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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Description:

This note provides users with a reconciliation between Canadian and American measures of household disposable income, debt and the household credit market debt to disposable income ratio.

Description:

This guide focuses on the following topic: Language. Provides information that enables users to effectively use, apply and interpret data from the 2011 Census. Each guide contains definitions and explanations on census concepts, talks about changes made to the 2011 Census, data quality and historical comparability, as well as comparison with other data sources. Additional information will be included for specific variables to help general users better understand the concepts and questions used in the census.

Description:

This article has been prepared to help users understand the changes introduced as a result of the historical revision of the National Balance Sheet Account, due to the implementation of the new international standards published in System of National Accounts 2008.

Description:

This report highlights the revisions to the quarterly estimates of labour productivity and associated variables in the business sector resulting from the historical revision of the national gross domestic product by income and by expenditure accounts (NIEA) released on October 1st, 2012.

Description:

This article has been prepared to help users understand the changes introduced as a result of the historical revision of the international accounts of the Canadian System of National Accounts (CSNA), due to the implementation of the new international standards published in System of National Accounts 2008 and in Balance of Payments Manual, Sixth Edition.

Description:

This guide focuses on the following topic: Family variables. Provides information that enables users to effectively use, apply and interpret data from the 2011 Census. Each guide contains definitions and explanations on census concepts, talks about changes made to the 2011 Census, data quality and historical comparability, as well as comparison with other data sources. Additional information will be included for specific variables to help general users better understand the concepts and questions used in the census.

Description:

This guide focuses on the following topic: Structural Type of Dwelling and Collectives variables.

Provides information that enables users to effectively use, apply and interpret data from the 2011 Census. Each guide contains definitions and explanations on census concepts, talks about changes made to the 2011 Census, data quality and historical comparability, as well as comparison with other data sources. Additional information will be included for specific variables to help general users better understand the concepts and questions used in the census.

Description: This catalogue briefly describes all Labour Force Survey products offered on a monthly, annual and occasional basis. It includes products, uses, general release dates, formats available and prices, as well as special request services and Internet services. It also introduces any changes to products.

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.

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.