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Description: Recent changes in Canada’s immigration levels have heightened interest in understanding how immigration affects housing demand. This article develops a methodological framework for projecting housing use associated with permanent residents (PRs) and non-permanent residents (NPRs) under alternative immigration scenarios. The framework applies observed per capita housing use rates from the Census of Population to estimate incremental housing use by tenure over time.

Description: The Technical Guide on Demographic Estimates at Statistics Canada provides detailed descriptions of the most current data sources and methods used by the Centre for demography at Statistics Canada to produce demographic estimates as part of the Demographic estimates program. They comprise postcensal and intercensal population estimates; base population; births and deaths; immigrants; emigrants; returning emigrants; non-permanent residents; interprovincial migration; subprovincial estimates of population and intraprovincial migration; population estimates by age and gender; and census family estimates. A glossary of commonly used terms is available at the end of the guide.

Description: This video presents Statistics Canada’s estimation method of the number of non-permanent residents.

Description: This paper introduces and explains modifications made to the Labour Force Survey estimates.

Description: The public use microdata file from the 2010 Canada Survey of Giving, Volunteering and Participating is now available. This file contains information collected from nearly 15,000 respondents aged 15 and over residing in private households in the provinces. The public use microdata file provides provincial-level information about the ways in which Canadians donate money and in-kind gifts to charitable and nonprofit organizations; volunteer their time to these organizations; provide help directly to others. Socio-demographic, income and labour force data are also included on the file.

Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.

Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.

Description: In accordance with Statistics Canada’s long-term Disaggregated Data Action Plan (DDAP), several initiatives have been implemented into the Labour Force Survey (LFS). One of the more direct initiatives was a targeted increase in the size of the monthly LFS sample. Furthermore, a regular Supplement program was introduced, where an additional series of questions are asked to a subset of LFS respondents and analyzed in a monthly or quarterly production cycle. Finally, the production of modelled estimates based on Small Area Estimation (SAE) methodologies resumed for the LFS and will include a wider scope with more analytical value than what had existed in the past. This paper will give an overview of these three initiatives.

Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.

Description: We present design-based Horvitz-Thompson and multiplicity estimators of the population size, as well as of the total and mean of a response variable associated with the elements of a hidden population to be used with the link-tracing sampling variant proposed by Félix-Medina and Thompson (2004). Since the computation of the estimators requires to know the inclusion probabilities of the sampled people, but they are unknown, we propose a Bayesian model which allows us to estimate them, and consequently to compute the estimators of the population parameters. The results of a small numeric study indicate that the performance of the proposed estimators is acceptable.

Description: The public use microdata file from the 2010 Canada Survey of Giving, Volunteering and Participating is now available. This file contains information collected from nearly 15,000 respondents aged 15 and over residing in private households in the provinces. The public use microdata file provides provincial-level information about the ways in which Canadians donate money and in-kind gifts to charitable and nonprofit organizations; volunteer their time to these organizations; provide help directly to others. Socio-demographic, income and labour force data are also included on the file.

Description: Microdata files are unique among census products in that they give users access to unaggregated data. This makes the public use microdata files (PUMFs) powerful research tools. Each file contains anonymous individual responses on a large number of variables. The PUMF user can group and manipulate these variables to suit his/her own data and research requirements. Tabulations not included in other census products can be created or relationships between variables can be analysed by using different statistical tests. PUMFs provide quick access to a comprehensive social and economic database about Canada and its people. All subject-matter covered by the census is included in the microdata files. However, to ensure the anonymity of the respondents, geographic identifiers have been restricted to the provinces/territories and large metropolitan areas. Microdata files have traditionally been disseminated on magnetic tape, which required access to a mainframe computer. For the first time, the 1991 PUMFs will also be available on CD-ROM for microcomputer applications. This file contains data based on a 3% of the population enumerated in the 1991 Census. It provides information on the demographic, social and economic characteristics of the Canadian population. The Individual File allows users to return to the base unit of the census, enabling them to group and manipulate the data to suit their own data and research requirements.

This product provides two basic tools to assist users in accessing and using the 1991 Census Public Use Microdata File - Individuals CD-ROM.

Description: Microdata files are unique among census products in that they give users access to unaggregated data. This makes the public use microdata files (PUMFs) powerful research tools. Each file contains anonymous individual responses on a large number of variables. The PUMF user can group and manipulate these variables to suit his/her own data and research requirements. Tabulations not included in other census products can be created or relationships between variables can be analysed by using different statistical tests. PUMFs provide quick access to a comprehensive social and economic database about Canada and its people. All subject-matter covered by the census is included in the microdata files. However, to ensure the anonymity of the respondents, geographic identifiers have been restricted to the provinces/territories and large metropolitan areas. Microdata files have traditionally been disseminated on magnetic tape, which required access to a mainframe computer. For the first time, the 1991 PUMFs will also be available on CD-ROM for microcomputer applications. This file contains data based on a 3% of the population enumerated in the 1991 Census. It provides information on the demographic, social and economic characteristics of the Canadian population. The Households and Housing File allows users to return to the base unit of the census, enabling them to group and manipulate the data to suit their own data and research requirements.

This product provides two basic tools to assist users in accessing and using the 1991 Census Public Use Microdata File - Households and Housing CD-ROM.

Description: The Canadian Tobacco, Alcohol and Drugs Survey (CTADS) is a biennial general population survey of tobacco, alcohol and drug use among Canadians aged 15 years and older, with the primary focus on 15- to 24-year-olds. The CTADS is a telephone survey conducted by Statistics Canada on behalf of Health Canada.

Description:

This package was designed to enable users to access and manipulate the microdata file for Cycle 22 (2008) of the General Social Survey (GSS). It contains information on the objectives, methodology and estimation procedures, as well as guidelines for releasing estimates based on the survey. Cycle 22 collected data from persons 15 years and over living in private households in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut; and full-time residents of institutions. The survey covered a range of topics such as social networks, and social and civic participation. Information was also collected on major changes in respondents' lives in the last 12 months, the resources they used during these transitions and unmet needs for help. Questions were also asked on trust, sense of belonging, volunteering and unpaid work.

Description: The Participation and Activity Limitation Survey (PALS) is a post-censal survey of adults with disabilities, including any person whose everyday activities are limited because of a physical condition or health problem.

The survey covers themes such as activity limitations, help with everyday activities, education, employment status, social participation and economic characteristics.

Description:

This package was designed to enable users to access and manipulate the microdata file for the 21st cycle (2007) of the General Social Survey (GSS). It contains information on the objectives, methodology and estimation procedures, as well as guidelines for releasing estimates based on the survey. Cycle 21 of the GSS collected data from persons aged 45 years and over living in private households in the 10 provinces of Canada. The survey covered a wide range of topics such as well-being, family composition, retirement decisions and plans, care giving and care receiving experiences, social networks and housing.

Description: The Aboriginal Peoples Survey (APS) provides data on the social and economic conditions of Aboriginal people in Canada. Its specific purpose was to identify the needs of Aboriginal people focusing on issues such as health, schooling and language. The survey was designed and implemented in partnership with national Aboriginal organizations.

This product contains information for the Aboriginal child and youth population (under 15 years) living in off-reserve areas.

Description:

Cycle 16 of the GSS is the second cycle (after cycle 11) to collect information social support for older Canadians, introducing modules on preparations for retirement and retirement experience. The GSS is an annual telephone survey covering the non-institutionalized population in the 10 provinces. Respondents were randomly selected from a list of individuals aged 45 and over who had responded to another Statistics Canada survey. Data were collected over an 11-month period from February to December 2002. The representative sample had about 25,000 respondents. The response rate was almost 84%.

The main objective of the 2002 GSS was to provide data on the aging population. However, the survey allows detailed analysis of characteristics of family and friends who provide care to seniors; characteristics of seniors receiving formal and informal care; links to broader determinants of health (such as income, education and social networks); and people's retirement plans and experiences.

Description:

Topics covered include social contact with friends and relatives, unpaid help given and received, volunteering and charitable giving, civic engagement, political engagement, religious participation, trust and reciprocity. Cycle 17 of the General Social Survey is the first cycle to collect detailed information on social engagement in Canada.

The target population for Cycle 17 is all persons 15 years of age and older in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut, and full-time residents of institutions.

Description: This video presents Statistics Canada’s estimation method of the number of non-permanent residents.

Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.

Description: Estimation at fine levels of aggregation is necessary to better describe society. Small area estimation model-based approaches that combine sparse survey data with rich data from auxiliary sources have been proven useful to improve the reliability of estimates for small domains. Considered here is a scenario where small area model-based estimates, produced at a given aggregation level, needed to be disaggregated to better describe the social structure at finer levels. For this scenario, an allocation method was developed to implement the disaggregation, overcoming challenges associated with data availability and model development at such fine levels. The method is applied to adult literacy and numeracy estimation at the county-by-group-level, using data from the U.S. Program for the International Assessment of Adult Competencies. In this application the groups are defined in terms of age or education, but the method could be applied to estimation of other equity-deserving groups.

Description: In accordance with Statistics Canada’s long-term Disaggregated Data Action Plan (DDAP), several initiatives have been implemented into the Labour Force Survey (LFS). One of the more direct initiatives was a targeted increase in the size of the monthly LFS sample. Furthermore, a regular Supplement program was introduced, where an additional series of questions are asked to a subset of LFS respondents and analyzed in a monthly or quarterly production cycle. Finally, the production of modelled estimates based on Small Area Estimation (SAE) methodologies resumed for the LFS and will include a wider scope with more analytical value than what had existed in the past. This paper will give an overview of these three initiatives.

Description: Sampling variance smoothing is an important topic in small area estimation. In this paper, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis indicate that the proposed sampling variance smoothing methods work very well for small area estimation.

Description: We present design-based Horvitz-Thompson and multiplicity estimators of the population size, as well as of the total and mean of a response variable associated with the elements of a hidden population to be used with the link-tracing sampling variant proposed by Félix-Medina and Thompson (2004). Since the computation of the estimators requires to know the inclusion probabilities of the sampled people, but they are unknown, we propose a Bayesian model which allows us to estimate them, and consequently to compute the estimators of the population parameters. The results of a small numeric study indicate that the performance of the proposed estimators is acceptable.

Description: The Longitudinal Social Data Development Program (LSDDP) is a social data integration approach aimed at providing longitudinal analytical opportunities without imposing additional burden on respondents. The LSDDP uses a multitude of signals from different data sources for the same individual, which helps to better understand their interactions and track changes over time. This article looks at how the ethnicity status of people in Canada can be estimated at the most detailed disaggregated level possible using the results from a variety of business rules applied to linked data and to the LSDDP denominator. It will then show how improvements were obtained using machine learning methods, such as decision trees and random forest techniques.

Description: The validity of survival estimates from cancer registry data depends, in part, on the identification of the deaths of deceased cancer patients. People whose deaths are missed seemingly live on forever and are informally referred to as “immortals”, and their presence in registry data can result in inflated survival estimates. This study assesses the issue of immortals in the Canadian Cancer Registry (CCR) using a recently proposed method that compares the survival of long-term survivors of cancers for which “statistical” cure has been reported with that of similar people from the general population.

Description: This report explores four potential methods of estimating the number of girls and women currently living in Canada who are considered at risk for female genital mutilation or cutting (FGM/C) based on their (and their parents’) country of birth. In this report, “at risk for FGM/C” broadly means at risk of having experienced FGM/C or of experiencing it in the future.

Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and systems used to produce income estimates with the release of its 2021 reference year estimates. This paper describes the changes and presents the approximate net result of these changes on income estimates using data for 2019 and 2020. The changes described in this paper highlight the ways in which data quality has been improved while producing minimal impact on key CIS estimates and trends.

Description:

Data fusion as discussed here means to create a set of data on not jointly observed variables from two different sources. Suppose for instance that observations are available for (X,Z) on a set of individuals and for (Y,Z) on a different set of individuals. Each of X, Y and Z may be a vector variable. The main purpose is to gain insight into the joint distribution of (X,Y) using Z as a so-called matching variable. At first however, it is attempted to recover as much information as possible on the joint distribution of (X,Y,Z) from the distinct sets of data. Such fusions can only be done at the cost of implementing some distributional properties for the fused data. These are conditional independencies given the matching variables. Fused data are typically discussed from the point of view of how appropriate this underlying assumption is. Here we give a different perspective. We formulate the problem as follows: how can distributions be estimated in situations when only observations from certain marginal distributions are available. It can be solved by applying the maximum entropy criterium. We show in particular that data created by fusing different sources can be interpreted as a special case of this situation. Thus, we derive the needed assumption of conditional independence as a consequence of the type of data available.

Description:

The effect of the environment on health is of increasing concern, in particular the effects of the release of industrial pollutants into the air, the ground and into water. An assessment of the risks to public health of any particular pollution source is often made using the routine health, demographic and environmental data collected by government agencies. These datasets have important differences in sampling geography and in sampling epochs which affect the epidemiological analyses which draw them together. In the UK, health events are recorded for individuals, giving cause codes, a data of diagnosis or death, and using the unit postcode as a geographical reference. In contrast, small area demographic data are recorded only at the decennial census, and released as area level data in areas distinct from postcode geography. Environmental exposure data may be available at yet another resolution, depending on the type of exposure and the source of the measurements.

Description:

To augment the amount of available information, data from different sources are increasingly being combined. These databases are often combined using record linkage methods. When there is no unique identifier, a probabilistic linkage is used. In that case, a record on a first file is associated with a probability that is linked to a record on a second file, and then a decision is taken on whether a possible link is a true link or not. This usually requires a non-negligible amount of manual resolution. It might then be legitimate to evaluate if manual resolution can be reduced or even eliminated. This issue is addressed in this paper where one tries to produce an estimate of a total (or a mean) of one population, when using a sample selected from another population linked somehow to the first population. In other words, having two populations linked through probabilistic record linkage, we try to avoid any decision concerning the validity of links and still be able to produce an unbiased estimate for a total of the one of two populations. To achieve this goal, we suggest the use of the Generalised Weight Share Method (GWSM) described by Lavallée (1995).

Description:

The application of dual system estimation (DSE) to matched Census / Post Enumeration Survey (PES) data in order to measure net undercount is well understood (Hogan, 1993). However, this approach has so far not been used to measure net undercount in the UK. The 2001 PES in the UK will use this methodology. This paper presents the general approach to design and estimation for this PES (the 2001 Census Coverage Survey). The estimation combines DSE with standard ratio and regression estimation. A simulation study using census data from the 1991 Census of England and Wales demonstrates that the ratio model is in general more robust than the regression model.

Description:

Often, the same information is gathered almost simultaneously for several different surveys. In France, this practice is institutionalized for household surveys that have a common set of demographic variables, i.e., employment, residence and income. These variables are important co-factors for the variables of interest in each survey, and if used carefully, can reinforce the estimates derived from each survey. Techniques for calibrating uncertain data can apply naturally in this context. This involves finding the best unbiased estimator in common variables and calibrating each survey based on that estimator. The estimator thus obtained in each survey is always a linear estimator, the weightings of which can be easily explained and the variance can be obtained with no new problems, as can the variance estimate. To supplement the list of regression estimators, this technique can also be seen as a ridge-regression estimator, or as a Bayesian-regression estimator.

Description:

The U.S. Consumer Expenditure Survey uses two instruments, a diary and an in-person interview, to collect data on many categories of consumer expenditures. Consequently, it is important to use these data efficiently to estimate mean expenditures and related parameters. Three options are: (1) use only data from the diary source; (2) Use only data from the interview source; and (3) use generalized least squares, or related methods, to combine the diary and interview data. Historically, the U.S. Bureau of Labor Statistics has focused on options (1) and (2) for estimation at the five or six-digit Universal Classification Code level. Evaluation and possible implementation of option (3) depends on several factors, including possible measurement biases in the diary and interview data; the empirical magnitude of these biases, relative to the standard errors of customary mean estimators; and the degree of homogeneity of these biases across strata and periods. This paper reviews some issues related to options (1) through (3); describes a relatively simple generalized least squares method for implementation of option (3); and discussed the need for diagnostics to evaluate the feasibility and relative efficiency of the generalized least squares method.

Description:

The artificial sample was generated in two steps. The first step, based on a master panel, was a Multiple Correspondence Analysis (MCA) carried out on basic variables. Then, "dummy" individuals were generated randomly using the distribution of each "significant" factor in the analysis. Finally, for each individual, a value was generated for each basic variable most closely linked to one of the previous factors. This method ensured that sets of variables were drawn independently. The second step consisted in grafting some other data bases, based on certain property requirements. A variable was generated to be added on the basis of its estimated distribution, using a generalized linear model for common variables and those already added. The same procedure was then used to graft the other samples. This method was applied to the generation of an artificial sample taken from two surveys. The artificial sample that was generated was validated using sample comparison testing. The results were positive, demonstrating the feasibility of this method.

Description:

Electricity rates that vary by time-of-day have the potential to significantly increase economic efficiency in the energy market. A number of utilities have undertaken economic studies of time-of-use rates schemes for their residential customers. This paper uses meta-analysis to examine the impact of time-of-use rates on electricity demand pooling the results of thirty-eight separate programs. There are four key findings. First, very large peak to off-peak price ratios are needed to significantly affect peak demand. Second, summer peak rates are relatively effective compared to winter peak rates. Third, permanent time-or-use rates are relatively effective compared to experimental ones. Fourth, demand charges rival ordinary time-of-use rates in terms of impact.

Description:

We use data on 14 populations of coho salmon to estimate critical parameters that are vital for management of fish populations. Parameter estimates from individual data sets are inefficient and can be highly biased, and we investigate methods to overcome these problems. Combination of data sets using nonlinear mixed effects models provides more useful results, however questions of influence and robustness are raised. For comparison, robust estimates are obtained. Model-robustness is also explored using a family of alternative functional forms. Our results allow ready calculation of the limits of exploitation and may help to prevent extinction of fish stocks. Similar methods can be applied in other contexts where parameter estimation is part of a larger decision-making process.

Description:

This report deals with sampling and weighting, a process whereby certain characteristics are collected and processed for a random sample of dwellings and persons identified in the complete census enumeration. Data for the whole population are then obtained by scaling up the results for the sample to the full population level. The use of sampling may lead to substantial reductions in costs and respondent burden, or alternatively, can allow the scope of a census to be broadened at the same cost.