Since our 2025 advice, we have delved further into our analysis. This section outlines the additional analysis that we did for our 2026 advice.
MPI Forecasts
For our 2026 advice, we reviewed the analysis that we did of the MPI workforce forecasts for our 2025 advice. This did not change, and our 2025 advice remained our starting point for our 2026 advice.
Our main source for workforce forecasts remained the extensive work undertaken by the NZIER, in consultation with industries, for the Ministry for Primary Industries and published in January 2023. This work sets the workforce supply needs for each industry by 2032 for three possible scenarios.
In all scenarios, employment grows solidly, between 8 percent and 16 percent from the 2020 base to 2032. Over the same period the overall New Zealand workforce is expected to grow around 11 percent. All scenarios point toward the need to improve skills within the industries.
The forecasts are split by ‘skills mix’ – managed, semi-autonomous, and managers – which are built on extensive mapping of these ‘skill’ titles to roles/occupations in specific industries, as determined through interviews with industry representatives.
We collated information from the ‘employment pathway’ for all our qualification to provide a list of qualifications and associated pathway occupations. This was matched to the MPI forecasts.
This formed the basis for calculating the required number of learners each year for each qualification.
Industry Engagement
What industries have told us about their skills and training needs is the key component to our advice.
We capture this information as part of our continuous engagement with industry.
In addition to this engagement, this year we undertook specific consultation with industries on our draft TEC Investment Advice for 2026.
Feedback from industry is the primary driver of changes to the advice that we provided for 2025.
GDP and Occupation Forecasting
For our 2026 Investment, as a further check against the MPI Forecasts, we undertook in-house GDP and Occupation Forecasting that provided insights into the economy and job market by displaying historical and future Gross Domestic Product (GDP) by industry and forecasting the number of people in occupations in various industries.
The model used for this project consisted of three main parts:
- Using official information (such as historic GDP by aggregated industry-by-region) and breaking this down to more detailed industries (ANZSIC class). This is done by splitting the official GDP proportional to the income of all people associated with a low-level industry (in other words, if an industry accounts for 10% of the income it is assigned 10% of the GDP). This split is corrected for industries with particularly large profits not reflected in the income of the people.
- Forecasting GDP estimates and people counts. This approach averages national GDP forecasts from different sources (Reserve Bank of New Zealand, Stats NZ, Infometrics, Statista) and determines the ratio of the GDP of each industry in each region to the national GDP over time and extrapolates this. Therefore, it takes into account both the overall state of the economy and the individual development of each industry in each region. People counts are forecasted in a similar manner.
- Determining and forecasting the count of people in each occupation. This is based almost entirely on the data from the five-yearly censuses. For each census, the distributions of occupations within each industry are determined, separately for each region and ethnicity. These distributions are then applied to the forecasted counts of people within each in industry.
Skills Forecasting – Interactive Training Demand Model for the Food and Fibre sector
We are developing a microsimulation model that will provide training demand forecasting focusing on the skills needs of the food and fibre sector.
The model uses existing workforce forecasts and other important drivers/inputs to forecast training demand for specific industries, specific skills and by level of training required. This model goes beyond just predicting the future – it allows us to play out different situations and test ideas. Starting with the current workforce details, the model mimics real-world workforce activities for each person, such as attraction, retention, and training. We can then try out various scenarios that impact demand and supply, like predicting the number and skills needed by industries (demand) and estimating the available workforce and skills (supply).
We are continuing to refine the model and are not yet in the position to use it for specific elements of our TEC Investment Advice. However, we have used the initial build to investigate some overarching training dynamics for our industries. This modelling indicates that, all other things being equal, if current training levels are only maintained, there will not be enough trained people to meet industries’ current skills needs.