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Commodity prices co-move, but the strength of this co-movement changes over time due to structural factors, like changing energy intensity in production and consumption as well as changing composition of underlying shocks. This paper explores whether econometric models that exploit this...
Persistent link: https://www.econbiz.de/10014543637
Density forecast combinations are examined in real-time using the log score to compare five methods: fixed weights, static and dynamic prediction pools, as well as Bayesian and dynamic model averaging. Since real-time data involves one vintage per time period and are subject to revisions, the...
Persistent link: https://www.econbiz.de/10012422040
encompasses a general unrestricted model and it forecast encompasses the competitors when tested on 20 quarters of one step ahead …
Persistent link: https://www.econbiz.de/10011604368
The rank of the spectral density matrix conveys relevant information in a variety of statistical modelling scenarios. This note shows how to estimate the rank of the spectral density matrix at any given frequency. The method presented is valid for any hermitian positive de?nite matrix estimate...
Persistent link: https://www.econbiz.de/10011604395
We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets-Wouters model and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a...
Persistent link: https://www.econbiz.de/10011853328
general and can be used to measure the informational importance of observables with respect to latent variables in DSGE models …
Persistent link: https://www.econbiz.de/10011916865
composite leading indicators are carefully selected from around 160 candidate leading series using a general …
Persistent link: https://www.econbiz.de/10011916879
This paper shows how to compute the h-step-ahead predictive likelihood for any subset of the observed variables in parametric discrete time series models estimated with Bayesian methods. The subset of variables may vary across forecast horizons and the problem thereby covers marginal and joint...
Persistent link: https://www.econbiz.de/10011605581
A researcher is interested in a set of variables that he wants to model with a vector auto-regression and he has a dataset with more variables. Which variables from the dataset to include in the VAR, in addition to the variables of interest? This question arises in many applications of VARs, in...
Persistent link: https://www.econbiz.de/10011605645
This paper assesses the forecasting performance of various variable reduction and variable selection methods. A small and a large set of wisely chosen variables are used in forecasting the industrial production growth for four Euro Area economies. The results indicate that the Automatic Leading...
Persistent link: https://www.econbiz.de/10011605818