Nominal Median and Nominal Mean Income Measures by National Income Definition, Year and Statistic

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Cross sectional data, all countries for the statistic Nominal_Exchange_Rate_3_Year_Change_In_Percent. Indicator Definition:Nominal Exchange Rate 1 Year Change In Percent. The Exchange Rate is defined according to the Quantity Notation, that is, foreign currency (here always the USD) per domestic currency (for example the euro for Germany). Hence, a higher value means, that the domestic currency appreciated as more foreign currency units can be purchased for one unit of domestic currency.Indicator Unit:The statistic is measured in Percent.Descriptive Statistics regarding the Indicator "Nominal Exchange Rate 3 Year Change In Percent":The number of countries with data stands at: 153 countries.The average value across those countries stands at: -4.50.The standard deviation across those countries stands at: 25.54.The lowest value stands at: -98.32, and was observed in Lebanon (LBP), which in this case constitutes the country that ranks last.The highest value stands at: 36.51, and was observed in Albania (ALL), which in this case constitutes the country that ranks first.Looking at countries with values, the top 5 countries are:1. Albania, actual value 36.51, actual ranking 1.2. Costa Rica, actual value 36.30, actual ranking 2.3. Afghanistan, actual value 24.75, actual ranking 3.4. Poland, actual value 23.95, actual ranking 4.5. Sri Lanka, actual value 20.48, actual ranking 5.Looking at countries with values, the bottom 5 countries are:1. Lebanon, actual value -98.32, actual ranking 153.2. Venezuela, RB, actual value -94.88, actual ranking 152.3. Iran, Islamic Rep., actual value -93.01, actual ranking 151.4. Argentina, actual value -89.58, actual ranking 150.5. South Sudan, actual value -89.00, actual ranking 149.

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 3 (SA3) boundaries as at 1 January 2025 as defined by Stats NZ. This version contains 929 SA3s, including 4 non-digitised SA3s.

The SA3 geography aims to meet three purposes:

1. approximate suburbs in major, large, and medium urban areas,
2. in predominantly rural areas, provide geographical areas that are larger in area and population size than SA2s but smaller than territorial authorities,
3. minimise data suppression.

SA3s in major, large, and medium urban areas were created by combining SA2s to approximate suburbs as delineated in the Fire and Emergency NZ (FENZ) Localities dataset. Some of the resulting SA3s have very large populations.

Outside of major, large, and medium urban areas, SA3s generally have populations of 5,000–10,000. These SA3s may represent either a single small urban area, a combination of small urban areas and their surrounding rural SA2s, or a combination of rural SA2s.

Zero or nominal population SA3s

To minimise the amount of unsuppressed data that can be provided in multivariate statistical tables, SA2s with fewer than 1,000 residents are combined with other SA2s wherever possible to reach the 1,000 SA3 population target. However, there are still a number of SA3s with zero or nominal populations.

Small population SA2s designed to maintain alignment between territorial authority and regional council geographies are merged with other SA2s to reach the 5,000–10,000 SA3 population target. These merges mean that some SA3s do not align with regional council boundaries but are aligned to territorial authority.

Small population island SA2s are included in their adjacent land-based SA3.

Island SA2s outside territorial authority or region are the same in the SA3 geography.

Inland water SA2s are aggregated and named by territorial authority, as in the urban rural classification.

Inlet SA2s are aggregated and named by territorial authority or regional council where the water area is outside the territorial authority.

Oceanic SA2s translate directly to SA3s as they are already aggregated to regional council.

The 16 non-digitised SA2s are aggregated to the following 4 non-digitised SA3s (SA3 code; SA3 name):

70001; Oceanic outside region, 70002; Oceanic oil rigs, 70003; Islands outside region, 70004; Ross Dependency outside region.

SA3 numbering and naming

Each SA3 is a single geographic entity with a name and a numeric code. The name refers to a suburb, recognised place name, or portion of a territorial authority. In some instances where place names are the same or very similar, the SA3s are differentiated by their territorial authority, for example, Hillcrest (Hamilton City) and Hillcrest (Rotorua District).

SA3 codes have five digits. North Island SA3 codes start with a 5, South Island SA3 codes start with a 6 and non-digitised SA3 codes start with a 7. They are numbered approximately north to south within their respective territorial authorities. When first created in 2025, the last digit of each code was 0. When SA3 boundaries change in future, only the last digit of the code will change to ensure the north-south pattern is maintained.

​

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.

​

Macrons

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

​

Digital data

Digital boundary data became freely available on 1 July 2007

​

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

Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.

The quarterly Labour Cost Index (LCI) is one of the Principal European economic indicators. It shows the short-term development of the labour cost, the total cost on an hourly basis of employing labour. In other words, the LCI measures the cost pressure arising from the production factor “labour”.

The data covered by the LCI collection relate to the total average hourly labour costs and its components "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer" (known as the non-wage component of the LCI). The data on vocational training costs and other expenditures such as recruitment costs and working clothes expenditure is not included in the calculation of the labour cost index.

The data is broken down by economic activity (NACE Rev 1.1 Sections C to O (1996Q1-2008Q4) and NACE Rev. 2 Sections B to S (2009Q1 onwards). The data is available for the EU aggregates and the EU Member States, EFTA countries (Iceland and Norway) as well as candidate and potential candidate countries (Serbia and Turkey). The data is available as 'unadjusted data (neither seasonally adjusted nor calendar adjusted data)', 'calendar-adjusted data' as well as 'seasonally and calendar adjusted' data.

The data on the Labour Cost Index is given in the form of index numbers (current base year: 2020) and as annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). Since June 2023 (publication of 2023Q1 data) base year of the indices changed from 2016 to 2020. Indices with the base year 2016 will no longer be published.

The National Statistical Institutes compile the indicators based on the available structural and short-term information collected directly from the sampled enterprises or taken from administrative data sources. All enterprises, irrespective of the size (measured by the number of employees) are covered in the LCI.

In addition, Eurostat estimates of the annual labour cost per hour in euros are provided for the EU Member States as well as the whole EU; they were obtained by combining the four-yearly Labour cost survey (LCS) with the quarterly labour cost index. Methodological information related to the annual estimates of hourly labour costs is available in separate metadata accessible here.

Early estimates of the Labour Cost Index (‘flash estimates’ or ‘FEs’) (quarterly)

Since May 2024, Eurostat has started publishing early estimates for the Labour Cost Index (‘flash estimates’ or ‘FEs’). The flash estimates (are published around t+50 days, as specified in the general release calendar of Eurostat, based on the data transmitted at t+45 days. EU countries that participate in the FE data collection are those whose annual number of employees (over the age of 15) represents more than 3% of EU totals or 3% of euro area totals, based on LFS data assessed over a period of three consecutive years. These 9 selected countries (i.e. ‘FE countries ’) are: Germany, France, Italy, Spain, the Netherlands, Belgium, Portugal, Poland and Romania (see table 1).

Table 1: Share of EA/EU employees in each of the participating countries.

(Source: EU-LFS, reference period 2023)

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.

​

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.

​

Macrons

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

​

Digital data

Digital boundary data became freely available on 1 July 2007.

​

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

Statistical area 3 (SA3) is a new output geography, introduced in 2023, that allows aggregations of population data between the SA2 geography and territorial authority geography.

​

This dataset is the definitive version of the annually released statistical area 3 (SA3) boundaries as at 1 January 2023 as defined by Stats NZ. This version contains 929 SA3s, including 4 non-digitised SA3s.

​

The SA3 geography aims to meet three purposes:

1. approximate suburbs in major, large, and medium urban areas,

2. in predominantly rural areas, provide geographical areas that are larger in area and population size than SA2s but smaller than territorial authorities,

3. minimise data suppression.

​

SA3s in major, large, and medium urban areas were created by combining SA2s to approximate suburbs as delineated in the Fire and Emergency NZ (FENZ) Localities dataset. Some of the resulting SA3s have very large populations.

​

Outside of major, large, and medium urban areas, SA3s generally have populations of 5,000–10,000. These SA3s may represent either a single small urban area, a combination of small urban areas and their surrounding rural SA2s, or a combination of rural SA2s.

​

Zero or nominal population SA3s

To minimise the amount of unsuppressed data that can be provided in multivariate statistical tables, SA2s with fewer than 1,000 residents are combined with other SA2s wherever possible to reach the 1,000 SA3 population target. However, there are still a number of SA3s with zero or nominal populations.

​

Small population SA2s designed to maintain alignment between territorial authority and regional council geographies are merged with other SA2s to reach the 5,000–10,000 SA3 population target. These merges mean that some SA3s do not align with regional council boundaries but are aligned to territorial authority.

​

Small population island SA2s are included in their adjacent land-based SA3.

​

Island SA2s outside territorial authority or region are the same in the SA3 geography.

​

Inland water SA2s are aggregated and named by territorial authority, as in the urban rural classification.

​

Inlet SA2s are aggregated and named by territorial authority or regional council where the water area is outside the territorial authority.

​

Oceanic SA2s translate directly to SA3s as they are already aggregated to regional council.

​

The 16 non-digitised SA2s are aggregated to the following 4 non-digitised SA3s (SA3 code; SA3 name):

70001; Oceanic outside region, 70002; Oceanic oil rigs, 70003; Islands outside region, 70004; Ross Dependency outside region.

​

SA3 numbering and naming

Each SA3 is a single geographic entity with a name and a numeric code. The name refers to a suburb,recognised place name, or portion of a territorial authority. In some instances where place names are the same or very similar, the SA3s are differentiated by their territorial authority, for example, Hillcrest (Hamilton City) and Hillcrest (Rotorua District).

​

SA3 codes have five digits. North Island SA3 codes start with a 5, South Island SA3 codes start with a 6 and non-digitised SA3 codes start with a 7. They are numbered approximately north to south within their respective territorial authorities. When first created in 2023, the last digit of each code was 0. When SA3 boundaries change in future, only the last digit of the code will change to ensure the north-south pattern is maintained.

​

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

​

Generalised version

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

​

Macrons

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

​

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

Refer to the current geographies boundaries table for a list of all current geographies and recent updates.

This dataset is the definitive version of the annually released statistical area 3 (SA3) boundaries as at 1 January 2025 as defined by Stats NZ, clipped to the coastline. This clipped version has been created for cartographic purposes and so does not fully represent the official full extent boundaries. This version contains 873 SA3s, excluding 4 non-digitised SA3s.

The SA3 geography aims to meet three purposes:

1. approximate suburbs in major, large, and medium urban areas,

2. in predominantly rural areas, provide geographical areas that are larger in area and population size than SA2s but smaller than territorial authorities,

3. minimise data suppression.

SA3s in major, large, and medium urban areas were created by combining SA2s to approximate suburbs as delineated in the Fire and Emergency NZ (FENZ) Localities dataset. Some of the resulting SA3s have very large populations.

Outside of major, large, and medium urban areas, SA3s generally have populations of 5,000–10,000. These SA3s may represent either a single small urban area, a combination of small urban areas and their surrounding rural SA2s, or a combination of rural SA2s.

Zero or nominal population SA3s

To minimise the amount of unsuppressed data that can be provided in multivariate statistical tables, SA2s with fewer than 1,000 residents are combined with other SA2s wherever possible to reach the 1,000 SA3 population target. However, there are still a number of SA3s with zero or nominal populations.

Small population SA2s designed to maintain alignment between territorial authority and regional council geographies are merged with other SA2s to reach the 5,000–10,000 SA3 population target. These merges mean that some SA3s do not align with regional council boundaries but are aligned to territorial authority.

Small population island SA2s are included in their adjacent land-based SA3.

Island SA2s outside territorial authority or region are the same in the SA3 geography.

Inland water SA2s are aggregated and named by territorial authority, as in the urban rural classification.

Inlet SA2s are aggregated and named by territorial authority or regional council where the water area is outside the territorial authority.

Oceanic SA2s translate directly to SA3s as they are already aggregated to regional council.

The 16 non-digitised SA2s are aggregated to the following 4 non-digitised SA3s (SA3 code; SA3 name):

70001; Oceanic outside region, 70002; Oceanic oil rigs, 70003; Islands outside region, 70004; Ross Dependency outside region.

SA3 numbering and naming

Each SA3 is a single geographic entity with a name and a numeric code. The name refers to a suburb, recognised place name, or portion of a territorial authority. In some instances where place names are the same or very similar, the SA3s are differentiated by their territorial authority, for example, Hillcrest (Hamilton City) and Hillcrest (Rotorua District).

SA3 codes have five digits. North Island SA3 codes start with a 5, South Island SA3 codes start with a 6 and non-digitised SA3 codes start with a 7. They are numbered approximately north to south within their respective territorial authorities. When first created in 2025, the last digit of each code was 0. When SA3 boundaries change in future, only the last digit of the code will change to ensure the north-south pattern is maintained.

​

Clipped Version

This clipped version has been created for cartographic purposes and so does not fully represent the official full extent boundaries.

​

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.

​

Macrons

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

​

Digital data

Digital boundary data became freely available on 1 July 2007.

​

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

Labour cost statistics constitute a hierarchical system of multi-annual, yearly and quarterly statistics, designed to provide a comprehensive and detailed picture of the level, structure and short-term development of labour costs in the different sectors of economic activity in the European Union and certain other countries. All statistics are based on a harmonised definition of labour costs.

The quarterly Labour Cost Index (LCI) is one of the Principal European economic indicators. It shows the short-term development of the labour cost, the total cost on an hourly basis of employing labour. In other words, the LCI measures the cost pressure arising from the production factor “labour”.

The data covered by the LCI collection relate to the total average hourly labour costs and its components "wages and salaries" and "employers' social security contributions plus taxes paid minus subsidies received by the employer" (known as the non-wage component of the LCI). The data on vocational training costs and other expenditures such as recruitment costs and working clothes expenditure is not included in the calculation of the labour cost index.

The data is broken down by economic activity (NACE Rev 1.1 Sections C to O (1996Q1-2008Q4) and NACE Rev. 2 Sections B to S (2009Q1 onwards). The data is available for the EU aggregates and the EU Member States, EFTA countries (Iceland and Norway) as well as candidate and potential candidate countries (Serbia and Turkey). The data is available as 'unadjusted data (neither seasonally adjusted nor calendar adjusted data)', 'calendar-adjusted data' as well as 'seasonally and calendar adjusted' data.

The data on the Labour Cost Index is given in the form of index numbers (current base year: 2020) and as annual and quarterly growth rates (comparison with the previous quarter, or the same quarter of the previous year). Since June 2023 (publication of 2023Q1 data) base year of the indices changed from 2016 to 2020. Indices with the base year 2016 will no longer be published.

The National Statistical Institutes compile the indicators based on the available structural and short-term information collected directly from the sampled enterprises or taken from administrative data sources. All enterprises, irrespective of the size (measured by the number of employees) are covered in the LCI.

In addition, Eurostat estimates of the annual labour cost per hour in euros are provided for the EU Member States as well as the whole EU; they were obtained by combining the four-yearly Labour cost survey (LCS) with the quarterly labour cost index. Methodological information related to the annual estimates of hourly labour costs is available in separate metadata accessible here.

Early estimates of the Labour Cost Index (‘flash estimates’ or ‘FEs’) (quarterly)

Since May 2024, Eurostat has started publishing early estimates for the Labour Cost Index (‘flash estimates’ or ‘FEs’). The flash estimates (are published around t+50 days, as specified in the general release calendar of Eurostat, based on the data transmitted at t+45 days. EU countries that participate in the FE data collection are those whose annual number of employees (over the age of 15) represents more than 3% of EU totals or 3% of euro area totals, based on LFS data assessed over a period of three consecutive years. These 9 selected countries (i.e. ‘FE countries ’) are: Germany, France, Italy, Spain, the Netherlands, Belgium, Portugal, Poland and Romania (see table 1).

Table 1: Share of EA/EU employees in each of the participating countries.

(Source: EU-LFS, reference period 2023)