Household debt in Malaysia: an analysis on macroeconomic variables / Nurul Syaznirah Taharudin
Bibliographic record
Abstract
In Malaysia there are two concerns related to debt have often been discussed. One of the debts are household debt, mainly for housing and purchase of a personal car, which contribute about 80 per cent of the gross domestic product (GDP). The expansion of loans has led to the rise of household debt and it has been an increasing trend since the early 2000s. The increase in Malaysia’s household debt has risen to 84% of total GDP in 2017. However, in the third quarter of 2018 Malaysia’s household debt has fall to 83.2% (Bank Negara Malaysia, 2018). The purpose of this study is to examine the impact of household debt in Malaysia using time series data. This study employs the ordinary least square (OLS) method and the macroeconomic variables used consist of gross domestic product, consumer price index, interest rate, housing price index and unemployment as independent variables taken in the period from 2003 to 2018 annually. The finding shows that GDP, house price index, interest rate and unemployment rate have negative significant with household debt.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 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 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".