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The Information Content of Financial Aggregates in Australia

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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.

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Paper provided by Reserve Bank of Australia in its series RBA Research Discussion Papers with number rdp9606.

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Date of creation: Nov 1996
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Handle: RePEc:rba:rbardp:rdp9606

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  1. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
  2. 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.
  3. Orden, David & Fisher, Lance A, 1993. "Financial Deregulation and the Dynamics of Money, Prices, and Output in New Zealand and Australia," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(2), pages 273-92, May.
  4. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-42, October.
  5. Stock, James H. & Watson, Mark W., 1989. "Interpreting the evidence on money-income causality," Journal of Econometrics, Elsevier, vol. 40(1), pages 161-181, January.
  6. Stephen G. Cecchetti, 1995. "Inflation Indicators and Inflation Policy," NBER Chapters, in: NBER Macroeconomics Annual 1995, Volume 10, pages 189-236 National Bureau of Economic Research, Inc.
  7. Gordon de Brouwer & Neil R. Ericsson, 1995. "Modelling inflation in Australia," International Finance Discussion Papers 530, Board of Governors of the Federal Reserve System (U.S.).
  8. Mark A. Thoma & Jo Anna Gray, 1994. "On leading indicators: getting it straight," Proceedings, Federal Reserve Bank of Dallas, issue Apr.
  9. Michael Coelli & Jerome Fahrer, 1992. "Indicators of Inflationary Pressure," RBA Research Discussion Papers rdp9207, Reserve Bank of Australia.
  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. 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.
  2. Simatele, Munacinga C H, 2004. "Financial sector reforms and monetary policy reforms in Zambia," MPRA Paper 21575, University Library of Munich, Germany.
  3. 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.

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