Labour Market Statistics: March 2019 quarter

#Period-specific information ##Response Rates Survey Reference period Response rate Sample rate HLFS Each week during the quarter (31 December 2018 – 31 March 2019) Target: 90 percent Achieved: 82.8 percent Target: 76 percent Achieved: 74.7 percent QES The pay week ending on, or before, 20 February 2019 Target: 89 percent Achieved: 86.6 percent N/A LCI Pay rates at 15 February 2019 Target: 94 percent Achieved: 95.0 percent N/A See New quality measures for the Household Labour Force Survey for more information on the sample rate and response rates. ##LCI and QES The Government increased the minimum wage by $1.20 to $17.70 per hour on 1 April 2019. Stats NZ expects to see these changes reflected in the June 2019 quarter. However, the LCI has started to see some minor movement within the retail, accommodation and food services, and manufacturing industries. ##HLFS ###Adjustment to data series In the December 2018 quarter, an adjustment (in addition to seasonal adjustment) was made to ten high-level data series. The adjustment was implemented to improve the accuracy of, and coherence between, the trend and seasonally adjusted series. While select series were subject to a direct adjustment, several other series were also impacted. We have reviewed the data adjustment implemented in the December 2018 quarter and have concluded that no changes should be made to the data adjustment at this time. We will continue to review the prior adjustments until the December 2019 quarter, at which time a final decision will be made regarding next steps, if any. See Labour Market Statistics: December 2018 quarter – metadata for more information on the data adjustment and a list of series adjusted. Underutilisation series The underutilisation series were not subject to last quarter’s direct data adjustment. Users are advised to be cautious when drawing comparisons with December 2018 quarter data and to focus on longer-term trends. Not in Employment, Education or Training series The distribution of Stats NZ’s data collection throughout the December 2018 quarter affected the rise in NEET youth. More people than usual were surveyed towards the end of the quarter, when tertiary education had ended for the year. This means Stats NZ was more likely to have captured youth who had ended their studies, and not yet started work or further study. Users are advised to be cautious when drawing comparisons with December 2018 quarter data and to focus on longer-term trends. ###Impact of the Christchurch terrorist attack on 15 March 2019 The Christchurch terrorist attack on 15 March 2019 did not significantly impact the achieved sample rate (ASR). Just over 75.0 percent of respondents were interviewed prior to 15 March 2019. As expected, the ASR did begin to decline after this date, but not so far as to influence the distribution of responses. The ASR for the March 2019 quarter is not unusual in terms of its level or weekly distribution. Our analysis concludes the degree of accuracy of estimates for the March 2019 quarter HLFS are comparable with previous quarters. ###Impact of new outcomes-based measure of migration In November 2018, Stats NZ introduced the new outcomes-based measure of migration. This was reflected in International migration: December 2018, published on 18 February 2019. HLFS estimated working-age population for the March 2019 quarter partly reflects the new migration measure. It is reflected in the population estimates for the December 2018 quarter but is not yet reflected in the estimate of change for the quarter due to net migration. Net migration is based on historic permanent and long-term migration data. We expect to revise the working-age population and HLFS estimates (September 2013 quarter–June 2019 quarter) ahead of the Labour market statistics: September 2019 quarter release, scheduled for 6 November 2019. ###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 2018 Sep 2018 P Dec 2018 P Mar 2019 ###HLFS pre- and post-calibration weight The following figure shows that while the distribution of the pre- and post-calibration weights differs within a quarter, the difference between the weights typically does not change from quarter to quarter. The undercoverage rate indicates how representative the pre-calibrated sample is. The higher the undercoverage rate, the less representative the pre-calibrated sample. Usually the undercoverage rate in the HLFS is around 20 percent. The overall undercoverage rate for the HLFS in the March 2019 quarter was 19.0 percent. This compares with 20.2 in the December 2018 quarter and 18.7 percent in the March 2018 quarter. ###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. The December 2018 quarter unemployment rate was unchanged at 4.3 percent after we applied seasonal adjustment. 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 2018 0.06 0.09 0.60 -0.94 -0.17 -0.05 Jun 2018 0.00 -0.01 -0.12 -0.77 0.01 -0.02 Sep 2018 -0.01 -0.04 0.39 0.59 0.06 0.11 Dec 2018 -0.05 -0.06 -0.96 1.49 0.12 -0.05 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 2018 0.02 0.04 0.00 -0.45 -0.07 -0.04 Jun 2018 0.02 0.02 0.35 -0.71 -0.10 0.02 Sep 2018 0.04 0.04 0.79 -0.46 0.03 0.03 Dec 2018 -0.25 -0.23 -3.20 4.72 1.41 -0.07 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 0.08 0.17 0.17 Female employed 0.06 0.11 0.24 0.24 Male unemployed 0.48 0.76 1.81 1.81 Female unemployed 0.53 0.88 1.95 2.00 Male not in labour force 0.10 0.17 0.39 0.38 Female not in labour force 0.09 0.14 0.37 0.39 ##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