Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Medium-term conditional forecasting of euro-area macroeconomic variables with DSGE and BVARX models L. Burlon, S. Emiliozzi, A. Notarpietro, M. Pisani Bank of Italy Abstract The paper assesses the performance of medium-term forecasts of euro-area GDP and inflation obtained with a DSGE model and a BVARX model currently in use at the Bank of Italy. The performance is compared with that of simple univariate models and with the Eurosystem projections; the same real time assumptions underlying the latter are used to condition the DSGE and the BVARX forecasts. We find that the performance of both forecasts is similar to that of Eurosystem forecasts and overall more accurate than that of simple autoregressive models. The DSGE model shows a relatively better performance in forecasting inflation, while the BVARX model fares better in forecasting GDP. What do we do? Annual RMSFE • We focus on quarterly forecasts of euro-area GDP and inflation for each quarter from 2002Q3 to 2014Q1 obtained with a DSGE and a BVARX over the same 3 full-years horizon adopted in Eurosystem projections. • The DSGE and BVARX forecasts are conditional to the (main) assumptions underlying Eurosystem projections • Their predictive performance is compared with the Eurosystem projections and those of simple univariate models GDP GDP Inflation Inflation 1 yr ahead 2 yrs ahead 1 yr ahead 2 yrs ahead Eurosystem 0.4982 1.9763 0.2716 0.9012 AR(4) 0.4925 2.2831 0.2303 1.0848 0.2373 0.8235 DSGE anticipated 0.4769 2.0080 DSGE unanticipated 0.5052 1.9185 0.2200 0.7555 BVAR 0.4824 1.8367 0.2398 0.9828 BVARX 0.4915 1.8967 0.2577 1.0041 RMSFE Main results GDP 1 0.8 • The forecasting performance of both models, using the RMSFE metric, is comparable to the historical performance of the Eurosystem projections • The DSGE-based forecasts are relatively more accurate for inflation • The BVARX fares relatively better in forecasting GDP 0.6 0.4 0.2 1 2 3 4 5 6 7 8 Consumption deflator 0.5 0.4 0.3 DSGE model 0.2 • Two-country New Keynesian model estimated with euro-area and rest-of-the-world data with nominal and real rigidities • Estimated recursively from 1995Q1 to 2013Q4 • 12 euro-area and 2 rest-of-the-world observables used in the estimation 0.1 1 AR(4) 2 3 DSGE anticipated 4 5 6 DSGE unanticipated 7 BVAR 8 BVARX Historical errors GDP (4 quarters ahead) – EA: GDP, private and public consumption, investment, exports, imports, total employment, nominal compensation for employee, the consumption and investment deflators and energy and non-energy components of the HICP. – RoTW: US 3-month interest rate and World GDP deflator Consumption deflator (4 quarters ahead) 2 1 1 0.5 0 0 −1 −0.5 −2 −1 −3 −1.5 −4 2002:3 2004:3 2006:3 2008:3 2010:3 2012:3 • In the DSGE, the conditioning over Eurosystem projections’ assumptions differs according to the economic agent’ information set ( anticipated vs unanticipated conditional forecasts ) −2 2002:3 2004:3 2006:3 2008:3 2010:3 2012:3 GDP (8 quarters ahead) Consumption deflator (8 quarters ahead) 2 1 1 0.5 0 0 −1 BVARX model −0.5 −2 −1 −3 −4 2002:3 2004:3 2006:3 2008:3 2010:3 2012:3 • The BVARX model contains: – 6 endogenous variables for the euro area: GDP, imports, exports, pri- AR(4) vate consumption deflator, unit labor cost, EA long-run interest rate – 5 exogenous variables coming from the Eurosystem projections assuptions • Estimated recursively from 1985Q1 to 2013Q4 • A Litterman prior is used over the block of endogenous variables • Priors for the coefficients on exogenous variables are centered on the elasticities of the Eurosystem models DSGE anticipated DSGE unanticipated Forecast Bias 0.2 • The inflation rate is sistematically underestimated by both models 0 −0.2 2 3 4 5 6 7 8 Consumption deflator 0.2 0 −0.1 −0.2 1 AR(4) BVARX • The DSGE unanticipated conditional projections tend to be more accurate 0.1 • Conditioning set: Euribor 3 month interest rate, euro-area foreign demand, euro NEER vis-à-vis 20 countries and Brent oil price (in US dollars) • We control for high-frequency information coming from surveys and nowcasts: one step-ahead forecasts are constrained to be equal to the Eurosystem projection. BVAR Some final remarks GDP 0.4 −0.4 1 Setup of forecast exercise −1.5 2002:3 2004:3 2006:3 2008:3 2010:3 2012:3 2 3 DSGE anticipated 4 5 6 DSGE unanticipated 7 BVAR 8 BVARX • Both models fail to predict 2008Q4 fall in GDP • DSGE forecasts show a smaller bias than the BVARX in forecasting the 2008Q4 inflation rate • Future developments – Forecasts pooling – Density forecasts