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VAR Forecasting Models of the Australian Economy: A Preliminary Analysis

Author

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  • Robert G. Trevor

    (Reserve Bank of Australia)

  • Susan J. Thorp

    (Reserve Bank of Australia)

Abstract

Vector autoregressions (VARs) have been proposed as good forecasting models of macroeconomic variables. This paper presents three naive VAR models of the Australian economy estimated on quarterly data for fifteen variables to 1985(4). Their performance in “forecasting” the calendar and financial year outcomes for 1986–87 (on an ex-ante basis) is compared with that of three sets of private sector forecasts, the 1986–87 Budget forecasts and the actual outcomes from the same period. In general, the VAR forecasts perform at least as well or better than comparable private sector forecasts. Each VAR model is estimated using a different method for allowing for trends in the data. The detrending procedure is an important determinant of the quality of forecasts, with the best forecasts produced by the two models which employ detrending processes appropriate for data which follow a random walk.

Suggested Citation

  • Robert G. Trevor & Susan J. Thorp, 1988. "VAR Forecasting Models of the Australian Economy: A Preliminary Analysis," RBA Research Discussion Papers rdp8802, Reserve Bank of Australia.
    • Handle: RePEc:rba:rbardp:rdp8802
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    Cited by:

    1. Ellis W. Tallman & Naveen Chandra, 1996. "The Information Content of Financial Aggregates in Australia," RBA Research Discussion Papers rdp9606, Reserve Bank of Australia.
    2. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Research Discussion Papers 4/1991, Bank of Finland.
    3. Peter M. Summers, 1999. "Macroeconomic Forecasting at the Melbourne Institute," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 32(2), pages 197-205, June.
    4. Starck, Christian, 1991. "Specifying a Bayesian vector autoregression for short-run macroeconomic forecasting with an application to Finland," Bank of Finland Research Discussion Papers 4/1991, Bank of Finland.
    5. Peter C.B. Phillips, 1995. "Automated Forecasts of Asia-Pacific Economic Activity," Cowles Foundation Discussion Papers 1103, Cowles Foundation for Research in Economics, Yale University.
    6. repec:bla:ecorec:v:76:y:2000:i:235:p:321-42 is not listed on IDEAS
    7. Tyson Lamarra & Aaron Bruhn & Michael Miller, 2023. "Stochastic modelling of the home equity access scheme," Australian Journal of Management, Australian School of Business, vol. 48(3), pages 652-677, August.
    8. Meredith Beechey & Pär Österholm, 2008. "A Bayesian Vector Autoregressive Model with Informative Steady‐state Priors for the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 84(267), pages 449-465, December.
    9. repec:zbw:bofrdp:1991_004 is not listed on IDEAS
    10. Kim, Jae H., 1999. "Asymptotic and bootstrap prediction regions for vector autoregression," International Journal of Forecasting, Elsevier, vol. 15(4), pages 393-403, October.
    11. Mardi Dungey & Adrian Pagan, 2000. "A Structural VAR Model of the Australian Economy," The Economic Record, The Economic Society of Australia, vol. 76(235), pages 321-342, December.
    12. Feto, Adem & M. K., Jayamohan, 2023. "Can Ethiopia Reach a Lower-Middle-Income Status by 2025? A Framework of DSGE and VAR Models," Ethiopian Journal of Economics, Ethiopian Economics Association, vol. 32(01), April.

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