analysis the factors that influence earnings response coefficient
TRANSCRIPT
ANALYSIS THE FACTORS THAT INFLUENCE EARNINGS RESPONSE
COEFFICIENT (ERC) IN THE MANUFACTURING COMPANY LISTED IN
INDONESIA STOCK EXCHANGE
Rekyan Shinta HapsariAirlangga Univesity SurabayaEmail: [email protected]
Abstract
This research is aimed to analyze the factors that influence Earnings Response Coefficient (ERC) in the manufacturing company listed in Indonesia Stock Exchange. This research used seven factors which are firm size, beta risk, earnings persistence, growth opportunities, capital structure, board composition and audit quality. It based on the different market response toward earnings information of some companies over the others. The sample of this research is 132 companies selected by using purposive sampling method. This research tested the hypotheses by using multiple regression analysis models.
The result of this research found that firm size gives no significant influence because it also used as the proxy for other firm characteristics. Beta risk gives negative significant influence toward ERC because higher beta risk will increase the portfolio risk. Earnings persistence gives no significant influence toward ERC because the investors less response the persistence in earnings change and consider the others information to make investment decision. Growth opportunities give positive significant influence toward ERC because it indicate other success in future project and easy to attract capital. Capital structure gives negative significant influence toward ERC because the good news in high leverage company will give benefit to the debtholders over the stockholders. Board composition gives negative significant influence toward ERC because the investors doubt about the ability of independent directors in monitoring the management and decrease the financial statement fraud. The audit quality gives no
significant influence toward ERC because the investors only concern to the amount earnings number rather than the accuracy of the earnings.
Keywords: Earnings Response Coefficient (ERC), firm size, beta risk, earnings persistence, growth opportunities, capital structure, board composition, audit quality.
1. INTRODUCTION
1.1 Background
Financial statements contain information that will
be response by the investors as consideration for
decision making. Information which is responses by the
investors has quality of value relevant which is capable
to make different in decision. The investors’ response
toward earnings information will be different for some
company over the others company. Then it leads to the
study called earnings response coefficient (ERC) which is
identify and explain the different market response toward
earnings information.
Traditional empirical research by Ball and Brown
(1968) measured the information content of earnings by
classifying the reported earnings into good news (GN) if
greater than the market expectation and bad news (BN) if
less than expectation. They found that stock return
response to the information content in financial
statements. Lev (1989) in Scott (2009:196) found that the
market response to bad news and good news is really
quite. It means most of the variability of security
return due to factors other than the change in earnings.
Then this finding led to the studies called value
relevant of financial information.
The value relevance theory then led to the next
important direction of Ball and Brown’s study called as
earnings response coefficient (ERC) theory. For a given
amount of unexpected earnings, the security market
response will greater for some company than the others.
Earnings response coefficient (ERC) explained and
identified the difference market response toward earnings
information.
There were many researchers that analyze the factors
that caused the different in market response by using
earnings response coefficient (ERC), such as Earnings
Persistency (Kormendi and Lipe, 1987 and Collins and
Kothari, 1989), growth opportunities (Collins and
Kothari, 1989); beta risk (Collins and Kothari, 1989;
Chambers et al., 2005 and Dhaliwal and Reynolds, 1994),
capital structure (Dhaliwal et al., 1991), firm size
(Chaney and Jeter, 1991), auditor quality (Teoh and Wong,
1993), board composition (Petra, 2005), industry effect
(Biddle and Seow, 1991), timeliness (Jaswadi, 2004),
accounting method (Chandrarin, 2003).
The motivations of this paper referred to the
possibility of other factors other than change in
earnings that can cause different market response toward
earnings information. This paper will combine the factors
that used in previous research which are firm size, beta
risk, earning persistence, growth opportunities, capital
structure, and audit quality. Second motivation is expand
the previous research by analyzing one of corporate
governance mechanism which is board composition, since
the corporate governance became crucial issue relating
the responsibility of management in providing financial
information. The third motivation is relating to the
inconsistencies result in previous earnings response
coefficient research such as firm size (Easton Zmijewsky,
1989; Chaney and Jeter, 2005; Collins and Khotari, 1989)
and earnings persistence (Kormedi and Lipe, 1987; Ali
Zarowin, 1992).
This different of ERC research from previous ERC
research is that the ERC research expands the previous
research by using value relevant method which is extent
the observation period. Based on value relevant theory,
the timeliness is not the main issue. The research still
examine the relation between stock price and accounting
information, but the research identify the drivers of
value that may be reflected in price over a longer time
period (Beaver, 2002).
This research will analyze the influence of each
independent which are firm size, beta risk, earning
persistence, growth opportunities, capital structure,
board composition and audit quality toward dependent
variable which is earnings response coefficient (ERC) in
the manufacturing company listed in Indonesia Stock
Exchange (IDX) through multiple regression analysis by
using Eviews 4.0.
1.2 Problem Statement
According to the research background elaborated
above, the problem of this research is relating to the
factors that influence earnings response coefficient
(ERC) and how far those factors give influence to ERC.
The problem statement in this research is:
“Do firm size, beta risk, earnings persistence, growth
opportunities, capital structure, board composition and
audit quality influence earnings response coefficient
(ERC)?”
1.3 Research Contributions
The contributions of this research consist of
contribution for theory, empirical and policy. This
research hopefully can enrich the concept and theories
that support the development of science relating the
research of the earnings response coefficient and the
factors that influence it. The empirical contribution of
this research is to give direction for the management and
accountant to improve the usefulness of financial
statements information so that the investors can use the
information as consideration for decision making. The
contribution of this research to the policy making is the
result of this research can give consideration and
feedback for the standard setters of accounting policy to
evaluate and make the standard that can improve the
usefulness of financial statements.
2. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT
2.1 Value Relevant Theory
SFAC 2 defines value relevance as the information
that can help the users of financial statement to form
their own predictions of event. According to Scott
(2009:196) value relevance is closely related to the
concept of earnings quality, since it uses security
market reaction to measure the extent to which financial
statements information assist investors to predict future
performance of the company. That theory opens the
possibility for other factors other than change in
earnings to influence market response.
The focus of value relevant study is the variable
that asses the valuation characteristics of particular
accounting amount. In the other hand it was assess about
how well the accounting number reflect the information
used by investors in valuing the economics performance of
the company. Beaver (2002) explained two major
characteristics of value relevance research that
distinguish from other capital market research. The first
is that, value relevance research demands an in-depth
knowledge of accounting institutions, accounting
standards, and the specific features of the reported
numbers more than the other research area. A second
distinguishing characteristic is that timeliness of
information is the main issue in value relevance
research. Value relevance research still includes studies
examine the relation between the level of stock price and
accounting data, but it’s not encompasses in event study.
In contrast to event study, value relevance studies
identify the drivers of value that may be reflected in
price over a longer time period than assumed in event
study.
2.2 Earnings Response Coefficient Theory
Earnings Response coefficient (ERC) is the reaction
of earnings that announced by the company. Collins and
Kothari (1989) defined earnings response coefficient as,
“The price change including by one-dollar stock to
current earnings and is equal to one plus the present
value of the revisions in expected future earnings caused
by this stock.”. ERC is one important direction from the
research by Ball and Brown (1968) that can identify and
explain the different market response toward earnings
information.
The principal of ERC is that the investors have
expectation before the company announced their earnings.
When the annual earnings announced, if the actual
earnings higher than the investors’ expectation it become
good news (GN), so the investors will revise upward their
expectation toward earnings and performance of the
company and decide to buy the stock of the company. The
opposite, if the expectation is higher than the actual
earnings, it becomes bad news (BN), so the investor will
revise downward their expectation toward earnings and
performance of the company and decides to sell their
stock. The increasing and decreasing of the stock price
will accumulate in the cumulative abnormal return (CAR)
for each company. Expectation of future earnings can be
based on information of current earnings, but the
accuracy of the prediction depends on the earnings
behavior.
2.3 Determinant of Earnings Response Coefficient and
Hypotheses Development
For a given amount of unexpected net income, the
extent of security price or abnormal return depends on
some factors; those factors are called as determinant of
ERC. Those factors can influence the magnitude of ERC.
The determinants of ERC that will be reviewed in this
research are firm size, beta risk, earnings persistence,
growth opportunities, capital structure, board
composition and audit quality.
2.3.1Firm size
Firm size in ERC research is used as a proxy for the
informativeness of stock price (Scoot, 2009:158).
Research by Atiase (1985) in Chaney and Jeter (2005)
found that firm size is negatively related with ERC
because the big company disclosed much information
relating earnings throughout the year, so when the
earnings announcement release the information become less
informative for investor. Research by Mulyani et al.
(2007) and Easton and Zmijewski (1989) found that firm
size is not significant variable in explaining earnings
response coefficient. The reason is probably, the size of
the firm also used as the proxy for others
characteristics of the company, such as profitability,
risk and growth. Different result found by Chaney and
Jeter (2005) and Susilawati (2008). They found that firm
size is positively related with the magnitude of Earnings
response coefficient.
Larger the size of the firm, the ability to generate
future return trough its subdivision will be higher. Good
news for larger company size, the investors will respond
by buying the stock of the company. Higher demand of
company stock implies higher increase in market price and
shares return in response to the GN, hence, a higher ERC.
H1: firm size of the company has positive influence
toward ERC
2.3.2 Beta risk
Every company has systematic risk which is risk that
influences a large number of assets and cannot be
diversified. Assumed that the investors are typical of
risk-averse, rational investors will increase the
expected value and decrease the risk of return of
portfolio. Higher beta of the company will increase
portfolio risk, consequently the investor would not buy
as much more as if the security was has low beta,
although the company has good news. The demand of GN
company stock will be lower for the higher beta, other
things equal. Lower demand implies lower increase in
market price and stock return in response to GN, hence,
lower ERC.
The previous researches by Collins and Kothari
(1989) found that high-risk companies have lower ERC than
low-risk companies. Research results by Dhaliwal and
Reynold (1994), Willing (1999), and Mulyani et al. (2007)
also found that beta risk is negatively related with the
earnings response coefficient (ERC).
H2: Beta risk of the company has negative influence
toward ERC
2.3.3 Earnings persistence
The earnings persistency can be seen from the
earnings innovation in current year related to the stock
price changing (Scott, 2009:155). The investor would
expect the companies that have steady changes from year
to year. Study by Kormedi and Lipe (1987) and Mulyani et
al. (2007) found that earnings persistence has positively
influence the earnings response coefficient. Different
with Ali and Zarowin (1992) found that ERC has negative
correlation the earnings persistence.
Earnings persistence explains the ability of the
company to persist the earnings that earn in current
period until next period. Steady GN of a company, the
investors will react by buying the stock of the company.
Higher demand of the company stock implies higher
increase in market price and stock return in response to
the GN, hence, higher ERC.
H3: earnings persistence of the company has positive
influence toward ERC
2.3.4 Growth opportunities
The company with higher opportunity to growth will
have more ability to generate earnings and increase the
earnings in the future because they have bigger
opportunity to invest in the next period (Scoot,
2009:158). Study by Collins and Kothari (1989) and
Mulyani et al. (2007) found growth opportunities has
positively influence the earnings response coefficient.
Growth opportunities include existing project or
opportunities to invest in project that are expected to
yield rates of return that exceed the risk adjusted rate
of return. High investment opportunities make company can
increase the value of the company. Such company can
easily attract capital and additional sources of growth.
Thus the stock demand of GN company stock will be
higher for growth company. Higher demand implies higher
increase in market price and stock return in response to
GN in response to GN, hence, higher ERC.
H4: growth opportunities of the company has positive
influence toward ERC
2.3.5 Capital structure
Capital structure is defined as that mix of debt,
preferred, and common equity that causes its stock price
to be maximized. In this research, capital structure is
proxy by leverage. Leverage refers to the extent to which
a firm relies on debt (Ross et al., 2008:553). Study by
Dhaliwal et al. (1991) and Mulyani et al. (2007) found
that capital structure that proxied by leverage has
negatively influence with earnings response coefficient.
The company which have higher leverage will have
lower earnings response coefficient. The good news of
highly leverage company will adds strength and safety to
bonds and other outstanding debt. As much as the GN of
highly leveraged company, the earnings will goes to
debtholders rather than shareholders.
H5: Leverage level of the company has negative influence
to ERC
2.3.6 Board composition
Board composition deals with the proportion of
independent directors compare with the total number of
directors on the board. Higher number of independent
board of directors hypothesized to increase the integrity
of financial information by limiting management’s ability
to manipulate earnings. Independent directors are seen as
a mean for monitoring management and for ensuring that
management decision are aligned with the best interest of
the shareholders. Independent directors have no
contractual relationships with the companies are free
from relationships which could interfere with their
capacity to act in an independent manner.
The demand of the GN company stock will be higher
for the company that has higher proportion of independent
board of directors. Higher demands of stock imply higher
market price and stock return response to the GN, hence,
higher ERC. Study by Petra (2005) resulted that
proportion of independent directors has positive
influence to earnings informativeness.
H6: Boards composition positive influence toward ERC
2.3.6 Audit quality
Auditor function is as a party that gives assurance
toward the accounting number and assurance the fairness
of accounting number in financial statement. Higher
quality of audit that proxied by size of audit firm will
increase the accuracy of financial statement. The reason
is that the big-four audit firm will give the best effort
to audit the financial statement of the company in order
to defense their reputation. The previous research
conduct by Teoh and Wong (1993) resulted the audit
quality has positive relation with the earnings response
coefficient.
H7: Audit quality has positive influence toward ERC
3 RESEARCH DESIGN
3.1 Data and Sample of Research
The type of data that used in this research is
secondary data that obtain from Indonesia stock exchange
(www.idx.com), Indonesia Capital Market Directory and
Central Data of Business and Economics of Gajahmada
University (www.pdbe.com). Data that used in this
research is consists of:
1. Financial statement of the manufacturing company for
year 2004-2008
2. The company profile of the manufacturing company in
year 2008
3. Stock exchange trading that consists of daily
abnormal return, closing price and beta correction
for year 2004-2008.
The population of this research is manufacturing
company that listed in Indonesia stock exchange. Sampling
technique that used in this research is purposive
sampling technique that draws the sample according to
certain criteria as follows:
1. Manufacturing company in Indonesia stock exchange
that reports their financial statement for year 2004
– 2008.
2. The information about company’s daily abnormal
returns is available continuously in year 2004-2008.
3. The financial statements are representing in Rupiah.
4. The company profiles are available in Indonesia
Stock Exchange website.
The sample of this research is consists 132
manufacturing company listed in Indonesia Stock exchange.
The sample selection procedure is depicted in table 1.
3.3 Operational Definition and Variable Measurement.
Operational definition and variable measurement of the
variables can be seen in table 2.
3.4 Data Technique Analysis
This research is attempted to analyze the factors
that influence earnings response coefficient by using
regression analysis as the research conducted. This
research is using Eviews4.0 software to process the data
and analyze the hypothesis. The hypotheses in this
research are tested by the following regression.
....(11)
ERCit : Earnings response coefficient company i period t
SIZEit: Firm size of company i in period t
BETAit: Beta risk of company i in period t
PERSit: Earnings persistence of company i in period t
GRTHit: Earnings growth of company i in period t
LEVit : Capital structure of company i in period t
BRDCit: Percentage of independent board of directors of company i in period t
AUDQit: Audit quality of company i in period t
4 RESULT AND DISCUSSION
4.1 Statistics Descriptive
The dependent variable is the earnings response
coefficient, while the independent variables are firm
size, beta risk, earnings persistence, growth
opportunities, capital structure, board composition and
audit quality. The statistic descriptive is depicted in
table 4.1.
4.2 Classical Assumption Testing
The test for the factors that influence earnings
response coefficient (ERC) used multiple regression
analysis models. It needs to know the relationship
between the dependent variable and independent variable
in the multiple linear regression models in order to
achieve the best linear unbiased estimator (BLUE). The
relationship between dependent variable and independent
variable is tested by classic assumption test. The
classic assumption tests consist of normality test,
autocorrelation test, heteroscedasticity test and
multicolinearity test.
The normality is tested by using Histogram Normality
test, autocorrelation is tested by using Breusch-Godfrey
method (Widarjono, 2009:147), heteroscedasticity is
tested by using White method (Widarjono, 2009:128) and
the multicolinearity is tested by analyze the correlation
matrix of independent variables (Ghozali, 2001:95).
4.3 Hypotheses Testing
The factors that analyze in this research are firm
size, beta risk, earnings persistence, growth
opportunities, capital structure, board composition, and
audit quality. Table 4 will present the test result of
the factors that influence earnings response coefficient.
This research used seven variables as the factors
that influence earnings response coefficient. Those
factors are firm size, beta risk, earning persistence,
growth opportunities, capital structure, board
composition and audit quality. From the result test,
variables of beta risk, growth opportunities, capital
structure and board composition have significant
influence toward earnings response coefficient. Firm
size, earnings persistence, and audit quality gives no
significant influence toward earnings response
coefficient. The detail explanation will be discussed as
follows:
4.4 DISCUSSION
4.4.1 Firm size
The result of this research found that firm size has
no significant influence toward earnings response
coefficient. Larger the size of the company does not make
the ERC higher. This finding supported the previous
research by Easton and Zmijewski (1989) and contrary with
the research by Chaney and Jeter (2005) and Mulyani et
al. (2007) that found significant influence of firm size
toward ERC. Scoot (2009:153) used the firm size as the
proxy for the informativeness of earnings. The firm size
has no significant influence toward ERC probably because
the firm size also used as the proxy for others firm
characteristics, such as growth and risk (Easton and
Zmijewski, 1989).
4.4.2 Beta risk
This research found that beta risk has negative
significant influence toward earnings response
coefficient (ERC). It means that higher beta risk will
cause lower earnings response coefficient (ERC). This
finding supported the previous research by Collins and
Kothari (1989), Dhaliwal and Reynold (1994) and Mulyani
et al. (2007). This finding gives evidence that market
will response negatively to the company that has higher
beta risk. Higher beta of the company will increase
portfolio risk, consequently the investors will not buy
the stock as much as the company that have lower beta.
4.4.3 Earnings persistence
This research found that earnings persistence have
no significant influence toward earnings response
coefficient. It means that earnings persistence does not
influence the earnings response coefficient. This finding
supported the previous research by Harahap (2004) and
contrary with the research by Collins and Kothari (1989)
and Mulyani et al. (2007) that found significant
influence of earnings persistence toward ERC.
This result gives evidence that investors less
response the information earnings change although the
company can persist the earnings for the future period.
This indicated that in making economic decision, the
investors not only considered the earnings information,
but they also use others information to support their
economic decision
4.4.4 Growth opportunities
This research found that growth opportunities have
positive influence toward earnings response. This finding
supported pervious research by Collins and Khotari
(1989), Mulyani et al. (2007). The positive influence of
growth opportunities implied that the investors will
response more to the earnings information that released
by the company that have higher opportunities to growth
than non-growth company. Company that success in the
project and labeled as growth company will easily to
attract capital for additional sources of growth. Growth
because of investing in projects that yield above normal
rates of return in generally referred to as economic
growth.
4.4.5 Capital structure
In this research, leverage has negative influence
toward earnings response coefficient. It means the higher
leverage level, the earnings response coefficient (ERC)
will be lower. This finding support the previous research
by Dhaliwal et al. (1991), Billings (1999), Setiati
(2004), Mulyani et al. (2007).
Leverage ratio reflect the amount of debt that used
by the company to fund the business activities. The
reaction of stock prices to unexpected earnings will be
affected by liability risk. This is because the liability
risk that determined the mechanism for allocating of
wealth change due to unexpected earnings among the
stockholders and debtholders. High leverage ratio
indicates that the source of fund is dominated by the
debt over the equity. Much of the good news in earnings
goes to debtholders rather than stockholders (Scoot,
2009:154).
4.4.6 Board composition
Board composition in this research was proxied by
the proportion of independent directors that served in
the board of directors. The result is the board
compositions have negative significant influence toward
earnings response coefficient. This finding is contrary
with the previous research by Petra (2005) and Ahmed et
al. (2006) that found no significant influence of board
composition toward ERC.
Independent directors limited in the involvement of
company activities and day-to-day operation of the
company’s business (Ahmed, 2006). This characteristic
makes the market doubtful whether the independent
directors are able to provide any significant business
advice to increase the performance of the company.
4.4.7 Audit quality
In this research Audit quality has no significant
influence toward earnings response coefficient. This
finding supported the previous research by Mulyani et al.
(2007) and Riyatno (2007). This result gives finding that
the quality of the audit did not influence the investors’
response toward earnings announcement. The investors only
concern about the earnings reported in the financial
statement without pay attention to the accuracy of the
earnings (Mulyani et al., 2007).
5 CONCLUSION, LIMITATIONS, SUGGESTIONS and
IMPLICATIONS
The result of this research find that beta risk,
growth opportunities, capital structure, and board
composition give significant influence toward earnings
response coefficient while firm size, earning
persistence, and audit quality have no significant
influence toward earnings response coefficient.
The limitations of this research are the variables
in this research have more than one measurement and this
research did not consider the economic event that can
caused strong response from the market such as merger.
Based on the limitation, this research suggests for
the next researchers to use others measurement of
variables and adding the economic event to the model to
be analyzed.
The implication of this research are the management
and accountant profession can increase the quality and
credibility of financial statement so that the investors
can make investment decision more accurately by using
those information.
REFERENCES
Ahmed, K., M. Hossain, and M.B. Adams. 2006. The Effect of Board Composition and Board Size on the Informativeness of Annual Accounting Earnings. Corporate Governance Journal 14, No.5 : 418-431.
Ali, A. Dan P. Zarowin, 1992, ”Permanent vs. Transitory Components of Annual Earnings and Estimation Error in Earning Response Coefficients”. Journal of Accounting and Economics, 15, 249-64
Ball, R. dan P. Brown. 1968. An Empirical Evaluation of Accounting Income Numbers. Journal of Accounting Research 6 (Autumn).
Beaver, W.H. 2002. Perspectives on Recent Capital Market Research. The Accounting Review. Vol 77 No 2 (April): 453-474
Billings, Bruce K. 1999. Revisiting the Relation between the Default Risk of Debt and the Earnings Response Coefficient. The Accounting Review. Vol. 74 No. 4. October (p. 509—522)
Bungin, B. 2001. Metodologu Penelitian Sosial: Format-format Kuantitative dan Kualitaive. Airlangga Univercity Press: Surabaya.
Chandrarin, G., 2003. The Impact of Accounting Methods of Translation Gains (Losses) on the Earnings Response Coefficients. Proceeding Articles on SNA 5, 24-35.
Chaney, P.K. dan D.C. Jeter, 1991, The Effect of Size on the Magnitude of Long Window Earnings Response Coefficients", Contemporary Accounting Research. Vol 8 No.2 : 540-560.
Collin, D.W. dan S.P. Khotari. 1989. An Analysis of Intertemporal and Cross Sectional Determinants of Earnings Response Coefficients. Journal of Accounting and Economics. Vo. 11 (p. 143—181)
Dhaliwal, D.S, K.J. Lee dan S.S. Reynolds, 1994, “The Effect of the Default Risk of Debt on the Earnings Response Coefficients, ” The Accounting Review 69, No. 2 (April): 412-419.
Dhaliwal, D.S., K.J. Lee dan N.L. Farger, 1991, “The assosiation between Unexpected Earnings and Abnormal Security Returns in the Presence of Financial Leverage”, Contemporary Accounting Research 8, No. 1: 20-41.
Donnely, R. 2002. Earnings Persisrence, Losses and The estimation of Earnings Response Coefficient. ABACUS. Vol. 38 No.1.
Easton, P.D. dan M. Zmijewski. 1989. Cross-sectional Variation in the Stock Market Response to Accounting Earnings Announcements. Journal of Accounting and Economics 11:117-141.
El-Mahdy, D.F. and A.A. Abdou. 2007. Trends of the Return- Earnings Association Over the Last Three Decades. Journal of Focus on Finance and Accounting Research. 117-145.
Esme, F. 2007. All About Stock, 3E. McGraw-Hill Proffesional.
Eugene, F.B. and M.C. Ehrhardt. 2008. Financial Management: Theory and Practice. Cengage Learning.
Financial Accounting Standard Board. 1996/97. Statements of Financial Accounting Concepts: Accounting Standards. John Wiley & Sons, Inc. New York.
Freeman, R., and S. Tse. 1992. An Earnings Prediction Approach to examining intercompany Information Transfer. Journal of Accounting and Economics. Vol 15 (p: 509-523).
Ghozali, I., (2001), “Aplikasi Analisis Multivariat: dengan Program SPSS,” Badan Penerbit Universitas Diponegoro, Semarang.
Godfrey, J et al. 2010. Accounting Theory. 7th Edition. John Wiley & Sons, Inc. Australia.
Gujarati, D., 1995,”Basic Econometrics”, 3th Ed., Mc-Grawhill, New York.
Harahap, K., 2004. Asosiasi Antara Praktik Perataan Laba Dengan Koefisien Respon Laba. Makalah. Simposium Nasional Akuntansi VII. Bali: 1-14.
Hebert, B.M. 2007. Investment: an introduction. Chengage Learning.
Ikatan Akuntan Indonesia. 2004. Standar Akuntansi Keuangan. Salemba Empat, Jakarta
Jaswadi. 2004. Dampak Earnings Reporting Lags terhadap Koefisien Respon Laba. Jurnal Riset Akuntansi Indonesia. Vol 8, No.3 : 295-315
Kam. V. 1990. Accounting Theory. 2th Edition. John Wiley & Sons, Inc. Canada
Kieso, D.E., J.J. Weygandt, dan T.D. Warfield, 2007. Intermediate Accounting. 12th Edition, FASB Update. John Wiley & Sons, Inc
Kormendi, R dan R. Lipe, 1987, “Earnings Innovations, Earnings Persistance, and Stock Return”, Journal of Business 60:323-345.
Lev, dan P. Zarowin. 1999. The Boundaries of Financial Reporting and How To Extend Them. Journal of Accounting Research 37: 353-385.
Mike, W.P. 2008. Global Business. Cengage Learning.
Mulyani, S., N.F. Asyik, and Andayani. 2007.Faktor-faktor yang Mempengaruhi Earnings Response Coefficient pada Perusahaan yang Terdaftar di Bursa Efek Jakarta. JAAI 11, No. 1 : 35-45.
Murwaningsari, E. 2008. Pengujian Simultan: Beberapa Faktor yang mempengaruhi Earnings Response
Coefficient (ERC). Doctoral Thesis. Trisakti University.
Naimah, Z. dan U. Sidharta. 2006. Pengaruh Ukuran Perusahaan, Pertumbuhan, dan Profitabilitas Perusahaan Terhadap Koefisien Respon Laba dan Koefisien Respon Nilai Buku Ekuitas: Studi Pada Perusahaan Manufaktur Di Bursa Efek Jakarta. Makalah. Simposium Nasional Akuntansi 9 Padang. K-AKPM 12: 1-26.
Palupi, M. J. 2006. Analisis Faktor-faktor yang Mempengaruhi Koefisien Respon Laba: Bukti Empiris pada Bursa Efek Jakarta. Jurnal EKUBANK. Vol 3.
Panikkos, P., K. Smyrnios and Sabine, K. 2006. Handbook of Research on Family Business. Edward Elgar Publishing.
Riduwan, A. 2004. Pengaruh Alokasi antar perioda Berdasarkan PSAK No.46 terhadap Koefisien Respon Laba Akuntansi. Journal Simposium Nasional Akuntansi VII. Denpasar.
Riyatno. 2007. Pengaruh Ukuran Kantor Akuntan Oublik terhadap Earnings Response Coefficients. Jurnal Keuangan dan Bisnis 5, No.2 : 148-162.
Ross, S.A., R.W. Westerfield and B.D. Jordan. 2008. Corporate Financial Fundamenta. Eight Edition. McGraw-Hill: America.
Sawyer, M.C. 1985. The economics of Industry and Firm. Routledge.
Scott, William R. 2009. Financial Accounting Theory, fifth edition. Prentice Hall Canada Inc. Scarborough, Ontario.
Sekaran, Uma. (2003). Research Methods for Business: A Skill Building Approach, 4th Ed. New York : John Wiley & Sons.
Steven, T.P. 2006. The Effect of corporate governance on the informativeness of earnings. Journal of Economics and Governance 8:129-152
Susilawati, C.D. 2008. Faktor-faktor penentu ERC. Jurnal Ilmiah Akuntansi 7, No.2 : 146-161.
Teets, W.R. dan C.E. Wasley. 1996. Estimating Earning Response Coefficients: Pooled versus Firm Specific Models. Journal of Accounting and Economics. 21, 279-295
Teoh, S.H., and T.J., Wong. 1993. Perceived Auditor Quality and Earning Response Coefficients. The Accounting Review. 68, April: 346-366
Vishnani, S. and B.K. Shah. 2008. Value Relevance of Published Financial Statement with Special Emphasis on Impact of Cash Flow Reporting. International Research Journal of Finance and Economics. (p: 84-90)
Wallison, P.J. 2006. All the Rage: Will Independent Directors Produce Good Corporate Governance?American Enterprise Institute for Public Policy Research.www.aei.org.
Widarjono. A. 2005. Ekonometrika: Teori dan Aplikasi Untuk Ekonomi dan Bisnis. Penerbit Ekonesia. Fakultas Ekonomi UII. Yograkarta
www.icmd.com
www.idx.com
www.pdbe.feugm.ac.id
ATTACHMENTS
Table 1 Sample Selection Procedure
Sample Criteria Total
1) Company that listed in Indonesia Stock Exchange year 2004
330
2) Non-manufacture companies (127)
3) Company that have no stock trading data continuously from year 2004-2008
(68)
4) Company that have no company profile in year 2008
(3)
Total 132
Source: Processed secondary data
Table 2 Operational Definition and Measurement
No Variable Definition Measurement
1 Earnings Response Coefficient (ERC)
the response of the market toward the earnings information that released by the company
CARit : cumulative
abnormal return company i
in period t
UEit : Unexpected
earnings
β : ERC
εit : Component of error
in the model of company i
in period t
CAR : Cummulative
abnormal return
company i in reseach
period five years
2004-2008
ARit : Abnormal return
company i in year t
UEit : Unexpected
earnings company i in
period (year) t
Eit : Accounting
earnings company i in
period (year ) t
Eit-1 : Accounting
earnings company i in
period (year) before (t-
1)
2 Firm Size (SIZE)
Firm size is the total asset that own by the company which reflects the ability for the company to generate earnings (Susilawati,
2008)
3 Beta Risk (BETA)
Beta coefficient, or beta for short define as the amount systematic risk present in a particular risky asset relative to that in average risky asset (Ross et al., 2008:418)
market model by using CAPM formula
Rit : return of company
i in year t
Rmt : market return in
year t
4 Earnings Persistence (PERS)
Earnings persistence is a measurement that explains the ability of the company to persist the earnings that earn in current period until next period (Jaswadi, 2004).
regression slope of the differences between current earnings and previous earnings (Chandrarin, 2003)
Xit : Earnings of
company i in year t
Xit-1 : Earnings of
company i in year t-1
5 Growth Opportunities (GRTH)
Growth opportunity is the level
market-to-book value ratio
of earnings growth of the company in one period to next period (Jaswadi, 2004)
Equity book value =
total equity/ outstanding
stock
Equity market value =
average closing price x
outstanding stock
6 Capital Structure (LEV)
Capital structure represents the combination of fund for the company to run their business (Ross et al., 2008)
Capital structure in this research is proxied by leverage ratio using the formula of company’s total debt to its total assets of company i in year t (Petra, 2005)
TL= Total liabilities
TA = Total asset
7 Board Composition (BRDC)
Board composition is the mix between insider and outsider board of directors. Inside
percentage of independent directors compare with the total number of directors on the board of company i for year t
director is a member of the boards who is as top executive of the company while outside director is the non-management member of the board (Peng, 2008)
8 Audit Quality (AUDQ)
audit quality is often related to the ability of the auditor to detect material misstatement of the financial statements (competence) and his/her willingness to issue an appropriate audit report based on audit findings (independence)
size of the audit firm whether form big four (B4) or non-big four (NB4) and measured by dummy variable (1,0).
1 : For the company
audited by big four audit
firm
0 : For the company
audited by others audit
firm
Table 3
Statistic Descriptive of Research VariablesVariables Min Max Range Average Median Std.Dev
Earnings Response Coefficient (ERC)
-2.3092 1.1526 3.4618 -0.0411 0.0001 0.3566
Firm Size (SIZE)
21.2205 32.0223 10.8017 27.3944 27.3883 1.8167
Beta Risk (BETA)
0.0412 0.1446 0.1034 0.0847 0.0842 0.0206
Earnings Persistence (PERS)
-3.1238 11.2865 14.4103 0.4746 0.2559 1.4599
Growth Opportunities (GRTH)
-2.6971 1306.161 1308.858 25.1901 0.1028 150.9070
Capital Ratio (LEV)
0 72.73 72.73 1.1805 0.56 6.3163
Board Composition (BRDC)
0 1 1 0.1484 0 0.2688
Audit Quality (AUDQ)
0 1 1 0.3893 0 0.4895
Source: Processed secondary data
Table 4
The Result Test of the Factors that Influence Earnings Response Coefficient
Variable Prediction
Coefficient
Std. Error
t-Statist
ic
Prob.
Constanta 0.082266 0.1194
770.68855
20.492
6Firm Size (SIZE) + 0.0000238 0.0042
480.00560
60.995
5Beta Risk (BETA) - -0.838593 0.3421
76-
2.450766
0.0159
Earnings Persistence
(PERS)
+ -0.000564 0.013172
-0.12407
3
0.9015
Growth Opportunities
(GRTH)
+ 0.000159 0.000044
3.620689
0.0005
Capital Structure (LEV)
- -0.002287 0.001112
-2.05650
8
0.0422
Board Composition (BRDC)
+ -0.054861 0.029634
-1.85132
2
0.0669
Audit Quality (AUDQ)
+ -0.00577 0.015255
-0.37823
0.706
F-statistic 4.826986 Prob. (F-statistic)
0.000095
R-squared 0.241714
Source: Processed secondary data