Analyst Coverage and Earnings Management: Evidence from China

1Zhao-hua Lan, 2Su-sheng Wang, 3Tao Yu, 4Zhen Yu Shenzhen Graduate School,Harbin Institute of Technology,Shenzhen, China ([email protected],[email protected],[email protected],[email protected])

Abstract - Besides information function, security rms from the financial industry are discarded by conventi analysts may play external supervision role in corporate on. Due to carrying out of new accounting principle in 1/ governance which has been verified in developed market. 1/2007, the sample starts from 1/1/2007, to 31/12/2010. Whether it is popular in China is unresolved. Nowadays, The sample consists of 953 firms. security analysts have become more and more important as intermediary in Chinese flourishing capital market. This paper study the relationship of analyst coverage and earnings management, trying to find direct evidence that To account for the effect of the type of actual controll security analysts’ coverage have restraint effect on er, which is specific and can affect both analyst follow an managers’ earnings management decisions. The empirical d earnings management in China, This paper control it (a result supports the opinion, and this paper contributes to dummy variable Control) in all tests. The controller infor the corporation governance theory and application. mation comes from Wind. The value of Control equals 1 when the firm is controlled by state or government, other Keywords - security analyst, analyst coverage, earnings s equals 0. Other variables, such as market value, return o management, corporate governance n net asset (ROE), the growth rate of asset, institution ow nership, also affect both analysts’ follow and earnings ma nagement. Furthermore, this paper uses the average value I. INTRODUCTION of tradable shares at the beginning and the end of the yea Jensen and Meckling (1976)[1] first point out that the sec r. For each firm, the average institutional holdings of four urities analysts’ activity can influence corporate governa quarters are adopted. nce . Moyer, Chatfield and Sisneros (1989) [2] make an e Table1 shows the summary statistics at the firm level. mpirical test about it based on Jensen and Meckling (197 The mean of Control is 0.68, indicating that more than ha 6). The result indicates that the higher degree of separatio lf sample is state-owned which is in line with reality in C n of ownership and control, the less demand for analysts hina. The mean logarithm of market value is 8.08, return follow. In the other hand, analysts’ coverage increase the on net asset is 9.51, growth rate of assets is 0.23 and insti firm’s value (Tobin’s Q) (Chung and Jo ,1996)[3]. tutional ownership is 31.11%, demonstrating the high gro Besides these indirect evidence, Dyck, Morse and Zin wth of capital market in China. gales (2008) and Yu (2008) found direct evidence about Table 1. Summary of Variables This table presents the summary statistics for the sample. The sample co analysts’ influence on corporate governance [4][5]. Anal nsists of all A-shares market in both Shanghai and Shenzhen security exchan ysts play an important role in discovering company's fina ge from 2007 to 2010. Control is a dummy variable, which indicates the actu ncial fraud, especially like Compaq, Motorola (Dyck , M al controller of a firm. LnMV is the logarithm of market value. Market value equals price multiply by the tradable stock. ROE is the return rate of net asse orse and Zingales, 2008)[4]. By studying the relationship ts, calculated by return scaled by net assets. GrowAsset represents the growt between analyst coverage and earnings management, Yu h rate of assets yearly. Institution is the value of institutional ownership, whi (2008) find that firms with more coverage manage their e ch is defined by the average institution holdings of four quarters. Number of Standard arnings less in developed capital market [5]. But whether Variables Obser- Mean Median Deviation it is true or not in China (flourishing capital market) is un vation resolved. Control 3812 0.68 1.00 0.47 LnMV 3812 8.08 7.97 0.98 II. DATA AND METHODOLOGY ROE 3812 9.51 8.36 11.43 GrowAsset 3812 0.23 0.13 0.71 2.1. Sample Selection Institution 3812 31.11 28.57 20.49

Firstly, all A-share public firms which listed before 2007 Table 2 shows the distribution of analysts’ coverage a in Shanghai and Shenzhen security exchange are selected. mong different industries and years. As shown in the tabl Analyst coverage information come from CMSAR datab e, the differences of average coverage among different in ase and accounting variables come from Wind. Second, fi dustries are apparent. Media and cultural industries have rms with missing values for sales, total assets, net income the highest average coverage in all 4 years. before extraordinary items, cash flow from operations, m arket value less than 10 million RMB are deleted, Also, fi Table 2. The Distribution of Analysts’ Coverage In-code presents different industries. The data of analyst’s coverage com (1) es from CMSAR database. Num- 2007 2008 2009 2010 Where i indexes firms, t indexes time, equals ber of Average Average Average Average In-code net income minus cash flow from operations; is firms coverage coverage coverage coverage A 17 5.00 11.24 12.06 17.94 changes in sales revenues; and , fixed asset; B 25 6.52 25.56 21.20 33.28 , legged total asset. All variables used here are scaled by legged total assets. We estimate the cross sec- C-C0 41 6.37 19.44 20.10 26.22 tional models separately by each industry and get the val- C-C1 37 2.76 6.43 6.68 7.59 ue of , , and . C-C2 4 1.50 2.00 7.75 8.75 Then we use the estimated ; ; and to calcu- C-C3 18 6.06 17.39 13.11 11.44 late nondiscretionary accruals. C-C4 92 3.55 9.91 9.88 10.52 (2) C-C5 37 4.19 9.68 8.97 12.51 C-C6 84 7.08 20.06 16.43 25.73 represents the change in receivables. Thus, C-C7 144 6.38 17.78 16.83 19.94 discretionary accruals can be derived as C-C8 70 5.91 15.37 14.56 19.13 (3) C-C99 9 6.56 13.67 11.11 13.11 Because all the variables are scaled by total assets at D 57 3.58 8.98 10.82 13.35 the beginning of each period, the magnitude of a firm’s E 24 2.83 8.42 8.96 14.71 discretionary accruals is demonstrated as a percentage of F 51 7.20 18.47 17.51 22.20 the assets of the firm. G 47 7.04 17.96 18.43 19.13 The magnitude of a firm’s discretionary accruals is in H 74 3.99 11.00 12.80 16.07 dicated as a percentage of the lagged assets of the firm. P ositive DAs suggests income-increasing manipulations, J 58 4.05 12.38 11.98 14.72 while negative DAs indicates income decreasing manipul K 22 7.73 22.27 18.68 25.55 ations. Managers have incentives to manage earnings not L 6 12.00 30.83 36.17 39.83 only upward, but also downward. In good years, they cou M 36 1.64 4.64 4.17 5.83 ld want to hide some earnings for future reporting use, w Min 4 1.50 2.00 4.17 5.83 hile, in bad years, they could take a bath (e.g., overstate b Max 144 12.00 30.83 36.17 39.83 ad assets or take a large restructuring charge) to make fut ure earnings targets easier to meet. Because we are intere 2.2. Estimation of Earnings Management sted in manipulations in both directions, we use the absol ute value of discretionary accruals, that is also used in se DA (Discretionary Accruals) can be used to present earni veral recent studies (e.g., Warfield, Wild, and Wild, 1995; ngs management. Besides cash, other major part, account Gu, 1999; Klein, 2002; Bergstresser and Philippon, 200 ing adjustments sometimes are called accruals. Manager 6)[9][10][11][6]. always determine the signs and level of accruals accordin In addition, we split the sample according to the sign g to their experience and estimation, they manipulate acc of discretionary accruals for all the tests. Doing so allows ruals easily. But earnings manipulation is just only one p us to check whether the patterns of effects on signed disc art of accruals. For some specific goal, it is needful and s retionary accruals are consistent with each other. uitable to adjust some accrual on a regular basis. Thus, n Table 3 demonstrates the absolute value of discretion ondiscretionary accruals (NDAs) together with discretion ary accruals, which means that the more analyst coverage, ary accruals (DAs) make up total accruals (TAs). A varie the less discretionary accruals. ty of papers use discretionary accruals (DAs) as the prox y for earnings management, such as Bergstresser and Phil Table 3. The Distribution of Discretionary Accruals ippon(2006) [6]. AbsDA is the absolute value of discretionary accruals which is computed There are several models to calculate DAs. Accord- through the OLS regression model above. ing to our sample firms and scope, the modified version Analyst Coverage Number of Firms AbsDA of the Jones model would be a good model to estimate 0 812 677.20 the firms’ DAs (Jones, 1991; Dechow, Sloan, and 1-5 1156 744.27 Sweeney, 1995) [7][8]. In the first step, by running the 6-10 474 709.94 following cross-sectional OLS regression of total accru- 10-15 298 700.10 als (TAs) on changes in sales and fixed assets (FA) with- in industries, we can estimate coefficients , , and . 15-20 263 697.62 >20 809 615.77 R-squared 0.5192 Mean dependent var 1.8053 III. THE EFFECT OF ANALYST COVERAGE ON Adjusted R-squared 0.5159 S.D. dependent var 1.3408 EARNINGS MANAGEMENT S.E. of regression 0.9328 Akaike info criterion 2.7059 In the first part of this section, We use discretionary ac- Sum squared resid 3293.7170 Schwarz criterion 2.7501 cruals as a proxy for earnings management and start the Log likelihood -5130.4560 Hannan-Quinn criter. 2.7216 analysis with OLS regressions. F-statistic 157.2160 Durbin-Watson stat 1.7824 Analyst coverage is associated with many factors, Prob(F-statistic) 0.0000 such as firm size, past performance, growth, external fi- nancing activities, and volatility of business (Bhushan, We label the residuals from the above regression as 1989; Dechow and Dichev, 2002; Kasznik, 1999)[12] “residual coverage” and use it as the main proxy for ana- [13][14].Some of those factors could also affect firms’ lyst coverage. It can be considered as a component of an- earnings management. To control for those factors, we alyst coverage that is uncorrelated with market value, first run the following regression: profit rate of asset, growth rate of assets, external financ- ing activities, or volatility of business. (4) Then we estimate the effect of analyst coverage on earnings management with the following OLS regres-

Where analyst coverage (ACi) is the number of ana- sion: lysts who made forecasts about firm’s earnings in any given year. αt are year fixed effects. γin is the industry (5) fixed effect. ei is an error term. lnMVi is the logarithm of market value. ROE represents the profit rate of net asset. i Where is year fixed effects, is industry fixed GrowAsset are the growth rate of assets. Institution rep- i i effects, represents firm ’s analyst coverage resents institutional ownership and Controli is the type of actual controller of firms. residual in year t. is the type of actual control of Table 4 show the regression result of analyst cover- firm i. , , represent the loga- age on independent variables. It can be indicated that rithm of market value, the growth rate of assets and the LnMV, Institution, ROE is significant at 0.1% level, return rate on net assets. means that the larger market value, the more analyst cov- From the table 5, the AcResidual is significant at 5% erage, and the more institutional holding, the more cover- level, while F-statistic is 26.9882 significantly, and other age, the better performance, the more coverage, which is statistics are acceptable, which infer that security ana- consistent with institution and available literature. Also, lysts’ coverage have restraint effect on managers’ earn- year and industry effects, GrowAsset and Control is sig- ings management decisions. nificant. The adjusted R-squared is 0.5159, and F-statistic Table 5. The Result of Earnings Management on Analyst Coverage is year fixed effects, is industry fixed effects, repre- is 157.2160 with Prob 0.0000, other statistics is accept- sents firm ’s analyst coverage residual in year t. is the type of actu- able too, which means the regression model is suitable. al control of firm i. , , represent the logarithm of market value, the growth rate of assets and the return rate on net assets. Table 4. The Result of Analyst Coverage on Independent variables Variable Coefficient Std. Error t-Statistic Prob. Analyst coverage (AC) is the number of analysts who made forecasts C 718.8726 156.0222 4.6075 0.0000 about firm’s earnings in any given year. LnMV is the logarithm of market value. ROE represents the profit rate of net asset. GrowAsset is the growth D1 28.6345 40.7607 0.7025 0.4824 rate of assets. Institution represents institutional ownership and Control is the type of actual controller of firms. D2 22.4723 40.1838 0.5592 0.5760 Variable Coefficient Std. Error t-Statistic Prob. D3 88.8899 37.7125 2.3570 0.0185 C -4.3141 0.1804 -23.9184 0.0000 AcResidual -35.9370 14.0603 -2.5559 0.0106 D1 -0.1925 0.0471 -4.0857 0.0000 YES D2 0.2406 0.0465 5.1798 0.0000 LnMV -8.4303 17.2809 -0.4878 0.6257 ROE 2.7999 1.2862 2.1769 0.0296 D3 0.2684 0.0436 6.1570 0.0000 GrowAsset 334.1501 18.6237 17.9422 0.0000 YES Institution -0.7027 0.8247 -0.8521 0.3942 LnMV 0.5776 0.0200 28.9118 0.0000 Control -59.7162 29.4820 -2.0255 0.0429 ROE 0.0244 0.0015 16.4343 0.0000 R-squared 0.1615 Mean dependent var 691.7734 GrowAsset 0.0604 0.0215 2.8047 0.0051 Adjusted R- 0.1555 S.D. dependent var 878.0796 Institution 0.0149 0.0010 15.6569 0.0000 squared Control -0.0628 0.0341 -1.8433 0.0654 S.E. of [11] Klein, A., 2002. Audit committee, board of director char- 806.9304 Akaike info criterion 16.2317 regression acteristic, and earnings management. Journal of Account- Sum squared ing and Economics 33,pp. 375–400. 2.46E+09 Schwarz criterion 16.2776 resid [12] Bhushan, R., 1989. Firm characteristics and analyst fol- lowing. Journal of Accounting and Economics 121, pp. Log likelihood -30909 Hannan-Quinn criter. 16.2480 255–274. F-statistic 26.9882 Durbin-Watson stat 2.0097 [13] Dechow, P., Dichev, I., 2002. The quality of accruals and Prob(F-statistic) 0.0000 earnings: the role of accrual estimation errors. The Ac- counting Review 77, pp. 35–59. [14] Kasznik, R., 1999. On the association between voluntary IV. CONCLUSION disclosure and earnings management. Journal of Account- Nowadays, security analysts have become more and ing Research 37, pp. 57–81. more important as intermediary in Chinese flourishing capital market. Furthermore, security analysts play exter- nal supervision role in corporate governance, indicating that more analyst coverage, less earnings coverage. The result is consistent with developed market. This paper contributes to the corporation governance theory and ap- plication. In future, other corporation governance func- tion of analyst coverage, such as reducing tunneling, de- creasing information asymmetry, et al. can be explored.

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