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The Information Content of Financial Aggregates in Australia

Author

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  • Ellis W. Tallman

    (Reserve Bank of Australia)

  • Naveen Chandra

    (Reserve Bank of Australia)

Abstract

This paper examines the information provided by financial aggregates as predictors of real output and inflation. We employ vector autoregression (VAR) techniques to summarise the information in the data, providing evidence on the incremental forecasting value of financial aggregates in a range of forecasting systems for these variables. The in-sample results suggest significant predictive power in only a small number of cases. We then test the forecast performance of the VAR systems for two years out-of-sample in order to mimic more closely the real-time forecasting problem faced by policymakers. Overall, both in-sample and out-of-sample results suggest no robust finding of exploitable information for forecasting purposes in any of the financial aggregates under examination. There is some evidence that the aggregates yield improved forecasts late in the sample period, but there is insufficient subsequent data to draw robust conclusions from this.

Suggested Citation

  • Ellis W. Tallman & Naveen Chandra, 1996. "The Information Content of Financial Aggregates in Australia," RBA Research Discussion Papers rdp9606, Reserve Bank of Australia.
    • Handle: RePEc:rba:rbardp:rdp9606
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    References listed on IDEAS

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    1. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-442, October.
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    10. Benjamin M. Friedman, 1996. "The Rise and Fall of Money Growth Targets as Guidelines for U.S. Monetary Policy," NBER Working Papers 5465, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Onour, Ibrahim, 2015. "Modeling inflation dynamics in a conflict economy," MPRA Paper 63527, University Library of Munich, Germany.
    2. Ellis W. Tallman & Naveen Chandra, 1997. "Financial Aggregates as Conditioning Information for Australian Output and Inflation," RBA Research Discussion Papers rdp9704, Reserve Bank of Australia.
    3. Mwankemwa, Lusajo P. & Mlamka, Bonaventura, 2022. "Effects of Monetary Policy on Bank’s Credit Dynamics in Tanzania," African Journal of Economic Review, African Journal of Economic Review, vol. 10(2), March.
    4. Michael Adebayo Adebiyi, 2007. "Does Money Tell Us Anything About Inflation In Nigeria?," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 52(01), pages 117-134.
    5. Simatele, Munacinga C H, 2004. "Financial sector reforms and monetary policy reforms in Zambia," MPRA Paper 21575, University Library of Munich, Germany.
    6. Feridun, M. & Adebiyi, M.A., 2006. "Forecasting Inflation in Developing Economies: The Case of Nigeria, 1986-1998," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 3(1), pages 55-84.
    7. Katherine Avram, 1998. "Implications Of New Payments Technology For Monetary Policy," Economic Papers, The Economic Society of Australia, vol. 17(4), pages 54-68, December.

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    More about this item

    JEL classification:

    • E40 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - General
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E51 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Money Supply; Credit; Money Multipliers

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