A STUDY ON QUALITY OF EARNINGS IN FMCG...

Volume 4, Number 3, July – September’ 2015

ISSN (Print):2279-0934, (Online):2279-0942

PEZZOTTAITE JOURNALS SJIF (2012): 3.735, SJIF (2013): 5.020, SJIF (2014): 5.996

International Journal of Retailing & Rural Business Perspectives © Pezzottaite Journals. 1788 |P a g e

A STUDY ON QUALITY OF EARNINGS IN FMCG SECTOR

B. Sudheer Kumar32 Dr. V. Mallikarjuna33

ABSTRACT

When any investor goes for investment, he sacrifices his present benefits for the sake of future profits. Any investment made is

to earn profits by accepting some sort of risk. In the wake of present Scenario of highly publicized financial frauds and

failures and accounting manipulations, the emphasis on earnings quality has renewed. That„s why investors and creditors

from all over the world are turning toward the assessment of the earnings quality of the individual company in which they are

trying to invest their investment. Through present study on quality earnings, it was found that various earnings quality proxy„s

which represent the quality of earnings position in the organization. The quality earnings from a company to company vary

according to the parameters they depend on. In the study, the quality earnings often are high in personal care industry and

leather industry. The results of present investigation show that intellectual capital has positive impact on earnings quality,

because relationship between VAIC values and DA is linear and inversely proportional and its lead to conclude that

intellectual capital has a positive role in best financial practices and reporting.

KEYWORDS

Calculation of Intellectual Capital, Human Capital Coefficient, Structural Capital Coefficient etc.

INTRODUCTION

There are many way through which the organizations are manipulating the financial statements, they use certain approaches that

help a firm to hide the true conditions. The investors need to assess the extent to which a firm's reported earnings are free from

mistake or manipulation, so they should have an idea about the possible approaches and ways the firms use to lower its earning

quality and increase their speculative profits. They are:

Recording revenue too soon or of questionable quality,

Recording fictitious revenue,

Boosting income with one-time gains,

Shifting current expense to a different period,

Failing to record or improperly reducing liabilities,

Shifting current revenue to a later period, and

Shifting future expenses to the current period as a special charge.

NEED OF STUDY

In order to understand a company financial report genuinely, you need to understand the accounting concepts that are used to

justify the accounting rules. Basically, these accounting concepts provide rule makers with guidance that will result in financial

reports the best help investors, creditors and other financial report user‗s asses. Investors overlook factors outside the financial

reporting system that quantify their profits or losses most of the time without even their acknowledgement, by the study of earning

quality of the firm we can throne a light on all the other factors that can affect earnings quality and organizations true earnings, by

which the investors, creditors, share holders and others depend on the firm‗s financial well-being get benefited.

OBJECTIVES OF THE STUDY

To estimate earning quality of selected industries,

To develop between intellectual capital and earning quality,

To establish relationship between earning quality and stock returns,

To develop relationship between values added intellectual co-efficient and its components,

To develop between discretionary accruals with other components.

32Assistant Professor & H.O.D., Department of MBA, Vaagdevi Institute of Technology & Science, Andhra Pradesh, India,

[email protected] 33Professor & H.O.D., Department of MBA, Sri Sai Institute of IT and Management, Andhra Pradesh, India, [email protected]

mailto:[email protected]

mailto:[email protected]





LITERATURE REVIEW

There are many literatures published on the different approaches used for assessment of quality of earnings. Earnings quality is

used in numerous empirical studies to show trends over time; to evaluate changes in financial accounting standards and in other

institutions, such as enforcement and corporate governance; to compare financial reporting systems in different countries; and to

study the effect of earnings quality on the cost of capital.

Jennifer bender and frank Nielsen (2013) indicated that earning quality as an investment signal has been popular

among equity portfolio managers for the last decade. The basic idea behind this accruals anomaly is that stocks with

high and increasing accruals tend to have low earnings quality, while stocks with low and decreasing accruals tend to

have high earning quality. The earnings quality signal stopped working in the mid-2000s, but has staged a remarkable

rebound since the end of 2008. The authors evaluate whether earnings quality is a true alpha signal, a risk factor, or

both. They find that, in the periods when the signal worked, the strategy was largely driven by stock selection,

suggestion that earnings quality is indeed an alpha signal. The authors also find that earnings quality is not a good risk

factor, in that it does not have high statistical significance when regressed cross-sectional on returns, along with other

well-known risk factors, and is not very volatile over time. Overall, their results indicate that earnings quality may be

that rare example of a pure alpha factor.

Ralf Ewert and Alfred Wagenhofer (2009) discussed and evaluated the usefulness and appropriateness of commonly

used earnings metrics. In a rational expectations equilibrium model, through studying the information content of

earnings that can be biased by a manager who has market price, earnings, and smoothing incentives. It defines earnings

quality as the reduction of the market‘s uncertainty about the firm‘s terminal value due to the earnings report and

compares this measure with value relevance, persistence, predictability, smoothness, and accrual quality. The evaluation

is based on their ability to capture the effects of a variation of the manager‘s incentives and information, and of

accounting risk. It is found that each metric captures different effects, but some of them, including value relevance and

persistence, are closely related to our earnings quality measure. Discretionary accruals are problematic as their behavior

depends on specific circumstances. These results provide insights into regulatory changes and guidance for selecting

earnings quality metrics in empirical tests of earnings quality.

Jeffrey T. Doyle, Weili Ge, and Sarah McVay (2007), examined the relation between accruals quality and internal

controls using 705 firms that disclosed at least one material weakness from August 2002 to November 2005 and find

that weaknesses are generally associated with poorly estimated accruals that are not realized as cash flows. Further, it is

found that this relation between weak internal controls and lower accruals quality is driven by weakness disclosures that

relate to overall company‐level controls, which may be more difficult to ―audit around.‖ No such relation for more

auditable, account‐specific weaknesses is found. Similar results using four additional measures of accruals quality:

discretionary accruals, average accruals quality, historical accounting restatements, and earnings persistence are

estimated. The results obtained are robust to the inclusion of firm characteristics that proxy for difficulty in accrual

estimation, known determinants of material weaknesses, and corrections for self‐selection bias.

Nahum D. Melumad and Doron Nissim (2008), discussed about earning quality and the related concepts of earning

management, focusing on the primary financial accounts. For each key line-item from the financial statements, it is

summarized that accountings and economic consideration applicable to that item, discuss implications for earning

quality, evaluate the susceptibility of the item to manipulation, and identify potential red flags. The red flags and

specific issues discussed for the individual line-item provide a frame work for fundamental and contextual analysis by

academic researcher and practitioner

METHODOLOGY & COLLECTION OF THE DATA

In this study, secondary data was used to achieve the designated Objectives. The secondary data is from various websites,

magazines, journals and financial newspapers.

The collected parameters are Revenue, debt, assets, book value and cash flow from operations, fixed assets, expenses and

employee cost. The analysis was made based on secondary data, published papers and expert opinion.

DATA ANALYSIS PROCEDURE

For the study, certain approaches are used to assess the quality of earnings, intellectual capital and stock returns.





Calculation of Quality Earnings

Quality of earnings is calculated through the following formula

DA i,t :Is discretionary accrual that is a proxy of earnings quality

TAi,t : Represents total accruals measured as net income minus cash flow from operations of firm i in year t.

i.e., TA = NI – CFFO; NI = NET INCOME; CA = CAS FLOW FROM OPERATION

REVi, t is REENUE of firm i in year t

REC i, t is RECEIABLES of firm i in year t

PPE i, t is plant, property and equipment i.e., firms i FIXED COST in year t

Ai, t-1 is TOTAL ASSETS at the end of year t-1 of the firm i

Later the value is calculated by using the multiple regression equation, which is as:

Follows,

Here the equation is in the form of y = a + x1b + x2c + x3d, through applying the regression analysis to the above equation we can

get DA value. The regression analysis can be applied by the software that is analysis tool pak, after applying regression to the

above equation the resulted x1 – intercept, x2 – intercept, x3 – intercept should be substituted in the DA formula to get the value

of DA.

DA : Discretionary Accurals

(DAit):

Caluculation of Intellectual Capital (VAIC)

Value Added Intellectual Coefficient (VAIC) Calculation

1. Value Added (VA)

VA = OUT – IN, OUT = Revenues, IN = Expenses

2. Human Capital Coefficient (HCE)

HCE = VA/HC, HC = Employee cost

3. Structural Capital Coefficient (SCE)

SCE = SC/VA , SC = VA-HC, SC = Structural cost

4. Capital Employed Efficiency (CEE)

CEE = VA/CA, CA = Book-value of net assets

5. Value Added Intellectual Coefficient (VAIC)

VAIC = HCE+SCE+ CEE

Caluculation of stock returns (R)

STOCK RETURNS (R) = (P1-P0)/P0*100

Here, P1 = Closin price

P0 = Opening price





Caluculation of Leverage ratio and size

LEVIT = Debt/Total Assets, SIZEIT = Total assets in millions

DATA ANALYSIS AND INTERPRETATIONS

General

The secondary data was analyzed using the statistical technique and the obtained results were presented in the form of graphs and

tables. The obtained results were discussed with the help of existing literature and the expert opinion.

Assessment of Earnings quality for ITC

Table-1: Values of DA of ITC

Year DA Year DA Year DA

2005 3242.179 2009 28761.21 2012 76867.77

2006 29262.82 2010 35344.13 2013 78432.41

2007 30376.55 2011 73977.02 2014 78608.54

2008 30393.28

Regression Statistics

Multiple R 0.93388

R Square 0.87213

Adjusted R Square 0.8356

Standard Error 59.8419

Observations 10

ANOVA

d.f. SS MS F Significance F

Regression 2 170978 85488.9 23.8726 0.00075

Residual 7 25067.4 3581.05

Total 9 196045

Coefficients

Standard

Error t Stat P-value

Lower

95%

Upper

95%

Lower

95%

Upper

95%

Intercept 186.116 135.571 1.37283 0.21217 -134.458 506.691 -134.46 506.6913

X Variable 1 -8915.2 4022.5 -2.21633 0.06221 -18426.9 596.503 -18427 596.5034

X Variable 2 0.01098 0.00616 1.78253 0.11786 -0.00359 0.02554 -0.0036 0.025544

Sources: Authors Compilation

Interpretation: It can be seen that the ITC company exhibit highest earning quality 28761.21 in 2009, this indicates low DA

values and high earning quality and the firm also shows low earning quality in 2014 which is 78608.54.

Note: I can mention one sample calculation of earning quality of selected industries and remaining as usual same as above

example.

Relation b/w VAIC and DA for ITC

Table-2: Relation between VAIC and DA for ITC

YEAR VAIC DA YEAR VAIC DA

2005 18.39781 3242.179 2010 189.436 35344.13

2006 157.3192 29262.82 2011 396.7991 73977.02

2007 163.4979 30376.55 2012 412.1003 76867.77

2008 163.4226 30393.28 2013 420.2428 78432.41

2009 154.3295 28761.21 2014 420.9062 78608.54






Figure-1: Relationship between VAIC and DA of ITC


Interpretation: The relations of VAIC and DA have a directly proportional. So the company represents same that the VAIC will

have a positive influence on the DA because in the company using its intellectual capital efficiency then the officials does not try

to manipulate the earninga of the company.

Note: I can mention one sample calculation of intellectual capital and earning quality selected industries and remaining as usual

same as above example.

Relation between Stock Returns and DA for ITC

Table-3: Relation between Stock Returns and DA for ITC

YEAR Stock Returns DA YEAR Stock Returns DA

2005 -89.2789732 3242.179 2010 -66.50671785 35344.13

2006 23.47368421 29262.82 2011 14.50511945 3977.02

2007 18.21247892 30376.55 2012 41.28078818 76867.77

2008 -19.12735849 30393.28 2013 11.95822454 78432.41

2009 45.42028986 28761.21 2014 13.94989174 78608.54


Figure-2: Relationship b/w STOCK RETURNS and DA of ITC


Interpretation: It is observed that the Stock returns and DA relationship is inversely proportional because high accruals

suggesting low-quality earnings are associated with poor stock returns in that relative year. When the Stock returns are high,DA

will be less which indicates earnings quality is high. The relationship between stock returns and DA of Itc is not significant

because of R2 = 0.175.

Note: I can mention one sample calculation of earning quality and stock returns of selected industries and remaining as usual

same as above example.

y = 186.85x - 108.75

R² = 1 D

A

VAIC

Relationship b/w VAIC and DA

DA

Linear (DA)

y = 267.91x + 36082

R² = 0.1457

DA

Stockreturns

Relationship b/w Stockreturns and DA

DA

Linear (DA)





Relation b/w VAIC and its Components for ITC

The values of VAIC and it component of ITC are presented in tables below:

Table-4(a) Table 4.4.1(b) Table 4.4.1(c)

Year HCE VAIC Year SCE VAIC Year CEE VAIC

2005 7.03786 18.3978 2005 0.85791 18.3978 2005 10.502 18.3978

2006 6.63386 157.319 2006 0.84926 157.319 2006 149.836 157.319

2007 6.82239 163.498 2007 0.85342 163.498 2007 155.822 163.498

2008 6.6653 163.423 2008 0.84997 163.423 2008 155.907 163.423

2009 5.92031 154.329 2009 0.83109 154.329 2009 147.578 154.329

2010 6.58003 189.436 2010 0.84802 189.436 2010 182.008 189.436

2011 7.01087 396.799 2011 0.85736 396.799 2011 388.931 396.799

2012 7.64492 412.1 2012 0.86919 412.1 2012 403.586 412.1

2013 8.33895 420.243 2013 0.88008 420.243 2013 411.024 420.243

2014 8.43213 420.906 2014 0.88141 420.906 2014 411.593 420.906


Figure-3: Relationship b/w VAIC and HCE of ITC


Interpretation: HCE represents the (human capital coefficient) intellectuals that are entered in the company they contribute for

the efficient VAIC to the firm, which in term affects the quality earnings.

Figure-4: Relationship b/w VAIC and SCE of ITC


y = 134.91x - 709.37

R² = 0.535

VA

IC

HCE

Relationship b/w VAICand HCE

VAIC

Linear (VAIC)

y = 6793.8x - 5577.9

R² = 0.5053

VA

IC

SCE

Relationship b/w VAIC and SCE

VAIC

Linear (VAIC)





Figure-5: Relationship b/w VAIC and CEE of ITC


Interpretation: SCE (structural capital co-efficiency), represents the optimum structure of the firm which points out low debts

and better VAIC investment to enhance the value of the company and intellectual if considered appropriate structural capital, if

not the debts will be high than the profits which becomes the reason for the companies to use manipulated earnings.

CEE (Capital employed efficiency), is usually available for the firm for the purpose of operations it should be used intellectually,

by the intellectual use of capital employed in the firm only the firm can perform better and avoid the fraud earnings representation

in the financial statements.

Note: I can mention one sample calculation of value added intellectual co-efficient and its components of selected industries and

remaining as usual same as above example.

Relation b/w DA and its components of ITC

The values of DA and its components of ITC is presented below:

Table-5(a) Table-5(b) Table-5(c)

Year DA VAIC YEAR DA LEV YEAR DA SIZE

2005 3242.179 18.39781 2005 3242.179 0.030362 2005 3242.179 8,081.07

2006 29262.82 157.3192 2006 29262.82 0.013125 2006 29262.82 9,122.04

2007 30376.55 163.4979 2007 30376.55 0.018985 2007 30376.55 10,580.88

2008 30393.28 163.4226 2008 30393.28 0.017553 2008 30393.28 12,215.98

2009 28761.21 154.3295 2009 28761.21 0.012809 2009 28761.21 13,857.54

2010 35344.13 189.436 2010 35344.13 0.007629 2010 35344.13 14,117.70

2011 73977.02 396.7991 2011 73977.02 0.005536 2011 73977.02 15,988.45

2012 76867.77 412.1003 2012 76867.77 0.004203 2012 76867.77 18,817.93

2013 78432.41 420.2428 2013 78432.41 0.002977 2013 78432.41 22,301.50

2014 78608.54 420.9062 2014 78608.54 0.001947 2014 78608.54 26,260.75


Figure-6: Relation b/w DA and VAIC of ITC


y = 1.004x + 6.9895

R² = 1 V

AIC

CEE

Relationship b/w VAICand CEE

VAIC

Linear (VAIC)

y = 0.0054x + 0.583

R² = 1

VA

IC

DA

Relationship b/w DA and VAIC

VAIC

Linear (VAIC)





Figure-7: Relation b/w DA and LEVit of ITC


Figure-8: Relation b/w DA and SIZEit of ITC


Interpretation: The correlation ship between the DA and its components is no significant but these components have influenced

in the companies quality earnings because all the three components can be manipulated easily. It can also be seen that the

relationship between the DA and its components.

Note: I can mention one sample calculation of discretionary accruals with other components of selected industries and remaining

as usual same as above example.

FINDINGS

Through present study on quality earnings, it was found that various earnings quality proxy‘s which represent the quality

of earnings position in the organization.

The quality earnings from a company to company vary according to the parameters they depend on.

The results of present investigation show that intellectual capital has positive impact on earnings quality, because

relationship between VAIC values and DA is linear and inversely proportional and its lead to conclude that intellectual

capital has a positive role in best financial practices and reporting.

Earnings with high accruals suggesting low-quality earnings are associated with poor stock returns in that relative year.

The Human capital efficiency (HCE) and Capital employed efficiency (CEE) both have a positive relation with the VAIC

whereas Structural capital efficiency (SCE) has an inverse relationship with VAIC because the employed capital is not

properly used for the operating a structure that makes the intellectuals become efficient.

The components of the DA that are VAIC, LEVIT (leverage), SIZEIT (total assets) combine shows a little effect on the

majority of the companies however individual components especially VAIC has predominant influence on the quality

earnings.

y = -2E-07x + 0.0178

R² = 0.3112

LE

Vit

DA

Relationship b/w DA and LEVit

LEV

Linear (LEV)

y = 0.2182x + 4531

R² = 0.8146

SIZ

Eit

DA

Relationship b/w DA and SIZEit

SIZE

Linear (SIZE)





CONCLUSION

The Study of Quality of Earnings is useful for the investors and any person who are depending on the company‘s financial

statement, it helps the investors the firms‘ financial position is real, rather than that reported by the firms itself. The investors are

suffer which company is best to invest the money, because of now companies are to show the high earnings only based on that

reported earnings shown by the company due to the manipulations done. So through the study the earnings quality of the 10

companies from 1 sector is considered.

The Quality of earnings topic arose from the wake of many situations in the present scenario, which are representing the

manipulations in the reported earnings to promote the companies‘ shares. It is revealed in the study done that most of the

companies try to manipulate the reported earnings at least to a certain extent by adding abnormal earnings to the companies true

earnings.

The investors who are trying to invest in any company should not only consider the reported earnings but should also analyze

quality of those earnings. In the study some of the companies‘ like ITC, Dabur, Britannia, Himalaya, Godrej, Emami, Nestle,

Ruchi showed good quality earnings so the small investors should try to invest their investment in these type of companies,

whereas speculators can consider the companies like Pidilite, Marico that have somewhat low earnings quality because they are

ready to face risk.

The companies that have good quality earnings are the companies that pay their taxes properly. So government can give subsides

on the taxation in order to encourage the company for maintaining true earnings.

REFERENCES

1. Retrieved from www.moneycontrol.com

2. Retrieved from www.bseindia.com

3. Retrieved from http://economictimes.indiatimes.com

4. McAnally, M. L., A., Srivastava, & C., D. Weaver. (2008). Executive stock options, missed earnings targets, and

earnings management. The Accounting Review, 83(1), 185–216.

5. McVay, S. E. (2006). Earnings management using classification shifting: An examination of core earnings and special

items. The Account- ing Review, 81(3), 501–531.

6. Mizik, N., & R., Jacobson. (2007). Myopic Marketing Management: Evidence of the phenomenon and its long-term

performance consequences in the SEO context. Marketing Science, 26(3), 361–379.

7. Roya, Darabi, S., Kamran Rad, & M., Ghadiri. (2012). The Relationship between Intellectual Capital and Earnings

Quality.

8. David, Aboody, John, hughes, & Jing, Liu. (2005). Earnings Quality, Insider Trading, and Cost of Capital.

9. Patricia, M. Dechow, & Ilia, D. Dichev. (2002). The Quality of Accruals and Earnings: The Role of Accrual

Estimation Errors.

10. Jennifer, Bender, & Frank, Nielsen. (2013). Earnings Quality Revisited.

11. Ralf, Ewert, & Alfred, Wagenhofer. (2009). Earnings Quality Metrics and What They Measure.

12. Jeffrey, T. Doyle, Weili, Ge, & Sarah, McVay. (2007). Accruals Quality and Internal Control over Financial

Reporting.

13. Nahum, D. Melumad, & Doron, Nissim. (2008). Line-Item Analysis of Earnings Quality.

14. Peter, R. Demerjian, Baruch, Lev, Melissa, F. Lewis, & Sarah, E. McVay. (2013). Managerial Ability and Earnings

Quality.

15. Retrieved from https://www.kellogg.northwestern.edu/accounting/papers/Ewert.pdf

www.moneycontrol.com

www.bseindia.com

http://economictimes.indiatimes.com/

https://www.kellogg.northwestern.edu/accounting/papers/Ewert.pdf





16. Retrieved from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=789985&rec=1&srcabs=794669&alg=1&...

17. Retrieved from

http://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID789985_code542089.pdf?abstractid=789985&mirid=1

18. Retrieved from http://ajbasweb.com/old/ajbas/2013/February/535-540.pdf

19. Retrieved from https://www.scribd.com/doc/278960848/RRL-Matrix-ToPIC-1-Effect-of-the-New-IFRS-15-Adoption-

Revenue-R...

20. Retrieved from https://www.scribd.com/doc/278960848/RRL-Matrix-ToPIC-1-Effect-of...

21. Retrieved from http://en.wikipedia.org/wiki/Earnings_quality#Rationale

22. Retrieved from http://en.wikipedia.org/wiki/Earnings_quality#Assessing_earnings_quality

23. Retrieved from http://en.wikipedia.org/wiki/Earnings_quality

24. Retrieved from https://en.m.wikipedia.org/wiki/Earnings_quality

25. Retrieved from http://www.investopedia.com/university/accounting-earnings-quality/earnings2.asp

26. Retrieved from http://www.maxwellsci.com/print/rjaset/v4-4192-4199.pdf

*****

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=789985&rec=1&srcabs=794669&alg=1&...

http://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID789985_code542089.pdf?abstractid=789985&mirid=1

http://ajbasweb.com/old/ajbas/2013/February/535-540.pdf

https://www.scribd.com/doc/278960848/RRL-Matrix-ToPIC-1-Effect-of-the-New-IFRS-15-Adoption-Revenue-R...

https://www.scribd.com/doc/278960848/RRL-Matrix-ToPIC-1-Effect-of-the-New-IFRS-15-Adoption-Revenue-R...

https://www.scribd.com/doc/278960848/RRL-Matrix-ToPIC-1-Effect-of...

http://en.wikipedia.org/wiki/Earnings_quality%23Rationale

http://en.wikipedia.org/wiki/Earnings_quality%23Assessing_earnings_quality

http://en.wikipedia.org/wiki/Earnings_quality

https://en.m.wikipedia.org/wiki/Earnings_quality

http://www.investopedia.com/university/accounting-earnings-quality/earnings2.asp

http://www.maxwellsci.com/print/rjaset/v4-4192-4199.pdf

A STUDY ON QUALITY OF EARNINGS IN FMCG...

Documents

Transcript of A STUDY ON QUALITY OF EARNINGS IN FMCG...