Bibliographic record
Abstract
This report assesses the impact that policy changes to increase (or decrease) development contributions (DCs) are likely to have on housing markets in the context of proposals by Auckland Council officers to include post-2031 infrastructure expenditure in DCs so as to better reflect the long-run public infrastructure costs caused by housing development.Development contributions (DCs) are a tax on converting property to more intensive uses, levied to fund infrastructure to support urban growth. They are long-established and commonly used in cities around the world. Questions of their economic incidence have been thoroughly examined.The size of the proposed DC changes in Drury is in line with changes happening elsewhere in high- growth and high-value cities like Toronto, Sydney, and Los Angeles.The analysis here shows that the common claim that DCs are passed through to house prices and rents is not supported by theory or evidence. Dwelling prices reflect the capitalised value of the housing services dwellings provide, as determined within larger housing markets, and so additional development costs cannot be passed forward to rents or prices but instead will be passed back to land in the form of lower land values.For the Drury-Opāheke investment priority area the proposed policy change is expected to increase DCs by around \$50,000 per dwelling to a total of \$84,500 per dwelling. Although this increase is significant in percentage terms, DCs around this level are not large enough to render housing development unviable given the high incremental value from changing properties in the area to residential use.The proposal is expected to have no impact on the pace of development across Auckland as a whole, though it may alter the sequence of sites taken up for new housing across the city. Whether development proceeds faster or slower in the areas subject to higher DCs depends on several factors. On the one hand, an additional cost to development may increase the return to holding land undeveloped – but on the other, earlier delivery of infrastructure funded by DCs is likely to accelerate development. Regardless, these local impacts are likely small relative to the influence of other market factors.The neutrality of DCs with respect to house prices is confirmed by the best empirical evidence available. The highest-quality econometric studies find no relationship between changes in DCs and prices, in accordance with established theory.An ongoing charge on property owners in the form of a targeted rate is economically equivalent if levied on the same base. If the base is changed from a per-dwelling rate to a per-land area rate, there may be small changes to incentives that bear on the size and style of dwellings constructed.
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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 | 0.004 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".