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Population Pyramid

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Voting Age Population Pyramid

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New Voters Calculation Methodology

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Data Interpolation Methodology

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Why is interpolation needed?

The official subnational population projections provided by Stats NZ are typically released for specific years, often at 5-year intervals (e.g., 2023, 2028, 2033, 2038, 2043). However, we need population estimates for years that fall between these official projection points to analyse the potential voting-age population for specific election years (2026, 2029, 2032, 2035, 2041). Interpolation allows us to estimate these intermediate values.

How is linear interpolation performed?

This tool uses linear interpolation to estimate the population for the required election years. Here's how it works:

Grouping: The population data is grouped by unique combinations of Region (Area), Ethnicity, Sex, Age Band, and Projection scenario (Medium projection is used for this analysis).
Finding Bracketing Years: For a target election year (e.g., 2029) that does not have official data, the function identifies the closest available projection years before (e.g., 2028) and after (e.g., 2033) within each specific demographic group.
Estimating Population: It assumes a straight-line (linear) change in population between the known data points (e.g., between 2028 and 2033). The population for the target year (2029) is then calculated based on where it falls proportionally along that straight line.
Applying to All Groups: This process is repeated for every combination of region, ethnicity, sex, and age band to build a complete estimated dataset for the target election years.

Example: Interpolating for 2029

Available data: 2028 and 2033 projection points
Target year: 2029
Position: 2029 is 1 year into a 5-year span (1/5 = 20% of the way)
Calculation: Population₂₀₂₉ = Population₂₀₂₈ + 0.2 × (Population₂₀₃₃ - Population₂₀₂₈)
Result: Estimated population for 2029 based on linear trend

Quality Considerations

Strengths:

Based on official Stats NZ demographic projections
Maintains consistency across demographic groups
Simple, transparent methodology
Preserves demographic trends from official projections

Limitations:

Assumes linear population change between projection points
Cannot account for unexpected demographic events
Less accurate for areas with highly variable population trends
Interpolated values are estimates, not official projections

Purpose and Interpretation:

Purpose: This interpolation provides the best available estimate for the voting-age population structure in specific election years based on the trends shown in the official 5-yearly projections. It allows for meaningful analysis even when official data for the exact year of interest is unavailable.

Interpretation: Use interpolated estimates as indicative values for planning and analysis purposes. For the most precise demographic projections, refer to the official Stats NZ projection years.

More Information

Working Age Population Pyramid

Dashboard Guide

Population Demographics Explorer

About This Application

Key Features:

Interactive Population Pyramids: Explore age and gender distributions with hover details.
Regional Analysis: Compare demographic trends across New Zealand's regions.

Electoral Insights: Examine voting-age populations and new voter estimates.
Data Export: Download selected data and complete datasets for further analysis.
Multiple Projections: View low, medium, and high projection scenarios.

About iNZight Analytics

Background & Purpose

We help you use data to tell your story. Decision-makers need to collect, access, and understand data to make informed choices. We design new data-collection and analysis tools, improve access to existing data, and increase data literacy.

We design our data services and research based on your needs, rather than just producing datasets and software. With extensive experience as data users, we create approaches that work for users first — then we handle the technical complexities.

Our Services

Data Collection Design: Efficient, effective research projects tailored to your needs, including Māori research perspectives.
Data Analysis: Specialising in applied social and epidemiological analysis, including Statistics New Zealand Integrated Data Infrastructure.
Training & Education: Making data learning fun, accessible, and relatable through workshops and courses.
Data Sovereignty: Supporting communities in research design that meets their goals and aspirations.
Visualisation & Storytelling: Creating interactive tools that make data accessible whilst keeping it secure.
Consulting: From project management to hourly advisory work.

Data for tāngata, by tāngata, with tāngata. We help communities design research that meets their aspirations, providing guidance on research design, planning, and Māori data sovereignty decision-making.

Application Authors

Eric Marshall, Gemma Ngari & Andrew Sporle
iNZight Analytics

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This application demonstrates iNZight Analytics' commitment to making complex demographic data accessible and actionable for decision-makers across Aotearoa New Zealand.

Population Projection Explorer

Please select a demographic dataset to explore:

Aotearoa Population Projections

Pacific Populations in Aotearoa

Pacific Populations in the Pacific

Select Year:

Select Population:

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Select Election Year:

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Select Projection:

Display Population:

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Export Data:

Dashboard Guide

New Voters Calculation Methodology

Data Interpolation Methodology

Why is interpolation needed?

How is linear interpolation performed?

Example: Interpolating for 2029

Quality Considerations

Strengths:

Limitations:

Purpose and Interpretation:

Select Year:

Working age group:

Select Population:

Select Geography:

Right Panel Display:

Export Data:

Dashboard Guide

Population Demographics Explorer

About This Application

Key Features:

About iNZight Analytics

Background & Purpose

Our Services

Application Authors