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Labour Market Statistics: September 2015 quarter
Embargoed until 10:45am  –  04 November 2015
Data quality

Period-specific information
This section is for information that changes between periods.

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

Period-specific information

Response rates

 Survey Reference period   Response rate
 HLFS Each week during the quarter (29 June 2015–27 September 2015) Target: 90 percent
Achieved: 85.8 percent
 QES The pay week ending on, or before, 20 August 2015 Target: 89 percent
Achieved: 89.5 percent
 LCI Pay rates at 15 August 2015 Target: 94 percent
Achieved: 94.9 percent

See New quality measures for the Household Labour Force Survey for more information on the sample rate and response rates.

Rounding in LCI

We round index numbers to the nearest index point, which affected some percentage increases in the September 2015 quarter. Below is a table of percentage changes calculated on unrounded index numbers.

Percentage changes calculated from rounded and unrounded index numbers, September 2015 quarter
   Quarter percentage change Annual percentage change 
 All salary and wage rates  rounded  unrounded  rounded  unrounded
 Private sector  0.4  0.4  1.7  1.8

 Central government





 Ordinary time wage rates





 Private sector





 Local government  0.4  0.4  2.1  2.0

General information

Comparison between HLFS and QES


HLFS – measures the number of people employed from an individual perspective. Measures the number of hours people usually and actually work. Regional estimates are more robust due to how they are weighted.
QES – use when wanting to measure the number of filled jobs from a business’s perspective, or when wanting to measure the number of hours businesses pay for.


HLFS – includes agricultural workers, self-employed workers, unpaid family workers, and those on unpaid leave among the employed. Limited to the working-age population, aged 15 years and older.
QES – jobs filled by overseas workers resident in New Zealand for less than 12 months are included. Filled jobs are not limited by age.

Reference period

HLFS – surveys all weeks of the quarter.
QES – based on a reference week in the middle of the quarter.

Comparison between LCI and QES


LCI – measures changes in wage inflation.
QES – measures the change in hourly earnings a business has to pay on average across all jobs.


LCI – jobs filled by paid employees in all occupations and in all industries except private households employing staff.
QES – does not include the earnings of those working in agriculture, fisheries, or earnings from self-employment.



  • Adjusted LCI measures the rates employers pay to have the same job completed to the same standard.
  • Controls for changes in sector, industry, and occupation by assigning fixed weights. Weights reflect relative importance of job descriptions for different combinations of sectors of ownership, occupation, and industry.
  • Unadjusted LCI measures the rates employers pay to have the same job completed to a differing standard (allowing the quality of labour within occupations to improve).


  • Reflects changes in composition of paid workforce, and changes to earnings paid by surveyed businesses within industries, and between industries.
  • Compositional effects between industries can affect the QES when industries with higher or lower earnings than the average total hourly earnings for all industries change in relative importance (eg make up a bigger share of the total hours).
  • Compositional changes within industries can affect the QES, as the composition of the paid workforce is reflected (eg the occupations that firms hire).

Data sources


We source HLFS data through surveying and interviewing across a period of 13 weeks. The information obtained relates to the week before the interview. We first interview respondents face-to-face at their home. Subsequent interviews are by telephone wherever possible. Respondents can also to file self-completed questionnaires.

Where practicable, we obtain information directly from each household member. Otherwise, a proxy interview is conducted, in which we obtain details from another adult in the household.


Data source is quarterly electronic and postal surveys. We collect quarterly data from businesses for the middle month of the respective quarter.


A quarterly postal survey of employers provides data for a fixed set of job descriptions. Each quarter, we survey salary and wage rates for what employers pay at the 15th of the middle month of the quarter.

Survey samples


The sample contains about 15,000 private households and about 30,000 individuals each quarter. We sample households on a statistically representative basis from areas throughout New Zealand. The HLFS is sampled so that is representative of geographic region, urban and rural areas, ethnic density, and socio-economic characteristics of the population.

Households stay in the survey for two years. Each quarter, one-eighth of the households in the sample is rotated out and replaced by a new set of households.

Following every census we review the HLFS sample. After the 2013 Census, we implemented an improved sample design.

The new sample will be rolled in over eight quarters. Each quarter, one-eighth of the households in the old sample is rotated out and replaced by a set of households in the new sample. By changing the sampling units one rotation group at a time, we reduce the risk of affecting the labour force outcomes. The first set of respondents in the improved design was rotated in for the December 2014 quarter.

Every quarter we monitor the quality of the sample. We did not find any evidence to suggest the new rotation group was driving unexpected movements in labour force outcomes.


Sample of approximately 18,000 business locations selected from a population of economically significant enterprises in surveyed industries.


We collect salary and ordinary time wage rates for about 6,000 job descriptions each quarter (and nearly 1,000 overtime descriptions).

Approximately 2,000 businesses provide information.



The target population for the HLFS is the civilian, usually resident, non-institutionalised population aged 15 years and over. The statistics in this release do not cover:

  • long-term residents of homes for older people, hospitals, and psychiatric institutions
  • inmates of penal institutions
  • members of the permanent armed forces
  • members of the non-New Zealand armed forces
  • overseas diplomats
  • overseas visitors who expect to be a resident in New Zealand for less than 12 months.

The QES samples economically significant enterprises in surveyed industries. An economically significant enterprise is 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.

The QES does not include data from the agriculture, fisheries, and several smaller industries.


Jobs filled by paid employees in all occupations and in all industries except private households employing staff. We extended coverage to include jobs filled by paid employees aged under 15 years when the index was reweighted and re-expressed on a base of the June 2001 quarter (=1000).



Obtaining a sample that represents the population is essential when it comes to producing reliable labour force estimates. The HLFS goes through three stages of weighting to achieve this.

First, we give every household in the HLFS sample an initial weight. This is based on the probability of the household being selected for the survey. Currently the HLFS is in a period of sample transition, where we are replacing existing sampling units with units drawn using a different design and frame. The sample transition will occur between the December 2014 and September 2016 quarters. This will affect the probabilities of a given household being selected into the survey. We apply an adjustment to the initial weights during the transition period to use data collected from both new and existing sampling units.

Second, this weight is adjusted, by month and region, for households that did not respond. This results in a ‘non-response-adjusted’ weight.

Third, we adjust the sample weights to known population benchmark totals (calibration process). The HLFS benchmarks are: overall sex by five-year age groups, Māori by sex by age group, and the 12 regions. This process results in a final weight for each household.

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.

Age distribution in the HLFS, by age group

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 September 2015 quarter was 18.8 percent. This compares with 20.3 percent in the June 2015 quarter and 15.3 percent in the September 2014 quarter.


We allocate weights to each of the selected business locations. These represent the population weights based on employee counts sourced from the Business Register.


Each job description used in calculating the index is assigned a weight that reflects the relative importance of the job description within its sector of ownership, industry, and occupation group.

Weights were calculated using: 2013 Census of Population and Dwellings information on the relative importance of occupations within each sector by industry group, Business Register (previously known as Business Frame) information on the relative importance of industry groups within each sector, and pay rates surveyed in the June 2014 quarter.  

Sampling errors

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 we survey a sample of eligible businesses, rather than the entire population. 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.

If a movement is larger than its corresponding sampling error, it is statistically significant.


Sampling errors are calculated using the jackknife method. It is based on the variation between estimates of different subsamples taken from the whole sample.

When we conduct a proxy interview, more than 90 percent of related people answer correctly for key variables. A typical proxy rate in the HLFS is around 30–35 percent. This excludes quarters when a supplement was attached to the HLFS.


Sampling errors are calculated using the Horvitz Thompson method.


Based on a purposive sample (ie based on judgement); sampling errors are difficult to estimate.


The labour market statistics release includes specific statistics about industry, occupation, study, ethnicity, and region. This section lists the classifications we use for these statistics.

Email for further information about the classifications we use.


Imputation is the process of estimating data for surveyed respondents or businesses that do not respond.


We impute for people who have missing values for their sex, age, or full-time employment variables (ie whether the respondent is in or seeking full-time or part-time employment).  


Ratio imputation – used for businesses entering the sample in the current quarter. We use employee count from the Business Register to impute.

Historical imputation – used for ongoing businesses. Data is imputed by multiplying the previous quarter’s data by the average movement of responding businesses of similar characteristics.


We carry forward the previous price for the relevant position that did not reply. 

Email for further information about the imputation methods, or the effects of imputation on the final dataset.

Seasonal adjustment

For any series, we can break the estimates down into three components: 

  • trend (direction of the series) – for example, women increasing their labour force participation over time 
  • seasonal (typical calendar events) – for example, a large pool of students looking for work in the summertime
  • irregular (random movements) – for example, increase in employment for a one-off event.

Seasonally adjusted series have the seasonal component removed. Trend series have both the seasonal and irregular components removed, and reveal the underlying direction of movement in a series.

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

See Seasonal adjustment in Statistics New Zealand for more information.



We round seasonally adjusted and trend series to the nearest thousand. Unadjusted series are rounded to the nearest hundred. We calculate quarterly and annual changes for figures on unrounded numbers. The one exception is percentage-point changes – which are based on rounded figures.


Filled jobs, FTEs, total hours, and total earnings are rounded to the nearest hundred. Average hours, average earnings, and hourly earnings are rounded to two decimal places.


Index numbers are rounded to the nearest whole number. We calculate percentage changes on rounded numbers. For this reason, total percentage changes for an index may not appear consistent with the percentage changes for its components.

LCI-specific information

Index calculation formula and base

We calculate the LCI using the price-relatives form of the base-weighted Laspeyres formula, and express it on a base of the June 2009 quarter (=1000). The index’s calculation base is periodically updated to reflect changes in the sector of ownership of organisations.

Quality control

The LCI is a quality-controlled measure. Only changes in salary and wage rates for the same quality and quantity of work are reflected in the index. We achieve this by asking respondents to provide reasons for movements in salary and wage rates. If a movement is due to more than one reason, we also ask the respondents to indicate how much of the movement is due to each reason.

In theory, these job descriptions should remain fixed between index revisions. In practice, many descriptions change over time, usually as a result of changes to contractual arrangements or because specific employees are being tracked through time. If a newly negotiated contract involves an increase in the number of ordinary time hours worked per week, then we amend the description and an adjustment is made to ensure that the pay rate movement used in the index relates to the same quantity of work as specified in the new contract.

Similarly, rates being paid for job descriptions in the survey may change partly or wholly because employees undertaking these jobs have become more experienced, more (or less) proficient or productive, better qualified, have taken on additional responsibilities, or have been promoted. Components of salary and wage rate movements that are due to changes of this type in the quality of work are not reflected in index movements. The policy of excluding increases due to service increments and merit promotions is consistent with this approach.

We also exclude one-off payments in lieu of pay rises, as they do not result in changes to pay rates, as such.

Regular fixed allowances and regular fixed bonuses are included in surveyed pay rates. Where included, these are specified in job descriptions. However, we exclude payments such as commissions and irregular bonuses, as these payments are usually performance related.

In instances where allowances, penal rates, and other payments (eg commissions), which have not previously been included in surveyed rates, are incorporated into base rates, only the overall effect of such changes is reflected in the index.

Contract indexation

Parties that engage in commercial contracts use a range of price indexes produced by Statistics NZ in their indexation clauses (also known as contract escalation clauses). An indexation clause provides both parties to a contract with an agreed procedure for adjusting an originally contracted price, to reflect changes in costs or prices during the life of the contract.

Contract indexation: A Guide for Businesses (published 2009) provides information on the price indexes we produce and issues relating to their use in indexation clauses. The guide also outlines some points to consider when preparing an indexation clause, and includes an example of the mechanics of a simple indexation formula.

Analytical unadjusted series

An analytical unadjusted index series, based on ordinary time pay rates collected in the LCI sample, is available in the tables of this release (see the 'Downloads' box). The analytical unadjusted series is an additional measure intended to complement the official LCI and QES indicators and provide customers with a fuller picture on the wages front. The analytical unadjusted series is not affected by relative employment shifts between industries and between occupations, but, in addition to price change, it does reflect quality change within occupations.

In simple terms, the approaches we take in compiling the published and analytical unadjusted series are summarised as:

Published index: 

  • often tracks employees, but does not show performance-related increases or service increments 
  • commonly links in new employees (without showing change).

Analytical unadjusted index: 

  • often tracks employees, and shows performance-related increases and service increments 
  • shows any change when new employees replace incumbents.

The LCI is a price index that measures change in pay rates for a fixed quality and quantity of labour input. We show price-related change in rates reported by respondents, such as those to reflect the cost of living, to match market rates, to retain staff, and to attract staff. We don't show changes in reported rates that are the result of service increments, merit promotions, increases (and decreases) relating to the performance of individual employees, and change in hours worked are not shown in the index, as they are considered to represent quality or quantity change.

The analytical unadjusted index retains fixed weights for occupations within industries, within sectors of ownership, but is based on a matched sample of reported rates for the previous and current quarters before quality control. In addition to price change, it reflects quality change within occupations, such as change in the performance of individual employees, change in the qualifications, responsibility or experience of employees filling surveyed positions, and the effect of different employees replacing incumbent employees in surveyed positions at lower or higher rates.

Rates for which the pay periods reported by respondents (eg per year, week, or hour) differ from those for the previous period, and rates where change is wholly or partly due to change in hours worked, are excluded from the matched sample. Typically, we exclude between 1 and 2 percent of surveyed rates from the unadjusted index each quarter for these reasons.

We calculate the analytical unadjusted index using a matched sample of reported rates for the previous and current quarters. Expenditure weights are used to weight movements in reported rates from the previous quarter to the current quarter. To derive the expenditure weights, we use the price changes (after quality control) of job positions in the sample (from the base period to the previous quarter) to scale base-period expenditure weights (which are then assigned to job positions in the sample).

Note: the LCI is designed to measure change in pay rates for a fixed quality and quantity of labour input. The sample of surveyed pay rates is not particularly suitable for preparing a measure that includes quality change. This is due in part to the fact that some positions in the survey follow individual employees (with corresponding pay rates subject to both quality and price change) and some positions specify particular points on pay scales (which are usually subject only to price change). In general,  we track individual employees for positions surveyed in the private sector, and for positions surveyed in the public sector there is a mix of points on pay scales and individual employees being tracked.

The analytical unadjusted index reflects quality change within occupations. How well this is measured partly depends on how well the sample represents entrances and exits of employees, and on whether the sample replacement practice is unbiased in this regard (eg in some cases, replacement employees are incumbent employees filling other positions rather than new employees filling the existing positions – this can happen when there is a delay filling vacancies in surveyed positions). In addition, the analytical unadjusted index tends to reflect the effect of turnover in, and the cessation of, existing positions, but not the price and/or quality effect associated with employees being hired to fill new positions. An unadjusted measure designed from scratch might use the average pay rate, within each surveyed firm, of all employees filling jobs in each surveyed occupation.

The published LCI is a fixed-weight price index that measures changes in pay rates for a fixed quality and quantity of labour input. The index is not affected by relative shifts in the occupational and industrial composition of the pool of paid employees. It is useful in the context of the extent to which changes in businesses' input labour costs might put pressure on the output prices they charge for goods and services.

The analytical unadjusted LCI series has fixed weights for occupations within industries, within sectors of ownership, so is not affected by relative employment shifts between industries and occupations. However, it does reflect quality shifts within occupations. The index uses weights based on the mix of employment in occupations and industries evident in 2013.

It does not take account of the effect of any subsequent shifts in the mix of employment in occupations and industries. In addition, it will not reflect:

  • the effect of very new or emerging occupations and industries
  • the effect of employers mitigating the effect of skill shortages by substituting away from occupations showing high relative price change to occupations showing lower relative price change (eg from carpenter to builder's labourer, or from registered nurse to nurse aide).

Timing of published data

Labour market statistics are published within six weeks after the end of the quarter's reference period.


Only people authorised by the Statistics Act 1975 are allowed to see your individual information, and they must use it only for statistical purposes. Your information is combined with similar information from other people, households or businesses to prepare summary statistics.

More information

See more information about the Household Labour Force Survey
See Quarterly Employment Survey for more information.

Statistics in this release have been produced in accordance with the Official Statistics System principles and protocols for producers of Tier 1 statistics for quality. They conform to the Statistics NZ Methodological Standard for Reporting of Data Quality.


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 accept responsibility for any such delay.

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