Filter results by

Search Help
Currently selected filters that can be removed

Keyword(s)

Survey or statistical program

497 facets displayed. 0 facets selected.

Content

1 facets displayed. 0 facets selected.
Sort Help
entries

Results

All (10,026)

All (10,026) (80 to 90 of 10,026 results)

  • Articles and reports: 11-522-X202200100017
    Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.
    Release date: 2024-06-28

  • Journals and periodicals: 11-522-X
    Description: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.
    Release date: 2024-06-28

  • Stats in brief: 11-001-X20241794822
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-27

  • Articles and reports: 75-005-M2024002
    Description: Survey of Employment, Payrolls and Hours (SEPH) and the Labour Force Survey (LFS) each provide monthly indicators of pay received by employees. Year-over-year variations in average weekly earnings (from SEPH) and average hourly wages (from LFS) provide information on current wage dynamics. This guide provides information to help analysts use each indicator by highlighting their key conceptual and measurement differences. It also outlines possible causes of variations for each indicator and provides general examples of using both measures.
    Release date: 2024-06-27

  • Journals and periodicals: 75-005-M
    Description: The papers in this series cover a variety of technical topics related to the Centre for Labour Market Information programs, such as the Labour Force Survey, the Survey of Employment Payrolls and Hours, the Employment insurance Coverage Survey, the Employment Insurance Statistics program as well as data from administrative sources.
    Release date: 2024-06-27

  • Articles and reports: 36-28-0001202400600001
    Description: Obtaining a work permit enables foreign nationals to work in Canada temporarily, and for many individuals, this serves as a stepping stone toward obtaining permanent residency (PR). This article examines the recent changes in the transition to PR across work permit programs and immigration pathways for individuals who have made the transition. The analysis focuses on work permit holders who are in Canada for work purposes under either the Temporary Foreign Worker Program (TFWP) or the International Mobility Program (IMP).
    Release date: 2024-06-26

  • Articles and reports: 36-28-0001202400600002
    Description: Retaining and recruiting young skilled workers are important for any community, but perhaps even more so for communities where the main language spoken is a minority official language. This article informs the issue by calculating the share of youth who grew up in a province and eventually obtained a postsecondary education, but who left to work in another part of the country (termed “skill loss”). Likewise, the article also looks at young postsecondary graduates who entered a province to work, as a share of that province’s initial population of homegrown young postsecondary graduates (termed “skill gain”).
    Release date: 2024-06-26

  • Articles and reports: 36-28-0001202400600003
    Description: Businesses have faced numerous challenges since the beginning of the COVID-19 pandemic. Public health restrictions on business and personal activities aimed at stopping the spread of the virus were associated with a slowing of economic activity. This article examines how new businesses that entered after the beginning of the pandemic fared compared with previous entry cohorts.
    Release date: 2024-06-26

  • Articles and reports: 36-28-0001202400600004
    Description: On average, individuals who own their dwelling report higher satisfaction with their dwelling, neighbourhood and life than renters. These differences may reflect a positive causal impact of ownership on satisfaction. However, these differences could also reflect compositional effects, such as differences in household, dwelling and neighbourhood characteristics. Using the 2021 Canadian Housing Survey, this study provides a comparison of renters’ and owners’ reported dwelling, neighbourhood and life satisfaction accounting for compositional effects.
    Release date: 2024-06-26

  • Articles and reports: 36-28-0001202400600005
    Description: Approximately one in four individuals in Canada is currently or has been a landed immigrant or permanent resident. From 2016 to 2021, about 1.3 million new immigrants arrived in Canada and accounted for 80% of the growth in the labour force. Alongside increases in immigrants, there has been a rise in same-sex couples within Canada. This study explores select sociodemographic and economic characteristics of immigrants in same-sex couples compared with their counterparts in opposite-sex couples from 2000 to 2020.
    Release date: 2024-06-26
Stats in brief (2,683)

Stats in brief (2,683) (0 to 10 of 2,683 results)

Articles and reports (7,021)

Articles and reports (7,021) (30 to 40 of 7,021 results)

  • Articles and reports: 12-001-X202400100004
    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.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100005
    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.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100006
    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.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100007
    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.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100008
    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.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100009
    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.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100010
    Description: This discussion summarizes the interesting new findings around measurement errors in opt-in surveys by Kennedy, Mercer and Lau (KML). While KML enlighten readers about “bogus responding” and possible patterns in them, this discussion suggests combining these new-found results with other avenues of research in nonprobability sampling, such as improvement of representativeness.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100011
    Description: Kennedy, Mercer, and Lau explore misreporting by respondents in non-probability samples and discover a new feature, namely that of deliberate misreporting of demographic characteristics. This finding suggests that the “arms race” between researchers and those determined to disrupt the practice of social science is not over and researchers need to account for such respondents if using high-quality probability surveys to help reduce error in non-probability samples.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100012
    Description: Nonprobability samples are quick and low-cost and have become popular for some types of survey research. Kennedy, Mercer and Lau examine data quality issues associated with opt-in nonprobability samples frequently used in the United States. They show that the estimates from these samples have serious problems that go beyond representativeness. A total survey error perspective is important for evaluating all types of surveys.
    Release date: 2024-06-25

  • Articles and reports: 12-001-X202400100013
    Description: Statistical approaches developed for nonprobability samples generally focus on nonrandom selection as the primary reason survey respondents might differ systematically from the target population. Well-established theory states that in these instances, by conditioning on the necessary auxiliary variables, selection can be rendered ignorable and survey estimates will be free of bias. But this logic rests on the assumption that measurement error is nonexistent or small. In this study we test this assumption in two ways. First, we use a large benchmarking study to identify subgroups for which errors in commercial, online nonprobability samples are especially large in ways that are unlikely due to selection effects. Then we present a follow-up study examining one cause of the large errors: bogus responding (i.e., survey answers that are fraudulent, mischievous or otherwise insincere). We find that bogus responding, particularly among respondents identifying as young or Hispanic, is a significant and widespread problem in commercial, online nonprobability samples, at least in the United States. This research highlights the need for statisticians working with commercial nonprobability samples to address bogus responding and issues of representativeness – not just the latter.
    Release date: 2024-06-25
Journals and periodicals (322)

Journals and periodicals (322) (320 to 330 of 322 results)

  • Journals and periodicals: 75-002-X
    Description:

    A quarterly newsletter designed to keep data users and other interested persons broadly informed about the Survey of Labour and Income Dynamics. It provides updates on survey developments and issues as they arise. Every issue also includes a brief description of newly released documents in the SLID research paper series.

    Release date: 1997-09-09

  • Journals and periodicals: 85-542-X
    Geography: Canada
    Description:

    The purpose of this report is to reduce the level of confusion arising from the use of crime data originating from two very different sources (i.e., the Uniform Crime Reporting Survey - UCR and the General Social Survey - GSS) and to inform discussions about which is the better measure of crime. It explains why the findings based on these data sources diverge and summarizes the major differences between the two surveys.

    Release date: 1997-05-14
Date modified: