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Canada's economic story owes much to its bountiful natural resources. The December edition of Canadian Megatrends examines the role these assets have played in the growth and development of this country.

This report examines Canadians’ social connections, using the 2013 General Social Survey on Social Identity. Three aspects are examined 1) size of social networks (number and type of social connections), 2) frequency and types of communication, and 3) characteristics of friends. The report ends with a short discussion of the possible impact of social connections on Canadians’ overall quality of life.

This manuscript describes the use of multiple imputation to combine information from multiple surveys of the same underlying population. We use a newly developed method to generate synthetic populations nonparametrically using a finite population Bayesian bootstrap that automatically accounts for complex sample designs. We then analyze each synthetic population with standard complete-data software for simple random samples and obtain valid inference by combining the point and variance estimates using extensions of existing combining rules for synthetic data. We illustrate the approach by combining data from the 2006 National Health Interview Survey (NHIS) and the 2006 Medical Expenditure Panel Survey (MEPS).

When studying a finite population, it is sometimes necessary to select samples from several sampling frames in order to represent all individuals. Here we are interested in the scenario where two samples are selected using a two-stage design, with common first-stage selection. We apply the Hartley (1962), Bankier (1986) and Kalton and Anderson (1986) methods, and we show that these methods can be applied conditional on first-stage selection. We also compare the performance of several estimators as part of a simulation study. Our results suggest that the estimator should be chosen carefully when there are multiple sampling frames, and that a simple estimator is sometimes preferable, even if it uses only part of the information collected.

Parametric fractional imputation (PFI), proposed by Kim (2011), is a tool for general purpose parameter estimation under missing data. We propose a fractional hot deck imputation (FHDI) which is more robust than PFI or multiple imputation. In the proposed method, the imputed values are chosen from the set of respondents and assigned proper fractional weights. The weights are then adjusted to meet certain calibration conditions, which makes the resulting FHDI estimator efficient. Two simulation studies are presented to compare the proposed method with existing methods.

Survey methodologists have long studied the effects of interviewers on the variance of survey estimates. Statistical models including random interviewer effects are often fitted in such investigations, and research interest lies in the magnitude of the interviewer variance component. One question that might arise in a methodological investigation is whether or not different groups of interviewers (e.g., those with prior experience on a given survey vs. new hires, or CAPI interviewers vs. CATI interviewers) have significantly different variance components in these models. Significant differences may indicate a need for additional training in particular subgroups, or sub-optimal properties of different modes or interviewing styles for particular survey items (in terms of the overall mean squared error of survey estimates). Survey researchers seeking answers to these types of questions have different statistical tools available to them. This paper aims to provide an overview of alternative frequentist and Bayesian approaches to the comparison of variance components in different groups of survey interviewers, using a hierarchical generalized linear modeling framework that accommodates a variety of different types of survey variables. We first consider the benefits and limitations of each approach, contrasting the methods used for estimation and inference. We next present a simulation study, empirically evaluating the ability of each approach to efficiently estimate differences in variance components. We then apply the two approaches to an analysis of real survey data collected in the U.S. National Survey of Family Growth (NSFG). We conclude that the two approaches tend to result in very similar inferences, and we provide suggestions for practice given some of the subtle differences observed.

In order to obtain better coverage of the population of interest and cost less, a number of surveys employ dual frame structure, in which independent samples are taken from two overlapping sampling frames. This research considers chi-squared tests in dual frame surveys when categorical data is encountered. We extend generalized Wald’s test (Wald 1943), Rao-Scott first-order and second-order corrected tests (Rao and Scott 1981) from a single survey to a dual frame survey and derive the asymptotic distributions. Simulation studies show that both Rao-Scott type corrected tests work well and thus are recommended for use in dual frame surveys. An example is given to illustrate the usage of the developed tests.

When monthly business surveys are not completely overlapping, there are two different estimators for the monthly growth rate of the turnover: (i) one that is based on the monthly estimated population totals and (ii) one that is purely based on enterprises observed on both occasions in the overlap of the corresponding surveys. The resulting estimates and variances might be quite different. This paper proposes an optimal composite estimator for the growth rate as well as the population totals.

In developing the sample design for a survey we attempt to produce a good design for the funds available. Information on costs can be used to develop sample designs that minimise the sampling variance of an estimator of total for fixed cost. Improvements in survey management systems mean that it is now sometimes possible to estimate the cost of including each unit in the sample. This paper develops relatively simple approaches to determine whether the potential gains arising from using this unit level cost information are likely to be of practical use. It is shown that the key factor is the coefficient of variation of the costs relative to the coefficient of variation of the relative error on the estimated cost coefficients.

Rotating panel surveys are used to calculate estimates of gross flows between two consecutive periods of measurement. This paper considers a general procedure for the estimation of gross flows when the rotating panel survey has been generated from a complex survey design with random nonresponse. A pseudo maximum likelihood approach is considered through a two-stage model of Markov chains for the allocation of individuals among the categories in the survey and for modeling for nonresponse.

This table is part of the topic 'Age and sex', which provides age and sex distributions for the entire population of Canada. The 2011 Census data show the age group structure of the Canadian population and are used to calculate indicators of aging for each province and territory.

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.

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 census metropolitan areas and census agglomerations. 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 2013 Representation Order) level. Profile component data for all other standard geographic areas, including dissemination areas, dissolved census subdivisions, and forward sortation areas, will be available after the major days of release.

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.

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.

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.

Using 2011 National Household Survey (NHS) data, this profile provides a statistical overview of variables describing immigration and ethnocultural diversity, Aboriginal peoples, education, labour, mobility and migration, income and earnings, and housing and shelter costs.

In the National Household Survey 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 NHS cycle, starting with the Immigration and Ethnocultural Diversity, and Aboriginal Peoples releases. Together, they will form a complete NHS Profile of all the variables for each level of geography. Profile-component data are available at the Canada, province and territory, census division and census subdivision levels, at the census metropolitan area and census agglomeration levels, census tract level, and at the federal electoral district (based on the 2013 Representation Order) level.

The census is designed to provide information about the demographic and social characteristics of the people living in Canada and the housing or dwelling units they occupy.

'Age and sex' data are presented in a variety of different data products and analytical products which illustrate the age group structure of the Canadian population, and are used to calculate indicators of aging for each province and territory.

Analytical products

The analytical document provides analysis on the key findings and trends in the data, and is complimented with highlight tables which present key indicators for various levels of geography, and the short articles found in Census in Brief and the Focus on Geography series.

Data products

The Census Profile is one data product which provides a statistical overview of user selected geographic areas based on a number of detailed variables and/or groups of variables. Other data products include topic-based tabulations which are a series of cross-tabulations ranging in complexity and are available for various levels of geography, as well as the Visual census which provides a visual representation of selected variables accompanied by their tabular source data.

The census is designed to provide information about the demographic and social characteristics of the people living in Canada and the housing or dwelling units they occupy.

Data for 'Families, households and marital status' are presented in a variety of different data products and analytical products, which illustrate the living arrangements and structure of family units across Canada, along with the household's characteristics.

Analytical products

The analytical document provides analysis on the key findings and trends in the data, and is complemented with highlight tables which present key indicators for various levels of geography, and the short articles found in 'Census in Brief' and the 'Focus on Geography Series.'

Data products

The Census Profile is one data product which provides a statistical overview of user selected geographic areas based on a number of detailed variables and/or groups of variables. Other data products include topic-based tabulations which are a series of cross-tabulations ranging in complexity and are available for various levels of geography, as well as the Visual Census which provides a visual representation of selected variables accompanied by their tabular source data.

This application is designed to give quick access to the latest health-related data for a selected health region or census metropolitan area, providing the corresponding provincial data by default, but users can easily select a different area for comparison. The Health Profile features sub-provincial data from a number of sources including Statistics Canada's vital statistics, Canadian Cancer Registry, the Canadian Community Health Survey, and Census of Population, as well as hospitalization data from the Canadian Institute for Health Information.

Canada's economic story owes much to its bountiful natural resources. The December edition of Canadian Megatrends examines the role these assets have played in the growth and development of this country.

This report examines Canadians’ social connections, using the 2013 General Social Survey on Social Identity. Three aspects are examined 1) size of social networks (number and type of social connections), 2) frequency and types of communication, and 3) characteristics of friends. The report ends with a short discussion of the possible impact of social connections on Canadians’ overall quality of life.

This manuscript describes the use of multiple imputation to combine information from multiple surveys of the same underlying population. We use a newly developed method to generate synthetic populations nonparametrically using a finite population Bayesian bootstrap that automatically accounts for complex sample designs. We then analyze each synthetic population with standard complete-data software for simple random samples and obtain valid inference by combining the point and variance estimates using extensions of existing combining rules for synthetic data. We illustrate the approach by combining data from the 2006 National Health Interview Survey (NHIS) and the 2006 Medical Expenditure Panel Survey (MEPS).

When studying a finite population, it is sometimes necessary to select samples from several sampling frames in order to represent all individuals. Here we are interested in the scenario where two samples are selected using a two-stage design, with common first-stage selection. We apply the Hartley (1962), Bankier (1986) and Kalton and Anderson (1986) methods, and we show that these methods can be applied conditional on first-stage selection. We also compare the performance of several estimators as part of a simulation study. Our results suggest that the estimator should be chosen carefully when there are multiple sampling frames, and that a simple estimator is sometimes preferable, even if it uses only part of the information collected.

Parametric fractional imputation (PFI), proposed by Kim (2011), is a tool for general purpose parameter estimation under missing data. We propose a fractional hot deck imputation (FHDI) which is more robust than PFI or multiple imputation. In the proposed method, the imputed values are chosen from the set of respondents and assigned proper fractional weights. The weights are then adjusted to meet certain calibration conditions, which makes the resulting FHDI estimator efficient. Two simulation studies are presented to compare the proposed method with existing methods.

Survey methodologists have long studied the effects of interviewers on the variance of survey estimates. Statistical models including random interviewer effects are often fitted in such investigations, and research interest lies in the magnitude of the interviewer variance component. One question that might arise in a methodological investigation is whether or not different groups of interviewers (e.g., those with prior experience on a given survey vs. new hires, or CAPI interviewers vs. CATI interviewers) have significantly different variance components in these models. Significant differences may indicate a need for additional training in particular subgroups, or sub-optimal properties of different modes or interviewing styles for particular survey items (in terms of the overall mean squared error of survey estimates). Survey researchers seeking answers to these types of questions have different statistical tools available to them. This paper aims to provide an overview of alternative frequentist and Bayesian approaches to the comparison of variance components in different groups of survey interviewers, using a hierarchical generalized linear modeling framework that accommodates a variety of different types of survey variables. We first consider the benefits and limitations of each approach, contrasting the methods used for estimation and inference. We next present a simulation study, empirically evaluating the ability of each approach to efficiently estimate differences in variance components. We then apply the two approaches to an analysis of real survey data collected in the U.S. National Survey of Family Growth (NSFG). We conclude that the two approaches tend to result in very similar inferences, and we provide suggestions for practice given some of the subtle differences observed.

In order to obtain better coverage of the population of interest and cost less, a number of surveys employ dual frame structure, in which independent samples are taken from two overlapping sampling frames. This research considers chi-squared tests in dual frame surveys when categorical data is encountered. We extend generalized Wald’s test (Wald 1943), Rao-Scott first-order and second-order corrected tests (Rao and Scott 1981) from a single survey to a dual frame survey and derive the asymptotic distributions. Simulation studies show that both Rao-Scott type corrected tests work well and thus are recommended for use in dual frame surveys. An example is given to illustrate the usage of the developed tests.

When monthly business surveys are not completely overlapping, there are two different estimators for the monthly growth rate of the turnover: (i) one that is based on the monthly estimated population totals and (ii) one that is purely based on enterprises observed on both occasions in the overlap of the corresponding surveys. The resulting estimates and variances might be quite different. This paper proposes an optimal composite estimator for the growth rate as well as the population totals.

In developing the sample design for a survey we attempt to produce a good design for the funds available. Information on costs can be used to develop sample designs that minimise the sampling variance of an estimator of total for fixed cost. Improvements in survey management systems mean that it is now sometimes possible to estimate the cost of including each unit in the sample. This paper develops relatively simple approaches to determine whether the potential gains arising from using this unit level cost information are likely to be of practical use. It is shown that the key factor is the coefficient of variation of the costs relative to the coefficient of variation of the relative error on the estimated cost coefficients.

Rotating panel surveys are used to calculate estimates of gross flows between two consecutive periods of measurement. This paper considers a general procedure for the estimation of gross flows when the rotating panel survey has been generated from a complex survey design with random nonresponse. A pseudo maximum likelihood approach is considered through a two-stage model of Markov chains for the allocation of individuals among the categories in the survey and for modeling for nonresponse.

Starting with the 2012 reference year, annual individual and family income data is produced by the Canadian Income Survey (CIS). The CIS is a cross-sectional survey developed to provide information on the income and income sources of Canadians, along with their individual and household characteristics. The CIS reports on many of the same statistics as the Survey of Labour and Income Dynamics (SLID), which last reported on income for the 2011 reference year. This note describes the CIS methodology, as well as the main differences in survey objectives, methodology and questionnaires between CIS and SLID.

Statistics Canada's Newsletter for Communities offers information to those working for municipal and community organizations about Statistics Canada's data and services. The newsletter also offers links to data releases of the Census and National Household Survey, videos, tutorials, media advisories, learning sessions and presentations.

Statistics Canada's Newsletter for Small and Medium-sized Businesses offers information to the business community about Statistics Canada's data and services. The newsletter also offers links to data releases of the Census and National Household Survey, videos, tutorials, media advisories, learning sessions and presentations.

An overview of the Canadian Government Finance Statistics (CGFS) framework; how it relates to other government statistics such as the Canadian System of Macroeconomic Accounts and the Public Accounts; and the new GFS data products available to users

Beginning in November 2014, International Trade in goods data will be provided on a Balance of Payments (BOP) basis for additional country detail. In publishing this data, BOP-based exports to and imports from 27 countries, referred to as Canada’s Principal Trading Partners (PTPs), will be highlighted for the first time. BOP-based trade in goods data will be available for countries such as China and Mexico, Brazil and India, South Korea, and our largest European Union trading partners, in response to substantial demand for information on these countries in recent years. Until now, Canada’s geographical trading patterns have been examined almost exclusively through analysis of Customs-based trade data. Moreover, BOP trade in goods data for these countries will be available alongside the now quarterly Trade in Services data as well as annual Foreign Direct Investment data for many of these Principal Trading Partners, facilitating country-level international trade and investment analysis using fully comparable data. The objective of this article is to introduce these new measures. This note will first walk users through the key BOP concepts, most importantly the concept of change in ownership. This will serve to familiarize analysts with the Balance of Payments framework for analyzing country-level data, in contrast to Customs-based trade data. Second, some preliminary analysis will be reviewed to illustrate the concepts, with provisional estimates for BOP-based trade with China serving as the principal example. Lastly, we will outline the expansion of quarterly trade in services to generate new estimates of trade for the PTPs and discuss future work in trade statistics.

The National Fuel Consumption Survey (FCS) was created in 2013 and is a quarterly survey that is designed to analyze distance driven and fuel consumption for passenger cars and other vehicles weighing less than 4,500 kilograms. The sampling frame consists of vehicles extracted from the vehicle registration files, which are maintained by provincial ministries. For collection, FCS uses car chips for a part of the sampled units to collect information about the trips and the fuel consumed. There are numerous advantages to using this new technology, for example, reduction in response burden, collection costs and effects on data quality. For the quarters in 2013, the sampled units were surveyed 95% via paper questionnaires and 5% with car chips, and in Q1 2014, 40% of sampled units were surveyed with car chips. This study outlines the methodology of the survey process, examines the advantages and challenges in processing and imputation for the two collection modes, presents some initial results and concludes with a summary of the lessons learned.

In an effort to reduce response burden on farm operators, Statistics Canada is studying alternative approaches to telephone surveys for producing field crop estimates. One option is to publish harvested area and yield estimates in September as is currently done, but to calculate them using models based on satellite and weather data, and data from the July telephone survey. However before adopting such an approach, a method must be found which produces estimates with a sufficient level of accuracy. Research is taking place to investigate different possibilities. Initial research results and issues to consider are discussed in this paper.

The Survey of Employment, Payrolls and Hours (SEPH) produces monthly estimates and determines the month-to-month changes for variables such as employment, earnings and hours at detailed industrial levels for Canada, the provinces and territories. In order to improve the efficiency of collection activities for this survey, an electronic questionnaire (EQ) was introduced in the fall of 2012. Given the timeframe allowed for this transition as well as the production calendar of the survey, a conversion strategy was developed for the integration of this new mode. The goal of the strategy was to ensure a good adaptation of the collection environment and also to allow the implementation of a plan of analysis that would evaluate the impact of this change on the results of the survey. This paper will give an overview of the conversion strategy, the different adjustments that were made during the transition period and the results of various evaluations that were conducted. For example, the impact of the integration of the EQ on the collection process, the response rate and the follow-up rate will be presented. In addition, the effect that this new collection mode has on the survey estimates will also be discussed. More specifically, the results of a randomized experiment that was conducted in order to determine the presence of a mode effect will be presented.

The Census Overcoverage Study (COS) is a critical post-census coverage measurement study. Its main objective is to produce estimates of the number of people erroneously enumerated, by province and territory, study the characteristics of individuals counted multiple times and identify possible reasons for the errors. The COS is based on the sampling and clerical review of groups of connected records that are built by linking the census response database to an administrative frame, and to itself. In this paper we describe the new 2011 COS methodology. This methodology has incorporated numerous improvements including a greater use of probabilistic record-linkage, the estimation of linking parameters with an Expectation-Maximization (E-M) algorithm, and the efficient use of household information to detect more overcoverage cases.

In January and February 2014, Statistics Canada conducted a test aiming at measuring the effectiveness of different collection strategies using an online self-reporting survey. Sampled units were contacted using mailed introductory letters and asked to complete the online survey without any interviewer contact. The objectives of this test were to measure the take-up rates for completing an online survey, and to profile the respondents/non-respondents. Different samples and letters were tested to determine the relative effectiveness of the different approaches. The results of this project will be used to inform various social surveys that are preparing to include an internet response option in their surveys. The paper will present the general methodology of the test as well as results observed from collection and the analysis of profiles.