Business demography statistics

Business demography statistics provide an annual snapshot (as at February) of the structure and characteristics of New Zealand businesses. Statistics produced include counts of enterprises and geographic units by industry, geography such as region or statistical area 2 (SA2), institutional sector, business type, degree of overseas ownership, enterprise births, enterprise deaths, survival rate of enterprises and employment levels.

The series covers economically significant private-sector and public-sector enterprises that are engaged in the production of goods and services in New Zealand. These enterprises are maintained on the Statistics NZ Business Register (BR), which generally includes all employing units and those enterprises with GST turnover greater than $30,000 per year.

For further information: https://www.stats.govt.nz/information-releases/new-zealand-business-demography-statistics-at-february-2020

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Statistical geography

This dataset provides data for the SA2 geography (SA22020_V1_00). Names are provided with and without tohutō/macrons. The name field without macrons is suffixed ‘ascii’. Data for earlier years is available in NZ.Stat– see Geographic units by industry and statistical area 2000-2020.

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Geographic units

The geographic unit represents a business location engaged in one, or predominantly one, kind of economic activity at a single physical site or base (e.g. a factory, a farm, a shop, an office). Geographic units are unique to enterprises and an enterprise unit can have one or many geographic units (business locations). Typically, an enterprise unit only has a single geographic unit, unless the enterprise has paid employees who permanently work at more than one location. Geographic units can be transferred between enterprises (e.g. enterprise B purchases a factory (a geographic unit on the BR) as a going concern from enterprise A).

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Employee count data

Employee counts (ECs) are sourced from the Inland Revenue employer monthly schedule (EMS) tax form.

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Industry

The Australian and New Zealand Standard Industrial Classification (ANZSIC) 2006 is used to compile Business Demography statistics. The classification can be viewed and downloaded from Ariā.

ANZSIC 2006 divisions are:

A Agriculture, Forestry and Fishing

B Mining

C Manufacturing

D Electricity, Gas, Water and Waste Services

E Construction

F Wholesale Trade

G Retail Trade

H Accommodation and Food Services

I Transport, Postal and Warehousing

J Information Media and Telecommunications

K Financial and Insurance Services

L Rental, Hiring and Real Estate Services

M Professional, Scientific and Technical Services

N Administrative and Support Services

O Public Administration and Safety

P Education and Training

Q Health Care and Social Assistance

R Arts and Recreation Services

S Other Services

Total Industry

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Rounding

Enterprise, geographic unit, and EC counts are randomly rounded. Due to rounding, individual figures may not sum to the published totals.

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Quality limitations of fine-level data, including SA2-level data

We recommend caution when using fine-level regional and industry business demography data. The Business Register (BR) supports quality national-level and aggregate industry-level statistics but is not designed to provide quality fine-level regional or industry statistics. The BR update sources can have timing lags and less robust information for small and medium-sized enterprises. These quality weaknesses can be highlighted in fine-level business demography statistics.

For more information about data quality and available data go to DataInfo+.

Business demography statistics provide an annual snapshot (at February) of the structure and characteristics of New Zealand businesses. The series covers economically significant enterprises that are engaged in producing goods and services in New Zealand.

Business demography statistics provide an annual snapshot (at February) of the structure and characteristics of New Zealand businesses. The series covers economically significant enterprises that are engaged in producing goods and services in New Zealand.

Context

Tatauranga umanga Māori – Statistics for Māori businesses: 2017–18 – metadata for CSV files. Tatauranga = statistics. Umanga = business. Aotearoa = New Zealand. Máori language. These files contain the metadata for the CSV files published with this release. List of worksheets:
Agriculture Production Survey.
Business Demography Statistics.
Business Operations Survey.
Linked Employer-Employee Dataset (LEED).
Conditions of supply.
Published by Stats NZ, 07 June 2019.
www.stats.govt.nz https://www.stats.govt.nz/large-datasets/csv-files-for-download/

Content

Statistics New Zealand, branded as Stats NZ, is the public service department of New Zealand charged with the collection of statistics related to the economy, population and society of New Zealand. To this end, Stats NZ produces censuses and surveys. https://en.wikipedia.org/wiki/Statistics_New_Zealand Tatauranga mean statistics (mathematical science). https://en.wiktionary.org/wiki/

Acknowledgements

"Source: Stats NZ and licensed by Stats NZ for re-use under the Creative Commons Attribution 4.0 International licence."

***Photo by pixpoetry on Unsplash.

Inspiration

Aotearoa is the Maori name for the country of New Zealand. The literal translation of Aotearoa is "land of the long white cloud". https://www.maori.com/aotearoa Te Reo Máori it's a taonga (treasure) to be protected.

Business demography statistics provide an annual snapshot (at February) of the structure and characteristics of New Zealand businesses. The series covers economically significant enterprises that are engaged in producing goods and services in New Zealand.

Business demography statistics provide an annual snapshot (at February) of the structure and characteristics of New Zealand businesses. The series covers economically significant enterprises that are engaged in producing goods and services in New Zealand.

Refer to the 'Current Geographic Boundaries Table' layer for a list of all current geographies and recent updates.

This dataset is the definitive version of the annually released statistical area 2 (SA2) boundaries as at 1 January 2025 as defined by Stats NZ. This version contains 2,395 SA2s (2,379 digitised and 16 with empty or null geometries (non-digitised)).

SA2 is an output geography that provides higher aggregations of population data than can be provided at the statistical area 1 (SA1) level. The SA2 geography aims to reflect communities that interact together socially and economically. In populated areas, SA2s generally contain similar sized populations.

The SA2 should:

form a contiguous cluster of one or more SA1s,

excluding exceptions below, allow the release of multivariate statistics with minimal data suppression,

capture a similar type of area, such as a high-density urban area, farmland, wilderness area, and water area,

be socially homogeneous and capture a community of interest. It may have, for example:

• a shared road network,
• shared community facilities,
• shared historical or social links, or
• socio-economic similarity,

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form a nested hierarchy with statistical output geographies and administrative boundaries. It must:

• be built from SA1s,
• either define or aggregate to define SA3s, urban areas, territorial authorities, and regional councils.

SA2s in city council areas generally have a population of 2,000–4,000 residents while SA2s in district council areas generally have a population of 1,000–3,000 residents.

In major urban areas, an SA2 or a group of SA2s often approximates a single suburb. In rural areas, rural settlements are included in their respective SA2 with the surrounding rural area.

SA2s in urban areas where there is significant business and industrial activity, for example ports, airports, industrial, commercial, and retail areas, often have fewer than 1,000 residents. These SA2s are useful for analysing business demographics, labour markets, and commuting patterns.

In rural areas, some SA2s have fewer than 1,000 residents because they are in conservation areas or contain sparse populations that cover a large area.

To minimise suppression of population data, small islands with zero or low populations close to the mainland, and marinas are generally included in their adjacent land-based SA2.

Zero or nominal population SA2s

To ensure that the SA2 geography covers all of New Zealand and aligns with New Zealand’s topography and local government boundaries, some SA2s have zero or nominal populations. These include:

• SA2s where territorial authority boundaries straddle regional council boundaries. These SA2s each have fewer than 200 residents and are: Arahiwi, Tiroa, Rangataiki, Kaimanawa, Taharua, Te More, Ngamatea, Whangamomona, and Mara.
• SA2s created for single islands or groups of islands that are some distance from the mainland or to separate large unpopulated islands from urban areas
• SA2s that represent inland water, inlets or oceanic areas including: inland lakes larger than 50 square kilometres, harbours larger than 40 square kilometres, major ports, other non-contiguous inlets and harbours defined by territorial authority, and contiguous oceanic areas defined by regional council.
• SA2s for non-digitised oceanic areas, offshore oil rigs, islands, and the Ross Dependency. Each SA2 is represented by a single meshblock. The following 16 SA2s are held in non-digitised form (SA2 code; SA2 name):

400001; New Zealand Economic Zone, 400002; Oceanic Kermadec Islands, 400003; Kermadec Islands, 400004; Oceanic Oil Rig Taranaki, 400005; Oceanic Campbell Island, 400006; Campbell Island, 400007; Oceanic Oil Rig Southland, 400008; Oceanic Auckland Islands, 400009; Auckland Islands, 400010 ; Oceanic Bounty Islands, 400011; Bounty Islands, 400012; Oceanic Snares Islands, 400013; Snares Islands, 400014; Oceanic Antipodes Islands, 400015; Antipodes Islands, 400016; Ross Dependency.

SA2 numbering and naming

Each SA2 is a single geographic entity with a name and a numeric code. The name refers to a geographic feature or a recognised place name or suburb. In some instances where place names are the same or very similar, the SA2s are differentiated by their territorial authority name, for example, Gladstone (Carterton District) and Gladstone (Invercargill City).

SA2 codes have six digits. North Island SA2 codes start with a 1 or 2, South Island SA2 codes start with a 3 and non-digitised SA2 codes start with a 4. They are numbered approximately north to south within their respective territorial authorities. To ensure the north–south code pattern is maintained, the SA2 codes were given 00 for the last two digits when the geography was created in 2018. When SA2 names or boundaries change only the last two digits of the code will change.

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High-definition version

This high definition (HD) version is the most detailed geometry, suitable for use in GIS for geometric analysis operations and for the computation of areas, centroids and other metrics. The HD version is aligned to the LINZ cadastre.

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Macrons

Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

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Digital data

Digital boundary data became freely available on 1 July 2007.

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Further information

To download geographic classifications in table formats such as CSV please use Ariā

For more information please refer to the Statistical standard for geographic areas 2023.

Contact: geography@stats.govt.nz

Business demography statistics provide an annual snapshot (at February) of the structure and characteristics of New Zealand businesses. The series covers economically significant enterprises that are engaged in producing goods and services in New Zealand.

Statistical Area 2 2023 update

SA2 2023 is the first major update of the geography since it was first created in 2018. The update is to ensure SA2s are relevant and meet criteria before each five-yearly population and dwelling census. SA2 2023 contains 135 new SA2s. Updates were made to reflect real world change of population and dwelling growth mainly in urban areas, and to make some improvements to their delineation of communities of interest.

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Description

This dataset is the definitive version of the annually released statistical area 2 (SA2) boundaries as at 1 January 2023 as defined by Stats NZ. This version contains 2,395 SA2s (2,379 digitised and 16 with empty or null geometries (non-digitised)).

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SA2 is an output geography that provides higher aggregations of population data than can be provided at the statistical area 1 (SA1) level. The SA2 geography aims to reflect communities that interact together socially and economically. In populated areas, SA2s generally contain similar sized populations.

​

The SA2 should:

form a contiguous cluster of one or more SA1s,

excluding exceptions below, allow the release of multivariate statistics with minimal data suppression,

capture a similar type of area, such as a high-density urban area, farmland, wilderness area, and water area,

be socially homogeneous and capture a community of interest. It may have, for example:

​

• a shared road network,
• shared community facilities,
• shared historical or social links, or
• socio-economic similarity,

​

form a nested hierarchy with statistical output geographies and administrative boundaries. It must:

​

• be built from SA1s,
• either define or aggregate to define SA3s, urban areas, territorial authorities, and regional councils.

​

SA2s in city council areas generally have a population of 2,000–4,000 residents while SA2s in district council areas generally have a population of 1,000–3,000 residents.

​

In major urban areas, an SA2 or a group of SA2s often approximates a single suburb. In rural areas, rural settlements are included in their respective SA2 with the surrounding rural area.

​

SA2s in urban areas where there is significant business and industrial activity, for example ports, airports, industrial, commercial, and retail areas, often have fewer than 1,000 residents. These SA2s are useful for analysing business demographics, labour markets, and commuting patterns.

​

In rural areas, some SA2s have fewer than 1,000 residents because they are in conservation areas or contain sparse populations that cover a large area.

​

To minimise suppression of population data, small islands with zero or low populations close to the mainland, and marinas are generally included in their adjacent land-based SA2.

​

Zero or nominal population SA2s

To ensure that the SA2 geography covers all of New Zealand and aligns with New Zealand’s topography and local government boundaries, some SA2s have zero or nominal populations. These include:

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• SA2s where territorial authority boundaries straddle regional council boundaries. These SA2s each have fewer than 200 residents and are: Arahiwi, Tiroa, Rangataiki, Kaimanawa, Taharua, Te More, Ngamatea, Whangamomona, and Mara.
• SA2s created for single islands or groups of islands that are some distance from the mainland or to separate large unpopulated islands from urban areas
• SA2s that represent inland water, inlets or oceanic areas including: inland lakes larger than 50 square kilometres, harbours larger than 40 square kilometres, major ports, other non-contiguous inlets and harbours defined by territorial authority, and contiguous oceanic areas defined by regional council.
• SA2s for non-digitised oceanic areas, offshore oil rigs, islands, and the Ross Dependency. Each SA2 is represented by a single meshblock. The following 16 SA2s are held in non-digitised form (SA2 code; SA2 name):

400001; New Zealand Economic Zone, 400002; Oceanic Kermadec Islands, 400003; Kermadec Islands, 400004; Oceanic Oil Rig Taranaki, 400005; Oceanic Campbell Island, 400006; Campbell Island, 400007; Oceanic Oil Rig Southland, 400008; Oceanic Auckland Islands, 400009; Auckland Islands, 400010 ; Oceanic Bounty Islands, 400011; Bounty Islands, 400012; Oceanic Snares Islands, 400013; Snares Islands, 400014; Oceanic Antipodes Islands, 400015; Antipodes Islands, 400016; Ross Dependency.

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SA2 numbering and naming

Each SA2 is a single geographic entity with a name and a numeric code. The name refers to a geographic feature or a recognised place name or suburb. In some instances where place names are the same or very similar, the SA2s are differentiated by their territorial authority name, for example, Gladstone (Carterton District) and Gladstone (Invercargill City).

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SA2 codes have six digits. North Island SA2 codes start with a 1 or 2, South Island SA2 codes start with a 3 and non-digitised SA2 codes start with a 4. They are numbered approximately north to south within their respective territorial authorities. To ensure the north–south code pattern is maintained, the SA2 codes were given 00 for the last two digits when the geography was created in 2018. When SA2 names or boundaries change only the last two digits of the code will change.

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For more information please refer to the Statistical standard for geographic areas 2023.

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Generalised version

This generalised version has been simplified for rapid drawing and is designed for thematic or web mapping purposes.

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Macrons

Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

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Digital data

Digital boundary data became freely available on 1 July 2007.

​

To download geographic classifications in table formats such as CSV please use Ariā

This report analyses the estimated resident population of New Zealand aged between 15 and 45. The estimated resident population refers to all the people who usually live in New Zealand on a given date. The data from this report is sourced from Statistics New Zealand (Tatauranga Aotearoa) and is measured in people residing in New Zealand at the end of each financial year.

Abstract

The intention is to collect data for the calendar year 2009 (or the nearest year for which each business keeps its accounts. The survey is considered a one-off survey, although for accurate NAs, such a survey should be conducted at least every five years to enable regular updating of the ratios, etc., needed to adjust the ongoing indicator data (mainly VAGST) to NA concepts. The questionnaire will be drafted by FSD, largely following the previous BAS, updated to current accounting terminology where necessary. The questionnaire will be pilot tested, using some accountants who are likely to complete a number of the forms on behalf of their business clients, and a small sample of businesses. Consultations will also include Ministry of Finance, Ministry of Commerce, Industry and Labour, Central Bank of Samoa (CBS), Samoa Tourism Authority, Chamber of Commerce, and other business associations (hotels, retail, etc.).

The questionnaire will collect a number of items of information about the business ownership, locations at which it operates and each establishment for which detailed data can be provided (in the case of complex businesses), contact information, and other general information needed to clearly identify each unique business. The main body of the questionnaire will collect data on income and expenses, to enable value added to be derived accurately. The questionnaire will also collect data on capital formation, and will contain supplementary pages for relevant industries to collect volume of production data for selected commodities and to collect information to enable an estimate of value added generated by key tourism activities.

The principal user of the data will be FSD which will incorporate the survey data into benchmarks for the NA, mainly on the current published production measure of GDP. The information on capital formation and other relevant data will also be incorporated into the experimental estimates of expenditure on GDP. The supplementary data on volumes of production will be used by FSD to redevelop the industrial production index which has recently been transferred under the SBS from the CBS. The general information about the business ownership, etc., will be used to update the Business Register.

Outputs will be produced in a number of formats, including a printed report containing descriptive information of the survey design, data tables, and analysis of the results. The report will also be made available on the SBS website in “.pdf” format, and the tables will be available on the SBS website in excel tables. Data by region may also be produced, although at a higher level of aggregation than the national data. All data will be fully confidentialised, to protect the anonymity of all respondents. Consideration may also be made to provide, for selected analytical users, confidentialised unit record files (CURFs).

A high level of accuracy is needed because the principal purpose of the survey is to develop revised benchmarks for the NA. The initial plan was that the survey will be conducted as a stratified sample survey, with full enumeration of large establishments and a sample of the remainder.

Geographic coverage

National Coverage

Analysis unit

The main statistical unit to be used for the survey is the establishment. For simple businesses that undertake a single activity at a single location there is a one-to-one relationship between the establishment and the enterprise. For large and complex enterprises, however, it is desirable to separate each activity of an enterprise into establishments to provide the most detailed information possible for industrial analysis. The business register will need to be developed in such a way that records the links between establishments and their parent enterprises. The business register will be created from administrative records and may not have enough information to recognize all establishments of complex enterprises. Large businesses will be contacted prior to the survey post-out to determine if they have separate establishments. If so, the extended structure of the enterprise will be recorded on the business register and a questionnaire will be sent to the enterprise to be completed for each establishment.

SBS has decided to follow the New Zealand simplified version of its statistical units model for the 2009 BAS. Future surveys may consider location units and enterprise groups if they are found to be useful for statistical collections.

It should be noted that while establishment data may enable the derivation of detailed benchmark accounts, it may be necessary to aggregate up to enterprise level data for the benchmarks if the ongoing data used to extrapolate the benchmark forward (mainly VAGST) are only available at the enterprise level.

Universe

The BAS's covered all employing units, and excluded small non-employing units such as the market sellers. The surveys also excluded central government agencies engaged in public administration (ministries, public education and health, etc.). It only covers businesses that pay the VAGST. (Threshold SAT$75,000 and upwards).

Kind of data

Sample survey data [ssd]

Sampling procedure

-Total Sample Size was 1240 -Out of the 1240, 902 successfully completed the questionnaire. -The other remaining 338 either never responded or were omitted (some businesses were ommitted from the sample as they do not meet the requirement to be surveyed) -Selection was all employing units paying VAGST (Threshold SAT $75,000 upwards)

WILL CONFIRM LATER!!

OSO LE MEA E LE FAASA...AEA :-)

Mode of data collection

Mail Questionnaire [mail]

Research instrument

1. General instructions, authority for the survey, etc;
2. Business demography information on ownership, contact details, structure, etc.;
3. Employment;
4. Income;
5. Expenses;
6. Inventories;
7. Profit or loss and reconciliation to business accounts' profit and loss;
8. Fixed assets - purchases, disposals, book values
9. Thank you and signature of respondent.

Supplementary Pages Additional pages have been prepared to collect data for a limited range of industries. 1.Production data. To rebase and redevelop the Industrial Production Index (IPI), it is intended to collect volume of production information from a selection of large manufacturing businesses. The selection of businesses and products is critical to the usefulness of the IPI. The products must be homogeneous, and be of enough importance to the economy to justify collecting the data. Significance criteria should be established for the selection of products to include in the IPI, and the 2009 BAS provides an opportunity to collect benchmark data for a range of products known to be significant (based on information in the existing IPI, CPI weights, export data, etc.) as well as open questions for respondents to provide information on other significant products. 2.Tourism. There is a strong demand for estimates of tourism value added. To estimate tourism value added using the international standard Tourism Satellite Account methodology requires the use of an input-output table, which is beyond the capacity of SBS at present. However, some indicative estimates of the main parts of the economy influenced by tourism can be derived if the necessary data are collected. Tourism is a demand concept, based on defining tourists (the international standard includes both international and domestic tourists), what products are characteristically purchased by tourists, and which industries supply those products. Some questions targeted at those industries that have significant involvement with tourists (hotels, restaurants, transport and tour operators, vehicle hire, etc.), on how much of their income is sourced from tourism would provide valuable indicators of the size of the direct impact of tourism.

Cleaning operations

Partial imputation was done at the time of receipt of questionnaires, after follow-up procedures to obtain fully completed questionnaires have been followed. Imputation followed a process, i.e., apply ratios from responding units in the imputation cell to the partial data that was supplied. Procedures were established during the editing stage (a) to preserve the integrity of the questionnaires as supplied by respondents, and (b) to record all changes made to the questionnaires during editing. If SBS staff writes on the form, for example, this should only be done in red pen, to distinguish the alterations from the original information.

Additional edit checks were developed, including checking against external data at enterprise/establishment level. External data to be checked against include VAGST and SNPF for turnover and purchases, and salaries and wages and employment data respectively. Editing and imputation processes were undertaken by FSD using Excel.

Sampling error estimates

NOT APPLICABLE!!

Dataset shows an individual’s statistical area 3 (SA3) of usual residence and the SA3 of their workplace address, for the employed census usually resident population count aged 15 years and over, by main means of travel to work from the 2018 and 2023 Censuses.

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The main means of travel to work categories are:

• Work at home
• Drive a private car, truck, or van
• Drive a company car, truck, or van
• Passenger in a car, truck, van, or company bus
• Public bus
• Train
• Bicycle
• Walk or jog
• Ferry
• Other.

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Main means of travel to work is the usual method which an employed person aged 15 years and over used to travel the longest distance to their place of work.

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Workplace address refers to where someone usually works in their main job, that is the job in which they worked the most hours. For people who work at home, this is the same address as their usual residence address. For people who do not work at home, this could be the address of the business they work for or another address, such as a building site.

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Workplace address is coded to the most detailed geography possible from the available information. This dataset only includes travel to work information for individuals whose workplace address is available at SA3 level. The sum of the counts for each region in this dataset may not equal the total employed census usually resident population count aged 15 years and over for that region. Workplace address – 2023 Census: Information by concept has more information.

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This dataset can be used in conjunction with the following spatial files by joining on the SA3 code values:

• Statistical area 3 2023 (generalised)

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Download data table using the instructions in the Koordinates help guide.

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Footnotes

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Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Subnational census usually resident population

The census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. 

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Population counts

Stats NZ publishes a number of different population counts, each using a different definition and methodology. Population statistics – user guide has more information about different counts. 

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data).

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Workplace address time series

Workplace address time series data should be interpreted with care at lower geographic levels, such as statistical area 2 (SA2). Methodological improvements in 2023 Census resulted in greater data accuracy, including a greater proportion of people being counted at lower geographic areas compared to the 2018 Census. Workplace address – 2023 Census: Information by concept has more information.

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Working at home

In the census, working at home captures both remote work, and people whose business is at their home address (e.g. farmers or small business owners operating from their home). The census asks respondents whether they ‘mostly’ work at home or away from home. It does not capture whether someone does both, or how frequently they do one or the other.

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Rows excluded from the dataset

Rows show SA3 of usual residence by SA3 of workplace address. Rows with a total population count of less than six have been removed to reduce the size of the dataset, given only a small proportion of SA3-SA3 combinations have commuter flows.

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Quality rating of a variable

The quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable.

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Main means of travel to work quality rating

Main means of travel to work is rated as moderate quality.

Main means of travel to work – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Workplace address quality rating

Workplace address is rated as moderate quality.

Workplace address – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for ‘Total stated’ where this applies.

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Symbol

-999 Confidential

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

The report analyses the estimated resident population of New Zealand aged 50 and older. The estimated resident population refers to all the people who usually live in New Zealand on a given date. The data from this report is sourced from Statistics New Zealand (Tatauranga Aotearoa) and is measured in people residing in New Zealand at the end of each financial year.

Своевременные показатели предпринимательства стали неотъемлемой частью бизнес-статистики большинства стран - членов ОЭСР и за ее пределами. Он дополняет более полные годовые наборы данных (например, демография бизнеса, структурная статистика бизнеса по классам размеров) более своевременной ежемесячной или квартальной информацией по ограниченному числу показателей.Данные, когда они доступны, представлены в разбивке по видам экономической деятельности в соответствии с Международной стандартной отраслевой классификацией, пересмотр 4 (ISIC Rev.4): Пересмотренный МСОК 4 на уровне разделов (букв) и более высоких агрегированных показателей, чаще всего охватывающих экономику в целом,географический район страны и Уровень TL2 территориальных сетей ОЭСР ,организационно-правовую форму можно разделить на три основные группы: общество с ограниченной ответственностью (LL), товарищество (PA) и индивидуальный предприниматель (SP).С очень за редким исключением, серии не корректируются по сезонам или календарю, поэтому следует проявлять осторожность при интерпретации изменений, происходящих раз в полгода. Своевременные показатели развития предпринимательства предоставляют политикам и исследователям ценную информацию о самых последних тенденциях в динамике бизнеса.В этом наборе данных представлены актуальные показатели для Новой Зеландии.Связанные наборы данных:Статистика демографии бизнеса работодателей,Статистика демографии бизнеса,Структурная бизнес-статистика по классам размера. Показатели эффективности предпринимательской деятельности являются объединенной партией по статистике предприятий с большим количеством платежеспособных членов в мире и за его пределами. Полный перечень предприятий за год, а также завершенные проекты (например, демография предприятий, статистические данные о структуре предприятий в классе taille), включая информацию о мужчинах по триместрам, а также актуальную информацию по номенклатурным показателям.Проблемы с вентиляцией, которые могут возникнуть в связи сдеятельностью в области экономики выбор типа международной классификации для промышленности, раздел 4 (раздел 4 CITI) : ГОРОД № 4 ау история секций (литературы) и высших агрономов, история экономики в целом,географическая зона, история оплаты труда и история ОКР TL2, юридическая форма> в трех группах руководителей: с ограниченной ответственностью (LL), в Обществе коллективного пользования (PA) и в индивидуальном предпринимательстве (SP). В настоящее время существует множество редких исключений, серий и исправлений для сезонных изменений в календарях. Удобно проявлять благоразумие при интерпретации изменений в течение года. Показатели эффективности предпринимательской деятельности основаны на информации, направленной на решение политических проблем и на поддержку тенденций, а также на динамику предприятий.Вот таблица, представленная начальниками для Новой Зеландии.Начальники ассоциацийДемография предприятий, работающих по найму,Демография предприятий,Статистические структуры предприятий в классе taille. Timely Indicators of Entrepreneurship have become integral part of business statistics offering of most OECD member countries and beyond. It supplements more complete annual datasets (e.g. Business Demography, Structural Business Statistics by Size class) with more timely monthly or quarterly information on a limited number of indicators.Data are broken down whenever available byeconomic activity according to International Standard Industrial Classification, Revision 4 (ISIC Rev.4): ISIC Rev. 4 at the level of sections (letters) and higher aggregates, most often covering the total economy,geographic area at country and TL2 level of the OECD Territorial grids,legal form into three main groups: Limited liability (LL), Partnership (PA) and Sole proprietorship (SP).With very few exceptions, series are not seasonally or calendar adjusted, so care should be taken in interpreting sub-annual changes. Timely Indicators of Entrepreneurship provide valuable information to policy makers and researchers on most recent trends in business dynamics.This dataset presents timely indicators for New Zealand.Related datasets:Employer Business Demography Statistics,Business Demography Statistics,Structural Business Statistics by Size Class. Les indicateurs rapides de l'entrepreneuriat font désormais partie intégrante de l’offre de statistiques d’entreprises de la plupart des pays membres de l’OCDE et au-delà. Il complète l'ensembles de données annuelles plus complètes (par exemple, démographie des entreprises, statistiques structurelles des entreprises par classe de taille) avec des informations mensuelles ou trimestrielles plus actuelles sur un nombre limité d'indicateurs.Les données sont ventilées dès que possible paractivité économique selon la Classification internationale type par industrie, révision 4 (CITI Rév.4) : CITI Rév. 4 au niveau des sections (lettres) et des agrégats supérieurs, couvrant le plus souvent l'économie totale,zone géographique au niveau du pays et au niveau OCDE TL2, forme juridique en trois groupes principaux : Responsabilité limitée (LL), Société en nom collectif (PA) et Entreprise individuelle (SP). À de très rares exceptions près, les séries ne sont pas corrigées des variations saisonnières ou calendaires. Il convient donc d'être prudent dans l'interprétation des changements infra-annuels. Les indicateurs rapides de l'entrepreneuriat fournissent des informations précieuses aux décideurs politiques et aux chercheurs sur les tendances les plus récentes de la dynamique des entreprises.Ce tableau présente les données pour la Nouvelle-Zélande.Données associésDémographie des entreprises employant des salariés,Démographie des entreprises,Statistiques structurelles des entreprises par classe de taille.

The internet penetration rate in New Zealand is relatively high, following global trends of internet usage. Around ** percent of the population in New Zealand were active internet users in 2021, a share that had increased from the previous year. Unlimited broadband, unlimited possibilities New Zealanders require large amounts of data for their everyday living; from communicating via social media platforms, purchasing goods online as well as for entertainment. Supporting this massive data requirement, most of the broadband connections across the country had unlimited data caps in 2018. New Zealanders required not only large amounts of data, but also fast internet connections. Almost half of the broadband connections across the country had download speeds falling between ** and ** megabits per second in the same year. Staying connected Copper wire connections accounted for the largest share of connection types, with fiber optic following closely behind. Fiber optic connections have been increasing their share of the market since the government implemented the Ultra-Fast Broadband (UFB) initiative in 2011. This program aimed to bring fiber network internet access to ** percent of the population by 2022, a move that would support New Zealanders and New Zealand businesses in their fast-growing internet needs, allowing Kiwis to stay connected with the rest of the world.

Statistical Area 1 2023 update

SA1 2023 is the first major update of the geography since it was first created in 2018. The update is to ensure SA1s are relevant and meet criteria before each five-yearly population and dwelling census. SA1 2023 contains 3,251 new SA1s. Updates were made to reflect real world changes including new subdivisions and motorways, improve the delineation of urban rural and other statistical areas and to ensure they meet population criteria by reducing the number of SA1s with small or large populations.

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Description

This dataset is the definitive version of the annually released statistical area 1 (SA1) boundaries as at 1 January 2023, as defined by Stats NZ. This version contains 33,164 SA1s (33,148 digitised and 16 with empty or null geometries (non-digitised).

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SA1 is an output geography that allows the release of more low-level data than is available at the meshblock level. Built by joining meshblocks, SA1s have an ideal size range of 100–200 residents, and a maximum population of about 500. This is to minimise suppression of population data in multivariate statistics tables.

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The SA1 should:

form a contiguous cluster of one or more meshblocks,

be either urban, rural, or water in character,

be small enough to:

• allow flexibility for aggregation to other statistical geographies,

• allow users to aggregate areas into their own defined communities of interest,

form a nested hierarchy with statistical output geographies and administrative boundaries. It must:

• be built from meshblocks,

• either define or aggregate to define SA2s, urban rural areas, territorial authorities, and regional councils.

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SA1s generally have a population of 100–200 residents, with some exceptions:

• SA1s with nil or nominal resident populations are created to represent remote mainland areas, unpopulated islands, inland water, inlets, or oceanic areas.

• Some SA1s in remote rural areas and urban industrial or business areas have fewer than 100 residents.

• Some SA1s that contain apartment blocks, retirement villages, and large non-residential facilities (prisons, boarding schools, etc) have more than 500 residents.

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SA1 numbering

SA1s are not named. SA1 codes have seven digits starting with a 7 and are numbered approximately north to south. Non-digitised codes start with 79.

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As new SA1s are created, they are given the next available numeric code. If the composition of an SA1 changes through splitting or amalgamating different meshblocks, the SA1 is given a new code. The previous code no longer exists within that version and future versions of the SA1 classification.

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Digitised and non-digitised SA1s

The digital geographic boundaries are defined and maintained by Stats NZ.

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Aggregated from meshblocks, SA1s cover the land area of New Zealand, the water area to the 12-mile limit, the Chatham Islands, Kermadec Islands, sub-Antarctic islands, off-shore oil rigs, and Ross Dependency. The following 16 SA1s are held in non-digitised form.

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7999901; New Zealand Economic Zone, 7999902; Oceanic Kermadec Islands,7999903; Kermadec Islands, 7999904; Oceanic Oil Rig Taranaki,7999905; Oceanic Campbell Island, 7999906; Campbell Island, 7999907; Oceanic Oil Rig Southland, 7999908; Oceanic Auckland Islands, 7999909; Auckland Islands, 7999910; Oceanic Bounty Islands, 7999911; Bounty Islands, 7999912; Oceanic Snares Islands, 7999913; Snares Islands, 7999914; Oceanic Antipodes Islands, 7999915; Antipodes Islands, 7999916; Ross Dependency.

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For more information please refer to the Statistical standard for geographic areas 2023.

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Generalised version

This generalised version has been simplified for rapid drawing and is designed for thematic or web mapping purposes.

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Digital data

Digital boundary data became freely available on 1 July 2007.

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To download geographic classifications in table formats such as CSV please use Ariā

Abstract

The Future of Business Survey is a new source of information on small and medium-sized enterprises (SMEs). Launched in February 2016, the monthly survey - a partnership between Facebook, OECD, and The World Bank - provides a timely pulse on the economic environment in which businesses operate and who those businesses are to help inform decision-making at all levels and to deliver insights that can help businesses grow. The Future of Business Survey provides a perspective from newer and long-standing digitalized businesses and provides a unique window into a new mobilized economy.

Policymakers, researchers and businesses share a common interest in the environment in which SMEs operate, as well their outlook on the future, not least because young and innovative SMEs in particular are often an important source of considerable economic and employment growth. Better insights and timely information about SMEs improve our understanding of economic trends, and can provide new insights that can further stimulate and help these businesses grow.

To help provide these insights, Facebook, OECD and The World Bank have collaborated to develop a monthly survey that attempts to improve our understanding of SMEs in a timely and forward-looking manner. The three organizations share a desire to create new ways to hear from businesses and help them succeed in the emerging digitally-connected economy. The shared goal is to help policymakers, researchers, and businesses better understand business sentiment, and to leverage a digital platform to provide a unique source of information to complement existing indicators.

With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

Geographic coverage

When the survey was initially launched in February 2016, it included 22 countries. When the survey was initially launched in February 2016, it included 22 countries. The Future of Business Survey is now conducted in over 90 countries in every region of the world.

Countries included in at least one wave: Albania Algeria American Samoa Andorra Angola Anguilla Antigua and Barbuda Argentina Aruba Australia Austria Azerbaijan Bahamas (the) Bangladesh Barbados Belarus Belgium Belize Benin Bolivia (Plurinational State of) Bonaire, Sint Eustatius and Saba Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Cayman Islands (the) Central African Republic (the) Chad Chile Colombia Congo (the) Curaçao Cyprus Czechia Côte d'Ivoire Denmark Djibouti Dominica Dominican Republic (the) Ecuador Egypt El Salvador Equatorial Guinea Estonia Eswatini Ethiopia Faroe Islands (the) Fiji Finland France French Polynesia Gabon Gambia (the) Germany Ghana Gibraltar Greece Grenada Guadeloupe Guam Guatemala Guernsey Guinea Guinea-Bissau Guyana Haiti Honduras Hong Kong Hungary Iceland India Indonesia Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jersey Jordan Kenya Korea (the Republic of) Kuwait Lao People's Democratic Republic (the) Lebanon Lesotho Liberia Libya Liechtenstein Lithuania Luxembourg Malawi Malaysia Mali Malta Martinique Mauritania Mauritius Mayotte Mexico Monaco Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands (the) New Caledonia New Zealand Nicaragua Niger (the) Nigeria North Macedonia Northern Mariana Islands (the) Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines (the) Poland Portugal Qatar Romania Russian Federation (the) Rwanda Réunion Saint Kitts and Nevis Saint Lucia Saint Vincent and the Grenadines Samoa San Marino Sao Tome and Principe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore Sint Maarten (Dutch part) Slovakia Slovenia Solomon Islands South Africa Spain Sweden Switzerland Taiwan Tanzania, the United Republic of Thailand Timor-Leste Togo Tonga Trinidad and Tobago Tunisia Turkey Turks and Caicos Islands (the) Uganda United Arab Emirates (the) United Kingdom of Great Britain and Northern Ireland (the) United States of America (the) Uruguay Vanuatu Viet Nam Virgin Islands (British) Virgin Islands (U.S.) Zambia.

Analysis unit

The study describes small and medium-sized enterprises.

Universe

The target population consists of SMEs that have an active Facebook business Page and include both newer and longer-standing businesses, spanning across a variety of sectors. With more businesses leveraging online tools each day, the survey provides a lens into a new mobilized, digital economy and, in particular, insights on the actors: a relatively unmeasured community worthy of deeper consideration and considerable policy interest.

Kind of data

Sample survey data [ssd]

Sampling procedure

Twice a year in over 97 countries, the Facebook Survey Team sends the Future of Business to admins and owners of Facebook-designated small business pages. When we share data from this survey, we anonymize responses to all survey questions and only share country-level data publicly. To achieve better representation of the broader small business population, we also weight our results based on known characteristics of the Facebook Page admin population.

A random sample of firms, representing the target population in each country, is selected to respond to the Future of Business Survey each month.

Mode of data collection

Internet [int]

Research instrument

The survey includes questions about perceptions of current and future economic activity, challenges, business characteristics and strategy. Custom modules include questions related to regulation, access to finance, digital payments, and digital skills. The full questionnaire is available for download.

Response rate

Response rates to online surveys vary widely depending on a number of factors including survey length, region, strength of the relationship with invitees, incentive mechanisms, invite copy, interest of respondents in the topic and survey design.

Note: Response rates are calculated as the number of respondents who completed the survey divided by the total number of SMEs invited.

Sampling error estimates

Any survey data is prone to several forms of error and biases that need to be considered to understand how closely the results reflect the intended population. In particular, the following components of the total survey error are noteworthy:

Sampling error is a natural characteristic of every survey based on samples and reflects the uncertainty in any survey result that is attributable to the fact that not the whole population is surveyed.

Other factors beyond sampling error that contribute to such potential differences are frame or coverage error (sampling frame of page owners does not include all relevant businesses but also may include individuals that don't represent businesses), and nonresponse error.

Note that the sample is meant to reflect the population of businesses on Facebook, not the population of small businesses in general. This group of digitized SMEs is itself a community worthy of deeper consideration and of considerable policy interest. However, care should be taken when extrapolating to the population of SMEs in general. Moreover, future work should evaluate the external validity of the sample. Particularly, respondents should be compared to the broader population of SMEs on Facebook, and the economy as a whole.

Business demographic statistics give an annual snapshot (as at February) of the structure and characteristics of New Zealand businesses.

Business demographic statistics give an annual snapshot (as at February) of the structure and characteristics of New Zealand businesses.

This dataset contains selected series on immigration, emigration, population and trade drawn from published Statistics NZ and Ministry of Business, Innovation and Employment data.