International Research Journal of Finance and Economics

ISSN 1450-2887 Issue 116 November, 2013

http://www.internationalresearchjournaloffinanceandeconomics.com

Earnings Management, Firm Performance, and the

Value of Indian Manufacturing Firms

Amarjit Gill

The University of SaskatchewanEdwards School of Business

25 Campus DriveSaskatoon, SK, S7N-5A7, Canada

E-mail: agill02@shaw.ca

Phone: 306-966-4785; Fax: 306-966-5408

Nahum Biger

School of Business Carmel Academic Center Haifa, Israel 33031

E-mail: nahum_b@carmel.ac.il

Harvinder S. Mand

University College Ghudda (Bathinda) District Bathinda

Pin Code: 151401 East Punjab, India

E-mail: hsmand27@gmail.com

Telephone: 98554-92501

Neil Mathur

College of Management & Technology Walden University

100 Washington Avenue South, Suite 900 Minneapolis, MN, USA 55401

E-mail: neil.mathur@waldenu.edu

Tel: 781.626.3240

Abstract

The purpose of this study was to test whether the practice of earnings management

that affects and perhaps benefits management of Indian companies has an effect on a firms’

performance, and whether earnings management has an effect on other stakeholders. This

study applied a co-relational research design. A sample of 250 firms was selected from Top

500 Companies listed on the Bombay Stock Exchange (BSE) for a period of 4 years (from

2009-2012). The findings of this study indicate that the more intense the practice of

earnings management, the greater it’s adverse effect on corporate rate of return on assets in

the following year. The study also found that to some extent, the market realizes that

management acts with selfish motives and responds by lowering share prices and corporate

market value. This study contributes to the literature on the association between several

features of earnings management and firm performance, and the value of the firm. It is

confined to Indian firms where companies perform intense earnings management. The

findings may be useful for financial managers, investors, financial management

consultants, and other stakeholders.

Keywords: Earnings management, Firm performance, Market value of the firm,

Shareholders’ wealth.

International Research Journal of Finance and Economics, Issue 116 (2013) 121

1. Introduction Earnings management is the practice of managerial actions that are reflected in a company's financial

reports either to give the impression of smooth periodic or annual earnings, to show high profits in a

given year at the 'expense' of lowering reported earnings in the future or to show low profit in a given

year so that in future years reported profits will be higher. In some cases, management uses various

accounting methods in order to convey private information to financial report readers. Management of

earnings may mislead stakeholders about the true financial performance of the company. If

management gains anything from managing earnings, one must ask whether such gains are at the

expense of anybody.

The study explores the relationship between the practice of earnings management, firm

performance, and firm's value for a sample of publicly traded Indian companies. We chose to study the

relationships for Indian companies because Indian companies have been notorious for practicing

earnings management in order to achieve several objectives. Varma, for example, states that Indian

companies regularly manipulate earnings and lists several motivations for such manipulation in India

including but not limited to personal gain of management, performance based incentives, and pressure

to achieve specified earnings targets. The prevalence of earnings management in India can be

explained by some local factors: Flexibilities provided by Indian regulatory bodies; unclear lines that

can differentiate fraud and aggressive accounting (earning manipulation); weak market competition;

information asymmetry; investors’ lack of awareness about the accounting concepts; and the high

emphasis of both managers and accountants on reported earnings (Verma, 2012, p. 539-540).

In developing countries, rules of law are weak and there are claims that corruption is high.

According to Transparency International (2012), corruption has increased in India over the last five

years. Dyreng, Hanlon, and Maydew (2011) found that firms’ earnings management is more common

in weak rule-of-law countries than in companies operating in locations where the rule of law is strong.

They also found some evidence that profitable firms with an extensive tax haven manage earnings

more than other firms and most earnings management takes place in domestic rather than foreign

income. This study then concentrates on Indian companies where rules of law are weak.

Due to the intense practice of earnings management (EM) in India, the relationship between the

intensity of the practice and firm performance and value is studies using several methods of

measurement of the intensity of EM. We apply standard regression analysis in order to examine the

extent to which there is a significant relationship between the intensity of earning management

practices and company's rate of return on total assets, and whether there is a significant relationship

between the intensity of EM and the market value of firms. We hypothesize that both relationships

should be negative.

Since the practice of earnings management is prevalent in many Indian companies, the paper is

interested in two research questions:

Does intensive use of earnings management by Indian companies adversely affect companies’

rate of return on assets?

Does intensive use of earnings management by Indian companies adversely affect corporate

market values?

This study provides insights for policy-makers as to the importance of earnings management

(FP) and firm performance in influencing shareholder wealth in Indian Top 500 Firms. The results may

be generalized to similar companies listed in Indian Top 500 Firms.

2. Literature Review Section 2 provides a literature review to formulate hypotheses.

The study of earnings management dates back to Healy’s (1985) study titled “the effect of

bonus schemes on accounting decisions.” Since that time, different authors conducted studies on

earnings management. While some authors (Sloan, 1996; Fairfield et al., 2003; Fama and French,

122 International Research Journal of Finance and Economics, Issue 116 (2013)

2006; Cooper et al., 2008; and Chu, 2012) have tested the relationship between EM and FP, other

authors (Teoh, Welch, and Wong, 1998; Othman and Zeghal, 2006; Huddart and Louis, 2009; Li,

2010; Cohen et al., 2011; Mashadi et al., 2012; and Gholami, Nickjoo, and Nemati, 2012) have tested

the relationship between EM and firm value. Although empirical studies in developed economies have

found that EM and FP affect the market price of shares, there has not been much research conducted on

developing countries (Ogundipe, Idowu, and Ogundipe, 2012).

2.1. Earnings Management and Firm Performance

It is important to understand the methods of earnings manipulation because firm performance (e.g.,

return on assets) relies on net income and managers can manipulate net income through current assets.

For example, managers can overstate ending inventory to manipulate cost of goods sold.

Earnings management (manipulation) is done by affecting total accruals and discretionary

accruals. Richardson et al. (2006) also found that accruals are associated with earnings manipulation.

Healy and Walden (1999) define EM as the alteration of a firm's reported economic performance by

insiders in order to either mislead some stakeholders or to influence contractual outcomes. The

alteration can be done by altering transactions (e.g., ending inventory, employee wages accruals in

month-ends, etc.). Fairfield et al. (2003), by sampling US firms for a period of 1963-1992 found that

working capital accruals have a negative relation with future profitability. Working capital accruals

include current assets and current liabilities. Verma (2012, p. 540) described that some of the earning

management techniques available and duly allowed by regulatory bodies (including Indian regulatory

bodies) are: i) inventory valuation methods (e.g., first in-first out, last in-first out, and weighted

average method), ii) more expenses accrued for a future period, iii) revenue and expense recognition

techniques, iv) using more of derivatives, v) transferring goods to an inflated market to increase the

profits or buying goods from a deflated market to produce desired results, and vi) showing unexpected

gains or losses from long term assets which were shown at cost.

Earnings management such as depositing current period A/R checks in the next period can

cause abnormal cash flows from operations which can impact the reported future profit of the firm. The

findings related to the relationship between EM and FP differs between authors. Sloan (1996), used

40,679 observations from US firms and found that the accrual component of operating income is less

persistent than the cash components for explaining one-year-ahead performance measured by the rate

of return on assets (ROA). Cooper et al. (2008), sampling US firms for a period of 1963-2003, found a

negative correlation between total asset growth and subsequent firm abnormal returns. Fama and

French (2006) analyzed data of US firms and found that accruals negatively predict one-year-ahead

reported profitability. Chu (2012), analyzing a sample of 4,438 US firms for a period of 1978-2007

found that high growth firms with low accruals experience high future profitability and returns.

In summary, the literature review indicates that EM impacts firm performance. Hence, the

following hypotheses are formulated:

H1: Earnings management by Indian companies adversely impacts firm performance.

2.2. Earnings Management and the Value of the Firm

One of the motivations behind earnings management is to provide good news to corporate boards by

showing good results in a certain period. This is a problem of potential endogeneity; that is, managers

are reluctant to announce earnings below analysts’ forecasts (Cohen et al., 2011) because it may have a

negative impact on market price per share. Because market price per share impacts the value of the

firm, managers tend to manipulate the components of the income statement and balance sheet through

accruals to maintain and/or to maximize share price for the current and subsequent year. However,

earnings manipulation tends to start backfiring after some time. For example, Teoh, Welch, and Wong

(1998), sampling 1,649 US initial public offering (IPO) firms from 1985-1992 found that issuers with

unusually high accruals in the IPO year experience poor stock return performance in the three years

thereafter.

International Research Journal of Finance and Economics, Issue 116 (2013) 123

Managers also tend to manipulate earnings to surprise investors, improve share price, and lower

debt costs. DuCharme and Malatesta (2004), sampling US companies for the period of 200-2001 found that

abnormal stock returns are positively related to the earnings surprise. Othman and Zeghal (2006), using

1,674 Canadian and 1,470 French firm-year observations for a period of 1996-2000 found that contractual

debt costs cause earnings management in French firms and issuing new equity leads to earnings

management in Canadian firms. Huddart and Louis (2009), used data from US COMPUSTAT for a period

of 1984-1999 and found that earnings management positively impact market price per share and led to the

1990s stock market bubble. Li (2010) took a sample of 7,861 US firms for the period 1988-2008 and found

that real earnings management practices of managers are related to subsequent higher stock returns. Cohen

et al. (2011), using a sample of 71,848 firm-quarter observations of US firms for a period of 1998-2008

found that the information environment is a crucial determinant of the market’s response to share price.

Gholami, Nickjoo, and Nemati (2012) sampled 1,200 US IPO firms for the period of 2000-2010. The

authors found that IPO firms engaged in earnings management with high investor beliefs have an influence

on the long-run abnormal stock return performance.

In contrast to some of these studies, we believe that the practice of earnings management is in a

sense a zero sum game; if management is to gain from earnings management and if creditors are not

deceived by earnings manipulation and are not offering cheaper credit to companies that manage

earnings, then shareholders must be on the losing end. Hence, the following hypothesis is formulated:

H2: Earnings management by Indian companies adversely impacts the firm value.

We also examined the extent to which some control variables have any effect on the postulated

hypotheses.

3. Methods This study applied a co-relational research design.

3.1. Measurement

The variables used in the analysis were:

i. Tobin’s Q represents the firm value.

ii. Rate of return on assets.

iii. Firm size.

iv. Financial leverage.

v. Current ratio.

vi. Four alternative measures of earnings management (EM) were adopted from modified

DeAngelo (1986), Jones’s (1991), and Abed, Al-Attar, and Suwaidan (2012), and Revenues

as a means of earnings management (managed revenues) was adopted from Stubben

(2010).1 Table 1 provides definitions of the dependent, independent, and control variables used in the analysis.

Table 1: Proxy Variables and their Measurements

Dependent Variables Measurement

Return on assets (ROAi,t) Net income after tax / Total assets

Market value (Qi,t)

Tobin’s Q = (Market value of equity + Book

value of debt) / Book value of total assets

Market value of equity = (Highest market value

per share + Lowest market value per shares) / 2

1 Details of the four alternative method of estimating earnings management are provided in the Appendix to the paper.

124 International Research Journal of Finance and Economics, Issue 116 (2013)

Table 1: Proxy Variables and their Measurements – (continued)

Independent Variables Measurement

Earnings Management Indicators

(a) Managed revenues (Ri,t) ΔAR i,t = C x ΔR i,t + (1 - C) x ΔDR i,t (b) Total accruals [balance-sheet approach] (TACC-B i,t) TACC-Bi,t = ∆CAi,t - ∆Cashi,t - ∆CLi,t + ∆DCi,t - DEPi,t (c) Total accruals [cash flow approach] (TACC-Oi,t) TACC-Oi,t = EARN�,t - CFO�,t (d) Discretionary accruals [cash flow approach] (DACC-

Oi,t) DACC-Oi,t = (TACCi,t - TACCi,t-1) / TAi,t

Control Variable

Firm size (FSi,t) Logarithm of total assets

Financial leverage (FLi,t) Total debt / Total assets

Current ratio - liquidity (CRi,t) Current assets / Current liabilities

µi,t = the error term

εјt = Error term for Firm j in Year t

The accruals measurement provided by Healy (1985) and Jones (1991) and other authors were

used because we examined four alternative measures or proxies of the intensity of earnings

management. We examined whether they all provided the same explanation or at lease brought about

the same sign or directional effect. Discussion of the various measures related to earnings management

is provided in Appendix A.

The basic regression equation defined the dependent variable (ROA or Q) and used either one

of the fours independent (explanatory) variables (R; TACC-B; TACC-O or DACC-O) in order to find

whether the slope coefficient was negative and statistically significant. We also added several control

variables to the regressions in order to find whether any of these variables had any significant

relationship with the dependent variables.

3.2. Data Collection

A database was built from a selection of approximately 500 financial reports from publicly traded

companies between January 1, 2007 and December 31, 2011. The selection was drawn from the

Bombay Stock Exchange (BSC) Top 500 companies (www.prowess.cmie.com) to collect a random

sample of manufacturing firms. Out of approximately 500 financial reports announced by public

companies between January 1, 2009 and December 31, 2012, only 250 financial reports were usable.

The cross sectional yearly data was used in this study. Thus, 250 financial reports resulted to 750 total

observations. Since the random sampling method was used to select companies, the sample is

considered a representative sample.

All companies from the service industry were omitted because in general these companies do

not provide all the necessary information. Some other firms for which data was unavailable were also

excluded.

3.3. Descriptive Statistics

Table 2: provides descriptive statistics of the sample.and.Descriptive Statistics

Minimum Maximum Mean SD

R10 -0.99 1.95 0.22 0.45

TACC-B10 0.01 4.90 3.01 0.91

TACC-O10 1.02 5.31 3.14 0.72

DACC-O10 -0.39 0.56 0.01 0.12

FS10 1.31 6.40 4.47 0.62

FL10 0.02 8.70 0.54 0.54

CR10 0.42 8.59 2.57 1.72

ROA10 -0.70 0.51 0.09 0.09

Q10 -6.08 17.65 3.45 2.87

R11 -0.69 1.94 0.28 0.33

TACC-B11 -13.76 14.88 1.41 3.14

International Research Journal of Finance and Economics, Issue 116 (2013) 125

Table 2: provides descriptive statistics of the sample.and.Descriptive Statistics – (continued)

TACC-O11 0.76 4.80 3.21 0.67

DACC-O11 -0.27 0.33 0.02 0.09

FS11 3.34 6.45 4.57 0.55

FL11 0.06 0.96 0.51 0.17

CR11 0.27 9.46 2.64 1.84

ROA11 -0.15 0.70 0.08 0.08

Q11 -14.52 17.86 3.46 3.51

R12 -0.99 0.91 0.17 0.28

TACC-B12 -16.38 17.85 0.79 3.78

TACC-O12 -13.28 8.88 1.36 3.18

DACC-O12 -0.35 0.47 -0.01 0.09

FS12 2.40 6.47 4.64 0.57

FL12 0.05 0.89 0.51 0.18

CR12 0.36 8.68 2.45 1.65

ROA12 -0.13 0.76 0.09 0.08

Q12 -4.71 18.63 3.23 3.42

SD = Standard deviation

R = Change in managed revenues

TACC-B = Change in total accruals (balance-sheet approach)

TACC-O = Total accruals (cash flow approach)

DACC-O = Change in discretionary accruals (cash flow approach)

FS = Firm size

FL = Financial leverage

CR = Current ratio (liquidity management)

ROA = Return on assets

Q = Market value of the firm

Appendix B provides the estimates of the Pearson pair-wise correlations between the alternative

proxies of the intensity of earnings management in the two years 2010 and 2011. Note that there is a

high correlation between the TACC-B proxies in 2010 and 2011, and between the TACC-O proxies in

2010 and 2011, indicating consistency in management practice in the two years. The two proxies were

highly correlated in 2010 but only weakly correlated in 2011.

4. Regression Analysis, Findings, Discussion, Conclusion, Limitations, and Future

Research Pooled data and cross sections were used to conduct this study. This practice may lead to a problem of

heteroskedasticity [changing variation after a short period of time] (Raheman and Nasr, 2007, P. 292).

To counter this problem, the weighted least square regression model with a cross section weight of

three industries (consumer products manufacturing, industrials products manufacturing, and energy

production) was used. In this regression, the common intercept was calculated for all variables and

assigned a weight.

There was also the possibility of endogeneity issues because we used multiple regression

analysis. The issue of endogeneity also takes place if certain variables are omitted and there are

measurement errors (Gill and Biger, 2013). To minimize endogeneity issues, the most important

variables that impact firm performance and firm value were used and the measurements were borrowed

from the previous empirical studies. As the sample of companies only included companies that

'survived' during the study period, there might have been a survival bias in the study. We consider this

to be a minor issue as the purpose of the study was to focus on the impact of earnings management and

firm performance on the value of the firms.

Table 3 provides the regression results for firm performance (return on assets) in 2011. We

used the Change in Managed Revenue proxy of earnings management intensity and two control

variables: firm size and financial leverage to test whether any of these control variables was related to

the following year's rate of return on assets – a proxy of firm performance.

126 International Research Journal of Finance and Economics, Issue 116 (2013)

Table 3: Earning Management and Future Firm Performance (Year 2011)

Un-standardized Coefficients Standardized Coefficients c T Sig. Collinearity Statistics

B Std. Error Beta Tolerance VIF

(Constant) 0.259 0.036 7.235 0.000

R10 -0.020 0.010 -0.120 -1.997 0.047 0.996 1.004

FS10 -0.033 0.008 -0.270 -4.377 0.000 0.943 1.060

FL10 -0.035 0.009 -0.250 -4.043 0.000 0.940 1.064

R10, FS10, FL10, and ROA11

R2 = 0.122; Adjusted R

2 = 0.111

For performance in 2011, change in managed revenues (a measure of the intensity of EM in the

previous year), as well as firm size and financial leverage all had statistically significant negative

coefficients, supporting our first hypothesis.

We also examined an alternative measure of the intensity of EM, and the results are presented below:

Table 4: Earning Management and Future Firm Performance (Year 2011)

Un-standardized Coefficients Standardized Coefficients c t Sig. Collinearity Statistics

B Std. Error Beta Tolerance VIF

(Constant) 0.194 0.018 10.823 0.000

TACC-B10 -0.035 0.005 -0.566 -6.593 0.000 0.938 1.066

FL10 -0.028 0.006 -0.421 -4.904 0.000 0.938 1.066

TACC-B10, FL10, and ROA11

R2 = 0.379; Adjusted R

2 = 0.365

The relationship between the intensity of EM in 2010 and performance in the following year

was again negative and highly significant. We also found that high financial leverage used by firms

was also negatively related to the following year's performance.

We also examined the relationship between another proxy of EM intensity, change in total

accruals, cash flow approach (TACC-O) and firm performance in the following year. The results are

displayed in Table 5:

Table 5: Earning Management and Future Firm Performance (Year 2011)

Un-standardized Coefficients Standardized Coefficients c t Sig. Collinearity Statistics

B Std. Error Beta Tolerance VIF

(Constant) 0.260 0.036 7.249 0.000

DACC-O10 -0.074 0.040 -0.111 -1.834 0.068 0.974 1.027

FS10 -0.034 0.008 -0.275 -4.461 0.000 0.944 1.059

FL10 -0.039 0.009 -0.276 -4.421 0.000 0.920 1.087

DACC-O10, FS10, FL10, and ROA11

R2 = 0.120; Adjusted R

2 = 0.109

This time, the relationship between the EM proxy and firm performance in the following year is

negative albeit only significant at p=0.068.

In contrast to the relationships between the EM proxies and firm performance in 2011, the

results for 2012 were in the opposite direction. We found that both the Change in total accruals – cash

flow approach proxy of EM (TACC-O) in 2011 and the Change in discretionary accruals – cash flow

approach (DACC-O) proxy had positive and significant relationships with the firm's performance in

2012. The results of the regressions are displayed in Tables 6 and 7.

Table 6: Earning Management and Future Firm Performance (Year 2012)

Un-standardized Coefficients Standardized Coefficients c t Sig. Collinearity Statistics

B Std. Error Beta Tolerance VIF

(Constant) 0.312 0.047 6.580 0.000

TACC-O11 0.045 0.011 0.360 4.327 0.000 0.604 1.657

International Research Journal of Finance and Economics, Issue 116 (2013) 127

Table 6: Earning Management and Future Firm Performance (Year 2012) – (continued)

FS11 -0.048 0.013 -0.323 -3.813 0.000 0.582 1.718

FL11 -0.208 0.033 -0.429 -6.306 0.000 0.901 1.110

CR11 -0.011 0.003 -0.261 -3.857 0.000 0.910 1.098

TACC-O11, FS11, FL10, CR11, and ROA12

R2 = 0.303; Adjusted R

2 = 0.286

Table 7: Earning Management and Future Firm Performance (Year 2012)

Un-standardized Coefficients Standardized Coefficients c t Sig. Collinearity Statistics

B Std. Error Beta Tolerance VIF

(Constant) 0.181 0.017 10.803 0.000

DACC-O11 0.297 0.049 0.331 6.041 0.000 0.944 1.059

FL11 -0.175 0.026 -0.385 -6.787 0.000 0.880 1.136

CR11 -0.004 0.002 -0.104 -1.878 0.062 0.930 1.075

DACC-O11, FL11, CR11, and Q12

R2 = 0.304; Adjusted R

2 = 0.296

The other two proxies of EM had no significant relationship with firm performance.

Note that a test for multicollinearity was performed. All the variance inflation factor (VIF)

coefficients were less than 2 and tolerance coefficients were greater than 0.50.

The practice of earnings management might have an effect on reported profitability in the year

that follows the activities that 'manage' profits. If management wishes to show high profit in a given

year, this may be done at the expense of next year (reported) profit. In order to examine this conjecture,

we ran regressions where the explanatory variables, one by one, were the alternative proxies of the

intensity of earning management, and the dependent variables were the following year rate of return on

assets. The results of these regressions were as follows:

For ROA11:

a. ROA11 = 0.091 – 0.024 R10, with t-value of -2.18 and p=0.03

b. ROA11 = 0.157 – 0.029 TACC-B10, with t-value of -4.957 and p=0.00

c. ROA11 = 1.537 – 0.49 TACC-O10, with t-value of -2.454 and p=0.015

d. ROA11 = 0.086 – 0.049 DACC-O10, but this explanatory variable was not statistically

different from zero.

The results confirm the hypothesis for 2011: in 2010 earnings management by Indian publicly

traded companies, adversely affected the rate of return on assets in the following year2.

Conversely, the following year, 2012, we found that two proxies of EM in 2011 had a positive

relationship with form performance. This result is at lease puzzling and we humbly provide no

explanation to this finding.

4.1. The Relationship between Earnings Management and the Value of Firm

The hypothesis regarding market perception of the practice of management of earnings by corporate

executives was examined for both 2011 and 2012. Regression of each one of the measures of earnings

management in 2010 on corporate value, measures by the Tobin's Q was run. As stated above, several

studies conjectured a positive relationship between the practice of earnings management and corporate

value. We hypothesize that since the practice of earnings management is usually undertaken in order to

advance top management interests, such practice is done at the expense of other stakeholders and must

therefore adversely affect the market value of the firm.

We conducted several single variable regressions. As stated, we examined each one of the

measures of earnings management as an explanatory variable of the variation of the Tobin-Q value in

2 The four alternative proxies for the intensity of earnings management in our study were not highly correlated. The only

two proxies that were found to be highly correlated in 2010 were the TACC-O10 and TACC-B10 with a correlation coefficient of 0.48. For 2011, none of the four proxies were significantly correlated with each other.

128 International Research Journal of Finance and Economics, Issue 116 (2013)

the following year. For the year 2011 two of the earnings management proxies were found to be

significant with the following regression results:

a. Q11 = 5.324 – 0.771 (TACC-B10), with t-value of the slope coefficient 1.98, and p = 0.05

b. Q11 = 6.67 – 0.891 (TACC-O10), with t-value of the slope coefficient 2.215 and p = 0.028

The other two proxies of earning management in 2010, R10 and DACC-O10 also showed a

negative slope coefficient, but the results were not statistically significant.

Our hypothesis regarding the effect of practicing earnings management was then confirmed for

2011. Top management practice of management of reported earnings adversely affected share prices

and the value of corporations, and the more prevalent the practice, the more adverse the effects.

We then performed the same test for earnings management in 2011. This time, for all four

proxies of earnings management in 2011, the slope coefficients were negative, but none of the

regression coefficients was found to be statistically significant.

We also attempted to determine whether practicing earnings management in the two

consecutive years affects the market value of companies in the following year. We found no significant

relationship of the corporate value for the proxy DACC10 and DACC11. Similarly, no significant

relationship was found when the EM proxies were R10 and R11.

For the proxies TACC-B10 and TACC-B11, we obtained the following regression results:

Q12 = 5.33 – 8.74 (TACC-B10), with t-value of the slope coefficient 2.415, and p = 0.018

Q12 = 3.38 – 1.09 (TACC-B11), with t-value of the slope coefficient 1.582, and p = 0.115

4.2. Discussion

The main purpose of this study was to test whether the practice of earnings management has an effect

on firm performance, and whether earnings management has an effect on firm value. The study focused

on Indian firms where the practice of earnings management is reported to be very common. We found

that for Indian companies, earnings management in 2010 adversely affected the performance of the

firm in the following year. Thus, the findings of this study lend some support to the findings of Fama

and French (2006). At variance, we found that EM in 2011 had a positive relationship with firm

performance in the following year, and we cannot provide a reasonable explanation to this finding. The

term "performance" was presented by the ratio of reported annual earnings as reported by the firms

divided by the firms' total assets. This rather tentative definition of performance might have been

improper measure of true economic performance of the firms since earnings that were measured in

2012 might have been 'managed' and it is conceivable that in 2012, firms had reasons to show higher

than true accounting profits so the positive relationship between 2011 EM and the return on assets in

2012 might be spurious.

With regard to the relationship between EM and market values, we found that, at least in the

context of our sample of Indian companies traded on the Mumbai stock exchange, there are rather clear

signs that, to some extent, the market realizes that management acts for selfish motives and responds

by lowering share prices and corporate market value. In some cases, and depending on the proxy one

uses to reflect and measure the extent of earnings management, the negative impact on the value is

statistically significant. For other measures that were proposed in several academic papers, the

relationships were negative; albeit not statistically significant. In any case, for the sample of Indian

companies, we did not find a single case where earnings management practices had a positive effect on

corporate market value. In the Indian context, investors tend to penalize companies whose management

performs intensive earnings management. These findings should be taken into account by managers

and should serve as a warning. If indeed part of the reasons for practicing management of earnings is

related to market-based bonus to management in the form of stock options or other price related

bonuses, the fact that the market price is adversely affected by such practices might partially deter

management from managing earnings. It will be noted that the findings of this study lend some support

to the findings of Teoh, Welch, and Wong (1998) and Gholami, Nickjoo, and Nemati (2012) but

contradict the findings of Huddart and Louis (2009) and Li (2010).

International Research Journal of Finance and Economics, Issue 116 (2013) 129

4.3. Conclusion

The present study found that the more intense the practice of earnings management, the greater its

adverse effect on firms’ rate of return on assets in the following year. Management seems to transfer

gains from the future to the present period in order to gain from reporting relatively good results in the

present period at the expense of the future. The market however, seems to detest this practice. We

found that the more intensive the activity of earnings management, the greater the negative effect of

such actions on corporate values. If managers are at all concerned with shareholders wealth instead of

their own, they should avoid the temptation of manage reported corporate earnings. Furthermore, if

managers manage earnings in an effort to gain from current year performance, but their gain takes the

form of stock options or other future price related compensations, they should realize that their

management of earnings in a given year has an adverse effect on market prices in subsequent years and

thus they might actually be on the losing end of the scale.

4.4. Limitations

This is a co-relational study that investigated the association between i) earnings management and firm

performance and ii) earnings management and firm value. There is not necessarily a causal relationship

between the two although some conjectures were provided to the findings.

This study is limited to the sample of Indian manufacturing firms. The findings of this study

could only be generalized to firms similar to those that were included in this research. In addition,

sample size is small.

4.5. Future Research

Future research should investigate generalizations of the findings beyond the Indian firms. Important

control variables such as industry sectors from different countries should also be used.

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Appendix A: Details on Earnings Management Models Healy (1985) model

Healy (1985) model assumed that non-discretionary accruals follow the regression of white noise,

whose average is zero. It follows that the value of expected non-discretionary accruals is zero. If the

value of total accruals (TACC), which is the sum of discretionary accruals (DACC), and non-

discretionary accruals (NDACC) is non-zero, it is the result of earnings management.

For a given firm, i,

DACCi,t = TACCi,t / TAi,t-1 where

TAi,t-1 = Total assets of firm i in period t

DACC = Discretionary accruals

DeAngelo (1986) Model

DeAngelo (1986) model assumed that non-discretionary accruals follow a random walk. For a

company in a stationary condition, the non-discretionary accrual in period t is equal to the non-

discretionary accrual in period t-1. As a result, the difference between the non-discretionary accruals in

period t and t-1 is the discretionary accrual which is related to earnings management.

DACCi,t = (TACCi,t - TACCi,t-1) / TAi,t where

DACC = Discretionary accruals

TACC = Total accruals

TA = Total assets

DACC-Oi,t = (TACCi,t - TACCi,t-1) / TAi,t

DACC-O = Discretionary accruals under operating cash flow approach of Jones (1991)

Modified Jones (1991) Model

The cross-sectional modified version of Jones’ model (Jones, 1991; Dechow et al., 1995) was also

applied to obtain proxies total accruals. The details on Jones’s model are as follows:

Jones’s (1991) model uses the balance-sheet approach, the cash-flow approach, and the

difference between earnings before extraordinary items and cash flow from operations. The

explanation of each measurement component that was used in this study is described as follows:

Total accruals computed under the balance-sheet approach are represented by the following

equation:

TACC-Bi,t = ∆CAi,t - ∆Cashi,t - ∆CLi,t + ∆DCi,t - DEPi,t

where

TACC-Bi,t = Total accruals under the balance-sheet approach for firm i in year t

∆CAi,t = Change in current assets for firm i in year t

∆Cashi,t = Change in cash and cash equivalents for firm i in year t

∆CLi,t = Change in current liabilities for firm i in year t

132 International Research Journal of Finance and Economics, Issue 116 (2013)

∆DCi,t = Change in debt included in current liabilities for firm i in year t

DEPi,t = Depreciation and amortization expense for firm i in year t

Total accruals calculated as the difference between earnings before extraordinary items and

cash flow from operations is reflected by the following equation:

TACC-Oi,t = EARNј,t - CFOј,t

TACC-Oј,t = Total accruals under operating cash-flow approach for firm i in year t

EARNј,t = Earnings before extraordinary items for firm i in year t

CFOј,t = Cash flows from operations for firm i in year t

Revenues as a Means of Earnings Management

The model of discretionary revenues can be described as follows:

Managed revenues (R) - the sum of nondiscretionary revenues (NDR) and discretionary

revenues (DR).

R = NDRi,t + DRi,t

A fraction (C) of nondiscretionary revenues remains uncollected at year-end, and it is assumed

that there are no cash collections of discretionary revenues. Thus, accounts receivable (AR) equals the

sum of uncollected nondiscretionary revenues (NDR) and discretionary revenues (DR)

AR i,t = C x (NDRi,t + DRi,t)

Discretionary revenues increase accounts receivable and revenues by the same amount;

discretionary receivables equals discretionary revenues.

Nondiscretionary revenues are not observable; therefore, terms have been rearranged to express

ending receivables in terms of reported revenues and then, took first differences to arrive at the

following expression for the receivables accrual:

∆ARi,t = C x ∆Ri,t + (1 - C) x ∆DRi,t

Appendix B: Pearson Correlations Coefficients

2 3 4 5 6 7

DACC-

O11

1 R10.010 .172 .266 -.013 .017 .013 -.155

2 TACC-B10 .480 -.031 -.053 .099 .469 -.461

3 TACC-O10 .295 -.061 -.105 .673 -.382

4 DACC-O10-.035 -.065 .025 -.320

5 R11.114 .106 .193

6 TACC-B11.150 .170

7 TACC-O11.122

Bold numbers are significant at p<0.05

Pearson Correlation coefficients