Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/105299
Authors: 
Simionescu, Mihaela
Year of Publication: 
2014
Citation: 
[Journal:] UTMS Journal of Economics [ISSN:] 1857-6982 [Volume:] 5 [Year:] 2014 [Issue:] 2 [Pages:] 131-140
Abstract: 
There are many types of econometric models used in predicting the inflation rate, but in this study we used a Bayesian shrinkage combination approach. This methodology is used in order to improve the predictions accuracy by including information that is not captured by the econometric models. Therefore, experts' forecasts are utilized as prior information, for Romania these predictions being provided by Institute for Economic Forecasting (Dobrescu macromodel), National Commission for Prognosis and European Commission. The empirical results for Romanian inflation show the superiority of a fixed effects model compared to other types of econometric models like VAR, Bayesian VAR, simultaneous equations model, dynamic model, log-linear model. The Bayesian combinations that used experts' predictions as priors, when the shrinkage parameter tends to infinite, improved the accuracy of all forecasts based on individual models, outperforming also zero and equal weights predictions and naïve forecasts.
Subjects: 
Bayesian forecasts combination
forecasts accuracy
prior
shrinkage parameter
econometric model.
JEL: 
E37
C51
C52
C53
Document Type: 
Article
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