Arbeitspapier
Forecasting using Bayesian VARs: A Benchmark for STREAM
This study develops a suite of Bayesian Vector Autoregression (BVAR) models for the Maltese economy to benchmark the forecasting performance of STREAM, the traditional macro-econometric model used by the Central Bank of Malta for its regular forecasting exercises. Three different BVARs are proposed, containing an endogenous and exogenous block, and differ only in terms of the crosssectional size of the former. The small BVAR contains only three endogenous variables, the medium BVAR includes 17 variables, while the large BVAR includes 32 endogenous variables. The exogenous block remains consistent across the three models. By using a similar information set, the Bayesian VARs developed in this study are utilised to benchmark the forecast performance of STREAM. In general, for real GDP, the GDP deflator, and the unemployment rate, BVAR median projections for the period 2014-2016 improve the forecast performance at the one, two, and four-step ahead horizons when compared to STREAM. However, the latter does rather well at annual projections, but it is broadly outperformed by the medium and large BVARs.
- Sprache
-
Englisch
- Erschienen in
-
Series: CBM Working Papers ; No. WP/04/2018
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Model Evaluation, Validation, and Selection
Forecasting Models; Simulation Methods
Large Data Sets: Modeling and Analysis
General Aggregative Models: Forecasting and Simulation: Models and Applications
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Borg, Ian
Ruisi, Germano
- Ereignis
-
Veröffentlichung
- (wer)
-
Central Bank of Malta
- (wo)
-
Valletta
- (wann)
-
2018
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Borg, Ian
- Ruisi, Germano
- Central Bank of Malta
Entstanden
- 2018
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