A study on relationship between inflation rate, interest rate and population growth towards housing price in Malaysia
Bibliographic record
Abstract
This study aims to examine the factors affecting Housing Price in Malaysia from 2006 until 2016. The continuous increase of housing price in Malaysia is becoming one of the hot issues discussed these days. Thus, this study would like to investigate the significant relationship among the housing price and independent variables namely Inflation Rate (CPI), Interest Rate (LR), and Population Growth (PG) that affect the housing prices in Malaysia (HPI). Ordinary Least Square (OLS) method is implemented to this study and interactive software package E- views would be used for testing and analyzing the data collected. This study will be done based on quarterly time series data over the period from 2006 Quarter 1 until 2016 Quarter 4 with 44 total observations. The findings benefit various parties such as investors, policy makers, housing developers, speculators and home buyers. The results concluded that Interest Rate (LR), and Population Growth (PG) have the major effects in determining the housing price.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".