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All (67)
All (67) (0 to 10 of 67 results)
- Articles and reports: 17-20-00022026001Description: The Canadian Social Environment Typology (CanSET) is a geographic classification tool to compare neighbourhoods across Canadian Census Metropolitan Areas and Census Agglomerations. It provides three levels of neighbourhood classifications based on combinations of 30 socioeconomic, demographic, ethnocultural and housing variables from the Census of population. Each social environment cluster is a group of similar dissemination areas and represents a unique neighbourhood type. The CanSET data comes with definitions of each neighbourhood type so that users can compare health and social outcomes by neighbourhood characteristics. The CanSET classification includes data and user guide for the 2016 and 2021 versions. Select the version closest to the year of the outcome data. The 2016 CanSET classification is not directly comparable to the 2021 CanSET classification.Release date: 2026-03-19
- Classification: 65-209-XDescription: The Canadian Export Classification is a structured, hierarchical classification system based on the Harmonized Description and Coding System. The HS nomenclature is divided into 21 Sections, which in general, group goods produced in the same sector of the economy.Release date: 2025-12-04
- Classification: 89-26-0004Description: This classification system was developed conjointly by the Social Sciences and Humanities Research Council of Canada (SSHRC), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), and Statistics Canada which is the custodian. This shared standard classification, inspired by the Frascati Model 2015 of the Organisation for Economic Co-operation and Development (OECD), will be used by the federal granting agencies and Statistics Canada to collect, and disseminate data related to research and development in Canada. The Canadian Research and Development Classification (CRDC) first official version was the 2020 Version 1.0, now being replaced by CRDC Version 2.0. The CRDC is revised within 2 years for minor changes, and every five years for major revisions. CRDC 2020 Version 2.0 is composed of 3 main pieces: the type of activity or TOA (with 3 categories), the field of research or FOR (with 1,671 fields at the lowest level) and socioeconomic objective or SEO (with 85 main groups at the lowest level).Release date: 2024-04-30
- Classification: 12-590-XDescription:
The Classification of Instructional Programs (CIP) is used for classifying instructional programs according to field of study. CIP was originally created by the National Center for Education Statistics (NCES) in the United States. It is a hierarchical classification. The classification provides a detailed description of each instructional program class together with illustrative examples of the types of instructional programs found in that class. Illustrative examples are also provided of closely related programs that are classified elsewhere. In addition, the classification includes an introduction to CIP and an alternative structure for the aggregation of field of study data. CIP has a ten-year revision cycle.
Release date: 2022-11-08 - Geographic files and documentation: 12-571-XDescription: The Standard Geographical Classification (SGC) provides a systematic structure for classifying Canada's geographic areas. It is the official classification system used for the Census of Population and other Statistics Canada surveys.The classification is presented in two volumes: Volume I, The Classification and Volume II, Reference Maps.Volume I describes the classification and related standard geographic areas and place names. It presents the names and codes for the geographical regions of Canada, provinces and territories, census divisions and census subdivisions, as well as those of the geographic regions that make up the different variants of the classification. It provides information on changes between the current version of the SGC and the previous one, including changes in name, type or code, and indicates the correspondence between the new and old codes. Volume II contains reference maps.Volume II. Reference Maps is available (12-572-X).Release date: 2022-02-09
- Classification: 12-501-XDescription: The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply-side or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance.
NAICS is a comprehensive system encompassing all economic activities. It has a hierarchical structure. At the highest level, it divides the economy into 20 sectors. At lower levels, it further distinguishes the different economic activities in which businesses are engaged.
Email: statcan.csds-standards-industry-cnsd-normes-industrie.statcan@statcan.gc.ca
Release date: 2022-01-27 - Articles and reports: 11-522-X202100100012Description: The modernization of price statistics by National Statistical Offices (NSO) such as Statistics Canada focuses on the adoption of alternative data sources that include the near-universe of all products sold in the country, a scale that requires machine learning classification of the data. The process of evaluating classifiers to select appropriate ones for production, as well as monitoring classifiers once in production, needs to be based on robust metrics to measure misclassification. As commonly utilized metrics, such as the Fß-score may not take into account key aspects applicable to prices statistics in all cases, such as unequal importance of categories, a careful consideration of the metric space is necessary to select appropriate methods to evaluate classifiers. This working paper provides insight on the metric space applicable to price statistics and proposes an operational framework to evaluate and monitor classifiers, focusing specifically on the needs of the Canadian Consumer Prices Index and demonstrating discussed metrics using a publicly available dataset.
Key Words: Consumer price index; supervised classification; evaluation metrics; taxonomy
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100013Description: Statistics Canada’s Labour Force Survey (LFS) plays a fundamental role in the mandate of Statistics Canada. The labour market information provided by the LFS is among the most timely and important measures of the Canadian economy’s overall performance. An integral part of the LFS monthly data processing is the coding of respondent’s industry according to the North American Industrial Classification System (NAICS), occupation according to the National Occupational Classification System (NOC) and the Primary Class of Workers (PCOW). Each month, up to 20,000 records are coded manually. In 2020, Statistics Canada worked on developing Machine Learning models using fastText to code responses to the LFS questionnaire according to the three classifications mentioned previously. This article will provide an overview on the methodology developed and results obtained from a potential application of the use of fastText into the LFS coding process.
Key Words: Machine Learning; Labour Force Survey; Text classification; fastText.
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100003Description:
The increasing size and richness of digital data allow for modeling more complex relationships and interactions, which is the strongpoint of machine learning. Here we applied gradient boosting to the Dutch system of social statistical datasets to estimate transition probabilities into and out of poverty. Individual estimates are reasonable, but the main advantages of the approach in combination with SHAP and global surrogate models are the simultaneous ranking of hundreds of features by their importance, detailed insight into their relationship with the transition probabilities, and the data-driven identification of subpopulations with relatively high and low transition probabilities. In addition, we decompose the difference in feature importance between general and subpopulation into a frequency and a feature effect. We caution for misinterpretation and discuss future directions.
Key Words: Classification; Explainability; Gradient boosting; Life event; Risk factors; SHAP decomposition.
Release date: 2021-10-15 - Classification: 12-583-XDescription: This publication provides a systematic classification structure to identify and categorize the entire range of occupational activity in Canada. Definitions and occupational titles are provided for each unit group. An alphabetical index of the occupational titles classified to the unit group level is also included.Release date: 2021-09-21
Data (7)
Data (7) ((7 results))
- Table: 99-012-X2011057Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration partDescription:
This table presents a cross-tabulation of data using selected characteristics from the National Household Survey.
Release date: 2013-12-11 - Table: 99-012-X2011058Geography: Province or territoryDescription: This table presents a cross-tabulation of data using selected characteristics from the National Household Survey.Release date: 2013-12-11
- 3. Statistical Area Classification, 2011 ArchivedThematic map: 98-320-X2011003Description:
This map shows the Statistical Area Classification - Variant of SGC 2011. This map illustrates the spatial distribution of CSDs among CMAs, CAs and MIZs.
Release date: 2012-02-08 - Profile of a community or region: 94-581-X2006011Description:
This table contains information from the 2006 Census, presented according to the statistical area classification (SAC). The SAC groups census subdivisions according to whether they are a component of a census metropolitan area, a census agglomeration, a census metropolitan area and census agglomeration influenced zone (strong MIZ, moderate MIZ, weak MIZ or no MIZ) or of the territories (Northwest Territories, Nunavut and Yukon Territory). The SAC is used for data dissemination purposes.
Data characteristics presented according to the SAC include age, marital status, Aboriginal identity, mother tongue, knowledge of official languages, mobility status, immigration, visible minority groups, education, labour force activity, occupation, industry, income and dwellings. Data are presented for Canada, provinces and territories. The data characteristics presented within this table may differ from those of other products in the "Profiles" series.
Release date: 2008-11-25 - Table: 97-556-X2006021Description:
Data for Canada, provinces, territories and census metropolitan areas are shown in this table.
This table is part of the topic 'Mobility and migration', which presents data on the geographic mobility of Canadians; that is, on place of residence one year and five years prior to the census. These data include changes in place of residence for persons who moved within Canada and place of origin for persons who moved to Canada from another country at a given point in time.
It is possible to subscribe to all the day-of-release topic bundles. Refer to Catalogue no. 97-569-XCB for more information.
Release date: 2008-04-08 - Profile of a community or region: 95F0495X2001012Description:
This table contains information from the 2001 Census, presented according to the statistical area classification (SAC). The SAC groups census subdivisions according to whether they are a component of a census metropolitan area, a census agglomeration, a census metropolitan area and census agglomeration influenced zone (strong MIZ, moderate MIZ, weak MIZ or no MIZ) or of the territories (Northwest Territories, Nunavut and Yukon Territory). The SAC is used for data dissemination purposes.
Data characteristics presented according to the SAC include age, visible minority groups, immigration, mother tongue, education, income, work and dwellings. Data are presented for Canada, provinces and territories. The data characteristics presented within this table may differ from those of other products in the "Profiles" series.
Release date: 2004-02-27 - 7. Census Metropolitan Area and Census Agglomeration Influenced Zones (MIZ) with Census Data ArchivedTable: 92F0138M2000001Description: With this working paper, Statistics Canada is releasing 1991 Census data tabulated by a new geographic classification called "census metropolitan area and census agglomeration influenced zones", or MIZ. This classification applies to census subdivisions (municipalities) that lie outside census metropolitan areas and census agglomerations. This part of Canada covers 96% of the country's total land mass and contains 22% of its population, yet up to now we have been limited in our means of differentiating this vast area. The MIZ classification shows the influence of census metropolitan areas (CMA) and census agglomerations (CA) on surrounding census subdivisions as measured by commuting flows based on 1991 Census place of work data. This version of the MIZ classification also incorporates a preliminary version of a north concept that flags census subdivisions according to their location in the north or south of Canada.
The series of tables presented here show detailed demographic, social and economic characteristics for Canada as a whole, for the six major regions of Canada, and for individual provinces and territories. Within each table, the data are subdivided into five categories: census metropolitan area or census agglomeration, strong MIZ, moderate MIZ, weak MIZ and no MIZ. Within each of these categories, the data are further subdivided into north and south.
Readers are invited to review and use the data tables to assess whether this combined MIZ and north/south classification of non-CMA/CA areas provides sufficient detail to support data analysis and research. The intent of this MIZ classification is to reveal previously hidden data detail and thereby help users address issues related to this vast geographic area.
This is the first of three related Geography working papers (catalogue no. 92F0138MPE). The second working paper (no. 2000-2, 92F0138MPE00002) provides background information about the methodology used to delineate the MIZ classification. The third working paper (no. 2000-3, 92F0138MPE00003) describes the methodology used to define a continuous line across Canada that separates the north from the south to further differentiate the MIZ classification.
Release date: 2000-02-03
Analysis (23)
Analysis (23) (0 to 10 of 23 results)
- Articles and reports: 17-20-00022026001Description: The Canadian Social Environment Typology (CanSET) is a geographic classification tool to compare neighbourhoods across Canadian Census Metropolitan Areas and Census Agglomerations. It provides three levels of neighbourhood classifications based on combinations of 30 socioeconomic, demographic, ethnocultural and housing variables from the Census of population. Each social environment cluster is a group of similar dissemination areas and represents a unique neighbourhood type. The CanSET data comes with definitions of each neighbourhood type so that users can compare health and social outcomes by neighbourhood characteristics. The CanSET classification includes data and user guide for the 2016 and 2021 versions. Select the version closest to the year of the outcome data. The 2016 CanSET classification is not directly comparable to the 2021 CanSET classification.Release date: 2026-03-19
- Articles and reports: 11-522-X202100100012Description: The modernization of price statistics by National Statistical Offices (NSO) such as Statistics Canada focuses on the adoption of alternative data sources that include the near-universe of all products sold in the country, a scale that requires machine learning classification of the data. The process of evaluating classifiers to select appropriate ones for production, as well as monitoring classifiers once in production, needs to be based on robust metrics to measure misclassification. As commonly utilized metrics, such as the Fß-score may not take into account key aspects applicable to prices statistics in all cases, such as unequal importance of categories, a careful consideration of the metric space is necessary to select appropriate methods to evaluate classifiers. This working paper provides insight on the metric space applicable to price statistics and proposes an operational framework to evaluate and monitor classifiers, focusing specifically on the needs of the Canadian Consumer Prices Index and demonstrating discussed metrics using a publicly available dataset.
Key Words: Consumer price index; supervised classification; evaluation metrics; taxonomy
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100013Description: Statistics Canada’s Labour Force Survey (LFS) plays a fundamental role in the mandate of Statistics Canada. The labour market information provided by the LFS is among the most timely and important measures of the Canadian economy’s overall performance. An integral part of the LFS monthly data processing is the coding of respondent’s industry according to the North American Industrial Classification System (NAICS), occupation according to the National Occupational Classification System (NOC) and the Primary Class of Workers (PCOW). Each month, up to 20,000 records are coded manually. In 2020, Statistics Canada worked on developing Machine Learning models using fastText to code responses to the LFS questionnaire according to the three classifications mentioned previously. This article will provide an overview on the methodology developed and results obtained from a potential application of the use of fastText into the LFS coding process.
Key Words: Machine Learning; Labour Force Survey; Text classification; fastText.
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100003Description:
The increasing size and richness of digital data allow for modeling more complex relationships and interactions, which is the strongpoint of machine learning. Here we applied gradient boosting to the Dutch system of social statistical datasets to estimate transition probabilities into and out of poverty. Individual estimates are reasonable, but the main advantages of the approach in combination with SHAP and global surrogate models are the simultaneous ranking of hundreds of features by their importance, detailed insight into their relationship with the transition probabilities, and the data-driven identification of subpopulations with relatively high and low transition probabilities. In addition, we decompose the difference in feature importance between general and subpopulation into a frequency and a feature effect. We caution for misinterpretation and discuss future directions.
Key Words: Classification; Explainability; Gradient boosting; Life event; Risk factors; SHAP decomposition.
Release date: 2021-10-15 - Journals and periodicals: 57-602-GDescription:
The objective of this document is to present a proposed Statistical Framework for Energy in Canada, which will help guide data providers and users in the development of a strategic plan for addressing priority elements of the proposed framework.
The framework is intended to apply to energy statistics in Canada in general, with application across a broad range of stakeholders involved in the collection, dissemination and use of energy statistics, including provincial and territorial administrative and statistical agencies.
Release date: 2016-02-19 - Articles and reports: 13-605-X201501014292Description:
This article describes the revisions to the balance of payments data and related statistical products introduced as part of the 2015 Comprehensive Revision of the Canadian System of Macroeconomic Accounts (CSMA). This exercise is conducted to strengthen the overall quality of the international accounts program and to introduce new concepts and classifications as recommended by updated international standards. The revisions are also harmonized with those of the corresponding accounts in the CSMA.
Release date: 2015-11-30 - Articles and reports: 12-001-X201200111683Description:
We consider alternatives to poststratification for doubly classified data in which at least one of the two-way cells is too small to allow the poststratification based upon this double classification. In our study data set, the expected count in the smallest cell is 0.36. One approach is simply to collapse cells. This is likely, however, to destroy the double classification structure. Our alternative approaches allows one to maintain the original double classification of the data. The approaches are based upon the calibration study by Chang and Kott (2008). We choose weight adjustments dependent upon the marginal classifications (but not full cross classification) to minimize an objective function of the differences between the population counts of the two way cells and their sample estimates. In the terminology of Chang and Kott (2008), if the row and column classifications have I and J cells respectively, this results in IJ benchmark variables and I + J - 1 model variables. We study the performance of these estimators by constructing simulation simple random samples from the 2005 Quarterly Census of Employment and Wages which is maintained by the Bureau of Labor Statistics. We use the double classification of state and industry group. In our study, the calibration approaches introduced an asymptotically trivial bias, but reduced the MSE, compared to the unbiased estimator, by as much as 20% for a small sample.
Release date: 2012-06-27 - 8. Self-contained Labour Areas: A Proposed Delineation and Classification by Degree of Rurality ArchivedArticles and reports: 21-006-X2008008Geography: CanadaDescription:
One of the most common terms in economic and social reporting is that of "labour market". This concept is normally used with two main connotations, which to some extent overlap. The first emphasizes a set of employment norms, practices and trends that are in some cases specific to certain occupations or industries. The second connotation emphasizes the spatial dimension of the market, as the geographic area in which a multitude of labour activities occur. In this bulletin, our focus is on this second aspect: we identify a set of self-contained labour areas (SLAs), which in broad terms can be described as geographic spaces in which the majority of the residents in the labour force also have their place of work.
Release date: 2011-12-19 - Articles and reports: 82-003-X200800410747Geography: CanadaDescription:
A selective approach may be used in an ecological study where the aim is to choose a subset of units of analysis (UAs) and produce interpretations about a population of interest (PI) based solely on those UAs. The results for the PI will be reliable if that population is concentrated in the selected UAs and rare in other UAs. This article presents a graphical tool that helps determine whether these conditions are satisfied.
Release date: 2008-12-17 - 10. Labour Force Classification in SLID ArchivedArticles and reports: 75F0002M1992006Description:
Labour force status will be an important analytical variable for many users of SLID data. The document discusses the issues involved in deriving this variable, and details the approach to be adopted.
Briefly, a value will be assigned for every one-week period, with three possibilities: employed, unemployed and not in the labour force. To a large extent, concepts used in the Canadian Labour Force Survey will be used. Since there are several situations where a straightforward approach to the classification is not possible, additional information will be available to data users who wish to adjust the definitions used.
Release date: 2008-02-29
Reference (37)
Reference (37) (20 to 30 of 37 results)
- Classification: 65-209-SDescription:
The Canadian Export Classification, incorporates amendments to the Nomenclature of the Harmonized Commodity and Coding System.
Release date: 2009-01-07 - Surveys and statistical programs – Documentation: 15-206-X2008016Description: This paper focuses on the role of investments in infrastructure in Canada. The size of infrastructure investments relative to other capital stock sets this country apart from most other Organisation for Economic Co-operation and Development countries. The paper reviews the approaches taken by other researchers to define infrastructure. It then outlines a taxonomy to define those assets that should be considered as infrastructure and that can be used to assess the importance of different types of capital investments. It briefly considers how to define the portion of infrastructure that should be considered 'public'. The final two parts of the paper apply the proposed classification system to data on Canada's capital stock, and ask the following questions: how much infrastructure does Canada have and in which sectors of the economy is this infrastructure located? Finally, the paper investigates how Canada's infrastructure has evolved over the last four decades, both in the commercial and non-commercial sectors, and compares these trends with the pattern that can be found in the United States.Release date: 2008-03-12
- Notices and consultations: 13-605-X200700610374Description:
Effective with the 2006 Provincial Economic Accounts release on November 8, 2007, the expenditure-based gross domestic product (GDP) will be converted to a 2002 reference year for its volume and price estimates.
On October 31, 2007, the monthly gross domestic product (GDP) by industry estimates will use the North American Industry Classification System, NAICS 2002, and will convert to reference year 2002 for its volume estimates.
Release date: 2007-10-25 - Geographic files and documentation: 12-571-PDescription:
The Standard Geographical Classification (SGC) is a system of names and codes representing areas of Canada. It consists of a three-tiered hierarchy - province or territory, census division, and census subdivision. This relationship is reflected in the seven-digit code. The SGC is used to identify information for particular geographical areas and to tabulate statistics. This volume is designed as a reference and coding manual. It contains tables of SGC units with their names and codes, as well as tables of metropolitan areas. This preliminary version of Volume I will be followed in January 2007 by the final version.
Release date: 2006-10-18 - Surveys and statistical programs – Documentation: 82-619-M2006003Description:
This document examines the functional limitations, physical, emotional and social, related to the musculoskeletal conditions having the largest impact on the health of Canadians. These functional limitations are described and classified using the Classification and Measurement System of Functional Health (CLAMES).
These descriptions and classifications are the first step in a new approach to measuring the health of Canadians that examines what factors are adversely affecting population health and how to address them. This document also provides health professionals, advocacy groups, and individual Canadians with an overview of how living with certain musculoskeletal conditions affects day-to-day functioning.
Release date: 2006-04-04 - Surveys and statistical programs – Documentation: 84-548-XDescription:
This report describes the design, methodology, and results of the first study undertaken by Statistics Canada to measure the impact on Canadian cause of death trends of a new revision of the World Health Organization's International Classification of Diseases (ICD).
Using 1999 Canadian mortality data, Statistics Canada carried out a comparability, or "bridge-coding", study by dual-coding deaths to both the Ninth and Tenth Revisions of the International Classification of Diseases (ICD-9 and ICD-10). The preliminary results of this exercise were used to generate comparability ratios; these ratios measure the net effect of the new revision, with ratios above 1.00 indicating a net increase in deaths classified to a cause of death, and ratios below 1.00 indicating a net decrease.
The comparability ratios derived from dual-coding medical certificates of cause of death presented in this report estimate the size and direction of the disruption to cause of death trends due to the implementation of ICD-10. Researchers and analysts using Canadian mortality data should use these summary measures to calculate comparability-modified death counts and mortality rates to bridge the gap between ICD-9 and ICD-10.
Release date: 2005-11-23 - Surveys and statistical programs – Documentation: 92-404-GDescription:
This guide will provide users of census data with an understanding of the differences between the NAICS97 and the SIC80, and the impact of those differences on census industry data.
Release date: 2005-07-12 - 28. National Reference Maps, 2001 Census (Geography Products: Geographic Reference Products) ArchivedGeographic files and documentation: 92F0144XDescription:
For the 2001 Census, four national maps (covering all of Canada) show the following standard geographic areas:
(a) Census Divisions, 2001 - Shows the census division (CD) boundaries and codes within each province and territory, on a background of major lakes and rivers. The map also lists the CD names in CD code order, by province and territory.
(b) Economic Regions and Census Divisions, 2001 - Shows the economic region (ER) and census division (CD) boundaries and codes within each province and territory. The map also lists, by province and territory, the ER names in ER code order, within which their component CD codes and names are numerically listed.
(c) Census Metropolitan Areas and Census Agglomerations, 2001 - Shows the general location of census metropolitan areas (CMAs) and census agglomerations (CAs) within each province and territory, with large dots designating CMAs and small dots designating CAs. The map also lists the CMA/CA names in CMA/CA code order, by province and territory.
(d) Statistical Area Classification, 2001 Census Subdivisions - Shows census subdivisions (CSDs) classified by colour according to the category of the Statistical Area Classification (SAC) they are assigned to. The categories include: component of a census metropolitan area/census agglomeration, component of a census metropolitan area and census agglomeration influenced zone (strongly influenced, moderately influenced, weakly influenced or not influenced), or component of the north (Northwest Territories, Nunavut and Yukon Territory).
The scale of the CD, ER, and CD, and CMA and CA maps is 1:10,000,000 (with an inset showing southern Quebec and southern Ontario at 1:5,000,000), and their approximate dimensions are 91 cm by 66 cm (36 inches by 26 inches). The approximate size of the PDF files varies between 1.2 MB and 1.4 MB.
The scale of the SAC map is 1:7,500,000 (with an inset showing southern Quebec and southern Ontario at 1:4,000,000), and its approximate dimensions are 91 cm by 91 cm (36 inches by 36 inches). The approximate size of the PDF files is 4.3 MB.
For the 2001 Census, reference maps are available free on the Internet (www.statcan.gc.ca), or they can be purchased through the nearest Regional Reference Centre in electronic format (PDF on CD-ROM) or paper format.
Release date: 2002-03-12 - Geographic files and documentation: 92F0152XDescription:
This national map shows the boundaries, names and codes of federal electoral districts (FEDs) according to the 1996 Representation Order, on a background of major lakes and rivers. Insets show more detail for the congested areas on the map. The FED map was produced by Natural Resources Canada for Elections Canada. The dimensions of this map are approximately 28 cm by 79 cm (11 inches by 31 inches).
Release date: 2002-03-12 - 30. Adoption of NAICS ArchivedSurveys and statistical programs – Documentation: 13-605-X20010028518Description:
As of September 28, 2001 the annual revision of monthly GDP by industry estimates will include major classification and conceptual changes: Adoption of NAICS.
Release date: 2001-09-28