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All (13) (0 to 10 of 13 results)
- Articles and reports: 12-001-X202600100002Description: Survey data typically have missing values due to unit and item nonresponse. Sometimes, survey organizations know the marginal distributions of certain categorical variables in the target population. As shown in previous work, survey organizations can leverage these distributions in multiple imputation for nonignorable unit nonresponse, generating imputations that result in plausible completed-data estimates for the variables with known margins. However, this prior work does not use the design weights for unit nonrespondents. We extend this previous work to utilize the design weights for all sampled units. We illustrate the approach using simulation studies.Release date: 2026-06-29
- Articles and reports: 62F0014M2026001Description: This report provides research and analysis pertaining to Transportation services index (TSI) and Supply Chain Services Price Index (SCSPI). Monthly data are available from January 2018 at Canada Level. The base period for the index is (Jan 2018=100).Release date: 2026-03-20
- Articles and reports: 12-001-X202500200007Description: Although probability samples have been regarded as the gold standard to collect information for population-based study, non-probability samples have been used frequently in practice due to low cost, convenience, and the lack of the sampling frame for the survey. Naïve estimates based on non-probability samples without any adjustments may be misleading due to selection bias. Recently, a valid data integration approach that includes mass imputation, propensity score weighting, and calibration has been used to improve the representativeness of non-probability samples. The effectiveness of the mass imputation approach depends on the underlying model assumptions. In this paper, we propose using deep learning for the mass imputation in the combining of probability and non-probability samples and compare it with several modern machine learning-based mass imputation approaches, including generalized additive modeling, regression tree, random forest, and XG-boosting. In the simulation study, deep learning-based approaches have been shown to be more robust and effective than other mass imputation approaches against the failure of underlying model assumptions under non-linearity scenarios.Release date: 2025-12-23
- Articles and reports: 36-28-0001202501100001Description: Citizenship acquisition marks a pivotal milestone in immigrant integration, influencing social cohesion and political participation. While aggregate naturalization rates provide macro-level insights, disparities by source country reveal diverse integration pathways. Through comparative analysis of Australia and Canada—nations with comparable immigration scales and broadly similar immigration approaches, yet notable differences in naturalization frameworks—this study investigates how source-country characteristics affect naturalization patterns.Release date: 2025-11-26
- Articles and reports: 36-28-0001202500700001Description: Postsecondary education is a key element in developing a skilled workforce. International students are often seen as a potential source of labour supply beyond their temporary employment while studying. This study examines the alignment between the fields of study and occupations of immigrants with a postsecondary education who held study permits before becoming permanent residents from 2011 to 2021. It compares them with other immigrants who became permanent residents during the same period and Canadian-born postsecondary graduates.Release date: 2025-07-23
- Articles and reports: 36-28-0001202500600001Description: The United States would be a useful comparison country for Canada in studying immigrant naturalization, as both are major immigrant-receiving nations with close geographic and economic ties. However, differences in available data complicate comparisons of immigrant citizenship rates. This article examines key data sources for studying immigrant citizenship in both countries and highlights the challenges in comparing citizenship rates and trends.Release date: 2025-06-25
- 7. Design-based estimation of small and empty domains in survey data analysis using order constraintsArticles and reports: 12-001-X202400200010Description: Recent work in survey domain estimation has shown that incorporating a priori assumptions about orderings of population domain means reduces the variance of the estimators and provides smaller confidence intervals with good coverage. Here we show how partial ordering assumptions allow design-based estimation of sample means in domains for which the sample size is zero, with conservative variance estimates and confidence intervals. Order restrictions can also substantially improve estimation and inference in small-size domains. Examples with well-known survey data sets demonstrate the utility of the methods. Code to implement the examples using the R package csurvey is given in the appendix.Release date: 2024-12-20
- Articles and reports: 36-28-0001202400300001Description: The agricultural sector in Canada has relied increasingly on temporary foreign workers (TFWs) to fill the longstanding labour shortage. The number of TFWs in crop production, animal production and aquaculture, and support activities for crop and animal production more than tripled between 2005 and 2020. This study examines the transition to permanent residency (PR) of TFWs in primary agriculture and the retention in the sector among those who obtained PR. The study focuses on TFWs whose first employment was in primary agriculture and who entered the sector between 2005 and 2020.Release date: 2024-03-27
- Articles and reports: 12-001-X202300100001Description: Recent work in survey domain estimation allows for estimation of population domain means under a priori assumptions expressed in terms of linear inequality constraints. For example, it might be known that the population means are non-decreasing along ordered domains. Imposing the constraints has been shown to provide estimators with smaller variance and tighter confidence intervals. In this paper we consider a formal test of the null hypothesis that all the constraints are binding, versus the alternative that at least one constraint is non-binding. The test of constant versus increasing domain means is a special case. The power of the test is substantially better than the test with the same null hypothesis and an unconstrained alternative. The new test is used with data from the National Survey of College Graduates, to show that salaries are positively related to the subject’s father’s educational level, across fields of study and over several years of cohorts.Release date: 2023-06-30
- Articles and reports: 36-28-0001202300100002Description: A large body of studies have consistently demonstrated that higher proficiency in the destination-country language improves immigrant labour market outcomes. However, because of the lack of objective measures of language skills, previous studies have mainly drawn on subjective measures of language proficiency and were confined to the effect of only one dimension or general language skills. This study examines the effects of test-based measures of official language proficiency in four dimensions — listening, speaking, reading and writing —on immigrant employment and earnings.Release date: 2023-01-25
Articles and reports (13)
Articles and reports (13) (0 to 10 of 13 results)
- Articles and reports: 12-001-X202600100002Description: Survey data typically have missing values due to unit and item nonresponse. Sometimes, survey organizations know the marginal distributions of certain categorical variables in the target population. As shown in previous work, survey organizations can leverage these distributions in multiple imputation for nonignorable unit nonresponse, generating imputations that result in plausible completed-data estimates for the variables with known margins. However, this prior work does not use the design weights for unit nonrespondents. We extend this previous work to utilize the design weights for all sampled units. We illustrate the approach using simulation studies.Release date: 2026-06-29
- Articles and reports: 62F0014M2026001Description: This report provides research and analysis pertaining to Transportation services index (TSI) and Supply Chain Services Price Index (SCSPI). Monthly data are available from January 2018 at Canada Level. The base period for the index is (Jan 2018=100).Release date: 2026-03-20
- Articles and reports: 12-001-X202500200007Description: Although probability samples have been regarded as the gold standard to collect information for population-based study, non-probability samples have been used frequently in practice due to low cost, convenience, and the lack of the sampling frame for the survey. Naïve estimates based on non-probability samples without any adjustments may be misleading due to selection bias. Recently, a valid data integration approach that includes mass imputation, propensity score weighting, and calibration has been used to improve the representativeness of non-probability samples. The effectiveness of the mass imputation approach depends on the underlying model assumptions. In this paper, we propose using deep learning for the mass imputation in the combining of probability and non-probability samples and compare it with several modern machine learning-based mass imputation approaches, including generalized additive modeling, regression tree, random forest, and XG-boosting. In the simulation study, deep learning-based approaches have been shown to be more robust and effective than other mass imputation approaches against the failure of underlying model assumptions under non-linearity scenarios.Release date: 2025-12-23
- Articles and reports: 36-28-0001202501100001Description: Citizenship acquisition marks a pivotal milestone in immigrant integration, influencing social cohesion and political participation. While aggregate naturalization rates provide macro-level insights, disparities by source country reveal diverse integration pathways. Through comparative analysis of Australia and Canada—nations with comparable immigration scales and broadly similar immigration approaches, yet notable differences in naturalization frameworks—this study investigates how source-country characteristics affect naturalization patterns.Release date: 2025-11-26
- Articles and reports: 36-28-0001202500700001Description: Postsecondary education is a key element in developing a skilled workforce. International students are often seen as a potential source of labour supply beyond their temporary employment while studying. This study examines the alignment between the fields of study and occupations of immigrants with a postsecondary education who held study permits before becoming permanent residents from 2011 to 2021. It compares them with other immigrants who became permanent residents during the same period and Canadian-born postsecondary graduates.Release date: 2025-07-23
- Articles and reports: 36-28-0001202500600001Description: The United States would be a useful comparison country for Canada in studying immigrant naturalization, as both are major immigrant-receiving nations with close geographic and economic ties. However, differences in available data complicate comparisons of immigrant citizenship rates. This article examines key data sources for studying immigrant citizenship in both countries and highlights the challenges in comparing citizenship rates and trends.Release date: 2025-06-25
- 7. Design-based estimation of small and empty domains in survey data analysis using order constraintsArticles and reports: 12-001-X202400200010Description: Recent work in survey domain estimation has shown that incorporating a priori assumptions about orderings of population domain means reduces the variance of the estimators and provides smaller confidence intervals with good coverage. Here we show how partial ordering assumptions allow design-based estimation of sample means in domains for which the sample size is zero, with conservative variance estimates and confidence intervals. Order restrictions can also substantially improve estimation and inference in small-size domains. Examples with well-known survey data sets demonstrate the utility of the methods. Code to implement the examples using the R package csurvey is given in the appendix.Release date: 2024-12-20
- Articles and reports: 36-28-0001202400300001Description: The agricultural sector in Canada has relied increasingly on temporary foreign workers (TFWs) to fill the longstanding labour shortage. The number of TFWs in crop production, animal production and aquaculture, and support activities for crop and animal production more than tripled between 2005 and 2020. This study examines the transition to permanent residency (PR) of TFWs in primary agriculture and the retention in the sector among those who obtained PR. The study focuses on TFWs whose first employment was in primary agriculture and who entered the sector between 2005 and 2020.Release date: 2024-03-27
- Articles and reports: 12-001-X202300100001Description: Recent work in survey domain estimation allows for estimation of population domain means under a priori assumptions expressed in terms of linear inequality constraints. For example, it might be known that the population means are non-decreasing along ordered domains. Imposing the constraints has been shown to provide estimators with smaller variance and tighter confidence intervals. In this paper we consider a formal test of the null hypothesis that all the constraints are binding, versus the alternative that at least one constraint is non-binding. The test of constant versus increasing domain means is a special case. The power of the test is substantially better than the test with the same null hypothesis and an unconstrained alternative. The new test is used with data from the National Survey of College Graduates, to show that salaries are positively related to the subject’s father’s educational level, across fields of study and over several years of cohorts.Release date: 2023-06-30
- Articles and reports: 36-28-0001202300100002Description: A large body of studies have consistently demonstrated that higher proficiency in the destination-country language improves immigrant labour market outcomes. However, because of the lack of objective measures of language skills, previous studies have mainly drawn on subjective measures of language proficiency and were confined to the effect of only one dimension or general language skills. This study examines the effects of test-based measures of official language proficiency in four dimensions — listening, speaking, reading and writing —on immigrant employment and earnings.Release date: 2023-01-25