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Description:

Retail Trade, sales by industries based on North American Industry Classification System (NAICS), monthly.

Description:

Retail Trade, e-commerce sales, Canada, by industries based on North American Industry Classification System (NAICS), monthly.

Description:

Retail trade sales figures for the motor vehicle and parts dealers industry. Data are available on a monthly basis for Canada and provinces, in dollars x 1,000.

Description:

Retail trade sales, price, and volume, for Canada, includes all members under North American Industry Classification System. Data is seasonally adjusted, available on a monthly basis in dollars x 1,000,000.

Description: Retail trade sales, price, and volume for motor vehicle and parts dealers. Data are seasonally adjusted, available on a monthly basis for Canada, in dollars x 1,000,000.

Description: Crude oil and petroleum products opening and closing inventories, by mode of transport including pipelines, marine vessels and associated terminals, by product type, monthly, not seasonally adjusted.

Description: Crude oil and petroleum products movements, by mode of transport including pipelines, marine vessels and associated terminals, by product type, moved from shipping region to receiving region, monthly, not seasonally adjusted.

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: The need for alternative data sources is of growing importance for both supplementing Statistics Canada's data holdings and for nowcasting economic activity. In response to this need, Statistics Canada initiated the development of a Real-time Local Business Conditions Index (RT-LBCI). The index brings together data from a few different sources, including Google's Places API (containing data on temporary and permanent businesses closures), TomTom Real-time traffic API (road traffic data), as well as information from Statistics Canada data holdings (monthly retail and wholesale, Business Register, etc.). The project aims to compute a near real-time index of economic activity in Canadian major cities.

Description:

This table contains 27 series, with data starting from 1981 (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); Type of currency (27 items: Australian dollar, daily average; Brazilian real, daily average; Chinese renminbi, daily average; European euro, daily average; ...).

Description:

The RT-LBCI is released as an experimental statistic. It is intended to provide a real-time signal on business activities following the disruptions brought about by the pandemic and through the recovery phase.

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: 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 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); ...).

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:

Monthly credit aggregates for the household sector, by category.

Description:

Monthly credit aggregates for the private non-financial corporations sector, by category.

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: 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: 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:

This technical reference guide is intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The data for the products associated with this issue are based on the longitudinal Postsecondary Student Information System (PSIS) administrative data files. Statistics Canada has derived a series of annual indicators of public postsecondary students including persistence rates, graduation rates, and average time to graduation by educational qualification, field of study, age group and gender for Canada, the provinces, and the three combined Territories.

Description:

As is the case in advance of each Census, content consultations are being held with data users. The Census Content Consultation Guide gives you the opportunity to provide input.

Description: This reference guide provides information to help users effectively use and interpret income data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: This reference guide provides information to help users effectively use and interpret education data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description:

This guide focuses on the following topic: education. This reference guide provides information that enables users to effectively use, apply and interpret data from the 2016 Census. This guide contains definitions and explanations of concepts, classifications, data quality and comparability to other sources. Additional information is included for specific variables to help general users better understand the concepts and questions used in the census.

Description:

This reference guide provides information to help users effectively use and interpret language data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: This reference guide provides information to help users effectively use and interpret commuting data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: This reference guide provides information to help users effectively use and interpret labour data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: This reference guide provides information to help users effectively use and interpret instruction in the minority official language data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: The Census Dictionary is a reference document which contains detailed definitions of Census of Population concepts, variables and geographic terms, as well as historical information.

By referring to the Census Dictionary, both beginner and intermediate data users will gain a better understanding of the data and how to compare variables between census years.

The Census Dictionary will be released iteratively starting with geography and non-data dependent topic definitions, tables, figures and appendices with additional content made available based on subsequent topic releases.