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Comparison of univariate ARIMA, multivariate ARIMA and vector autoregression forecasting

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  • Michael L. Bagshaw

Abstract

A comparison of the forecasting abilities of univariate ARIMA, multivariate ARIMA, and VAR, and examination of whether series should be differenced before estimating models for forecasting purposes.

Suggested Citation

  • Michael L. Bagshaw, 1986. "Comparison of univariate ARIMA, multivariate ARIMA and vector autoregression forecasting," Working Papers (Old Series) 8602, Federal Reserve Bank of Cleveland.
    • Handle: RePEc:fip:fedcwp:8602
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    File URL: https://fraser.stlouisfed.org/title/working-paper-federal-reserve-bank-cleveland-4494/comparison-univariate-arima-multivariate-arima-vector-autoregression-forecasting-494465
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    References listed on IDEAS

    as
    1. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    2. M. N. Bhattacharyya, 1982. "Lydia Pinkham Data Remodelled," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(2), pages 81-102, March.
    3. Thomas Doan & Robert B. Litterman & Christopher A. Sims, 1983. "Forecasting and Conditional Projection Using Realistic Prior Distributions," NBER Working Papers 1202, National Bureau of Economic Research, Inc.
    4. Litterman, Robert, 1986. "Forecasting with Bayesian vector autoregressions -- Five years of experience : Robert B. Litterman, Journal of Business and Economic Statistics 4 (1986) 25-38," International Journal of Forecasting, Elsevier, vol. 2(4), pages 497-498.
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    Cited by:

    1. John E. Connaughton & Ronald A. Madsen, 1990. "A Comparison of Regional Forecasting Techniques," The Review of Regional Studies, Southern Regional Science Association, vol. 20(3), pages 4-11, Fall.

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