The determinants of housing price index in Malaysia / Mohd Hazwan Harman Shah
Bibliographic record
Abstract
This study is to research about the Determinants of Housing Price Index in Malaysia. There are five independent variables that have been select for this research. The independent variables are consumer price index (MCPI), lending rates (MLR), money supply (MMS), gross domestic product (MGDP) and unemployment rate (MUR). This study use the quarterly data from quarter 3 of 2006 to quarter 1 of 2017 which total number of observation is 43 sample. Multiple linear regression model is applied to study the relationship between explanatory variables and explained variable. Empirical result of Equation 3 shows that MLR, MGDP and MUR significantly affect MHPI. While MCPI and MMS insignificantly affect MHPI. This study shows that the most significant relationship with MHPI is MLR followed by MGDP and MUR.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".