15030425

SCIENCE ROAD JOURNAL

Corresponding Author: Sanaz Hadji Email: [email protected] Acceptance Date: 02/28/2015

255

SCIENCE ROAD

Journal

Year: 2015 Volume: 03 Issue: 04 Pages: 255-267

Sanaz Hadji PhD Student of Accounting, Faculty of Management and Accounting, Semnan branch, Islamic

Azad University (IAU), Semnan, Iran

Concentration on Industry, Homogeneity in Industry and Strategic Competition and

Earning Predictability

Abstract:

The environment in which the Company is active could potentially have positive or negative impact on the quality of earning.

For example, quick growth of technology in computer industry can result in increase of rare and useless goods. On the other

hand, change of technology is very slow in many industries. Thus change of technology is considered as an important factor to

assess the earning quality for these industries. That is why the companies that are active in the industries enjoying high

technological growth are more prone to face the issues of earning quality in comparison with the companies that are active in

the industries enjoying an almost fixed growth of technology. The results of the study show that there is no significant relation

between industrial concentration and earning predictability and describe that there is no difference between the existing

companies in the concentrated industries that keep protecting their competitive advantages and the other companies. Also

there is no significant relation between industrial homogeneity and earning predictability, and taking a certain level of industrial

concentration into consideration, there is no difference between the earning predictability of the companies that compete using

a pro-active strategy and the companies that compete using a passive strategy.

Keywords: Industrial Concentration, Strategic Competition, Competition in Product Market, Earning Predictability,

Industrial Homogeneity.



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1. Introduction

This study investigates the relation between dimensions of competition in product market and earning predictability

which is one of the criteria of income quality. Competitiveness of the market means that different companies

compete closely to produce and sell goods and their goods are not very much different from one another because

otherwise the market will be inclined toward exclusivity/multiple exclusivity [1]. Competition has three dimensions

of concentration on industry, homogeneity in industry and strategic competition in the product market and this study

investigates these three dimensions.

1.1. Concentration of industry and the quality of accounting information

Industrial concentration refers to the dimensions of distributing the size of company in one market or special

company which was used in the past to show the degree of competition in the market (Carranza, 2008. The structural

theory of the type of industry believes that the company's concentration in the market is one of the important

elements of the market structure and the factor to determine competition. According to this hypothesis,

concentration leads to reduced competition through increased behaviors accompanied by collusion. The high or low

industrial concentration leads to high or low level of competition if the other conditions are equal [2, 3 and 4] The

studies show that increasing concentration of the market is in connection with the unusual prices and incomes that

consequently lead to increased allocated costs of these companies. Ali Kalsa and Yeung [5]showed that the

companies that have high concentration in industries do not disclose their information completely not to provide the

rival companies with useful and strategic information in this way.

1.2. Industrial Homogeneity and Quality of Accounting Information

The industries that are formed by companies having very similar nature, technology and products are called

homogeneous industries. These industries are completely different from industries that are formed by very dissimilar

companies. The conducted studies regarding the industrial organizations show that for a certain level of

concentration in industry, the industries formed by similar companies have higher level of competition. Since

companies that are part of homogeneous industries have similar structural costs and sell similar products, if the

conditions are similar, the structures would be similar and they would sell similar products. In case of similar

conditions, competition in homogeneous industries is more tangible than non-homogeneous industries. Homogeneity

of industry shows the degree of shocking effect on an industrial environment for all the companies at a single time.

That is why it is easier for the similar companies' shareholders to regain information about the counter relations.

This information also helps the foreign investors who obtained information about the real environment of activity of

the companies and allows them potentially to organize the internal conditions of the company according to the

information. Parrino [6] showed in an experimental research that homogeneous industries have relatively organized

performance and the directors could easily identify the weaker organizations. This issue leads to increased turnover

of transactions by CEOs in that industry. Homogenous industries have information advantage for shareholders in

comparison with the industries that are formed by non-homogeneous companies; therefore, use of relative

performance evaluation (RPE) will be more effective and relative performance evaluation (RPE) leads to facilitating

the study of the directors' performance and that is why it leads to reduction of organizational costs and increased

quality of accounting information. According to Parrino's study, 1997, the criterion of this study for industrial

homogeneity is correlation among the yield of shares of the producing companies existing in Tehran Stock

Exchange Market. Selection of this criterion depending on changes in the price of shares is ordinary for criterion of

homogeneity in industry because the price of company's shares reflects the current value of the remaining cash

flows. Defond and Park [7] expressed direct evidences regarding relative performance evaluation affected by



257

competition of product market which in turn leads to the direct effects on the method of making transactions by the

senior directors. They particularly showed that there is a positive relation between the degree of transactions

turnover by the senior directors and the competition level in industry and indicated that relative performance

evaluation is a useful action in competitive industries and could be applied to many competitive industries. However

industrial concentration measures competition through market shares and calculates the industrial coordination and

competition using the degree of similarity of individuals' performance inside the market.

1.3. Strategic Competition Solution and Accounting Information Quality

In industries that have group exclusivity or multi-polar competition market, the companies' interests depend on the

reciprocal relation among companies necessarily and also as a general industry. Under such circumstances, the value

of the companies is not just the outcome of the company's performance, but performance is a set of options that are

provided by the rival companies [8] The companies could increase their strategic behavior under such

circumstances. These behaviors consist of activities that lead to create suitable response by the rival companies. The

strategic reciprocal relations among companies in the production market could be divided as the supplementary

strategic alternatives. The decisions of a company are called supplementary or alternative strategy when that

company adopts a pro-active strategy and is the one in line with proactive actions of the rival companies. This issue

increases or decreases the company's margin of profit. As a result, the companies that compete with each other by a

supplementary strategy have higher degrees of competition in comparison with the companies that adopt alternative

strategies [9] Without taking the reciprocal strategic effect into consideration, it is expected that the quality of

company's accounting information to be in connection with the degree of competitive relation among industries.

According to the previous topics when the degree of competitive relation in one industry increases or its intensity

goes up, the companies are subject to reduction of private, representative and political costs. Under such

circumstances, there is less incentive for the companies to create a non-transparent environment to prevent attracting

the attention of the rival companies and political sanctions. Reduced representation costs should appear in the

quality of the presented financial information by the relevant directors [10]

1.4. Reciprocal Relation between Industrial Concentration, Industrial Homogeneity and Strategic

Competition

The above items studied the effect of the individual dimensions of competition on the quality of accounting

information and paid no attention to the existing relation among different dimensions. Industrial concentration and

homogeneity both calculate competition according to the structure of the companies' market in industries. Industrial

concentration particularly connects competition to market shares. While the industrial homogeneity connects

competition to the performance environment of the company, strategic competition calculates the competition

according to the reciprocal relation of the companies that are active inside the market. Strategic competition

calculates competition on the basis of reciprocal relations of the companies inside the market. The companies can

take action at a certain level of industrial concentration in a completely similar and or different way as far as cost

structure is concerned and could take pro-active or compromising actions against the measures adopted by the rival

companies [11] According to the effect of competition on the private, representative and political costs at a certain

level of industrial concentration, it is expected that the accounting information have high quality in homogeneous

industries in comparison with non-homogeneous industries. At the same time, it is expected at a certain level of

industrial concentration that the quality of the accounting information of the companies that have supplementary

strategies to be higher than their sample in the companies that have alternative strategy.



258

1.5. Methods to assess the earning quality

Generally speaking, there are four methods to assess the earning quality as follows:

1. Method based on relation with value of shares: In this method, the relation among different amounts of earning

and the price of shares (market) is measured using regression. The more the degree of adjusted correlation

coefficient is, the more the earning variable becomes dependent on value (Barth et al, 2001).

2. Method based on information content: In this method the relation between price changes and shares yield, the

unexpected levels and changes of different amounts of earning are measured using regression. The closer the amount

of adjusted correlation coefficient is to 1, the heavier information load it indicates.

3. Method based on predictability: In this method the important thing is that the old amounts of earning could

predict the future amounts. The less the amount of average absolute value is, the more its predictability will be.

4. Method based on economic profit: In this method the criteria based on prediction of capital costs are mainly

considered. It is understood that these figures have higher quality in comparison with the accounting profit. The

criterion of economic added value is one of the criteria that relies on this method [12]

1.6. Earning predictability

The expected future earning prediction on the basis of information content of old earnings depends on the fact that

how much the old earnings are stable. Stability of the old earnings means that it is predicted that the old earnings

also happen in the future. Changes in earning are interpreted as the index of sensitivity. Index of sensitivity is a

share of the sustainable changes of earning that could be 100%, between 0 and 100% and bigger than 100%. Thus

the degree of relevance of the old earnings to the future earnings depends on stability of earnings. If the users are

successful to differentiate the stable and unstable parts of the earnings, they will most likely predict the future

earnings well and in this way prediction will be useful for the users. Many factors could change the trend of

earnings. For example, inflation increases some costs such as wages, materials and incomes, but it has very low

effect on some costs and incomes such as depreciation costs and income of the interest of government bonds [14]

Authorization of accountants to use the different accounting procedures is considered as another factor to change the

future earnings considering the temporal conditions and the direct impact of accounting principles and methods on

measurement of earning. Change of rules and regulations has a type of unpredictable change on the effective rules

and regulations on commercial units and has impact on the activity of commercial units. Also directors have

different ways of thinking. Every director runs the company according to his own knowledge and way of thinking.

Hence there is a direct relation between the activity of commercial units and their knowledge, way of thinking and

management ideas and management change leads to change in the structure of incomes and company's costs [15]

Also change in the combination of the board of directors could also affect the activity of the company and its

competition in the product market [16]Unexpected incidents usually affect the ordinary and current operation of the

companies due to the impact on commercial environment in addition to imposing direct costs resulting from them.

One of the criteria to asses accounting information is usefulness in prediction that depends on experimental

researches. On this basis, accounting measurements are assessed considering their predictability for the user. Most

of the accounting discussions aim at choosing one measurement method about logicality of a method in comparison

with the other methods. But logical discussions are not sufficient on their own to choose a method. Many articles

paid attention to this point and called for experimental studies in accounting. Although all of them stress on

experimental studies to draw a link between assessment criteria and accounting goals, inability to determine the

nature of the experimental study is one of the deterrent factors. Also there are problems when it comes to

implementing them such as determination of the events that form the specifications of the decision-making model



259

and theoretical specifications so that it is one of these problems to correspond with a type of relation to predict the

accounting criteria. The results of the study regarding the usefulness criterion to predict depend on recognition of

the prediction model. Presentation of a prediction model requires to determine the type of relations and to define

variables which are other executive problems. Earning assessment in prediction requires taking loss from prediction

error into consideration which also depends on awareness of other variables of decision-making model [17]

Thus, different measurement methods are assessed according to their ability and capacity to predict the desirable

incidents and attention of the decision-makers. In other words, the methods that have the highest capacity to predict

regarding one incident are considered as the best method for that specific incident.

1.7. Research History

No study was conducted in Iran so far to investigate the relation between competition in the product market and

earning predictability. Thus a brief mention of relevant foreign researches is made as follows:

Lafond and Watts, [17] used study and review of the old earnings during time in their study to predict the future

earning and believed that the only way to predict earning is to use the average old earnings and this idea was paid

attention to by the other researchers, and acceptable models were also presented in this area.

Ball and Shivakumar, [18] conducted their study in the area of profit and price of shares and found out that the price

of shares are affected by the changes of predictable earning and this effect has direct relation through predicting the

earning of 100 companies recognized by New York Stock Exchange Market.

Hayes [19] studied the predictability of the accounting data in form of ratio with regard to the changes of incidents

on rate of government bonds to determine the rate of newly-issued government bonds. The experimental part and the

studies required collecting data from organizations that are capable to reimburse the loan on the date of maturation

and also the organizations that do not have this ability. The ratio of debts over properties of each organization was

calculated and the objective was to find out which of these calculated ratios predict the situation of the organizations

better. Then classification of each case was compared with the actual situation of the organization as far as inability

to pay at due date was concerned and the percentage of wrong predictions was specified. The lower the degree of

error is, the higher the power of prediction will be and the adopted method that leads to the lower percentage of error

will be considered as the better method to predict the non-payment of loan on the due date.

Lang et al [20] found out in their studies that apart from the time series of the old earnings, other information such as

newly issued rate of government bonds and the ratio of debts to properties of each organization could be effective to

predict the future profits, but in case the other information is not accessible, the old earnings are the best parameter

to predict the future earnings of the commercial units. Thus in the current study, the old earnings of the companies

recognized by Tehran Stock Exchange Market were used to predict their future earnings.

2. Research Hypotheses

Considering the theoretical grounds and conducted studies, the research hypotheses are presented as follows:

First hypothesis: There is a significant relation between level of concentration in industry and earning predictability.

Second hypothesis: There is a significant relation between industrial homogeneity and earning predictability.



260

Third hypothesis: There is a significant relation between strategic competition and the relation between industrial

concentration and earning predictability.

3. Research Method

This goal of this study is of applied type and it is descriptive-correlative as far as its nature is concerned. In this

study combined data method was used due to the type of the data under study. The method of combined data is a

method to consolidate sectional data and time series. Firstly F-Limer test was used in combined data to select

between panel data and consolidated data. If the calculated F-Limer is smaller than the F-Limer in the table, panel

data are used, otherwise, consolidated data will be used. If the probability of Hausman test is less than 5%, H0

(random effects) is rejected and fixed effects are selected. If the probability of Hausman test is higher than 5%, H0 is

not rejected and random effects are selected. According to the results of F-Limer test and Hausman test, regression

method was selected. If panel data method is used, when the number of the companies is higher than the number of

periods, the models might face the problem of variance anisotropy. In order to remove this problem, generalized

least square (GLS) regression method is used to estimate the model. Further on for each of the hypotheses, F-Limer

test and Hausman test were conducted separately and the results of the regression were analyzed by t statistic, t

probability and F statistic and its probability and determination coefficient.

3.1. Statistical Society and Sample

The statistical society of this study is all the companies recognized by Stock Exchange Market. Since the studied

variables were considered in the recent 7-year trend, all the companies recognized by Stock Exchange market are

part of the statistical society of this research. In this study, systematic elimination method was used for sampling.

For this purpose the companies in question were selected according to the following criteria:

1. To be present in Stock Exchange Market from March 2006 to March 2013.

2. The relevant information to the selected variables to be accessible in this study.

3. In order to compare the information, the fiscal year of the companies should end on 20 March of each year.

4. The transaction of their shares should not have stopped during the research period more than three months in

Tehran Stock Exchange market.

5. They should not have more than 3-month transactional stop during the timescale of the research in each year.

6. Their activity should be of producing type in order to maintain homogeneity of information.

Considering the above conditions and restrictions, the total number of 90 companies was selected among the

recognized companies by Tehran Stock Exchange Market. In order to conduct the statistical tests, Stata statistical

software was used to estimate the coefficients, to statistically analyze the required amounts such as t and F tests, to

estimate the parameters of regression equations, correlative coefficients, etc.

3.2. Used Models

To test the research hypotheses in connection with the effect of different dimensions of competition in the product

market on the quality of income, the following experimental model was used:



261

In the above formula, EQit as the dependent variable represents the quality of the j company's income in t year that

will be presented by earning predictability. COMPETTTIONit variable will be presented by different dimensions of

competition which will be presented for COMPETITIONit first hypothesis by concentration coefficient of the (HI-

CENSUS ( industry and for the second hypothesis by industry homogeneity, i.e., HOMOGENEITY. In order to

determine the income quality, several control variables were added to the above formula that is presented in table 1.

Also the following model is used for strategic competition:

In this formula, the variables of the test are HI-CENSUS and CSMD and interactive variable is HI-CENSUS and

CSMD. CSMD is equal to one when the company competes with passive strategy and it is equal to zero when it

competes with a pro-active strategy

4. Research Variables and Method to assess them

4.1. Earning predictability

The old earnings can predict the future earnings with the least possible error and the performance of the earnings has

positive relation with the predictability of the constituents of the earning and their continuity. In other words, those

earning constituents that have more continuity or have higher quality could predict the earnings in a more suitable

way [21] the criterion of this study is extracted from AR1 models of every year of the company in connection with

the earning predictability. Also the second root of the changes in variance was used in the formula and then it was

multiplied by -1 to extract the measurement criterion of the earning predictability. The bigger (smaller) amounts

indicate the higher or lower predictable earnings and the model is as follows:

2

, TJLITYPREDICTABI

4.2. Industrial Concentration and Homogeneity

The industrial concentration was measured using Herfindahl index which is equal to the total squares of the market

share of all the existing companies in the market which is calculated by using Herfindhal index formula as follows:

(4)

Homogeneity means the average partial correlative coefficient (rRj,t , Rit/Rmt ) for all the existing companies in the

industries active in Tehran Stock Exchange Market which were calculated through the following regression.

EQit=b0+b1SAZEit+b2σ(CFO)it+b3σ(SALES)+b4OPCYCLEit+b5NEGEARNit

+b6LEVERAGEit+b7MBit +b8COMPETTTIONit+eit

1)

3)

EQit=b0+b1SAZEit+b2σ(CFO)it+b3σ(SALES)+b4OPCYCLEit+b5NEGEARNit+b6LEVERAGEit

+b7MBit +b8HI-CENSUSit+b9CSMDit+b10CSMD*HI-CENSUSit +Yr-Dummiesit+Ind-Dummiesit +eit 2)

2

1/

n

J jji XXHI



262

(5)

The partial correlative coefficient r Rj,t , Rit / Rmt measures the intensity of the linear relation between the company's

yield and the industrial yield following control regarding the effect of market yield. The high quantity of

HOMOGENEITY indicates the higher homogeneity of the existing companies in one industry.

4.3. Table to introduce variables

Table 1-Definitions of the used variables in models

Model variable Type Remarks

Main

SAZE Independen

t Natural logarithm of total properties of i company in t yea

σ(CFO) Independen

t

Criterion deviation of operational cash flows of company in the past 7 years in t

year

σ(SALES) Independen

t Criterion deviation of sales in the past 7 years in t year

OPCYCLEit Independen

t

Logarithm of total days to receive receivable accounts of the company and the

time for the goods inventory to wait for t year.

NEGEARNit Independen

t Ratio of the Company's loss in the past 7 years for t year

LEVERAGEi

t

Independen

t

Logarithm of the total long-term and short-term debts of the company divided by

value of its shareholders' equity in t year.

MBit Independen

t

Market value of company's capital divided by book value of its shareholders'

equity in t year.

4 Xi Independen

t Sale of j company in I industry and no companies are in this industry

5

Rjt Dependent Yield of j company's shares in I industry for t month

Rmt Independen

t Rhythmical mean of yield of market shares in t month

Descriptive Statistics

Rjt=b0+b1Rit+b2Rmt+eit



263

Table 2-Descriptive statistics of research variables

Criterion

deviation Mean Maximum Minimum Quantity Sign Variable name

12009.68893 990.2023397 0.034788789 177855.1352 630 EPre Earning predictability

0.072869169 0.078464685 0.27237496 0.00152262 630 ICON ]Industrial

concentration

0.395405187 0.140813366 3.424 0.7299- 630 IHOM Industrial homogeneity

0.665501054 5.676100393 8.476334278 4.244994166 630 SIZE Size

1.47835E+12 1.90108E11+ 2.64004E13+ 6480.25 630 CFO Operational cash flows

2.75186E+13 3.81259E12+ 4.10522E14+ 14762.25 630 SALES Sale

0.642193873 2.98411356 6.328613222 1.184280333 630 OPCYCLE Operational cycle

0.50271298 0.335580311 6.763607829 5.7417E-05 630 NEGEAM Loss ratio

0.385202599

0.382384445

2.280966211

1.209162311

630 LEVERAGE Market lever

6.34864272 4.129672125 78.17577301 4.129672125 630 MB

Ratio of market value

on book value of the

shareholders' equity

In order to present a general view of the important characteristics of the calculated variables in table 1, the number

of observations, mean, criterion deviation, maximum and minimum of the observations were provided.

4.4. Test Results of the first research hypothesis

The results from the statistical analysis of the first research hypothesis are shown in table 3:

Table 3-Results of statistical analysis of testing the first research hypothesis

F

R2

Co

ns

MB

Lev

erage

Neg

earn

Op

cycle

Sales

Co

f

Size

Icon

Pro

bab

ili

ty o

f

Hau

sma

n test

Pro

bab

ili

ty o

f F-

Lim

er

test

Sign

09

/0

12

/0

02

2/

0

96

8/

0

77

4/

0

40

8/

0

96

7/

0

93

1/

0

95

5/

0

00

1/

0

67

/1

07

1/

0

06

/0

00

0/

0

Earning

predictability

Insig

nifican

t

-

Sig

nican

t Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Sig

nifican

t

Insig

nifican

t

Ran

do

mly

fixed

Pan

el

Considering the results reflected in table 3, the obtained results of estimation of regression model toward panel data

method-fixed effects show that there is not a significant relation between dependent variable of earning



264

predictability and independent variable of main concentration level in industry. The amount of probability of this

relation (sig) is 0.09 which is not significant by 95% certainty. Regarding control variables, also the relation

between size and earning predictability variables is significant by 95% of certainty. As the results reflected in table 3

show, the calculated F is bigger than the F in the table (p<0.05). Thus it could be said that this regression model is

significant with 95% probability. In other words, this model is highly valid and the determination coefficient shows

that 12% of the amounts of dependent variables are explained by the independent variables.

4.5. Test of the second research hypothesis

The obtained results of statistical analysis of the second hypothesis of the study are shown in table 4. Considering

the results reflected in table 4, the obtained results of estimation of regression model in panel data method-random

effects show that there is not a significant relation between dependent variable of earning predictability and

independent variable of main industrial homogeneity. The amount of probability of this relation (sig) is 0.989 which

is not significant by 95% certainty. Regarding control variables, the relation between no variables and earning

predictability is not significant by 95% of certainty. As the results reflected in table 4 show, the calculated F is

bigger than the F in the table (p<0.05). Thus it could be said that this regression model is significant with 95%

probability and the determination coefficient shows that 1% of the amounts of dependent variables are explained by

the independent variables.

Table 4-Results of statistical analysis of testing the second research hypothesis

F

R2

Co

ns

MB

Lev

erage

Neg

earn

Op

cycle

Sales

Co

f

Size

Icon

Pro

bab

ili

ty o

f

Hau

sma

n test

Pro

bab

ili

ty o

f F-

Lim

er

test

Sign

98

9/

0

01

/0

39

3/

0

95

9/

0

75

8/

0

43

5/

0

97

3/

0

9/0

43

8/

0

64

5/

0

69

/0

49

1/

0

94

6/

0

00

0/

0

Earning

predictability

Insig

nifican

t

-

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t In

sign

ificant an

t

Insig

nifican

t

Insig

nifican

t

Ran

do

m effects

Pan

el

4.6. Test of the third research hypothesis

The obtained results of statistical analysis of the third hypothesis of the study are shown in table 5.



265

Table 5-Results of statistical analysis of testing the third research hypothesis

F R2

Co

ns

MB

Lev

erage

Neg

earn

Op

cycle

Sales

Co

f

Size

Icon

S

com

Hau

sman

test Po

ssiblity

of F

-

Lim

er test

Sign

99

2/

0

01

/0

40

4/

0

89

2/

0

77

1/

0

42

3/

0

96

3/

0

91

1/

0

98

4/

0

67

8/

0

51

7/

0

96

/1

05

/0

08

7/

0

00

0/

0

Earning

predictability

Insig

nifican

t

-

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t In

sign

ificant

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t

Insig

nifican

t In

sign

ificant

Insig

nifican

t

اR

and

om

effects

Pan

el

Considering the results obtained from estimation of regression model in panel data method-fixed effects shown in

table 5, there is not a significant relation between earning predictability and independent variable of main strategic

competition. The amount of probability of this relation (sig) is 0.992 which is not significant by 95% certainty.

Regarding control variables as shown in table 5, the relation between no variables and earning predictability is not

significant by 95% of certainty. As the results reflected in table 5 show, the calculated F is bigger than the F in the

table (p<0.05). Thus it could be said that this regression model is significant with 95% probability and the

determination coefficient shows that 1% of the amounts of dependent variables are explained by the independent

variables.

5. Results of Testing Research Hypotheses

The first hypothesis expresses that "There is a significant relation between the concentration level in industry and

earning predictability ". The obtained results from the estimation of the regression model in panel data method-fixed

effects show that there is not a significant relation between dependent variable of earning predictability and main

independent variable of concentration level in industry.

The second hypothesis expresses that "There is a significant relation between industrial homogeneity and earning

predictability." The obtained results from the estimation of the regression model in panel data –random effects show

that there is not a significant relation between dependent variable of earning predictability and the main independent

variable of industrial homogeneity.

The third hypothesis expresses that "There is a significant relation between strategic competition and relation

between industrial concentration and earning predictability." The obtained results from the estimation of the

regression model in panel data method–fixed effects show that there is not a significant relation between dependent

variable of earning predictability and the main independent variable of strategic competition.

6. Conclusion

The main goal of this research is to test the effect of competition in the product market on income smoothing in

companies and it was conducted by a sample of companies recognized by Tehran Stock Exchange Market. The

results of the research showed that there is not a significant relation between industrial concentration and withheld



266

items. Furthermore, the existing companies in concentrated industries do not seek procedures leading to income

smoothing in order to protect their competitive advantages to select procedures or disclose them. Also there is not a

significant relation between industrial homogeneity and quality of withheld items. At a certain level of industrial

concentration, the companies that compete enjoying proactive strategy do not use income smoothing in comparison

with the companies that compete relying on a passive strategy.

The conducted studies are mainly concentrated on procedures to disclose the company and the company's mastery

mechanisms. The relation between competition in the product market and predictability in an environment like Iran's

economy has not been established and it was only taken into account in very limited cases foreign studies. In

addition, contrary to the former studies, the three dimensions of competition, i.e., concentration on industry,

homogeneity in industry and competitive strategy were used and their impact on earning predictability was tested.

Other characteristic of this study was its large volume and use of more variables as it could be said at the end that

the obtained results could be used in more cases. The objective of this study is to fill the above gaps through testing

the effect of competition on the product market which is tested through concentration on industry, industrial

homogeneity and the amount of competitive interactions over the quality of the companies' earnings.

The conducted study adds the new findings to the accounting literature and enriches it in two ways. Firstly, it is the

first study that has been conducted in an environment like Iran that provides evidences regarding the relation

between market competition and earning predictability. Secondly, the former conducted studies only used certain

levels of industrial concentration as a criterion for competition, while competition consists of several dimensions. In

this study the relation between competition and earning predictability on the basis of three dimensions of

concentration on industry, industrial homogeneity and strategic competition was investigated.

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