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Financial Aggregates as Conditioning Information for Australian Output and Inflation

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  • Ellis W. Tallman

    (Reserve Bank of Australia)

  • Naveen Chandra

    (Reserve Bank of Australia)

Abstract

This paper examines whether financial aggregates provide information useful for predicting real output growth and inflation, extending the inquiry conducted in Tallman and Chandra (1996). First, we investigate whether perfect knowledge of the future values of financial aggregates helps improve significantly the forecasting accuracy of output and inflation in a simple vector autoregression framework. The results display only one notable improvement to the forecasts with the addition of perfect information on the financial aggregates – future information on credit growth helps improve the prediction accuracy of real output growth. The improvement is most noticeable during the early 1990s recession. Second, we test whether the financial aggregates are important explanators within single-equation models that are more rigorously fitted to the data. We find only one instance in which an aggregate helps explain the variation in either real output growth or inflation – that is, the growth in credit helps explain the growth in real output in a particular specification of the output model. This finding, though, is sensitive to the choice of foreign output proxy. In sum, we conclude that while credit may have some useful information in times of financial restructuring it is unlikely that there is information in financial aggregates that is exploitable systematically for predicting either real output growth or inflation.

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Bibliographic Info

Paper provided by Reserve Bank of Australia in its series RBA Research Discussion Papers with number rdp9704.

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Date of creation: Jul 1997
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Handle: RePEc:rba:rbardp:rdp9704

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  1. Gordon de Brouwer & Neil R. Ericsson, 1995. "Modelling Inflation in Australia," RBA Research Discussion Papers rdp9510, Reserve Bank of Australia.
  2. Estrella, Arturo & Mishkin, Frederic S., 1997. "Is there a role for monetary aggregates in the conduct of monetary policy?," Journal of Monetary Economics, Elsevier, vol. 40(2), pages 279-304, October.
  3. Roberds, William & Whiteman, Charles H, 1992. "Monetary Aggregates as Monetary Targets: A Statistical Investigation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 24(2), pages 141-61, May.
  4. David Gruen & John Romalis & Naveen Chandra, 1997. "The Lags of Monetary Policy," RBA Research Discussion Papers rdp9702, Reserve Bank of Australia.
  5. 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.
  6. Ellis W. Tallman & Naveen Chandra, 1996. "The information content of financial aggregates in Australia," Working Paper 96-14, Federal Reserve Bank of Atlanta.
  7. Mankiw, N. Gregory (ed.), 1997. "Monetary Policy," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226503097, Winter.
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Cited by:
  1. Palle S. Andersen, 1997. "Forecast errors and financial developments," BIS Working Papers 51, Bank for International Settlements.
  2. 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.
  3. Simatele, Munacinga C H, 2004. "Financial sector reforms and monetary policy reforms in Zambia," MPRA Paper 21575, University Library of Munich, Germany.

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