The Role of Financial Variables in Predicting Economic Activity in the Euro Area

The U.S. business cycle typically leads the European cycle by a few quarters and this can be used to forecast euro area GDP. We investigate whether financial variables carry additional information. We use vector autoregressions (VARs) which include the U.S. and the euro area GDPs as a minimal set of variables as well as growth in the Rest of the World (an aggregation of seven small countries) and selected combinations of financial variables. Impulse responses (in-sample) show that shocks to financial variables influence real activity. However, according to out-of-sample forecast exercises usin

MoreLess

Year of publication:	2009
Authors:	Lombardi, Marco
Other Persons:	Espinoza, Raphael A. (contributor) ; Fornari, Fabio (contributor)
Publisher:	Washington : International Monetary Fund
Subject:	Eurozone \| Euro area \| EU-Staaten \| EU countries \| Wirtschaftsindikator \| Economic indicator

Online Resource

Check full text access |

More access options

Check Google Scholar

In libraries world-wide (WorldCat)

In German libraries (KVK)

subito order

I need help

Extent:	Online-Ressource (56 p)
Series:	IMF Working Papers ; v.Working Paper No. 09/241 IMF working paper ; 09/241
Type of publication:	Book / Working Paper
Language:	English
Notes:	Description based upon print version of record Cover Page; Title Page; Copyright Page; Contents; I. Introduction; II. The VAR models; A. Data; 1. Rates of Growth of Real GDP in the Three Economic Areas (quarter-on-quarter); B. Specifications; III. Characterizing the Models; A. IRFs and Pre-1985 and Post-1985 Evidence; 2. Impulse Response Functions from a Trivariate VAR; 3. Impulse Response Function from a 9-Variable VAR; 4. Impulse Response Function to GDP Shocks Across Sub-Samples; 5. Impulse Response Functions Across Sub-Samples; B. Linkages and the Role of Financial Shocks; 6. Forecast Error Variance Decomposition for the Euro Area GDP 1. Variance Decomposition of the GDP in the Three Areas2. R2 of a Regression of Δlog GDP on its Counterfactual; 7. Historical Decomposition; IV. Out-of-Sample Evidence; A. 'Unconditional' Forecast Evaluation; 3. Unconditional Out-of-Sample RMSE; B. Conditional Forecast Evaluation; 4. Out-of-Sample RMSE; 5. Out-of-Sample RMSE; C. Additional Explanatory Factors; 6. Conditional Choice Between Models at Selected Horizons; V. Conditional Evaluation; A. Rolling RMSEs; 8. RMSE from Competing Classes of Models; 9. RMSE from Competing Classes of Models (ctd.); B. Conditional Predictive Ability Test 10. GW Test for Conditional Predictive - Random Walk Model11. GW Test for Conditional Predictive Ability - 2 GDP VAR; 12. GW Test for Conditional Predictive Ability - 3 GDP VAR; VI. Conclusions; References; Footnotes
ISBN:	978-1-4518-7388-7 ; 978-1-4527-8840-1 ; 978-1-4518-7388-7
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012677494