Saint Vincent and the Grenadines VC: External Health Expenditure Per Capita: Current PPP data was reported at 0.000 Intl $ mn in 2015. This records an increase from the previous number of 0.000 Intl $ mn for 2014. Saint Vincent and the Grenadines VC: External Health Expenditure Per Capita: Current PPP data is updated yearly, averaging 0.000 Intl $ mn from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 0.000 Intl $ mn in 2015 and a record low of 0.000 Intl $ mn in 2002. Saint Vincent and the Grenadines VC: External Health Expenditure Per Capita: Current PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s St. Vincent and the Grenadines – Table VC.World Bank: Health Statistics. Current external expenditures on health per capita expressed in international dollars at purchasing power parity (PPP). External sources are composed of direct foreign transfers and foreign transfers distributed by government encompassing all financial inflows into the national health system from outside the country.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;

VC: Time Required to Enforce a Contract data was reported at 595.000 Day in 2017. This stayed constant from the previous number of 595.000 Day for 2016. VC: Time Required to Enforce a Contract data is updated yearly, averaging 394.000 Day from Dec 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 595.000 Day in 2017 and a record low of 394.000 Day in 2011. VC: Time Required to Enforce a Contract data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s St. Vincent and the Grenadines – Table VC.World Bank: Company Statistics. Time required to enforce a contract is the number of calendar days from the filing of the lawsuit in court until the final determination and, in appropriate cases, payment.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

Saint Vincent and the Grenadines VC: Time Required to Build a Warehouse data was reported at 92.000 Day in 2017. This stayed constant from the previous number of 92.000 Day for 2016. Saint Vincent and the Grenadines VC: Time Required to Build a Warehouse data is updated yearly, averaging 82.000 Day from Dec 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 92.000 Day in 2017 and a record low of 81.000 Day in 2011. Saint Vincent and the Grenadines VC: Time Required to Build a Warehouse data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s St. Vincent and the Grenadines – Table VC.World Bank: Company Statistics. Time required to build a warehouse is the number of calendar days needed to complete the required procedures for building a warehouse. If a procedure can be speeded up at additional cost, the fastest procedure, independent of cost, is chosen.; ; World Bank, Doing Business project (http://www.doingbusiness.org/).; Unweighted average; Data are presented for the survey year instead of publication year.

Monthly data on federally administered Supplemental Security Income payments.

This dataset is a polygon coverage of counties limited to the extent of the Pond Creek coal bed resource areas and attributed with statistics on the thickness of the Pond Creek coal zone, its elevation, and overburden thickness, in feet. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C.

2018-2023 Statistics on the work of the Legal Department

This dataset is the definitive set of statistical area 2 (SA2) boundaries for 2020 as defined by Stats NZ. This version contains 2,255 SA2 categories.

SA2s were introduced as part of the Statistical Standard for Geographic Areas 2018 (SSGA2018) which replaced the New Zealand Standard Areas Classification (NZSAC1992). The SA2 geography replaces the (NZSAC1992) area unit geography.

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.

SA2s are built from SA1s and either define or aggregate to define urban rural 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 rural areas, many SA2s have fewer than 1,000 residents because they are in conservation areas or contain sparse populations that cover a large area.

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

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

Digital boundary data became freely available on 1 July 2007.

Hydrographic and Impairment Statistics (HIS) is a National Park Service (NPS) Water Resources Division (WRD) project established to track certain goals created in response to the Government Performance and Results Act of 1993 (GPRA). One water resources management goal established by the Department of the Interior under GRPA requires NPS to track the percent of its managed surface waters that are meeting Clean Water Act (CWA) water quality standards. This goal requires an accurate inventory that spatially quantifies the surface water hydrography that each bureau manages and a procedure to determine and track which waterbodies are or are not meeting water quality standards as outlined by Section 303(d) of the CWA. This project helps meet this DOI GRPA goal by inventorying and monitoring in a geographic information system for the NPS: (1) CWA 303(d) quality impaired waters and causes; and (2) hydrographic statistics based on the United States Geological Survey (USGS) National Hydrography Dataset (NHD). Hydrographic and 303(d) impairment statistics were evaluated based on a combination of 1:24,000 (NHD) and finer scale data (frequently provided by state GIS layers).

The monthly resident population statistics by gender and age for each township and city in Changhua County.

The CMS Program Statistics - Medicare Physician, Non-Physician Practitioner and Supplier tables provide use and payment data for physicians, other practitioners, limited-licensed practitioners, and durable medical equipment, prosthetic, and orthotic (DMEPOS) suppliers.

For additional information on enrollment, providers, and Medicare use and payment, visit the CMS Program Statistics page.

These data do not exist in a machine-readable format, so the view data and API options are not available. Please use the download function to access the data.

Below is the list of tables:

MDCR PHYSSUPP 1. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Type of Entitlement, Yearly Trend MDCR PHYSSUPP 2. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Demographic Characteristics and Medicare-Medicaid Enrollment Status MDCR PHYSSUPP 3. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, Cost Sharing, and Balance Billing for Original Medicare Beneficiaries, by Area of Residence MDCR PHYSSUPP 4. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Type of Service MDCR PHYSSUPP 5. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Place of Service MDCR PHYSSUPP 6. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization, Program Payments, and Balance Billing for Original Medicare Beneficiaries, by Physician Specialty MDCR PHYSSUPP 7. Medicare Physicians, Non-Physician Practitioners, and Suppliers: Utilization and Program Payments for Original Medicare Beneficiaries, by Berenson-Eggers Type of Service (BETOS) Classification

This table gives an overview of government expenditure on regular education in the Netherlands since 1900. All figures presented have been calculated according to the standardised definitions of the OECD.

Government expenditure on education consists of expenditure by central and local government on education institutions and education. Government finance schools, colleges and universities. It pays for research and development conducted by universities. Furthermore it provides student grants and loans, allowances for school costs, provisions for students with a disability and child care allowances to households as well as subsidies to companies and non-profit organisations.

Total government expenditure is broken down into expenditure on education institutions and education on the one hand and government expenditure on student grants and loans and allowances for school costs to households on the other. If applicable these subjects are broken down into pre-primary and primary education, special needs primary education, secondary education, senior secondary vocational and adult education, higher professional education and university education. Data are available from 1900. Figures for the Second World War period are based on estimations due to a lack of source material.

The table also includes the indicator government expenditure on education as a percentage of gross domestic product (GDP). This indicator is used to compare government expenditure on education internationally. The indicator is compounded on the basis of definitions of the OECD (Organisation for Economic Cooperation and Development). The indicator is also presented in the StatLine table education; Education expenditure and CBS/OECD indicators. Figures for the First World War and Second World War period are not available for this indicator due to a lack of reliable data on GDP for these periods.

The statistic on education spending is compiled on a cash basis. This means that the education expenditure and revenues are allocated to the year in which they are paid out or received. However, the activity or transaction associated with the payment or receipt can take place in a different year.

Statistics Netherlands published the revised National Accounts in June 2018. Among other things, GDP has been adjusted upwards as a result of the revision. The revision has not been extended to the years before 1995. In the indicator “Total government expenditure as % of GDP”, a break occurs between 1994 and 1995 as a result of the revision.

Data available from: 1900

Status of the figures: The figures from 1995 to 2020 are final. The 2021 figures are revised provisional, the 2022 figures are provisional.

Changes on 7 December 2023: The revised provisional figures of 2021 and the provisional figures of 2022 have been added.

When will new figures be published? The final figures for 2021 will be published in the first quarter of 2024. The final figures for 2022 and the provisional figures for 2023 will be published in December 2024.

This dataset presents resources that summarize agency workforce characteristics for classified and unclassified employees separately.

This dataset provides a comprehensive view of government revenue, including detailed classifications of taxes, social contributions, grants receivable, and other revenue.

Dataset contains counts and measures for individuals from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.

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The variables included in this dataset are for the census usually resident population count (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated).

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The variables for part 1 of the dataset are:

• Census usually resident population count
• Census night population count
• Age (5-year groups)
• Age (life cycle groups)
• Median age
• Birthplace (NZ born/overseas born)
• Birthplace (broad geographic areas)
• Ethnicity (total responses) for level 1 and ‘Other Ethnicity’ grouped by ‘New Zealander’ and ‘Other Ethnicity nec’
• Māori descent indicator
• Languages spoken (total responses)
• Official language indicator
• Gender
• Cisgender and transgender status – census usually resident population count aged 15 years and over
• Sex at birth
• Rainbow/LGBTIQ+ indicator for the census usually resident population count aged 15 years and over
• Sexual identity for the census usually resident population count aged 15 years and over
• Legally registered relationship status for the census usually resident population count aged 15 years and over
• Partnership status in current relationship for the census usually resident population count aged 15 years and over
• Number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Average number of children born for the sex at birth female census usually resident population count aged 15 years and over
• Religious affiliation (total responses)
• Cigarette smoking behaviour for the census usually resident population count aged 15 years and over
• Disability indicator for the census usually resident population count aged 5 years and over
• Difficulty communicating for the census usually resident population count aged 5 years and over
• Difficulty hearing for the census usually resident population count aged 5 years and over
• Difficulty remembering or concentrating for the census usually resident population count aged 5 years and over
• Difficulty seeing for the census usually resident population count aged 5 years and over
• Difficulty walking for the census usually resident population count aged 5 years and over
• Difficulty washing for the census usually resident population count aged 5 years and over.

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Download lookup file for part 1 from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Te Whata

Under the Mana Ōrite Relationship Agreement, Te Kāhui Raraunga (TKR) will be publishing Māori descent and iwi affiliation data from the 2023 Census in partnership with Stats NZ. This will be available on Te Whata, a TKR platform.

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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), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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Study participation time series

In the 2013 Census study participation was only collected for the census usually resident population count aged 15 years and over.

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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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Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

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Disability indicator

This data should not be used as an official measure of disability prevalence. Disability prevalence estimates are only available from the 2023 Household Disability Survey. Household Disability Survey 2023: Final content has more information about the survey.

Activity limitations are measured using the Washington Group Short Set (WGSS). The WGSS asks about six basic activities that a person might have difficulty with: seeing, hearing, walking or climbing stairs, remembering or concentrating, washing all over or dressing, and communicating. A person was classified as disabled in the 2023 Census if there was at least one of these activities that they had a lot of difficulty with or could not do at all.

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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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Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value during measures calculations. Averages and medians based on less than six units (e.g. individuals, dwellings, households, families, or extended families) are suppressed. This suppression threshold changes for other quantiles. Where the cells have been suppressed, a placeholder value has been used.

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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

-997 Not available

-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.

Annual statistics of the number of ships and types of goods (on each dock)

This User Guide contains information about the NSUL including: directory content; data currency; the methodology for assigning areas to postcodes; data formats; data quality and limitations and details of recent changes that have impacted on the data. Various annexes and tables provide more detailed supporting information. The download includes PDF and ODT versions of the user guide. (File size - 344 KB)

DO NOT EDIT THIS DATASET. This dataset, which is automatically updated contains Bureau of Labor Statistics data. This dataset is updated by a Socrata process; please contact support@socrata.com if you encounter any questions or issues.