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  • 1. Architectural, Engineering and Related Services Price Index: Data Visualization Tool
    Data Visualization: 71-607-X2020004
    Description: This data visualization tool provides access to current and historical data for the Architectural, Engineering and Related Services Price Index (AESPI), and it's subcomponents at the national level, as well as at regional levels for B.C. and Territories, the Prairies, Ontario, Quebec and the Atlantic Provinces. It allows users to view the index series, quarter-over-quarter and year-over-year percent changes, and to compare and analyze price changes across the different sub-components and regions. This web-based application is updated quarterly.
    Release date: 2026-08-14
  • 2. Monthly Survey of Manufacturing June 2026
    Stats in brief: 11-001-X20262263628
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2026-08-14
  • 3. Wholesale trade June 2026
    Stats in brief: 11-001-X20262263647
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2026-08-14
  • 4. Statistics Canada - Data Visualization Products
    Data Visualization: 71-607-X
    Description: 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: 2026-08-14
  • 5. Fisher commodity price index, United States dollar terms, Bank of Canada, monthly
    Table: 10-10-0132-01
    Geography: Canada
    Frequency: Monthly
    Description: This table contains 7 series, with data starting from 1972 (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 ...), Commodity (7 items: Total; all commodities; Metals and Minerals; Energy; Total excluding energy ...).
    Release date: 2026-08-14
  • 6. Selected United States dollar interest rates, Wednesdays, Bank of Canada
    Table: 10-10-0138-01
    Frequency: Weekly
    Description: This table contains 12 series, with data starting from 1954 (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: United States); Rates (12 items: Federal Reserve Bank of New York - discount rate; Prime rate charged by banks; Federal funds rate;Commercial paper, adjusted: 1 month; ...).
    Release date: 2026-08-14
  • 7. Bank of Canada, money market and other interest rates
    Table: 10-10-0139-01
    Geography: Canada
    Frequency: Daily
    Description: 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: 2026-08-14
  • 8. Fisher commodity price index, United States dollar terms, Bank of Canada, Fisher commodity price index, United States dollar terms, Bank of Canada, weekly
    Table: 10-10-0143-01
    Geography: Canada
    Frequency: Weekly
    Description: This table contains 7 series, with data starting from 1972 (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), Commodity (7 items: Total, all commodities; Total excluding energy; Energy; Metals and Minerals; ...).
    Release date: 2026-08-14
  • 9. Financial market statistics, as at Wednesday, Bank of Canada
    Table: 10-10-0145-01
    Geography: Canada
    Frequency: Weekly
    Description: This table contains 38 series, with data starting from 1957 (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 (38 items: Bank rate; Chartered bank administered interest rates - prime business; Chartered bank - consumer loan rate; Forward premium or discount (-), United States dollars in Canada: 1 month; ...).
    Release date: 2026-08-14
  • 10. Manufacturing sales, by industry for 15 Selected Census Metropolitan Areas
    Table: 16-10-0011-01
    Geography: Census metropolitan area
    Frequency: Monthly
    Description:

    Monthly Canadian manufacturer's sales for 15 census metropolitan areas (CMA) for durable and non-durable goods by North American Industry Classification System (NAICS). Data in thousands of dollars. Unadjusted and seasonally adjusted data available from January 2013 to the current reference month. Not all combinations are available.

    Release date: 2026-08-14
Data (13,299)

Data (13,299) (70 to 80 of 13,299 results)

Analysis (10,828)

Analysis (10,828) (60 to 70 of 10,828 results)

  • 61. Comparing two common approaches to within-household sampling: A field experiment in Costa Rica
    Articles and reports: 12-001-X202600100004
    Description: 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
  • 62. Improving the coverage of confidence intervals with respect to degrees of freedom: Application to the Canadian Census
    Articles and reports: 12-001-X202600100005
    Description: 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
  • 63. Master samples with optimized panels
    Articles and reports: 12-001-X202600100006
    Description: 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
  • 64. Spreading response burden in business surveys at Statistics Netherlands: Evaluating sample coordination methods targeting highly burdened businesses
    Articles and reports: 12-001-X202600100007
    Description: 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
  • 65. Graphical finite population sampling
    Articles and reports: 12-001-X202600100008
    Description: 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
  • 66. The inverse-variance trap: A simple ratio fix for combining skewed data
    Articles and reports: 12-001-X202600100009
    Description: 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
  • 67. Variance of the generalized regression estimator under measurement error
    Articles and reports: 12-001-X202600100010
    Description: 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
  • 68. Bayesian differential privacy for small counties and individual commodities
    Articles and reports: 12-001-X202600100011
    Description: 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
  • 69. Small area estimation of general indicators in off-census years
    Articles and reports: 12-001-X202600100012
    Description: 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
  • 70. Improving measurement error and representativeness in nonprobability surveys
    Articles and reports: 12-001-X202600100013
    Description: 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
Reference (2,031)

Reference (2,031) (30 to 40 of 2,031 results)

  • 31. Statistics Canada Fees Report
    Notices and consultations: 89-26-0001
    Description: The Fees Report must be tabled in parliament annually, as per the Service Fees Act, which came into force in June 2017. The Service Fees Act introduces a modern legislative framework that enables cost-effective delivery of services and, through enhanced reporting to Parliament, improved transparency and oversight.
    Release date: 2025-11-07
  • 32. Longitudinal Administrative Data Dictionary
    Surveys and statistical programs – Documentation: 12-585-X
    Description: This product is the dictionary for the Longitudinal Administrative Databank (LAD). The dictionary contains a complete description for each of the income and demographic variables in the LAD, including name, acronym, definition, source, historical availability and historical continuity.

    The following is a partial list of LAD variables: age, sex, marital status, family type, number and age of children, total income, wages and salaries, self-employment, Employment Insurance, Old Age Security, Canada and Quebec Pension Plans, social assistance, investment income, rental income, alimony, registered retirement savings plan (RRSP) income and contributions, low-income status, full-time education deduction, provincial refundable tax credits, goods and service tax (GST) credits, Canada Child Tax Benefits, selected immigration variables, Tax Free Savings (TFSA) information and Canadian Controlled Private Corporations (CCPC) information.

    Release date: 2025-10-31
  • 33. Technical Guide for the Architectural, Engineering and Related Services Price Index, 2025
    Surveys and statistical programs – Documentation: 62F0014M2025006
    Description: This technical guide describes the methodological details for the Architectural, Engineering and Related Services Price Index (AESPI) from 2024 onward. The document includes information about the purpose of the index, data sources, and index estimation and aggregation.
    Release date: 2025-10-24
  • 34. Technical Guide for the Accounting Services Price Index, 2025
    Surveys and statistical programs – Documentation: 62F0014M2025007
    Description: This technical guide describes the methodological details for the Accounting Services Price Index (ASPI) from 2024 onward. The document includes information about the purpose of the index, data sources, and index estimation and aggregation.
    Release date: 2025-10-24
  • 35. Education Indicators in Canada: Handbook for the Report of the Pan-Canadian Education Indicators Program
    Surveys and statistical programs – Documentation: 81-582-G
    Description: This handbook complements the tables of the Pan-Canadian Education Indicators Program (PCEIP). It is a guide that provides general descriptions for each indicator and indicator component. PCEIP has five broad indicator sets: a portrait of the school-age population; financing education systems; elementary and secondary education; postsecondary education; and transitions and outcomes.

    The Pan-Canadian Education Indicators Program (PCEIP) is a joint venture of Statistics Canada and the Council of Ministers of Education, Canada.

    Release date: 2025-10-24
  • 36. Reference Guide to Canadian International Merchandise Trade Statistics
    Surveys and statistical programs – Documentation: 13-605-X202500100003
    Description: This reference guide presents information to enhance an understanding of Canadian International Merchandise Trade statistics. It provides essential definitions, describes key concepts and methodology, and outlines data processes. An overview of the published data, including descriptions of product, industry, and geographical classifications, is provided along with links to the products where these data are available.
    Release date: 2025-08-29
  • 37. Table builder: Part 6, Summary of data table components, table display and metadata
    Surveys and statistical programs – Documentation: 98-20-00032021041
    Description: The purpose of this series of videos is to provide you with a good understanding of data table building concepts and to present you with some of the data table key components that might come into play when analyzing data. This video will explore data table components, table displays, and metadata.
    Release date: 2025-07-30
  • 38. Census of Population web pages: Data tables, part 2
    Surveys and statistical programs – Documentation: 98-20-00032021043
    Description: This video is part of a series that is designed to give you a basic understanding of the Census of Population web pages. The purpose of this video is to show you how to customize a census table to meet your data needs.
    Release date: 2025-07-30
  • 39. Census of Population concept videos
    Surveys and statistical programs – Documentation: 98-20-0003
    Description: Once every five years, the Census of Population provides a detailed and comprehensive statistical portrait of Canada that is vital to our country. It is the primary source of sociodemographic data for specific population groups such as lone-parent families, Indigenous peoples, immigrants, seniors and language groups.

    In order to help users of census products to better understand the various Census of Population concepts, Statistics Canada has developed, in the context of the activities of the 2021 Census and previous censuses, a collection of short videos. These videos are a reference source for users who are new to census concepts or those who have some experience with these concepts, but may need a refresher or would like to expand their knowledge.

    Release date: 2025-07-30
  • 40. T1 Family File, Final Estimates, 2023
    Surveys and statistical programs – Documentation: 72-212-X2025001
    Description: Data on income of census families, individuals and seniors are derived from the T1 Family File (T1FF). This file is based on information from the T1 form, Income Tax and Benefit Return, which Statistics Canada receives from Canada Revenue Agency (CRA) thirteen months after the end of the taxation year.
    Release date: 2025-07-18

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