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- 21. Seasonal adjustment of short series ArchivedArticles and reports: 11-522-X20030017693Description:
This paper evaluates changes in the quality performances of two different and widely used programs for seasonal adjustment, X-12-Regarima and Tramo-Seats, when the length of time series is progressively reduced.
Release date: 2005-01-26 - 22. Large and complex surveys - discussion ArchivedArticles and reports: 11-522-X20010016230Description:
This publication consists of three papers, each addressing data quality issues associated with a large and complex survey. Two of the case studies involve household surveys of labour force activity and the third focuses on a business survey. The papers each address a data quality topic from a different perspective, but share some interesting common threads.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016260Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
The Canadian Vehicle Survey (CVS), which began in 1999, is designed to collect information about the usage of motor vehicles registered in Canada. The CVS target population includes all on-road vehicles (except special equipment, trailers and motorcycles) registered in Canada. A sample of vehicles is drawn each quarter and a seven-day trip log is used to gather detailed vehicle usage patterns. The log includes questions on kilometres driven, number of passengers, vehicle characteristics, trip purpose and travel times, driver and passenger demographics and fuel usage. Since this is a voluntary survey and the log takes seven days to complete, every effort is made to ensure a good response rate and prevent response errors. The first part of this paper describes the current survey design, data collection, and editing and imputation methodology. Then it goes on to explain the challenges associated with the different steps of the survey. Finally, findings from the research carried out to minimize the effects of non-sampling errors are presented.
Release date: 2002-09-12 - 24. Hot deck imputation for the response model ArchivedArticles and reports: 11-522-X20010016275Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
Hot deck imputation, in which missing items are replaced with values from respondents, is often used in survey sampling. A model supporting such procedures is the model in which response probabilities are assumed equal within imputation cells. In this paper, an efficient version of hot deck imputation is described, as are the variance of the efficient version derived under the cell response model and an approximation to the fully efficient procedure in which a small number of values are imputed for each non-respondent, respectively. Variance estimation procedures are presented and illustrated in a Monte Carlo study.
Release date: 2002-09-12 - 25. Regression estimation for survey samples ArchivedArticles and reports: 12-001-X20020016408Description:
Regression and regression-related procedures have become common in survey estimation. We review the basic properties of regression estimators, discuss implementation of regression estimation, and investigate variance estimation for regression estimators. The role of models in constructing regression estimators and the use of regression in non-response adjustment are also explored.
Release date: 2002-07-05 - 26. New time series on for-hire trucking ArchivedArticles and reports: 53-222-X19980006587Description:
The primary purpose of this article is to present a new time series data and to demonstrate its analytical potential and not to provide a detailed analysis of these data. The analysis in section 5.2.4 will deal primarily with the trends of major variables dealing with domestic and transborder traffic.
Release date: 2000-03-07 - 27. Toward variances for X-11 seasonal adjustments ArchivedArticles and reports: 12-001-X19990014709Description:
We develop an approach to estimating variances for X-11 seasonal adjustments that recognizes the effects of sampling error and errors from forecast extension. In our approach, seasonal adjustment error in the central values of a sufficiently long series results only from the effect of the X-11 filtering on the sampling errors. Towards either end of the series, we also recognize the contribution to seasonal adjustment error from forecast and backcast errors. We extend the approach to produce variances of errors in X-11 trend estimates, and to recognize error in estimation of regression coefficients used to model, e.g., calendar effects. In empirical results, the contribution of sampling error often dominated the seasonal adjustment variances. Trend estimate variances, however, showed large increases at the ends of series due to the effects of fore/backcast error. Nonstationarities in the sampling errors produced striking patterns in the seasonal adjustment and trend estimate variances.
Release date: 1999-10-08
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- Journals and periodicals: 12-206-XDescription: This report summarizes the annual achievements of the Methodology Research and Development Program (MRDP) sponsored by the Modern Statistical Methods and Data Science Branch at Statistics Canada. This program covers research and development activities in statistical methods with potentially broad application in the agency’s statistical programs; these activities would otherwise be less likely to be carried out during the provision of regular methodology services to those programs. The MRDP also includes activities that provide support in the application of past successful developments in order to promote the use of the results of research and development work. Selected prospective research activities are also presented.Release date: 2023-10-11
- Articles and reports: 12-001-X202300100010Description: Precise and unbiased estimates of response propensities (RPs) play a decisive role in the monitoring, analysis, and adaptation of data collection. In a fixed survey climate, those parameters are stable and their estimates ultimately converge when sufficient historic data is collected. In survey practice, however, response rates gradually vary in time. Understanding time-dependent variation in predicting response rates is key when adapting survey design. This paper illuminates time-dependent variation in response rates through multi-level time-series models. Reliable predictions can be generated by learning from historic time series and updating with new data in a Bayesian framework. As an illustrative case study, we focus on Web response rates in the Dutch Health Survey from 2014 to 2019.Release date: 2023-06-30
- Articles and reports: 11-522-X202100100004Description:
With labour market uncertainty increasing across Canada, there is a need for innovative ways to help displaced workers to re-skill/up-skill and potentially pivot to in-demand occupations. In our study, we present a unique approach to bridge the gap between the displaced and in-demand occupations and provide a machine learning framework that may be able to forecast employment by NAICS for 6 months. We have combined the monthly employment data from Statistics Canada’s Survey of Employment and Payroll Hours, and the monthly job ads counts from Burning Glass to achieve our goal. Our approach consists of three steps: 1. Finding the displaced occupations in Alberta over the last 7 years based on the integrated actual employment and job ads count data. Step. 2. Using the list of displaced occupations, a unique pivot graph is developed to map a displaced occupation to a list of in-demand occupations which have skills similar to the chosen displaced occupation. Step 3. Applying SARIMA and SARIMAX models to forecast employment for 6 months. The above approaches are aimed at assisting public policy and planning
Key Words: Employment; Labour Market; Job Ads; Skills; Time Series Analysis; Forecasting.
Release date: 2021-10-15 - Articles and reports: 11-522-X202100100020Description: Seasonal adjustment of time series at Statistics Canada is performed using the X-12-ARIMA method. For most statistical programs performing seasonal adjustment, subject matter experts (SMEs) are responsible for managing the program and for verification, analysis and dissemination of the data, while methodologists from the Time Series Research and Analysis Center (TSRAC) are responsible for developing and maintaining the seasonal adjustment process and for providing support on seasonal adjustment to SMEs. A visual summary report called the seasonal adjustment dashboard has been developed in R Shiny by the TSRAC to build capacity to interpret seasonally adjusted data and to reduce the resources needed to support seasonal adjustment. It is currently being made available internally to assist SMEs to interpret and explain seasonally adjusted results. The summary report includes graphs of the series across time, as well as summaries of individual seasonal and calendar effects and patterns. Additionally, key seasonal adjustment diagnostics are presented and the net effect of seasonal adjustment is decomposed into its various components. This paper gives a visual representation of the seasonal adjustment process, while demonstrating the dashboard and its interactive functionality.
Key Words: Time Series; X-12-ARIMA; Summary Report; R Shiny.
Release date: 2021-10-15 - 5. Growth Rates Preservation (GRP) temporal benchmarking: Drawbacks and alternative solutions ArchivedArticles and reports: 12-001-X201800154927Description:
Benchmarking monthly or quarterly series to annual data is a common practice in many National Statistical Institutes. The benchmarking problem arises when time series data for the same target variable are measured at different frequencies and there is a need to remove discrepancies between the sums of the sub-annual values and their annual benchmarks. Several benchmarking methods are available in the literature. The Growth Rates Preservation (GRP) benchmarking procedure is often considered the best method. It is often claimed that this procedure is grounded on an ideal movement preservation principle. However, we show that there are important drawbacks to GRP, relevant for practical applications, that are unknown in the literature. Alternative benchmarking models will be considered that do not suffer from some of GRP’s side effects.
Release date: 2018-06-21 - Articles and reports: 11-626-X2016063Description:
This Economic Insights article highlights notable changes in the pace and composition of industrial research and development (R&D) spending in Canada during the 2000-to-2013 period. The analysis is based on historical time series data that conclude with the publication of estimates for reference year 2013. New data on industrial R&D will be released in the coming months. These new survey results begin with estimates for reference year 2014 and reflect conceptual and methodological changes designed to enhance the scope and relevance of the program. Following the introduction of these changes, a study on the break in the time series will be conducted later in 2017. his article highlights trends in industrial R&D spending in advance of the upcoming release of the new data. The analysis underscores the extent to which support for higher R&D spending in more recent years has come from resource-based companies.
Release date: 2017-02-15 - Articles and reports: 13-604-M2015077Description:
This new dataset increases the information available for comparing the performance of provinces and territories across a range of measures. It combines often fragmented provincial time series data that, as such, are of limited utility for examining the evolution of provincial economies over extended periods. More advanced statistical methods, and models with greater breadth and depth, are difficult to apply to existing fragmented Canadian data. The longitudinal nature of the new provincial dataset remedies this shortcoming. This report explains the construction of the latest vintage of the dataset. The dataset contains the most up-to-date information available.
Release date: 2015-02-12 - 8. What can we learn about low-income dynamics in Canada from the Longitudinal Administrative Databank? ArchivedArticles and reports: 75F0002M2014002Description:
Statistics that depict the movements in the bottom end of the income distribution, such as the proportion of low-income persons exiting low income from one year to the next, provide important information for developing policy on poverty and income inequality. Since the mid 1990s, these statistics have been generated using data from the Survey of Labour and Income Dynamics (SLID). The longitudinal component of the SLID was discontinued in 2010. This paper examines new and alternative time series on low income dynamics that can be created using the Longitudinal Administrative Databank (LAD).
Release date: 2014-12-19 - 9. Precipitation trends in Canada ArchivedArticles and reports: 16-002-X201100311547Geography: CanadaDescription: This article describes annual and seasonal time series of precipitation over a 62 year period and is the third in an ongoing series of short analytical articles featuring climate related data. This and future articles in the series are the product of ongoing collaboration among Statistics Canada, Environment Canada and Natural Resources Canada.Release date: 2011-09-20
- 10. Shelters for abused women in Canada, 2010 ArchivedArticles and reports: 85-002-X201100111495Geography: CanadaDescription:
This Juristat article analyses residential facilities in Canada that offered shelter to abused women in 2010. It presents information on the different types of facilities, the number of annual admissions, the reasons that women seek shelter and the variety of services offered to clients. In addition, this article examines the use of shelters that offer culturally sensitive services to Aboriginal people, living both on and off reserves. The data for this article was collected by the 2010 Transition Home Survey (THS), a census of residential facilities for female victims of abuse conducted by the Canadian Centre for Justice Statistics as part of the federal government's Family Violence Initiative. Annual admissions and expenditures information pertain to a 12-month period over 2009/2010, while other admissions and client characteristics are based on a one-day "snapshot" date of April 15, 2010. Comparisons using time-series data from the THS Trend File are also included. The THS Trend File contains only those facilities that have participated in each cycle of the survey since the 2002 survey cycle.
Release date: 2011-06-27
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- Surveys and statistical programs – Documentation: 13-606-G201600114622Description:
An explanation of the national accounts price-quantity decomposition using Laspeyres, Paasche and Fisher indexes.
Release date: 2016-11-30 - 2. Finding and Using Statistics ArchivedSurveys and statistical programs – Documentation: 11-533-XDescription:
This guide has been created especially for users needing a step-by-step review on how to find, read and use data, with quick tips on locating information on the Statistics Canada website. Originally published in paper format in the 1980s, revised as part of the 1994 Statistics Canada Catalogue, and then transformed into an electronic version, this guide is continually being updated to maintain its currency and usefulness.
Release date: 2007-11-19
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