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VARMA versus VAR for Macroeconomic Forecasting

  • Athanasopoulos, George
  • Vahid, Farshid

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.

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Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 26 (2008)
Issue (Month): (April)
Pages: 237-252

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Handle: RePEc:bes:jnlbes:v:26:y:2008:p:237-252
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  1. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
  2. 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.
  3. 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.
  4. Lutkepohl, Helmut & Poskitt, D S, 1996. "Specification of Echelon-Form VARMA Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 69-79, January.
  5. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
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