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Investigation of profit management in the companies accepted in Isfahan stock market.


In companies that continuously report profit, the fact that how much of the reported profit is real and how much of it is manipulated is interested by audits and investors. Real profit management is paraphrased as attempts for responding to economic conditions by management. Management of fake profit is a kind of accounting manipulation and utilization of principles and regulations of accounting which is carried out by managers in order to control profit as they like and they manage profit flow authentically [10]. Evidence shows that managers have motivations for reaching a particular profit (targeted profit) or going beyond that. But the fact that how much they are able to reach their goals is an issue. Professional managers and formulators of accounting standards claim that reaching targeted profit is difficult in this way [5]. According to this viewpoint, reaching or going beyond targeted profit can be a reason for applying profit management in companies [7]. Jenson [5] showed that managers, who reach profit thresholds, may have been involved in profit management. He believes that manipulation of profit is a widespread method used for achieving predicted figures and the results expected by capital market. He also proved that about one third of companies in the past two decades have been made to present revised statements and figures due to presenting manipulated statements and reports [7]. In the present research, managers' behavior throughout the years they exercise profit management was investigated. In other words, profit management level which is performed by managers during their profit chain was investigated. Profit chain is referred to years in which a company reports profit. It seems that managers use increasing profit management for reporting profit as a model with positive growth rate throughout the lifetime of their company [14]. A manger reports net profit in the form of an increasing earning chain and failure of this chain may lead to costs like losing fame and popularity and reduction in the company's popularity in capital market.

Research literature:

Dechu and Skinner [4] investigated profit management behavior in companies which had strong motivations for breaking profit chain pattern of the company but their research results did not indicate that how much and when managers tend to break their company's profit chain [5].

Bieti et al [2] proposed that mangers get involved in profit management when their companies are presenting successive reports of increase in profit. Furthermore, they stated that banks have longer profit chain and report fewer oscillations. Restaurants and food industry have increasing profit chain. In other words, they investigated profit chain in different industries [4].

Jenson [5] believes that mangers who have always achieved predetermined goals in profit must have used profit management. He states that the only way for achieving profit goals is that they should show figures in a way that they can cover the uncertainty present in their business [7].

Tan et al [13] investigated the reasons of using profit management. He states that some managers interpret accounting regulations in a special way which is to their benefit and therefore manipulate the reported profit. The present research results showed that managers are persuaded to use profit management due to reasons like increase in stock market price, increase in management reward, manager's occupational security and reduction in capital cost.

Mashayekhi et al [9] investigated the role of optional items in managing profit in Isfahan Stock Market companies and concluded that profit management had been conducted in the companies and managers had increased profit through increasing discretionary accruals when cash reduced due to weak performance of commercial unit [1].

Venous et al [14] investigated the smoothing of profit in Isfahan stock market using standard number 15 of investments accounting (which allows many methods for investments). Their results showed that although the mentioned tool had not been used widely, but smoothing behavior was observable in companies which reported profit through selling investments [2].

Theoretical framework and hypotheses formulation:

There is evidence that shows that managers of companies which have profit chain have some motivations for manipulating profits and avoiding from company profit chain breaking. For example, Beaty et al [2] found that companies with long profit chain had reported insignificant profit increase in many periods. They deduced that such small increases are due to managers' tendency for keeping profit chain [4]. Richardson et al [12] proved that companies with the most revisions in their reports were those companies which had longer profit chains. these studies show that managers have behaviors which verify the fact that they are aware of profit chain breakage [14]. Key et al [6] found that managers are able to predict profit chain breakage at least two years before that [8]. Therefore, it seems that companies get involved in increasing profit management several years before profit chain breakage. Research hypothesis is therefore as follows.


There is significant relationship between breakage in profit chain and profit management.

Profit management will affect both a period's operational net assets and the period profit. Therefore, if managers manipulate profits in every period optimistically and if they are not able to incorporate past period's impact in the present period, it is possible that they will not be able to maintain company's condition and profit at an acceptable level [14]. Consequently, increasing profit management cannot be steady and continuous application of this method will result in profit chain breakage. Bareton and Skiemo [1] stated that companies which have higher ratio of operational net assets to sales have lower flexibility for profit manipulation. They aimed to investigate why some companies do not succeed in achieving predicted figures. They assumed that possibly these companies have lost the ability of managing increasing profit and have used the mentioned ratio. Their results showed that the possibility of achieving profit goals in companies with higher ratio of operational assets to sales is less than other companies [3]. It seems that reduction of companies' accounting flexibility level will restrict profit management behaviors and directs them towards profit chain breakage point.

Profit chain breakage:

According to Oyang's definition [10], breakage in profit chain is an event in which a company cannot continue producing increase in net profit. Barton et al [1] believe that a company cannot maintain profit growth rate possibly due to restrictions arisen from reduction in accounting flexibility [14]. Following the above studies for measuring profit chain and incorporating it into hypotheses test model, net profit periodical variations were calculated and the periods in which these variations were negative were considered as profit chain breakage event period.

[DELTA]NIit = NIit-NI it-1

Method of estimating profit management level:

Adjusted model of Jones which was presented and tested by Koutari et al [7] was used for estimating profit management level. This method is based on estimating accruals and their separation into discretionary and non-discretionary parts in several steps and discretionary part of accruals reflect profit management level. According to Koutari et al [7] and Oyang [10], the following redression model is fitted.

TACC/[TA.sub.i,t-1] = [alpha]1 (1/T[A.sub.i,t-1] + [alpha]2 ([DELTA][] - [DELTA][]/[TA.sub.i,t-1]) + [alpha]3 ([]/[TA.sub.i,t-1]) + [alpha](ROA) + [[epsilon]]


TACC: total accruals

DeltaREV: change in sale income in comparison with previous period

DeltaREC: change in accounts receivable in comparison with previous period

PPE: sum of assets, machinery and equipment

ROA: assets yield (ratio of net profit to assets book value)

TA: sum of assets book value

The following relationship was used to calculate total accruals (TAC)

TACC = (DCA - DCash) - (DCL - DSTDebt)

DCA:change in current assets

Dcash: change in remaining cash

DCL: change in current liabilities

DSTDebt: change in short-term received loans

Non-discretionary accruals part is independent of decisions and estimations and is affected by sale growth. In the above relationship, change in receivable accounts was subtracted from sale growth. This helps neutralize influences of sale growth through giving credit to customers [3]. After fitting the above regression model, coefficients obtained from regression are incorporated into the relationship for estimating level of discretionary accruals.

[] = [[??].sub.1](1/[TA.sub.i,t-1]) + [??]2([DELTA][] - [DELTA][]/[TA.sub.i,t-1]) + [??]3([]/[TA.sub.i,t-1]) + [??]4(ROA)

Finally, the following relationship is used for calculating non-discretionary accruals (Mousali et al, 2011).

DAC = [absolute value of TAC ([[]/[TA.sub.i,t-1]] - [NDA.sub.i,t])]

As the size of discretionary accruals (DAC) figure is larger, profit management level is higher [9]. Hypotheses test method

Regression models presented by Oyang [10] were used for testing hypotheses. A regression model was used for testing the first hypothesis in which profit management level was a function of breakage in profit chain and control variables [14].

EMi,t = a0 + a1 (PREBREAKi,t) + a2 (BEGSTRINGi,t) + a3 (SIZEi,t) +a4 (LEVERAGEAGEi,t) + a5 (BMi,t) + [mu]it

EM: level of discretionary accruals (profit management index)

PREBREAK: it is a virtual variable and if participation in the mentioned period is faced a breakage in profit chain, its value is 1. Otherwise, it will be zero.

SIZE: company size as a control variable (natural logarithm of sale income)

LEVERAGEAGE: financial leverage as control variable (ratio of total liabilities to assets)

BM: ratio of book value of equity to market value of distributed shares as control variable

The model of second hypothesis test is a regression model in which possibility of profit chain breakage is dependent variable and it is a function of accounting flexibility level and control variables.

Prob (BREAK) = [beta]0 + [beta]1 EMCi,t + [beta]2 EMCi,t-1 + [beta]3 SIZEi,t + [beta]4 LEVERAGEAGEi,t + [beta]5 GROWTHi,t + [beta]6ROAi,t + [beta]7BMi,t + [epsilon]i,t

Prob (BREAK): it is a virtual variable and if the company faces profit chain breakage in a period of time, its value is 1. Otherwise, it will be zero.

EMC: accounting flexibility level (ratio of operational circulating assets to sale)

Because the dependent variable of the above model is a variable with two cases (1,0), logistic regression was used for fitting.

Results of the first hypothesis test:

In the first hypothesis, it was predicted that there is relationship between breakage in profit chain and profit management. Regression model of this hypothesis test has some control variables which reflect companies statistical sample characteristics and are effective in explaining profit management level. Therefore, possibility of presence of colinearity among these variables is not unrespectable. Therefore, step-by-step method was used for fitting regression model of this hypothesis in which independent variables were incorporated into model and invalid variables were eliminated from the model and test output presents the most valid and most significant variables in the form of a regression model. Results of model fitting of the first hypothesis test have been listed in table 1.
F significance F statistic Durbin Watson Adjusted
level statistic r-squared

0.000 16.217 2.005 0.053

After fitting the model of the first hypothesis test, 4 variables which were presented in the above table were identified as valid and significant in step-by-step regression method and BEGSTRING variable was eliminated from the model. In the first part of table 1, results of regression model fitting have been presented. Results show that Durbin-Watson statistic is between 1.5 and 2.5, therefore there is no autocorrelation between regression model errors.

Results of regression variance analysis (ANOVA) for the fitted model of the first hypothesis which is studied based on F statistic has been presented in the last column of table 1. Statistical hypothesis related to F statistic analysis is as follows:

H0: [beta]i=0 regression model is not significant

H1: [beta]I[not equal to]0 regression model is significant

Significance level of F statistic is less than test error level (alpha=0.05). consequently, H0 is rejected and estimated models are statistically significant and the relationships between variables are linear.

Second part of the table 1 shows the results of statistical analysis for coefficients of independent variables of regression model. The results show the type, intensity, validity and significance of relationship between independent variables and dependent variables of the regression model. The results of co-linearity tests have been presented in the last two columns of the second part of the table. Co-linearity statistics for all variables are near 1 and show that there is not an intense co-linearity between independent variables of regression model. In general, results of the test indicate statistical validity of fitted regression model.

According to the results, estimated coefficient for PREBREAK variable which shows the impact of breakage in profit chain on management level of statistical sample companies, is 0.066 with significance level equal to 0.027. this is indicative of a direct and significant relationship between variables. In other words, according to the claim of the hypothesis and literature review, as possibility of breakage in profit chain increases, managers become more involved in profit management. Results of statistical analysis for control variables show that there is an opposite and significant relationship between financial leverage and company size and profit management level. In fact, companies with higher financial leverage and larger size have managed their profits less than other companies. This is while companies with higher ratio of book value to market value have excersized more profit management in financial reports. In general, results show that profit chain breakage has positive impact on profit management in sample companies and therefore, the first hypothesis of the research is verified in 95% certainty level.

Applied recommendations:

According to the results, it is advised to capital market investors to pay more attention to the evaluation of information environment of companies which have an increasing trend in their former reports. This is true for the companies which show small increase in reported profits and possibility of profit management must be considered seriously. It is also advised to investors to avoid such companies if they have long-term perspectives. It is advised to companies to be more conservative in reporting financial reports and limit increasing profit management, so that accumulation of outstanding accruals in financial statements and reduction of accounting flexibility is avoided.

Recommendations for future research:

1) formulation of new criteria for measuring flexibility level in accounting system of companies and its test in Iranian Stock Market Companies

2) investigation of relationship between accounting flexibility and companies profit quality

3) investigation of impact of accounting flexibility on performance criteria based on companies financial information

4) investigation of capital market response to profit chain breakage event.


[1.] Barton, J. and P.J. Simko, 2002. The balance sheet as an profit management constraint. The Accounting Review, 77: 1-27.

[2.] Beatty, A.L., B. Ke and K.R. Petroni, 2002. Profit management to avoid profit declines across publicly and privately held banks. The Accounting Review, 77: 547-570.

[3.] Dechow, P.M., R.G. Sloan and A.P. Sweeney, 1995. Detecting profit management. The Accounting Review 70: 193-225.

[4.] Dechow, P.M. and D. Skinner, 2000. Profit management: Reconciling the views of accounting academics, practitioners, and regulators. Accounting Horizons, 14: 235-250.

[5.] Jensen, M.C., 2005. Agency costs of overvalued equity. Financial Management, 34: 5-19.

[6.] Ke, B., S. Huddart and K. Petroni, 2003. What insiders know about future profit and how they use it: Evidence from insider trades. Journal of Accounting and Economics., 35: 315-346.

[7.] Kothari, S.P., A.J. Leone and C.E. Wasley, 2005. Performance matched discretionary accrual measures. Journal of Accounting and Economics., 39: 163-197.

[8.] Lee, C.J., L.Y. Li and H. Yue, 2006. Performance, growth and profit management. Review of Accounting Studies., 11: 305-334.

[9.] Mashayekhi, Beeta, Mehrani, Sasan, Mehrani, Kavhoukrami, Gholamreza, 2005. Role of discretionary accruals in managing the profits of Iranian Stock Market companies. Accounting and auditing studies quarterly, management faculty, Isfahan University, number 42

[10.] Ow Yong. K., 2011. PROFIT BREAKS AND PROFIT MANAGEMENT. Department of Business Administration Duke University.

[11.] Palmrose, Z. and S. Scholz, 2010. The circumstances and legal consequences of non-GAAP reporting: Evidence from restatements. Contemporary Accounting Research, 21: 139180.

[12.] Richardson, S., I. Tuna and M. Wu, 2002. Predicting profit management: The case of profit restatements. Working paper. University of Pennsylvania and Hong Kong University of Science and Technology

[13.] Tan, H-T., R. Libby and J. Hunton, 2007. When do analysts adjust for biases in management guidance? Effects of guidance track record and analysts' incentives. Working Paper. Nanyang Technological University.

[14.] Venous, Davar, Karami, Gholamreza and Tajeek, Kamran, 2006. Investigation of smoothing of profit in Isfahan Stock Market companies through accounting standard number 15. Accounting and auditing studies quarterly, number 43.

Esmaeel Eskandari

Payame Noor University, PO BOX 19395-3697, Tehran, IRAN

Corresponding Author

Esmaeel Eskandari, Payame Noor University, PO BOX 19395-3697, Tehran, IRAN

E-mail:; Tel.: +98-916-804-0630
Table 1: Results of statistical analysis for testing
the first hypothesis

Co-linearity tests Significance t-statistic
 level (P-value)
Variance Telurance
inflation factor

1.032 0.969 0.027 2.219
1.205 0.83 0.000 -4.676
1.206 0.829 0.001 3.443
1.017 0.984 0.008 -2.656

F significance F Durbin Adjusted
level statistic Watson r-squared

0.000 16.217 2.005 0.053

Co-linearity tests Standardized variable
 Beta value
Variance Telurance
inflation factor

1.032 0.969 0.066 PREBREAK
1.205 0.83 -0.151 LEVERAGEAGE
1.206 0.829 0.111 BM
1.017 0.984 -0.079 Size
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Title Annotation:Original Article
Author:Eskandari, Esmaeel
Publication:Advances in Environmental Biology
Article Type:Report
Geographic Code:7IRAN
Date:Aug 1, 2013
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