Filled jobs in New Zealand
By age group and sex, as at June 2024
| Age group | Sex | Number of filled jobs |
|---|---|---|
| 15-19 | Male | 59,524 |
| 20-24 | Male | 113,455 |
| 25-29 | Male | 134,103 |
| 30-34 | Male | 152,930 |
| 35-39 | Male | 142,561 |
| 40-44 | Male | 124,855 |
| 45-49 | Male | 108,482 |
| 50-54 | Male | 106,847 |
| 55-59 | Male | 93,567 |
| 60-64 | Male | 81,365 |
| 65+ | Male | 66,590 |
| 15-19 | Female | 61,485 |
| 20-24 | Female | 104,731 |
| 25-29 | Female | 119,253 |
| 30-34 | Female | 137,343 |
| 35-39 | Female | 131,577 |
| 40-44 | Female | 121,618 |
| 45-49 | Female | 113,865 |
| 50-54 | Female | 118,642 |
| 55-59 | Female | 103,946 |
| 60-64 | Female | 87,988 |
| 65+ | Female | 63,140 |
Definitions
Filled jobs: Paid jobs. They are measured using an average weekly calculation for the calendar month.
Gross earnings (cash): Earnings paid on a cash basis. It covers the amount paid in the reference month.It excludes retirement payments, redundancy payments, and employee benefits. The length of an employee’s pay period can cause variability in the number of pay days in the month – for example, a fortnightly pay normally occurs twice a month but, on some occasions, can occur three times in a month. This can cause volatility in the monthly series.
Gross earnings (accrued): Calculated on an accrual basis where earnings are allocated proportionally to the period in which it was earned. The accrual method removes the volatility of monthly data.
Data calculation/treatment
An error has occurred that impacts the regional series for filled jobs in the West Coast and Canterbury regions from the start of the series in May 2019. A postcode was incorrectly allocated to Westland when it should have been allocated to Selwyn. This error has been corrected and the revised data published in this release.
The revision has resulted in fewer filled jobs in the West Coast region and more in the Canterbury region.
For more information
Data provided by
Dataset name
Employment Indicators: June 2024
Webpage:
https://www.stats.govt.nz/information-releases/employment-indicators-march-2024
How to find the data
At URL provided, select 'Employment indicators: March 2024' – CSV file, download, and unzip the file.
Import & extraction details
File as imported: Employment Indicators: June 2024
From the dataset Employment Indicators: June 2024, this data was extracted:
- Rows: 23,394-24,757
- Column: 3
- Provided: 1,364 data points
This data forms the table Employment - Filled jobs by age group and sex May 2019–Jun 2024.
Dataset originally released on:
July 29, 2024
About this dataset
The Employment indicator data provides information about filled jobs, gross earnings at industry and region levels by age groups and sex. Use this dataset when wanting to measure the number of filled jobs or total earning from business perspective.
Purpose of collection
The Employment Indicators provide an early indication of changes in the labour market. There is four to five weeks between the end of the reference month and the publication date for the employment indicators.
They provide timely indicators for labour demand and are conceptually closer to LEED and the QES (Quarterly Employment Survey) than to HLFS (Household Labour Force Survey).
Method of collection/Data provider
Two data sources are being used in the production of the monthly filled jobs and gross earnings indicators series:
- From April 1999 to April 2019, Stats NZ used Employer Monthly Schedule (EMS) data. All New Zealand employers are required to report PAYE (pay as you earn) data for their employees to Inland Revenue.
- From May 2019 onwards, Stats NZ used payday filing data. Since 1 April 2019, all New Zealand employers paying more than $50,000 PAYE and Employer Superannuation Contribution tax (ESCT) per year are required to electronically file payroll information, known as payday filing. Larger employers need to file within two working days of each payday, however, smaller employers can choose to file by paper and have slightly longer timeframes.
Payday filing is timelier and has more information about employees’ pay period, making it a more flexible and useful data source than the EMS, and enables the indicators to be produced sooner than using EMS data.