Nonemployer Statistics is an annual series that provides statistics on U.S. businesses with no paid employees or payroll, are subject to federal income taxes, and have receipts of $1,000 or more ($1 or more for the Construction sector). This program is authorized by the United States Code, Titles 13 and 26. Also, the collection provides data for approximately 450 North American Industry Classification System (NAICS) industries at the national, state, county, metropolitan statistical area, and combined statistical area geography levels. The majority of NAICS industries are included with some exceptions as follows: crop and animal production; investment funds, trusts, and other financial vehicles; management of companies and enterprises; and public administration. Data are also presented by Legal Form of Organization (LFO) (U.S. and state only) as filed with the Internal Revenue Service (IRS). Most nonemployers are self-employed individuals operating unincorporated businesses (known as sole proprietorships), which may or may not be the owner's principal source of income. Nonemployers Statistics features nonemployers in several arts-related industries and occupations, including the following: Arts, entertainment, and recreation (NAICS Code 71) Performing arts companies Spectator sports Promoters of performing arts, sports, and similar events Independent artists, writers, and performers Museums, historical sites, and similar institutions Amusement parks and arcades Professional, scientific, and technical services (NAICS Code 54) Architectural services Landscape architectural services Photographic services Retail trade (NAICS Code 44-45) Sporting goods, hobby, and musical instrument stores Sewing, needlework, and piece goods stores Book stores Art dealers Nonemployer Statistics data originate from statistical information obtained through business income tax records that the Internal Revenue Service (IRS) provides to the Census Bureau. The data are processed through various automated and analytical review to eliminate employers from the tabulation, correct and complete data items, remove anomalies, and validate geography coding and industry classification. Prior to publication, the noise infusion method is applied to protect individual businesses from disclosure. Noise infusion was first applied to Nonemployer Statistics in 2005. Prior to 2005, data were suppressed using the complementary cell suppression method. For more information on the coverage and methods used in Nonemployer Statistics, refer to NES Methodology. The majority of all business establishments in the United States are nonemployers, yet these firms average less than 4 percent of all sales and receipts nationally. Due to their small economic impact, these firms are excluded from most other Census Bureau business statistics (the primary exception being the Survey of Business Owners). The Nonemployers Statistics series is the primary resource available to study the scope and activities of nonemployers at a detailed geographic level. For complementary statistics on the firms that do have paid employees, refer to the County Business Patterns. Additional sources of data on small businesses include the Economic Census, and the Statistics of U.S. Businesses. The annual Nonemployer Statistics data are available approximately 18 months after each reference year. Data for years since 2002 are published via comma-delimited format (csv) for spreadsheet or database use, and in the American FactFinder (AFF). For help accessing the data, please refer to the Data User Guide.

This data report presents oceanographic observations made in Massachusetts Bay in August 1998 as part of the Massachusetts Bay Internal Wave Experiment (MBIWE98). MBIWE98 was carried out to characterize large-amplitude internal waves in Massachusetts Bay and to investigate the possible resuspension and transport of bottom sediments caused by these waves. This data report presents a description of the field program, an overview of the data through summary plots and statistics, and the time-series data in NetCDF format. The objective of this report is to make the data available in digital form and to provide summary plots and statistics to facilitate browsing of the data set.

Japan Internal Migrants: Annual: Migration Rate data was reported at 3.930 % in 2017. This records an increase from the previous number of 3.900 % for 2016. Japan Internal Migrants: Annual: Migration Rate data is updated yearly, averaging 5.385 % from Dec 1954 (Median) to 2017, with 64 observations. The data reached an all-time high of 8.020 % in 1970 and a record low of 3.900 % in 2016. Japan Internal Migrants: Annual: Migration Rate data remains active status in CEIC and is reported by Statistical Bureau. The data is categorized under Global Database’s Japan – Table JP.G006: Vital Statistics: Migration.

Table of INEBase Number of organisms that carry out internal R&D. National. Statistics on R&D Activities in the Business Sector

United States US: Internally Displaced Persons: New Displacement Associated with Disasters data was reported at 1,686,000.000 Case in 2017. This records an increase from the previous number of 1,107,000.000 Case for 2016. United States US: Internally Displaced Persons: New Displacement Associated with Disasters data is updated yearly, averaging 188,000.000 Case from Dec 2008 (Median) to 2017, with 9 observations. The data reached an all-time high of 2,020,000.000 Case in 2008 and a record low of 1,300.000 Case in 2009. United States US: Internally Displaced Persons: New Displacement Associated with Disasters data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Population and Urbanization Statistics. Internally displaced persons are defined according to the 1998 Guiding Principles (http://www.internal-displacement.org/publications/1998/ocha-guiding-principles-on-internal-displacement) as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border. 'New Displacement' refers to the number of new cases or incidents of displacement recorded over the specified year, rather than the number of people displaced. This is done because people may have been displaced more than once.; ; The Internal Displacement Monitoring Centre (http://www.internal-displacement.org/); Sum;

Table of INEBase Total internal expenditure in R+D activities as regards the GDP by years y fields of operation. National. Statistics on R&D Activities in the Business Sector

In 2020, the North Italian regions of Emilia-Romagna and Trentino-South Tyrol had the largest increase in inhabitants, with a net migration of 2.9 per 1,000 inhabitants, respectively. On the contrary, Calabria recorded the lowest net migration rate, with a negative value of 4.3. Similarly, several regions in the South and in the Center showed negative figures, which means that the amount of residents who moved out of these regions was higher than the number of residents moving into the same areas.

Annual mid-year data on internal migration moves into and out of each local authority in England and Wales, including moves to and from Scotland and Northern Ireland.

Financial industry internal audit staff gender statistics by position data

The Internal Audit Service market has become an essential component for organizations aiming to enhance governance, risk management, and overall operational efficiency. Internal auditing acts as a critical function that not only evaluates the effectiveness of internal controls but also provides valuable insights for

Laos Postal: Internal: Materials data was reported at 44.230 Ton in 2017. This records an increase from the previous number of 40.280 Ton for 2016. Laos Postal: Internal: Materials data is updated yearly, averaging 8.350 Ton from Dec 1976 (Median) to 2017, with 22 observations. The data reached an all-time high of 47.730 Ton in 2013 and a record low of 0.800 Ton in 2005. Laos Postal: Internal: Materials data remains active status in CEIC and is reported by Lao Statistics Bureau. The data is categorized under Global Database’s Laos – Table LA.TB001: Postal Statistics.

Contains resident demographic data at a summary level. The Resident Data Book is compiled to serve as an information source for queries involving resident demographic as well as a source of data for internal analysis. Statistics are compiled via HUD mandated annual income reviews involving NYCHA Staff and residents. Data is then aggregated and compiled by development. Each record pertains to a single public housing development.

Dataset contains counts for territorial authority local board area (TALB) of usual residence by TALB of usual residence address one year ago and five years ago, and by life cycle age group, for the census usually resident population count, 2023 Census.

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This dataset compares usual residence at the 2023 Census with usual residence one and five years earlier to show population mobility and internal migration patterns of people within New Zealand.

‘Usual residence address’ is the address of the dwelling where a person considers that they usually live.

‘Usual residence one year ago address’ identifies an individual’s usual residence on 7 March 2022, which may be different to their current usual residence on census night 2023 (7 March 2023).

‘Usual residence five years ago address’ identifies an individual’s usual residence on 6 March 2018, which may be different to their current usual residence on census night 2023 (7 March 2023).

Note: This dataset only includes usual residence address information for individuals whose usual residence address one year ago and five years ago is available at TALB.

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Life cycle age groups are categorised as:

• under 15 years
• 15–29 years
• 30–64 years
• 65 years and over.

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

• Territorial authority local board (generalised)

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Footnotes

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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Rows excluded from the dataset

Rows show TALB of usual residence by TALB of usual residence one year ago and five years ago, by life cycle age group. Cells with a number less than six have been confidentialised. Responses to categories unable to be mapped, such as response unidentifiable, not stated, and Auckland (not further defined), have also been excluded from this dataset.

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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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Age quality rating

Age is rated as very high quality.

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

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Census usually resident population quality rating

The census usually resident population count is rated as very high quality.

Census usually resident population count – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Usual residence address quality rating

Usual residence address is rated as high quality.

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

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Usual residence one year ago quality rating

Usual residence one year ago area is rated as high quality.

Usual residence one year ago – 2023 Census: Information by concept has more information, for example, definitions and data quality.

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Usual residence five years ago quality rating

Usual residence five years ago area is rated as high quality.

Usual residence five years ago – 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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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.

Brochure Theme: S7 – Statistical Data – Services, Trade and Transport Under Theme: S700.A1 – Internal trade and transport Brochure Theme: S7 – Statistical Data – Services, Trade and Transport Under Theme:S700.A1 – Internal trade and transportS7 – Statistical Data – Services, Trade and Transport Under Theme: S700.A1 – Internal trade and transport Brochure Theme: S7 – Statistical Data – Services, Trade and Transport

Under Theme: S700.A1 – Internal trade and transport

The Internal Gear Grinder market has emerged as a vital segment in the machinery and manufacturing industries, owing to its crucial role in producing high-precision gears essential for various applications. Internal gear grinders are primarily utilized for the grinding of internal gear teeth to achieve tight toleran

This table contains 46 series, with data for years 1871 - 1971 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (12 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...);  Estimates (4 items: Migrants by province of residence; Migrants by province of birth; Natural population increase; Net migration).

Germany Auto Industry: Internal Expenditure on Research & Development data was reported at 28,746.000 EUR mn in 2022. This records an increase from the previous number of 26,011.000 EUR mn for 2021. Germany Auto Industry: Internal Expenditure on Research & Development data is updated yearly, averaging 23,153.000 EUR mn from Dec 2011 (Median) to 2022, with 12 observations. The data reached an all-time high of 28,746.000 EUR mn in 2022 and a record low of 15,771.000 EUR mn in 2011. Germany Auto Industry: Internal Expenditure on Research & Development data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.RA001: Auto Industry Statistics.

This dataset presents the estimates of the internal and overseas migration statistics of Australia by age by Statistical Area Level 2 (SA2) following the 2016 Australian Statistical Geography Standard (ASGS). The dataset spans from the 2016-17 financial year up to the 2019-20 financial year.

Overseas migration is the movement of people from overseas to Australia's sub-state areas and vice-versa. It cannot be directly measured and is estimated by breaking down overseas migrant arrivals and departures at the state level to sub-state areas, using information from the most recent Census. The state-level overseas migration data is sourced from Department of Home Affairs processing systems, visa information, and incoming passenger cards, and is published in National, state and territory population.

Internal migration is the movement of people across a specified boundary within Australia involving a change in place of usual residence. It cannot be directly measured and is instead estimated using administrative data. The movement of people between and within Australia's states and territories cannot be directly measured and is estimated using administrative data. Internal migration is estimated based on a combination of Census data (usual address one year ago), Medicare change of address data (provided by Services Australia), and Department of Defence records (for military personnel only).

The Medicare source data is assigned to a state or territory and GCCSA for a person's departure and arrival locations, based on the postcodes of their residential addresses as registered with Medicare. Postcodes are assigned wholly to a state/territory and GCCSA based on best fit. Where a postcode is split across areas, it is assigned to the area that contains the majority of that postcode's population.

For more information please visit the Regional population methodology.

AURIN has spatially enabled the original data.

Key Table Information.Table Title.Nonemployer Statistics by Demographics series (NES-D): Legal Form of Organization Statistics for Nonemployer Firms by Industry, Sex, Ethnicity, Race, and Veteran Status for the U.S., States, Metro Areas, and Counties: 2022.Table ID.ABSNESD2022.AB2200NESD03.Survey/Program.Economic Surveys.Year.2022.Dataset.ECNSVY Nonemployer Statistics by Demographics Company Summary.Source.U.S. Census Bureau, 2022 Economic Surveys, Nonemployer Statistics by Demographics.Release Date.2025-05-08.Release Schedule.The Nonemployer Statistics by Demographics (NES-D) is released yearly, beginning in 2017..Sponsor.National Center for Science and Engineering Statistics, U.S. National Science Foundation.Table Universe.Includes U.S. firms with no paid employment or payroll, annual receipts of $1,000 or more ($1 or more in the construction industries) and filing Internal Revenue Service (IRS) tax forms for sole proprietorships (Form 1040, Schedule C), partnerships (Form 1065), or corporations (the Form 1120 series).Data are also obtained from administrative records, the 2022 Economic Census, and other economic surveys..Methodology.Data Items and Other Identifying Records.Number of nonemployer firmsSales, value of shipments, or revenue of nonemployer firms ($1,000)These data are aggregated by sex, ethnicity, race, and veteran status when classifiable.The data are also shown by the following legal form of organization (LFO) categories: S-Corporations C-Corporations Individual proprietorships Partnerships Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the NES-D and the ABS are companies or firms rather than establishments. A company or firm is comprised of one or more in-scope establishments that operate under the ownership or control of a single organization..Geography Coverage.The 2022 data are shown for the total of all sectors (00) and the 2-digit NAICS code levels for:United StatesStates and the District of ColumbiaIn addition, the total of all sectors (00) NAICS is shown for:Metropolitan Statistical AreasMicropolitan Statistical AreasCountiesFor information about geographies, see Geographies..Industry Coverage.The data are shown for the total of all sectors ("00"), and at the 2-digit NAICS code levels depending on geography. Sector "00" is not an official NAICS sector but is rather a way to indicate a total for multiple sectors. Note: Other programs outside of ABS may use sector 00 to indicate when multiple NAICS sectors are being displayed within the same table and/or dataset.The following are excluded from the total of all sectors:Crop and Animal Production (NAICS 111 and 112)Rail Transportation (NAICS 482)Postal Service (NAICS 491)Monetary Authorities-Central Bank (NAICS 521)Funds, Trusts, and Other Financial Vehicles (NAICS 525)Office of Notaries (NAICS 541120)Religious, Grantmaking, Civic, Professional, and Similar Organizations (NAICS 813)Private Households (NAICS 814)Public Administration (NAICS 92)For information about NAICS, see North American Industry Classification System..Sampling.NES-D nonemployer data are not conducted through sampling. Nonemployer Statistics (NES) data originate from statistical information obtained through business income tax records that the Internal Revenue Service (IRS) provides to the Census Bureau. The NES-D adds demographic characteristics to the NES data and produces the total firm counts and the total receipts by those demographic characteristics. The NES-D utilizes various administrative records (AR) and the Census Bureau data sources that include the Business Register (BR), Internal Revenue Service (IRS) tax Form 1040 data, tax Schedule K-1 data, Decennial Census and American Community Survey (ACS) data, Social Security Administration's database (Numident), and AR from the Department of Veterans Affairs (VA).For more information, see Nonemployer Statistics by Demographics Methodology..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. P-7504866, Disclosure Review Board (DRB) approval number: CBDRB-FY25-0195).This dataset contains both nonemployer and employer data.For the nonemployer data, the NES-D uses noise infusion as the primary method of disclosure avoidance for receipts, and In certain circumstances, some individual cells may be suppressed for additional disclosure avoidance. More information on nonemployer firm disclosure avoidance is available in the Nonemployer Statistics by Demographics Methodology.For the employer data, data rows with high relative standard errors (RSE) are not presented. Additionally, firm counts are suppressed when other select statistics in the same row are suppressed. More information on employer firm disclosure avoidance is available in the Annual Business Survey Methodology..Te...

Abstract

The central statistical offices in most countries place heavy emphasis on constructing sound databases for all activities within the Internal Trade sector. PCBS’ Internal Trade Statistics Program is part of the Economic Statistics Program, which is part of the larger program for establishing the System of Official Statistics for Palestine. PCBS initiated, in the reference year 1994, the economic surveys series. The series includes, in addition to Internal Trade survey, surveys on industry, Services, construction-contractors, and transport and storage sectors for the purpose of establishing a time series data base of economic activities in line with international recommendations specified in System of National Account (SNA) 93 and in the UN manual for Services Statistics. The sampling frame for the different economic surveys was based on the findings of the 2007 Establishment Census conducted by PCBS. The services survey provide data needed for:

Objectives: The objective of the survey was to obtain data on:

1. Number of enterprises and persons engaged in Internal Trade by activity and location.
2. Value of output, intermediate consumption and stocks.
3. Value added components.
4. Payments and transfers.
5. Capital formation.
6. Contribution of the surveyed activities to the GDP and other National Accounts variables.

Target Population

PCBS depends on the International and Industrial Classification of all economic activities, version 3, (ISIC - 3) by the United Nation to classify the economic activities. All enterprises and establishments are classified according to the Establishments Census 2007, which works in agreement with (ISIC - 3).
The Internal trade survey covers the following activities: 1. Sale & repair of motor vehicles . 2. Wholesale trade & commission trade . 3. Retail trade, repair of personal goods .

Geographic coverage

West Bank and Gaza Strip

Analysis unit

Enterprise constitutes the primary sampling unit (PSU)

Universe

Sample from Internal Trade Enterprises (privet sector)

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the Internal trade Survey is a single-stage stratified random - systematic sample in which the enterprise constitutes the primary sampling unit (PSU). Three levels of strata were used to arrive at an efficient representative sample (i.e. economic activity, size of employment and geographical levels). .

The sample size amounted to (1,840) enterprises out of the (10,037) enterprises that comprise the survey frame.

Mode of data collection

Face-to-face [f2f]

Research instrument

They are one forms of the Internal trade survey questionnaire 2011 of the Palestinian Territory, it's related to household and branches, and the non-financial companies sector. The questionnaire contains the following main variables: 1. The persons engaged in enterprise and compensation of these employees. 2. Value of output from the main activity and secondary activity. 3. Production inputs of goods and services. 4. Payments and transfers. 5. Taxes on production. 6. Assets and capital formation.

Cleaning operations

To ensure the quality and consistency of data, a set of measures was introduced as follows: · Creation of a data entry program prior to the collection of data to ensure this would be ready. · A set of validation rules were applied to the program to check the consistency of data. · The efficiency of the program was pre-tested by entering a few questionnaires, including incorrect information, and checking its efficiency in capturing the incorrect information. · Well-trained data entry personnel were selected and trained for main data entry. · Weekly data files were received by project management to be checked for accuracy and consistency: correction notes were provided to data entry management for implementation.

Response rate

Response rate: 81.4%

Sampling error estimates

Statistical Errors: The findings of the survey are affected by statistical errors due to using sampling in conducting the survey for the units of the target population, which increases the chances of having variances from the actual values we expect to obtain from the data had we conducted the survey using comprehensive enumeration. The variance of the key goods in the survey was computed and dissemination was carried out on the level of the Palestinian Territory for reasons related to sample design and computation of the variance of the different indicators.

Non-Statistical Errors These types of errors could appear on one or all the survey stages that include data collection and data entry: Response errors: these types of errors are related to, responders, fieldworkers, and data entry personnel's. And to avoid mistakes and reduce the impact has been a series of actions that would enhance the accuracy of the data through a process of data collection from the field and the data processing.

Data appraisal

The data are compatible with ISIC-4 on economic activities, whereas previous reports published adhered to ISIC-3 of economic activities.