Worker turnover rate in the mining and utilities industries in New Zealand
By age group, 2022 Q2–2023 Q1, % of jobs within each age group
Quarter | Age group | % of total jobs |
---|---|---|
2022 Q2 | 15-19 | 31.8% |
2022 Q2 | 20-24 | 24.1% |
2022 Q2 | 25-29 | 18.4% |
2022 Q2 | 30-34 | 16.1% |
2022 Q2 | 35-39 | 13.9% |
2022 Q2 | 40-44 | 12% |
2022 Q2 | 45-49 | 11.2% |
2022 Q2 | 50-54 | 11.8% |
2022 Q2 | 55-59 | 10.4% |
2022 Q2 | 60-64 | 9.9% |
2022 Q2 | 65+ | 11.8% |
2022 Q3 | 15-19 | 28.5% |
2022 Q3 | 20-24 | 19.4% |
2022 Q3 | 25-29 | 17.7% |
2022 Q3 | 30-34 | 14.9% |
2022 Q3 | 35-39 | 13.3% |
2022 Q3 | 40-44 | 12.6% |
2022 Q3 | 45-49 | 11.7% |
2022 Q3 | 50-54 | 10.2% |
2022 Q3 | 55-59 | 9% |
2022 Q3 | 60-64 | 8.9% |
2022 Q3 | 65+ | 10.6% |
2022 Q4 | 15-19 | 28.4% |
2022 Q4 | 20-24 | 18.8% |
2022 Q4 | 25-29 | 12.3% |
2022 Q4 | 30-34 | 11.8% |
2022 Q4 | 35-39 | 9.5% |
2022 Q4 | 40-44 | 8.5% |
2022 Q4 | 45-49 | 8.5% |
2022 Q4 | 50-54 | 7.1% |
2022 Q4 | 55-59 | 7.8% |
2022 Q4 | 60-64 | 6.3% |
2022 Q4 | 65+ | 8.4% |
2023 Q1 | 15-19 | 31.9% |
2023 Q1 | 20-24 | 18.8% |
2023 Q1 | 25-29 | 13.2% |
2023 Q1 | 30-34 | 11.5% |
2023 Q1 | 35-39 | 10.1% |
2023 Q1 | 40-44 | 8.9% |
2023 Q1 | 45-49 | 9.3% |
2023 Q1 | 50-54 | 9.3% |
2023 Q1 | 55-59 | 8.2% |
2023 Q1 | 60-64 | 8.5% |
2023 Q1 | 65+ | 10.9% |
Definitions
Job: a unique employer-employee pair present on an EMS in the reference quarter.
Full-quarter jobs: jobs that exist continuously over the reference quarter.
Total filled jobs: The number of jobs (defined as an employer-employee match) on the 15th of the middle month of the reference quarter. Does not distinguish between part-time and full-time jobs.
Accessions: The number of employees who have joined employers since the previous reference date.
Separations: The number of employees who have left employers since the previous reference date.
Worker turnover rate: The ratio of the average of the total accessions and separations to the average of the total jobs in the reference quarter (t) and the previous quarter (t-1), as represented in the formula:
[ (accessions + separations)/2 ] / [ (jobs(t) + jobs(t-1))/2 ].
Job creation: The number of jobs created, since the previous reference date, when businesses expand or start up. For example, a business employing 100 workers with 10 accessions and five separations has job creation of five.
Job destruction: The number of jobs lost, since the previous reference date, when businesses contract or shut down. For example, a business employing 100 workers with five accessions and 15 separations has job destruction of 10.
Job turnover rate: The ratio of the average of the total creations and destructions to the average of the total jobs in the reference quarter (t) and the previous quarter (t-1), as represented in the formula:
[ (creation + destruction)/2 ] / [ (jobs(t) + jobs(t-1))/2 ].
Mean/median earnings: Mean (average) or median earnings of all full-quarter jobs.
Mean/median earnings for continuing jobs: Mean (average) or median earnings for jobs that were full-quarter in the reference quarter and previous quarters.
Mean/median earnings for new hires: Mean (average) or median earnings for jobs that were full-quarter in the reference quarter and began sometime in the previous quarter, but were not present in the four previous quarters.
Mean/median earnings ratio: The ratio of the mean or median earnings for new hires to the mean or median earnings for continuing jobs.
Total earnings: The sum of all earnings paid in the reference quarter, including employees with invalid IRD identifiers and individuals under 15 years of age.
For more information
Inclusions
LEED covers all individuals (‘employees’) who receive income from which tax is deducted at source. These payments are made by organisations that are registered with Inland Revenue. Note that the data from LEED includes social assistance payments, such as paid parental leave, student allowances, benefits, pensions, and Accident Compensation Corporation payments, although these are excluded from the quarterly measures.
The fundamental basis of the LEED quarterly measures is ‘jobs’.
For inclusion in the LEED quarterly statistics, the job must:
- relate to a person 15 years of age and over
- have PAYE tax deducted at source
- be in relation to ‘paid employment’ rather than a social assistance payment
- have a valid IRD identifier.
An exception is the total earnings measure, which includes all jobs with PAYE tax deducted at source (irrespective of age and IRD identifier) apart from those relating to social assistance payments.
All the earnings measures represent quarterly earnings inclusive of tax. They include payments reported as lump sums to Inland Revenue.
Data provided by
Dataset name
Linked Employer-Employee Dataset: LEED measures by age and industry (based on ANZSIC06) March 2023 quarter
Webpage:
How to find the data
Data is displayed at URL provided. All variables were selected to create this dataset.
In order to avoid duplicates, only select the industries (19) and age groups (12) at the most detailed level of disaggregation.
Import & extraction details
File as imported: Linked Employer-Employee Dataset: LEED measures by age and industry (based on ANZSIC06) March 2023 quarter
From the dataset Linked Employer-Employee Dataset: LEED measures by age and industry (based on ANZSIC06) March 2023 quarter, this data was extracted:
- Rows: 2-256,945
- Column: 13
- Provided: 256,944 data points
This data forms the table Jobs - All LEED measures by industry and age group 1999 Q2–2023 Q1.
Dataset originally released on:
May 23, 2024
About this dataset
The LEED dataset is created by linking a longitudinal employer series from the Stats NZ Business Register to a longitudinal series of EMS payroll data from Inland Revenue.
Purpose of collection
Official quarterly statistics produced from LEED measure labour market dynamics at various levels – including industry, region, territorial authority, firm size, sector, sex, and age – providing an insight into the operation of New Zealand's labour market. Stats NZ releases other official labour market statistics that show changes in employment at an aggregate level. Statistics from LEED, such as job and worker flows, help to explain what causes these aggregate movements and are therefore useful for explaining changes in the labour market.