Abstract
Statistics Canada’s official policy of using concurrent seasonal adjustment was established in 1975; gradually, other foreign statistical agencies followed it. The old practice for seasonally adjusting a current (monthly or quarterly) observation was to apply year-ahead seasonal factors generated from a series that ended in the month of December of the previous year. Since these projected factors were calculated ahead of the actual time they were applied, they didn’t take into account the most recent information incorporated into the series. On the other hand, the use of a concurrent seasonal factor to produce a current seasonally adjusted datum implies the use of all the data in the series up to and including the current month’s observation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Box, G. E. P., and G. M. Jenkins (1970), Time Series Analysis, Forecasting and Control. San Francisco: Holden-Day.
Bayer, A., and D. Wilcox (1981), “An evaluation of concurrent seasonal adjustment”. Technical Report, Washington, D. C. Board of Governors of the Federal Reserve System, Special Studies Section.
Burridge, P., and K. F. Wallis (1984), “Unobserved-components models for seasonal adjustment filters”. Journal of Business and Economic Statistics 2, 350–359.
Dagum, E. B. (1978), Comparison and Assessment of Seasonal Adjustment Methods for Labor Force Series. Washington, D. C: U. S. Government Printing Office, Stock No. 052–003–00603–1.
Dagum, E. B. (1980), The X-11-ARIMA Seasonal Adjustment Method. Ottawa: Statistics Canada Catalogue No. 12–564E.
Dagum, E. B. (1982a), “The effects of asymmetric filters on seasonal factor revisions”. Journal of the American Statistical Association 77, 732–738.
Dagum, E. B. (1982b), “Revisions of seasonally adjusted data due to filter changes”. Proceedings of the Business and Economic Statistics Section, American Statistical Association, pp. 39–45.
Dagum, E. B. (1983), “Spectral properties of the concurrent and forecasting linear filters of the X-11-ARIMA method”. Canadian Journal of Statistics 2, 73–90.
Dagum, E. B., and M. Morry (1984), “Basic issues on the seasonal adjustment of the Canadian consumer price index”. Journal of Business and Economic Statistics 2, 250–259.
Kenny, P., and J. Durbin (1982), “Local trend estimation and seasonal adjustment of economic time series”. Journal of the Royal Statistical Society, Series A 145, 1–41.
McKenzie, S. (1982), “An evaluation of concurrent adjustment on Census Bureau time series”. Proceedings of the Business and Economic Statistics Section, American Statistical Association, pp. 46–55.
McKenzie, S. (1984), “Concurrent seasonal adjustment with Census X-11”. Journal of Business and Economic Statistics 2, 235–249.
Pierce, D., and S. McKenzie (1985), “On concurrent seasonal adjustment”. Special Studies No. 164, U. S. Federal Reserve Board.
Shiskin, J., A. H. Young, and J. C. Musgrave (1967), “The X-11 variant of census method II seasonal adjustment program”. Technical Paper 15, Washington, D. C.: U. S. Bureau of Census.
Wallis, K. F. (1974), “Seasonal adjustment and relations between variables”. Journal of the American Statistical Association 69, 18–31.
Young, A. H. (1968), “Linear approximations to the census and BLS seasonal adjustment methods”. Journal of the American Statistical Association 63, 445–457.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1987 D. Reidel Publishing Company
About this chapter
Cite this chapter
Dagum, E.B. (1987). Monthly versus Annual Revisions of Concurrent Seasonally Adjusted Series. In: MacNeill, I.B., Umphrey, G.J., Carter, R.A.L., McLeod, A.I., Ullah, A. (eds) Time Series and Econometric Modelling. The University of Western Ontario Series in Philosophy of Science, vol 36. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-4790-0_11
Download citation
DOI: https://doi.org/10.1007/978-94-009-4790-0_11
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-8624-0
Online ISBN: 978-94-009-4790-0
eBook Packages: Springer Book Archive