Understanding the impact of macroeconomic factors towards household debt in Malaysia / Helisa Julius Lius
Bibliographic record
Abstract
The purpose of this study is to identify the factors that influence household debt in Malaysia via time series data. This study will employ the time series, Diagnostic Test and Ordinary Least Test method and the macroeconomic variables used consists of house price index, interest rate, gross domestic product, unemployment rate and consumer price index as independent variable taken from first quarter 2011 to fourth quarter 2018. The result revealed that house pricing index show positive relationship with household debt, which indicates that the rise of household debt is determined by the rise of house price index. However, interest rate, gross domestic product, unemployment and consumer price index 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 Department of Statistics Malaysia (DoSM). This study could provide some guidance to the academicians and policy makers in controlling the mounting debt level and may help in realizing the nation economic nowadays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".