Nowcasting Irish GDP:
This paper presents a dynamic factor model that produces nowcasts and backcasts of Irish quarterly GDP using timely data from a panel dataset of 35 indicators. We apply a recently developed methodology, whereby numerous potentially useful indicator series for Irish GDP can be availed of in a parsimo...
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| Other Authors: | , |
| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
Paris
OECD Publishing
2012
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| Subjects: | |
| Online Access: | DE-384 DE-473 DE-824 DE-29 DE-739 DE-355 DE-20 DE-1028 DE-1049 DE-521 DE-861 DE-898 DE-92 DE-91 DE-573 DE-19 Volltext |
| Summary: | This paper presents a dynamic factor model that produces nowcasts and backcasts of Irish quarterly GDP using timely data from a panel dataset of 35 indicators. We apply a recently developed methodology, whereby numerous potentially useful indicator series for Irish GDP can be availed of in a parsimonious manner and the unsynchronised nature of the release calendar for a wide range of higher frequency indicators can be handled. The nowcasts in this paper are generated by using dynamic factor analysis to extract common factors from the panel dataset. Bridge equations are then used to relate these factors to quarterly GDP estimates. We conduct an out-of-sample forecasting simulation exercise, where the results of the nowcasting exercise are compared with those of a standard benchmark model |
| Physical Description: | 1 Online-Ressource (11 Seiten) 21 x 28cm |
| DOI: | 10.1787/jbcma-2012-5k92n2pwccwb |
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| spelling | D'Agostino, Antonello Verfasser aut Nowcasting Irish GDP Antonello D'Agostino, Kieran McQuinn and Derry O'Brien Paris OECD Publishing 2012 1 Online-Ressource (11 Seiten) 21 x 28cm txt rdacontent c rdamedia cr rdacarrier This paper presents a dynamic factor model that produces nowcasts and backcasts of Irish quarterly GDP using timely data from a panel dataset of 35 indicators. We apply a recently developed methodology, whereby numerous potentially useful indicator series for Irish GDP can be availed of in a parsimonious manner and the unsynchronised nature of the release calendar for a wide range of higher frequency indicators can be handled. The nowcasts in this paper are generated by using dynamic factor analysis to extract common factors from the panel dataset. Bridge equations are then used to relate these factors to quarterly GDP estimates. We conduct an out-of-sample forecasting simulation exercise, where the results of the nowcasting exercise are compared with those of a standard benchmark model Economics Ireland McQuinn, Kieran ctb O'Brien, Derry ctb https://doi.org/10.1787/jbcma-2012-5k92n2pwccwb Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | D'Agostino, Antonello Nowcasting Irish GDP Economics Ireland |
| title | Nowcasting Irish GDP |
| title_auth | Nowcasting Irish GDP |
| title_exact_search | Nowcasting Irish GDP |
| title_exact_search_txtP | Nowcasting Irish GDP |
| title_full | Nowcasting Irish GDP Antonello D'Agostino, Kieran McQuinn and Derry O'Brien |
| title_fullStr | Nowcasting Irish GDP Antonello D'Agostino, Kieran McQuinn and Derry O'Brien |
| title_full_unstemmed | Nowcasting Irish GDP Antonello D'Agostino, Kieran McQuinn and Derry O'Brien |
| title_short | Nowcasting Irish GDP |
| title_sort | nowcasting irish gdp |
| topic | Economics Ireland |
| topic_facet | Economics Ireland |
| url | https://doi.org/10.1787/jbcma-2012-5k92n2pwccwb |
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