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This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). We use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to...
Persistent link: https://www.econbiz.de/10012463776
multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly … Bayesian estimation provides strong evidence for a small predictable component in consumption growth (even if asset return data … are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our …
Persistent link: https://www.econbiz.de/10012458363
Recent work has analyzed the forecasting performance of standard dynamic stochastic general equilibrium (DSGE) models, but little attention has been given to DSGE models that incorporate nonlinearities in exogenous driving processes. Against that background, we explore whether incorporating...
Persistent link: https://www.econbiz.de/10012456064
We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call Dynamic Pools, and use it to investigate the relative forecasting performance of DSGE models with and without financial frictions for output growth and inflation from 1992 to 2011. We...
Persistent link: https://www.econbiz.de/10012458090