New Zealand Wage and Salary Distributions for Individuals
Our guide uses Figure.NZ sampling and data to share income bands for wage and salary earners for the year ended 31 March 2024
Updated 30 December 2024
Summary
Data Sampling Disclaimer:
- Understanding wage distribution is essential for gaining a clear picture of New Zealand's economic landscape. Unlike average income by age data, which can mask disparities, a detailed breakdown of how wages and salaries are spread across income bands highlights New Zealand taxpayer's earnings diversity.
- While the data doesn't provide specifics about the professions or industries that generate the highest incomes, the insight that approximately 750 New Zealanders earn over $1 million annually offers some insights into the diversity of earnings across the country.
Data Sampling Disclaimer:
- Figure.NZ outlines that the data is based on a random sample and has been scaled up to population estimates. The sample is 2% of wage and salary earners, and 10% of IR3 filers.
- Income is reported to the year ended 31 March 2024; Figure.NZ has classified this as '2023 data'. 2024 data will not be considered complete until after 31 March 2025, and we expect this to be updated in mid to late 2025.
- People who did not receive any wage or salary income are not included in the dataset. Specifically excluded are New Zealand Superannuation, taxable welfare benefits, student allowances, earnings-related ACC payments, and shareholder-employee salaries (since there was no PAYE deducted).
Figure.NZ Data - Wage and Salary Distributions for the Tax Year Ended 31 March 2024
Taxable Income Band ($) | Total Number of Earners in Income Band | Percentage of Total Earners | Cumulative Percentage |
---|---|---|---|
1 to 10,000 | 383,590 | 13.18% | 13.18% |
10,001 to 20,000 | 243,330 | 8.36% | 21.53% |
20,001 to 30,000 | 207,680 | 7.13% | 28.67% |
30,001 to 40,000 | 201,880 | 6.93% | 35.60% |
40,001 to 50,000 | 222,040 | 7.63% | 43.23% |
50,001 to 60,000 | 278,730 | 9.57% | 52.80% |
60,001 to 70,000 | 280,220 | 9.63% | 62.43% |
70,001 to 80,000 | 234,890 | 8.07% | 70.50% |
80,001 to 90,000 | 182,830 | 6.28% | 76.78% |
90,001 to 100,000 | 143,020 | 4.91% | 81.69% |
100,001 to 110,000 | 115,440 | 3.97% | 85.66% |
110,001 to 120,000 | 85,550 | 2.94% | 88.59% |
120,001 to 130,000 | 65,610 | 2.25% | 90.85% |
130,001 to 140,000 | 50,510 | 1.73% | 92.58% |
140,001 to 150,000 | 40,880 | 1.40% | 93.99% |
150,001 to 160,000 | 32,090 | 1.10% | 95.09% |
160,001 to 170,000 | 24,860 | 0.85% | 95.94% |
170,001 to 180,000 | 19,820 | 0.68% | 96.62% |
180,001 to 190,000 | 15,650 | 0.54% | 97.16% |
190,001 to 200,000 | 12,070 | 0.41% | 97.58% |
200,001 to 210,000 | 10,090 | 0.35% | 97.92% |
210,001 to 220,000 | 7,730 | 0.27% | 98.19% |
220,001 to 230,000 | 6,670 | 0.23% | 98.42% |
230,001 to 240,000 | 5,530 | 0.19% | 98.61% |
240,001 to 250,000 | 4,760 | 0.16% | 98.77% |
250,001 to 260,000 | 3,900 | 0.13% | 98.91% |
260,001 to 270,000 | 3,370 | 0.12% | 99.02% |
270,001 to 280,000 | 2,790 | 0.10% | 99.12% |
280,001 to 290,000 | 2,510 | 0.09% | 99.20% |
290,001 to 300,000 | 2,150 | 0.07% | 99.28% |
300,001 to 350,000 | 7,460 | 0.26% | 99.53% |
350,001 to 400,000 | 4,400 | 0.15% | 99.68% |
400,001 to 450,000 | 2,740 | 0.09% | 99.78% |
450,001 to 500,000 | 1,750 | 0.06% | 99.84% |
500,001 to 550,000 | 1,130 | 0.04% | 99.88% |
550,001 to 600,000 | 780 | 0.03% | 99.90% |
600,001 to 650,000 | 530 | 0.02% | 99.92% |
650,001 to 700,000 | 370 | 0.01% | 99.94% |
700,001 to 750,000 | 320 | 0.01% | 99.95% |
750,001 to 800,000 | 260 | 0.01% | 99.96% |
800,001 to 850,000 | 200 | 0.01% | 99.96% |
850,001 to 900,000 | 130 | 0.00% | 99.97% |
900,001 to 950,000 | 120 | 0.00% | 99.97% |
950,001 to 1,000,000 | 110 | 0.00% | 99.97% |
1,000,001+ | 750 | 0.03% | 100.00% |
Total | 2,911,240 |
Please note that the data is provided by Figure.NZ, which has a fully interactive graph that reveals the number of earners per salary band.
Important: Why a 2% Sample Size Can Be Accurate
- We appreciate the work of Figure.NZ to bring data into the public domain. We believe a well-executed random sample ensures that every individual has an equal chance of being selected. This minimises biases and helps the sample reflect the larger population.
- Even small random samples (like 2%) can yield reliable results within a narrow margin of error for large populations. However, the accuracy decreases for smaller subgroups, such as extremely high-income earners.
- Overall, we believe the data is sufficiently accurate for identifying broad trends and insights about income distribution, as it is based on data from 1 in 50 qualifying New Zealanders - a significant and reliable sample size for this purpose.
Salary and Wage Insights, and What They Mean for You
Most working New Zealanders would like to get paid more, and, understandably, questions will be asked about what industries and professions pay approximately 20,000 people over $300,000 or the 750 people earning over $1 million.
Our view is simple - you can compare your salary and see how many people earn within the same $10,000 band, but New Zealand lacks data about what industries pay the most. Without that, it's difficult to make assumptions about upskilling, pursuing higher education, or shifting to industries where demand and salaries are increasing.
However, the data shows that if you feel your industry has a cap but want to earn more, the pathways to higher income brackets may come from working smarter, not harder. This data can provide motivation and direction if you're considering a change.
Looking for more insights? Explore our PAYE calculator and New Zealand's average salary by age.
Our view is simple - you can compare your salary and see how many people earn within the same $10,000 band, but New Zealand lacks data about what industries pay the most. Without that, it's difficult to make assumptions about upskilling, pursuing higher education, or shifting to industries where demand and salaries are increasing.
However, the data shows that if you feel your industry has a cap but want to earn more, the pathways to higher income brackets may come from working smarter, not harder. This data can provide motivation and direction if you're considering a change.
Looking for more insights? Explore our PAYE calculator and New Zealand's average salary by age.
MoneyHub Founder Christopher Walsh shares his comments about this data and its limits:
"The 2024 wage distribution data provides an intriguing snapshot of how New Zealanders are earning, but it also highlights the lack of transparency in wage and salary data collected from the IRD. While we know the number of people earning in specific income bands, we're left guessing about the industries or roles driving these figures.
However, I don't believe it's the IRD's role to collect detailed data on specific industries and professions, as doing so would raise significant privacy concerns and stretch their mandate beyond tax collection. Their focus should remain on ensuring compliance and fairness in the tax system rather than becoming a repository for granular occupational data. For New Zealanders considering a career pivot or upskilling, it is hard to identify clear opportunities to boost earnings without such insights. It's a stark reminder that career decisions need to be driven by both passion and a deep understanding of market trends - not just blind ambition." What's fascinating about the data is the sharp growth in the $100,000+ brackets over the past decade. This suggests opportunities exist for those who are strategic about their careers or entrepreneurial ventures. However, I know how hard it is in New Zealand to get ahead - these opportunities don't fall into anyone's lap. If you're earning in a lower band and want to break through, it's not just about working harder. It's about understanding where your skills are most valued and deliberately seeking those roles. If you feel underpaid, the data is a wake-up call to examine your career trajectory critically. For many, the standout statistic is that 750 New Zealanders earn over $1 million annually. While this might seem inspiring, it's essential to put it in context - these earners represent less than 0.02% of wage and salary workers. It's a reminder that building wealth often requires consistent effort, smart decisions, and some luck. If you're motivated by this data, focus on what you can control: upskilling, networking, and finding ways to provide exceptional value in your field". |
Christopher Walsh
MoneyHub Founder |