The connection of rental and house price affordability measures in New Zealand
Bibliographic record
Abstract
The aim of this paper is to examine the cointegration and long-run relation between affordability measures of house ownership prices and house rental prices in New Zealand. Using the approaches by Westerlund (2007) and Dumitrescu and Hurlin (2012), the study shows that there is an existence of cointegration and unidirectional causality effects between house price affordability (HPA) and rental price affordability (RPA) across 11 regions. Auckland, Wellington and Canterbury are the three regions in which the results detect the most extreme effects among HPA and RPA compared to other places in the country. We extend our study by examining the lead-lad correlation between those two affordability measures. Our extended empirical work shows interesting results that the lead-lad effects of HPA and RPA on each other and mortgage rate have been discovered in New Zealand using GLS approach and for each of 11 regions via OLS model. Those effects are consistent for both methods but are changed at individual lead-lag variables and among different regions. The study empirically provides useful insight for both academia and practitioners in examining the long-run effects and cointegration between house price and rental price affordability. Application of the bootstrap robust Westerlund technique confirms the presence of strong cointegration between these two housing affordability indicators. Application of Dumitrescu and Hurlin’s (2012) Granger non-causality panel tests reveal that the statistically optimal lag length is equal to one quarter with house price affordability Granger-causing rental price affordability over the period 2000q1 to 2017q4. Application of Dumitrescu and Hurlin’s (2012) Granger non-causality test results to individual regions suggest that house price affordability Granger-causes rental price affordability in Wellington, Auckland, Canterbury, Nelson and Hawkes Bay and that rental price affordability Granger-causes house price affordability in Wellington only.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".