New Zealand's Residential Price Dynamics: Do capability to consume and government policies matter?
Bibliographic record
Abstract
The objectives of this paper are to provide empirical evidences on whether i) government policies represented by mortgage rate and loan-to-value ratio are associated with the dynamics of the New Zealand Residential Price Index, ii) macroeconomic factors such as house price to income ratio and inflation rate that proxy capability to consume, as well as population growth rate are the driving forces of housing market dynamics of the country. After testing a battery of statistical assumptions, this study adopts the Autoregressive Distributed Lag (ARDL) cointegration method to examine data from Quarter 1, 2009 to Quarter 2, 2019 for the short and long-run relationships among the variables. Findings show that mortgage rate, loan-to-value ratio, and inflation rate have negative long-run relationship with Residential Price Index. On the other hand, population growth rate and house price to income ratio are shown to have positive long-run impact on housing price. Results obtained from Error Correction Model reveal that whenever there is a short-run shock in the residential price dynamics, the Residential Price Index will take about three quarters to fully restore back to its long-run equilibrium. Additionally, mortgage rate, population growth rate, loan-to-value ratio and house price to income ratio are found to significantly Granger-cause New Zealand's residential price dynamics during the study period.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".