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Optimal univariate inflation forecasting with symmetric stable shocks

Author

Listed:
  • Prasad V. Bidarkota

    (School of Business, La Trobe University, Bundoora, Victoria 3083, Australia)

  • J. Huston McCulloch

    (Department of Economics, The Ohio State University, 410 Arps Hall, 1945 North High Street, Columbus, OH 43210, USA)

Abstract

Monthly inflation in the United States indicates non-normality in the form of either occasional big shocks or marked changes in the level of the series. We develop a univariate state space model with symmetric stable shocks for this series. The non-Gaussian model is estimated by the Sorenson-Alspach filtering algorithm. Even after removing conditional heteroscedasticity, normality is rejected in favour of a stable distribution with exponent 1·83. Our model can be used for forecasting future inflation, and to simulate historical inflation forecasts conditional on the history of inflation. Relative to the Gaussian model, the stable model accounts for outliers and level shifts better, provides tighter estimates of trend inflation, and gives more realistic assessment of uncertainty during confusing episodes. © 1998 John Wiley & Sons, Ltd.

Suggested Citation

  • Prasad V. Bidarkota & J. Huston McCulloch, 1998. "Optimal univariate inflation forecasting with symmetric stable shocks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(6), pages 659-670.
  • Handle: RePEc:jae:japmet:v:13:y:1998:i:6:p:659-670
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    File URL: http://qed.econ.queensu.ca:80/jae/1998-v13.6/
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    Cited by:

    1. J Huston McCulloch, 2000. "State-Space Times Series Modeling of Structural Breaks," Working Papers 00-11, Ohio State University, Department of Economics.
    2. Zhiguang Wang & Prasad Bidarkota, 2012. "Risk premia in forward foreign exchange rates: a comparison of signal extraction and regression methods," Empirical Economics, Springer, vol. 42(1), pages 21-51, February.
    3. Khurshid M. Kiani, 2016. "On Modelling and Forecasting Predictable Components in European Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 48(3), pages 487-502, October.
    4. Khurshid Kiani, 2009. "Inflation in Transition Economies: An Empirical Analysis," Transition Studies Review, Springer;Central Eastern European University Network (CEEUN), vol. 16(1), pages 34-46, May.
    5. KIANI, Khurshid M., 2007. "Determination Of Volatility And Mean Returns: An Evidence From An Emerging Stock Market," International Journal of Applied Econometrics and Quantitative Studies, Euro-American Association of Economic Development, vol. 4(1), pages 103-118.
    6. J. Huston McCulloch & Prasad V. Bidarkota, 2003. "Signal Extraction can Generate Volatility Clusters," Computing in Economics and Finance 2003 59, Society for Computational Economics.
    7. J. Huston McCulloch & Prasad V. Bidarkota, 2002. "Signal Extraction Can Generate Volatility Clusters From IID Shocks," Working Papers 02-04, Ohio State University, Department of Economics.
    8. Bidarkota, Prasad V. & Dupoyet, Brice V. & McCulloch, J. Huston, 2009. "Asset pricing with incomplete information and fat tails," Journal of Economic Dynamics and Control, Elsevier, vol. 33(6), pages 1314-1331, June.
    9. J. Huston McCulloch & Levin A. Kochen, 1998. "The Inflation Premium Implicit in the US Real and Nominal Term Structures of Interest Rates," Working Papers 98-12, Ohio State University, Department of Economics.
    10. Serttas, Fatma Ozgu, 2010. "Essays on infinite-variance stable errors and robust estimation procedures," ISU General Staff Papers 201001010800002742, Iowa State University, Department of Economics.
    11. J. Huston McCulloch, 2001. "The Inflation Premium implicit in the US Real and Nominal," Computing in Economics and Finance 2001 210, Society for Computational Economics.
    12. J. Huston McCulloch, 2005. "The Kalman Foundations of Adaptive Least Squares: Applications to Unemployment and Inflation," Computing in Economics and Finance 2005 239, Society for Computational Economics.
    13. Hill, Jonathan B., 2010. "On Tail Index Estimation For Dependent, Heterogeneous Data," Econometric Theory, Cambridge University Press, vol. 26(05), pages 1398-1436, October.
    14. Khurshid M. Kiani, 2006. "Predictability in Stock Returns in an Emerging Market: Evidence from KSE 100 Stock Price Index," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 45(3), pages 369-381.

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