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The asymptotic efficiency of improved prediction intervals

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  • Kabaila, Paul
  • Syuhada, Khreshna

Abstract

We consider the Barndorff-Nielsen and Cox (1994, p. 319) method of modifying an estimative prediction interval to obtain an improved prediction interval with better conditional coverage properties. The parameter estimator, on which this improved interval is based, is assumed to have the same asymptotic distribution as the conditional maximum likelihood estimator. This improved interval depends strongly on the asymptotic conditional bias of this estimator, which can be very sensitive to small changes in this estimator. We show, however, that the asymptotic efficiency of this improved prediction interval does not depend on this bias.

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  • Kabaila, Paul & Syuhada, Khreshna, 2010. "The asymptotic efficiency of improved prediction intervals," Statistics & Probability Letters, Elsevier, vol. 80(17-18), pages 1348-1353, September.
    • Handle: RePEc:eee:stapro:v:80:y:2010:i:17-18:p:1348-1353
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    References listed on IDEAS

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    1. Corcuera, José M., 2008. "Approximate predictive pivots for autoregressive processes," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2685-2691, November.
    2. Phillips, Peter C. B., 1979. "The sampling distribution of forecasts from a first-order autoregression," Journal of Econometrics, Elsevier, vol. 9(3), pages 241-261, February.
    3. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-862, November.
    4. Paolo Vidoni, 2004. "Improved prediction intervals for stochastic process models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 137-154, January.
    5. Paul Kabaila & Khreshna Syuhada, 2008. "Improved Prediction Limits For AR(p) and ARCH(p) Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 213-223, March.
    6. Paul Kabaila, 1993. "On Bootstrap Predictive Inference For Autoregressive Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 14(5), pages 473-484, September.
    7. Paul Kabaila & Zhisong He, 2004. "The adjustment of prediction intervals to account for errors in parameter estimation," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(3), pages 351-358, May.
    8. Paolo Vidoni, 2009. "A simple procedure for computing improved prediction intervals for autoregressive models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(6), pages 577-590, November.
    9. Paul Kabaila, 1999. "The Relevance Property For Prediction Intervals," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(6), pages 655-662, November.
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    Cited by:

    1. Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2017. "A Justification of Conditional Confidence Intervals," Papers 1710.00643, arXiv.org, revised Jan 2019.
    2. Bony Josaphat & Khreshna Syuhada, 2020. "Dependent Conditional Value-at-Risk for Aggregate Risk Models," Papers 2009.02904, arXiv.org.

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