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1. Production of concentrated milk products
Table: 32-10-0247-01
Geography: Canada, Province or territory
Frequency: Monthly
Description: Production of concentrated milk products, Canada and provinces (in tonnes). Data are available on a monthly basis.
Release date: 2024-12-20
2. Daily average foreign exchange rates in Canadian dollars, Bank of Canada
Table: 33-10-0036-01
Geography: Canada
Frequency: Daily
Description:
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: 2024-12-20
3. Experimental estimates for business openings and closures for Canada, provinces and territories, census metropolitan areas, seasonally adjusted
Table: 33-10-0270-01
Geography: Canada, Province or territory, Census metropolitan area
Frequency: Monthly
Description:
This table presents experimental counts of businesses that open, close, or continue their operations each month for various levels of geographic and industry detail across Canada going back to January 2015. The data are available as series that are adjusted for seasonality. The level of geographic detail includes national, provincial and territorial, as well as census metropolitan areas (CMA). The data are also broken down by two-digit North American Industry Classification System (NAICS) with some common aggregations, including one for the total business sector for national, provincial and territorial levels of geography.

Release date: 2024-12-20
4. Exploring a skewness conjecture: Expanding Cochran’s rule to a proportion estimated from a complex sample
Articles and reports: 12-001-X202400200001
Description: Cochran’s rule states that a standard (Wald) two-sided 95% confidence interval around a sample mean drawn from a population with positive skewness is reasonable when the sample size is greater than 25 times the square of the skewness coefficient of the population. We investigate whether a variant of this crude rule applies for a proportion estimated from a stratified simple random sample.
Release date: 2024-12-20
5. Daily rhythm of data quality: Evidence from the Survey of Unemployed Workers in New Jersey
Articles and reports: 12-001-X202400200002
Description: This paper investigates whether survey data quality fluctuates over the day. After laying out the argument theoretically, panel data from the Survey of Unemployed Workers in New Jersey are analyzed. Several indirect indicators of response error are investigated, including item nonresponse, interview completion time, rounding, and measures of the quality of time diary data. The evidence that we assemble for a time of day of interview effect is weak or nonexistent. Item nonresponse and the probability that interview completion time is among the 5% shortest appear to increase in the evening, but a more thorough assessment requires instrumental variables.
Release date: 2024-12-20
6. Recursive Neyman algorithm for optimum sample allocation under box constraints on sample sizes in strata
Articles and reports: 12-001-X202400200003
Description: The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified \pi estimator of the population total (or mean) for a given study variable assumes its minimum. In this work, we consider the optimum allocation of a sample, under lower and upper bounds imposed jointly on sample sizes in strata. We are concerned with the variance function of some generic form that, in particular, covers the case of the simple random sampling without replacement in strata. The goal of this paper is twofold. First, we establish (using the Karush-Kuhn-Tucker conditions) a generic form of the optimal solution, the so-called optimality conditions. Second, based on the established optimality conditions, we derive an efficient recursive algorithm, named RNABOX, which solves the allocation problem under study. The RNABOX can be viewed as a generalization of the classical recursive Neyman allocation algorithm, a popular tool for optimum allocation when only upper bounds are imposed on sample strata-sizes. We implement RNABOX in R as a part of our package stratallo which is available from the Comprehensive R Archive Network (CRAN) repository.
Release date: 2024-12-20
7. Bayesian predictive inference of a finite population mean without specifying the relation between the study variable and the covariates
Articles and reports: 12-001-X202400200004
Description: While we avoid specifying the parametric relationship between the study variable and covariates, we illustrate the advantage of including a spatial component to better account for the covariates in our models to make Bayesian predictive inference. We treat each unique covariate combination as an individual stratum, then we use small area estimation techniques to make inference about the finite population mean of the continuous response variable. The two spatial models used are the conditional autoregressive and simple conditional autoregressive models. We include the spatial effects by creating the adjacency matrix via the Mahalanobis distance between covariates. We also show how to incorporate survey weights into the spatial models when dealing with probability survey data. We compare the results of two non-spatial models including the Scott-Smith model and the Battese, Harter, and Fuller model to the spatial models. We illustrate the comparison between the aforementioned models with an application using BMI data from eight counties in California. Our goal is to have neighboring strata yield similar predictions, and to increase the difference between strata that are not neighbors. Ultimately, using the spatial models shows less global pooling compared to the non-spatial models, which was the desired outcome.
Release date: 2024-12-20
8. Robust adaptive survey design for time changes in mixed-mode response propensities
Articles and reports: 12-001-X202400200005
Description: Adaptive survey designs (ASDs) tailor recruitment protocols to population subgroups that are relevant to a survey. In recent years, effective ASD optimization has been the topic of research and several applications. However, the performance of an optimized ASD over time is sensitive to time changes in response propensities. How adaptation strategies can adjust to such variation over time is not yet fully understood. In this paper, we propose a robust optimization approach in the context of sequential mixed-mode surveys employing Bayesian analysis. The approach is formulated as a mathematical programming problem that explicitly accounts for uncertainty due to time change. ASD decisions can then be made by considering time-dependent variation in conditional mode response propensities and between-mode correlations in response propensities. The approach is demonstrated using a case study: the 2014-2017 Dutch Health Survey. We evaluate the sensitivity of ASD performance to 1) the budget level and 2) the length of applicable historic time-series data. We find there is only a moderate dependence on the budget level and the dependence on historic data is moderated by the amount of seasonality during the year.
Release date: 2024-12-20
9. Investigating mode effects in interviewer variances using two representative multi-mode surveys
Articles and reports: 12-001-X202400200006
Description: As mixed-mode designs become increasingly popular, their effects on data quality have attracted much scholarly attention. Most studies focused on the bias properties of mixed-mode designs; few of them have investigated whether mixed-mode designs have heterogeneous variance structures across modes. While many characteristics of mixed-mode designs, such as varied interviewer usage, systematic differences in respondents, varying levels of social desirability bias, among others, may lead to heterogeneous variances in mode-specific point estimates of population means, this study specifically investigates whether interviewer variances remain consistent across different modes in mixed-mode studies. To address this research question, we utilize data collected from two distinct study designs. In the first design, when interviewers are responsible for either face-to-face or telephone mode, we examine whether there are mode differences in interviewer variances for 1) sensitive political questions, 2) international items, 3) and item missing indicators on international items, using the Arab Barometer wave 6 Jordan data. In the second design, we draw on Health and Retirement Study (HRS) 2016 core survey data to examine the question on three topics when interviewers are responsible for both modes. The topics cover 1) the CESD depression scale, 2) interviewer observations, and 3) the physical activity scale. To account for the lack of interpenetrated designs in both data sources, we include respondent-level covariates in our models. We find significant differences in interviewer variances on one item (twelve items in total) in the Arab Barometer study; whereas for HRS, the results are three out of eighteen. Overall, we find the magnitude of the interviewer variances larger in FTF than TEL on sensitive items. We conduct simulations to understand the power to detect mode effects in the typically modest interviewer sample sizes.
Release date: 2024-12-20
10. Models of linkage error for capture-recapture estimation without clerical reviews
12-001-X202400200007
Description: The capture-recapture method can be applied to measure the coverage of administrative and big data sources, in official statistics. In its basic form, it involves the linkage of two sources while assuming a perfect linkage and other standard assumptions. In practice, linkage errors arise and are a potential source of bias, where the linkage is based on quasi-identifiers. These errors include false positives and false negatives, where the former arise when linking a pair of records from different units, and the latter arise when not linking a pair of records from the same unit. So far, the existing solutions have resorted to costly clerical reviews, or they have made the restrictive conditional independence assumption. In this work, these requirements are relaxed by modeling the number of links from a record instead. The same approach may be taken to estimate the linkage accuracy without clerical reviews, when linking two sources that each have some undercoverage.
Release date: 2024-12-20

Data (12,234)

Data (12,234) (0 to 10 of 12,234 results)

1. Production of concentrated milk products
Table: 32-10-0247-01
Geography: Canada, Province or territory
Frequency: Monthly
Description: Production of concentrated milk products, Canada and provinces (in tonnes). Data are available on a monthly basis.
Release date: 2024-12-20
2. Daily average foreign exchange rates in Canadian dollars, Bank of Canada
Table: 33-10-0036-01
Geography: Canada
Frequency: Daily
Description:
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: 2024-12-20
3. Experimental estimates for business openings and closures for Canada, provinces and territories, census metropolitan areas, seasonally adjusted
Table: 33-10-0270-01
Geography: Canada, Province or territory, Census metropolitan area
Frequency: Monthly
Description:
This table presents experimental counts of businesses that open, close, or continue their operations each month for various levels of geographic and industry detail across Canada going back to January 2015. The data are available as series that are adjusted for seasonality. The level of geographic detail includes national, provincial and territorial, as well as census metropolitan areas (CMA). The data are also broken down by two-digit North American Industry Classification System (NAICS) with some common aggregations, including one for the total business sector for national, provincial and territorial levels of geography.

Release date: 2024-12-20
4. Experimental estimates for business openings and closures by employment size for Canada, provinces and territories, census metropolitan areas, seasonally adjusted
Table: 33-10-0722-01
Geography: Canada, Province or territory, Census metropolitan area
Frequency: Monthly
Description: This table presents experimental counts of businesses that open, close, or continue their operations each month for various levels of geographic and industry detail across Canada going back to January 2015. The data are available as series that are adjusted for seasonality. The level of geographic detail includes national, provincial and territorial, as well as census metropolitan areas (CMA). The data are also broken down by employment size and two-digit North American Industry Classification System (NAICS) with some common aggregations, including one for the total business sector.
Release date: 2024-12-20
5. Environmental and Clean Technology Products Economic Account, production account
Table: 36-10-0627-01
Geography: Canada, Province or territory
Frequency: Annual
Description: Annual output, intermediate consumption, and gross value added of the environmental and clean technology products sector, by goods and services category, for Canada, provinces and territories.
Release date: 2024-12-20
6. Environmental and Clean Technology Products Economic Account, generation of income account
Table: 36-10-0628-01
Geography: Canada, Province or territory
Frequency: Annual
Description: Annual gross value added, taxes less subsidies, compensation of employees, mixed income and gross operating surplus of the environmental and clean technology products sector, per goods and services category, for Canada, provinces and territories.
Release date: 2024-12-20
7. Environmental and Clean Technology Products Economic Account, supply and use table
Table: 36-10-0629-01
Geography: Canada, Province or territory
Frequency: Annual
Description: Annual total supply, output margins, international and interprovincial imports, total use, intermediate input, domestic demand, inventories, and international and interprovincial exports of the environmental and clean technology product sector, per goods and services category, for Canada, provinces and territories.
Release date: 2024-12-20
8. Environmental and Clean Technology Products Economic Account, gross domestic product
Table: 36-10-0630-01
Geography: Canada, Province or territory
Frequency: Annual
Description: Annual gross domestic product at basic prices, implicit gross domestic product deflator, and real gross domestic product at basic prices of the environmental and clean technology products sector, per goods and services category, for Canada, provinces and territories.
Release date: 2024-12-20
9. Environmental and Clean Technology Products Economic Account, international trade in real (volume) terms
Table: 36-10-0631-01
Geography: Canada, Province or territory
Frequency: Annual
Description: Annual international imports and exports of the environmental and clean technology products sector, by goods and services category, for Canada, provinces and territories.
Release date: 2024-12-20
10. Environmental and Clean Technology Products Economic Account, employment
Table: 36-10-0632-01
Geography: Canada, Province or territory
Frequency: Annual
Description: Annual output, intermediate consumption, and gross value added of the environmental and clean technology produtcs sector, by goods and services category, for Canada, provinces and territories.
Release date: 2024-12-20

Analysis (10,160)

Analysis (10,160) (0 to 10 of 10,160 results)

1. Exploring a skewness conjecture: Expanding Cochran’s rule to a proportion estimated from a complex sample
Articles and reports: 12-001-X202400200001
Description: Cochran’s rule states that a standard (Wald) two-sided 95% confidence interval around a sample mean drawn from a population with positive skewness is reasonable when the sample size is greater than 25 times the square of the skewness coefficient of the population. We investigate whether a variant of this crude rule applies for a proportion estimated from a stratified simple random sample.
Release date: 2024-12-20
2. Daily rhythm of data quality: Evidence from the Survey of Unemployed Workers in New Jersey
Articles and reports: 12-001-X202400200002
Description: This paper investigates whether survey data quality fluctuates over the day. After laying out the argument theoretically, panel data from the Survey of Unemployed Workers in New Jersey are analyzed. Several indirect indicators of response error are investigated, including item nonresponse, interview completion time, rounding, and measures of the quality of time diary data. The evidence that we assemble for a time of day of interview effect is weak or nonexistent. Item nonresponse and the probability that interview completion time is among the 5% shortest appear to increase in the evening, but a more thorough assessment requires instrumental variables.
Release date: 2024-12-20
3. Recursive Neyman algorithm for optimum sample allocation under box constraints on sample sizes in strata
Articles and reports: 12-001-X202400200003
Description: The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified \pi estimator of the population total (or mean) for a given study variable assumes its minimum. In this work, we consider the optimum allocation of a sample, under lower and upper bounds imposed jointly on sample sizes in strata. We are concerned with the variance function of some generic form that, in particular, covers the case of the simple random sampling without replacement in strata. The goal of this paper is twofold. First, we establish (using the Karush-Kuhn-Tucker conditions) a generic form of the optimal solution, the so-called optimality conditions. Second, based on the established optimality conditions, we derive an efficient recursive algorithm, named RNABOX, which solves the allocation problem under study. The RNABOX can be viewed as a generalization of the classical recursive Neyman allocation algorithm, a popular tool for optimum allocation when only upper bounds are imposed on sample strata-sizes. We implement RNABOX in R as a part of our package stratallo which is available from the Comprehensive R Archive Network (CRAN) repository.
Release date: 2024-12-20
4. Bayesian predictive inference of a finite population mean without specifying the relation between the study variable and the covariates
Articles and reports: 12-001-X202400200004
Description: While we avoid specifying the parametric relationship between the study variable and covariates, we illustrate the advantage of including a spatial component to better account for the covariates in our models to make Bayesian predictive inference. We treat each unique covariate combination as an individual stratum, then we use small area estimation techniques to make inference about the finite population mean of the continuous response variable. The two spatial models used are the conditional autoregressive and simple conditional autoregressive models. We include the spatial effects by creating the adjacency matrix via the Mahalanobis distance between covariates. We also show how to incorporate survey weights into the spatial models when dealing with probability survey data. We compare the results of two non-spatial models including the Scott-Smith model and the Battese, Harter, and Fuller model to the spatial models. We illustrate the comparison between the aforementioned models with an application using BMI data from eight counties in California. Our goal is to have neighboring strata yield similar predictions, and to increase the difference between strata that are not neighbors. Ultimately, using the spatial models shows less global pooling compared to the non-spatial models, which was the desired outcome.
Release date: 2024-12-20
5. Robust adaptive survey design for time changes in mixed-mode response propensities
Articles and reports: 12-001-X202400200005
Description: Adaptive survey designs (ASDs) tailor recruitment protocols to population subgroups that are relevant to a survey. In recent years, effective ASD optimization has been the topic of research and several applications. However, the performance of an optimized ASD over time is sensitive to time changes in response propensities. How adaptation strategies can adjust to such variation over time is not yet fully understood. In this paper, we propose a robust optimization approach in the context of sequential mixed-mode surveys employing Bayesian analysis. The approach is formulated as a mathematical programming problem that explicitly accounts for uncertainty due to time change. ASD decisions can then be made by considering time-dependent variation in conditional mode response propensities and between-mode correlations in response propensities. The approach is demonstrated using a case study: the 2014-2017 Dutch Health Survey. We evaluate the sensitivity of ASD performance to 1) the budget level and 2) the length of applicable historic time-series data. We find there is only a moderate dependence on the budget level and the dependence on historic data is moderated by the amount of seasonality during the year.
Release date: 2024-12-20
6. Investigating mode effects in interviewer variances using two representative multi-mode surveys
Articles and reports: 12-001-X202400200006
Description: As mixed-mode designs become increasingly popular, their effects on data quality have attracted much scholarly attention. Most studies focused on the bias properties of mixed-mode designs; few of them have investigated whether mixed-mode designs have heterogeneous variance structures across modes. While many characteristics of mixed-mode designs, such as varied interviewer usage, systematic differences in respondents, varying levels of social desirability bias, among others, may lead to heterogeneous variances in mode-specific point estimates of population means, this study specifically investigates whether interviewer variances remain consistent across different modes in mixed-mode studies. To address this research question, we utilize data collected from two distinct study designs. In the first design, when interviewers are responsible for either face-to-face or telephone mode, we examine whether there are mode differences in interviewer variances for 1) sensitive political questions, 2) international items, 3) and item missing indicators on international items, using the Arab Barometer wave 6 Jordan data. In the second design, we draw on Health and Retirement Study (HRS) 2016 core survey data to examine the question on three topics when interviewers are responsible for both modes. The topics cover 1) the CESD depression scale, 2) interviewer observations, and 3) the physical activity scale. To account for the lack of interpenetrated designs in both data sources, we include respondent-level covariates in our models. We find significant differences in interviewer variances on one item (twelve items in total) in the Arab Barometer study; whereas for HRS, the results are three out of eighteen. Overall, we find the magnitude of the interviewer variances larger in FTF than TEL on sensitive items. We conduct simulations to understand the power to detect mode effects in the typically modest interviewer sample sizes.
Release date: 2024-12-20
7. Fully synthetic data for complex surveys
Articles and reports: 12-001-X202400200008
Description: When seeking to release public use files for confidential data, statistical agencies can generate fully synthetic data. We propose an approach for making fully synthetic data from surveys collected with complex sampling designs. Our approach adheres to the general strategy proposed by Rubin (1993). Specifically, we generate pseudo-populations by applying the weighted finite population Bayesian bootstrap to account for survey weights, take simple random samples from those pseudo-populations, estimate synthesis models using these simple random samples, and release simulated data drawn from the models as public use files. To facilitate variance estimation, we use the framework of multiple imputation with two data generation strategies. In the first, we generate multiple data sets from each simple random sample. In the second, we generate a single synthetic data set from each simple random sample. We present multiple imputation combining rules for each setting. We illustrate the repeated sampling properties of the combining rules via simulation studies, including comparisons with synthetic data generation based on pseudo-likelihood methods. We apply the proposed methods to a subset of data from the American Community Survey.
Release date: 2024-12-20
8. A small area estimation approach for reconciling differences in two surveys of recreational fishing effort
Articles and reports: 12-001-X202400200009
Description: Many studies face the problem of comparing estimates obtained with different survey methodology, including differences in frames, measurement instruments, and modes of delivery. The problem arises in multimode surveys and in surveys that are redesigned. Major redesign of survey processes could affect survey estimates systematically, and it is important to quantify and adjust for such discontinuities between the designs to ensure comparability of estimates over time. We propose a small area estimation approach to reconcile two sets of survey estimates, and apply it to two surveys in the Marine Recreational Information Program (MRIP), which monitors recreational fishing along the Atlantic and Gulf coasts of the United States. We develop a log-normal model for the estimates from the two surveys, accounting for temporal dynamics through regression on population size and state-by-wave seasonal factors, and accounting in part for changing coverage properties through regression on wireless telephone penetration. Using the estimated design variances, we develop a regression model that is analytically consistent with the log-normal mean model. We use the modeled design variances in a Fay-Herriot small area estimation procedure to obtain empirical best linear unbiased predictors of the reconciled estimates of fishing effort (requiring predictions at new sets of covariates), and provide an asymptotically valid mean square error approximation.
Release date: 2024-12-20
9. Design-based estimation of small and empty domains in survey data analysis using order constraints
Articles and reports: 12-001-X202400200010
Description: Recent work in survey domain estimation has shown that incorporating a priori assumptions about orderings of population domain means reduces the variance of the estimators and provides smaller confidence intervals with good coverage. Here we show how partial ordering assumptions allow design-based estimation of sample means in domains for which the sample size is zero, with conservative variance estimates and confidence intervals. Order restrictions can also substantially improve estimation and inference in small-size domains. Examples with well-known survey data sets demonstrate the utility of the methods. Code to implement the examples using the R package csurvey is given in the appendix.
Release date: 2024-12-20
10. A hierarchical gamma prior for modeling random effects in small area estimation
Articles and reports: 12-001-X202400200011
Description: Small area estimation (SAE) is becoming increasingly popular among survey statisticians. Since the direct estimates of small areas usually have large standard errors, model-based approaches are often adopted to borrow strength across areas. SAE models often use covariates to link different areas and random effects to account for the additional variation. Recent studies showed that random effects are not necessary for all areas, so global-local (GL) shrinkage priors have been introduced to effectively model the sparsity in random effects. The GL priors vary in tail behavior, and their performance differs under different sparsity levels of random effects. As a result, one needs to fit the model with different choices of priors and then select the most appropriate one based on the deviance information criterion or other evaluation metrics. In this paper, we propose a flexible prior for modeling random effects in SAE. The hyperparameters of the prior determine the tail behavior and can be estimated in a fully Bayesian framework. Therefore, the resulting model is adaptive to the sparsity level of random effects without repetitive fitting. We demonstrate the performance of the proposed prior via simulations and real applications.
Release date: 2024-12-20

Reference (1,945)

Reference (1,945) (0 to 10 of 1,945 results)

1. Departmental Results Report
Notices and consultations: 11-628-X
Description: Departmental Results Reports (DRRs) are part of the Estimates family of documents. Estimates documents support appropriation acts, which specify the amounts and broad purposes for which funds can be spent by the government. The Estimates document family has three parts.

Part I (Government Expenditure Plan) provides an overview of federal spending.

Part II (Main Estimates) lists the financial resources required by individual departments, agencies and Crown corporations for the upcoming fiscal year.

Part III (Departmental Expenditure Plans) consists of two documents. Departmental Plans (DPs) are expenditure plans for each appropriated department and agency (excluding Crown corporations).
Release date: 2024-12-17
2. Census of Environment: Spatial information products
Geographic files and documentation: 16-510-X
Description: 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: 2024-12-16
3. Survey on the Official Language Minority Population: User guide, 2022
Surveys and statistical programs – Documentation: 89-657-X2024009
Description: The Survey on the Official Language Minority Population (SOLMP) user guide contains a description of the survey, along with survey concepts and definitions and an overview of the content development. The target and survey populations, the sample design and sample size are described in the Methodology section. Finally, in the Data Collection module, the collection period and instrument, modes of collection, collection and communications strategies and response rates are provided.
Release date: 2024-12-16
4. Ocean and coastal ecosystem extent: Data product specifications
Geographic files and documentation: 16-510-X2024005
Description: This product contains specifications intended for users of the ocean and coastal ecosystem extent geospatial files. This document provides important technical information for users and links to methodology.
Release date: 2024-12-16
5. Ocean and coastal ecosystem extent: Geospatial files
Geographic files and documentation: 16-510-X2024006
Description: This product contains gridded datasets of ocean and coastal ecosystem extent for ocean and coastal areas of Canada. Mapping the extent of ocean ecosystems is the first stage in creating spatially explicit accounts, to help understand the ocean and coastal ecosystems of Canada. The files cover the area from the coastline, defined by the 2021 Statistics Canada Census of Population, to the outer boundary of Canada’s exclusive economic zone (EEZ). Coastal areas of salt marsh are also included in the files.
Release date: 2024-12-16
6. Latest Developments in the Canadian Economic Accounts
Notices and consultations: 13-605-X
Description: 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: 2024-12-12
7. Technical Reference Guides for the Education and Labour Market Longitudinal Platform (ELMLP)
Surveys and statistical programs – Documentation: 37-20-0001
Description: 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: 2024-12-11
8. Persistence and graduation indicators of postsecondary students, 2011/2012 to 2022/2023
Surveys and statistical programs – Documentation: 37-20-00012024003
Description: This technical reference guide is intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The data for the products associated with this issue are based on the longitudinal Postsecondary Student Information System (PSIS) administrative data files. Statistics Canada has derived a series of annual indicators of public postsecondary students including persistence rates, graduation rates, and average time to graduation by educational qualification, field of study, age group and gender for Canada, the provinces, and the three combined Territories.
Release date: 2024-12-11
9. Multi-year Consolidated Plan for Research, Modelling and Data Development, 2024 to 2026
Surveys and statistical programs – Documentation: 11-633-X2024005
Description: The Analytical Studies and Modelling Branch is the research (ASMB), modelling, training and access hub of Statistics Canada. It focuses on leveraging the agency’s vast data holdings to generate in-depth insights that support evidence-based policy making and to enable others to do so through analytical training and data access. The ASMB, like other program areas in the agency, works to support Statistics Canada’s overall mission of delivering insights through data for a better Canada.
Release date: 2024-12-06
10. Canadian Export Classification
Classification: 65-209-X
Description: 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: 2024-12-05

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