Worker turnover rate in the health care and social assistance industry in New Zealand

By sex, 1999 Q4–2023 Q4, % of jobs

The following information applies to all values in the table. Industry: Q, Measure: Workers turnover rate
Quarter	Sex	% of total jobs
1999 Q4	Female	12.5%
1999 Q4	Male	11.4%
2000 Q1	Female	15.6%
2000 Q1	Male	18.2%
2000 Q2	Female	13.6%
2000 Q2	Male	12.5%
2000 Q3	Female	12.8%
2000 Q3	Male	12.3%
2000 Q4	Female	12.8%
2000 Q4	Male	12.2%
2001 Q1	Female	16%
2001 Q1	Male	17.4%
2001 Q2	Female	13.3%
2001 Q2	Male	11.9%
2001 Q3	Female	14.1%
2001 Q3	Male	14%
2001 Q4	Female	12.5%
2001 Q4	Male	11.4%
2002 Q1	Female	15.3%
2002 Q1	Male	16.5%
2002 Q2	Female	14.1%
2002 Q2	Male	13.2%
2002 Q3	Female	13%
2002 Q3	Male	12.7%
2002 Q4	Female	12.6%
2002 Q4	Male	11.4%
2003 Q1	Female	13.6%
2003 Q1	Male	14.5%
2003 Q2	Female	15.3%
2003 Q2	Male	14.5%
2003 Q3	Female	12.2%
2003 Q3	Male	11.8%
2003 Q4	Female	12.5%
2003 Q4	Male	11.6%
2004 Q1	Female	13.8%
2004 Q1	Male	14.4%
2004 Q2	Female	13.6%
2004 Q2	Male	12.7%
2004 Q3	Female	12.2%
2004 Q3	Male	12.3%
2004 Q4	Female	12.4%
2004 Q4	Male	11.3%
2005 Q1	Female	13.2%
2005 Q1	Male	14%
2005 Q2	Female	17.2%
2005 Q2	Male	16.5%
2005 Q3	Female	13.9%
2005 Q3	Male	13.7%
2005 Q4	Female	12.1%
2005 Q4	Male	11.3%
2006 Q1	Female	13.8%
2006 Q1	Male	14.2%
2006 Q2	Female	15%
2006 Q2	Male	14.6%
2006 Q3	Female	12.2%
2006 Q3	Male	12.6%
2006 Q4	Female	12.3%
2006 Q4	Male	11.9%
2007 Q1	Female	12.8%
2007 Q1	Male	13.9%
2007 Q2	Female	15.4%
2007 Q2	Male	15.4%
2007 Q3	Female	11.9%
2007 Q3	Male	12.1%
2007 Q4	Female	11.5%
2007 Q4	Male	10.9%
2008 Q1	Female	13.2%
2008 Q1	Male	13.9%
2008 Q2	Female	14.2%
2008 Q2	Male	13%
2008 Q3	Female	11.6%
2008 Q3	Male	11.2%
2008 Q4	Female	11.5%
2008 Q4	Male	10.2%
2009 Q1	Female	12.9%
2009 Q1	Male	14%
2009 Q2	Female	11.5%
2009 Q2	Male	11.2%
2009 Q3	Female	9.5%
2009 Q3	Male	9.6%
2009 Q4	Female	9.6%
2009 Q4	Male	9.4%
2010 Q1	Female	12.2%
2010 Q1	Male	12.7%
2010 Q2	Female	17.4%
2010 Q2	Male	19.1%
2010 Q3	Female	11%
2010 Q3	Male	11.9%
2010 Q4	Female	10.2%
2010 Q4	Male	10.6%
2011 Q1	Female	11.8%
2011 Q1	Male	13.6%
2011 Q2	Female	13.1%
2011 Q2	Male	13.6%
2011 Q3	Female	10.6%
2011 Q3	Male	10.5%
2011 Q4	Female	9.6%
2011 Q4	Male	9.6%
2012 Q1	Female	12%
2012 Q1	Male	13.8%
2012 Q2	Female	10.8%
2012 Q2	Male	11.1%
2012 Q3	Female	9.7%
2012 Q3	Male	10.3%
2012 Q4	Female	9.9%
2012 Q4	Male	9.7%
2013 Q1	Female	10.4%
2013 Q1	Male	11.3%
2013 Q2	Female	11.3%
2013 Q2	Male	11.3%
2013 Q3	Female	10.4%
2013 Q3	Male	10.8%
2013 Q4	Female	10%
2013 Q4	Male	9.3%
2014 Q1	Female	11.7%
2014 Q1	Male	12.2%
2014 Q2	Female	10.5%
2014 Q2	Male	10%
2014 Q3	Female	11%
2014 Q3	Male	10.9%
2014 Q4	Female	10%
2014 Q4	Male	9.8%
2015 Q1	Female	12.6%
2015 Q1	Male	13.2%
2015 Q2	Female	12.3%
2015 Q2	Male	12.4%
2015 Q3	Female	10.4%
2015 Q3	Male	10.5%
2015 Q4	Female	10.1%
2015 Q4	Male	9.8%
2016 Q1	Female	12.5%
2016 Q1	Male	12.9%
2016 Q2	Female	11.7%
2016 Q2	Male	11.3%
2016 Q3	Female	10.9%
2016 Q3	Male	11%
2016 Q4	Female	10.7%
2016 Q4	Male	10.3%
2017 Q1	Female	12.9%
2017 Q1	Male	13.4%
2017 Q2	Female	12.8%
2017 Q2	Male	12.2%
2017 Q3	Female	11.1%
2017 Q3	Male	11.1%
2017 Q4	Female	10.3%
2017 Q4	Male	9.7%
2018 Q1	Female	17.5%
2018 Q1	Male	18.8%
2018 Q2	Female	15.2%
2018 Q2	Male	14.2%
2018 Q3	Female	11.5%
2018 Q3	Male	11.8%
2018 Q4	Female	10.9%
2018 Q4	Male	11.2%
2019 Q1	Female	13.2%
2019 Q1	Male	13.6%
2019 Q2	Female	12.3%
2019 Q2	Male	11.8%
2019 Q3	Female	12.3%
2019 Q3	Male	11.9%
2019 Q4	Female	10.5%
2019 Q4	Male	10.5%
2020 Q1	Female	13.4%
2020 Q1	Male	14.5%
2020 Q2	Female	10.7%
2020 Q2	Male	11%
2020 Q3	Female	9.8%
2020 Q3	Male	10.2%
2020 Q4	Female	9.8%
2020 Q4	Male	9.3%
2021 Q1	Female	11.1%
2021 Q1	Male	12%
2021 Q2	Female	14.5%
2021 Q2	Male	14.2%
2021 Q3	Female	12.2%
2021 Q3	Male	12.6%
2021 Q4	Female	11.1%
2021 Q4	Male	11.1%
2022 Q1	Female	13.7%
2022 Q1	Male	13.6%
2022 Q2	Female	14.6%
2022 Q2	Male	14.8%
2022 Q3	Female	12.1%
2022 Q3	Male	12.2%
2022 Q4	Female	11.6%
2022 Q4	Male	11.2%
2023 Q1	Female	13.3%
2023 Q1	Male	13.8%
2023 Q2	Female	13.9%
2023 Q2	Male	14.2%
2023 Q3	Female	11.8%
2023 Q3	Male	11.7%
2023 Q4	Female	10.2%
2023 Q4	Male	10%

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

http://www.stats.govt.nz/browse_for_stats/income-and-work/employment_and_unemployment/LEED-quarterly-tech-notes.aspx
http://nzdotstat.stats.govt.nz/OECDStat_Metadata/ShowMetadata.ashx?Dataset=TABLECODE7013&Lang=en

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

Stats NZ

Dataset name

Linked Employer-Employee Dataset: LEED measures by industry (based on ANZSIC06) and sex December 2023 quarter

Webpage:

https://explore.data.stats.govt.nz/vis?tm=by%20industry%20%28based%20on%20ANZSIC06%29%20and%20sex&pg=0&snb=4&df[ds]=ds-nsiws-disseminate&df[id]=LEED_Q2W_007&df[ag]=STATSNZ&df[vs]=1.0

How to find the data

Data is displayed at URL provided. To create this dataset, click on download and “Filtered data in tabular text (CSV)”.
Industries were selected only at the lowest node to prevent the Aotearoa Data Explorer from generating duplicate records.

Import & extraction details

File as imported: Linked Employer-Employee Dataset: LEED measures by industry (based on ANZSIC06) and sex December 2023 quarter

From the dataset Linked Employer-Employee Dataset: LEED measures by industry (based on ANZSIC06) and sex December 2023 quarter, this data was extracted:

Rows: 2-66,292
Column: 13
Provided: 66,291 data points

This data forms the table Jobs - All LEED measures by industry and sex 1999 Q2–2023 Q4.

Dataset originally released on:

February 06, 2025

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.

Worker turnover rate in the health care and social assistance industry in New Zealand

By sex, 1999 Q4–2023 Q4, % of jobs

About this data

Related Content