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- Annual Income Estimates for Census Families and Individuals (T1 Family File) (136)
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- Longitudinal Administrative Databank (52)
- Annual Survey of Research and Development in Canadian Industry (111)
- Research and Development of Canadian Private Non-Profit Organizations (76)
- Energy Research and Development Expenditures by Area of Technology (8)
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- Survey of Digital Technology and Internet Use (90)
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- Programme for the International Assessment of Adult Competencies (78)
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- Longitudinal Survey of Immigrants to Canada (17)
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- General Social Survey - Giving, Volunteering and Participating (70)
- Canadian Internet Use Survey (141)
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- Public Service Employee Survey (3)
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- Canadian Tobacco, Alcohol and Drugs Survey (13)
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- National Longitudinal Survey of Children and Youth (33)
- General Social Survey - Education, Work and Retirement (6)
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- Time Use Survey (95)
- General Social Survey - Victimization (147)
- General Social Survey - Access to and Use of Information Communication Technology (14)
- Ethnic Diversity Survey (17)
- Annual Survey of the Aquaculture Industry (2)
- Survey of the Construction Industry (1)
- Survey of the Couriers and Local Messengers Industry (12)
- Annual Survey of Service Industries: Food Services and Drinking Places (14)
- Annual Survey of Service Industries: Real Estate Rental and Leasing and Property Management (8)
- Annual Survey of Service Industries: Real Estate Agents, Brokers, Appraisers and Other Real Estate Activities (5)
- Survey of the Taxi and Limousine Services Industry (1)
- Survey of Service Industries: Newspaper Publishers (21)
- Annual Survey of Service Industries: Translation and Interpretation Services (1)
- Annual Survey of Service Industries: Surveying and Mapping (14)
- Annual Survey of Service Industries: Accounting Services (21)
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- Annual Survey of Service Industries: Employment Services (21)
- Annual Survey of Service Industries: Specialized Design (21)
- Annual Survey of Service Industries: Repair and Maintenance Services (7)
- Annual Survey of Service Industries: Automotive Repair and Maintenance Services (1)
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- Survey of Knowledge Management Practices (11)
- Health Services Access Survey (44)
- National Population Health Survey: Health Institutions Component, Longitudinal (5)
- National Population Health Survey: North Component (31)
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- Mental Health and Access to Care Survey (MHACS) (44)
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- Postsecondary Student Information System (232)
- Maternity Experiences Survey (1)
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- National Survey of Community Sector Organizations (3)
- General Social Survey - Social Identity (95)
- Monthly Civil Aviation Survey (11)
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- Balance Sheet of the Agricultural Sector at December 31 (2)
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- Computer and peripherals price indexes (15)
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- Labour Productivity Measures - National (Quarterly) (7)
- Farm Management Survey (57)
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- Feed Grain Purchases Survey (3)
- Annual Industrial Consumption of Energy Survey (10)
- Canadian Community Health Survey - Nutrition (49)
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- Longitudinal Immigration Database (134)
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- Survey of Principals (1)
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- International Survey of Reading Skills (2)
- Canadian Health Measures Survey (225)
- Bioproducts Production and Development Survey (5)
- Register of Postsecondary and Adult Education Institutions (2)
- National Survey of the Work and Health of Nurses (3)
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- Canadian Armed Forces Members and Veterans Mental Health Follow-up Survey (6)
- Culture Trade - Goods (3)
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- Survey of Service Industries: Periodical Publishers (22)
- Survey of Business Incubation (4)
- Survey on the Vitality of Official-Language Minorities (19)
- Crop Protection Survey (1)
- Elementary-Secondary Education Survey (49)
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- Annual Survey of Service Industries: Spectator Sports, Event Promoters, Artists and Related Industries (19)
- Survey of Fraud Against Businesses (1)
- Retail Services Price Index (21)
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- Canadian Survey of Experiences with Primary Health Care (4)
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- Annual Survey of Secondary Distributors of Refined Petroleum Products (2)
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- Canadian Income Survey (110)
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- Nova Scotia re-contact analytical file (1)
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- Survey on Early Learning and Child Care Arrangements (SELCCA) (46)
- Municipal Wastewater Systems in Canada (MWSC) (6)
- Canadian Alcohol and Drugs Survey (CADS) (1)
- Survey on Sexual Misconduct at Work (5)
- Survey of Intellectual Property Awareness and Use (7)
- Transport Canada in brief (17)
- Monthly Renewable Fuel and Hydrogen Survey (MRFHS) (7)
- Canadian international merchandise trade by industry for all countries (5)
- Gender Statistics (7)
- Survey of Postsecondary Faculty and Researchers (12)
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- Resale Residential Property Price Index (RRPPI) (1)
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- Canadian Perspectives Survey Series (CPSS) (39)
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- Canadian Survey on Business Conditions (838)
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- Survey on COVID-19 and Mental Health (4)
- Canadian System of Environmental-Economic Accounts - Ecosystem Accounts (100)
- Personal Protective Equipment Survey (15)
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- Canadian Legal Problems Survey (6)
- Canadian Survey on the Provision of Child Care Services (609)
- Canadian COVID-19 Antibody and Health Survey (CCAHS) (16)
- Impacts of COVID-19 on Health Care Workers: Infection Prevention and Control (ICHCWIPC) (2)
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- Nursing and Residential Care Facility Survey (NRCFS) (12)
- Survey on Before and After School Care in Canada (11)
- Survey on Accessibility in Federal Sector Organizations (SAFSO) (7)
- Survey on Access to Health Care and Pharmaceuticals During the Pandemic (9)
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- Canadian Social Survey (101)
- Survey on the Official Language Minority Population (SOLMP) (19)
- Emergency and recovery benefits (8)
- Canadian Tourism Activity Tracker (3)
- Simcoe Muskoka Opioid Overdose Cohort (9)
- Survey on Health Care Workers' Experiences During the Pandemic (6)
- Provincial and Territorial Culture Indicators (1)
- Office of the Commissioner for Federal Judicial Affairs Canada (FJA) (2)
- Distributions of household economic accounts for wealth of Canadian households (8)
- Distributions of household economic accounts for income, consumption and saving of Canadian households (11)
- Canadian Survey on Early Learning and Child Care (CSELCC) (24)
- Covid 19 Restrictions indexes; Daily (2)
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- Labour Market Indicators (9)
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- Release of new content from the Canadian Veteran Health Survey (1)
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- Survey on Early Learning and Child Care Arrangements - Children with Long-term Conditions and Disabilities (SELCCA - CLCD) (12)
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- Canadian Survey on Interprovincial Trade (CSIT) (40)
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- Pan-Canadian Education Indicators Program (PCEIP) (46)
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Portal
Results
All (26,625)
All (26,625) (0 to 10 of 26,625 results)
- Table: 33-10-0036-01Geography: CanadaFrequency: DailyDescription:
This table contains 27 series, with data starting from 1981 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Type of currency (27 items: Australian dollar, daily average; Brazilian real, daily average; Chinese renminbi, daily average; European euro, daily average; ...).
Release date: 2026-08-13 - Data Visualization: 71-607-XDescription: Statistics Canada produces a variety of interactive visualization tools that present data in a graphical form. These tools provide a useful way of interpreting trends behind our data on various social and economic topics.Release date: 2026-08-13
- Table: 18-10-0178-01Geography: CanadaFrequency: QuarterlyDescription:
Consulting Services Price Index (COSPI) by services. Quarterly data are available from the first quarter of 2014. The table presents data for the most recent reference period and the last four periods. The base period for the index is (2018=100).
Release date: 2026-08-13 - Table: 18-10-0178-02Geography: CanadaFrequency: QuarterlyDescription:
Consulting Services Price Index, percentage change (COSPI) by services. Quarterly data are available from the second quarter of 2014. The table presents quarter-to-quarter and year-to-year percentage changes for various aggregation levels. The base period for the index is (2018=100).
Release date: 2026-08-13 - Stats in brief: 11-001-X202622514183Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2026-08-13
- Data Visualization: 71-607-X2022008Description: The Extractive Sector Transparency Measures Act (ESTMA) Data Portal is a collaboration between Statistics Canada and Natural Resources Canada, which administers the ESTMA. The ESTMA helps the Government of Canada deter corruption in the extractive sector by requiring extractive entities that are active in Canada to publicly disclose, on an annual basis, certain types of payments made to governments in Canada and abroad. The goal of the data portal is to increase the accessibility and utility of the payment information collected under the ESTMA by bringing together all available ESTMA data in one online location, and further enriching the payment data with analytical functions that help users to leverage the complete ESTMA dataset. The database has also been designed with mobility in mind to ensure that users and stakeholders have mobile access to ESTMA data.Release date: 2026-08-13
- Data Visualization: 71-607-X2023022Description: The Canadian Economic Tracker presents selected monthly indicators from Statistics Canada's Common Output Database Repository (CODR) to highlight interrelated dynamics within the Canadian economy.Release date: 2026-08-13
- Table: 10-10-0108-01Geography: CanadaFrequency: MonthlyDescription: This table contains 38 series, with data starting from 1935 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Assets and liabilities (38 items: Total assets; Total; Government of Canada; bonds; Total; Government of Canada; direct and guaranteed securities; Government of Canada; Treasury Bills ...).Release date: 2026-08-13
- Table: 10-10-0139-01Geography: CanadaFrequency: DailyDescription: This table contains 39 series, with data for starting from 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Financial market statistics (39 items: Government of Canada Treasury Bills, 1-month (composite rates); Government of Canada Treasury Bills, 2-month (composite rates); Government of Canada Treasury Bills, 3-month (composite rates);Government of Canada Treasury Bills, 6-month (composite rates); ...).Release date: 2026-08-13
- Table: 10-10-0144-01Geography: CanadaFrequency: WeeklyDescription: This table contains 8 series, with data starting from 1992 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Rates (8 items: Bank rate; Treasury bill auction - average yields: 3 month; Treasury bill auction - average yields: 6 month; Treasury bill auction - average yields: 1 year; ...).Release date: 2026-08-13
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Data (13,294)
Data (13,294) (20 to 30 of 13,294 results)
- Table: 24-10-0058-01Geography: Canada, Province or territoryFrequency: DailyDescription:
The table is part of Frontier Counts. The data comes from the Integrated Primary Inspection Line (IPIL), from the Canada Border Services Agency (CBSA). Keywords include: arrival, automobile, car, entry, international, motorcycle, port of entry, tourism, travel, traveller, visit and visitor.
Release date: 2026-08-11 - Table: 24-10-0059-01Geography: Canada, Province or territoryFrequency: DailyDescription:
The table is part of Frontier Counts. The data comes from the Integrated Primary Inspection Line (IPIL), from the Canada Border Services Agency (CBSA). Keywords include: arrival, crew, entry, international, port of entry, tourism, travel, traveller, visit and visitor.
Release date: 2026-08-11 - Data Visualization: 71-607-X2023020Description: The "Frontier Counts: Interactive Dashboard" provides access to data on the number of border crossings in an interactive and customizable format. The counts include only those travelling for tourism-related purposes. The dashboard includes four visualizations: leading indicator of air arrivals, leading indicator of land arrivals, returning Canadians, and visitors to Canada.Release date: 2026-08-11
- Table: 20-10-0080-01Geography: CanadaFrequency: MonthlyDescription: Retail sales, by commodities classified under the North American Product Classification System (NAPCS) Canada 2022, monthly, Canada.Release date: 2026-08-10
- Table: 32-10-0077-01Geography: Province or territoryFrequency: MonthlyDescription: Farm product prices, crops and livestock, by province (in dollars per metric tonne unless otherwise noted). Data are available on a monthly basis.Release date: 2026-08-10
- Table: 10-10-0136-01Geography: CanadaFrequency: WeeklyDescription: This table contains 29 series, with data starting from 1953 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Assets and liabilities (29 items: Total assets; Total, Government of Canada, direct and guaranteed securities; Government of Canada, Treasury Bills; Total, Government of Canada, bonds; ...).Release date: 2026-08-10
- Data Visualization: 14-20-0001Description: The Canadian Labour Market Observatory consists of interactive data visualization applications showcasing the vast amount of publicly available labour market information. The fully interactive applications allow Canadians to quickly and easily personalize the information in a way that is relevant to them and their interests.Release date: 2026-08-07
- Public use microdata: 71M0001XDescription: This public use microdata file (PUMF) contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). The LFS collects monthly information on the labour market activities of Canada's working age population. This product is for users who prefer to do their own analysis by focusing on specific subgroups in the population or by cross-classifying variables that are not in our catalogued products.
Monthly files are available back to 2006 and can be directly downloaded. For reference periods prior to 2006, files are available by request through Statistics Canada's Electronic File Transfer (EFT) service and date back to 1976.
Release date: 2026-08-07 - 29. Labour force characteristics by gender and detailed age group, monthly, unadjusted for seasonalityTable: 14-10-0017-01Geography: Canada, Province or territoryFrequency: MonthlyDescription: Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by gender and detailed age group.Release date: 2026-08-07
- Table: 14-10-0017-02Geography: Canada, Province or territoryFrequency: MonthlyDescription: Number of persons in the labour force (employment and unemployment) and not in the labour force, unemployment rate, participation rate, and employment rate, by gender and detailed age group. Data are presented for 24 months earlier, 12 months earlier and current month, as well as 24-month and year-over-year level change and percentage change.Release date: 2026-08-07
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Analysis (10,828)
Analysis (10,828) (60 to 70 of 10,828 results)
- Articles and reports: 12-001-X202600100004Description: We test the notion that a quasi-probabilistic method of selecting individuals within households (last birthday, LB) draws in a different sample compared to a non-probabilistic approach that selects respondents according to known parameters on age and gender (frequency matching, FM). With data from an original field experiment, we evaluate fieldwork efficiency (time and completed cases), economy (cost), success in recruiting a representative sample, and differences across a set of attitudinal and behavioral measures. We find that the FM approach performs better on efficiency and cost and achieves a comparable sample; importantly, this comparability extends across measures of personality traits and public opinion. With appropriate caveats, we conclude that researchers’ choice of selection methods should be guided by both theoretical benefits and practical tradeoffs.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100005Description: Confidence intervals are very often constructed based on a probability distribution that uses a certain number of degrees of freedom as a parameter. This is the case with the Student and the modified Wilson confidence intervals, discussed in this article, which use quantiles from the Student distribution where the number of degrees of freedom is generally unknown. For the length of a confidence interval to be representative of the reliability of an estimate, the actual coverage rate must match the nominal rate. To that end, the number of degrees of freedom in the probability distribution used in practice to calculate the confidence interval must be estimated as precisely as possible. An approximate rule is often used, although it tends to overestimate the actual number of degrees of freedom. In this article, a more precise version of degrees of freedom, derived from the Satterthwaite approximation, is obtained in the context of the Canadian Census of Population. The sampling design is equivalent to a simple random design without replacement, cluster-stratified, and the variance estimation method is an adaptation of the balanced repeated replication method. An explicit expression of the degrees of freedom is obtained under these conditions, enabling the factors influencing them to be identified. For comparison, the degree of freedom formula is also established for the conventional variance estimator. A simulation study shows that using this version of degrees of freedom corrects the undercoverage problem observed with the approximate rule, showing the importance of accurately assessing this number.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100006Description: We introduce a general framework for constructing master samples that preserve desirable design properties across panels. The core procedure is to order an initial probability sample. Since the final sequence must be robust to a uniform random rotation, we define and minimize an objective that aggregates panel-level performance across all possible circular panels. A final random rotation is applied to ensure design validity. The framework is flexible with respect to the choice of design criteria, such as spatial balance or marginal balance, and can be implemented efficiently using simulated annealing to obtain high-quality approximate solutions. By construction, the approach supports both positive and negative sample coordination for spatially balanced, marginally balanced, and doubly balanced samples. The method’s versatility is demonstrated through three applications: constructing a master sample with spatially balanced panels, marginally balanced panels, and doubly balanced panels.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100007Description: National statistical institutes operate sample coordination systems to spread the response burden in business surveys. Despite the applied sample coordination and monitoring the response burden, some businesses might still be heavily sampled within a short period. This may lead to a peaking response burden for individual businesses, which could affect response rates and response quality. This paper proposes a new sample coordination method based on Adapted Spatially Correlated Poisson (ASCP) sampling that focuses on businesses with a high response burden. The effects on the response burden will be evaluated in two simulation studies and compared with a stratified approach, a pragmatic method in which sampling fractions are manually adjusted and with the baseline method of ignoring the response burden. For the simulations, real-world scenarios and data from Statistics Netherlands are used. The first simulation study considers a practical situation in which a given sample is adjusted with the aim to avoid the occurrence of businesses with a peaking response burden. The second simulation study analyzes the longer-term effects of the different sample coordination methods and focuses both on the reduction and spread of the response burden. The advantages and disadvantages of the different methods will be explained and discussed in detail, and recommendations for applying these methods at national statistical institutes and other survey agencies will be given.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100008Description: This paper introduces an innovative and intuitive finite population sampling method that has been developed using a unique graphical framework. In this approach, first-order inclusion probabilities are represented as bars on a two-dimensional graph. By manipulating the positions of these bars, researchers can create a wide range of different sampling designs. This graphical visualization of sampling designs facilitates the exploration of alternative designs and may simplify certain aspects of the implementation compared to traditional mathematical algorithms. This novel approach holds significant promise for tackling complex challenges in sampling, such as achieving an optimal design. By applying a version of the greedy best-first search algorithm to this graphical approach, the potential for integrating intelligent algorithms into finite population sampling is demonstrated.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100009Description: Combining estimates from independent surveys via inverse-variance weights can lead to negative bias when unknown variances are estimated and the target variable is non-negative and positively skewed. In such cases, strong positive correlations typically arise between the estimators and their corresponding variance estimators, causing standard linear combinations with inverse-variance weights to exhibit negative bias. We introduce a strikingly simple method to reduce bias: replace the standard weight with the ratio of the estimator to the variance estimator. Under a linear model linking the two, we show that the new ratio-weighted estimator is approximately unbiased, whereas the conventional inverse-variance combination exhibits downward bias. Through simulations, we demonstrate that the new method brings both the bias and the mean squared error closer to the optimum for a wide range of different target variables. As our method uses only standardly reported summary statistics, it can be immediately adopted to reduce this widespread bias and improve the reliability of scientific findings in various fields.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100010Description: With the exception of two-phase sampling, the standard variance approximation of the generalized regression (GREG) estimator assumes that the population totals in the weighting scheme are observed without error. If the weighting model of the GREG estimator contains population totals that are observed with measurement error sources other than the sampling error of first-phase estimates, then this uncertainty will be ignored by the variance approximation of the GREG estimator. This paper proposes a variance approximation for the GREG estimator that accounts for additional uncertainty arising from measurement error in one or more of the population totals used in the weighting scheme. This approach has been developed for, and is being applied to, the Dutch Labour Force Survey (DLFS). The monthly publications of the DLFS are obtained with a time series model, which corrects for rotation group bias and discontinuities caused by major redesigns and the loss of face-to-face interviews during COVID-19. The GREG estimates for the quarterly figures are benchmarked to the average of the monthly publications to enforce numerical consistency between monthly and quarterly publication tables. The standard variance approximation of the GREG estimator assumes that these population totals are observed without error. This results in an underestimation of the variance of the GREG estimator. The variance approximation proposed in this paper results in more realistic standard errors for the quarterly GREG estimates.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100011Description: We construct a hybrid Bayesian method, which includes a differentially private mechanism, to mask Census county totals for a U.S. state on acreage of a commodity. We use surrogates for data collected at the farm level from a past U.S. Census of Agriculture to illustrate our procedure. We use two Bayesian small area models (parametric and mixture) to accommodate the smaller counties with fewer farms and some counties with large acres. In these models, the Laplace distribution provides a differentially private mechanism. In pre-processing, we also incorporate the Census weights to form the observed total acreage, a scaling factor to the Laplace mechanism for each county, a square-root transformation of the observed total acreage to avoid negative masked estimates especially for small counties, and the p-percent rule and the 3+ rule to partition the counties into suppressed counties, non-sensitive counties and sensitive counties. Because of difficulties in specifying and tuning the privacy budget (an unknown parameter), to balance security and utility, we specify a prior for the privacy budget, where the values are not specified, and the Gibbs sampler is used to fit the hierarchical Bayesian models. In post-processing, we use Bayesian predictive inference to obtain masked county acreages, and this includes a benchmarking so that the masked state total matches the observed state total. As a measure of reliability of the Bayesian procedure, we use the posterior coefficients of variation for the masked posterior means of the counties. As a measure of utility, we use the absolute relative errors for the individual counties, together with other global measures. For the sensitive counties, there are some differences between the two small area models but both are much better than an individual area model; the mixture model being the best compromise for security and utility.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100012Description: We propose small area estimators of general indicators in off-census years, which avoid the use of deprecated census microdata, but are nearly optimal in census years. The procedure is based on replacing the obsolete census file with a larger unit-level survey that adequately covers the areas of interest and contains the values of useful auxiliary variables. However, the minimal data requirement of the proposed method is a single survey with microdata on the target variable and suitable auxiliary variables for the period of interest. We also develop an estimator of the mean squared error (MSE) that accounts for the uncertainty introduced by the large survey used to replace the census of auxiliary information. Our empirical results indicate that the proposed predictors perform clearly better than the alternative predictors when census data are outdated, and are very close to optimal ones when census data are correct. They also illustrate that the proposed total MSE estimator corrects for the bias of purely model-based MSE estimators that do not account for the large survey uncertainty.Release date: 2026-06-29
- Articles and reports: 12-001-X202600100013Description: In the age of big data, nonprobability surveys are becoming increasingly abundant. Data integration techniques involving both probability and nonprobability surveys are being extensively used for providing improved estimates for finite population estimation. While much of the existing research has focused on mitigating selection bias in nonprobability surveys, the issue of measurement error within these surveys remains relatively unexplored. Statistical methods devised with the purpose of reducing selection bias are appropriate for reliable estimation, only under the assumption of accuracy of survey responses. Motivated by a recent case study of Kennedy, Mercer and Lau (2024), our research addresses bias from both measurement and sampling errors in nonprobability surveys. In this article, we propose a new data integration method that uses multiple probability and nonprobability surveys and leverages machine learning models to construct a composite estimator. The proposed composite estimator integrates probability and nonprobability surveys, when both contain response variables of interest. We analyze the performance of this estimator in comparison to an existing composite estimator in literature, analytically as well as empirically, using multiple survey data from Kennedy et al. (2024). Finally, we identify conditions under which the proposed estimator outperforms estimators based solely on probability surveys.Release date: 2026-06-29
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Reference (2,031)
Reference (2,031) (0 to 10 of 2,031 results)
- Geographic files and documentation: 92F0138M2026001Description: This document describes the structure of the Dissemination Geography Unique Identifier (DGUID), used to uniquely identify all geographic areas maintained by Statistics Canada and link them to data tables with a geographic dimension in the Common Output Database Repository (CODR).Release date: 2026-08-05
- Geographic files and documentation: 16-510-XDescription: Spatial information products provide users with data for visualization, reference, mapping and spatial analysis using geographical information systems (GIS). Available files include spatial environmental data as well as documentation and metadata. This information is released as part of a suite of products associated with the Census of Environment (CoE). The CoE organizes data about Canada’s natural environment using the System of Environmental-Economic Accounting – Ecosystem Accounting international statistical standard, which takes a spatial approach to accounting for Canada’s ecosystems and natural capital.Release date: 2026-06-25
- Geographic files and documentation: 16-510-X2026002Description: This product contains specifications intended for users of the human landscape modification index (HLMI) geospatial files that represent the degree of direct landscape modifications to Canada's terrestrial and freshwater extent (excluding the Great Lakes) around 2020. This document provides important technical information for users, including scope, data content and structure, data quality and data capture. This document also provides additional information about the datasets used to develop the HLMI.Release date: 2026-06-25
- Surveys and statistical programs – Documentation: 37-20-0001Description: These reference guides are intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The guide provides an overview of the Postsecondary Student Information System (PSIS) and the Registered Apprenticeship Information System (RAIS), the general methodology used to create longitudinal indicators, and important technical information for users.Release date: 2026-06-24
- Surveys and statistical programs – Documentation: 19-20-0001Description: Documents in this series provide insight into the statistical methods used by Statistics Canada to produce official statistics. They include introductory material, in-depth descriptions of techniques and methods, best practices, and guidelines. All documents have undergone review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted methodological standards and practices.Release date: 2026-06-16
- Surveys and statistical programs – Documentation: 19-20-00012026003Description: This article provides nontechnical answers to questions related to the production, use and interpretation of advance indicators for Statistics Canada’s Monthly Survey of Manufacturing, Monthly Wholesale Trade Survey and Monthly Retail Trade Survey.Release date: 2026-06-16
- Surveys and statistical programs – Documentation: 19-20-00012026002Description: This reference document provides answers on selected topics related to the use, interpretation, and calculation of trend-cycle estimates for seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment and trend-cycle estimation found in Statistics Canada publications and reference manuals.Release date: 2026-06-08
- Surveys and statistical programs – Documentation: 19-20-00012026001Description: This reference document provides nontechnical answers on selected topics related to the use and interpretation of seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment found in Statistics Canada publications and reference manuals.Release date: 2026-05-11
- Notices and consultations: 13-605-XDescription: This product contains articles related to the latest methodological, conceptual developments in the Canadian System of Macroeconomic Accounts as well as the analysis of the Canadian economy. It includes articles detailing new methods, concepts and statistical techniques used to compile the Canadian System of Macroeconomic Accounts. It also includes information related to new or expanded data products, provides updates and supplements to information found in various guides and analytical articles touching upon a broad range of topics related to the Canadian economy.Release date: 2026-05-04
- Geographic files and documentation: 82-402-XDescription: Health regions are defined by the provinces and represent administrative areas or regions of interest to health authorities. This product contains correspondence files (linking health regions to latest Census geographic codes) and digital boundary files. User documentation provides an overview of health regions, sources, methods, limitations and product description (file format and layout).
In addition to the geographic files, this product also includes Census data (basic profile) for health regions.
Release date: 2026-04-30
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