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Optimal Autoregressive Predictions

Author

Listed:
  • In Choi

    (Department of Economics, Sogang University, Seoul)

  • Sun Ho Hwang

    (Department of Economics, Sogang University, Seoul)

Abstract

This paper proposes a new, optimal estimator of the AR(1) coefficient that minimixes the prediction mean-squared-error. This estimator can be used to generate an optimal predictor. The new estimator¡®s asymptotic distributions are derived for the cases of stationarity and a near unit root. The optimal estimator is also derived for the AR(p) model (p>=2) and its asymptotic distributions are reported. Simulation results confirm advantages of using the optimal estimator for prediction.

Suggested Citation

  • In Choi & Sun Ho Hwang, 2016. "Optimal Autoregressive Predictions," Working Papers 1607, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    • Handle: RePEc:sgo:wpaper:1607
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    File URL: https://tinyurl.com/ykcmlvg7
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    References listed on IDEAS

    as
    1. Choi,In, 2015. "Almost All about Unit Roots," Cambridge Books, Cambridge University Press, number 9781107482500, January.
    2. Phillips, Peter C B, 1988. "Regression Theory for Near-Integrated Time Series," Econometrica, Econometric Society, vol. 56(5), pages 1021-1043, September.
    3. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    4. G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
    5. Andrew Atkeson & Lee E. Ohanian, 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 25(Win), pages 2-11.
    6. Choi, In, 1993. "Asymptotic Normality of the Least-Squares Estimates for Higher Order Autoregressive Integrated Processes with Some Applications," Econometric Theory, Cambridge University Press, vol. 9(2), pages 263-282, April.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Autoregressive model; prediction; near unit root;
    All these keywords.

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