This section contains data information that has changed since the last release.
This section contains information about data that does not change between releases.
This information release presents national employment indicator (NEI) statistics at the national level for the month of February 2012.
Accuracy of the data
The NEI data is based on employer monthly schedule (EMS) returns processed by Inland Revenue. Delays in receiving EMS returns, due to late filing by the employer or Inland Revenue processing, are possible. Inland Revenue processing of EMS returns can also be affected by updates to systems or administrative changes. Statistics New Zealand reviews the quality of the data each month and NEI releases will be delayed if required to ensure data is of sufficient quality for release.
The last two months of data in the NEI series are based on data supplied by Inland Revenue 11 weeks and 7 weeks after the reference month. Data in these two months are rated-up using multiplication factors, to account for extra data processed between 7 and 15 weeks after the reference month. All other data in the NEI is based on data processed within 15 weeks of the reference month by Inland Revenue and is considered final. The last two months of data are provisional and are revised when new data is received.
The NEI data is based on Inland Revenue's employer monthly schedule (EMS), which contains information about monthly earnings of individuals who are taxed at source. It does not contain any information relating to the number of hours worked for those earnings.
Seasonally adjusted series
The X-12-ARIMA package is used to produce the seasonally adjusted estimates and trend estimates for the NEI series. Seasonal adjustment aims to eliminate the impact of regular seasonal events (such as annual cycles in agricultural production, or annual public holidays) on time series. This makes the data for adjacent months more comparable and ensures that the underlying movements in the time series are more visible.
All seasonally adjusted figures are revised each month. This enables the seasonal component to be better estimated and removed from the series.
Most series can be broken down into three components: trend, seasonal, and irregular. While seasonally adjusted series have the seasonal component removed, trend series have both the seasonal and the irregular components removed. Trend estimates reveal the underlying direction of movement in a series, and are likely to indicate turning points more accurately than seasonally adjusted estimates.
The trend series are calculated using the X-12-ARIMA seasonal adjustment package. They are based on an 11-, 13-, or 23-month moving average of the seasonally adjusted series, with an adjustment for outlying values.
Trend estimates towards the end of the series incorporate new data as it becomes available and can therefore change as more observations are added to the series. Revisions can be particularly large if an observation is treated as an outlier in one month, but is found to be part of the underlying trend as further observations are added to the series. Typically, only the estimates for the most recent month will be subject to substantial revisions.
Interpreting the data
The NEI covers all filled jobs (regardless of whether they are full-time or part-time). People who had multiple jobs during the reference month are counted multiple times, once for each job. The prevalence of multiple job holders, or people who change employer frequently within a month, will affect the NEI series. For example, workers in the agriculture, forestry, and fishing industry will often be counted multiple times in the March reference month, as many have multiple short-term jobs in this month due to the seasonal pattern of harvesting and production. This leads to a higher number of filled jobs in the March month when compared with other months, when people are less likely to move rapidly between employers due to seasonal work.
We recommend focusing on changes and movements in the NEI series rather than the actual level of filled jobs. The NEI data is based on EMS data processed by Inland Revenue between 7 and 15 weeks after the reference month. Historically, this has captured 97 to 98 percent of all filled jobs processed by Inland Revenue within an 18-month period. Therefore, the level of filled jobs reported by the NEI will underestimate the actual level of all filled jobs in the New Zealand labour market.
The NEI complements other Statistics NZ labour market statistics by providing an early indicator of changes in total filled jobs. You can find more information about comparing our labour market statistics on our website.
Timing of published data
Statistics NZ aims to publish the NEI on the last Tuesday of each month, within eight weeks of the reference month. There are two exceptions to this.
- The October reference month (scheduled for publication in December) is delayed until January due to timing of the data supply over the holiday period.
- The November reference month is not released in January, due to anticipated delays in data processing and production. Therefore, data released in February includes two months of new data (November and December reference months).
Statistics NZ reviews the quality of the data each month and NEI releases will be delayed, if required, to ensure data is of sufficient quality for release.
Graduated random rounding is applied to all counts in the actual series. The seasonally adjusted and trend series are calculated using the rounded actual series.
While all care and diligence is used in processing, analysing, and extracting data and information in this publication, Statistics NZ gives no warranty it is error-free and will not be liable for any loss or damage suffered by the use directly, or indirectly, of the information in this publication.
Timed statistical releases are delivered using postal and electronic services provided by third parties. Delivery of these releases may be delayed by circumstances outside the control of Statistics NZ. Statistics NZ accepts no responsibility for any such delays.
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