International Migration and the Distribution of Income in New Zealand Metropolitan and Non-Metropolitan Areas
Bibliographic record
Abstract
Since the 1980s, income inequality in New Zealand has been a growing concern - particularly in metropolitan areas. At the same time, the encouragement of permanent and temporary immigration has led to the foreign-born accounting for a growing share of the population; this is disproportionally so in metropolitan areas. This paper investigates the impact of immigration, by skill level and length of stay, on the distribution of income in metropolitan and non-metropolitan areas. We apply decomposition methodologies to data obtained from the 1986, 1991, 1996, 2001, 2006 and 2013 Censuses of Population and Dwellings. We find that increases in the immigrant share of population in an area have an inequality-increasing and area-specific effect. Changes in immigrant-group-specific distributions of income are inequality reducing in non-metropolitan areas but inequality increasing in metropolitan areas. Inequality increased in metropolitan areas because the overall inequality-increasing effect of immigration is larger than the inequality-reducing changes for the New Zealand-born. The opposite is the case in non-metropolitan areas: the overall inequality-reducing change in the income distribution of the New Zealand born there is larger than the inequality-increasing effect of immigration. The methodologies adopted here can also benefit the study of income distribution changes in countries with similar immigration policies, such as Australia and Canada.
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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 | 0.001 | 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 | 0.001 |
| 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".