Labour Market Statistics: March 2022 quarter ^en-NZ

Labour Market Statistics: March 2022 quarter ^en-NZ

Period-specific information

Response Rates

Survey	Reference period	Response rate	Sample rate
HLFS	Each week during the quarter (1 January 2022 – 31 March 2022)	Target: 90 percent Achieved: 82.5 percent	Target: 76 percent Achieved: 76.2 percent
QES	The pay week ending on, or before, 20 February 2022	Target: 90 percent Achieved: 92.0 percent	N/A
LCI	Pay rates at 15 February 2022	Target: 94 percent Achieved: 92.1 percent	N/A

See Household Labour Force Survey sources and methods: 2016 for more information on the sample rate and response rates.

HLFS

Coverage rates

Usually, the undercoverage rate in the HLFS is around 20 percent. The overall undercoverage rate for the HLFS in the March 2022 quarter was 20.1 percent. This compares with 18.8 in the December 2021 quarter and 20.8 percent in the March 2021 quarter.

Data quality

We continue to investigate possible ways of improving the resilience of our data. This follows challenges in HLFS data collection faced during the December 2021 quarter.

We will let our customers know about adjustments we make to the data as a result of any improvements.

In the meantime, we continue to recommend looking at longer term trends and taking sample errors into account when looking at changes in estimates for the regions and groups most impacted.

See Labour Market Statistics: December 2021 quarter, Period-specific information for more information about the affected subgroups and possible adjustments being tested.

Publication of trend series

In the March 2022 quarter, the publication of the trend series has resumed as there is now sufficient data to allow for the calculation of stable trend series.

Publication of the trend series was originally suspended in the September 2021 quarter due to the impact of Covid-19 on the observed seasonal pattern, as trends are slow to respond to change.

New Sample

Following every census, we review the HLFS sample design. The updated sample design will be implemented over eight quarters (two years), starting in the December 2020 quarter.

For the March 2022 quarter, six of the eight waves are from the new sample.

Outliers

During the seasonal adjustment process, X-13-ARIMA-SEATS can give less weight to the irregular component. Specifically, if the estimated irregular component at a point in time is sufficiently large compared with the standard deviation of the irregular component as a whole, then the irregular component at that point can be downweighted or removed completely and re-estimated. We refer to such observations as partial- and zero-outliers, respectively. In practice, the downweighting of outliers does little to seasonally adjusted data, but the impact of the outliers on the trend series will generally be reduced. However, if an outlier ceases to be an outlier as more data becomes available, then significant revisions to the trend series become possible.

Outliers
Quarters	Male employed	Female employed	Male unemployed	Female unemployed	Male not in the labour force	Female not in the labour force
Jun 2021	..	..	..	..	..	..
Sep 2021	..	..	..	..	..	..
Dec 2021	..	..	..	..	..	Z
Mar 2022	..	..	..	..	..	..

Key: .. – no adjustment. P – partial weight. Z – zero weight.

Revisions to HLFS

Each quarter, we apply the seasonal adjustment process to the latest quarter and all previous quarters. Every estimate is subject to revision each quarter as new data is added, which means that seasonally adjusted estimates for previous quarters may change slightly. In practice, estimates more than two years from the end-point will change little.

This table lists the changes in estimates between the current and previous quarters for the seasonally adjusted data.

Percent revision from last estimate, seasonally adjusted
Quarter	Male employed	Female employed	Male unemployed	Female unemployed	Male not in labour force	Female not in labour force
Mar 2021	0.05	0.06	-0.32	0.16	0.03	-0.02
Jun 2021	0.01	0.02	0.10	-0.03	0.00	0.01
Sep 2021	-0.02	-0.02	0.18	-0.12	-0.02	-0.01
Dec 2021	-0.06	-0.08	0.11	-0.05	0.00	0.03

This table presents revisions for the trend estimates. Trend revisions are generally larger than those of the seasonally adjusted data.

Percent revision from last estimate, trend
Quarter	Male employed	Female employed	Male unemployed	Female unemployed	Male not in labour force	Female not in labour force
Mar 2021	0.02	0.02	-0.16	0.07	0.02	0.00
Jun 2021	0.03	0.04	-0.01	-0.02	0.00	0.00
Sep 2021	0.01	0.03	0.21	-0.06	0.00	0.01
Dec 2021	-0.11	-0.16	0.14	-0.52	-0.08	0.04

The table below shows the average of all such absolute revisions, expressed relatively, and indicates to what extent the current estimates might be revised when the revised data for the next quarter becomes available.

Mean absolute percent revisions
	Seasonally adjusted		Trend
	1-step	4-step	1-step	4-step
Male employed	0.05	0.09	0.19	0.21
Female employed	0.06	0.10	0.25	0.27
Male unemployed	0.55	0.90	2.17	2.21
Female unemployed	0.52	0.95	2.10	2.24
Male not in labour force	0.10	0.17	0.40	0.40
Female not in labour force	0.10	0.15	0.38	0.41

QES

Response rate

The response rate for the Quarterly Employment Survey in the March 2022 quarter was 92.0 percent.

Understanding inter-quarter variability in the Quarterly Employment Survey

Stratified sample design divides a population into smaller mutually exclusive groups, called strata. Random samples are drawn within these strata. The goal of stratification is to group similar units, by industry and employment count for QES. Reducing variability in output variables between units within each stratum allows a more efficient and representative selection of units to be surveyed over the population.

Different strata have different probabilities of selection and sample weights, according to the expected level of variability and contribution to the population’s outputs. For example, the very largest businesses may have a 100% chance of selection and carry a weight of 1, so that they represent only themselves. Meanwhile, very small businesses have a low chance of selection, and those sampled carry a large weight to represent many units.

Each quarter, units in QES are allocated to strata based on ANZSIC division and specific cut-offs in employment count. A sample is drawn according to the probabilities of selection in each stratum. Typically, a similar group of businesses is sampled each quarter since selection at the strata level is based on a fixed span of permanent random numbers, to which each business is assigned. Similarity of the sample between quarters promotes accuracy in inter-quarter movements. Conversely, sample changes due to business births, deaths and movements between strata reduce accuracy in inter-quarter movements.

Prior to March 2021, the old sample design maintained a constant strata allocation but still experienced some changes in the sample due to business births and deaths. The new sample design reallocates strata each quarter to maintain an efficient and representative sample. The downside of regular reallocation is larger variability in inter-quarter movements than previously experienced, especially at the industry level.

Data based on full-coverage administrative sources may be more suitable than sample data such as QES for studying inter-quarter movements at lower levels. Please refer to the Monthly Employment Indicator (MEI) or Business Employment Data (BED) series for more information.

LCI

The LCI measures changes in salary and wage rates for a fixed quantity and quality of labour. LCI data is collected by postal and electronic surveys.

For the March 2022 quarter, respondents were asked to report pay rates on the reference date of February 15th 2022. The response rate was 92.1 percent, finishing below the target response rate of 94 percent. The response rate for key firms was 100 percent, meeting the target of 100 percent.

General information and methodology

For general information and methodology on the specific surveys within the labour market statistics release, please see the following Datainfo+ pages:

• Household Labour Force Survey
• Labour Cost Index
• Quarterly Employment Survey

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