A statistical approach for disaggregating mixed-frequency economic time series data / by Wai-Sum Chan and Zhao-Guo Chen. : CS11-617/97-4E-PDF
"The problem of mixed-frequency time series data arises from changing the observation frequency. For example, we may have a time series with quarterly observations in the first portion and annual figures in the remainder. We shall call that quarter-year mixed-frequency data. In this paper we suggest a method to disaggregate the annual observations to quarterly values. The proposed method can easily be generalised to the year-quarter, quarter-month, year-month and other mixed-frequency situations; it may avoid difficulties of time series modelling and is easy to implement. A step-by-step algorithm of the method is given so that econometricians not expert in this area can still perform the procedure. The proposed method is illustrated through two real examples. We also conduct a small scale Monte Carlo experiment to compare the proposed procedure with two existing alternative methods. Finally, some concluding remarks are given"--Abstract.
Lien permanent pour cette publication :
publications.gc.ca/pub?id=9.840623&sl=1
| Ministère/Organisme | Canada. Statistics Canada. Methodology Branch. |
|---|---|
| Titre | A statistical approach for disaggregating mixed-frequency economic time series data / by Wai-Sum Chan and Zhao-Guo Chen. |
| Titre de la série | Working paper ; 97-4 |
| Type de publication | Série - Voir l'enregistrement principal |
| Langue | [Anglais] |
| Format | Électronique |
| Document électronique | |
| Note(s) | Digitized edition from print [produced by Statistics Canada]. "Working Paper No. BSMD-97-004E." "July, 1997." Includes bibliographic references. Abstract also in French. |
| Information sur la publication | Ottawa : Statistics Canada, 1997. |
| Auteur / Contributeur | Chan, Wai-Sum. Chen, Zhao-Guo,1943- |
| Description | 14, [5] p. : figures. |
| Numéro de catalogue |
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| Numéro de catalogue du ministère | 11-617 no. 97-04E |
| Descripteurs | Methodology Statistical analysis |
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