Labour Market Statistics: June 2022 quarter

Period-specific information Response Rates Survey Reference period Response rate Sample rate HLFS Each week during the quarter (1 April 2022 – 30 June 2022) Target: 90 percent Achieved: 76.6 percent Target: 76 percent Achieved: 69.3 percent QES The pay week ending on, or before, 20 May 2022 Target: 90 percent Achieved: 89.1 percent N/A LCI Pay rates at 15 May 2022 Target: 94 percent Achieved: 93.0 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 June 2022 quarter was 21.1 percent. This compares with 20.0 percent in the March 2022 quarter and 20.7 percent in the June 2021 quarter. Data quality We continue to investigate possible ways of improving the resilience of our data following HLFS data collection challenges. 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 smaller population groups. See Labour Market Statistics: December 2021 quarter, Period-specific information for more information about the affected subgroups and possible adjustments being tested. 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. In the June 2022 quarter, seven 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 Sep 2021 .. .. .. .. .. .. Dec 2021 .. .. .. .. .. Z Mar 2022 .. .. .. .. .. P Jun 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 Jun 2021 0.10 0.06 0.04 -0.95 -0.08 -0.01 Sep 2021 0.05 0.01 0.06 -0.09 -0.02 0.00 Dec 2021 -0.02 -0.04 -0.13 0.47 0.05 0.01 Mar 2022 -0.14 -0.04 0.03 0.66 0.06 -0.01 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 Jun 2021 0.03 0.03 0.05 -0.43 -0.04 -0.01 Sep 2021 0.07 0.02 -0.03 -0.31 -0.03 0.01 Dec 2021 0.00 0.00 0.14 0.18 -0.01 0.01 Mar 2022 -0.21 -0.11 -0.67 1.52 0.23 -0.10 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 0.20 0.21 Female employed 0.06 0.10 0.25 0.27 Male unemployed 0.54 0.91 2.16 2.21 Female unemployed 0.53 0.97 2.11 2.26 Male not in labour force 0.10 0.17 0.39 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 June 2022 quarter was 89.1 percent. End of petroleum refining activity The end of petroleum refining activity in New Zealand in March 2022 is reflected in the QES quarters results, beginning in the June 2022 quarter. This change resulted in some businesses being classified to different Australian New Zealand Standard Industrial Classification (ANZSIC06) industries in June 2022 quarter compared with March 2022 quarter. Activity has moved from being captured in manufacturing to wholesale trade, or transport, postal, and warehousing. Businesses are classified to the ANZSIC06 industry that best represents their predominant activity. 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 June 2022 quarter, respondents were asked to report pay rates on the reference date of May 15th 2022. The response rate was 93.0 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 en-NZ