04154nam 2200673Ia 450 991046368790332120200504041405.01-4623-2750-81-282-84441-597866128444161-4518-7388-31-4527-8840-5(CKB)3170000000055371(EBL)1605949(SSID)ssj0000939930(PQKBManifestationID)11596385(PQKBTitleCode)TC0000939930(PQKBWorkID)10939159(PQKB)11177470(OCoLC)680613569(MiAaPQ)EBC1605949(EXLCZ)99317000000005537120100408d2009 uf 0engur|n|---|||||txtccrThe role of financial variables in predicting economic activity in the Euro area[electronic resource] /prepared by Raphael Espinoza, Fabio Fornari and Marco Lombardi[Washington, D.C.] International Monetary Fund, Middle East and Central Asia Dept.20091 online resource (56 p.)IMF working paper ;09/241"November 2009."1-4519-1805-4 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 GDP1. 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 Test10. 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; FootnotesThe 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 usinIMF working paper ;WP/09/241.Business cyclesEuropeBusiness cyclesUnited StatesEconomic indicatorsEuropeEconomic indicatorsUnited StatesElectronic books.Business cyclesBusiness cyclesEconomic indicatorsEconomic indicatorsEspinoza Raphael A873063Fornari Fabio928678Lombardi Marco J.1976-35223International Monetary Fund.Middle East and Central Asia Dept.MiAaPQMiAaPQMiAaPQBOOK9910463687903321The role of financial variables in predicting economic activity in the Euro area2087089UNINA