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Quarterly Employment Survey: September 2012 quarter
Embargoed until 10:45am  –  06 November 2012
Data quality

Period-specific information
This section contains information about data that has changed since the last release.

General information
This section contains information about data that does not change between releases.

Period-specific information

Reference period

The reference period for the Quarterly Employment Survey: September 2012 quarter is the payweek ending on, or before, 20 August 2012.

Response rate

The survey met its desired response rate in the September 2012 quarter.

The desired response rate by weighted FTEs is 89.0 percent. The September 2012 quarter response rate by weighted FTEs was 89.8 percent.

General information

Data source

The Quarterly Employment Survey (QES) is a sample of approximately 18,000 business locations selected from a population of economically significant enterprises in surveyed industries. Weights are allocated to each of the selected business locations. These represent the population weights based on employee counts sourced from the Business Frame.

An economically significant enterprise is defined as one that meets at least one of the following criteria:

  • has greater than $30,000 annual GST expenses or sales
  • has at least three employees for its rolling mean employment (the average employee count over the previous 12 months)
  • recorded over $40,000 of income in the IR10 annual tax return
  • is part of a group of enterprises
  • is a new GST registration that is compulsory, special, or forced
  • is registered for GST and involved in agriculture or forestry.

Businesses in the following Australian and New Zealand Industrial Classification 2006 (ANZSIC06) industries are not surveyed as part of the QES:

  • A01 Agriculture
  • A02 Aquaculture
  • A04 Fishing, hunting, and trapping
  • A052 Agriculture and fishing support services
  • L6711 Residential property operators
  • O7552 Foreign government representation
  • O76 Non-civilian defence staff
  • S96 Households employing staff
  • T99 Not included elsewhere.


Imputation is the process of estimating data for surveyed businesses that do not respond. One of two methods of imputation is used.

  • Ratio imputation – used for businesses entering the sample in the current quarter. Data is imputed using the employee count from the Business Frame. This assumes the relationship between the employee count and earnings and hours data is robust.
  • Historical imputation – used for businesses that are in the sample in consecutive quarters. The imputed data is calculated by multiplying the previous quarter’s data by the average movement of responding businesses that are in the same industry and of similar size.

For further information about the imputation methods, or the effects of imputation on the final dataset, please email

Accuracy of survey data

Survey data is subject to two types of possible error: sampling error and non-sampling error.

Sampling error is a measure of variability that occurs by chance because a sample of eligible businesses, rather than the entire population, is surveyed. The magnitude of the sampling error is controlled by the size of the sample and sound sample selection practice.

Non-sampling error includes errors arising from biases in the patterns of response and non-response, inaccuracies in reporting by respondents, errors introduced by modelled data, and errors in the recording and coding of data. Non-sampling error is, by definition, difficult to measure. The magnitude of non-sampling error is not measured.

Seasonally adjusted and trend series

The X-12-ARIMA package is used to produce the seasonally adjusted estimates and trend estimates for selected QES series. Seasonal adjustment aims to eliminate the impact of regular seasonal events on time series. This makes the data for adjacent quarters more comparable, and ensures that the underlying movements in the time series are more visible.

All seasonally adjusted figures are revised each quarter. This enables the seasonal component to be better estimated and then removed from the series.

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.

Trend estimates towards the end of the series incorporate new data as it becomes available. They 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 quarter, 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 quarter will be subject to substantial revisions.

Consistency with other labour market statistics

Statistics NZ publishes a suite of labour market employment statistics. These include the following releases:

  • Household Labour Force Survey
  • Linked Employer-Employee Dataset.

Because of differences in coverage and timing, each of these measures provides a different view of employment. See Comparing our labour market statistics for more information.

Comparing the QES and the labour cost index (LCI)

The QES average earnings and LCI salary and wage rates are measures of labour costs paid by New Zealand businesses in the form of salary and wages.

The QES and LCI information releases are published on the same day each quarter and provide useful information on labour costs. The LCI provides a good measure of pure wage inflation, whereas the QES is a good measure of average hourly earnings, average number of hours paid in a week, or average weekly earnings from wages or salaries.

The following series are discussed below:

  • QES average ordinary time hourly earnings (QES)
  • LCI salary and ordinary time wage rates (LCI)
  • LCI analytical unadjusted salary and ordinary time wage rates (LCI analytical unadjusted)
QES average ordinary time hourly earnings

The QES has a sample of approximately 18,000 business locations selected from a population of economically significant enterprises in surveyed industries. The QES includes jobs filled by paid employees of all ages. The QES does not include the earnings of those working in agriculture or fisheries or several smaller industries (see Data source for all exclusions), nor earnings from self-employment.

The QES reference period is the payweek ending on, or before, the 20th of the middle month of the quarter.

The QES measures the average gross earnings paid to employees. The QES reflects changes in the composition of the paid workforce, and changes to earnings paid by surveyed businesses within industries and between industries. These compositional influences do not affect the LCI series, as it controls for changes in surveyed job descriptions and the standard of job performed, as well as for changes in the relative importance of job descriptions within each sector, occupation, and industry.

Compositional effects between industries can affect the QES. This happens when industries with higher or lower earnings than the average total hourly earnings for all industries change in relative importance, and contribute more or less towards the average total hourly earnings for all industries.

For example, average total hourly earnings in the retail trade industry are lower than the national average, and represents about 10 percent of the total paid hours of all industries combined. If the retail trade industry increased total paid hours relative to other industries, the average total hourly earnings for all industries would fall, everything else being held constant, because there is a relative increase in influence from a lower-paying industry.

Compositional changes within industries can affect the QES in different ways. Changes in the composition of the paid workforce are reflected in the QES. Such changes could arise from changes between male and female, part-time and full-time, qualifications, experience, occupations, and the performance of employees. Changes can also arise from changes to paid earnings by surveyed businesses within industries.

For example, the average ordinary time hourly earnings for the manufacturing industry increased from $24.51 in the June 2011 quarter to $24.81 in the September 2011 quarter. This may reflect individual manufacturing employees being paid a higher wage or salary, or higher-paying businesses joining the industry. It may also reflect a change toward higher-paid occupations, or more highly skilled employees, within a manufacturing business. Any of these events would lift manufacturing average ordinary time hourly earnings. The change in skill level would be reflected in the unadjusted LCI, but not the LCI salary and ordinary time wage rates.

LCI salary and ordinary time wage rates

The LCI covers jobs filled by paid employees in all occupations and in all industries except private households employing staff. The LCI includes jobs filled by paid employees of all ages. The LCI tracks a sample of nearly 6,000 jobs at 2,100 businesses.

Each quarter, salary and wage rates are surveyed to find what employers pay at the 15th of the middle month of the quarter.

This LCI measures changes in the gross salary and ordinary time wage rates that employers pay to have the same job completed to the same standard. This means that only changes for the same quality and quantity of work are reflected in the index. In practice, this means surveying a given set of job descriptions and making adjustments for any changes to hours worked, duties performed, experience, qualifications, or performance of employees filling the jobs. For example: an adjustment would be made to a skilled job being tracked in the LCI if a new employee who had just completed a bachelor’s degree, with no prior work experience, replaced an employee with a bachelor’s degree and 10 years’ experience in the role. The term ‘fixed quantity’ refers to a specific amount of labour, in particular hours worked per week.

The LCI shows changes arising from collective employment agreements, and changes to match market rates, retain or attract staff, or reflect the cost of living. Changes to reflect individual performance, experience, qualifications, and responsibilities are not shown.

The LCI controls for changes in sector, industry, and occupation by assigning fixed weights. Weights reflect the relative importance of job descriptions for different combinations of sectors of ownership, occupation, and industry. This means a change in salary and wage rates for managers – which has a high relative importance – has more influence on the overall series than a change of the same size in salary and wages for clerical and administrative workers.

Labour Cost Index (Salary and Wage Rates) has information on the weights for LCI salary and wage measures.

LCI analytical unadjusted salary and ordinary time wage rates

The LCI analytical unadjusted series has the same coverage and timing as the LCI.

The unadjusted LCI measures changes in salary and ordinary time wage rates for a fixed quantity of labour. It fixes the relative importance of industries and occupations, but does not fix the quality of labour within occupations. This means that any movement in the series will reflect changes in the cost of living, changes to match market rates, and to retain/attract staff, and may also include changes in labour quality. This could be a change in employee performance, qualifications, responsibilities and experience.

User guide for wage and income measures has more information on the various income and wage measures.

Timing of published data

QES data is released within six weeks of the end of the reference quarter.

More information

See also information about the Quarterly Employment Survey.


While all care and diligence has been 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.


Our information releases are delivered electronically by third parties. Delivery may be delayed by circumstances outside our control. Statistics NZ does not accept responsibility for any such delay.

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