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A Markov-switching Model of Inflation in Australia

Author

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  • John Simon

    (Reserve Bank of Australia)

Abstract

This paper applies the methodology of Markov-switching models to describe the inflation process in Australia in the period since the early 1960s. In contrast to conventional modelling, the approach makes explicit allowance for the possibility of structural change: inflation is modelled within a framework that allows endogenous switching between simple inflation equations. The approach may be relevant to understanding shifts in inflation expectations if the public also uses relatively simple forecasting rules in formulating expectations. The results suggest that inflation is reasonably well represented by relatively simple functions of past inflation and an output gap term, with major regime changes occurring in the early 1970s and early 1990s.

Suggested Citation

  • John Simon, 1996. "A Markov-switching Model of Inflation in Australia," RBA Research Discussion Papers rdp9611, Reserve Bank of Australia.
  • Handle: RePEc:rba:rbardp:rdp9611
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    File URL: http://www.rba.gov.au/publications/rdp/1996/pdf/rdp9611.pdf
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    References listed on IDEAS

    as
    1. Hansen, Bruce E, 1992. "The Likelihood Ratio Test under Nonstandard Conditions: Testing the Markov Switching Model of GNP," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(S), pages 61-82, Suppl. De.
    2. Taylor, John B., 1981. "On the relation between the variability of inflation and the average inflation rate," Carnegie-Rochester Conference Series on Public Policy, Elsevier, pages 57-85.
    3. 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.).
    4. Ball, Laurence, 1992. "Why does high inflation raise inflation uncertainty?," Journal of Monetary Economics, Elsevier, vol. 29(3), pages 371-388, June.
    5. de Brouwer, Gordon & Ericsson, Neil R, 1998. "Modeling Inflation in Australia," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 433-449, October.
    6. Martin Evans & Paul Wachtel, 1993. "Inflation regimes and the sources of inflation uncertainty," Proceedings, Federal Reserve Bank of Cleveland, pages 475-520.
    7. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    8. Perron, Pierre, 1990. "Testing for a Unit Root in a Time Series with a Changing Mean," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 153-162, April.
    9. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Kamin, Steve B. & Rogers, John H., 2000. "Output and the real exchange rate in developing countries: an application to Mexico," Journal of Development Economics, Elsevier, vol. 61(1), pages 85-109, February.
    2. Neil Dias Karunaratne & Ramprasad Bhar, 2010. "Regime-Shifts & Post-Float Inflation Dynamics In Australia," Discussion Papers Series 405, School of Economics, University of Queensland, Australia.
    3. Alison Tarditi, 1996. "Modelling the Australian Exchange Rate, Long Bond Yield and Inflationary Expectations," RBA Research Discussion Papers rdp9608, Reserve Bank of Australia.
    4. Joseph E. Gagnon, 2008. "Inflation regimes and inflation expectations," Review, Federal Reserve Bank of St. Louis, issue May, pages 229-243.
    5. Vugar Ahmadov & Shaig Adigozalov & Salman Huseynov & Fuad Mammadov & Vugar Rahimov, 2016. "Forecasting inflation in post-oil boom years: A case for non-linear models?," Working Papers 1601, Central Bank of Azerbaijan Republic.
    6. repec:wsd:irgpim:v:86:y:2011:i:1:p:185-199 is not listed on IDEAS
    7. Barsoum, Fady & Stankiewicz, Sandra, 2015. "Forecasting GDP growth using mixed-frequency models with switching regimes," International Journal of Forecasting, Elsevier, vol. 31(1), pages 33-50.
    8. Besso, Christophe Raoul, 2010. "Phillips Curve, case study in Cameroon: evaluation of fundamental assumptions," MPRA Paper 35614, University Library of Munich, Germany, revised 28 Dec 2011.
    9. Yucel, Eray, 2011. "A Review and Bibliography of Early Warning Models," MPRA Paper 32893, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • O56 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Oceania

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