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Forecasting Australian Economic Activity Using Leading Indicators

Author

Listed:
  • Andrea Brischetto

    (Reserve Bank of Australia)

  • Graham Voss

    (Reserve Bank of Australia)

Abstract

This paper examines the contribution leading indicators can make to forecasting measures of real activity in Australia. In a policy context, we are interested in forecasting the levels or growth of policy relevant variables throughout the cycle. We are less interested in forecasting turning points in the cycle or in forecasting coincident indices, which are subjectively defined overall measures of economic activity. This gives us a different focus to much of the recent work done in this area. We use a simple forecasting framework (bivariate VARs) to compare the Westpac-Melbourne Institute (WM), NATSTAT and ABS leading indices’ predictive performance for real GDP, employment and unemployment in Australia. Within sample we find all three indices help predict all of the activity variables, although with varying leads. Out of sample evidence, however, is weaker. Within our framework, we only find evidence in favour of the WM index when used to forecast GDP. Otherwise, the indices do not make any substantive contribution to forecast quality. To gauge the usefulness of the simple bivariate VAR models, we compare the out of sample forecasts of GDP, using the WM index, to those from a single equation structural model due to Gruen and Shuetrim (1994). Over a forecasting sample of relatively stable growth, the WM index model performs quite well relative to the Gruen and Shuetrim model. Over a longer forecasting sample period, one which includes the downturn in the early 1990s, there is some evidence that the WM index model performs relatively poorly.

Suggested Citation

  • Andrea Brischetto & Graham Voss, 2000. "Forecasting Australian Economic Activity Using Leading Indicators," RBA Research Discussion Papers rdp2000-02, Reserve Bank of Australia.
  • Handle: RePEc:rba:rbardp:rdp2000-02
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    File URL: http://www.rba.gov.au/publications/rdp/2000/pdf/rdp2000-02.pdf
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    References listed on IDEAS

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    1. Layton, Allan P, 1997. "Do Leading Indicators Really Predict Australian Business Cycle Turning Points?," The Economic Record, The Economic Society of Australia, vol. 73(222), pages 258-269, September.
    2. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, January.
    3. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
    4. Fair, Ray C & Shiller, Robert J, 1990. "Comparing Information in Forecasts from Econometric Models," American Economic Review, American Economic Association, vol. 80(3), pages 375-389, June.
    5. Don Harding & Adrian Pagan, 1999. "Knowing the Cycle," Melbourne Institute Working Paper Series wp1999n12, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    6. David Gruen & Geoffrey Shuetrim, 1994. "Internationalisation and the Macroeconomy," RBA Annual Conference Volume,in: Philip Lowe & Jacqueline Dwyer (ed.), International Intergration of the Australian Economy Reserve Bank of Australia.
    7. Granger, C. W. J. & Newbold, Paul, 1986. "Forecasting Economic Time Series," Elsevier Monographs, Elsevier, edition 2, number 9780122951831 edited by Shell, Karl.
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    Cited by:

    1. Bloom, David E. & Canning, David & Fink, Gunther & Finlay, Jocelyn E., 2007. "Does age structure forecast economic growth?," International Journal of Forecasting, Elsevier, vol. 23(4), pages 569-585.
    2. Sandra V. Rozo V., 2008. "Nuevo enfoque para la construcción de un único indicador líder de la actividad económica colombiana," COYUNTURA ECONÓMICA, FEDESARROLLO, December.

    More about this item

    Keywords

    forecasting; leading indices;

    JEL classification:

    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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