Factors influencing accounting policy choices for FRS 16 and FRS 40 of Singapore listed companies.
Due to increased incorporation of fair values into accounting standards in recent years, we would like to investigate the reasons influencing Singapore listed companies’ choice of accounting policies between historical cost and revaluation/fair value model for FRS 16 and FRS 40. The factors that wer...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/46477 |
| Summary: | Due to increased incorporation of fair values into accounting standards in recent years, we would like to investigate the reasons influencing Singapore listed companies’ choice of accounting policies between historical cost and revaluation/fair value model for FRS 16 and FRS 40. The factors that were investigated include size of company as proxied by log sales, debt/equity ratio, dilution of ownership structure and previous choice of accounting policy under FRS 25 (the predecessor of FRS 40). Deductive reasoning approach and descriptive research design were used to determine correlation and the logistic regression method was employed to determine if accounting policy choice was based on the abovementioned factors.
Data from a sample of 200 2009 annual reports of listed companies on the Singapore Exchange was collected to perform the statistical analysis. Our results support the hypotheses that firms with higher sales are more likely to adopt revaluation model under FRS 16 and firms who adopted the revaluation model under FRS 25 are more likely to adopt fair value accounting for investment property under FRS 40. The first hypothesis can be explained by the political cost hypothesis while the second hypothesis can be explained by firms’ conservatism in introducing uncertainty into their financial statements if they change accounting policies. Future studies can be improved through incorporation of more years of data and testing of additional variables like management bonuses. |
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