VARMA versus VAR for Macroeconomic Forecasting
In this paper, we argue that there is no compelling reason for restricting the class of multivariate models considered for macroeconomic forecasting to VARs given the recent advances in VARMA modelling methodology and improvements in computing power. To support this claim, we use real macroeconomic data and show that VARMA models forecast macroeconomic variables more accurately than VAR models.
|Date of creation:||Jan 2006|
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- D.S. Poskitt, "undated".
"Specification of echelon form VARMA models,"
Statistic und Oekonometrie
9305, Humboldt Universitaet Berlin.
- George Athanasopoulos & Farshid Vahid, 2008.
"A complete VARMA modelling methodology based on scalar components,"
Journal of Time Series Analysis,
Wiley Blackwell, vol. 29(3), pages 533-554, 05.
- George Athanasopoulos & Farshid Vahid, 2006. "A Complete VARMA Modelling Methodology Based on Scalar Components," Monash Econometrics and Business Statistics Working Papers 2/06, Monash University, Department of Econometrics and Business Statistics.
- Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
- Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
- Clements, M.P. & Hendry, D., 1992. "On the Limitations of Comparing Mean Square Forecast Errors," Economics Series Working Papers 99138, University of Oxford, Department of Economics.
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