Forecasting performance of multivariate time series models with full and reduced rank: an empirical examination

2004 ◽  
Vol 20 (4) ◽  
pp. 683-695 ◽  
Author(s):  
Zijun Wang ◽  
David A. Bessler
2014 ◽  
Vol 529 ◽  
pp. 621-624
Author(s):  
Syang Ke Kung ◽  
Chi Hsiu Wang

This article is devoted to examine the performance of power transformation in VAR and Bayesian VAR (BVAR) forecasts, in comparison with log-transformation. The effect of power transformation in multivariate time series model forecasts is still untouched in the literature. We examined the U.S. macroeconomic data from 1960 to 1987 and the Taiwan’s technology industrial production from 1990 to 2000. Our results showed that the power transformation provides outperforming forecasts in both VAR and BVAR models. Moreover, the non-informative prior BAVR with power transformation is the best predictive model and is recommendable to forecasting practice.


2011 ◽  
Vol 3 (1) ◽  
pp. 71 ◽  
Author(s):  
L. Boshnjaku ◽  
B. Ben-Kaabia ◽  
José M. Gil

The analysis of price relationships in commodity markets provides an approximate idea on markets performance as well as allows the researcher to analyze price responses to unanticipated shocks. The objective of this paper is to explore price relationships in geographical separated markets in the Spanish lamb sector. The methodology used is based on the specification of multivariate time series models which are flexible enough to take into account the stochastic properties of data, the multivariate nature of price relationships and to distinguish between short- and long-run horizons. Results indicate that lamb markets in Spain are strongly related being Zafra the leading market. The influence of Zafra is substantial in the southern markets while in the North, the Lonja del Ebro could be considered as the most representative market.


Author(s):  
Klaus Ackermann ◽  
Uta Streit ◽  
Hansjörg Ebell ◽  
Arno Steitz ◽  
Ilse M. Zalaman ◽  
...  

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