New Zealand - Unemployment

New Zealand: Unemployment

Mnemonic LBU.INZL
Unit Ths. #, SA
Adjustments Seasonally Adjusted
Quarterly 3.33 %
Data 2019 Q1 116
2018 Q4 120

Series Information

Source Statistics New Zealand
Release Household Labour Force Survey
Frequency Quarterly
Start Date 3/31/1986
End Date 3/31/2019

New Zealand: Labor

Reference Last Previous Units Frequency
Labor Force 2019 Q1 2,774 2,783 Ths. #, SA Quarterly
Labor Force Employment 2019 Q1 2,658 2,662 Ths. #, SA Quarterly
Unemployment 2019 Q1 116 120 Ths. #, SA Quarterly
Unemployment Rate 2019 Q1 4.2 4.3 %, SA Quarterly
Wage & Salaries 2019 Q1 1,974,524 1,948,161 Ths. NZD, SA Quarterly
Tertiary Industries Employment 2018 1,320,100 1,277,800 #, As at February, NSA Annual
Total Employment 2018 2,238,800 2,161,300 #, As at February, NSA Annual
Agriculture Employment 2017 176,765 169,705 # Annual

Release Information

The survey provides a regular, timely and comprehensive portrayal of New Zealand's labour force. Each quarter, a range of statistics relating to employment, unemployment, and people not in the labour force is published.

Survey Scope

The target population for the HLFS is the civilian, usually resident, non-institutionalised population aged 15 years and over. This means that 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 resident in New Zealand for less than 12 months; and those aged under 15 years.


The labour force category to which a person is assigned depends on their actual activity during a survey reference week. The following definitions, which conform closely to the international standard definitions specified by the International Labour Organization, are used for the HLFS:

Working-age population: The usually resident, non-institutionalised, civilian population of New Zealand aged 15 years and over.

Labour force: Members of the working-age population who during their survey reference week were classified as 'employed' or 'unemployed'.

Employed: All persons in the working-age population who during the reference week worked for one hour or more for pay or profit in the context of an employee/employer relationship or self-employment; or worked without pay for one hour or more in work which contributed directly to the operation of a farm, business or professional practice owned or operated by a relative; or had a job but were not at work due to: own illness or injury, personal or family responsibilities, bad weather or mechanical breakdown, direct involvement in an industrial dispute, or leave or holiday.

Unemployed: All persons in the working-age population who during the reference week were without a paid job, available for work and had either actively sought work in the past four weeks ending with the reference week, or had a new job to start within the next four weeks.

Not in the labour force: Any person in the working-age population who is neither employed nor unemployed. For example, this residual category includes persons who:

  • are retired
  • have personal or family responsibilities such as unpaid housework and childcare
  • attend educational institutions
  • are permanently unable to work due to physical or mental disabilities
  • were temporarily unavailable for work in the survey reference week
  • are not actively seeking work.

Unemployment rate: The number of unemployed persons expressed as a percentage of the labour force.

Labour force participation rate: The total labour force expressed as a percentage of the working-age population.

Seasonal adjustment

Seasonal adjustment makes data for adjacent quarters more comparable by smoothing out the effect on the times series of any regular seasonal events. This ensures that the underlying movements in the time series are more visible. Each quarter, the seasonal adjustment process is applied to the latest and all previous quarters. This means that seasonally adjusted estimates for any of the previously published quarters may change slightly.

Each series is adjusted separately. For this reason, the sum of the seasonally adjusted estimates for employment, unemployment, and people not in the labour force will usually not add up to the working-age population estimates.

Trend series

For any series, the survey estimate can be broken down into three components: trend, seasonal and irregular. Trend series have had both the seasonal and irregular components removed, and reveal the underlying direction of movement in a series. Revisions to the trend series can be particularly large, especially if any estimates were considered to be outliers, but turn out to be part of the underlying trend. Typically, only the last two or three estimates will be subject to substantial revisions

Response rates

The target response rate for the HLFS is 90 percent. The response rate is calculated by determining the number of eligible households who responded to the survey, as a proportion of the estimated number of total eligible households in the sample. The following table shows the HLFS response rates for the last five quarters. The response rate this quarter is lower than the target but still within acceptable bounds.

Two types of error are possible in estimates based on a sample survey: sampling error and non-sampling error.

Sampling errors 

Can be measured, and quantifies the variability that occurs by chance because a sample rather than an entire population is surveyed.

A change in an estimate, either from one adjacent quarter to the next, or between quarters a year apart, is said to be statistically significant if it is larger than the associated sampling error. Therefore, the example quoted above does represent a significant movement.

In general, the sampling errors associated with subnational estimates (eg breakdowns by regional council area or ethnic group) are larger than those associated with national estimates.

Non-sampling error

Is very difficult to measure, and if present can lead to biased estimates. Statistics New Zealand endeavours to minimise the impact of these errors through the application of best survey practices and monitoring of known indicators (eg non-response).