Household Debt and Macroeconomic Variables in Malaysia
Bibliographic record
Abstract
The rise of household debt in Malaysia has caused consternation since it has almost reached 89.1% of total GDP. The level of household debt is deemed to be at worrying stage as it may trigger another financial crisis. The purpose of this study is to examine factors that influence household debt in Malaysia via time series data. This study employs the ordinary least square (OLS) method and the macroeconomic variables used consist of base lending rate, housing price index, gross domestic product and unemployment as independent variables taken in the period from quarter one 2008 to quarter four 2015. The results show that the housing price index is the most significant variable, followed by base lending rate, unemployment and gross domestic product. House pricing index and gross domestic product show positive relationships with household debt, which indicates that the rise of household debt is determined by the rise of these explanatory variables. However, base lending rate and unemployment are found to have negative effects on the rise of household debt. The data are taken from Bank Negara Malaysia report, National Property Information Centre (NAPIC) and Asia Regional Integration Centre.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".