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Conditional density forecasting: A tempered importance sampling approach

Montes-Galdón, Carlos; Paredes, Joan; Wolf, Elias - 2022

variables in the model, rather than just on future paths as it is usually done in the conditional forecasting literature. The … forecasting densities of a BVAR and a DSGE model on information about the marginal densities of future oil prices. The results …-inflation over the considered forecasting horizon. Finally, a real-time forecasting exercise yields that introducing market …

Persistent link: https://www.econbiz.de/10014374354

Nowcasting made easier: A toolbox for economists

Linzenich, Jan; Meunier, Baptiste - 2024

We provide a versatile nowcasting toolbox that supports three model classes (dynamic factor models, large Bayesian VAR, bridge equations) and offers methods to manage data selection and adjust for Covid-19 observations. The toolbox aims at simplifying two key tasks: creating new nowcasting...

Persistent link: https://www.econbiz.de/10015199442

On the fit and forecasting performance of New-Keynesian models

Del Negro, Marco; Schorfheide, Frank; Smets, Frank; … - 2005

The paper provides new tools for the evaluation of DSGE models, and applies it to a large-scale New Keynesian dynamic stochastic general equilibrium (DSGE) model with price and wage stickiness and capital accumulation. Specifically, we approximate the DSGE model by a vector autoregression (VAR),...

Persistent link: https://www.econbiz.de/10011604537

Measuring inflation persistence: a structural time series approach

Dossche, Maarten; Everaert, Gerdie - 2005

Time series estimates of inflation persistence incur an upward bias if shifts in the inflation target of the central bank remain unaccounted for. Using a structural time series approach we measure different sorts of inflation persistence allowing for an unobserved time-varying inflation target....

Persistent link: https://www.econbiz.de/10011604541

Bayesian Prior Elicitation in DSGE Models : Macro- vs. Micro-Priors

Lombardi, Marco; Nicoletti, Giulio - 2021

Bayesian approaches to the estimation of DSGE models are becoming increasingly popular. Prior knowledge is normally formalized either be information concerning deep parameters’ values (‘microprior’) or some macroeconomic indicator, e.g. moments of observable variables (‘macroprior’)....

Persistent link: https://www.econbiz.de/10013316112

Forecasting daily electricity prices with monthly macroeconomic variables

Foroni, Claudia; Ravazzolo, Francesco; Rossini, Luca - 2019

forecasting daily electricity prices in two of the main European markets, Germany and Italy. We do that by means of mixed …-frequency models, introducing a Bayesian approach to reverse unrestricted MIDAS models (RU-MIDAS). We study the forecasting accuracy …

Persistent link: https://www.econbiz.de/10012142094

Hierarchical Markov normal mixture models with applications to financial asset returns

Geweke, John; Amisano, Gianni - 2007

With the aim of constructing predictive distributions for daily returns, we introduce a new Markov normal mixture model in which the components are themselves normal mixtures. We derive the restrictions on the autocovariances and linear representation of integer powers of the time series in...

Persistent link: https://www.econbiz.de/10011604877