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A Small BVAR-DSGE Model for Forecasting the Australian Economy

Author

Listed:
  • Andrew Hodge

    (Reserve Bank of Australia)

  • Tim Robinson

    (Reserve Bank of Australia)

  • Robyn Stuart

    (Reserve Bank of Australia)

Abstract

This paper estimates a small structural model of the Australian economy, designed principally for forecasting the key macroeconomic variables of output growth, underlying inflation and the cash rate. In contrast to models with purely statistical foundations, which are often used for forecasting, the Bayesian Vector Autoregressive Dynamic Stochastic General Equilibrium (BVAR-DSGE) model uses the theoretical information of a DSGE model to offset in-sample over-fitting. We follow the method of Del Negro and Schorfheide (2004) and use a variant of the small open economy DSGE model of Lubik and Schorfheide (2007) to provide prior information for the VAR. The forecasting performance of the model is competitive with benchmark models such as a Minnesota VAR and an independently estimated DSGE model.

Suggested Citation

  • Andrew Hodge & Tim Robinson & Robyn Stuart, 2008. "A Small BVAR-DSGE Model for Forecasting the Australian Economy," RBA Research Discussion Papers rdp2008-04, Reserve Bank of Australia.
    • Handle: RePEc:rba:rbardp:rdp2008-04
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    File URL: https://www.rba.gov.au/publications/rdp/2008/pdf/rdp2008-04.pdf
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    References listed on IDEAS

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    1. Richard Clarida & Jordi Galí & Mark Gertler, 2000. "Monetary Policy Rules and Macroeconomic Stability: Evidence and Some Theory," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(1), pages 147-180.
    2. Jarkko Jääskelä & Kristoffer Nimark, 2008. "A Medium-scale Open Economy Model of Australia," RBA Research Discussion Papers rdp2008-07, Reserve Bank of Australia.
    3. Lubik, Thomas A. & Schorfheide, Frank, 2007. "Do central banks respond to exchange rate movements? A structural investigation," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1069-1087, May.
    4. Marco Del Negro & Frank Schorfheide, 2004. "Priors from General Equilibrium Models for VARS," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 45(2), pages 643-673, May.
    5. Alejandro Justiniano & Bruce Preston, 2010. "Monetary policy and uncertainty in an empirical small open‐economy model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(1), pages 93-128, January.
    6. Kuttner, Ken & Robinson, Tim, 2010. "Understanding the flattening Phillips curve," The North American Journal of Economics and Finance, Elsevier, vol. 21(2), pages 110-125, August.
    7. Kristoffer P. Nimark, 2009. "A Structural Model of Australia as a Small Open Economy," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 42(1), pages 24-41, March.
    8. John Geweke, 1999. "Using Simulation Methods for Bayesian Econometric Models," Computing in Economics and Finance 1999 832, Society for Computational Economics.
    9. Hugo Gerard & Kristoffer Nimark, 2008. "Combining multivariate density forecasts using predictive criteria," Economics Working Papers 1117, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2008.
    10. Jordi Galí & Tommaso Monacelli, 2005. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 707-734.
    11. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    12. Kirdan Lees & Troy Matheson & Christie Smith, 2007. "Open economy DSGE-VAR forecasting and policy analysis - head to head with the RBNZ published forecasts," Reserve Bank of New Zealand Discussion Paper Series DP2007/01, Reserve Bank of New Zealand.
    13. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    14. Thomas Lubik & Frank Schorfheide, 2006. "A Bayesian Look at New Open Economy Macroeconomics," NBER Chapters, in: NBER Macroeconomics Annual 2005, Volume 20, pages 313-382, National Bureau of Economic Research, Inc.
    15. GORDON De BROUWER & JAMES GILBERT, 2005. "Monetary Policy Reaction Functions in Australia," The Economic Record, The Economic Society of Australia, vol. 81(253), pages 124-134, June.
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    Cited by:

    1. Rangan Gupta & Rudi Steinbach, 2010. "Forecasting Key Macroeconomic Variables of the South African Economy: A Small Open Economy New Keynesian DSGE-VAR Model," Working Papers 201019, University of Pretoria, Department of Economics.
    2. Ramezani, Fariba & Harvie, Charles & Arjomandi, Amir, 2016. "Australian Emissions Reduction Subsidy Policy under Persistent Productivity Shocks," 2016 Conference (60th), February 2-5, 2016, Canberra, Australia 235583, Australian Agricultural and Resource Economics Society.
    3. Gupta, Rangan & Steinbach, Rudi, 2013. "A DSGE-VAR model for forecasting key South African macroeconomic variables," Economic Modelling, Elsevier, vol. 33(C), pages 19-33.

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    More about this item

    Keywords

    BVAR-DSGE; forecasting;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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