Kaipara District economic profile

Metadata: Annual profile

Time period

This economic profile reports on March years (eg. 2018 refers to the 12 months to March 2018) for all indicators except population (as at June), dairy sector statistics (May year), and government social service expenditure and beneficiary data (June years).

Gross Domestic Product

Gross Domestic Product (GDP) measures the value economic units add to their inputs. It should not be confused with revenue or turnover. A company’s value adding is broadly equivalent to its sales revenue less the cost of materials (eg steel for making motor cars) and services (eg telecommunications) purchased from other firms.

Total GDP is calculated by summing the value added to all goods and services for final consumption – i.e. it does not include the value added to goods and services used as intermediate inputs for the production of other goods as this would result in double counting. As a result, GDP estimates should not be confused with revenue/turnover/gross output.

In this profile Gross Domestic Product for each region and territorial authority (TA) is estimated by Infometrics. A top down approach breaks national production-based GDP (published by Statistics New Zealand) down to territorial authority level by applying TA shares to the national total. Each TA’s share of industry output is based on the share of earnings measured in the Linked Employer Employee Data (LEED), which is, in turn, based on taxation data. This approach captures differences in productivity between TAs and changes in productivity over time. Our estimates are benchmarked on regional GDP published by Statistics New Zealand

GDP is measured in constant 2010 prices .

Tourism GDP

Our estimates of tourism GDP are measured in 2010 prices and make use of the Tourism Satellite Accounts (TSA) published by Statistics New Zealand, in conjunction with data on guest nights, visitor expenditure data from MBIE, and Infometrics’ regional GDP model. The TSA estimates the contribution of the tourism industry to GDP nationally. For the years 2009-2013, we have apportioned tourism GDP from the TSA to each territorial authority (TA) using constrained shares of visitor expenditure from MBIE’s visitor expenditure data.

For the years before 2009, we have calculated growth rates in each TA’s tourism GDP, by adjusting TSA industry ratios (that summarise the proportion each industry’s output associated with tourism) and applying these adjusted ratios to our estimates of the TA’s GDP. Our adjustment takes into consideration each TA’s relative exposures to industries and guest night shares compared to the national economy. The estimates for each TA are then benchmarked on the national total from the TSA.


In this profile, we present all GDP estimates in constant 2010 prices. GDP presented in constant prices is sometimes referred to as real GDP. By using constant prices we remove the distractionary effect of inflation. It enables us to meaningfully compare GDP from one year to the next.

Industrial classification

This profile uses industry categories from the 2006 Australia New Zealand Standard Industrial Classification (ANZSIC). The ANZSIC is a hierarchical classification with four levels, namely divisions (the broadest level also referred to as 1-digit categories), subdivisions (3-digit), groups (4-digit) and classes (7-digit).There are approximately 500 7-digit industries.

This profile also uses a grouping of 54 industries. These are the industries used by Statistics New Zealand in the national accounts.


Unallocated items include taxes levied on the purchaser rather than the producing industry (such as GST, import duties, and taxes on capital transactions), and items that cannot easily be allocated to a specific industry (such as the seasonal adjustment balancing item). A seasonal adjustment balancing item is necessary to ensure that the sum of all seasonally adjusted industries can be reconciled with total GDP.

Broad economic sectors

The primary sector extracts or harvests products from the earth and includes agriculture, forestry, fishing, and mining. The secondary sector produces manufactured and other processed goods and includes manufacturing, electricity, gas and water, and construction. The tertiary sector includes all service industries that are not knowledge intensive, such as retail trade, and food and accommodation services. The quaternary sector includes knowledge intensive service industries. ‘Other’ includes owner occupied property operation and unallocated activity.

Knowledge intensive industries

Knowledge-intensive industries are industries that satisfy two basic criteria: At least 25 per cent of the workforce must be qualified to degree level and at least 30 per cent of the workforce must be employed in professional, managerial, as well as scientific and technical occupations.

Employment by industry

Employment is measured as an average of the four quarters making up each year. The unit of measurement is filled jobs.

Regional employment numbers are from Infometrics’ Regional Industry Employment Model (RIEM). The model draws heavily on quarterly and annual Linked Employer Employee Data (LEED) published by Statistics New Zealand. RIEM differs from data from Business Demography in that it is a quarterly series (BD is annual) and it includes both employees and self-employed, whereas BD only includes employees.

Industrial classification can be found here.


Self-employment rates are from Annual Linked Employer Employee Data (LEED).


Regional level unemployment rates are sourced from Statistics New Zealand’s Household Labour Force Survey. Trends in the number of Jobseekers at TA level are used to break down regional unemployment rates to TA level. To reduce volatility the unemployment rate is presented as an average for the last four quarters.

NEET (Not in Education, Employment, or Training)

NEET rates measure the proportion of young people aged 15-24 that are not in education, employment or training.

Infometrics estimates NEET rates by territorial authority. The following datasets are used in to estimate territorial authority NEET rates: Household Labour Force Survey, Census data, Jobseeker Support recipients by age, and transient secondary school student numbers.

Territorial authority estimates are benchmarked on annual average regional NEET rates from Statistics New Zealand's Household Labour Force Survey, which at this level of disaggregation can be volatile from year to year. Large year-to-year changes are likely to be partially caused by sampling errors in the HLFS, rather than actual fundamental shifts in NEET rates. As the Household Labour Force Survey is the official measure of youth NEET in NZ, we benchmark our data to align with published NEET rates.

Tourism employment

Our estimates of tourism employment leverage off our tourism GDP estimates. We are able to use our understanding of the proportion of output in each industry in a territorial authority that is associated with tourism and apply this proportion to underlying employment levels in that industry. Summing up tourism employment by industry gives us an indication of the total number of jobs in a region that are attributable to the tourism industry.

Knowledge intensive employment

Knowledge intensive employment is measured as employment in industries (measured at the 7-digit industry level) which are defined as knowledge intensive.

Employment by occupation

Employment in each industry is converted to occupational employment using the relationship between industry and occupational employment observed in various Population Censuses. The Population Census measures the occupational composition of employment in each industry and how this changes over time. Occupations confirm to the categories used in the Australian New Zealand Standard Classification of Occupations (ANZSCO).

Employment by qualification and field of study

Employment by occupation is converted to employment by qualification using the unique matching between occupation and the five qualification or skill levels used in the Australian New Zealand Standard Classification of Occupations (ANZSCO). Fields of study for each combination of occupation and skill are obtained from Population Census. Shares of employment in a particular occupation and skill combination for each field of study can, thus, be aggregated into demand for labour by skill/qualification.

Broad skill levels

Highly skilled occupations typically require a bachelor degree or higher qualification and include professionals such as accountants, teachers, and engineers, as well as most managers such as chief executives. This category is consistent with skill level one of the Australia New Zealand Standard Classification of Occupations (ANZSCO).

Medium-high skilled occupations typically require an NZ Register Diploma, an Associate Degree or Advanced Diploma. The category includes some managers (such as retail managers) and technicians (such as architectural draftspersons, ICT support technicians and dental hygienists). This category is consistent with skill level two of the ANZSCO classification.

Medium skilled occupations typically require an NZ Register Level 4 qualification. The category includes tradespersons (such as motor mechanics), skilled service workers (such as firefighters), as well as skilled clerical and sales workers (such as legal secretaries and estate agents). This category is consistent with skill level three of the ANZSCO classification.

Low skilled occupations typically require an NZ Register Level 3 qualification or lower. It includes a range of lower skilled occupations from general clerks, caregivers, and sales assistants, through to cleaners and labourers. This category is consistent with skill level three and four of the ANZSCO classification.


Productivity measures the efficiency of production. In this profile, we measure productivity as GDP per filled job (ie. The amount of economic activity generated on average by each filled job). One needs to be aware that labour is only one input into production. The output of each employee may differ across industries in a region due to differing access to machinery, technology, and land. Therefore, productivity comparisons should only be made in circumstances where it is reasonable to assume that capital intensity will be broadly the same – for example, when looking at productivity within an industry over a limited-time period, or when comparing productivity of a particular industry with that same industry in another region.


Earnings data comes from the quarterly Linked Employer Employee Data published by Statistics New Zealand. LEED publishes the mean earnings of full quarter jobs for each quarter. Full quarter jobs may include full time and part time jobs. Earnings include overtime and lump sum payments. We sum the mean earnings for the four quarters making up the year to arrive at an estimate of average annual earnings.

House values

House value (dollar value) are sourced from QVNZ. The levels used are average current values. An average current value is the average (mean) value of all developed residential properties in the area based on the latest house value index from QVNZ. It is not an average or median sales price, as both of those figures only measure what happens to have sold in the period. These average current values are affected by the underlying value of houses (including those not on the market) and are quality adjusted based on the growth in each house’s price between sales.


The estimated resident population is an estimate of all people who usually live in that area at a given date. Visitors from elsewhere in New Zealand or from overseas are excluded.

The estimated resident population at 30 June 2013 is based on the 2013 census usually resident population count, adjusted for:

The estimated resident population is not directly comparable with the census usually resident population count because of these adjustments.

The estimated resident population is sourced from Statistics New Zealand.

Dependency ratio

The dependency ratio is the number of under 15 year olds and over 65 year olds as a ratio of the rest of the population (working age).

Business Units

Data on the number of businesses is sourced from the Business Demography statistics from Statistics New Zealand. Businesses are measured by geographic units, which represent a business location engaged in one, or predominantly one, kind of economic activity at a single physical site or base (eg. a factory, a farm, a shop, an office, etc). All non-trading or dormant enterprises, as well as enterprises outside of New Zealand, are excluded from business demography statistics.

A significant number of enterprises are recorded as having zero employment. Enterprises in the zero employee count size category may have:

Only business units that are economically significant enterprises are included. To be regarded as economically significant they must meet at least one of the following criteria:


Lack of regional specific data on exports requires us to employ a modeling approach. The main assumption of our approach is that the industries in the regions have the same export characteristics as those at the national level, i.e., their export orientation (export / gross output ratio) is the same as the national average. The export characteristic of the industry is calculated as an average for the period 2008-2010 and remains constant over time. Thus, an industry’s contribution to export growth in a region is different to the country as a whole (or another region) because of the relative importance of the industry in the region compared to the country as a whole (or another region). If a region becomes better represented in an industry with a relatively high export orientation, this industry is expected to make a higher positive contribution to the region’s overall export orientation and the latter will improve as a result. We therefore do not account for national level industry specific changes in export orientation nor for regional level industry specific export orientation or changes thereof. All export estimates are measured in current prices.


Rents ($ per week) are averaged across the year in question from monthly rental data sourced from MBIE. Rental data pertains to averages from data collected when bonds are lodged and does not control for specifications of the home (eg. size, number of bedrooms, age of home, etc).

Government social service expenditure

Government social service expenditure data is sourced from Contract Mapping, which is a service facilitated by the Ministry of Social Development (MSD). All figures are dollars spent in current prices. Some data pertains to contracts for delivery in specific areas, while at times there have been apportionments made by MSD using Census population data. Infometrics has only selected social service expenditure categories for which there is a complete time series and any figures shown by MSD as <$100 have been rounded to zero. Infometrics has performed per capita calculations using Statistics NZ’s most recent subnational population estimates. Region totals have been derived from aggregating territorial authorities.


Beneficiary numbers have been sourced from the Ministry of Social Development (MSD) and are shown as the average number of beneficiaries in each benefit category across each quarter for the current year. Benefit categories were changed in July 2013, and cannot be reconciled consistently with previous data, as a result decompositions of total beneficiaries are only given in the June 2014 year.

Our data shows the four main benefit categories established and reported on since the 2013 category changes. These are Jobseeker Support, Supported Living, Sole Parent Support, and Other (which includes all other residual main benefits). Further details of the benefit categories can be found on MSD’s website.


Dairy data has been sourced from the “New Zealand Dairy Statistics”, a publication co-owned by DairyNZ and LIC, as well as calculations made by Infometrics. The data accords to dairy seasons, which run from June to May.

Generally speaking data on herd numbers, cow numbers, milk solids production, and effective dairy hectares have been taken directly from DairyNZ/LIC for each territorial authority. However DairyNZ/LIC have aggregated together some neighbouring territorial authorities for confidentiality reasons (when there are fewer than four herds in one of the territorial authorities). In these cases, Infometrics has apportioned herds to individual territorial authorities using proportions from agricultural census data (and interpolating in between years), with a maximum of three herds allowed in the smaller territorial authority. Herds for Franklin have been apportioned between Auckland and Waikato District using employment shares in the dairy cattle farming sector that prevailed when Auckland Councils were amalgamated in 2010. Once apportionments of herds have been made, Infometrics then estimated cow numbers by utilising relative differences between herd sizes for members of the aggregated territorial authority shown in the agricultural census. Milk solids production and effective hectares were calculated for each member of an aggregated territorial authority by assuming that productivity and farming intensities of each territorial authority from years where a split was given persists for missing years (in cases where no split is ever given productivities and intensities between members of aggregated territorial authorities are assumed to be equal).

Total dairy payouts in each territorial authority have been calculated by Infometrics by utilising milk solids production in conjunction with Fonterra’s farmgate milk price (excluding dividends) from the dairy season in question.

All regional totals given have been calculated by Infometrics by aggregating territorial authorities within each region.

Tourism expenditure

Tourism expenditure is sourced from MBIE’s regional tourism estimates. These regional estimates are based on electronic card transaction data, but are calibrated to be consistent with national tourism expenditure data shown in Statistics NZ’s Tourism Satellite Account. This calibration takes into consideration the International Visitor Survey, so that differences in propensities to use cards versus cash for visitors from various countries of origin are accounted for.

Maori industry and occupational employment

Infometrics models Maori industry and occupational employment data by drawing on detailed data from the Census, Household Labour Force Survey (HLFS) as well as the Infometrics Regional Employment Industry Model (REIM) and the Infometrics Regional Industry-Occupational matrix.