The effects of macroeconomics policies on housing affordability in Malaysia
Bibliographic record
Abstract
Housing affordability remains conundrum in Malaysia despite the initiatives taken by the government. Malaysia's median multiple house price has surpassed the three times median annual household income threshold for housing affordability over the past two decades. This implies that Malaysian housing is severely unaffordable, resulting in supply overhang issues which cause non-profitable investment to the developer from previously built housing units. This study aims to explore the role of government intervention through macroeconomic policy, including monetary and fiscal policies, on housing affordability in Malaysia. This study employed Public Interest Theory to emphasise the significance of government intervention in a market involving public interest, as a government is a benevolent regulator with adequate information and absolute enforcement powers. The Autoregressive Distributed Lag (ARDL) and Vector Autoregression (VAR) estimation techniques were employed on quarterly data involving 61 observations from the first quarter of 2006 until the first quarter of 2021. The results revealed that money supply, government expenditure and tax have significant short and long-run impacts on housing affordability except for interest rates. The long-run cointegration between fiscal policy variables (i.e., tax and government expenditure) and housing affordability in conjunction with its significant short-run relationship has highlighted the pivotal role of fiscal policy in influencing housing affordability. Monetary policy is only effective through changes in money supply (in both the long and short run) and interest rates (only in the short run) in the Malaysian housing market. Policymakers are recommended to emphasize more on regulating fiscal policy than monetary policy in order to promote housing affordability in Malaysia efficiently. In the future, studies related to perspective from supply-side could also be incorporated to obtain a more comprehensive estimated model.
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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 | 0.001 | 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 | 0.001 |
| 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".