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Description: Statistics Canada regularly prepares presentations with statistical findings about the country’s economy, society and environment. These presentations may be intended for conferences, meetings with stakeholders, or other events held throughout the year to provide Statistics Canada with an opportunity to promote the role of official statistics and to better understand data users’ needs. This series provides online access to these presentations as well as new presentations created to help communicate research findings on a wide range of subjects to a broad audience.

Description: Economic and Social Reports includes in-depth research, brief analyses, and current economic updates on a variety of topics, such as labour, immigration, education and skills, income mobility, well-being, aging, firm dynamics, productivity, economic transitions, and economic geography. All the papers are institutionally reviewed and the research and analytical papers undergo peer review to ensure that they conform to Statistics Canada's mandate as a governmental statistical agency and adhere to generally accepted standards of good professional practice.

Description: Statistics Canada produces a variety of interactive visualization tools that present data in a graphical form. These tools provide a useful way of interpreting trends behind our data on various social and economic topics.

Description:

Monthly gross new issues, retirements and net new issues of debt securities, including direct and guaranteed bonds, Treasury Bills, and Canada Bills, by geography for the Government of Canada. Also included historical data by security type (common stocks, preferred stocks, trust units, bonds, treasury bills, commercial paper, and term securitizations), and by issuer type (provincial, municipal, corporate, institutions, and foreign debtors).

Description:

Month-end Government of Canada direct bonds outstanding data by currency. Also included historical data by currency for provinces, municipalities, corporations and other institutions.

Description: This table contains 39 series, with data for starting from 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Financial market statistics (39 items: Government of Canada Treasury Bills, 1-month (composite rates); Government of Canada Treasury Bills, 2-month (composite rates); Government of Canada Treasury Bills, 3-month (composite rates);Government of Canada Treasury Bills, 6-month (composite rates); ...).

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New housing price index (NHPI). Monthly data are available from January 1981. The table presents data for the most recent reference period and the last four periods. The base period for the index is (201612=100).

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New housing price index (NHPI). Monthly data are available from February 1981. The table presents month-over-month and year-over-year percentage changes for various aggregation levels. The base period for the index is (201612=100).

Description: Seasonally adjusted receipts of monthly survey of food services and drinking places, by North American Industry Classification System (NAICS), monthly, for five months of data.

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Weekly Itinerant aircraft movements (domestic, transborder and international), total of all Canadian airports with NAV CANADA towers.

Description: This table contains 7 series, with data starting from 1972 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Commodity (7 items: Total; all commodities; Metals and Minerals; Energy; Total excluding energy ...).

Description: This table contains 12 series, with data starting from 1954 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: United States); Rates (12 items: Federal Reserve Bank of New York - discount rate; Prime rate charged by banks; Federal funds rate;Commercial paper, adjusted: 1 month; ...).

Description: This table contains 7 series, with data starting from 1972 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Commodity (7 items: Total, all commodities; Total excluding energy; Energy; Metals and Minerals; ...).

Description: This table contains 38 series, with data starting from 1957 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Rates (38 items: Bank rate; Chartered bank administered interest rates - prime business; Chartered bank - consumer loan rate; Forward premium or discount (-), United States dollars in Canada: 1 month; ...).

Description:

This table presents a few different variables for over 50 products from the mining industry such as aluminum, cobalt, gold, iron, lead, nickel, silver, etc. The variables available in this table are the quantity produced, the quantity shipped, the closing inventories and the value of shipments. The data are published at the national, provincial and territorial levels.

Description:

This table presents different variables for a dozen of products from the mining industry such as diamonds, clay, gypsum, lime, potash, salt, etc. The variables available in this table are the quantity produced, the quantity shipped and the value of shipments. The data are published at the national, provincial and territorial levels.

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This table presents the value of shipments for multiple mining industry products such as cobalt, gold, iron, lead, platinum, titanium, zinc, diamonds, etc. The data are published at the national, provincial and territorial levels.

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Value of shipments of critical minerals, as defined by the Critical Minerals Centre of Excellence (CMCE) at Natural Resources Canada.

Description:

Industrial product price index (IPPI), by major product group by North American Product Classification System (NAPCS) 2017 Version 2.0. Monthly data are available from January 1956. The table presents data for the most recent reference period and the last four periods. The base period for the index is (202001=100).

Description:

Industrial product price index (IPPI), by major product group by North American Product Classification System (NAPCS) 2017 Version 2.0. Monthly data are available from January 1956. The table presents month-over-month and year-over-year percentage changes for various aggregation levels. The base period for the index is (202001=100).

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

Description: Inspired by the two excellent discussions of our paper, we offer some new insights and developments into the problem of estimating participation probabilities for non-probability samples. First, we propose an improvement of the method of Chen, Li and Wu (2020), based on best linear unbiased estimation theory, that more efficiently leverages the available probability and non-probability sample data. We also develop a sample likelihood approach, similar in spirit to the method of Elliott (2009), that properly accounts for the overlap between both samples when it can be identified in at least one of the samples. We use best linear unbiased prediction theory to handle the scenario where the overlap is unknown. Interestingly, our two proposed approaches coincide in the case of unknown overlap. Then, we show that many existing methods can be obtained as a special case of a general unbiased estimating function. Finally, we conclude with some comments on nonparametric estimation of participation probabilities.

Description: We provide comparisons among three parametric methods for the estimation of participation probabilities and some brief comments on homogeneous groups and post-stratification.

Description: Beaumont, Bosa, Brennan, Charlebois and Chu (2024) propose innovative model selection approaches for estimation of participation probabilities for non-probability sample units. We focus our discussion on the choice of a likelihood and parameterization of the model, which are key for the effectiveness of the techniques developed in the paper. We consider alternative likelihood and pseudo-likelihood based methods for estimation of participation probabilities and present simulations implementing and comparing the AIC based variable selection. We demonstrate that, under important practical scenarios, the approach based on a likelihood formulated over the observed pooled non-probability and probability samples performed better than the pseudo-likelihood based alternatives. The contrast in sensitivity of the AIC criteria is especially large for small probability sample sizes and low overlap in covariates domains.

Description: Non-probability samples are being increasingly explored in National Statistical Offices as an alternative to probability samples. However, it is well known that the use of a non-probability sample alone may produce estimates with significant bias due to the unknown nature of the underlying selection mechanism. Bias reduction can be achieved by integrating data from the non-probability sample with data from a probability sample provided that both samples contain auxiliary variables in common. We focus on inverse probability weighting methods, which involve modelling the probability of participation in the non-probability sample. First, we consider the logistic model along with pseudo maximum likelihood estimation. We propose a variable selection procedure based on a modified Akaike Information Criterion (AIC) that properly accounts for the data structure and the probability sampling design. We also propose a simple rank-based method of forming homogeneous post-strata. Then, we extend the Classification and Regression Trees (CART) algorithm to this data integration scenario, while again properly accounting for the probability sampling design. A bootstrap variance estimator is proposed that reflects two sources of variability: the probability sampling design and the participation model. Our methods are illustrated using Statistics Canada’s crowdsourcing and survey data.

Description: In this rejoinder, I address the comments from the discussants, Dr. Takumi Saegusa, Dr. Jae-Kwang Kim and Ms. Yonghyun Kwon. Dr. Saegusa’s comments about the differences between the conditional exchangeability (CE) assumption for causal inferences versus the CE assumption for finite population inferences using nonprobability samples, and the distinction between design-based versus model-based approaches for finite population inference using nonprobability samples, are elaborated and clarified in the context of my paper. Subsequently, I respond to Dr. Kim and Ms. Kwon’s comprehensive framework for categorizing existing approaches for estimating propensity scores (PS) into conditional and unconditional approaches. I expand their simulation studies to vary the sampling weights, allow for misspecified PS models, and include an additional estimator, i.e., scaled adjusted logistic propensity estimator (Wang, Valliant and Li (2021), denoted by sWBS). In my simulations, it is observed that the sWBS estimator consistently outperforms or is comparable to the other estimators under the misspecified PS model. The sWBS, as well as WBS or ABS described in my paper, do not assume that the overlapped units in both the nonprobability and probability reference samples are negligible, nor do they require the identification of overlap units as needed by the estimators proposed by Dr. Kim and Ms. Kwon.

Description: In some of non-probability sample literature, the conditional exchangeability assumption is considered to be necessary for valid statistical inference. This assumption is rooted in causal inference though its potential outcome framework differs greatly from that of non-probability samples. We describe similarities and differences of two frameworks and discuss issues to consider when adopting the conditional exchangeability assumption in non-probability sample setups. We also discuss the role of finite population inference in different approaches of propensity scores and outcome regression modeling to non-probability samples.

Description: Pseudo weight construction for data integration can be understood in the two-phase sampling framework. Using the two-phase sampling framework, we discuss two approaches to the estimation of propensity scores and develop a new way to construct the propensity score function for data integration using the conditional maximum likelihood method. Results from a limited simulation study are also presented.

Description: Nonprobability samples emerge rapidly to address time-sensitive priority topics in different areas. These data are timely but subject to selection bias. To reduce selection bias, there has been wide literature in survey research investigating the use of propensity-score (PS) adjustment methods to improve the population representativeness of nonprobability samples, using probability-based survey samples as external references. Conditional exchangeability (CE) assumption is one of the key assumptions required by PS-based adjustment methods. In this paper, I first explore the validity of the CE assumption conditional on various balancing score estimates that are used in existing PS-based adjustment methods. An adaptive balancing score is proposed for unbiased estimation of population means. The population mean estimators under the three CE assumptions are evaluated via Monte Carlo simulation studies and illustrated using the NIH SARS-CoV-2 seroprevalence study to estimate the proportion of U.S. adults with COVID-19 antibodies from April 01-August 04, 2020.

Description: Our comments respond to discussion from Sen, Brick, and Elliott. We weigh the potential upside and downside of Sen’s suggestion of using machine learning to identify bogus respondents through interactions and improbable combinations of variables. We join Brick in reflecting on bogus respondents’ impact on the state of commercial nonprobability surveys. Finally, we consider Elliott’s discussion of solutions to the challenge raised in our study.

Description: The Guide to Employment Insurance Statistics (EIS) summarizes the survey methodology and data source and includes a dictionary of concepts and definitions used by the program.

Description: Data on income of census families, individuals and seniors are derived from the T1 Family File (T1FF). This file is based on information from the T1 form, Income Tax and Benefit Return, which Statistics Canada receives from Canada Revenue Agency (CRA) thirteen months after the end of the taxation year.

Description: Data on income of census families, individuals and seniors are derived from income tax returns. The data for the products associated with this release are derived from the T1 file that Statistics Canada receives from Canada Revenue Agency (CRA) thirteen months after the end of the taxation year.

Description: This reference guide is intended for users of the Census Subdivisions Boundary File. The guide provides an overview of the file, the general methodology used to create it, and important technical information for users.

Description: The Census Subdivision Boundary File contains the boundaries of all census subdivisions which combined cover all of Canada. A census subdivision is a municipality or an area treated as an equivalent to a municipality for statistical purposes (for example, Indian reserves and unorganized territories). The file provides a framework for mapping and spatial analysis using commercially available geographic information systems (GIS) or other mapping software.

The Census Subdivision Boundary File is portrayed in Lambert conformal conic projection and is based on the North American Datum of 1983 (NAD83). A reference guide is available (92-162-G).

Description: This reference guide is intended for users of the Road Network File. The guide provides an overview of the file, the general methodology used to create it, and important technical information for users.

Description: The Road Network File (RNF) is a digital representation of Canada's national road network, containing information such as street names, types, directions and address ranges. The information comes from the National Geographic Database (NGD).

A reference guide is available (92-500-G).

Description: This report provides a summary of changes to municipal boundaries, status and names. The list is usually produced on an annual basis for changes that occurred during the previous year. A five year list is produced on Census of population years.

Description: This report aims to describe the methods used for the calculation of projection parameters, the various projection assumptions and their rationales.

Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality.