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On Autoregressive Order Selection Criteria

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  • Venus Khim-Sen Liew

Abstract

This study investigates the performance of various commonly applied order selection criteria in selecting order of Autoregressive (AR) process. The most important finding of this study is that Akaike’s information criterion, Schwarz information criterion, Hannan-Quinn criterion, final prediction error and Bayesian information criterion perform considerably well in estimating the true autoregressive order, even in small sample. Besides, there is no significant gain in differentiating these criteria unless one has a considerable large sample size. This study contributes to the empirical literature by providing helpfully guidelines regarding the use of order selection criteria in determining the autoregressive order.

Suggested Citation

  • Venus Khim-Sen Liew, 2004. "On Autoregressive Order Selection Criteria," Computational Economics 0404001, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpco:0404001
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    References listed on IDEAS

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    1. H. Yamada, 2000. "M2 demand relation and effective exchange rate in Japan: a cointegration analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 7(4), pages 229-232.
    2. Hirotugu Akaike, 1969. "Fitting autoregressive models for prediction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 243-247, December.
    3. Tan Hui Boon & Baharumshah Ahmad Zubaidi, 1999. "Dynamic Causal Chain of Money, Output, Interest Rate and Prices in Malaysia: Evidence Based On Vector Error- Correction Modelling Analysis," International Economic Journal, Taylor & Francis Journals, vol. 13(1), pages 103-120.
    4. Mark P. Taylor, 2003. "Purchasing Power Parity," Review of International Economics, Wiley Blackwell, vol. 11(3), pages 436-452, August.
    5. Sarantis, Nicholas, 2001. "Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence," International Journal of Forecasting, Elsevier, vol. 17(3), pages 459-482.
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    3. Rialdi Azhar & Fajrin Satria Dwi Kesumah & Ambya Ambya & Febryan Kusuma Wisnu & Edwin Russel, 2020. "Application of Short-term Forecasting Models for Energy Entity Stock Price (Study on Indika Energi Tbk, JII)," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 294-301.

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    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
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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