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- Articles and reports: 12-001-X202600100001Description: Wayne A. Fuller is a leading figure in statistics whose career at Iowa State University (ISU) began in 1959; he is now Distinguished Professor Emeritus in Statistics and Economics. This article briefly recounts his early life and training in agricultural economics at ISU and highlights influential contributions spanning time series analysis, measurement error models, and survey sampling. It documents his impact through seminal textbooks, methodological advances such as the Dickey-Fuller test and regression estimation, sustained work on major operational surveys (e.g., the National Resources Inventory), and mentorship of many graduate students. The article includes an interview conducted on May 20th, 2025, at Professor Fuller’s home.Release date: 2026-06-29
- Surveys and statistical programs – Documentation: 19-20-00012026002Description: This reference document provides answers on selected topics related to the use, interpretation, and calculation of trend-cycle estimates for seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment and trend-cycle estimation found in Statistics Canada publications and reference manuals.Release date: 2026-06-08
- Journals and periodicals: 11-633-XDescription: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.Release date: 2026-05-27
- Surveys and statistical programs – Documentation: 19-20-00012026001Description: This reference document provides nontechnical answers on selected topics related to the use and interpretation of seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment found in Statistics Canada publications and reference manuals.Release date: 2026-05-11
- Articles and reports: 75-006-X202400100007Description: This study uses data from multiple waves of the Canadian Social Survey (CSS) to examine trends in three key Quality of Life indicators, namely life satisfaction, experiences of financial hardship, and future outlook. Monitoring these well-being indicators following periods of considerable social and economic change is particularly important. Beginning in the summer of 2021, the CSS, a new quarterly survey, captured the latter part of the COVID-19 pandemic as well as the rising cost of living in Canada, allowing for an understanding of how Canadians are coping with these challenges.Release date: 2024-09-13
- Stats in brief: 11-001-X202425738424Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-09-13
- 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-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 - 9. 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: 82-003-X201800254908Description:
This study examined nine national surveys of the household population which collected information about drug use during the period from 1985 through 2015. These surveys are examined for comparability. The data are used to estimate past-year (current) cannabis use (total, and by sex and age). Based on the most comparable data, trends in use from 2004 through 2015 are estimated.
Release date: 2018-02-21
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- 41. Modelling and estimation for repeated surveys ArchivedArticles and reports: 12-001-X198900114579Description:
Estimation of the means of a characteristic for a population at different points in time, based on a series of repeated surveys, is briefly reviewed. By imposing a stochastic parametric model on these means, it is possible to estimate the parameters of the model and to obtain alternative estimators of the means themselves. We describe the case where the population means follow an autoregressive-moving average (ARMA) process and the survey errors can also be formulated as an ARMA process. An example using data from the Canadian Travel Survey is presented.
Release date: 1989-06-15 - 42. Current issues on seasonal adjustment ArchivedArticles and reports: 12-001-X198700114509Description:
This paper discusses three problems that have been a major preoccupation among researchers and practitioners of seasonal adjustment in statistical bureaus for the last ten years. These problems are: (l) the use of concurrent seasonal factors versus seasonal factor forecasts for current seasonal adjustment; (2) finding an optimal pattern of revisions for series seasonally adjusted with concurrent factors; and (3) smoothing highly irregular seasonally adjusted data.
Release date: 1987-06-15 - 43. Additive versus multiplicative seasonal adjustment when there are fast changes in the trend-cycle ArchivedArticles and reports: 12-001-X198600214448Description:
The seasonal adjustment of a time series is not a straightforward procedure particularly when the level of a series nearly doubles in just one year. The 1981-82 recession had a very sudden great impact not only on the structure of the series but on the estimation of the trend- cycle and seasonal components at the end of the series. Serious seasonal adjustment problems can occur. For instance: the selection of the wrong decomposition model may produce underadjustment in the seasonally high months and overadjustment in the seasonally low months. The wrong decomposition model may also signal a false turning point. This article analyses these two aspects of the interplay between a severe recession and seasonal adjustment.
Release date: 1986-12-15 - Articles and reports: 12-001-X198500214375Description:
This paper analyzes the revisions of eight seasonally adjusted labour force series during recession and non-recession periods. The four seasonal adjustment methods applied are X-11 and X-11-ARIMA using either concurrent or forecast seasonal factors. The series are seasonally adjusted with these four methodologies according to both a multiplicative and an additive decomposition model. The results indicate that the X-11-ARIMA concurrent adjustment yields the smallest revisions both during recession and non-recession periods regardless of the decomposition model used.
Release date: 1985-12-16 - 45. Relational patterns between total unemployment and unemployment insurance beneficiaries in Canada ArchivedArticles and reports: 12-001-X198500214376Description:
This study purports to assess whether there are temporal relationships between Unemployment Insurance Beneficiaries, Total Unemployment, Job Losers and Job Leavers in Canada using univariate and multivariate time series methods. The results indicate that during 1975-82 the Unemployment Insurance Beneficiaries series leads: (1) Total Unemployment by one month and (2) Job Leavers by two months. On the other hand, there are evidence of a feedback relationship between Unemployment Insurance Beneficiaries and Job Losers.
Release date: 1985-12-16 - 46. Performance of ARIMA models in time series ArchivedArticles and reports: 12-001-X198500114366Description:
This study is mainly concerned with an evaluation of the forecasting performance of a set of the most often applied ARIMA models. These models were fitted to a sample of two hundred seasonal time series chosen from eleven sectors of the Canadian economy. The performance of the models was judged according to eight variable criteria, namely: average forecast error for the last three years, the chi-square statistic for the randomness of the residuals, the presence of small parameters, overdifferencing, underdifferencing, correlation between the parameters, stationarity and invertibility. Overall and conditional rankings of the models are obtained and graphs are presented.
Release date: 1985-06-14 - 47. Estimating economic cycles in semi-annual series ArchivedArticles and reports: 12-001-X198400214355Description:
This paper presents a moving average which estimates the trend-cycle while eliminating seasonality from semi-annual series (observed twice yearly). The proposed average retains the power of all cycles which last three years or more; 90% of those of two years; and 55% of cycles of one year and a half. By comparison, the two by two moving average retains the power of respectively 75%, 50% and 25% of the same cycles.
Release date: 1984-12-14 - 48. Adjusting sub-annual series to yearly benchmarks ArchivedArticles and reports: 12-001-X198400114348Description:
This paper proposes a modification to the method of Denton (1971) for adjusting sub-annual series to yearly totals. These totals originate from more reliable sources and constitute annual benchmarks. The benchmarked series derived according to the modified method is more parallel to the unbenchmarked series than this is the case with the original method. An additive and a proportional variant of the method are presented. These can easily be adapted for flow, stock and index series. Also presented are a few recommendations about the preliminary benchmarking of current data and the management of “historical” estimates of the series.
Release date: 1984-06-15 - 49. Implications of population change ArchivedArticles and reports: 12-001-X198000254941Description:
This paper examines the effects of fertility, mortality and migration on the age profile of the Canadian population, particularly the effect of fluctuating fertility patterns which have occurred since the second World War. The author analyses the impact on social services and the economy as the shifting requirements of the “Baby Boom” cohorts move through their life cycle.
Release date: 1980-12-15
Reference (8)
Reference (8) ((8 results))
- Surveys and statistical programs – Documentation: 19-20-00012026002Description: This reference document provides answers on selected topics related to the use, interpretation, and calculation of trend-cycle estimates for seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment and trend-cycle estimation found in Statistics Canada publications and reference manuals.Release date: 2026-06-08
- Surveys and statistical programs – Documentation: 19-20-00012026001Description: This reference document provides nontechnical answers on selected topics related to the use and interpretation of seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment found in Statistics Canada publications and reference manuals.Release date: 2026-05-11
- Surveys and statistical programs – Documentation: 11-522-X19990015648Description:
We estimate the parameters of a stochastic model for labour force careers involving distributions of correlated durations employed, unemployed (with and without job search) and not in the labour force. If the model is to account for sub-annual labour force patterns as well as advancement towards retirement, then no single data source is adequate to inform it. However, it is possible to build up an approximation from a number of different sources.
Release date: 2000-03-02 - 4. Particulate matter and daily mortality: Combining time series information from eight U.S. cities ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015656Description:
Time series studies have shown associations between air pollution concentrations and morbidity and mortality. These studies have largely been conducted within single cities, and with varying methods. Critics of these studies have questioned the validity of the data sets used and the statistical techniques applied to them; the critics have noted inconsistencies in findings among studies and even in independent re-analyses of data from the same city. In this paper we review some of the statistical methods used to analyze a subset of a national data base of air pollution, mortality and weather assembled during the National Morbidity and Mortality Air Pollution Study (NMMAPS).
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19990015688Description:
The geographical and temporal relationship between outdoor air pollution and asthma was examined by linking together data from multiple sources. These included the administrative records of 59 general practices widely dispersed across England and Wales for half a million patients and all their consultations for asthma, supplemented by a socio-economic interview survey. Postcode enabled linkage with: (i) computed local road density; (ii) emission estimates of sulphur dioxide and nitrogen dioxides, (iii) measured/interpolated concentration of black smoke, sulphur dioxide, nitrogen dioxide and other pollutants at practice level. Parallel Poisson time series analysis took into account between-practice variations to examine daily correlations in practices close to air quality monitoring stations. Preliminary analyses show small and generally non-significant geographical associations between consultation rates and pollution markers. The methodological issues relevant to combining such data, and the interpretation of these results will be discussed.
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19980015031Description:
The U.S. Third National Health and Nutrition Examination Survey (NHANES III) was carried out from 1988 to 1994. This survey was intended primarily to provide estimates of cross-sectional parameters believed to be approximately constant over the six-year data collection period. However, for some variable (e.g., serum lead, body mass index and smoking behavior), substantive considerations suggest the possible presence of nontrivial changes in level between 1988 and 1994. For these variables, NHANES III is potentially a valuable source of time-change information, compared to other studies involving more restricted populations and samples. Exploration of possible change over time is complicated by two issues. First, there was of practical concern because some variables displayed substantial regional differences in level. This was of practical concern because some variables displayed substantial regional differences in level. Second, nontrivial changes in level over time can lead to nontrivial biases in some customary NHANES III variance estimators. This paper considers these two problems and discusses some related implications for statistical policy.
Release date: 1999-10-22 - 7. Probability of victimization over time: Results from the U.S. National Crime Victimization Survey ArchivedSurveys and statistical programs – Documentation: 11-522-X19980015033Description:
Victimizations are not randomly scattered through the population, but tend to be concentrated in relatively few victims. Data from the U.S. National Crime Victimization Survey (NCVS), a multistage rotating panel survey, are employed to estimate the conditional probabilities of being a crime victim at time t given the victimization status in earlier interviews. Models are presented and fit to allow use of partial information from households that move in or out of the housing unit during the study period. The estimated probability of being a crime victim at interview t given the status at interview (t-l) is found to decrease with t. Possible implications for estimating cross-sectional victimization rates are discusssed.
Release date: 1999-10-22 - Notices and consultations: 62-010-X19970023422Description:
The current official time base of the Consumer Price Index (CPI) is 1986=100. This time base was first used when the CPI for June 1990 was released. Statistics Canada is about to convert all price index series to the time base 1992=100. As a result, all constant dollar series will be converted to 1992 dollars. The CPI will shift to the new time base when the CPI for January 1998 is released on February 27th, 1998.
Release date: 1997-11-17