Using economic contribution insights to reframe advocacy

Recently, Infometrics measured the economic contribution of Indians living in New Zealand (Kiwi Indians). The methodology we used can be applied to any demographic group – nationalities, ethnicities, age groups or genders – to inform government, commercial and community engagement, and to inject much-needed economic rigor into conversations and public debate. Here, I walk you through how the method works and how an economic contribution study could work for your group.

The Kiwi Indian economic contribution is significant and most likely growing. The Kiwi Indian population is increasing, has a high employment rate, is becoming more highly qualified, and is shifting into more highly skilled work across a broader range of industries. Against the backdrop of the New Zealand India Free Trade Agreement, which came into force on 20 October 2026, we found that Kiwi Indians contributed $37.3bn in GDP and supported almost 221,000 full-time equivalent (FTE) jobs over the year to March 2025. That is equivalent to 8.6% of New Zealand's total GDP.

Kiwi Indian businesses are the powerhouse of this contribution, accounting for just under three-quarters of the total through their production of goods and services. Kiwi Indian households contribute a further quarter through their consumption, while Indian international students and Indian visitors together make up the remaining 2%.

The contribution reaches every industry (see Chart 1). The largest shares are in rental and property (almost $8bn in GDP), retail and hospitality (around $5.5bn) and professional services ($4.7bn). The full report has the detail.

We used input-output (IO) multiplier analysis to examine the economic contribution. Our IO model is based on inter-industry relationships within the New Zealand economy, enabling us to quantify how economic activity in one industry flows through to other industries and ultimately households. It uses multipliers estimated by Infometrics for the New Zealand economy which have recently been updated using the official 2024 New Zealand Input-Output tables from Stats NZ – the latest tables available. We have also estimated multipliers for each region and territorial local authority (TLA), based on the unique industry composition of their local economies. That lets us carry out economic contribution analyses for specific regions.

The model uses the 104 New Zealand Standard Industrial Output Categories (NZSIOC) industry classification used in the Stats NZ IO tables. As inputs, we measured the spending by Kiwi Indian businesses across these 104 industries, as well as spending by Indian households, visitors and international students on other businesses across the same 104 industries.

The model splits the contribution into three types (see Chart 2):

• Direct (46%). Economic activity created by Indian businesses, and by the businesses where Indian households, visitors and students spend their money.
• Indirect (16%). Economic activity created in the upstream supply chains of those businesses.
• Induced (38%). Economic activity created when staff at all of the above spend their earnings at other businesses.

For the Kiwi Indians report, we looked at four sources of economic activity.

We defined Indian businesses as those where the sole trader identifies as Indian, the majority of income goes to partners or shareholders who identify as Indian, or 100% of the business earnings go to employees who identify as Indian. This definition is based on earlier work by Te Puni Kōkiri to identify Māori businesses. The data came from the Integrated Data Infrastructure (IDI).

We defined an Indian household as any household where at least one resident identifies as Indian. We applied the Indian share of households to total household spending in the National Accounts to estimate Kiwi Indian household spending. The National Accounts also give the composition of household spending across industries. Without data on how Indian household spending differs across industries, we used the average of all households.

International student spending, including course fees and living costs, is recorded as education-related service exports to India in the New Zealand Trade Dashboard. We apportioned this total to spending categories using NZUSA’s 2017 Student Living Cost Survey, then mapped those categories to industries in our IO model.

Visitor spending is recorded as business travel and other personal travel service exports to India in Stats NZ’s Trade Dashboard. We apportioned this total to spending categories using the composition of 'rest of Asia' spending in MBIE's Monthly Regional Tourism Estimates, then mapped those categories to industries in our IO model.

In the Kiwi Indian study, double counting occurs when Indian households, visitors or students spend money at Indian businesses, and when Indian employees at Indian businesses earn wages that are spent in Indian household consumption. We estimated this and removed it.

Economic contribution is a measure of the size of a group's footprint in the economy. It isn't the same as the net effect of the group's presence, and it doesn't capture social and cultural value. Some of our inputs also rest on assumptions, such as the household spending pattern noted above. We think that is a fair price for estimates that can be produced consistently across groups and over time, but readers should treat the figures as well-founded estimates, not precise counts.

Economic contribution doesn't exist in isolation. We drew on a range of official datasets, such as the Census, to build an evidence-based narrative about the characteristics of the Kiwi Indian population that determine their economic contribution, how these had changed over time, and how they were likely to change in future.

For instance, we looked at how the size of the Kiwi Indian population had changed and projected it into the future. We examined qualification levels, fields of study, employment rates, the industries and occupations people work in, earnings and incomes, and the employment of Indian migrants in key sectors and roles such as Immigration Green List occupations.

The building blocks carry across to other groups, but not all of them, and not in the same form. Students and visitors only apply to nationality groups. Businesses can be applied to nationality, ethnicity, age or gender groups. Households can be applied to nationality, ethnicity and age groups. As an alternative to households, we could look at individuals. The business and household definitions might need to be adapted to your specific group. We would work with you to determine what definitions best capture your group's spending and business activity, based on the data available. What stays the same is the IO model, the 104-industry detail, the regional multipliers and the contextual analysis.

Being able to articulate your group's economic contribution reframes advocacy discussions around how further investment in your group can reap economic benefits for all New Zealanders. It can also bring economic rigour to public debate that is too often dominated by stereotypes, anecdotes and misconceptions. Because the method applies to any group, we can compare across groups, or examine how contribution varies by ethnicity, age or gender within your group. Repeating the analysis over time can show whether your group's position is improving, and whether a policy change or programme has moved the numbers.

Our insights can support your engagement with local and central government, chambers of commerce, trusts and commercial entities on a wide range of issues.

• Immigration policy: Evidence of your group's contribution can support your case on visa settings, migrant settlement services, language support, and migrant health and education programmes.
• Regional development: Our regional models let us focus the estimates on specific regions or TLAs, showing where your group's population is concentrated and what it adds locally. That can help councils and regional economic development agencies make a case for community infrastructure, or for retaining and attracting skilled people.
• Workforce and skills policy: Our labour market analysis can show where your group fills labour shortages, which supports arguments on skills recognition, visa settings or training pathways.

• Commercial opportunity: A group's spending and business activity tells banks, retailers, insurers and others how big the opportunity is, which can support better products and services for that community.
• Chambers of commerce and business networks: Regional contribution estimates help you make the case to local chambers to increase their membership among your group and to recruit associated sponsors.

• Funding applications: Philanthropic trusts and government funds increasingly want evidence of economic impact. Contribution data enables community organisations to quantify what they represent.
• Advocacy and representation: Peak bodies and community leaders can use the estimates to ask for a seat at the table, such as in consultations, advisory boards and public appointments.
• Community self-understanding: Your group sees itself reflected in the data, which can help strengthen identity, pride and civic participation.

If you'd like to explore what an economic contribution study could do for your group, the best starting point is a conversation. Tell us which group you represent, the question you want answered, and who you need to persuade. We'll tell you what data is available, what the analysis can show, and what a study would involve. Contact Rob Heyes, Principal Consultant.