4

2. LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT

2.1 Conceptual framework and definitions

2.1.1 Firm life cycle

The corporate life cycle connotes the phenomenon of incorporation of a firm,

it’s growth, progress to maturity and decline. As the firm grows from being a start-up

to the publically funded corporation it exhibits distinct characteristics pertaining to the

fundamental variables. The distinct phases of firm life cycle are function of various

internal and external factors, which in turn are resultant of firm level choices and

activities (Dickinson, 2011). ‘Firm life cycle’ represents a combination of distinct

product life cycles and also industry life cycle in case of well-diversified portfolio of

products.5

The availability of sources of finance, capital structure, investment

opportunities, accounting policies and even the objectives of existence of the firm

evolve over the firms’ life cycle.

Traditionally, the practitioners and academicians have criticized the profit-

maximizing objective of the firm’s managers. The critique of the conventional

business rationale of profit maximization gave birth to many competing theories

justifying the existence of an enterprise. One such explanation is embedded in the

‘Growth Hypothesis’, considering the growth in the size of firm as the ultimate

objective of the managers (Mueller, 1972). The life cycle theory emphasized on the

intentions of a manger to pursue growth rather than shareholder value maximization

as a corporation matures. The behaviour of the agent can be justified as their

monetary and non-monetary benefits are directly or indirectly attached to the firm’s

growth. In the initial stages of the entrepreneurial venture, both the managers and the

5 See, for example, Anderson & Zeithaml (1984); Klepper (1996); Polli & Cook

(1969); Jovanovic & MacDonald (1994)

5

stockholders aim for growth maximization strategies. As the organization grows and

matures, the conflict of the managerial utility maximization and stockholder wealth

maximization deepens. In the mature firms, declining profits and decreasing

investment opportunities result in ploughing back of profits at lower than market

returns (Grabowski & Mueller, 1975). The gradual shift in the policies of the

managers of firms because of transition from growth stage to mature phase leads to

over investment in growth while the stockholders prefer dividend pay outs. The

research (Senchack Jr. & Lee, 1980) attempted to model the optimal amount of

investment, financing and dividend policy decisions over the different earnings

growth stages of a firm life cycle, which maximize the shareholders’ wealth. The

three stages in the earnings growth model of financial life cycle of the firm are high,

low and negative growth stage. The liquidating dividends and reducing outstanding

debts characterize the low and negative growth stages. The fundamental financial

variables such as return on investment (ROI), debt-equity ratio, borrowing rate, equity

discount rate, depreciation rate and flotation cost affect the duration of the life cycle

stages both in terms of direction and magnitude. ROI has the highest effect on the

duration of the life cycle stages. The magnitude of such impact of the financial

variables is found to be greatest in firms that have lower leverage and growing

earnings than in firms with higher leverage.

The longitudinal analysis of 36 firms over 161 periods on the basis of 54

variables of strategy, situation, structure and decision making style supported the

manifestations of the life cycle hypothesis (Miller & Friesen, 1984). The firms’

characteristics over the 5 life stages namely introduction, growth, maturity, revival

and decline were found to be internally consistent, mutually distinct and

complementary. However, the sample firms reported exceptions in reporting a

6

deterministic sequence, thus emphasizing the availability of alternate paths to the

corporations while progressing in the life cycle.6

The availability of sources of finance and capital structure varies with the

financial growth life cycle of the firm with special reference to the small businesses

and entrepreneurial ventures (Berger & Udell, 1998). Depending on the financial

needs, access to the intermediaries and stage in the life cycle, firm’s sources of

finance varies from angel finance or insider finance on one end of the continuum to

public equity on the other end. The major point of difference between large firms and

small firms is the informational opacity and the firms’ contracts with stakeholders are

not publically available in case of small firms. The results of the empirical testing of

the Berger & Udell (1998) model in the context of small and medium enterprises

suggests that firm size as measured by the number of employees is a significant

predictor of capital structure decisions (Gregory, Rutherford, Oswald, & Gardiner,

2005). The authors also suggested that the younger firms are more likely to use public

equity and long-term debt than the older firms. It concluded that the small and

medium size business financing patterns couldn’t be mapped to a single model such

as Berger and Udell (1998) as these firms exhibit very distinct characteristics. Agency

problems and the issues related to the dysfunctional corporate governance are also not

pertinent in the smaller businesses. An agency theory perspective of a firm life cycle

suggests how the agents affect the firm’s life cycle (Bulmash, 1986). The dynamic

agency model over a multi-period horizon indicates that the agent’s incentive

structure affects the operating decisions taken by him over the firm’s life. The

productivity of the agent decreases at the time period near to retirement because the

6 See Miller & Friesen (1982) for discussion on the methodological perspective of

longitudinal studies in the area.

7

agent’s claim on future residual income is about to terminate. Hence the agent’s

behaviour, decisions and perceptions are bound to affect the firm life cycle indirectly.

The literature also provides evidences of the impact of corporate life cycle on

the dividend payout policy. Life cycle theory of firm posits that the decision to

distribute dividends is a function of the cost associated with retaining the cash

balances (DeAngelo, DeAngelo, & Stulz, 2006). The cost of retaining cash balances

also includes the availability of opportunities to managers for taking self- serving

decisions rather than wealth enhancing decisions in the presence of excess cash at

their disposal. However, only agency cost cannot explain the reasons for high payout

by the firms. The study suggests that the earned to contributed capital mix, which is

used as a proxy for firm life cycle significantly explains the dividend payout

decisions. Other factors such as growth and profitability are also found to be

significant; however their impact is relatively moderate as compared to the ratio of

earned to contributed capital mix. Anthony & Ramesh (1992) measured firm life

cycle using dividend payout (DP), sales growth (SG) and age as the life cycle

descriptors. The research suggested that the stock markets response as measured by

cumulative abnormal returns (CAR) to the two fundamental accounting performance

measures namely unexpected sales growth and unexpected capital expenditure

decreases linearly from growth to stagnant stage of a firm life cycle.

8

2.1.2 Financial Distress

Financial Distress as a phenomenon has been a focal point of study in corporate

finance since the notable corporate failure of Penn Central and railroad industry in

1970 (Altman, 1971; Altman & Nammacher, 1985). The terms ‘financial distress’

and ‘bankruptcy’, have commonly been often used synonymously; however the two

situations differ substantially in terms of the fundamental variables related to firm’s

financial health as well as in the sequence of events. Bankruptcy or insolvency or

liquidation is the situation, preceded by financial distress. Platt & Platt (2002)

emphasized that financial distress is the late stage of firm decline, which can be

followed by the major events such as bankruptcy, liquidation or insolvency.

Developing a theory of financial distress, Gordon (1971) suggested that the decrease

in the earnings capacity of the firm can result in the possibility of inability of the firm

to repay the principal or interest component of debt. Such a state represents the

distressed financial condition of the firm. Wruck (1990) also explained “financial

distress as a situation, where cash flows are insufficient to cover the current

obligations”. Researchers have attempted to unravel the causes and impact of

financial troubles, bankruptcy, debt restructuring along with the efforts to predict the

distressed conditions of the firms. Although, the financial distress has always been

perceived in a negative light, the literature documents that the phenomenon results

into costs as well as certain benefits to the corporations (Opler & Titman, 1994;

Wruck, 1990). Out of pocket or the direct costs (such as legal, administrative,

advisory fees), indirect or the opportunity costs (such as additional covenants,

decrease in product demand, increase in the cost of production, management’s effort

in distress resolution) are the major costs incurred by the firms experiencing the

distressed condition. The benefits that accrue as a result of financial distress ranges

9

from change in management, change in governance structures, improvement in the

organizational structures and strategies leading to impacting the organizational

efficiencies. The examination of effect of financial distress on organizational

efficiency suggests that net effect of financial distress on the firm is affected by

financial and ownership structure (Wruck, 1990). The value maximizing and

organizational efficiency enhancing resolution of financial distress can be achieved

through aligning the interest of the agents with the stakeholders thus minimizing the

conflict of interest. The research on industry distress by Opler & Titman (1994)

empirically tests the relationship between firm performance and the financial structure

(leverage) and the distressed industrial environment. A firm with high leverage

suffers a higher decline in sales at the time of industry wide downturn (distressed

industry). Losses to the firm in the distressed condition or environment can be

classified into customer driven, competitor driven and manager driven. The effect of

the leverage is higher in the industries with specialized products as the customer

driven losses are higher in such industries. Similarly the concentrated industries are

found to have more pronounced effects of leverage as the competitor driven losses are

high. The analysis suggests a positive relationship between firm performance and

financial condition of the firm in the times of reductions in the industrial outputs.

Extant literature documents the effect of financial distress on equity returns

and corporate performance. Since 1980’s, the equity of financially distressed firms or

firms with higher bankruptcy risk have been found to offer lower returns and higher

standard deviation (Campbell, Hilscher, & Szilagyi, 2008; Dichev, 1998) 7, thus

7 A competing strand of research focuses on the size effect and value effect and its

relation to the firm distress. The effects are found to be more pronounced in firms

with higher default risk (Garlappi & Yan, 2011; Griffin & Lemmon, 2002; Vassalou

& Xing, 2004). Hence, the value effect and size effect compensate for the higher

default risk, offering higher returns to distressed firms.

10

providing credence to the observed phenomenon of huge loss to investors when

corporations fail.

The literature associated with bankruptcy and financial distress prediction

models documents historical evolution of the techniques, which are constantly

evolving in the present day academic discourses. The financial distress and

bankruptcy prediction models can be categorized into financial ratio based (Altman,

1968; Beaver, 1966; MacKIE-MASON, 1990; Ohlson, 1980; Wilcox, 1971;

Zmijewski, 1984); Price based (Bharath & Shumway, 2008; Merton, 1974); and the

prediction models using the artificial neural networks , fuzzy logic, data envelopment

analysis (DEA) (Altman, Marco, & Varetto, 1994; Xu & Wang, 2009). The evolution

and the usage of each category of models is discussed below:

A. Financial ratio based models of distress and bankruptcy prediction

The seminal studies by Beaver (1966) verified the predictive ability of financial ratios

in the event of corporate failure based on the 30 individual ratios or univariate

analysis and suggested that ratios have the ability to detect the illness of firms much

before the corporate failure.8 Altman (1968) presented a bankruptcy prediction model

based on multiple discriminant analysis. The model based upon ratio analysis to

predict the financial health of the enterprise considers multivariate view along with

the interaction of the various independent variables instead of the earlier univariate

analysis. The predictive accuracy of the model is reported as 95%. The model

suggested in the paper based on the validation tests on the initial as well as secondary

samples found that the model’s predictive ability is highest up to two years prior to

the bankruptcy and the prediction power decreases as the lead time increases.

8 See Wilcox (1971), for a theoretical model explaining the empirical results of

Beaver (1966)

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The model is as follows:

Z =.012X1 +.014X2 +.033X3 +.006X4 +.999X5

Where, Xl =Working capital/Total assets

X2 = Retained Earnings/Total assets

X3 = Earnings before interest and taxes/Total assets

X4 =Market value of equity/Book value of total debt

X5 = Sales/Total assets

Z = Overall Index

The ratios used in the model were found to be considerably higher for the non-

bankrupt firms, hence leading to a higher Z score. Higher the Z score, lower is the

probability of bankruptcy for the firm.

With the evolution of the bankruptcy prediction models, emphasis shifted on

the virtues of conditional logit analysis from multiple discriminant analysis (MDA),

Ohlson (1980), used the conditional logit analysis to predict the bankruptcy among

105 bankrupt firms with non-bankrupt firms as a control sample. The following four

basic concepts affect the probability of failure.

a) Size of company

b) Measures of financial structure

c) Measures of performance

d) Measures of liquidity

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The discussed prediction models were based on the match sample comparisons of

failed/ bankrupt and non-failed/non-bankrupt firms 9 The major drawback of paired

comparison is the inability to draw inferences regarding the single observation or the

firm and its level of financial distress. Further, Altman (1968)’s model of predicting

the bankruptcy was modified by MacKIE-MASON (1990), by excluding one variable

form the original model. The excluded variable was Market value of equity to Total

debt (X4), as it is systematically related to the other variables, which are generally

examined in the financial studies such as leverage ratios (Lee, Koh, & Kang, 2011).

Many studies (Acharya, Bharath, & Srinivasan, 2007; Bhagat & Bolton, 2008; Burak

Güner, Malmendier, & Tate, 2008; Graham, Lemmon, & Schallheim, 1998) in the

literature have used the modified version of Z score estimation for predicting the

financial health of the company.

B. Price based model of distress and bankruptcy prediction

Building upon the informationally efficient capital markets, the price based model

takes into account the market related data such as stock prices and equity returns. The

major advantage of market data based models is the timeliness of the information

(Keasey & Watson, 1991). The market based models are derived from Black &

Scholes (1973) and Merton (1974) model of contingent claims. The model considers

firms’ equity as a call option on the underlying assets of the firm having a strike price

equal to face value of the firm’s debt or liability. Market based models thus calculate

the distress risk, which is the probability of face value of the underlying assets of the

9 See Zmijewski (1984) for discussion on sample selection biases in the matched

sample comparisons or paired comparison

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firm decreasing to a value below the face value of the firm’s liability or debt at the

end of the forecasting horizon thus known as Merton’s distance-to-default model. In

order to assess the predictive accuracy of Merton’s distance-to-default model with

unrealistic assumptions, Bharath & Shumway (2008), refined the Merton’s structural

model. The naïve DD model suggested by Bharath & Shumway (2008) outperformed

the Merton (1974) distance-to-default model and suggetsed that the iterative process

of the DD model is not very useful and a such structural model can only be used to

build the future predictive models. However, the market based models also suffer

from various limitations. Reisz & Perlich (2007) have suggested that accounting ratio

based measures have better predictive accuracy in shorter time horizons such as 1

year ahead bankruptcy prediction. The accounting based approaches are also

suggested to be robust and economically beneficial than the market approach

(Agarwal & Taffler, 2008).

C. Artificial neural network based distress and bankruptcy prediction

models

In an effort to improve the classification & prediction accuracy, the mathematical &

computational techniques such as artificial intelligence approaches, data mining

techniques, neural networks, data envelopment analysis (DEA), expert systems and

genetic algorithms have been widely used in the prediction of corporate failure (Xu &

Wang, 2009). The advantages of such techniques over the classical statistical

techniques are the absence of conformity to the assumptions of normality, linearity

and absence of multicollinearity. The artificial neural network techniques generally

involve dividing the data into two categories: Training sample (in sample) and test

sample (out sample). Randomly dividing the data into such categories introduces

biases in the model (Zhang, Y. Hu, Eddy Patuwo, & C. Indro, 1999). However, in

14

case of the computational techniques such as neural networks, it is difficult to

understand the underlying complexities of non-linear nature of underlying networks

(Altman et al., 1994). Thus, the limitations of stand-alone models based on neural

networks, call for using these techniques in an integrated manner with the classical

statistical techniques.

2.1.3 Earnings Management

The Indian Accounting Standard (Ind AS) 1 states that

“ the objective of financial statements is to provide information about the

financial position, financial performance and cash flows of an entity that is

useful to a wide range of users in making economic decisions.”

Hence, the informational quality of the financial statements is a function of the

decision context. Dechow, Ge, & Schrand (2010) emphasize that the earnings quality

is determined by its relevance to the particular decision context and informativeness

about the financial performance of the firm. Earnings reported by the firm are a

function of both, the fundamental financial performance of the firm as well as the

measurement of the performance by the accounting systems established in the firm.

The reported earnings are a function of how the accounting measurement systems are

implemented in the organizations which involves scope for personal judgments of the

managers and accountants resulting into biases in the reported earnings in the form of

earnings management. The constructs ‘earnings quality’ and ‘earnings management’

are related to each other such that higher earnings management leads to poorer

earnings quality. Many authors defined the terms ‘earnings quality’ and ‘earnings

management’ differently. Ronen & Yaari (2008) classify the definition of ‘earnings

management’ into white (beneficial earnings management enhancing the transparency

of financial statements); black (harmful earnings management involving

15

misrepresentation of reported numbers); grey (manipulating the reported numbers

within the legal framework or accounting standards). Healy & Wahlen (1999) state

that “earnings management occurs when managers use judgment in financial

reporting and in structuring transactions to alter financial reports to either mislead

some stakeholders about the underlying economic performance of the company or to

influence contractual outcomes that depend on reported accounting numbers”.

Similarly Walker (2013) defines ‘earnings management’ “as a use of managerial

discretion over (within GAAP) accounting choices, earnings reporting choices, and

real economic decisions to influence how underlying economic events are reflected in

one or more measures of earnings”. Thus, earnings management is generally

employed by top management of corporates to lure the investors and maintain the

market capitalization in spite of poor performance of the firm. In a way it enables the

management to use the flexibilities provided by the regulatory framework to

aesthetically manipulate the financial statements to make them appear, as the

management wants it to look to the outsiders including the shareholders and

stakeholders. Agency theory (Eisenhardt, 1989; Jensen & Meckling, 1976) provides

us the fundamental basis to study earnings management in the light of the principal-

agent relationship. Agency theory emphasizes that in a firm, managers have superior

information pertaining to firm value than the shareholders. Separation of ownership

and control in the firm affects the earnings informativeness and magnitude of

discretionary accruals adjustment (Warfield, Wild, & Wild, 1995). Agency theory

links the earnings management with three key aspects: Costly-contracting, Efficient

contracting and the information asymmetries (Walker, 2013). To a large extent these

approaches successfully justify the motives behind managing the reported numbers.

The costly contracting approach refers to the assumption in the agency theory that

16

firm is a nexus of contracts and the contracts are difficult to negotiate. Hence,

managers indulge in manipulation of earnings in order to avoid the violations of

contractual obligations (debt covenants and compensation contracts).

Efficient contracting approach (Holthausen, 1990) suggests that the parties to the

contract are efficient in designing the contracts so as to minimize the agency cost and

maximize the value of the firm, thus affecting the choice of accounting methods by

managers. Informational asymmetry approach emphasizes on the need of the firms to

influence the expectations of stakeholders and the third parties about the future cash

flow, in turn influencing the market capitalizations. The various studies in the

literature pertaining to the ‘earnings quality’ as a construct are categorized into

determinant studies and the consequences studies (Dechow et al., 2010). The

determinant studies pertain to the research related to the causes or determinants of

earnings quality where the earning quality is a dependent variable. However, the

consequences studies are related to the outcome of earnings quality. The proxies

measuring the earnings quality are categorized into three sections namely: Based on

properties of earnings; Based on investors’ responsiveness to earnings; Based on the

external indicators of earnings restatements. The properties of earnings, which are

considered as proxies for the earnings quality are: Earnings Persistence; Accruals

(normal and abnormal) and their modeling; Earnings smoothness; Asymmetric

timeliness and timely loss recognition; Earnings response coefficient; Target beating.

However, discretionary accruals has been the most widely used proxy in the literature

to measure the extent of earnings management as it accounts for the discretion used

by the managers in reporting the earnings (Cohen, Dey, & Lys, 2005). Discretionary

accruals can’t be estimated directly from the financial statements, thus posing a major

challenge for the stakeholders in detecting earning management. Extant literature

17

documents various models developed for estimating the discretionary accruals as a

proxy for earnings quality and earning management as synthesized by various review

papers (Dechow et al., 2010; Dechow, Sloan, & Sweeney, 1995). The major models

for estimating discretionary accruals as discussed in the literature are given in the

table:

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Table 1: Models for estimating discretionary accruals

S.No. Accrual Model Model Details

1. Healy (1985) ACC= NDA+ DA

The model divided the total accruals into two parts:

Discretionary and Non-discretionary. It divided the

sample under study into three groups: one with income

increasing activities (estimation group) and other two

with income decreasing activities (observation group).

It calculates the NDA as the mean total accruals (scaled

by logged total assets) of the estimation group. Total

accruals are estimated as the difference between

reported earnings and cash flow from operations.

2. DeAngelo (1986)

The model differs from the Healy’s Model in terms of

the estimation of NDA as NDA are calculated on the

previous year’s total accruals scaled by the logged total

assets.

3. Jones (1991) ⁄

ACCt= α+ β1∆ REVt+ β2PPEt+ εt

Equation for calculating the firm specific parameters α, β1, β2

( ⁄ )

The model accounts for the firm specific factors and

accruals are considered to be the function of revenue

growth and PPE. The second model calculates firm

specific parameters in the estimation period.

4. Modified Jones Model

Dechow et al., (1995)

ACCt=α+ βt ∆REVt-∆RECt+ βt PPEt+εt

Equation for calculating the firm specific parameters α, β1, β2

( ⁄ )

The model modified the calculation of the NDA by the

Jones Model by making an adjustment in the change in

revenues for the change in receivables. The original

Jones model calculates the firm specific factors.

5. Industry Model

Dechow & Sloan (1991)

Median TA= Median value of total accruals of the non sample

firms with same 2 digit SIC code

The model takes into consideration the industry

specific factors. The firm specific parameters are

calculated using the same model in the estimation

period.

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6. Performance matched Discretionary

accrual measures

Kothari, Leone, & Wasley (2005)

Performance matched discretionary accrual=Jones model

discretionary accrual of firm i in year t- Jones model discretionary

accruals of matched firm's in year t

The model controls the firm performance by matching

the firm performance on the basis of 2 digits SIC code

and return on assets.

7. Dechow & Dichev (2002) ∆ WC= α+ β 1CFOt-1+ β2CFOt+β3CFOt+1+εt The model defines earnings quality as how perfectly

the estimated accruals map into the realized cash flow.

Accrual quality is thus a function of the estimation

errors as well as assumptions in determining the

accruals. It measures the accruals quality by taking the

error term as a proxy in regressing the working capital

accruals over the past, present and future cash flows.

8. Discretionary Estimations errors

Francis, LaFond, Olsson, &

Schipper (2005)

TCAt= α+β1CFOt-1+β2CFOt+β3 CFOt+1+ β4∆ REVt+β5PPEt+εt

The model is based upon Dechow and Dichev model,

augmented by the fundamental variables from the

Modified Jones model. It further decomposes the

accruals quality into innate and discretionary

components.

Note: The description of the variables is as under: ACC/ACt= Total Accruals; NDA/NAt=Nondiscretionary accruals; DA/DAt=Discretionary Accruals; A= Total Assets;

ΔCAt = Change in current Assets; ΔCLt= Change in current liabilities; ΔCASH= Change in cash and cash equivalents; ΔSTD= Change in debt included in current liabilities;

Dep= Depreciation and amortization expenses; ∆ REV= Change in the revenue from the previous year; PPE= Gross property, plant and equipment; Δ WC= Change in

working capital accruals; CFOt-1= Previous years cash flow from operations; CFOt= Present year cash flow from operations; CFOt+1= Next year cash flow from operations.

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2.1.4 Capital Structure

The present study explores the effect of capital structure on the earnings management

and financial distress, which makes it important to study the underlying theories of

capital structure. Myers (2001)reviewed the various capital structure theories in the

corporate finance literature. The review emphasized that there are no universal

theories of capital structure, however all the theories can be called as conditional

theories suggesting the costs and benefits of different sources of finance. Modigliani

& Miller (1958) suggested that capital structure doesn’t affect the value of the firm,

cost of capital and the availability of the capital. However, the capital structure can be

affected by tax (Trade-off theory), information (Pecking Order Theory) and the

agency cost (free cash flow theory) (Myers, 2001). The extant literature documents

the various determinants of capital structure such as: Collateral Value of

Assets/Assets structure; Financial distress; Non-Debt Tax Shields; Age; Growth;

Uniqueness; Signalling; Industry Classification; Size; Volatility and Profitability

(Titman & Wessels, 1988).

The research (Grossman & Hart, 1982) also emphasizes on the role of debt in

signalling the quality of management by decreasing the incentive problems using

possibility of bankruptcy as a disciplinary tool. Debt financing in capital structure also

signals pre-commitment or bonding behaviour of the managers resulting in an

increase in the market value of the firm. The effectiveness of bankruptcy as a

disciplinary device in the agency relations is dependent upon the level of debt in the

capital structure. Measures of financial structure are one among the four fundamental

measures affecting the probability of failure in the firms along with size, measures of

performance and measures of liquidity. Debt acts as a signal for quality of firms’

management, resulting in an increase in the firm value, which in turn increases the

21

managers’ perquisites. Presence of debt in the capital structure may lead to demand

for higher quality of accounting information (Grossman & Hart, 1982). Hence, debt

acts as monitoring and disciplinary tool resulting in a demand for higher quality of

accounting information and signals the financial health of the firm.

The empirical studies on capital structure categorize the proxies for measuring

the capital structure into two categories: Leverage based on book values and leverage

based on market values. Book leverage refers to the ratio of book value of total debt

to book value of total assets. Market leverage refers to ratio of book value of the total

debt to the book value of total liabilities and the market value of the equity

(Chakraborty, 2010).

Although the most relevant measure of leverage depend on the context and

objective of the research, however various measures of leverage range from ratio of

debt to firm value, interest coverage ratio, total liabilities to total assets, ratio of debt

(short term and long term) to total assets and the ratio of total debt to net assets (total

assets less accounts payable and other liabilities) (Rajan & Zingales, 1995). Titman &

Wessels (1988) suggest that, the measurement of capital structure includes the long-

term, short-term, convertible debt divided by market or book values of equity (Titman

& Wessels, 1988). However, the study emphasizes on the various limitations such as

data availability of using the market value of data and suggests the use of book value

as measures of debt. Bowman (1980) suggested that the correlation between the

market value and book values of debt is significantly high, which makes them

indistinguishable. The book value has been used as it is considered to reflect

managerial decision making more directly (Carter, 2013; Kisgen, 2006). The book

value of debt is found to be more representative of the ability of the firm to repay to

the debt holders (Bradley, Jarrell, & Kim, 1984).

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2.2 Literature review of causal linkages

2.2.1 Firm Life cycle and Earnings Management

Corporate life cycle is a principal determinant of the value of the summary

measures of performance such as earnings and cash flows reported by the firm.

However, the relative value relevance of cash flows (operating, investing and

financing) to earnings varies with the corporate life cycle (Black, 1998). Earnings are

more value relevant than the cash flows at the maturity stage. While examining the

components of cash flow it is found that the investing cash flows are more relevant in

the growth stage and the operating cash flows are more relevant in the decline stage.

Further, research (Jenkins, Kane, & Velury, 2004) studied the relative value relevance

of disaggregated components of earnings on the corporate life cycle. Sales growth is

more value relevant during the growth phase of the firm as compared to profitability.

The relevance value of profitability is found to be higher in the mature stage of firm

life cycle. The search for appropriate measure of firm performance namely reported

earnings or realized cash flows has been a subject matter of research in this domain.

The relevance of performance measures is affected by performance measurement

interval, magnitude of the short-term working capital, environmental stability and

length of operating cycle. The study by Dechow (1994) suggested that accruals are a

better measure of firm performance in case of the shorter measurement interval. The

shorter the performance measurement interval, higher would be the timing and

matching problems with cash flows. Cash flow as a measure of performance doesn’t

include the short-term working capital; it however includes the longer term operating

accruals. The more stable the environment of the firms, lesser would be the random

fluctuations in the cash flows making accruals a better measure of firm performance

in the volatile environments. Length of operating cycle also affects the usefulness of

23

the earnings and cash flows as the summary measure of t firm-performance. Longer

operating cycles lower the usefulness of cash flow as a measure because of the higher

volatility of the working capital needs. Thus, many benefits accrue due to accrual

accounting, which addresses the reliability, and relevance trade off between realized

cash flows and reported earnings as performance measurement tools. However, the

research reports a decrease in the value relevance of reported earnings, cash flows and

book values due to the rapid changes in the businesses with major driver of change

being the intangible assets (Lev & Zarowin, 1999). The decline in the usefulness is

less pronounced in the case of cash flows as the cash flows are immune from the

effect of change related items and also the managerial manipulation. 10

Anthony & Ramesh (1992) studied that the stock markets response as measured by

cumulative abnormal returns (CAR) to the two fundamental accounting performance

measures namely unexpected sales growth and unexpected capital expenditure

decreases linearly from growth to the stagnant stage of firm life cycle. Guay, Kothari,

& Watts (1996) explored the variability and correlation between the various earnings

components and suggested that accruals are affected by the firms’ stage in the life

cycle. The time series analysis of ratios as the predictor of future documents the

evolution of ratios over time (Nissim & Penman, 2001). Residual earnings valuation

techniques are based on the financial statements number and fundamental analysis to

help in the equity valuation. Financial Statement informativeness about the firm’s

cash flow generating ability differs during the firm’s life cycle hence the earnings

response coefficient also varies with the firm life cycle (Kothari, 2001). Empirical

research focusing on the impact of mandatory auditor rotation on the earnings quality

10

See Jones (2003) for the vale relevance trends in Australia where Accounting

standards allow for the capitalization of R&D expenditure. Results were consistent

with the U.S. study, however the relationship was found to be steadier.

24

suggests that longer the tenure of the auditors, lesser the dispersion as well as

magnitude of the income decreasing as well as income increasing earnings

management (Myers, Myers, & Omer, 2003). The arguments in the favour of

mandatory auditor rotation suggest that as the auditors’ tenure increases in a firm the

auditors become complacent. The auditors with longer tenure do not effectively

constrain the managers in making the self-serving decisions regarding the financial

statements. The arguments opposing the motion suggest that with the passage of

time, the auditors gain firm specific expertise by understanding the intricacies of the

business, hence leading to a higher auditor quality. This suggests that accruals differ

with changes in firm life cycle. In the growth phase the pattern of accruals is distinct

from the mature or decline phase. Specifically, McNichols (2000), examined the

relationship between earnings management as proxied by discretionary accruals and

the growth of the firm as measured by earnings growth. The findings from the study

indicated that growing firms are expected to have higher discretionary accruals than

the lower growth firms, hence suggesting higher earnings management by the higher

growth firms. Comparative study (Madhogarhia, Sutton, & Kohers, 2009) between

the earnings management practices between value firms and growth firms, indicate

that the growth firms indulge more aggressively in both positive and negative

earnings management as compared to the value firms. Intuitively, firms in the growth

phase face higher need of the investment in the inventories and production process,

resulting into higher working capital accruals. Apart from the perspective of increased

investment in the working capital in the growth phase, the higher information

asymmetries in this phase also advocate the presence of higher amount of earnings

management in order to meet the earnings targets. These arguments lead to the

formulation of following hypothesis:

25

H1 (a) Earnings management, as measured by discretionary accruals quality in

growing firms is positive and higher than mature firms.

In case of declining firms, these firms decline on two fundamental accounts: financial

and human resources. The decline in the financial resources is connected to declining

profitability, cash reserves and borrowing capacity (D’aveni, 1989). The author also

suggested that the timing of consequences of decline also vary among firms. Hence,

firms might not exhibit the characteristics pertaining to organizational decline just

before the bankruptcy; rather they might linger in the post decline phase for several

years. The study by DeFond & Jiambalvo (1994) suggests that managers indulge in

manipulating the earnings via total accruals and working capital accruals in a year

prior to the covenant violation as well as in the year of violation. The analysis uses the

debt to equity ratio as the proxy for tightness of restrictive covenants after controlling

for management change (managers’ choices for estimating bad debt expanse,

inventory obsolescence and timing of sales) and the auditors’ going concern

qualification. The results (with both time series (Jones 1991) and cross- sectional

models) concluded that the firms indulge in income increasing (positive) accruals in

the year prior to the covenant violation. However, the accruals were reported

significantly positive in the year of violation after controlling for the management

change and the auditors’ going concern qualification. On the contrary, the firms

facing more permanent financial distress and expecting the debt contract renegotiation

after denial of the waivers are more likely to indulge in income decreasing earnings

management so as to negotiate better terms of debt (Jaggi & Lee, 2002). Thus, we

formulate the next hypothesis:

H1(b) Earnings management, as measured by discretionary accruals quality is higher

and negative (income decreasing) in declining firms than mature firms.

26

2.2.2 Earnings Management and Capital Structure

The extant literature on the relationship between the earnings management and capital

structure presents two differing strands of the influence of debt on the quality of the

reported performance parameters. The first strand of research emphasises on the role

of debt in signalling the quality of management by decreasing the incentive problems

using possibility of bankruptcy as a disciplinary tool. Debt financing in the capital

structure also signals pre-commitment or bonding behaviour of the managers resulting

in an increase of firms’ market value. Presence of debt in the capital structure, acts as

a disciplinary tool for the agents, thus improving the quality of management and also

the demand for higher quality of accounting information (Grossman & Hart, 1982).

However, another strand of research suggests that the presence of debt in the capital

structure motivates the managers to manage the reported earnings upwards. Debt

covenant hypothesis states that the extent of earnings manipulation increases with the

amount of debt in the capital structure as managers try to avoid the covenant

violations, as the cost of default is very high (Beneish & Press, 1993; Chen & Wei,

1993). Watts & Zimmerman (1990) suggests that a high level of debt financing has a

negative influence on the earnings quality as the presence of debt on the balance sheet

motivates the managers to manage earnings upward so as to avoid the debt covenant

violations. However, recent empirical research by Ghosh & Moon (2010) suggest that

the earnings quality as measured by accruals quality follows a non-monotonic

relationship with debt financing. The earnings quality first increases with the amount

of debt and then, after an inflection point at 41% debt in the capital structure, the

accrual quality decreases with the increase in debt. Hence, confirming the presence of

two competing perspectives on the relationship between the debt and earnings quality.

One perspective suggests that the managers use the quality of earnings to signal the

27

future potential of the firm in order to reduce the cost of debt resulting into a positive

relationship. Another perspective suggests that high financing firms manage the

accruals thus decreasing the accruals quality to avoid the covenant violations resulting

into negative relationship. Small and large firms differ on informational asymmetry,

which in turn affects the financing decisions of the firm. Carter (2013), presents two

streams of literature establishing the relation between capital structure and

information asymmetry. Pecking order theory suggests that as the informational

asymmetry decreases the leverage also decreases. However another strand of

literature suggests that the decreased information asymmetry leads to weaker debt

covenants and noisy equity prices. Although growth is negatively related to the long-

term debt, the short term and convertible debt acts as a substitute for the longer-term

debt in growing firms, thus indicating higher leverage in the growing firms (Titman &

Wessels, 1988). Additionally, raising capital through equity financing is far more

costly for smaller firms than the large firms, thus suggesting the smaller firms to be

highly levered (Myers, 2001). Consequently, we formulate the following hypotheses:

H2 (a) Earnings management, as measured by discretionary accruals quality is

positively related to the proportion of debt in growing firms.

H2 (b) Earnings management, as measured by discretionary accruals quality is

negatively related to the proportion of debt in declining firms

28

2.2.3 Capital Structure and Financial Distress

Research on the effect of capital structure on financial distress indicates that

presence of debt plays a significant role in ascertaining the financial health of the

firm. Ohlson (1980) in a research predicting bankruptcy suggested that financial

structure along with the firm size, measures of performance and measures of

liquidity affects the probability of failure of the firms. The research (Opler &

Titman, 1994) testing the empirical relationship between the firm performance,

leverage and distressed industrial environment indicated that a firm with high

leverage suffers a higher decline in the sales at the time of industry wide downturn

(distressed industry). Capital structure of the firm also impacts the creditors’

perspective in terms of decisions for granting waivers. The empirical findings

suggest that firms with higher probability of bankruptcy and higher leverage are

less likely to get the waivers. In terms of debt structures, smaller and secured debt

increases the probability of getting waivers (Chen & Wei, 1993). Among the

fundamental theories of capital structure, trade off theory posits that firms

maintain debt levels after taking into account the benefits (tax-shield) and costs

(possibility of financial distress) of leverage. Hence, higher the proportion of debt

in the capital structure greater is the possibility of financial distress. The capital

structure varies with the firm size as the informational asymmetry is considered to

be lower in the larger firms, hence have lower debt, making size as an inverse

proxy for probability of default. The effectiveness of bankruptcy as a disciplinary

device in the agency relations is dependent upon the presence of debt in the

capital structure. Debt acts as a signal for quality of firms’ management, hence

increasing the firm value, which in turn increases the agent’s perquisites

(Grossman & Hart, 1982). Thus we formulate the following hypotheses:

29

H3 (a) The financial distress is positively related to the proportion of debt in growing

firms.

H3 (b) The financial distress is positively related to the proportion of debt in the

declining firms.

2.2.4 Earnings Management and Financial Distress

Prior researches on the linkage between earnings management and financial distress

indicate that the managers’ decisions pertaining to the income decreasing or

increasing activities are a function of the financial health of the firm. Research by

DeAngelo, DeAngelo, & Skinner (1994) focuses on analyzing the accounting choices

of the managers’ of firms facing persistent financial troubles namely dividend

reduction and persistent earnings losses. The firms reported high negative accruals

after the dividend reduction, which is significantly contributed by inventory decline

followed by non cash-write off etc. The income decreasing choice of the managers

can be explained by increased monitoring by auditors, lenders and also to strengthen

the firms’ position in the negotiations with the union and the government agencies.

Hence the managers’ choice to manage accruals is primarily motivated by the

financial stability of the company. Various other motivations for the managers to

manipulate the earnings are concealing weak performance, avoidance of debt

covenant violations, reducing probability of future default etc. (DeFond & Jiambalvo,

1994; Jaggi & Lee, 2002). The severity of financial distress also impacts the

managerial accounting choices in terms of income increasing and income decreasing

accruals management (Jaggi & Lee, 2002). The firms facing temporary financial

distress and expecting to receive the waivers on debt covenant violations are more

likely to indulge in income increasing accruals management so as to signal the

creditors about the improving financial health of the firm. On the contrary, the firms

30

facing more permanent financial distress and expecting the debt contract renegotiation

after denial of the waivers are more likely to indulge in income decreasing earnings

management so as to negotiate better terms of debt. The objective of earnings

management differs for the two sets of firms thus resulting into different approaches

to earnings management. However, the results of studies on the managerial

accounting choices in the distressed firms are mixed i.e. income increasing, income

decreasing and no effects. Hence we formulate the following hypotheses:

H4 (a) Earnings management as measured by discretionary accruals quality is

positive (income increasing) and is positively associated with the level of financial

distress in growing firms.

H4 (b) Earnings management as measured by discretionary accruals quality is

negative (income decreasing) and positively associated with the level of financial

distress in declining firms.

31

2.3 Research Gap & Theoretical Model

The context relating to the increased accounting frauds and sparse literature on the

role of discretionary accruals and leverage in signalling the early stage of distressed

financial health of the firm provides us with an opportunity to undertake the present

research. Hence, the present study fills the gap in the literature by analysing the effect

of earnings management and capital structure on the financial health of the firms

considering the firm life cycle perspective.

Figure 1: Theoretical Model

Capital Structure

Earnings

Management

Financial Distress

H2

H4

Firm Life Cycle

H3

H1

32

2.4 Empirical Models

Table: 2 Empirical models under study

S.No. Research

Question Empirical Model

RQ.1

Discretionary

Accruals &

Firm Life

Cycle

DIS_AQi,t

= β0+β

1GrowthDummy

i,t+β

2DeclineDummy

i,t

+β3FirmSize

i,t+β

4FirmPerformace

i,t+ϵ

RQ.2 Discretionary

Accruals &

Debt

Financing

DIS_AQi,t

=β0+β

1Debt

i,t+ β

2 (Debt)

2

+ β5FirmSize

i,t+

β6FirmPerformance

i,t+ϵ

DIS_AQi,t

=β0+ β

1GrowthDummy

i,t+β

2DeclineDummy

i,t +

β3Debt

i,t+ β

4Growth Dummy

i,t * Debt i,t +

β5DeclineDummy

i,t* Debti,t + β

6FirmSize

i,t+

β7FirmPerformance

i,t+ϵ

RQ.3 Distress

Score;

Discretionary

accruals;

Debt; Firm

life cycle

ZScorei,t+1

= β0+β

1DIS_AQ

i,t+β

2Debt

i,t+β

3Growth

Dummyi,t

+β4DeclineDummy

i,t+β

5FirmSize

i,t+

Β6FirmPerformace

i,t+ϵ

ZScorei,t+1

= β0+ β

1GrowthDummy

i,t+β

2DeclineDummy

i,t

+ β3DIS_AQ

i,t+β

4Debt

i,t + β

5DIS_AQ

i,t * Growth

Dummy + β6DIS_AQ

i,t * Decline dummy + β

7Debt

i,t *

Growth Dummy + β8Debt

i,t * Decline Dummy

β9FirmSize

i,t+β

10FirmPerformace

i,t+ϵ