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  • Journals and periodicals: 11-402-X
    Geography: Canada
    Description:

    Presented in almanac style, the 2012 Canada Year Book contains more than 500 pages of tables, charts and succinct analytical articles on every major area of Statistics Canada's expertise. The Canada Year Book is the premier reference on the social and economic life of Canada and its citizens.

    Release date: 2012-12-24

  • Table: 15-001-X
    Description:

    This publication contains monthly, quarterly, and annual estimates of gross domestic product for 326 industries, including aggregates and special industry groupings. Estimates are seasonally adjusted, in 1997 dollars, for the year 1997 to the most current period. A brief text, supplemented by charts selected of major industry groupings, provides analytical highlights.

    Release date: 2012-12-21

  • 3. Survey Quality Archived
    Articles and reports: 12-001-X201200211751
    Description:

    Survey quality is a multi-faceted concept that originates from two different development paths. One path is the total survey error paradigm that rests on four pillars providing principles that guide survey design, survey implementation, survey evaluation, and survey data analysis. We should design surveys so that the mean squared error of an estimate is minimized given budget and other constraints. It is important to take all known error sources into account, to monitor major error sources during implementation, to periodically evaluate major error sources and combinations of these sources after the survey is completed, and to study the effects of errors on the survey analysis. In this context survey quality can be measured by the mean squared error and controlled by observations made during implementation and improved by evaluation studies. The paradigm has both strengths and weaknesses. One strength is that research can be defined by error sources and one weakness is that most total survey error assessments are incomplete in the sense that it is not possible to include the effects of all the error sources. The second path is influenced by ideas from the quality management sciences. These sciences concern business excellence in providing products and services with a focus on customers and competition from other providers. These ideas have had a great influence on many statistical organizations. One effect is the acceptance among data providers that product quality cannot be achieved without a sufficient underlying process quality and process quality cannot be achieved without a good organizational quality. These levels can be controlled and evaluated by service level agreements, customer surveys, paradata analysis using statistical process control, and organizational assessment using business excellence models or other sets of criteria. All levels can be improved by conducting improvement projects chosen by means of priority functions. The ultimate goal of improvement projects is that the processes involved should gradually approach a state where they are error-free. Of course, this might be an unattainable goal, albeit one to strive for. It is not realistic to hope for continuous measurements of the total survey error using the mean squared error. Instead one can hope that continuous quality improvement using management science ideas and statistical methods can minimize biases and other survey process problems so that the variance becomes an approximation of the mean squared error. If that can be achieved we have made the two development paths approximately coincide.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211752
    Description:

    Coca is a native bush from the Amazon rainforest from which cocaine, an illegal alkaloid, is extracted. Asking farmers about the extent of their coca cultivation areas is considered a sensitive question in remote coca growing regions in Peru. As a consequence, farmers tend not to participate in surveys, do not respond to the sensitive question(s), or underreport their individual coca cultivation areas. There is a political and policy concern in accurately and reliably measuring coca growing areas, therefore survey methodologists need to determine how to encourage response and truthful reporting of sensitive questions related to coca growing. Specific survey strategies applied in our case study included establishment of trust with farmers, confidentiality assurance, matching interviewer-respondent characteristics, changing the format of the sensitive question(s), and non enforcement of absolute isolation of respondents during the survey. The survey results were validated using satellite data. They suggest that farmers tend to underreport their coca areas to 35 to 40% of their true extent.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211753
    Description:

    Nonresponse in longitudinal studies often occurs in a nonmonotone pattern. In the Survey of Industrial Research and Development (SIRD), it is reasonable to assume that the nonresponse mechanism is past-value-dependent in the sense that the response propensity of a study variable at time point t depends on response status and observed or missing values of the same variable at time points prior to t. Since this nonresponse is nonignorable, the parametric likelihood approach is sensitive to the specification of parametric models on both the joint distribution of variables at different time points and the nonresponse mechanism. The nonmonotone nonresponse also limits the application of inverse propensity weighting methods. By discarding all observed data from a subject after its first missing value, one can create a dataset with a monotone ignorable nonresponse and then apply established methods for ignorable nonresponse. However, discarding observed data is not desirable and it may result in inefficient estimators when many observed data are discarded. We propose to impute nonrespondents through regression under imputation models carefully created under the past-value-dependent nonresponse mechanism. This method does not require any parametric model on the joint distribution of the variables across time points or the nonresponse mechanism. Performance of the estimated means based on the proposed imputation method is investigated through some simulation studies and empirical analysis of the SIRD data.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211754
    Description:

    The propensity-scoring-adjustment approach is commonly used to handle selection bias in survey sampling applications, including unit nonresponse and undercoverage. The propensity score is computed using auxiliary variables observed throughout the sample. We discuss some asymptotic properties of propensity-score-adjusted estimators and derive optimal estimators based on a regression model for the finite population. An optimal propensity-score-adjusted estimator can be implemented using an augmented propensity model. Variance estimation is discussed and the results from two simulation studies are presented.

    Release date: 2012-12-19

  • Surveys and statistical programs – Documentation: 12-001-X201200211755
    Description:

    Non-response in longitudinal studies is addressed by assessing the accuracy of response propensity models constructed to discriminate between and predict different types of non-response. Particular attention is paid to summary measures derived from receiver operating characteristic (ROC) curves and logit rank plots. The ideas are applied to data from the UK Millennium Cohort Study. The results suggest that the ability to discriminate between and predict non-respondents is not high. Weights generated from the response propensity models lead to only small adjustments in employment transitions. Conclusions are drawn in terms of the potential of interventions to prevent non-response.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211756
    Description:

    We propose a new approach to small area estimation based on joint modelling of means and variances. The proposed model and methodology not only improve small area estimators but also yield "smoothed" estimators of the true sampling variances. Maximum likelihood estimation of model parameters is carried out using EM algorithm due to the non-standard form of the likelihood function. Confidence intervals of small area parameters are derived using a more general decision theory approach, unlike the traditional way based on minimizing the squared error loss. Numerical properties of the proposed method are investigated via simulation studies and compared with other competitive methods in the literature. Theoretical justification for the effective performance of the resulting estimators and confidence intervals is also provided.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211757
    Description:

    Collinearities among explanatory variables in linear regression models affect estimates from survey data just as they do in non-survey data. Undesirable effects are unnecessarily inflated standard errors, spuriously low or high t-statistics, and parameter estimates with illogical signs. The available collinearity diagnostics are not generally appropriate for survey data because the variance estimators they incorporate do not properly account for stratification, clustering, and survey weights. In this article, we derive condition indexes and variance decompositions to diagnose collinearity problems in complex survey data. The adapted diagnostics are illustrated with data based on a survey of health characteristics.

    Release date: 2012-12-19

  • Surveys and statistical programs – Documentation: 12-001-X201200211758
    Description:

    This paper develops two Bayesian methods for inference about finite population quantiles of continuous survey variables from unequal probability sampling. The first method estimates cumulative distribution functions of the continuous survey variable by fitting a number of probit penalized spline regression models on the inclusion probabilities. The finite population quantiles are then obtained by inverting the estimated distribution function. This method is quite computationally demanding. The second method predicts non-sampled values by assuming a smoothly-varying relationship between the continuous survey variable and the probability of inclusion, by modeling both the mean function and the variance function using splines. The two Bayesian spline-model-based estimators yield a desirable balance between robustness and efficiency. Simulation studies show that both methods yield smaller root mean squared errors than the sample-weighted estimator and the ratio and difference estimators described by Rao, Kovar, and Mantel (RKM 1990), and are more robust to model misspecification than the regression through the origin model-based estimator described in Chambers and Dunstan (1986). When the sample size is small, the 95% credible intervals of the two new methods have closer to nominal confidence coverage than the sample-weighted estimator.

    Release date: 2012-12-19
Data (171)

Data (171) (0 to 10 of 171 results)

  • Table: 15-001-X
    Description:

    This publication contains monthly, quarterly, and annual estimates of gross domestic product for 326 industries, including aggregates and special industry groupings. Estimates are seasonally adjusted, in 1997 dollars, for the year 1997 to the most current period. A brief text, supplemented by charts selected of major industry groupings, provides analytical highlights.

    Release date: 2012-12-21

  • Table: 16F0006X
    Description:

    This document presents operating and capital expenditures made by primary and manufacturing industries in response to, or in anticipation of, environmental regulations and conventions. It also reports the use of environmental management processes and technologies including those used to reduce greenhouse gas emissions by Canadian businesses. The results are from the Survey of Environmental Protection Expenditures. The data contained in Environmental protection expenditures in the business sector help to fill important gaps in existing information on the demand side of the 'environment industry'. More specifically, it provides a measure of the cost to the industry of adopting pollution prevention and abatement technologies and other environmental protection practices. The document presents comparisons of current year spending with previous years' expenditures.

    Release date: 2012-12-17

  • Table: 54-205-X
    Description:

    This publication presents a comprehensive overview of domestic and international shipping activities at Canadian ports. It provides vessel traffic data and commodity detail by points of loading and unloading; containerization and commodity movements. With the release of the new 2000 issue the transport markets key indicators on the size and structure of the Canadian water carrier industry; as well as financial and operational statistics on revenues and expenditures, assets, liabilities, services, employees, property value and fuel comsumed are not included.

    Release date: 2012-11-30

  • Table: 98-314-X2011047
    Description:

    This topic presents data on the language composition of Canada and illustrates the linguistic characteristics of the Canadian population, including mother tongue, knowledge of official languages, first official language spoken and languages spoken at home.

    This topic also presents data on language retention and language transmission by the parents to the child by other demographic characteristics. Data on languages are presented at the person level.

    Release date: 2012-11-28

  • Profile of a community or region: 98-314-X2011052
    Description:

    Using 2011 Census data, this profile provides a statistical overview of the age and sex as well as families, households, marital status, structural type of dwelling and collectives, and language characteristics for Canada, provinces, territories, census divisions and dissolved census subdivisions.

    In the census product line, groups of related variables are referred to as 'release components of profiles.' These are made available with the major releases of variables of the census cycle, starting with age and sex. Together, they will form a complete Census Profile of all the variables for each level of geography, plus one cumulative profile for the dissolved census subdivisions.

    Starting with the age and sex major day of release, and on major days of release thereafter, profile component data are available at the Canada, province and territory, economic region, census division and census subdivision levels, at the census metropolitan area, census agglomeration, population centre, and census tract levels, designated places, and at the federal electoral district (based on the 2003 Representation Order) level.

    Release date: 2012-11-28

  • Table: 98-312-X2011017
    Description:

    This topic presents data on census families, including the number of families, family size and structure. The data also include persons living in families, with relatives, with non-relatives and living alone. Family structure refers to the classification of census families into married couples or common-law couples (including opposite-sex or same-sex), and lone-parent families.

    Data are also presented on household characteristics. The household type refers to the number and types of census families living in a household. The household size refers to the number of people in the household.

    This topic also presents data on marital status and common-law relationships, by age and sex, for the entire Canadian population. These data show the number of persons who never-married, are married, separated, divorced or widowed, and those who are not married, whether they are living common-law or not.

    Release date: 2012-11-21

  • Table: 98-312-X2011018
    Description:

    This topic presents data on census families, including the number of families, family size and structure. The data also include persons living in families, with relatives, with non-relatives and living alone. Family structure refers to the classification of census families into married couples or common-law couples (including opposite-sex or same-sex), and lone-parent families.

    Data are also presented on household characteristics. The household type refers to the number and types of census families living in a household. The household size refers to the number of people in the household.

    This topic also presents data on marital status and common-law relationships, by age and sex, for the entire Canadian population. These data show the number of persons who never-married, are married, separated, divorced or widowed, and those who are not married, whether they are living common-law or not.

    Release date: 2012-11-21

  • Table: 98-312-X2011022
    Description:

    This topic presents data on census families, including the number of families, family size and structure. The data also include persons living in families, with relatives, with non-relatives and living alone. Family structure refers to the classification of census families into married couples or common-law couples (including opposite-sex or same-sex), and lone-parent families.

    Data are also presented on household characteristics. The household type refers to the number and types of census families living in a household. The household size refers to the number of people in the household.

    This topic also presents data on marital status and common-law relationships, by age and sex, for the entire Canadian population. These data show the number of persons who never-married, are married, separated, divorced or widowed, and those who are not married, whether they are living common-law or not.

    Release date: 2012-11-21

  • Table: 98-312-X2011025
    Description:

    This topic presents data on census families, including the number of families, family size and structure. The data also include persons living in families, with relatives, with non-relatives and living alone. Family structure refers to the classification of census families into married couples or common-law couples (including opposite-sex or same-sex), and lone-parent families.

    Data are also presented on household characteristics. The household type refers to the number and types of census families living in a household. The household size refers to the number of people in the household.

    This topic also presents data on marital status and common-law relationships, by age and sex, for the entire Canadian population. These data show the number of persons who never-married, are married, separated, divorced or widowed, and those who are not married, whether they are living common-law or not.

    Release date: 2012-11-21

  • Table: 98-312-X2011028
    Description:

    This topic presents data on census families, including the number of families, family size and structure. The data also include persons living in families, with relatives, with non-relatives and living alone. Family structure refers to the classification of census families into married couples or common-law couples (including opposite-sex or same-sex), and lone-parent families.

    Data are also presented on household characteristics. The household type refers to the number and types of census families living in a household. The household size refers to the number of people in the household.

    This topic also presents data on marital status and common-law relationships, by age and sex, for the entire Canadian population. These data show the number of persons who never-married, are married, separated, divorced or widowed, and those who are not married, whether they are living common-law or not.

    Release date: 2012-11-21
Analysis (210)

Analysis (210) (0 to 10 of 210 results)

  • Journals and periodicals: 11-402-X
    Geography: Canada
    Description:

    Presented in almanac style, the 2012 Canada Year Book contains more than 500 pages of tables, charts and succinct analytical articles on every major area of Statistics Canada's expertise. The Canada Year Book is the premier reference on the social and economic life of Canada and its citizens.

    Release date: 2012-12-24

  • 2. Survey Quality Archived
    Articles and reports: 12-001-X201200211751
    Description:

    Survey quality is a multi-faceted concept that originates from two different development paths. One path is the total survey error paradigm that rests on four pillars providing principles that guide survey design, survey implementation, survey evaluation, and survey data analysis. We should design surveys so that the mean squared error of an estimate is minimized given budget and other constraints. It is important to take all known error sources into account, to monitor major error sources during implementation, to periodically evaluate major error sources and combinations of these sources after the survey is completed, and to study the effects of errors on the survey analysis. In this context survey quality can be measured by the mean squared error and controlled by observations made during implementation and improved by evaluation studies. The paradigm has both strengths and weaknesses. One strength is that research can be defined by error sources and one weakness is that most total survey error assessments are incomplete in the sense that it is not possible to include the effects of all the error sources. The second path is influenced by ideas from the quality management sciences. These sciences concern business excellence in providing products and services with a focus on customers and competition from other providers. These ideas have had a great influence on many statistical organizations. One effect is the acceptance among data providers that product quality cannot be achieved without a sufficient underlying process quality and process quality cannot be achieved without a good organizational quality. These levels can be controlled and evaluated by service level agreements, customer surveys, paradata analysis using statistical process control, and organizational assessment using business excellence models or other sets of criteria. All levels can be improved by conducting improvement projects chosen by means of priority functions. The ultimate goal of improvement projects is that the processes involved should gradually approach a state where they are error-free. Of course, this might be an unattainable goal, albeit one to strive for. It is not realistic to hope for continuous measurements of the total survey error using the mean squared error. Instead one can hope that continuous quality improvement using management science ideas and statistical methods can minimize biases and other survey process problems so that the variance becomes an approximation of the mean squared error. If that can be achieved we have made the two development paths approximately coincide.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211752
    Description:

    Coca is a native bush from the Amazon rainforest from which cocaine, an illegal alkaloid, is extracted. Asking farmers about the extent of their coca cultivation areas is considered a sensitive question in remote coca growing regions in Peru. As a consequence, farmers tend not to participate in surveys, do not respond to the sensitive question(s), or underreport their individual coca cultivation areas. There is a political and policy concern in accurately and reliably measuring coca growing areas, therefore survey methodologists need to determine how to encourage response and truthful reporting of sensitive questions related to coca growing. Specific survey strategies applied in our case study included establishment of trust with farmers, confidentiality assurance, matching interviewer-respondent characteristics, changing the format of the sensitive question(s), and non enforcement of absolute isolation of respondents during the survey. The survey results were validated using satellite data. They suggest that farmers tend to underreport their coca areas to 35 to 40% of their true extent.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211753
    Description:

    Nonresponse in longitudinal studies often occurs in a nonmonotone pattern. In the Survey of Industrial Research and Development (SIRD), it is reasonable to assume that the nonresponse mechanism is past-value-dependent in the sense that the response propensity of a study variable at time point t depends on response status and observed or missing values of the same variable at time points prior to t. Since this nonresponse is nonignorable, the parametric likelihood approach is sensitive to the specification of parametric models on both the joint distribution of variables at different time points and the nonresponse mechanism. The nonmonotone nonresponse also limits the application of inverse propensity weighting methods. By discarding all observed data from a subject after its first missing value, one can create a dataset with a monotone ignorable nonresponse and then apply established methods for ignorable nonresponse. However, discarding observed data is not desirable and it may result in inefficient estimators when many observed data are discarded. We propose to impute nonrespondents through regression under imputation models carefully created under the past-value-dependent nonresponse mechanism. This method does not require any parametric model on the joint distribution of the variables across time points or the nonresponse mechanism. Performance of the estimated means based on the proposed imputation method is investigated through some simulation studies and empirical analysis of the SIRD data.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211754
    Description:

    The propensity-scoring-adjustment approach is commonly used to handle selection bias in survey sampling applications, including unit nonresponse and undercoverage. The propensity score is computed using auxiliary variables observed throughout the sample. We discuss some asymptotic properties of propensity-score-adjusted estimators and derive optimal estimators based on a regression model for the finite population. An optimal propensity-score-adjusted estimator can be implemented using an augmented propensity model. Variance estimation is discussed and the results from two simulation studies are presented.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211756
    Description:

    We propose a new approach to small area estimation based on joint modelling of means and variances. The proposed model and methodology not only improve small area estimators but also yield "smoothed" estimators of the true sampling variances. Maximum likelihood estimation of model parameters is carried out using EM algorithm due to the non-standard form of the likelihood function. Confidence intervals of small area parameters are derived using a more general decision theory approach, unlike the traditional way based on minimizing the squared error loss. Numerical properties of the proposed method are investigated via simulation studies and compared with other competitive methods in the literature. Theoretical justification for the effective performance of the resulting estimators and confidence intervals is also provided.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211757
    Description:

    Collinearities among explanatory variables in linear regression models affect estimates from survey data just as they do in non-survey data. Undesirable effects are unnecessarily inflated standard errors, spuriously low or high t-statistics, and parameter estimates with illogical signs. The available collinearity diagnostics are not generally appropriate for survey data because the variance estimators they incorporate do not properly account for stratification, clustering, and survey weights. In this article, we derive condition indexes and variance decompositions to diagnose collinearity problems in complex survey data. The adapted diagnostics are illustrated with data based on a survey of health characteristics.

    Release date: 2012-12-19

  • Articles and reports: 12-001-X201200211759
    Description:

    A benefit of multiple imputation is that it allows users to make valid inferences using standard methods with simple combining rules. Existing combining rules for multivariate hypothesis tests fail when the sampling error is zero. This paper proposes modified tests for use with finite population analyses of multiply imputed census data for the applications of disclosure limitation and missing data and evaluates their frequentist properties through simulation.

    Release date: 2012-12-19

  • Articles and reports: 82-003-X201200411760
    Geography: Canada
    Description:

    This study uses data from the 2009 Canadian Community Health Survey-Healthy Aging to provide a profile of community-dwelling seniors receiving home care and describe the types of care they receive from formal and informal sources. Seniors' unmet needs for professional home care are also examined.

    Release date: 2012-12-19

  • Articles and reports: 82-003-X201200411761
    Geography: Canada
    Description:

    Data from the Discharge Abstract Database of the Canadian Institute for Health Information were used to examine acute care hospital days for patients with a mental condition coded as the most responsible diagnosis or a comorbid diagnosis in 2009/2010.

    Release date: 2012-12-19
Reference (27)

Reference (27) (10 to 20 of 27 results)

  • Surveys and statistical programs – Documentation: 12-001-X201200111680
    Description:

    Survey data are potentially affected by interviewer falsifications with data fabrication being the most blatant form. Even a small number of fabricated interviews might seriously impair the results of further empirical analysis. Besides reinterviews, some statistical approaches have been proposed for identifying this type of fraudulent behaviour. With the help of a small dataset, this paper demonstrates how cluster analysis, which is not commonly employed in this context, might be used to identify interviewers who falsify their work assignments. Several indicators are combined to classify 'at risk' interviewers based solely on the data collected. This multivariate classification seems superior to the application of a single indicator such as Benford's law.

    Release date: 2012-06-27

  • Surveys and statistical programs – Documentation: 12-001-X201200111683
    Description:

    We consider alternatives to poststratification for doubly classified data in which at least one of the two-way cells is too small to allow the poststratification based upon this double classification. In our study data set, the expected count in the smallest cell is 0.36. One approach is simply to collapse cells. This is likely, however, to destroy the double classification structure. Our alternative approaches allows one to maintain the original double classification of the data. The approaches are based upon the calibration study by Chang and Kott (2008). We choose weight adjustments dependent upon the marginal classifications (but not full cross classification) to minimize an objective function of the differences between the population counts of the two way cells and their sample estimates. In the terminology of Chang and Kott (2008), if the row and column classifications have I and J cells respectively, this results in IJ benchmark variables and I + J - 1 model variables. We study the performance of these estimators by constructing simulation simple random samples from the 2005 Quarterly Census of Employment and Wages which is maintained by the Bureau of Labor Statistics. We use the double classification of state and industry group. In our study, the calibration approaches introduced an asymptotically trivial bias, but reduced the MSE, compared to the unbiased estimator, by as much as 20% for a small sample.

    Release date: 2012-06-27

  • Surveys and statistical programs – Documentation: 12-001-X201200111687
    Description:

    To create public use files from large scale surveys, statistical agencies sometimes release random subsamples of the original records. Random subsampling reduces file sizes for secondary data analysts and reduces risks of unintended disclosures of survey participants' confidential information. However, subsampling does not eliminate risks, so that alteration of the data is needed before dissemination. We propose to create disclosure-protected subsamples from large scale surveys based on multiple imputation. The idea is to replace identifying or sensitive values in the original sample with draws from statistical models, and release subsamples of the disclosure-protected data. We present methods for making inferences with the multiple synthetic subsamples.

    Release date: 2012-06-27

  • Surveys and statistical programs – Documentation: 12-001-X201200111688
    Description:

    We study the problem of nonignorable nonresponse in a two dimensional contingency table which can be constructed for each of several small areas when there is both item and unit nonresponse. In general, the provision for both types of nonresponse with small areas introduces significant additional complexity in the estimation of model parameters. For this paper, we conceptualize the full data array for each area to consist of a table for complete data and three supplemental tables for missing row data, missing column data, and missing row and column data. For nonignorable nonresponse, the total cell probabilities are allowed to vary by area, cell and these three types of "missingness". The underlying cell probabilities (i.e., those which would apply if full classification were always possible) for each area are generated from a common distribution and their similarity across the areas is parametrically quantified. Our approach is an extension of the selection approach for nonignorable nonresponse investigated by Nandram and Choi (2002a, b) for binary data; this extension creates additional complexity because of the multivariate nature of the data coupled with the small area structure. As in that earlier work, the extension is an expansion model centered on an ignorable nonresponse model so that the total cell probability is dependent upon which of the categories is the response. Our investigation employs hierarchical Bayesian models and Markov chain Monte Carlo methods for posterior inference. The models and methods are illustrated with data from the third National Health and Nutrition Examination Survey.

    Release date: 2012-06-27

  • Notices and consultations: 13-605-X201200111671
    Description:

    Macroeconomic data for Canada, including Canada's National Accounts (gross domestic product (GDP), saving and net worth), Balance of International Payments (current and capital account surplus or deficit and International Investment Position) and Government Financial Statistics (government deficit and debt) are based on international standards. These international standards are set on a coordinated basis by international organizations including the United Nations, the Organisation for Economic Cooperation and Development (OECD), the International Monetary Fund (IMF), the World Bank and Eurostat, with input from experts around the world. Canada has always played an important role in the development and updating of these standards as they have transformed from the crude guidelines of the early to mid 20th century to the fully articulated standards that exist today.

    The purpose of this document is to introduce a new presentation of the quarterly National Accounts (Income and Expenditure Accounts, Financial Flow Accounts and National Balance Sheet Accounts) that will be published with the conversion of the Canadian National Accounts to the latest international standard - System of National Accounts 2008.

    Release date: 2012-05-30

  • Geographic files and documentation: 92-637-G
    Description:

    This Cartographic Boundary File for Canada contains the boundaries of all 82 census agricultural regions delineated for the 2011 Census of Agriculture together with the shoreline around Canada and the larger inland lakes, all integrated in a single layer. The boundary file co-ordinates are latitude/longitude and are based on the North American Datum of 1983 (NAD83). The file is available in ARC/INFO Interchange, MapInfo Interchange and Geography Markup Language formats.A reference guide is also provided.

    Release date: 2012-05-10

  • Geographic files and documentation: 92-637-X
    Description:

    This Cartographic Boundary File for Canada contains the boundaries of all 82 census agricultural regions delineated for the 2011 Census of Agriculture together with the shoreline around Canada and the larger inland lakes, all integrated in a single layer. The boundary file co-ordinates are latitude/longitude and are based on the North American Datum of 1983 (NAD83). The file is available in ARC/INFO Interchange, MapInfo Interchange and Geography Markup Language formats.

    A reference guide is also provided.

    Release date: 2012-05-10

  • Notices and consultations: 62F0026M2012001
    Geography: Province or territory
    Description:

    This report describes the quality indicators produced for the 2010 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.

    Release date: 2012-04-25

  • Notices and consultations: 62F0026M2012002
    Description:

    Starting with the 2010 survey year, the Survey of Household Spending (SHS) has used a different collection methodology from previous surveys. The new methodology combines a questionnaire and a diary of expenses. Also, data collection is now continuous throughout the year. This note provides information to users and prospective users of data from the SHS about the methodological differences between the redesigned SHS and the former SHS.

    Release date: 2012-04-25

  • Surveys and statistical programs – Documentation: 87-008-G
    Description:

    The Guide to Culture Statistics links users to information on culture surveys, data and analysis at Statistics Canada. Topics include film and video production and distribution, movie theatres, TV viewing and radio listening, the performing arts, book and periodical publishing, heritage institutions, government and private sector funding of culture, culture trade and investment, the culture labour force, Canadians consumption of culture, and more.

    This user's guide has been developed by the Culture Statistics Program to facilitate access to culture information throughout Statistics Canada. This guide is continually being updated to maintain its currency and usefulness.

    Release date: 2012-03-30
Date modified: