IMPLICATION, LIMITATION AND CONCLUSION.

2438 brand name audit firms, among others, do have an impact on the income smoothing activities that prevail in these companies. As for the factors affecting income smoothing, apart from the company size, profitability and indus trial sectors highlighted by Nasuhiyah et .al 1994, all except for management remuneration, the univariate and the multivariate tests results obtained largely support the alternative hypotheses that have been put forward in this study. The study also found that the model that utilized income attributable to shareholders as the income smoothing objective to be the best fit model. The could be due to the fact that income smoothing is most likely to be targeted at the shareholders. The above findings can have implications for users of financial statements and regulatory bodies. In particular, financial statement users should be aware of income smoothing and the factors affecting such behavior when they rely on financial statements to help them make decisions. Specifically, users should note the influence of the independent non-executive directors, chairman-duality and the brand name auditors, on such behavior. Further, since extensive income smoothing may lead to inadequate or 2439 misleading income disclosure, thus regulators should concentrate their efforts where income smoothing is most likely and most extensively to happen. There are few limitations that exist in this study. It is appropriate to highlight these potential limitations that should be considered when interpreting the results. They are; firstly, the study does not include companies that are not listed on Bursa Malaysia board, and also those companies that are categorized as financial institutions. The authors justify the former shortcoming, by stating that the companies that are listed on Bursa εalaysia contribute a larger scale to the well being of the country‘s economy, as compared to those that are not listed on the boards; while for the latter, the author justifies it on the basis that they are governed under different accounting regulations. Secondly, while Eckel‘s 1λ81 index identifies companies that artificially smooth their income, it may not identify all companies that attempt to do so. Thirdly, the companies that are taken into consideration are only those companies that have year 2000 annual report in the Bursa Malaysia website, as well as those 2440 companies that have a complete 10 years‘ income statement data with the www.klse- ris.com, to enable the calculation of the income smoothing index. And finally, the study may lack external validity in the sense that since it is based only on companies listed on Bursa εalaysia, especially those companies whose companies‘ websites are available on the Bursa Malaysia website, thus the result obtained may not be applicable in other settings or situations. However, the results obtained from this study could be an additional contribution towards the literature on income smoothing. This study is by no means completed or comprehensive; there are still avenues that can be further researched. For instance, research can be done on the factors that motivate managers to resort to income smoothing acts, such as in an agency setting, or on the use of various income smoothing objectives and instruments by managers. Further, following the limitations mentioned earlier, future study can also try to come up with improved methods in order to measure or even to detect income smoothing, as well as, to investigate it in different contexts e.g., different time frame or economic cycles. 2441 In conclusion, it is the authors‘ hope that with the findings compiled from the study could be of some assistance to the investors, the rule makers, as well as other interested parties with regards to financial statements issued by the listed companies. These affected parties are, therefore, able to take up certain precautionary steps so as not to be misled by the financial statements which might be a mere window dressing act by the management executives who may want to save themselves from being scrutinized or from being dismissed. The regulatory bodies thus are able to decide on the extend to which income smoothing needs to be monitored and controlled. 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C. and εeckling, W. 1λ76, ‗Theory of the Firmμ εanagerial Behavior, Agency Costs and Ownership Structure‘ Journal of Financial Economics, Vol.3 pg. 305-360. Johnston, J. 1984 Econometrics Methods, McGraw-Hill. Lai, L. and Tam, H. 2007 Independent Directors and the Propensity to Smooth Earnings: A Study of Corporate Governance in China, Cambridge Business Review, 7 , 328-335. 2446 Morck, R., Shleifer A. and Vishny, R. 1988 Management Ownership and Market Valuation: An Empirical Analysis, Journal of Financial Economics, 20, 293- 315. Moses, O.D., 1987 Income Smoothing and Incentives: Empirical Test Using Accounting Changes, Accounting Review, 62, 358-377. Nagy, A.L. and Neal, T.L. 2001 An Empirical Examination of Corporate Myopic Behaviorμ A Comparison of Japanese and US Companies‘, The International Journal of Accounting, 36 , 91-113. Nasuhiyah Ashari, Hian C.K., Soh L.T, and Wei H.W, 1994 Factors Affecting Income Smoothing Among listed Companies in Singapore, Accounting and Business Research , 24, 291-301. Patton, A. and J. Baker, 1987 Why Do Not Directors Rock the Boat?, Harvard Business Review, 65, 10-12 Trueman, B. and Titman, S.,1988 An Explanation for Accounting Income moothing, Journal of Accounting Research, 26, 127-139. 2447 Tsui, J. and Gul, A.F. 2000 Corporate Governance and Financial Transparencies in the Hong Kong Special Administrative Region of the People‘s Republic of China, paper presented at the Second Asian Roundtable on Corporate Governance, Hong Kong. Table 1: - Firms Sample Selection Procedure. No. of firms No of firms Firms reported on the 1990 Bursa Malaysia Listing 285 Less Finance institutions and finance related companies 19 Firms that do not have annual report web sites for the year 2000 21 Firms that do not have a complete ten-year record regarding their Profit and Loss account with the www:klse-ris.com.my 37 Change of accounting dates 47 124 Final sample 161 2448 Table 2 : Definitions of Variables Variable Measured as Represented by Expected sign of relationship Hypothesis variable Independent Non- executive director percentage of non-executive directors on the board NED - Duality 1 for companies with dual chairmanship duality, and 0 for otherwise DUAL +- Remuneration log total remuneration paid to all executives and non-executives over total sales REM + Institutional Investors percentage of the institutional shareholders INST +- Ownership Control percentage of the management shareholdings OWN +- Chinese-controlled companies percentage of Chinese directors on the board CCC - Auditor 1 for companies audited by the brand name auditors, and 0 for otherwise AUD - Control variable Industrial Commercial 1 for industrial commercial and 0 for others IND + Hotel Property 1 for hotelsproperties and 0 for others PROP + Company‘s size total asset after taking logarithm SIZE - 2449 Profitability net income after tax to total assets PROFIT +- Table 3: Descriptive Statistics of Sample Companies Based on Different Income Smoothing Objectives Smoothing Objectives Total sample Smoother Non-smoothers Income from Operations IFO 161 95 66 Profit Before Tax PBT 161 98 63 Profit After Tax PAT 161 95 66 Profit Attributable to Shareholders PATS 161 96 65 Table 4: Univariate Test Results Panel A: t-test Continuous Variables t-statistics for Different Income Smoothing Objective IFO PBT PAT PATS NED - 0.304 -0.070 1.183 0.304 REM + -0.324 0.104 -0.038 -0.748 INST + 0.666 0.681 1.833 0.758 OWN +- 0.616 0.355 0.187 1.756 CCC - 0.623 0.130 -0.430 0.623 SIZE - 0.272 -1.268 -1.554 -0.797 PROFIT +- 1.274 1.903 2.254 2.270 Panel B: Wilcoxon Signed Ranks Categorical Wilcoxon Signed Ranks z-statistics for Different Income Smoothing Objective 2450 Variables IFO PBT PAT PATS DUAL +- -6.328 -6.325 -6.254 -6.325 AUD - -6.405 -6.696 -6.114 -6.325 IND -5.966 -6.114 -5.766 -6.039 PROP -3.952 -3.628 -3.801 -3.579 Significant at the 0.01 level 1-tailed test Significant at the 0.01 level 2-tailed test Significant at the 0.05 level 1-tailed test Significant at the 0.05 level 2-tailed test Significant at the 0.10 level 1-tailed test Significant at the 0.10 level 2-tailed test Table 5: Logit Analysis Result Panel A: Income from Operation IFO

1. Logit Model Results

Beta p-value H1: Non-executive Directors -0.215 0.837 H2: Chairman Duality DUAL 0.241 0.565 H3 Remuneration REM 0.071 0.740 H4 Institutional Investors INST -0.007 0.558 H5 Ownership Control OWN -0.003 0.741 H6: Chinese Controlled -0.483 0.480 H7: Auditor AUD -0.145 0.731 IndustrialCommercial IND 0.553 0.095 HotelProperties PROP 0.593 0.081 Company‘s Size SIZE -0.078 0.803 Profitability PROFIT -0.127 0.381

2. Omnibus Test of Model Coefficients Chi-square 6.403

0.845 2451

3. Classification Results holdout accuracy rates

Predicted Actual Status Smoother Non-smoother Total Smoother 81 14 95 Non-smoother 53 13 66 Total sample 134 27 161 Overall accuracy rates 58.4 Panel B. Income Before Tax PBT. 1. Logit Model Results Variables Beta p-value H1: Non-executive Directors -0.030 0.978 H2: Chairman Duality DUAL -0.060 0.886 H3: Remuneration REM 0.011 0.957 H4: Institutional Investors INST -0.004 0.737 H5: Ownership Control OWN -0.005 0.546 H6: Chinese Controlled -0.164 0.812 H7: Auditor AUD -0.185 0.665 IndustrialCommercial IND -0.081 0.845 HotelProperties PROP 0.433 0.317 Company‘s Size SIZE 0.291 0.364 Profitability PROFIT -0.229 0.278

2. Omnibus Test of Model Coefficients chi-square 7.098 0.791

3. Classification Results holdout accuracy rates

Predicted Actual Status Smoother Non-smoother Total Smoother 94 4 98 Non-smoother 57 6 63 Total sample 151 10 161 Overall accuracy rates 62.1