Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are … improve forecasts from an unrestricted VAR. In testing forecasting capacity they also have quite weak power, particularly on … improve on VAR forecasts. …

the rational expectations solution of the structural New Keynesian Phillips curve, NKPC, and the reduced form VAR analysis …

these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …-data models at 5% and 1% VaR level. Specifically, independently from the data frequency, allowing for jumps in price (or providing … fat-tails) and leverage effects translates in more accurate VaR measure. …

Bayesian networks. A TSCM can be seen as a structural VAR identified by the causal relations among the variables. We classify … variables based on their observed time series data. It is shown that while an unconstrained VAR model does not imply any causal …