Vector autoregression modelling and forecasting
Article Abstract:
The use of vector autoregressive (VAR) models for forecasting has developed to an advanced degree since it was first introduced by C.S. Sim in 1980. At present, however, controversy continues over Sim's contention that economic theory is not necessary for system identification, a prerequisite in interpreting the effect of random shocks on the system. Meanwhile, Bayesian VAR models have been adopted due to their better performance over the unrestricted VAR.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1995
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Structural, VAR and BVAR models of exchange rate determination: a comparison of their forecasting performance
Article Abstract:
The out-of-sample forecasting accuracy of structural, Bayesian vector autoregressive (BVAR) and VAR characterizations of sterling exchange rates for different time periods was evaluated. The study confirmed the higher accuracy of the BVAR with respect to short-term predictions. Generally, both BVAR and VAR models outperformed the structural models investigated. These were the portfolio balance, modified uncovered interest parity and random walk models.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1995
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Business cycle analysis and forecasting with a structural vector autoregression model for Wales
Article Abstract:
A structural vector autoregression (VAR) model of the Welsh economy was employed to study the economy's response to random shocks brought about by business cycles. Specifically, the model differentiated between international and national shocks as well as their influence on regional economic variables. It use enabled an evaluation of how the Welsh economy's response to external factor differed with other regions of the UK.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1995
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