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All (13) (0 to 10 of 13 results)
- 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
- 2. 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 - 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 - 5. A nonparametric test for residual seasonality ArchivedArticles and reports: 12-001-X200900110885Description:
Peaks in the spectrum of a stationary process are indicative of the presence of stochastic periodic phenomena, such as a stochastic seasonal effect. This work proposes to measure and test for the presence of such spectral peaks via assessing their aggregate slope and convexity. Our method is developed nonparametrically, and thus may be useful during a preliminary analysis of a series. The technique is also useful for detecting the presence of residual seasonality in seasonally adjusted data. The diagnostic is investigated through simulation and an extensive case study using data from the U.S. Census Bureau and the Organization for Economic Co-operation and Development (OECD).
Release date: 2009-06-22 - 6. Estimating TFP in the Presence of Outliers and Leverage Points: An Examination of the KLEMS Dataset ArchivedArticles and reports: 11F0027M2007047Geography: CanadaDescription:
This paper examines the effect of aberrant observations in the Capital, Labour, Energy, Materials and Services (KLEMS) database and a method for dealing with them. The level of disaggregation, data construction and economic shocks all potentially lead to aberrant observations that can influence estimates and inference if care is not exercised. Commonly applied pre-tests, such as the augmented Dickey-Fuller and the Kwaitkowski, Phillips, Schmidt and Shin tests, need to be used with caution in this environment because they are sensitive to unusual data points. Moreover, widely known methods for generating statistical estimates, such as Ordinary Least Squares, may not work well when confronted with aberrant observations. To address this, a robust method for estimating statistical relationships is illustrated.
Release date: 2007-12-05 - 7. 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 - Articles and reports: 11-522-X20030017707Description:
The paper discusses the structure and the quality measures Eurostat uses to provide European Union and EU-Zone with economic seasonally adjusted series.
Release date: 2005-01-26 - Articles and reports: 12-001-X20000025536Description:
Many economic and social time series are based on sample surveys which have complex sample designs. The sample design affects the properties of the time series. In particular, the overlap of the sample from period to period affects the variability of the time series of survey estimates and the seasonally adjusted and trend estimates produced from them.
Release date: 2001-02-28 - 10. Issues and strategies for small area data ArchivedArticles and reports: 12-001-X199400114436Description:
This paper identifies some technical issues in the provision of small area data derived from censuses, administrative records and surveys. Although the issues are of a general nature, they are discussed in the context of programs at Statistics Canada. For survey-based estimates, the need for developing an overall strategy is stressed and salient features of survey design that have an impact on small area data are highlighted in the context of redesigning a household survey. A brief review of estimation methods with their strengths and weaknesses is also presented.
Release date: 1994-06-15
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- 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
- 2. 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 - 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 - 5. A nonparametric test for residual seasonality ArchivedArticles and reports: 12-001-X200900110885Description:
Peaks in the spectrum of a stationary process are indicative of the presence of stochastic periodic phenomena, such as a stochastic seasonal effect. This work proposes to measure and test for the presence of such spectral peaks via assessing their aggregate slope and convexity. Our method is developed nonparametrically, and thus may be useful during a preliminary analysis of a series. The technique is also useful for detecting the presence of residual seasonality in seasonally adjusted data. The diagnostic is investigated through simulation and an extensive case study using data from the U.S. Census Bureau and the Organization for Economic Co-operation and Development (OECD).
Release date: 2009-06-22 - 6. Estimating TFP in the Presence of Outliers and Leverage Points: An Examination of the KLEMS Dataset ArchivedArticles and reports: 11F0027M2007047Geography: CanadaDescription:
This paper examines the effect of aberrant observations in the Capital, Labour, Energy, Materials and Services (KLEMS) database and a method for dealing with them. The level of disaggregation, data construction and economic shocks all potentially lead to aberrant observations that can influence estimates and inference if care is not exercised. Commonly applied pre-tests, such as the augmented Dickey-Fuller and the Kwaitkowski, Phillips, Schmidt and Shin tests, need to be used with caution in this environment because they are sensitive to unusual data points. Moreover, widely known methods for generating statistical estimates, such as Ordinary Least Squares, may not work well when confronted with aberrant observations. To address this, a robust method for estimating statistical relationships is illustrated.
Release date: 2007-12-05 - 7. 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 - Articles and reports: 11-522-X20030017707Description:
The paper discusses the structure and the quality measures Eurostat uses to provide European Union and EU-Zone with economic seasonally adjusted series.
Release date: 2005-01-26 - Articles and reports: 12-001-X20000025536Description:
Many economic and social time series are based on sample surveys which have complex sample designs. The sample design affects the properties of the time series. In particular, the overlap of the sample from period to period affects the variability of the time series of survey estimates and the seasonally adjusted and trend estimates produced from them.
Release date: 2001-02-28 - 10. Issues and strategies for small area data ArchivedArticles and reports: 12-001-X199400114436Description:
This paper identifies some technical issues in the provision of small area data derived from censuses, administrative records and surveys. Although the issues are of a general nature, they are discussed in the context of programs at Statistics Canada. For survey-based estimates, the need for developing an overall strategy is stressed and salient features of survey design that have an impact on small area data are highlighted in the context of redesigning a household survey. A brief review of estimation methods with their strengths and weaknesses is also presented.
Release date: 1994-06-15
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