New Zealand's old‐age pension scheme and household saving
Bibliographic record
Abstract
Purpose The combination of low rates of private saving and projected increases in the fiscal burden of financing a public pension scheme for an ageing population poses a major policy challenge in New Zealand. Policy discourses espouse pension reform and the redoubling of household saving efforts. However, some of the policy options could have offsetting effects. To inform the debate with research findings, the purpose of this paper is to revisit the relationship between social security and household saving. Design/methodology/approach The paper employs a constructed social security wealth (SSW) variable in a hybrid life cycle‐permanent income consumption/saving model pioneered by Feldstein. Time series techniques are used. Findings The results show that an increase in the constructed gross SSW variable boosts saving. This suggests that concerns with accumulating assets to match the length of the implicit life expectancy at the current pension eligibility age overwhelm the view that the pension benefit is an adequate substitute for household assets. The other findings are consistent with a priori expectations: increases in disposable income boost saving; there is a significant propensity to consume out of household net wealth; and inflation and unemployment engender significant precautionary saving. Practical implications A policy to raise the retirement age may reduce the gross SSW and therefore the fiscal burden of the public pension scheme. However, in shortening the expected post‐retirement period that households have to save for, the policy may also reduce the saving rate. Originality/value Although the Feldstein approach has been used in studies in countries like Australia, Canada and the USA, a comparable study has not been undertaken in New Zealand. This study seeks to fill that void.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".