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Plumbers in the Northland Region, New Zealand

Estimates and projections for the year ended March 2017–2020

Limitations of the data

The employment forecasts included in this report are based on forecasts of quarterly GDP growth, contained in the Consensus Forecasts released for March 2017. The TWI, terms of trade and 90-day rates forecast used are based on the forecasts by the Treasury. The employment and unemployment rate forecasts by the Ministry are informed by the latest HLFS results.

Data provided by

Ministry of Business, Innovation, and Employment

Dataset name

Short-term Employment Forecasts: 2017-2020 - May 2017


Import & extraction details

File as imported: Short-term Employment Forecasts: 2017-2020 - May 2017

From the dataset Short-term Employment Forecasts: 2017-2020 - May 2017, this data was extracted:

  • Sheet: All Regions
  • Range: B36:EC133
  • Provided: 6,664 data points

This data forms the table Employment - Forecast employment by occupation and region 2017–2020.

Dataset originally released on:

May 11, 2017

About this dataset

The Short-term Employment Forecast: 2016-19 presents employment forecasts for 2016 to 2019 (March years). The forecasts will inform the Ministry’s advice relating to immigration priorities, and priority setting for tertiary education and industry training over the same period.

Method of collection/Data provider

The Ministry uses a short-term forecasting model that draws on the latest macroeconomic forecasts by the Treasury, covering detailed forecasts of terms of trade, exchange rates and interest rates.17 The detailed macroeconomic forecasts enable economic activity in broad industries to be forecast consistent with overall economic growth.
The Ministry used model-based forecasts of industry level economic activity and productivity (the latter moderated by the Ministry for consistency across individual sectors) to derive forecasts of industry employment. The industry level employment forecasts are then used to forecast employment by occupations and by skill levels by using the Census based occupational shares across industries.