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DSGE model-based forecasting

Marco Del Negro () and Frank Schorfheide ()

No 554, Staff Reports from Federal Reserve Bank of New York

Abstract: Dynamic stochastic general equilibrium (DSGE) models use modern macroeconomic theory to explain and predict comovements of aggregate time series over the business cycle and to perform policy analysis. We explain how to use DSGE models for all three purposes—forecasting, story telling, and policy experiments—and review their forecasting record. We also provide our own real-time assessment of the forecasting performance of the Smets and Wouters (2007) model data up to 2011, compare it with Blue Chip and Greenbook forecasts, and show how it changes as we augment the standard set of observables with external information from surveys (nowcasts, interest rate forecasts, and expectations for long-run inflation and output growth). We explore methods of generating forecasts in the presence of a zero-lower-bound constraint on nominal interest rates and conditional on counterfactual interest rate paths. Finally, we perform a postmortem of DSGE model forecasts of the Great Recession and show that forecasts from a version of the Smets-Wouters model augmented by financial frictions, and using spreads as an observable, compare well with Blue Chip forecasts.

Keywords: Stochastic analysis; Equilibrium (Economics); Time-series analysis; Econometric models; Monetary policy; Economic forecasting; Recessions (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dge, nep-ets, nep-for and nep-mac
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (43) Track citations by RSS feed

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Chapter: DSGE Model-Based Forecasting (2013) Downloads
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