Abstract
This paper presents an extension of the Stock and Watson coincident indicator model that allows one to include variables available at different frequencies while taking care of missing observations at any time period. The proposed procedure provides estimates of the unobserved common coincident component, of the unobserved monthly series underlying any included quarterly indicator, and of any missing values in the series. An application to a coincident indicator model for the Portuguese economy is presented. We use monthly indicators from business surveys whose results are published with a very short delay. By using the available data for the monthly indicators and for quarterly real GDP, it becomes possible to produce simultaneously a monthly composite index of coincident indicators and an estimate of the latest quarter real GDP growth well ahead of the release of the first official figures.
Original language | English |
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Pages (from-to) | 575-592 |
Number of pages | 18 |
Journal | Journal Of Forecasting |
Volume | 24 |
Issue number | 8 |
DOIs | |
Publication status | Published - Dec 2005 |
Keywords
- Coincident indicators
- Kalman filter
- State-space models
- Temporal disaggregation