A Predictive Likelihood Approach to Bayesian Averaging

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

A Predictive Likelihood Approach to Bayesian Averaging

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

A Predictive Likelihood Approach to Bayesian Averaging

Popis výsledku anglicky

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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AH - Ekonomie

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Acta Univ Agric Silvic Mendel Brun

ISSN

1211-8516

e-ISSN

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Svazek periodika

63

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

1269-1276

Kód UT WoS článku

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EID výsledku v databázi Scopus

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