Income statements transparency and firms' characteristics of companies listed on the Bursa Malaysia - Mohd Saad, Sazilah; Syed Ahmad, Syed Noh; Jusoff, Kamaruzaman; Md Daud, Mazlifa; Abd Rahim, Maisarah (Science Publications, 2009)
Problem statement: This research was intended to contribute to the one of Corporate Governance mechanism on transparency and disclosure on the financial statements. Approach: As in the recent development of findings from Financial Statements Review Committee (FSRC) that company did not disclose of Material expenses and not classified accordingly. Results: This study provides an evidence for the transparency level on income statements with regards of firms’ characteristics of 150 main and second boards companies listed on the Bursa Malaysia. The characteristics were grouped into three groups of variables: structural (firm size, leverage and number of shareholder), market related (listing type and industry type) and performance (profit margin, return on equity and liquidity). The study was started with the development of a Transparency Index based on the percentage of the details of expenses disclosed in annual reports (notes to the accounts) over the total expenses of the company. The findings suggested that this index on the average for the companies in the sample is about 64% with three companies scoring transparency index of 100%. Both univariate and multivariate statistical analysis were performed on the data. The stepwise regression method indicated that only one variable was significant at 5% which was the Number of Shareholders (LnNOSH). The other factors were not significant. Hence, this study will contributes to the enhancement of knowledge regarding income statements transparency and disclosure practices under new reporting regime in Malaysia. Conclusion/Recommendations: This study also served as a basis for further research in this area. This study also suggested that further research should be done on longitudinal study basis for several years of data with more appropriate or suitable variables to the model.