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Forecasting the stationary AR(1) with an almost unit root


  • George Halkos
  • Ilias Kevork


Although unit root tests have made a great contribution in time series econometrics, their major disadvantage is the low powers they attain on certain occasions, as for the case of the stationary AR(1), when φis close to one. In this study, considering the random walk as the true model, we derive the probability of the prediction interval to include any future value yT+s of AR(1). Using certain estimates from Monte Carlo simulations, we proceed to numerical computations, resulting in the main finding that the values for the specific probability depend upon the location the most recent available observation in the sample possesses in its marginal distribution.

Suggested Citation

  • George Halkos & Ilias Kevork, 2006. "Forecasting the stationary AR(1) with an almost unit root," Applied Economics Letters, Taylor & Francis Journals, vol. 13(12), pages 789-793.
  • Handle: RePEc:taf:apeclt:v:13:y:2006:i:12:p:789-793 DOI: 10.1080/13504850500407491

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    References listed on IDEAS

    1. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    2. Richard Levin & Peter C. Reiss, 1984. "Tests of a Schumpeterian Model of R&D and Market Structure," NBER Chapters,in: R&D, Patents, and Productivity, pages 175-208 National Bureau of Economic Research, Inc.
    3. Spence, Michael, 1984. "Cost Reduction, Competition, and Industry Performance," Econometrica, Econometric Society, vol. 52(1), pages 101-121, January.
    4. Drysdale, Peter & Huang, Yiping, 1997. "Technological Catch-up and Economic Growth in East Asia and the Pacific," The Economic Record, The Economic Society of Australia, vol. 73(222), pages 201-211, September.
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    Cited by:

    1. Konstantinos Nikolopoulos, 2010. "Forecasting with quantitative methods: the impact of special events in time series," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 947-955.
    2. Vicky Bamiatzi & Konstantinos Bozos & Konstantinos Nikolopoulos, 2010. "On the predictability of firm performance via simple time-series and econometric models: evidence from UK SMEs," Applied Economics Letters, Taylor & Francis Journals, vol. 17(3), pages 279-282, February.

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