Investment Property, Cost Model, Fair Value Model and Value Relevance: Evidence From Malaysia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The purpose of the study is to investigate the value relevance of investment property of Malaysian listed firms based on cost model and fair value model for measuring their investment properties. Some studies suggested fair value model is more value relevant and some other studies suggested cost model is more value relevant. The sample was selected using a simple random sampling so that all listed firms have equal chance to be selected. A final sample of 108 firm-year from various industries was selected for a period from 2018 to 2019. Equity valuation models developed by Landsman (1986) and Ohlson (1995) were used to test the value relevance of investment property employed by listed firms in Malaysia. The models were used to test the value relevant of pooled sample, fair value sample and cost sample. The results show that firms’ investment properties are value relevant regardless whether cost model or fair value model was selected. It was also found that depreciation included in cost model and fair value gain or loss included in fair value model net profits are value relevant. The study implicates that cost model is more value relevant in measuring investment property. The result provides useful insight to standard setter about the effect of selection of fair value model and cost model towards share market value. Standard setters, researchers and academics would benefit from this as prior research in Malaysia suggests that investment properties (in general) are not value relevant even though investment properties of property companies are value relevant.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it