Empirical results Proceeding E Book 4A Turky

555 performance tend to change their name. And the leverage ratio of corporate name change firms is higher and the size of corporate name change firms is smaller than Panel 2, so we find that the smaller firms more change their name. [Table 4 about here] The standard deviation of operating income and return on assets is big so that we try to minimize the eliminations of observations to represent the features of corporate name change firms. Instead we run parrel Mann-Whitney test for non-parametric statistics. Table 5 shows the correlation coefficients between the pairs of the variables of interest for the sample in Panel 1 corporate name change firms and Panel 2total firms. [Table 5 about here] The result of correlation analysis for both Panel 1 and Panel 2 indicates that corporate name change firm is significantly negatively correlated with discretionary accruals. It also shows that corporate name change by loss-reporting firms is significantly negatively correlated with discretionary accruals. And corporate name by largest stockholders change firms is significantly negatively correlated with discretionary accruals in panel 1. We find that cash from operationsCFO and total accrualsTA have a significant negative relationship and Leverage ratios have a significant negative relationship with both TA and DA. However, the growth rate of sales and the size of firms do not exhibit significant relationship with accruals. 4. 2 Regression Analysis The regression results for hypothesis 1 are reported in table 6. [Table 6 about here] The results are reported for regression DA1 2, 3 on NC and controlling for CFO, LEV, SIZE, GRW. We do not control CFO in model 2 because we already control it during drawing model 2. For all model, the coefficients on NC are negative and significant at the .01 level. We expect that corporate name change firms will lower their earnings because most of them have high debt-ratio or are administrative issues in the KOSDAQ market, so they cant manage earnings upward. We find that corporate name change firms have 556 negative discretionary accrual and the result is consistent with our expectation. All of the control variables exhibit coefficients consistent with the previous study and all variables are significant. Firms with higher debt ratio change corporate name more. Next we investigate whether there are differences of discretional accruals depending on the reason of corporate name change. Table 7 shows the result of regression of DA 12, 3 on LC, IC, OC and controlling for CFO, LEV, SIZE, GRW. LC is a dummy variable which has a value 1 when a firm reports current loss and IC is a dummy which has a value 1 when a firm change industry through consolidation or change the primary products. OC is a dummy which has a value 1 when the largest stockholders are changed for corporate name change firms. [Table 7 about here] We expect there is difference among the corporate name changes. Yang et al.2009 report that managers of loss-reporting firms may take actions to accelerate the collection of receivables, and delay the purchases of inventory and payment of payables. and those actions will result in the decrease of accruals. Our findings are consistent with the previous study. Corporate name change by loss-reporting firms have significantly negative discretionary accruals in all models, on the contrary the corporate name change of industry change firms and largest stockholders change firms have no significant relationship with discretionary accruals. Therefore, the result supports hypothesis 2 that there are statistically significant differences among the reasons for corporate name changes. Corporate name have changed by the interaction of multiple factors, by not just one factor. For example, corporate name change could be happened that the largest stockholders have changed by disposition of shares or the management right abundantly due to current bad performance. Largest stockholders could be changed following the industry consolidation or continued corporate restructuring. So we investigate the effect the interaction of multiple factors on discretionary accruals when corporate name change reasons are interplayed and table 8 reports that the result of regression. [Table 8 about here] We find that corporate name change by loss-reporting firms have significantly negative discretionary accruals in all models and corporate name change of largest stockholders change firms have significantly positive discretional accruals in model 1 557 and 3. And corporate name change by loss-reporting and largest stockholders change firms have significantly negative relationship with discretionary accruals. It means the relationship between corporate name change by loss-reporting firms and discretionary accruals is strongest among other purpose. Ⅴ. Conclusion Corporate name is supposed to serve as a signal to convey information about a firm ‘s major business or product lines. Investors will be better served as long as corporate names can be associated with major businesses or product lines. According to our investigation, there is a big increase in corporate name changes by loss-reporting firms even though it is accompanied by non-trivial costs such as consulting fees and corporate identity costs. In this paper, we focus the purpose of the management who change their name, different from the prior study. We investigate the background to corporate name changes of Korean listed companies in the years of 2004 to 2008. We first descriptively examine the current trend of corporate name change; how many firms change corporate names, how they have changed, why they change and who change names . Second we examine empirically whether name change firms are associated with discretional accruals. We further divide the reason of corporate name change into cosmetic change to hide negative earning, industry change or consolidation and change of the largest stockholders to examine whether there are differences among the name change reasons. We find that corporate name change firms generally report bad performance comparing non-changing firms and many corporate name change firms announce the embezzlements or misappropriation of management. Also there are many corporate name change firms of administration from KOSDAQ market. And there are general changes as industry change or largest stockholders change in the corporate name change firms. We find that name change firms have negative discretional accrual and especially name change firms with loss-reporting are significantly negatively associated with discretional accruals. This result means that there is difference among the purposes of corporate name change. And we also investigate the effect the interplay of multiple factors on discretional accruals when corporate name change purpose is interplayed, therefore we find that corporate name change of largest stockholders change with loss-reporting firms are significantly negatively 558 related with discretional accrual. It means that the relationship between corporate name change with loss-reporting and discretional accruals is strongest among other purposes. This result calls the validity of the corporate name change by loss- reporting firms in question. Our study adds to the literature in the sense that it is the first attempt to examine the characteristics of firms changing their names and to investigate the impact of corporate name changes on discretionary accruals. References AsiaEconomics. 2009. 05. 20. Investors cant believe Corporate English name E-today. 2008. 02. 13. 155 Corporate name change firms last year. E-today. 2009. 01. 21. corporate name change firms increased 18. 1 last year I-news. 2007. 11. 27. It will be more strict in KOSDAQ announcement. Bosch, J. C. and M, Hirschey. 1989. The valuation effects of corporate name change. Financial Management 18: 64-73. Cooper, M., H. Gulen and P. Rau. 2005. Changing names with style: Mutual fund name changes and their effect on fund flows. Journal of finance 60: 2825- 2858. DeAngelo, I. 1988. Managerial Competition, Information Costs, and Corporate Governance :The Use of Accounting Performance Measures in Proxy Contents. Journal of Accounting and Economics 10: 3-36. Harawa, R. D. 1992. Wall Street Announcements of News of Corporate Name Changes and The Response of Security Prices: An Application of Event. University of New York. Horsky, D.and P. Swyngedouw. 1987. Dose it pay to Change Your Companys Name? A Market Perspective. Marketing Science 6: 320-335. Howe, J. 1982. A rose by any other name? A note on corporate name changes. Financial Review 17: 271-278. Hung Wan Kot and Ji Zhang. 2008. Price reaction to corporate name changes. Working Paper. Karpoff, J. M. amd G. W. Rankin. 1994. In search of a signaling effect: The wealth effects of corporate name changes. Journal of Banking Finance 18: 1027- 1045. 559 Kothari, S., Sabino. and Zach, T. 2005. Implications of Survival and Data Trimming for Tests of Market Efficiency. Journal of Accounting and Economics 39: 129- 161. Lee, A. Y., Jun, S. B. and Park, S. S. 2007. Turnover of CEO and earnings management. Korean Accounting Review 32-2.: 117-150. Na, J. K. 1996. Executives compensation hypothesis and earning smoothing hypothesis about earning managements. Korean Accounting Review 21: 47-66. Oh, H. J. 2004. Corporate name change and Stock Price Reaction in KOSDAQ firms. Economics Research 22-4: 227-252. Oh, H. J. and Hyun, Y. H. 2003. Corporate name change and Stock Price Reaction. Korean Business Review 32-2: 647-669. Park, J. I. 2003. Corporate gorvernance and Earning management; The largest stockholders ownership. Korean Accounting Review 28-2: 135-172. Yang, D. J., Ko, D. Y. and Yoon, S. S. 2009. The Effect of Leverage of loss-reporting firms on Earning management. Working paper. Yoon, S. S. 2005. A Comparision of Earnings Management between KSE Firms and KOSDAQ Firms. The Journal of Business Finance Accounting 32: 1347- 1372. Yoon, S. Y. and Choi, Y. M. 2007. The relationship between corporate name change and Stock price in KOSPI. POSRI Business Research 7-3: 108-129. Yoon, S., and G. Miller. 2002. Cash from Operations and Earnings Management of Korean Firms. International Journal of Accounting 37: 395-412. Yoon, S., and H. Kim. 2008. Accounting Choice through Business Combinations: The case of Goodwill and Negative Goodwill. Korean Accounting Review 33-3: 261- 290. Warfield, T., J. Wild, and K. Wild. 1995. Managerial Ownership; Accounting Choices and Informativeness of Earnings. Journal of Accounting and Economics 20: 61-91. Watts R. and J. Zimmerman. 1996. Positive Accounting Theory, Englewood Cliffs, N. J. Prentice-Hall. www. kind. krx. co. kr www. dart. fss. co. kr 560 Table 3 The Comparison of corporate name change and non-changing firms Variables Sample firms n=401 Control firms n=4098 t-test Mann-Whitney test Z CFO -0.18 0.03 -6.67 -13.24 LEV 0.51 0.42 4.66 -4.64 NI -0.52 -0.05 -9.41 -15.95 OP -0.13 0.03 -8.84 -14.17 ROA -0.51 -0.07 -8.49 -15.62 Definition of variables CFO= the ratio of cash from operations to the beginning total assetsBTA; LEV= the ration of debts to total assets; NI= net income to BTA; OP= operating income to BTA; ROA= net income to total assets. 561 Table 4 Descriptive Statistics definition of variables NC= corporate name change firms; LC= loss-reporting firms in corporate name change; IC= industry change through consolidation or diversification in corporate name change; OC= the largest stockholders change in corporate name change; CFO= the ratio of cash from operations to the beginning total assetsBTA; LEV= the ration of debts to total assets; NI= net income to BTA; OP= operating income to BTA; ROA= net income to total assets; TA= total accruals; accruals are deflated by the BTA; DA12, 3= discretional accrual through model 12, 3; SIZE= natural log of the total assets at the end of the year; GRW= the growth of sales. Panel 1 Sample firms n = 401 mean min median max sd LC 0.73 0.00 1.00 1.00 0.44 IC 0.14 0.00 0.00 1.00 0.34 OC 0.60 0.00 1.00 1.00 0.48 DA1 -0.23 -7.09 -0.11 14.33 1.09 DA2 -0.25 -7.06 -0.13 10.91 1.01 DA3 -0.04 -6.20 -0.03 14.57 1.11 TA -0.33 -7.26 -0.17 9.48 0.96 CFO -0.18 -8.54 -0.07 3.59 0.64 LEV 0.57 0.00 0.45 3.62 0.37 OP -0.64 -32.23 -0.17 0.64 2.20 ROA -0.51 -7.92 -0.22 0.35 1.10 SIZE 23.93 20.35 24.01 28.78 1.01 GRW 0.28 -0.99 0.06 6.81 1.10 Panel 2 Total firms n = 4,498 mean min median max sd NC 0.09 0.00 0.00 1.00 0.28 LC 0.38 0.00 0.00 1.00 0.48 IC 0.01 0.00 0.00 1.00 0.11 OC 0.05 0.00 0.00 1.00 0.23 DA1 -0.04 -11.12 -0.00 14.33 0.49 DA2 -0.03 -10.68 0.00 10.92 0.46 DA3 0.01 -8.76 0.00 14.57 0.45 TA -0.10 -12.86 -0.04 9.48 0.49 CFO 0.01 -8.54 0.03 7.66 0.32 LEV 0.43 0.00 0.40 5.68 0.33 OP -0.11 -32.22 0.03 0.76 1.22 ROA -0.11 -9.24 0.02 0.65 0.62 SIZE 24.44 20.26 24.42 28.85 0.87 GRW 0.19 0.99 0.08 6.81 0.73 562 Table 5 Correlation Coefficients 1 PearsonSpearman correlation coefficients are reported abovebelow the diagonal. Statistical significance at 0.05 leveltwo-tailed. 2 Definition of variables; NC= corporate name change firms; LC= loss-reporting firms in corporate name change; IC= industry change through consolidation or diversification in corporate name change; OC= the largest stockholders change in corporate name change; CFO= the ratio of cash from operations to the beginning total assetsBTA; LEV= the ration of debts to total assets; NI= net income to BTA; OP= operating income to BTA; DA12, 3= discretional accrual through model 12, 3; SIZE= natural log of the total assets at the end of the year; GRW= the growth of sales. Panel 1: Sample firms n= 401 DA1 DA2 DA3 TA LC IC OC CFO LEV OP SIZE GRW DA1 1 0.93 0.80 0.93 -0.46 -0.00 -0.21 0.04 -0.15 0.38 0.05 0.07 DA2 0.96 1 0.75 0.91 -0.49 -0.00 -0.26 0.12 -0.17 0.43 0.11 0.05 DA3 0.90 0.85 1 0.72 -0.24 -0.00 -0.07 -0.22 -0.08 0.08 -0.05 -0.00 TA 0.97 0.96 0.85 1 -0.51 0.00 -0.30 0.08 -0.17 0.44 0.12 0.11 LC -0.27 -0.29 -0.16 -0.29 1 0.03 0.33 -0.49 0.10 -0.65 -0.16 -0.25 IC -0.00 0.01 -0.00 0.00 0.03 1 0.10 0.00 0.07 0.04 0.02 0.07 OC -0.11 -0.14 -0.03 -0.17 0.33 0.10 1 -0.28 0.03 -0.35 -0.34 -0.11 CFO -0.37 -0.26 -0.45 -0.25 -0.21 0.00 -0.15 1 -0.05 0.66 0.42 0.22 LEV -0.15 -0.15 -0.01 -0.17 0.14 0.04 0.06 -0.08 1 -0.03 0.09 0.05 OP 0.07 0.07 -0.00 0.09 -0.16 -0.10 -0.14 0.15 -0.16 1 0.29 0.41 SIZE 0.05 0.05 -0.00 0.13 -0.12 0.01 -0.31 0.38 0.02 0.11 1 -0.00 GRW -0.01 -0.01 -0.04 -0.02 -0.16 0.06 -0.03 0.05 -0.00 0.18 -0.13 1 Panel 2: Total firms n= 4,499 DA1 DA2 DA3 TA NC LC IC OC CFO LEV OP SIZE GRW DA1 1 0.92 0.85 0.82 -0.13 -0.37 -0.05 -0.14 -0.19 -0.13 0.27 0.05 0.09 DA2 0.94 1 0.76 0.78 -0.15 -0.44 -0.06 -0.17 -0.07 -0.14 0.33 0.08 0.09 DA3 0.88 0.80 1 0.67 -0.04 -0.11 -0.01 -0.04 -0.42 -0.02 0.01 -0.03 0.06 TA 0.90 0.86 0.78 1 -0.16 -0.49 -0.06 -0.19 -0.20 -0.16 0.37 0.09 0.17 NC -0.13 -0.16 -0.04 -0.15 1 0.22 0.36 0.76 -0.20 0.07 -0.22 -0.17 -0.02 LC -0.26 -0.30 -0.10 -0.30 0.22 1 0.09 0.23 -0.50 0.23 -0.72 -0.17 -0.27 IC -0.05 -0.05 -0.01 -0.05 0.35 0.08 1 0.33 -0.07 0.05 -0.07 -0.06 0.01 OC -0.15 -0.18 -0.04 -0.17 0.77 0.23 0.33 1 -0.20 0.06 -0.23 -0.19 -0.04 CFO -0.25 -0.08 -0.40 -0.19 -0.20 -0.29 -0.07 -0.20 1 -0.23 0.61 0.15 0.20 LEV -0.25 -0.27 -0.53 -0.26 0.10 0.25 0.04 0.08 -0.15 1 -0.24 0.13 0.01 OP 0.14 0.16 0.00 0.15 -0.17 -0.27 -0.14 -0.20 0.22 -0.18 1 0.17 0.36 SIZE 0.09 0.11 0.10 0.15 -0.19 -0.17 -0.06 -0.21 0.21 0.04 0.14 1 -0.00 GRW 0.02 0.02 0.02 -0.02 0.03 -0.09 0.04 0.01 0.02 0.00 0.13 -0.10 1 563 Table 6 Regression of the effect corporate name change on discretional accruals Definition of variables NC= a value 1 when a firm change corporate name; CFO= the ratio of cash from operations to the beginning total assetsBTA; LEV= the ration of debts to total assets; SIZE= natural log of the total assets at the end of the year; GRW= the growth of sales; DA12, 3= discretional accrual through model 12, 3. DA1DA2, DA3= b +b 1 NC+b 2 CFOit+b 3 LEV it +b4SIZE it +b 5 GROW it +e it DA1 DA2 DA3 Intercept -1.96 -10.15 -1.15 -6.23 -1.17 -6.82 NC -0.25 -10.49 -0.18 -8.07 -0.15 -7.15 CFO -0.55 -25.50 -0.64 -33.36 LEV -0.46 -21.70 -0.38 -18.53 -0.17 -8.73 SIZE 0.09 11.10 0.05 7.02 0.05 7.38 GRW 0.03 3.74 0.02 2.51 0.03 3.10 Adj. R 2 0.20 0.10 0.20 n= 4642 564 Table 7 Regression of discretionary accruals on the reasons for corporate name changes Definition of variables LC=a value 1 when a firm report current loss; IC=a value 1 when a firm change industry; OC=a value 1 when a firm change largest stockholders; CFO= the ratio of cash from operations to the beginning total assetsBTA; LEV= the ration of debts to total assets; SIZE= natural log of the total assets at the end of the year; GRW= the growth of sales; DA12, 3= discretional accrual through model 12, 3. DA1DA2, DA3 it = b +b 1 LC+b 2 IC+b 3 OC+b 4 CFOit+b 5 LEV it +b 6 SIZE it +b 7 GROW it +e it DA1 DA2 DA3 Intercept -4.91 -3.93 -0.01 -0.01 -4.40 -3.51 LC -0.81 -7.27 -0.60 -5.24 -0.63 -5.75 IC -0.03 -0.26 -0.09 -0.86 0.06 0.58 OC 0.06 0.47 0.10 0.75 0.02 0.12 CFO -0.90 -11.57 -0.94 -12.19 LEV -0.45 -3.67 -0.35 -2.79 -0.08 -0.65 SIZE 0.22 4.36 0.02 0.36 0.19 3.78 GRW -0.02 -0.41 -0.05 -1.12 -0.03 -0.78 Adj. R 2 0.31 0.10 0.30 565 Table 8 Regression of discretionary accruals on the reasons for corporate name changes with interaction terms DA1DA2, DA3 it = b +b 1 LC+b 2 IC+b 3 OC+b 4 LCIC+b 5 LCOC+b 6 ICOC+b 7 LCICOC +b 8 CFOit+b 9 LEV it +b 10 SIZE it +b 11 GROW it +e it DA1 DA2 DA3 Intercept -5.32 -4.29 -0.29 -0.24 -4.66 -3.77 LC -0.50 -3.33 -0.38 -2.38 -0.40 -2.63 OC

0.60 2.90 0.38 1.78

0.56 2.70 IC

-0.11 -0.20 -0.08 -0.16 -0.17 -0.32 LCOC -0.83 -3.50 -0.64 -2.60 -0.66 -2.77 LCIC 0.13 0.21 0.12 0.20 0.18 0.30 ICOC -0.34 -0.54 -0.28 -0.44 -0.22 -0.36 LCICOC 0.46 0.66 0.46 0.63 0.28 0.40 CFO -0.91 -11.80 -0.95 -12.33 LEV -0.47 -3.91 -0.37 -2.95 -0.10 -0.81 SIZE 0.23 4.61 0.02 0.51 0.20 3.96 GRW -0.02 -0.46 -0.05 -1.16 -0.03 -0.82 Adj. R 2 0.32 0.11 0.29 Definition of variables LC=a value 1 when a firm report current loss; IC=a value 1 when a firm change industry; OC=a value 1 when a firm change largest stockholders; LCIC= a value 1 when a loss-reporting firm change industry; LCOC= a value 1 when a loss-reporting firm change largest stockholders; ICOC= a value 1 when a firm change industry and largest stockholders; LCICOC= a value 1 when a loss- reporting firm change industry and largest stockholders; CFO= the ratio of cash from operations to the beginning total assetsBTA; LEV= the ration of debts to total assets; SIZE= natural log of the total assets at the end of the year; GRW= the growth of sales; DA12, 3= discretional accrual through model 12, 3. 566 THE EFFECT OF EARNINGS MANAGEMENT THROUGH REAL ACTIVITIES ON FUTURE OPERATING PERFORMANCE EMPIRICAL EVIDENCE FROM MANUFACTURING FIRMS LISTED IN INDONESIA STOCK EXCHANGE Rizqa Liaviani Afif , University of Indonesia Sylvia Veronica Siregar, University of Indonesia ABSTRACT This research aims to examine whether firms engage in real activities manipulation through selling, general, and administrative expense, production cost, and gain on asset sales and to examine the negative impact of real activities manipulation through these three indicators on future operating performance. Samples used in this research are 116 firms. Research model used is based on Gunny 2005 model. Statistic methods employed are one sample t-test and multiple linear regressions. The results show that manufacturing public firms in Indonesia engage in real activities manipulation through the three indicators. Moreover, this research finds that real activities manipulation through production cost has significantly negative effect on future operating performance by cash flow return on asset proxy and cannot be proved by operating income return on asset proxy. Moreover, real activities manipulation through gain on asset sales found has significantly positive effect on operating performance in short-term but insignificantly positive impact on operating performance in the long-term. However, this research does not find that real activities manipulation through selling, general, and administrative expense has significantly negative effect on future operating performance. Keywords : real activities manipulation, selling, general, and administrative expense, production cost, gain on asset sales, future operating performance

1. Introduction

Financial statements are prepared using accrual basis of accounting. Accrual accounting is superior compared to cash basis because of the ―matching principle‖ allows revenues to be matched with corresponding expenses that are incurred in the same period, without regard on the timing of cash flows. But the use of accrual basis also provide management the flexibility to choose accounting methods. When management is given that flexibility, there is a possibility that they will engage in earnings management activity Scott, 2009. According to Gunny 2005, earnings management can be classified into three catagories: fraud, accrual manipulation, and real earnings management or real activities manipulation. Real activities manipulation can be done by 1 reducing selling, general, and administrative 567 expense, 2 increasing production cost, 3 gain on asset sales Gunny, 2005; Roychowdhury, 2006. Oktorina 2008 finds that market performance of firms engaging in manipulation through operating cash flows is higher than firms not engaging in manipulation. Graham, Harvey, and Rajgopal 2005 suggest that in doing real activities manipulation, management tends to ignore future cash flows to achieve target earnings in this period. Cash flows is often used as a measure of operating performance that shows asset capabilities in generating operating income Pradhono and Christiawan, 2004. These indicates that real activities manipulation will effect future operating performance negatively. Gunny 2005 also finds that real activities manipulation has economically significant negative impact on future operating performance. Empirical research concerning real activities manipulation in Indonesia is still rare. This paper aims to examine whether firms engage in real activities manipulation through selling, general, and administrative expense, production cost, and gain on asset sales and to examine the negative impact of real activities manipulation through these three indicators on future operating performance. This paper contributes to the literature on earnings management in several ways. First, the evidence in this paper suggests that real activities manipulation through gain on asset sales has significantly positive impact on operating performance in short-term and has insignificantly positive impact on operating performance in long-term, thus, providing the evidence that in doing real activities manipulation, management is not always ignoring future operating performance. Second, we find no evidence that real activities manipulation through selling, general, and administrative expense has significantly negative impact on future operating performance. This finding maybe due to the presumation that manipulation is done repeatedly on the following years.

2. Literature Review

2.1 Earnings Management

According to Scott β009, earnings management is ―the choice by a manager of accounting policies, or actions affecting earnings, so as to