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- Articles and reports: 11-522-X20030017695Description:
This paper proposes methods to correct a seasonally adjusted series so that its annual totals match those of the raw series. The methods are illustrated with a seasonally adjusted series obtained with either X-11-ARIMA or X-12-ARIMA.
Release date: 2005-01-26 - 2. 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 - 3. 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 - 4. 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
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Articles and reports (4)
Articles and reports (4) ((4 results))
- Articles and reports: 11-522-X20030017695Description:
This paper proposes methods to correct a seasonally adjusted series so that its annual totals match those of the raw series. The methods are illustrated with a seasonally adjusted series obtained with either X-11-ARIMA or X-12-ARIMA.
Release date: 2005-01-26 - 2. 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 - 3. 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 - 4. 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
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