between IFRS
compliance and profitability measures is dependent on the information
that firms wanted to portray using their financial reports. Firms comply
with IFRS in order to affect the profitability presented in their
financial reports. However, this relationship is subject to a further
qualification such that:
"In an efficient stock market, the presentation of low quality
accounting information would be expected to be penalised, while quality
accounting disclosures would be expected to be rewarded by the stock
market (Chung et al., 2002). In an inefficient stock market, investors
may misvalue the information content of accounting disclosures, which
would in turn lead them to incorrect predictions and decisions (Botosan,
1997). Given that the quality of accounting information is essential for
enhancing the stock market efficiency, the questions that arise are how
accounting regulation should be improved to encompass all possible areas
of accounting practice, and how flexible financial reporting should
be."
It is mentioned as well in the same study, that the relationship
between compliance with an accounting regulation is dependent upon the
improvement of the efficiency of the stock market. Disclosures made by
firms will have possible impact if the stock market is efficient for
most of the users understand the meaning of the disclosures that will
consequently affect the decision of the managers to have complied fully
with IFRS.
In this regard, the researchers considered the relationship might
as well be read inversely such that profitability of the firms as driven
by the users do not primarily drive management's decision to comply
fully with IFRS. This finding is still plausible that it warrants that
the Philippine stock market shall further improve its efficiency in
order to realize the benefits of the firm's compliance with IFRS.
CONCLUSIONS
All of the relationships deduced from the regression analysis falls
below the significance check of ([alpha] < 0.05) such that the
researchers decided to reject the alternative hypothesis that there is
significant relationship between profitability ratios and IFRS
disclosure index; accept the null hypothesis that there is no
significant relationship between profitability ratios and the IFRS
disclosure index.
Ergo, Seen in the Philippine context, profitability measures such
as return on assets, return on equity, return on sales, basic earnings
per share and revenues have no significant relationship with
International Financial Reporting Standard Disclosure Requirements.
Applying agency theory in relationship to the correlation between
profitability measures and IFRS disclosure index, profitable publicly
listed corporations should be disclosing more financial information as
their agents or managers want to show off the firm's good financial
performance and financial position. However, the results show also that
less profitable publicly listed corporations disclosing more financial
information too. This implies how management would be willing to unveil
any quantitative and qualitative financial information shown on the face
of the financial statements and in its notes to financial statements
irrespective the result of operation.
The deviation of the results from prior literature was also due to
the difference in market conditions and practices here in the
Philippines compared to developed countries. Most literature that
expressed a positive relationship between profitability and corporate
governance disclosures are conducted in developed countries. Several
researches suggested that there was a huge difference between developing
and developed countries because their model of corporate governance
varies in terms of structural characteristics (Rabelo & Vasconcelos,
2002 as cited by Chua et. al., 2009).
Taking this into account, Kusumawati (2006) as cited by Chua et.
al. (2009) study on Indonesian firms found that profitability affects
corporate governance disclosure level negatively. The similarity of the
results in Philippine and Indonesian companies is because both countries
are located within the same region that have a relatively the same
economic conditions and practices.
Furthermore, the aforementioned studies from neighboring countries
such as Indonesia and Malaysia have relatively comparable results. The
Philippines, being a member of the Association of South East Asian
Nations (ASEAN) together with Indonesia and Malaysia suggests the
resemblance of their operating conditions. The counterintuitive
relationship may be credited to the lack of sophistication of the
markets within the region on contrast with other developed countries.
RECOMMENDATIONS
Audit is as dynamic as the changing landscape of business. With the
ever-growing diversification, audit has continued to adapt itself to
become attuned with the needs of each sector. Therefore, the continued
exchange of knowledge and check-and-balance in compliance audits will be
beneficial to the entities mentioned and the end users as well.
The results of this study would provide investors with a more
efficient way analyzing the figures presented in the financial
statements. The ASC may recommend revisions or even provide a new
standard with respect to reporting standards that would cater to the
needs of business entities.
The PICPA, through its circular and regular seminars, can update
its members and serve to upgrade the profession. The SEC may impose
stricter guidelines and reject statements haphazardly made or which are
not in accordance with the standards.
The academe should continue to prepare students and make them more
aware of the standards and help the students understand the impact of
profitability measures with IFRS disclosure requirements index, while
the auditing firms, through their annual audits, should prepare the
business sector in the objective of a unified system of preparing and
presenting financial statements.
The results of this study are subject to several limitations. The
study focuses solely on the relationship between the IFRS disclosure
index and profitability measures. The effects of IFRS disclosures on
financial performance of the firm value can be studied further. Another
limitation is the number of years covered by the study. Increasing the
number of years studied can neutralize the effects of irregular events
on the data collected and results. It would enable the researchers to
measure the performance of the firm on years without significant
external factors affecting the economy and the operations of the
business.
A topic that can be further explored is the relationship between
IFRS disclosure index and other financial ratios. Lastly, the population
of the research only included firms listed in the Philippine Stock
Exchange that belong to Food, Beverage & Tobacco (FBT),
Telecommunication (TI) and Information Technology Industries. This
population can be broadened by using other Industries with the
Securities and Exchange Commission of the Philippines.
Appendix A: Public Listed Corporations and Its Disclosure Index
BY INDUSTRY Disclosure
Index (DI)
1 Telecommunication Industry 0.9886
2 Information Technology Industry 0.9900
3 Food, Beverages and Tobacco Industry 0.9894
By Public listed Corporations
1. Telecommunication Industry Disclosure
Index
1 TCI A 0.9878
2 TCI B 0.9908
3 TCI C 0.9888
4 TCI D 0.9908
5 TCI E 0.9857
6 TCI F 0.9878
2. Information Technology
1 IT A 0.9888
2 IT B 0.9857
3 IT C 0.9929
4 IT D 0.9898
5 IT E 0.9918
6 IT F 0.9908
7 IT G 0.9898
3. Food Beverages and Tobacco
1 FBT A 0.9888
2 FBT B 0.9918
3 FBT C 0.9857
4 FBT D 0.9918
5 FBT E 0.9898
6 FBT F 0.9847
7 FBT G 0.9888
8 FBT H 0.9918
9 FBT I 0.9908
10 FBT J 0.9898
11 FBT K 0.9878
12 FBT L 0.9867
13 FBT M 0.9939
14 FBT N 0.9908
15 FBT O 0.9888
16 FBT P 0.9867
17 FBT Q 0.9878
18 FBT R 0.9898
19 FBT S 0.9929
20 FBT T 0.9888
21 FBT U 0.9898
Appendix B: White Heteroskedasticity Test:
F-statistic 0.809172 Probability 0.674540
Obs*R-squared 18.85442 Probability 0.531306
Test Equation:
Dependent Variable: RESID^2
Method: Least Squares
Date: 12/08/09 Time: 16:00
Sample: 1 34
Included observations: 34
Std.
Variable Coefficient Error t-Statistic Prob.
C 0.000242 0.000149 1.619096 0.1294
ROA -0.001749 0.000988 -1.770345 0.1001
ROA^2 -0.000240 0.000112 -2.134529 0.0524
ROA*ROE 0.000318 0.000218 1.460358 0.1679
ROA*BEPS -2.95E-05 6.32E-05 -0.467324 0.6480
ROA*REV 6.60E-05 3.47E-05 1.903323 0.0794
ROA*ROS -0.000385 0.000576 -0.667876 0.5159
ROE 0.000712 0.000385 1.847211 0.0876
ROE^2 -6.93E-06 4.56E-05 -0.152047 0.8815
ROE*BEPS -3.17E-06 4.12E-05 -0.077077 0.9397
ROE*REV -2.76E-05 1.48E-05 -1.861127 0.0855
ROE*ROS 0.000422 0.000561 0.751866 0.4655
BEPS 1.01E-05 1.18E-05 0.856351 0.4073
BEPS^2 -2.12E-08 5.35E-08 -0.395760 0.6987
BEPS*REV -3.34E-07 4.49E-07 -0.744157 0.4700
BEPS*ROS 2.05E-05 3.60E-05 0.567975 0.5797
REV -1.84E-05 1.18E-05 -1.557645 0.1433
REVA2 3.53E-07 2.33E-07 1.515272 0.1536
REV*ROS -4.63E-06 2.93E-06 -1.578363 0.1385
ROS 0.000109 6.98E-05 1.565437 0.1415
ROS^2 -7.80E-07 8.29E-07 -0.941885 0.3634
R-squared 0.554542 Mean dependent var 4.21E-06
Adjusted R-squared -0.130778 S.D. dependent var 4.90E-06
S.E. of regression 5.21E-06 Akaike info criterion -21.21726
Sum squared resid 3.53E-10 Schwarz criterion -20.27451
Log likelihood 381.6934 F-statistic 0.809172
Durbin-Watson stat 2.266353 Prob(F-statistic) 0.674540
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Table 1. Summary of Descriptive Statistics
DI ROA ROE
Mean 0.989387 0.067916 -0.026629
Median 0.989806 0.022199 0.021680
Minimum 0.98470948 -0.22208399 -1.81587031
Maximum 0.99388379 0.947438945 0.54098345
Range 0.00917431 1.169522931 2.356853756
Population variance 0.000005 0.038661 0.144096
Population standard
deviation 0.002227 0.196625 0.379600
Standard error
of the mean 0.000388 0.034228 0.066080
Skewness -0.151283 3.032066 -3.081078
Kurtosis -0.493399 11.542147 14.114110
Coefficient of
variation (CV) 0.23% 293.87% -1446.96%
BEPS REV ROS
Mean 8.160990 24.798397 -3.240630
Median 0.073500 24.575354 0.027409
Minimum -1.17 16.9939393 -109.475244
Maximum 181.65 31.4127431 0.649818448
Range 182.82 14.4188038 110.1250621
Population variance 1,116.158316 9.690649 342.205187
Population standard
deviation 33.408956 3.112981 18.498789
Standard error
of the mean 5.815753 0.541900 3.220226
Skewness 4.668939 -0.098719 -5.825272
Kurtosis 22.557628 0.177400 33.954018
Coefficient of
variation (CV) 415.53% 12.74% -579.42%
Table 2. Regression Output
Std.
Variables Coefficients error t-stat p-value
Intercept 0.9945 0.0036 77.080 1.10E-49
ROA -0.0011 0.0023 -0.470 .6421
ROE 0.0010 0.0012 0.838 .4090
BEPS -0.00002260 0.00001277 -1.770 .0876
REV -0.00019262 0.00014351 -1.342 .1903
ROS 0.00002108 0.00002186 0.964 .3433
S. E. of Regression = 0.002262
R-squared = 0.150238
Adjusted R-squared = 0.387605
Table 3. ANOVA Table for IFRS Disclosure Index
and Profitability Ratios
Source SS df MS F p-value
Regression 0.0000 5 0.0000 0.99 .4415
Residual 0.0001 28 0.0000
Total 0.0002 33
Table 4. Regression Output
Variables Coefficients Std. Error t-stat
Intercept 0.9945 0.0036 277.080
ROA -0.0011 0.0023 -0.470
ROE 0.0010 0.0012 0.838
BEPS -0.00002260 0.00001277 -1.770
REV -0.00019262 0.00014351 -1.342
ROS 0.00002108 0.00002186 0.964
Variables p-value VIF
Intercept 1.10E-49
ROA .6421 1.363
ROE .4090 1.278
BEPS .0876 1.209
REV .1903 1.326
ROS .3433 1.087
1.253
Mean VIF
Table 5. Summary of R-Squared and Tolerance
Values for Auxiliary Regression of Variables
Variable R-squared Tolerance *
ROA 0.010190 0.989810
ROE 0.000965 0.999035
BEPS 0.050231 0.949769
REV 0.019979 0.980021
ROS 0.014964 0.985036
Note. * Tolerance = 1-R-squared
Table 6. Summary Values for the Run's Test
Item Designation Value
[T.sub.1] Number of positive residuals 15
[T.sub.2] Number of negative residuals 19
T Number of observations 34
E (resid) Expected value of residuals 17.764706
[[sigma].sub.r.sub.2] Variance of residuals 8.0088078
[[sigma].sub.r] Standard deviation of residuals 2.8299837
