Analysis

Description:

The last global financial crisis revealed some important data gaps in countries’ statistics to properly assess the build-up of risk and the interconnectedness in financial markets. These gaps have led to the development of a series of initiatives at the international level with clear deliverables to enhance the quality of the information produced by countries in the area of financial investment statistics, including statistics on securities. The initiative undertaken at Statistics Canada to enhance securities statistics has produced many benefits with important expansions in terms of additional characteristics of instruments issued and held by Canadians, additional sector details as well as increased frequency and timeliness.

Description:

This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.

Description:

This documentation outlines a step towards a more complete program of annual distributional estimates for the household sector in the Canadian macroeconomic accounts. This documentation also presents the methodology used to develop distributions of wealth for the household sector of the National Balance Sheet Accounts (NBSA) for the reference years 2010 to 2018.

Description:

This note describes methodological changes made to the Market Basket Measure (MBM) in Calendar year 2019. These revisions mainly affect MBM estimates for 2008 and 2009, but they also affect the overall interpretation of the trends in the MBM over the 2000s.

Description:

Panel surveys are frequently used to measure the evolution of parameters over time. Panel samples may suffer from different types of unit non-response, which is currently handled by estimating the response probabilities and by reweighting respondents. In this work, we consider estimation and variance estimation under unit non-response for panel surveys. Extending the work by Kim and Kim (2007) for several times, we consider a propensity score adjusted estimator accounting for initial non-response and attrition, and propose a suitable variance estimator. It is then extended to cover most estimators encountered in surveys, including calibrated estimators, complex parameters and longitudinal estimators. The properties of the proposed variance estimator and of a simplified variance estimator are estimated through a simulation study. An illustration of the proposed methods on data from the ELFE survey is also presented.

Description:

Sample coordination seeks to create a probabilistic dependence between the selection of two or more samples drawn from the same population or from overlapping populations. Positive coordination increases the expected sample overlap, while negative coordination decreases it. There are numerous applications for sample coordination with varying objectives. A spatially balanced sample is a sample that is well-spread in some space. Forcing a spread within the selected samples is a general and very efficient variance reduction technique for the Horvitz-Thompson estimator. The local pivotal method and the spatially correlated Poisson sampling are two general schemes for achieving well-spread samples. We aim to introduce coordination for these sampling methods based on the concept of permanent random numbers. The goal is to coordinate such samples while preserving spatial balance. The proposed methods are motivated by examples from forestry, environmental studies, and official statistics.

Description:

These last years, balanced sampling techniques have experienced a recrudescence of interest. They constrain the Horvitz Thompson estimators of the totals of auxiliary variables to be equal, at least approximately, to the corresponding true totals, to avoid the occurrence of bad samples. Several procedures are available to carry out balanced sampling; there is the cube method, see Deville and Tillé (2004), and an alternative, the rejective algorithm introduced by Hájek (1964). After a brief review of these sampling methods, motivated by the planning of an angler survey, we investigate using Monte Carlo simulations, the survey designs produced by these two sampling algorithms.

Description:

Many studies conducted by various electric utilities around the world are based on the analysis of mean electricity consumption curves for various subpopulations, particularly geographic in nature. Those mean curves are estimated from samples of thousands of curves measured at very short intervals over long periods. Estimation for small subpopulations, also called small domains, is a very timely topic in sampling theory.

In this article, we will examine this problem based on functional data and we will try to estimate the mean curves for small domains. For this, we propose four methods: functional linear regression; modelling the scores of a principal component analysis by unit-level linear mixed models; and two non-parametric estimators, with one based on regression trees and the other on random forests, adapted to the curves. All these methods have been tested and compared using real electricity consumption data for households in France.

Description:

In Italy, the Labor Force Survey (LFS) is conducted quarterly by the National Statistical Institute (ISTAT) to produce estimates of the labor force status of the population at different geographical levels. In particular, ISTAT provides LFS estimates of employed and unemployed counts for local Labor Market Areas (LMAs). LMAs are 611 sub-regional clusters of municipalities and are unplanned domains for which direct estimates have overly large sampling errors. This implies the need of Small Area Estimation (SAE) methods. In this paper, we develop a new area level SAE method that uses a Latent Markov Model (LMM) as linking model. In LMMs, the characteristic of interest, and its evolution in time, is represented by a latent process that follows a Markov chain, usually of first order. Therefore, areas are allowed to change their latent state across time. The proposed model is applied to quarterly data from the LFS for the period 2004 to 2014 and fitted within a hierarchical Bayesian framework using a data augmentation Gibbs sampler. Estimates are compared with those obtained by the classical Fay-Herriot model, by a time-series area level SAE model, and on the basis of data coming from the 2011 Population Census.

Description:

When a linear imputation method is used to correct non-response based on certain assumptions, total variance can be assigned to non-responding units. Linear imputation is not as limited as it seems, given that the most common methods – ratio, donor, mean and auxiliary value imputation – are all linear imputation methods. We will discuss the inference framework and the unit-level decomposition of variance due to non-response. Simulation results will also be presented. This decomposition can be used to prioritize non-response follow-up or manual corrections, or simply to guide data analysis.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

This infographic denotes the process taken by Statistics Canada in collaboration with data providers and other stakeholders to review and standardize the collection of data on unfounded incidents through the Uniform Crime Reporting Survey, and the release of data to the public.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

Celebrate Statistics Canada’s centennial by looking back on our journey with Canada.

Description:

This release of awareness of the opioid issue in Canada is intended to provide a richer understanding of Canadians’ knowledge of the opioid issue, the risks associated and their willingness and ability to intervene in the event of an apparent opioid overdose.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

The first release from the Canadian Housing Statistics Program (CHSP) is intended to inform a richer understanding of the economic weight of non-resident owned assets in different segments of Toronto’s housing markets. These preliminary data provide information on the scope of non-resident ownership in 23 census subdivisions as of May 2017. The infographic includes estimates of the number and assessed value of selected types of properties owned by non-residents, living area and age of the structure.

Description:

The first release from the Canadian Housing Statistics Program (CHSP) is intended to inform a richer understanding of the economic weight of non-resident owned assets in different segments of Vancouver’s housing markets. These preliminary data provide information on the scope of non-resident ownership in 22 census subdivisions as of June 2017. The infographic includes estimates of the number and assessed value of selected types of properties owned by non-residents, living area and age of the structure.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description:

The last global financial crisis revealed some important data gaps in countries’ statistics to properly assess the build-up of risk and the interconnectedness in financial markets. These gaps have led to the development of a series of initiatives at the international level with clear deliverables to enhance the quality of the information produced by countries in the area of financial investment statistics, including statistics on securities. The initiative undertaken at Statistics Canada to enhance securities statistics has produced many benefits with important expansions in terms of additional characteristics of instruments issued and held by Canadians, additional sector details as well as increased frequency and timeliness.

Description:

This documentation outlines a step towards a more complete program of annual distributional estimates for the household sector in the Canadian macroeconomic accounts. This documentation also presents the methodology used to develop distributions of wealth for the household sector of the National Balance Sheet Accounts (NBSA) for the reference years 2010 to 2018.

Description:

This note describes methodological changes made to the Market Basket Measure (MBM) in Calendar year 2019. These revisions mainly affect MBM estimates for 2008 and 2009, but they also affect the overall interpretation of the trends in the MBM over the 2000s.

Description:

Panel surveys are frequently used to measure the evolution of parameters over time. Panel samples may suffer from different types of unit non-response, which is currently handled by estimating the response probabilities and by reweighting respondents. In this work, we consider estimation and variance estimation under unit non-response for panel surveys. Extending the work by Kim and Kim (2007) for several times, we consider a propensity score adjusted estimator accounting for initial non-response and attrition, and propose a suitable variance estimator. It is then extended to cover most estimators encountered in surveys, including calibrated estimators, complex parameters and longitudinal estimators. The properties of the proposed variance estimator and of a simplified variance estimator are estimated through a simulation study. An illustration of the proposed methods on data from the ELFE survey is also presented.

Description:

Sample coordination seeks to create a probabilistic dependence between the selection of two or more samples drawn from the same population or from overlapping populations. Positive coordination increases the expected sample overlap, while negative coordination decreases it. There are numerous applications for sample coordination with varying objectives. A spatially balanced sample is a sample that is well-spread in some space. Forcing a spread within the selected samples is a general and very efficient variance reduction technique for the Horvitz-Thompson estimator. The local pivotal method and the spatially correlated Poisson sampling are two general schemes for achieving well-spread samples. We aim to introduce coordination for these sampling methods based on the concept of permanent random numbers. The goal is to coordinate such samples while preserving spatial balance. The proposed methods are motivated by examples from forestry, environmental studies, and official statistics.

Description:

These last years, balanced sampling techniques have experienced a recrudescence of interest. They constrain the Horvitz Thompson estimators of the totals of auxiliary variables to be equal, at least approximately, to the corresponding true totals, to avoid the occurrence of bad samples. Several procedures are available to carry out balanced sampling; there is the cube method, see Deville and Tillé (2004), and an alternative, the rejective algorithm introduced by Hájek (1964). After a brief review of these sampling methods, motivated by the planning of an angler survey, we investigate using Monte Carlo simulations, the survey designs produced by these two sampling algorithms.

Description:

Many studies conducted by various electric utilities around the world are based on the analysis of mean electricity consumption curves for various subpopulations, particularly geographic in nature. Those mean curves are estimated from samples of thousands of curves measured at very short intervals over long periods. Estimation for small subpopulations, also called small domains, is a very timely topic in sampling theory.

In this article, we will examine this problem based on functional data and we will try to estimate the mean curves for small domains. For this, we propose four methods: functional linear regression; modelling the scores of a principal component analysis by unit-level linear mixed models; and two non-parametric estimators, with one based on regression trees and the other on random forests, adapted to the curves. All these methods have been tested and compared using real electricity consumption data for households in France.

Description:

In Italy, the Labor Force Survey (LFS) is conducted quarterly by the National Statistical Institute (ISTAT) to produce estimates of the labor force status of the population at different geographical levels. In particular, ISTAT provides LFS estimates of employed and unemployed counts for local Labor Market Areas (LMAs). LMAs are 611 sub-regional clusters of municipalities and are unplanned domains for which direct estimates have overly large sampling errors. This implies the need of Small Area Estimation (SAE) methods. In this paper, we develop a new area level SAE method that uses a Latent Markov Model (LMM) as linking model. In LMMs, the characteristic of interest, and its evolution in time, is represented by a latent process that follows a Markov chain, usually of first order. Therefore, areas are allowed to change their latent state across time. The proposed model is applied to quarterly data from the LFS for the period 2004 to 2014 and fitted within a hierarchical Bayesian framework using a data augmentation Gibbs sampler. Estimates are compared with those obtained by the classical Fay-Herriot model, by a time-series area level SAE model, and on the basis of data coming from the 2011 Population Census.

Description:

When a linear imputation method is used to correct non-response based on certain assumptions, total variance can be assigned to non-responding units. Linear imputation is not as limited as it seems, given that the most common methods – ratio, donor, mean and auxiliary value imputation – are all linear imputation methods. We will discuss the inference framework and the unit-level decomposition of variance due to non-response. Simulation results will also be presented. This decomposition can be used to prioritize non-response follow-up or manual corrections, or simply to guide data analysis.

Description:

Domains (or subpopulations) with small sample sizes are called small areas. Traditional direct estimators for small areas do not provide adequate precision because the area-specific sample sizes are small. On the other hand, demand for reliable small area statistics has greatly increased. Model-based indirect estimators of small area means or totals are currently used to address difficulties with direct estimation. These estimators are based on linking models that borrow information across areas to increase the efficiency. In particular, empirical best (EB) estimators under area level and unit level linear regression models with random small area effects have received a lot of attention in the literature. Model mean squared error (MSE) of EB estimators is often used to measure the variability of the estimators. Linearization-based estimators of model MSE as well as jackknife and bootstrap estimators are widely used. On the other hand, National Statistical Agencies are often interested in estimating the design MSE of EB estimators in line with traditional design MSE estimators associated with direct estimators for large areas with adequate sample sizes. Estimators of design MSE of EB estimators can be obtained for area level models but they tend to be unstable when the area sample size is small. Composite MSE estimators are proposed in this paper and they are obtained by taking a weighted sum of the design MSE estimator and the model MSE estimator. Properties of the MSE estimators under the area level model are studied in terms of design bias, relative root mean squared error and coverage rate of confidence intervals. The case of a unit level model is also examined under simple random sampling within each area. Results of a simulation study show that the proposed composite MSE estimators provide a good compromise in estimating the design MSE.

Description:

This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.

Description:

The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.

Description: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.

Description:

Historical works allow readers to peer into the past, not only to satisfy our curiosity about “the way things were,” but also to see how far we’ve come, and to learn from the past. For Statistics Canada, such works are also opportunities to commemorate the agency’s contributions to Canada and its people, and serve as a reminder that an institution such as this continues to evolve each and every day.

On the occasion of Statistics Canada’s 100th anniversary in 2018, Standing on the shoulders of giants: History of Statistics Canada: 1970 to 2008, builds on the work of two significant publications on the history of the agency, picking up the story in 1970 and carrying it through the next 36 years, until 2008. To that end, when enough time has passed to allow for sufficient objectivity, it will again be time to document the agency’s next chapter as it continues to tell Canada’s story in numbers.

Description:

This report summarizes the achievements program sponsored by the three methodology divisions of Statistics Canada. This program covers research and development activities in statistical methods with potentially broad application in the Agency's survey programs, which would not otherwise have been carried out during the provision of methodology services to those survey programs. They also include tasks that provided client support in the application of past successful developments in order to promote the utilization of the results of research and development work.

Description:

The Record Linkage Project Process Model (RLPPM) was developed by Statistics Canada to identify the processes and activities involved in record linkage. The RLPPM applies to linkage projects conducted at the individual and enterprise level using diverse data sources to create new data sources to meet analytical and operational needs.

Description:

This document briefly describes Demosim, the microsimulation population projection model, how it works as well as its methods and data sources. It is a methodological complement to the analytical products produced using Demosim.

Description:

This publication is a catalogue of strategies and mechanisms that a statistical organization should consider adopting, according to its particular context. This compendium is based on lessons learned and best practices of leadership and management of statistical agencies within the scope of Statistics Canada’s International Statistical Fellowship Program (ISFP). It contains four broad sections including, characteristics of an effective national statistical system; core management practices; improving, modernizing and finding efficiencies; and, strategies to better inform and engage key stakeholders.

Description:

Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.

Description:

The Geography working paper series is intended to stimulate discussion on a variety of topics covering conceptual, methodological or technical work to support the development and dissemination of the division's data, products and services. Readers of the series are encouraged to contact the Geography Division with comments and suggestions.