A Predictive Likelihood Approach to Bayesian Averaging

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F04274644%3A_____%2F15%3A%230000041" target="_blank" >RIV/04274644:_____/15:#0000041 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.11118/actaun201563041269" target="_blank" >http://dx.doi.org/10.11118/actaun201563041269</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.11118/actaun201563041269" target="_blank" >10.11118/actaun201563041269</a>

Result language
angličtina
Original language name
A Predictive Likelihood Approach to Bayesian Averaging
Original language description
Multivariate time series forecasting is applied in a wide range of economic activities related to regional competitiveness and is the basis of almost all macroeconomic analysis. In this paper we combine multivariate density forecasts of GDP growth, inflation and real interest rates from four various models, two type of Bayesian vector autoregression (BVAR) models, a New Keynesian dynamic stochastic general equilibrium (DSGE) model of small open economy and DSGE-VAR model. The performance of models is identified using historical dates including domestic economy and foreign economy, which is represented by countries of the Eurozone. Because forecast accuracy of observed models are different, the weighting scheme based on the predictive likelihood, the trace of past MSE matrix, model ranks are used to combine the models. The equal-weight scheme is used as a simple combination scheme. The results show that optimally combined densities are comparable to the best individual models.
Czech name
—
Czech description
—

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AH - Economics
OECD FORD branch
—

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)